198 results on '"Karczmar GS"'
Search Results
2. Different MR systems yield variable kinetic characteristics of malignant breast lesions.
- Author
-
Jansen, SA, primary, Zak, L, additional, Karczmar, GS, additional, Shimauchi, A, additional, and Newstead, GM, additional
- Published
- 2009
- Full Text
- View/download PDF
3. In vivo magnetic resonance imaging of the progression of murine ductal carcinoma in situ: finding timescales and predictors of future invasion.
- Author
-
Jansen, SA, primary, Conzen, SD, additional, Newstead, GM, additional, Markiewicz, EJ, additional, and Karczmar, GS, additional
- Published
- 2009
- Full Text
- View/download PDF
4. Normal parenchymal enhancement patterns in women undergoing MR screening of the breast.
- Author
-
Jansen SA, Lin VC, Giger ML, Li H, Karczmar GS, Newstead GM, Jansen, Sanaz A, Lin, Vicky C, Giger, Maryellen L, Li, Hui, Karczmar, Gregory S, and Newstead, Gillian M
- Abstract
Objectives: To characterize the kinetic and morphological presentation of normal breast tissue on DCE-MRI in a large cohort of asymptomatic women, and to relate these characteristics to breast tissue density.Methods: 335 consecutive breast MR examinations in 229 asymptomatic women undergoing high-risk screening evaluations based on recommendations from the American Cancer Society including strong family history and genetic predisposition were selected for IRB-approved review (average age 49.2 ± 10.5 years). Breast tissue density was assessed on precontrast T₂-weighted images. Parenchymal enhancement pattern (PEP) was qualitatively classified as minimal, homogeneous, heterogeneous or nodular. Quantitative analysis of parenchymal enhancement kinetics (PEK) was performed, including calculation of initial and peak enhancement percentages (E₁, E(peak)), the time to peak enhancement (T ( peak )) and the signal enhancement ratio (SER).Results: 41.8% of examinations were classified as minimal, 13.7% homogeneous, 23.9% heterogeneous and 21.2% nodular PEP. Women with heterogeneously or extremely dense breasts exhibited a higher proportion of nodular PEP (44.2% (27/61)) and significantly higher E₁, and E(peak) (p < 0.003) compared with those with less dense breasts.Conclusions: Qualitative and quantitative parenchymal enhancement characteristics vary by breast tissue density. In future work, the association between image-derived MR features of the normal breast and breast cancer risk should be explored. [ABSTRACT FROM AUTHOR]- Published
- 2011
- Full Text
- View/download PDF
5. Quantitative analysis of dynamic contrast enhanced MRI for assessment of bowel inflammation in Crohn's disease pilot study.
- Author
-
Oto A, Fan X, Mustafi D, Jansen SA, Karczmar GS, Rubin DT, and Kayhan A
- Published
- 2009
- Full Text
- View/download PDF
6. Introduction to matrix-based method for analyzing hybrid multidimensional prostate MRI data.
- Author
-
Fan X, Chatterjee A, Medved M, Antic T, Oto A, and Karczmar GS
- Abstract
A new approach to analysis of prostate hybrid multidimensional MRI (HM-MRI) data was introduced in this study. HM-MRI data were acquired for a combination of a few echo times (TEs) and a few b-values. Naturally, there is a matrix associated with HM-MRI data for each image pixel. To process the data, we first linearized HM-MRI data by taking the natural logarithm of the imaging signal intensity. Subsequently, a hybrid symmetric matrix was constructed by multiplying the matrix for each pixel by its own transpose. The eigenvalues for each pixel could then be calculated from the hybrid symmetric matrix. In order to compare eigenvalues between patients, three b-values and three TEs were used, because this was smallest number of b-values and TEs among all patients. The results of eigenvalues were displayed as qualitative color maps for easier visualization. For quantitative analysis, the ratio (λ
r ) of eigenvalues (λ1 , λ2 , λ3 ) was defined as λr = (λ1 /λ2 )/λ3 to compare region of interest (ROI) between prostate cancer (PCa) and normal tissue. The results show that the combined eigenvalue maps show PCas clearly and these maps are quite different from apparent diffusion coefficient (ADC) and T2 maps of the same prostate. The PCa has significant larger λr , smaller ADC and smaller T2 values than normal prostate tissue (p < 0.001). This suggests that the matrix-based method for analyzing HM-MRI data provides new information that may be clinically useful. The method is easy to use and could be easily implemented in clinical practice. The eigenvalues are associated with combination of ADC and T2 values, and could aid in the identification and staging of PCa., (© 2024 The Author(s). Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)- Published
- 2024
- Full Text
- View/download PDF
7. Quantitative Multi-Parametric MRI of the Prostate Reveals Racial Differences.
- Author
-
Chatterjee A, Fan X, Slear J, Asare G, Yousuf AN, Medved M, Antic T, Eggener S, Karczmar GS, and Oto A
- Abstract
Purpose: This study investigates whether quantitative MRI and histology of the prostate reveal differences between races, specifically African Americans (AAs) and Caucasian Americans (CAs), that can affect diagnosis. Materials and Methods: Patients (98 CAs, 47 AAs) with known or suspected prostate cancer (PCa) underwent 3T MRI (T2W, DWI, and DCE-MRI) prior to biopsy or prostatectomy. Quantitative mpMRI metrics: ADC, T2, and DCE empirical mathematical model parameters were calculated. Results: AAs had a greater percentage of higher Gleason-grade lesions compared to CAs. There were no significant differences in the quantitative ADC and T2 values between AAs and CAs. The cancer signal enhancement rate (α) on DCE-MRI was significantly higher for AAs compared to CAs (AAs: 13.3 ± 9.3 vs. CAs: 6.1 ± 4.7 s
-1 , p < 0.001). The DCE signal washout rate (β) was significantly lower in benign tissue of AAs (AAs: 0.01 ± 0.09 s-1 vs. CAs: 0.07 ± 0.07 s-1 , p < 0.001) and significantly elevated in cancer tissue in AAs (AAs: 0.12 ± 0.07 s-1 vs. CAs: 0.07 ± 0.08 s-1 , p = 0.02). DCE significantly improves the differentiation of PCa from benign in AAs (α: 52%, β: 62% more effective in AAs compared to CAs). Histologic analysis showed cancers have a greater proportion ( p = 0.04) of epithelium (50.9 ± 12.3 vs. 44.7 ± 12.8%) and lower lumen (10.5 ± 6.9 vs. 16.2 ± 6.8%) in CAs compared to AAs. Conclusions: This study shows that AAs have different quantitative DCE-MRI values for benign prostate and prostate cancer and different histologic makeup in PCa compared to CAs. Quantitative DCE-MRI can significantly improve the performance of MRI for PCa diagnosis in African Americans but is much less effective for Caucasian Americans.- Published
- 2024
- Full Text
- View/download PDF
8. Comparison of synthesized and acquired high b-value diffusion-weighted MRI for detection of prostate cancer.
- Author
-
Kallis K, Conlin CC, Zhong AY, Hussain TS, Chatterjee A, Karczmar GS, Rakow-Penner R, Dale AM, and Seibert TM
- Subjects
- Humans, Male, Aged, Retrospective Studies, Middle Aged, Aged, 80 and over, Prostate diagnostic imaging, Prostate pathology, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms pathology, Diffusion Magnetic Resonance Imaging methods
- Abstract
Background: High b-value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). This study qualitatively and quantitatively compares synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa., Methods: One hundred fifty-one consecutive patients who underwent prostate MRI and biopsy were included in the study. Axial DWI with b = 0, 500, 1000, and 2000 s/mm
2 using a 3T clinical scanner using a 32-channel phased-array body coil were acquired. We retrospectively synthesized DWI for b = 2000 s/mm2 via extrapolation based on mono-exponential decay, using b = 0 and b = 500 s/mm2 (sDWI500 ) and b = 0, b = 500 s/mm2 , and b = 1000 s/mm2 (sDWI1000 ). Differences in signal intensity between sDWI and aDWI were evaluated within different regions of interest (prostate alone, prostate plus 5 mm, 30 mm and 70 mm margin and full field of view). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI. Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC)., Results: Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46 ± 35% for sDWI1000 and -67 ± 24% for sDWI500 . AUC for aDWI, sDWI500, sDWI1000 , and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively., Conclusion: sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI., (© 2024. The Author(s).)- Published
- 2024
- Full Text
- View/download PDF
9. Self-supervised multicontrast super-resolution for diffusion-weighted prostate MRI.
- Author
-
Gundogdu B, Medved M, Chatterjee A, Engelmann R, Rosado A, Lee G, Oren NC, Oto A, and Karczmar GS
- Subjects
- Humans, Male, Image Processing, Computer-Assisted methods, Image Interpretation, Computer-Assisted methods, Neural Networks, Computer, Motion, Reproducibility of Results, Diffusion Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging, Phantoms, Imaging, Signal-To-Noise Ratio, Prostate diagnostic imaging, Algorithms
- Abstract
Purpose: This study addresses the challenge of low resolution and signal-to-noise ratio (SNR) in diffusion-weighted images (DWI), which are pivotal for cancer detection. Traditional methods increase SNR at high b-values through multiple acquisitions, but this results in diminished image resolution due to motion-induced variations. Our research aims to enhance spatial resolution by exploiting the global structure within multicontrast DWI scans and millimetric motion between acquisitions., Methods: We introduce a novel approach employing a "Perturbation Network" to learn subvoxel-size motions between scans, trained jointly with an implicit neural representation (INR) network. INR encodes the DWI as a continuous volumetric function, treating voxel intensities of low-resolution acquisitions as discrete samples. By evaluating this function with a finer grid, our model predicts higher-resolution signal intensities for intermediate voxel locations. The Perturbation Network's motion-correction efficacy was validated through experiments on biological phantoms and in vivo prostate scans., Results: Quantitative analyses revealed significantly higher structural similarity measures of super-resolution images to ground truth high-resolution images compared to high-order interpolation (p < $$ < $$ 0.005). In blind qualitative experiments, 96 . 1 % $$ 96.1\% $$ of super-resolution images were assessed to have superior diagnostic quality compared to interpolated images., Conclusion: High-resolution details in DWI can be obtained without the need for high-resolution training data. One notable advantage of the proposed method is that it does not require a super-resolution training set. This is important in clinical practice because the proposed method can easily be adapted to images with different scanner settings or body parts, whereas the supervised methods do not offer such an option., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)
- Published
- 2024
- Full Text
- View/download PDF
10. Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom.
- Author
-
Wu C, Hormuth DA 2nd, Easley T, Pineda F, Karczmar GS, and Yankeelov TE
- Abstract
Purpose: Validation of quantitative imaging biomarkers is a challenging task, due to the difficulty in measuring the ground truth of the target biological process. A digital phantom-based framework is established to systematically validate the quantitative characterization of tumor-associated vascular morphology and hemodynamics based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)., Approach: A digital phantom is employed to provide a ground-truth vascular system within which 45 synthetic tumors are simulated. Morphological analysis is performed on high-spatial resolution DCE-MRI data (spatial/temporal resolution = 30 to 300 μ m / 60 s ) to determine the accuracy of locating the arterial inputs of tumor-associated vessels (TAVs). Hemodynamic analysis is then performed on the combination of high-spatial resolution and high-temporal resolution (spatial/temporal resolution = 60 to 300 μ m / 1 to 10 s) DCE-MRI data, determining the accuracy of estimating tumor-associated blood pressure, vascular extraction rate, interstitial pressure, and interstitial flow velocity., Results: The observed effects of acquisition settings demonstrate that, when optimizing the DCE-MRI protocol for the morphological analysis, increasing the spatial resolution is helpful but not necessary, as the location and arterial input of TAVs can be recovered with high accuracy even with the lowest investigated spatial resolution. When optimizing the DCE-MRI protocol for hemodynamic analysis, increasing the spatial resolution of the images used for vessel segmentation is essential, and the spatial and temporal resolutions of the images used for the kinetic parameter fitting require simultaneous optimization., Conclusion: An in silico validation framework was generated to systematically quantify the effects of image acquisition settings on the ability to accurately estimate tumor-associated characteristics., (© 2024 Society of Photo-Optical Instrumentation Engineers (SPIE).)
- Published
- 2024
- Full Text
- View/download PDF
11. Prostate Cancers Invisible on Multiparametric MRI: Pathologic Features in Correlation with Whole-Mount Prostatectomy.
- Author
-
Chatterjee A, Gallan A, Fan X, Medved M, Akurati P, Bourne RM, Antic T, Karczmar GS, and Oto A
- Abstract
We investigated why some prostate cancers (PCas) are not identified on multiparametric MRI (mpMRI) by using ground truth reference from whole-mount prostatectomy specimens. A total of 61 patients with biopsy-confirmed PCa underwent 3T mpMRI followed by prostatectomy. Lesions visible on MRI prospectively or retrospectively identified after correlating with histology were considered "identified cancers" (ICs). Lesions that could not be identified on mpMRI were considered "unidentified cancers" (UCs). Pathologists marked the Gleason score, stage, size, and density of the cancer glands and performed quantitative histology to calculate the tissue composition. Out of 115 cancers, 19 were unidentified on MRI. The UCs were significantly smaller and had lower Gleason scores and clinical stage lesions compared with the ICs. The UCs had significantly ( p < 0.05) higher ADC (1.34 ± 0.38 vs. 1.02 ± 0.30 μm
2 /ms) and T2 (117.0 ± 31.1 vs. 97.1 ± 25.1 ms) compared with the ICs. The density of the cancer glands was significantly ( p = 0.04) lower in the UCs. The percentage of the Gleason 4 component in Gleason 3 + 4 lesions was nominally ( p = 0.15) higher in the ICs (20 ± 12%) compared with the UCs (15 ± 8%). The UCs had a significantly lower epithelium (32.9 ± 21.5 vs. 47.6 ± 13.1%, p = 0.034) and higher lumen volume (20.4 ± 10.0 vs. 13.3 ± 4.1%, p = 0.021) compared with the ICs. Independent from size and Gleason score, the tissue composition differences, specifically, the higher lumen and lower epithelium in UCs, can explain why some of the prostate cancers cannot be identified on mpMRI.- Published
- 2023
- Full Text
- View/download PDF
12. Bilateral asymmetry of quantitative parenchymal kinetics at ultrafast DCE-MRI predict response to neoadjuvant chemotherapy in patients with HER2+ breast cancer.
- Author
-
Ren Z, Pineda FD, Howard FM, Fan X, Nanda R, Abe H, Kulkarni K, and Karczmar GS
- Subjects
- Humans, Female, Middle Aged, Adult, Treatment Outcome, Aged, Kinetics, Sensitivity and Specificity, Breast Neoplasms diagnostic imaging, Breast Neoplasms drug therapy, Neoadjuvant Therapy, Magnetic Resonance Imaging methods, Contrast Media, Receptor, ErbB-2 metabolism
- Abstract
Purpose: To assess whether measurement of the bilateral asymmetry of semiquantitative and quantitative perfusion parameters from ultrafast dynamic contrast-enhanced MRI (DCE-MRI), allows early prediction of pathologic response after neoadjuvant chemotherapy (NAC) in patients with HER2+ breast cancer., Materials and Methods: Twenty-eight female patients with HER2+ breast cancer treated with NAC who underwent pre-NAC ultrafast DCE-MRI (3-9 s/phase) were enrolled for this study. Four semiquantitative and two quantitative parenchymal parameters were calculated for each patient. Ipsilateral/contralateral (I/C) ratio (for four parameters) and the difference between (for two parameters) ipsi- and contra-lateral parenchymal kinetic parameters (kBPE) were compared for patients with pathologic complete response (pCR) and those having residual disease. Lasso regression with leave-one-out cross validation was used to determine the optimal combination of parameters for a regression model and multivariable logistic regression was used to identify independent predictors for pCR. Chi-squared test, two-sided t-test and Kruskal-Wallis test were used., Results: The K
trans I/C ratio cutoff value of 1.11 had a sensitivity of 83.3% and specificity of 75% for pCR. The ve I/C ratio cutoff value of 1.1 had a sensitivity of 75% and specificity of 81.3% for pCR. The area under the receiver operating characteristic curve of the three-kBPE parameter model, including initial area under the enhancement curve (AUC30) I/C ratio, Ktrans I/C ratio and ve I/C ratio, was 0.89 with sensitivity of 91.7% at specificity of 81.3%., Conclusion: Quantitative assessment of bilateral asymmetry kBPE from pre-NAC ultrafast DCE-MRI can predict pCR in patients with HER2+ breast cancer., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 Elsevier Inc. All rights reserved.)- Published
- 2023
- Full Text
- View/download PDF
13. Parametric maps of spatial two-tissue compartment model for prostate dynamic contrast enhanced MRI - comparison with the standard tofts model in the diagnosis of prostate cancer.
- Author
-
Zhou X, Fan X, Chatterjee A, Yousuf A, Antic T, Oto A, and Karczmar GS
- Subjects
- Male, Humans, Magnetic Resonance Imaging methods, Contrast Media, Diffusion Magnetic Resonance Imaging, Prostate, Prostatic Neoplasms
- Abstract
The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data and compared with the standard Tofts model. A total of 29 patients with biopsy-confirmed prostate cancer were included in this IRB-approved study. MRI data were acquired on a Philips Achieva 3T-TX scanner. After T2-weighted and diffusion-weighted imaging, DCE data using 3D T1-FFE mDIXON sequence were acquired pre- and post-contrast media injection (0.1 mmol/kg Multihance) for 60 dynamic scans with temporal resolution of 8.3 s/image. The 2TCM has one fast ([Formula: see text] and [Formula: see text]) and one slow ([Formula: see text] and [Formula: see text]) exchanging compartment, compared with the standard Tofts model parameters (K
trans and kep ). On average, prostate cancer had significantly higher values (p < 0.01) than normal prostate tissue for all calculated parameters. There was a strong correlation (r = 0.94, p < 0.001) between Ktrans and [Formula: see text] for cancer, but weak correlation (r = 0.28, p < 0.05) between kep and [Formula: see text]. Average root-mean-square error (RMSE) in fits from the 2TCM was significantly smaller (p < 0.001) than the RMSE in fits from the Tofts model. Receiver operating characteristic (ROC) analysis showed that fast [Formula: see text] had the highest area under the curve (AUC) than any other individual parameter. The combined four parameters from the 2TCM had a considerably higher AUC value than the combined two parameters from the Tofts model. The 2TCM is useful for quantitative analysis of prostate DCE-MRI data and provides new information in the diagnosis of prostate cancer., (© 2023. Australasian College of Physical Scientists and Engineers in Medicine.)- Published
- 2023
- Full Text
- View/download PDF
14. An Interactive App with Multi-parametric MRI - Whole-Mount Histology Correlation for Enhanced Prostate MRI Training of Radiology Residents.
- Author
-
Chatterjee A, Szasz T, Munakami M, Karademir I, Yusufishaq MS, Martens S, Wheeler C, Antic T, Thomas S, Karczmar GS, and Oto A
- Subjects
- Male, Humans, Prostate diagnostic imaging, Prostate pathology, Retrospective Studies, Magnetic Resonance Imaging methods, Mobile Applications, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms pathology, Radiology
- Abstract
Rationale and Objectives: To validate the educational value of a newly created learning application in enhancing prostate MRI training of radiologists for detecting prostate cancer using an observer study., Materials and Methods: An interactive learning app, LearnRadiology, was developed using a web-based framework to display multi-parametric prostate MRI images with whole-mount histology for 20 cases curated for unique pathology and teaching points. Twenty new prostate MRI cases, different from the ones used in the web app, were uploaded on 3D Slicer. Three radiologists (R1: radiologist; R2, R3: residents) blinded to pathology results were asked to mark areas suspected of cancer and provide a confidence score (1-5, with 5 being high confidence level). Then after a minimum memory washout period of 1 month, the same radiologists used the learning app and then repeated the same observer study. The diagnostic performance for detecting cancers before and after accessing the learning app was measured by correlating MRI with whole-mount pathology by an independent reviewer., Results: The 20 subjects included in the observer study had 39 cancer lesions (13 Gleason 3 + 3, 17 Gleason 3 + 4, 7 Gleason 4 + 3, and 2 Gleason 4 + 5 lesions). The sensitivity (R1: 54% → 64%, P = 0.08; R2: 44% → 59%, P = 0.03; R3: 62% → 72%, P = 0.04) and positive predictive value (R1: 68% → 76%, P = 0.23; R2: 52% → 79%, P = 0.01; R3: 48% → 65%, P = 0.04) for all 3 radiologists improved after using the teaching app. The confidence score for true positive cancer lesion also improved significantly (R1: 4.0 ± 1.0 → 4.3 ± 0.8; R2: 3.1 ± 0.8 → 4.0 ± 1.1; R3: 2.8 ± 1.2 → 4.1 ± 1.1; P < 0.05)., Conclusion: The web-based and interactive LearnRadiology app learning resource can support medical student and postgraduate education by improving diagnostic performance of trainees for detecting prostate cancer., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Aritrick Chatterjee reports financial support was provided by Radiological Society of North America. Aritrick Chatterjee reports a relationship with QMIS LLC that includes: equity or stocks. Aytekin Oto reports a relationship with QMIS LLC that includes: equity or stocks. Gregory Karczmar reports a relationship with QMIS LLC that includes: equity or stocks., (Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)
- Published
- 2023
- Full Text
- View/download PDF
15. External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population.
- Author
-
Omoleye OJ, Woodard AE, Howard FM, Zhao F, Yoshimatsu TF, Zheng Y, Pearson AT, Levental M, Aribisala BS, Kulkarni K, Karczmar GS, Olopade OI, Abe H, and Huo D
- Abstract
Purpose: To externally evaluate a mammography-based deep learning (DL) model (Mirai) in a high-risk racially diverse population and compare its performance with other mammographic measures., Materials and Methods: A total of 6435 screening mammograms in 2096 female patients (median age, 56.4 years ± 11.2 [SD]) enrolled in a hospital-based case-control study from 2006 to 2020 were retrospectively evaluated. Pathologically confirmed breast cancer was the primary outcome. Mirai scores were the primary predictors. Breast density and Breast Imaging Reporting and Data System (BI-RADS) assessment categories were comparative predictors. Performance was evaluated using area under the receiver operating characteristic curve (AUC) and concordance index analyses., Results: Mirai achieved 1- and 5-year AUCs of 0.71 (95% CI: 0.68, 0.74) and 0.65 (95% CI: 0.64, 0.67), respectively. One-year AUCs for nondense versus dense breasts were 0.72 versus 0.58 ( P = .10). There was no evidence of a difference in near-term discrimination performance between BI-RADS and Mirai (1-year AUC, 0.73 vs 0.68; P = .34). For longer-term prediction (2-5 years), Mirai outperformed BI-RADS assessment (5-year AUC, 0.63 vs 0.54; P < .001). Using only images of the unaffected breast reduced the discriminatory performance of the DL model ( P < .001 at all time points), suggesting that its predictions are likely dependent on the detection of ipsilateral premalignant patterns., Conclusion: A mammography DL model showed good performance in a high-risk external dataset enriched for African American patients, benign breast disease, and BRCA mutation carriers, and study findings suggest that the model performance is likely driven by the detection of precancerous changes. Keywords: Breast, Cancer, Computer Applications, Convolutional Neural Network, Deep Learning Algorithms, Informatics, Epidemiology, Machine Learning, Mammography, Oncology, Radiomics Supplemental material is available for this article . © RSNA, 2023See also commentary by Kontos and Kalpathy-Cramer in this issue., Competing Interests: Disclosures of conflicts of interest: O.J.O. No relevant relationships. A.E.W. No relevant relationships. F.M.H. Funding from American Society of Clinical Oncology/Breast Cancer Research Foundation Young Investigator Award (2022YIA-6675470300), Department of Defense (DoD) Breakthrough Level 2 Award (BC211095P1), American Cancer Society Institutional Research Grant, National Institutes of Health (NIH)/National Cancer Institute (NCI) (K12CA139160), and Cancer Research Foundation Young Investigator Award. F.Z. No relevant relationships. T.F.Y. No relevant relationships. Y.Z. No relevant relationships. A.T.P. Funding from NIH/National Institute of Dental and Craniofacial Research (R56-DE030958), NIH/NCI (U01-CA243075), DoD Breakthrough Cancer Research program (BC211095), Horizon (2021-SC1-BHC), Stand Up to Cancer–Fanconi Anemia Research Fund–Farrah Fawcett Foundation, NCI/Department of Energy Innovative Methodologies and New Data for Predictive Oncology Model Evaluation (IMPROVE) project IAA; grants or contracts from AbbVie and Kura Oncology; honorarium from AbbVie; advisory board for Prelude, Elevar Therapeutics, Privo, and Ayala. M.L. No relevant relationships. B.S.A. No relevant relationships. K.K. No relevant relationships. G.S.K. No relevant relationships. O.I.O. Funding from the Susan & Richard Kiphart Family Foundation; leadership role with American Cancer Society and MacArthur Foundation; stock or stock options with CancerIq, Tempus, and Healthwell; receipt of equipment or services from Genentech/Roche, Cepheid, and Color Genomics. H.A. No relevant relationships. D.H. No relevant relationships., (© 2023 by the Radiological Society of North America, Inc.)
- Published
- 2023
- Full Text
- View/download PDF
16. Pharmacokinetic Analysis of Enhancement-Constrained Acceleration (ECA) reconstruction-based high temporal resolution breast DCE-MRI.
- Author
-
Ren Z, Easley TO, Pineda FD, Guo X, Barber RF, and Karczmar GS
- Subjects
- Female, Humans, Breast diagnostic imaging, Contrast Media pharmacokinetics, Follow-Up Studies, Image Enhancement methods, Breast Neoplasms diagnostic imaging, Magnetic Resonance Imaging methods
- Abstract
The high spatial and temporal resolution of dynamic contrast-enhanced MRI (DCE-MRI) can improve the diagnostic accuracy of breast cancer screening in patients who have dense breasts or are at high risk of breast cancer. However, the spatiotemporal resolution of DCE-MRI is limited by technical issues in clinical practice. Our earlier work demonstrated the use of image reconstruction with enhancement-constrained acceleration (ECA) to increase temporal resolution. ECA exploits the correlation in k-space between successive image acquisitions. Because of this correlation, and due to the very sparse enhancement at early times after contrast media injection, we can reconstruct images from highly under-sampled k-space data. Our previous results showed that ECA reconstruction at 0.25 seconds per image (4 Hz) can estimate bolus arrival time (BAT) and initial enhancement slope (iSlope) more accurately than a standard inverse fast Fourier transform (IFFT) when k-space data is sampled following a Cartesian based sampling trajectory with adequate signal-to-noise ratio (SNR). In this follow-up study, we investigated the effect of different Cartesian based sampling trajectories, SNRs and acceleration rates on the performance of ECA reconstruction in estimating contrast media kinetics in lesions (BAT, iSlope and Ktrans) and in arteries (Peak signal intensity of first pass, time to peak, and BAT). We further validated ECA reconstruction with a flow phantom experiment. Our results show that ECA reconstruction of k-space data acquired with 'Under-sampling with Repeated Advancing Phase' (UnWRAP) trajectories with an acceleration factor of 14, and temporal resolution of 0.5 s/image and high SNR (SNR ≥ 30 dB, noise standard deviation (std) < 3%) ensures minor errors (5% or 1 s error) in lesion kinetics. Medium SNR (SNR ≥ 20 dB, noise std ≤ 10%) was needed to accurately measure arterial enhancement kinetics. Our results also suggest that accelerated temporal resolution with ECA with 0.5 s/image is practical., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ren et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
- Full Text
- View/download PDF
17. Characterization of Effects of Compressed Sensing on High Spectral and Spatial Resolution (HiSS) MRI with Comparison to SENSE.
- Author
-
Medved M, Vicari M, and Karczmar GS
- Subjects
- Phantoms, Imaging, Magnetic Resonance Imaging methods, Artifacts
- Abstract
High Spectral and Spatial resolution (HiSS) MRI shows high diagnostic performance in the breast. Acceleration methods based on k-space undersampling could allow stronger T2*-based image contrast and/or higher spectral resolution, potentially increasing diagnostic performance. An agar/oil phantom was prepared with water-fat boundaries perpendicular to the readout and phase encoding directions in a breast coil. HiSS MRI was acquired at 3T, at sensitivity encoding (SENSE) acceleration factors R of up to 10, and the R = 1 dataset was used to simulate corresponding compressed sensing (CS) accelerations. Image quality was evaluated by quantifying noise and artifact levels. Effective spatial resolution was determined via modulation transfer function analysis. Dispersion vs. absorption (DISPA) analysis and full width at half maximum (FWHM) quantified spectral lineshape changes. Noise levels remained constant with R for CS but amplified with SENSE. SENSE preserved the spatial resolution of HiSS MRI, while CS reduced it in the phase encoding direction. SENSE showed no effect on FWHM or DISPA markers, while CS increased FWHM. Thus, CS might perform better in noise-limited or geometrically constrained applications, but in geometric configurations specific to breast MRI, spectral analysis might be compromised, decreasing the diagnostic performance of HiSS MRI.
- Published
- 2023
- Full Text
- View/download PDF
18. Standardization of Breast Dynamic Contrast-enhanced MRI Signal with Application to the Assessment of Background Parenchymal Enhancement Rate.
- Author
-
Medved M, Tsuchiya K, Fan X, Karczmar GS, and Abe H
- Abstract
Background: There is currently no clinically accepted method for quantifying background parenchymal enhancement (BPE), though a sensitive method might allow individualized risk management based on the response to cancer-preventative hormonal therapy., Objective: The objective of this pilot study is to demonstrate the utility of linear modeling of standardized dynamic contrast-enhanced MRI (DCEMRI) signal for quantifying changes in BPE rates., Methods: On a retrospective database search, 14 women with DCEMRI examinations pre- and post- treatment with tamoxifen were identified. DCEMRI signal was averaged over the parenchymal ROIs to obtain time-dependent signal curves S(t). The gradient echo signal equation was used to standardize scale S(t) to values of (FA) ̃ = 10° and (TR) ̃ = 5.5 ms, and obtain the standardized parameters of DCE-MRI signal S ̃_p (t). Relative signal enhancement (〖RSE〗_p ) ̃ was calculated from S ̃_p, and the reference tissue method for T1 calculation was used to standardize (〖RSE〗_p ) ̃ to gadodiamide as the contrast agent, obtaining (RSE) ̃. (RSE) ̃, in the first 6 minutes, post-contrast administration was fit to a linear model with the slope α ̃_RSE denoting the standardized rate relative BPE., Results: Changes in α ̃_RSE were not found to be significantly correlated with the average duration of tamoxifen treatment, age at the initiation of preventative treatment, or pre-treatment BIRADS breast density category. The average change in α ̃_RSE showed a large effect size of -1.12, significantly higher than -0.86 observed without signal standardization (p < 0.01)., Conclusion: Linear modeling of BPE in standardized DCEMRI can provide quantitative measurements of BPE rates, improving sensitivity to changes due to tamoxifen treatment., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)
- Published
- 2023
- Full Text
- View/download PDF
19. Comparison of synthesized and acquired high b -value diffusion-weighted MRI for detection of prostate cancer.
- Author
-
Kallis K, Conlin CC, Zhong AY, Hussain TS, Chatterjee A, Karczmar GS, Rakow-Penner R, Dale A, and Seibert T
- Abstract
Background: High b -value diffusion-weighted images (DWI) are used for detection of clinically significant prostate cancer (csPCa). To decrease scan time and improve signal-to-noise ratio, high b -value (>1000 s/mm
2 ) images are often synthesized instead of acquired., Purpose: Qualitatively and quantitatively compare synthesized DWI (sDWI) to acquired (aDWI) for detection of csPCa., Study Type: Retrospective., Subjects: 151 consecutive patients who underwent prostate MRI and biopsy., Sequence: Axial DWI with b =0, 500, 1000, and 2000 s/mm2 using a 3T clinical scanner using a 32-channel phased-array body coil., Assessment: We synthesized DWI for b =2000 s/mm2 via extrapolation based on monoexponential decay, using b =0 and b =500 s/mm2 (sDWI500 ) and b =0, b =500, and b =1000 s/mm2 (sDWI1000 ). Differences between sDWI and aDWI were evaluated within regions of interest (ROIs). The maximum DWI value within each ROI was evaluated for prediction of csPCa. Classification accuracy was also compared to Restriction Spectrum Imaging restriction score (RSIrs), a previously validated biomarker based on multi-exponential DWI., Statistical Tests: Discrimination of csPCa was evaluated via area under the receiver operating characteristic curve (AUC). Statistical significance was assessed using bootstrap difference (two-sided α=0.05)., Results: Within the prostate, mean ± standard deviation of percent mean differences between sDWI and aDWI signal were -46±35% for sDWI1000 and -67±24% for sDWI500 . AUC for aDWI, sDWI500, sDWI1000 , and RSIrs within the prostate 0.62[95% confidence interval: 0.53, 0.71], 0.63[0.54, 0.72], 0.65[0.56, 0.73] and 0.78[0.71, 0.86], respectively. When considering the whole field of view, classification accuracy and qualitative image quality decreased notably for sDWI compared to aDWI and RSIrs., Data Conclusion: sDWI is qualitatively comparable to aDWI within the prostate. However, hyperintense artifacts are introduced with sDWI in the surrounding pelvic tissue that interfere with quantitative cancer detection and might mask metastases. In the prostate, RSIrs yields superior quantitative csPCa detection than sDWI or aDWI.- Published
- 2023
- Full Text
- View/download PDF
20. Comparing Radiologist Performance in Diagnosing Clinically Significant Prostate Cancer with Multiparametric versus Hybrid Multidimensional MRI.
- Author
-
Lee GH, Chatterjee A, Karademir I, Engelmann R, Yousuf A, Giurcanu M, Harmath CB, Karczmar GS, and Oto A
- Subjects
- Male, Humans, Middle Aged, Magnetic Resonance Imaging methods, Retrospective Studies, Reproducibility of Results, Radiologists, Prostatic Neoplasms pathology
- Abstract
Background Variability of acquisition and interpretation of prostate multiparametric MRI (mpMRI) persists despite implementation of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 due to the range of reader experience and subjectivity of lesion characterization. A quantitative method, hybrid multidimensional MRI (HM-MRI), may introduce objectivity. Purpose To compare performance, interobserver agreement, and interpretation time of radiologists using mpMRI versus HM-MRI to diagnose clinically significant prostate cancer. Materials and Methods In this retrospective analysis, men with prostatectomy or MRI-fused transrectal US biopsy-confirmed prostate cancer underwent mpMRI (triplanar T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging) and HM-MRI (with multiple echo times and b value combinations) from August 2012 to February 2020. Four readers with 1-20 years of experience interpreted mpMRI and HM-MRI examinations independently, with a 4-week washout period between interpretations. PI-RADS score, lesion location, and interpretation time were recorded. mpMRI and HM-MRI interpretation time, interobserver agreement (Cronbach alpha), and performance of area under the receiver operating characteristic curve (AUC) analysis were compared for each radiologist with use of bootstrap analysis. Results Sixty-one men (mean age, 61 years ± 8 [SD]) were evaluated. Per-patient AUC was higher for HM-MRI for reader 4 compared with mpMRI (AUCs for readers 1-4: 0.61, 0.71, 0.59, and 0.64 vs 0.66, 0.60, 0.50, and 0.46; P = .57, .20, .32, and .04, respectively). Per-patient specificity was higher for HM-MRI for readers 2-4 compared with mpMRI (specificity for readers 1-4: 48%, 78%, 48%, and 46% vs 37%, 26%, 0%, and 7%; P = .34, P < .001, P < .001, and P < .001, respectively). Diagnostic performance improved for the reader least experienced with HM-MRI, reader 4 (AUC, 0.64 vs 0.46; P = .04). HM-MRI interobserver agreement (Cronbach alpha = 0.88 [95% CI: 0.82, 0.92]) was higher than that of mpMRI (Cronbach alpha = 0.26 [95% CI: 0.10, 0.52]; α > .60 indicates reliability; P = .03). HM-MRI mean interpretation time (73 seconds ± 43 [SD]) was shorter than that of mpMRI (254 seconds ± 133; P = .03). Conclusion Radiologists had similar or improved diagnostic performance, higher interobserver agreement, and lower interpretation time for clinically significant prostate cancer with hybrid multidimensional MRI than multiparametric MRI. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.
- Published
- 2022
- Full Text
- View/download PDF
21. Directional and inter-acquisition variability in diffusion-weighted imaging and editing for restricted diffusion.
- Author
-
Gundogdu B, Pittman JM, Chatterjee A, Szasz T, Lee G, Giurcanu M, Medved M, Engelmann R, Guo X, Yousuf A, Antic T, Devaraj A, Fan X, Oto A, and Karczmar GS
- Subjects
- Humans, Image Processing, Computer-Assisted methods, Male, Motion, Prostate, Diffusion Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging
- Abstract
Purpose: To evaluate and quantify inter-directional and inter-acquisition variation in diffusion-weighted imaging (DWI) and emphasize signals that report restricted diffusion to enhance cancer conspicuity, while reducing the effects of local microscopic motion and magnetic field fluctuations., Methods: Ten patients with biopsy-proven prostate cancer were studied under an Institutional Review Board-approved protocol. Individual acquisitions of DWI signal intensities were reconstructed to calculate inter-acquisition distributions and their statistics, which were compared for healthy versus cancer tissue. A method was proposed to detect and filter the acquisitions affected by motion-induced signal loss. First, signals that reflect restricted diffusion were separated from the acquisitions that suffer from signal loss, likely due to microscopic motion, by imposing a cutoff value. Furthermore, corrected apparent diffusion coefficient maps were calculated by employing a weighted sum of the multiple acquisitions, instead of conventional averaging. These weights were calculated by applying a soft-max function to the set of acquisitions per-voxel, making the analysis immune to acquisitions with significant signal loss, even if the number of such acquisitions is high., Results: Inter-acquisition variation is much larger than the Rician noise variance, local spatial variations, and the estimates of diffusion anisotropy based on the current data, as well as the published values of anisotropy. The proposed method increases the contrast for cancers and yields a sensitivity of 98 . 8 % $$ 98.8\% $$ with a false positive rate of 3 . 9 % $$ 3.9\% $$ ., Conclusion: Motion-induced signal loss makes conventional signal-averaging suboptimal and can obscure signals from areas with restricted diffusion. Filtering or weighting individual acquisitions prior to image analysis can overcome this problem., (© 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)
- Published
- 2022
- Full Text
- View/download PDF
22. Towards Patient-Specific Optimization of Neoadjuvant Treatment Protocols for Breast Cancer Based on Image-Guided Fluid Dynamics.
- Author
-
Wu C, Hormuth DA, Lorenzo G, Jarrett AM, Pineda F, Howard FM, Karczmar GS, and Yankeelov TE
- Subjects
- Humans, Female, Hydrodynamics, Prospective Studies, Doxorubicin therapeutic use, Treatment Outcome, Neoadjuvant Therapy, Breast Neoplasms diagnostic imaging, Breast Neoplasms drug therapy, Breast Neoplasms pathology
- Abstract
Objective: This study establishes a fluid dynamics model personalized with patient-specific imaging data to optimize neoadjuvant therapy (i.e., doxorubicin) protocols for breast cancers., Methods: Ten patients recruited at the University of Chicago were included in this study. Quantitative dynamic contrast-enhanced and diffusion weighted magnetic resonance imaging data are leveraged to estimate patient-specific hemodynamic properties, which are then used to constrain the mechanism-based drug delivery model. Then, computer simulations of this model yield the subsequent drug distribution throughout the breast. By systematically varying the dosing schedule, we identify an optimized regimen for each patient using the maximum safe therapeutic duration (MSTD), which is a metric balancing treatment efficacy and toxicity., Results: With an individually optimized dose (range = 12.11-15.11 mg/m
2 per injection), a 3-week regimen consisting of a uniform daily injection significantly outperforms all other scheduling strategies (P < 0.001). In particular, the optimal protocol is predicted to significantly outperform the standard protocol (P < 0.001), improving the MSTD by an average factor of 9.93 (range = 6.63 to 14.17)., Conclusion: A clinical-mathematical framework was developed by integrating quantitative MRI data, advanced image processing, and computational fluid dynamics to predict the efficacy and toxicity of neoadjuvant therapy protocols, thus enabling the rational identification of an optimal therapeutic regimen on a patient-specific basis., Significance: Our clinical-computational approach has the potential to enable optimization of therapeutic regimens on a patient-specific basis and provide guidance for prospective clinical trials aimed at refining neoadjuvant therapy protocols for breast cancers.- Published
- 2022
- Full Text
- View/download PDF
23. Differences Between Ipsilateral and Contralateral Early Parenchymal Enhancement Kinetics Predict Response of Breast Cancer to Neoadjuvant Therapy.
- Author
-
Ren Z, Pineda FD, Howard FM, Hill E, Szasz T, Safi R, Medved M, Nanda R, Yankeelov TE, Abe H, and Karczmar GS
- Subjects
- Breast pathology, Contrast Media, Female, Humans, Kinetics, Magnetic Resonance Imaging methods, Neoadjuvant Therapy, Retrospective Studies, Breast Neoplasms diagnostic imaging, Breast Neoplasms pathology, Breast Neoplasms therapy
- Abstract
Rationale and Objectives: To determine whether kinetics measured with ultrafast dynamic contrast-enhanced magnetic resonance imaging in tumor and normal parenchyma pre- and post-neoadjuvant therapy (NAT) can predict the response of breast cancer to NAT., Materials and Methods: Twenty-four patients with histologically confirmed invasive breast cancer were enrolled. They were scanned with ultrafast dynamic contrast-enhanced magnetic resonance imaging (3-7 seconds/frame) pre- and post-NAT. Four kinetic parameters were calculated in the segmented tumors, and ipsi- and contra-lateral normal parenchyma: (1) tumor (tSE30) or background parenchymal relative enhancement at 30 seconds (BPE30), (2) maximum relative enhancement slope (MaxSlope), (3) bolus arrival time (BAT), and (4) area under relative signal enhancement curve for the initial 30 seconds (AUC30). The tumor kinetics and the differences between ipsi- and contra-lateral parenchymal kinetics were compared for patients achieving pathologic complete response (pCR) vs those who had residual disease after NAT. The chi-squared test and two-sided t-test were used for baseline demographics. The Wilcoxon rank sum test and one-way analysis of variance were used for differential responses to therapy., Results: Patients with similar pre-NAT mean BPE30, median BAT and mean AUC30 in the ipsi- and contralateral normal parenchyma were more likely to achieve pCR following NAT (p < 0.02). Patients classified as having residual cancer burden (RCB) II after NAT showed higher post-NAT tSE30 and tumor AUC30 and higher post-NAT MaxSlope in ipsilateral normal parenchyma compared to those classified as RCB I or pCR (p < 0.05)., Conclusion: Bilateral asymmetry in normal parenchyma could predict treatment outcome prior to NAT. Post-NAT tumor kinetics could evaluate the aggressiveness of residual tumor., (Copyright © 2022. Published by Elsevier Inc.)
- Published
- 2022
- Full Text
- View/download PDF
24. Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding.
- Author
-
Penn A, Medved M, Abe H, Dialani V, Karczmar GS, and Brousseau D
- Subjects
- Adult, Biopsy, Breast diagnostic imaging, Breast pathology, Diagnosis, Differential, Diffusion Magnetic Resonance Imaging methods, Female, Humans, Prospective Studies, Sensitivity and Specificity, Breast Neoplasms diagnostic imaging, Breast Neoplasms pathology, Contrast Media
- Abstract
Background: Thresholding apparent diffusion coefficient (ADC) maps obtained from Diffusion-Weighted-Imaging (DWI) has been proposed for identifying benign lesions that can safely avoid biopsy. The presence of malignancies with high ADC values leads to high thresholds, limiting numbers of avoidable biopsies., Purpose: We evaluate two previously reported methods for identifying avoidable biopsies: using case-set dependent ADC thresholds that assure 100% sensitivity and using negative likelihood ratio (LR-) with a fixed ADC threshold of 1.50 × 10
-3 mm2 /s. We evaluated improvements in efficacy obtained by excluding non-mass lesions and lesions with anisotropic intra-lesion morphologic characteristics., Study Type: Prospective., Population: 55 adult females with dense breasts with 69 BI-RADS 4 or 5 lesions (38 malignant, 31 benign) identified on ultrasound and mammography and imaged with MRI prior to biopsy., Field Strength/sequence: 1.5 T and 3.0 T. DWI., Assessment: Analysis of DWI, including directional images was done on an ROI basis. ROIs were drawn on DWI images acquired prior to biopsy, referencing all available images including DCE, and mean ADC was measured. Anisotropy was quantified via variation in ADC values in the lesion core across directional DWI images., Statistical Tests: Improvement in specificity at 100% sensitivity was evaluated with exact McNemar test with 1-sided p-value < 0.05 indicating statistical significance., Results: Using ADC thresholding that assures 100% sensitivity, non-mass and directional variance filtering improved the percent of avoidable biopsies to 42% from baseline of 10% achieved with ADC thresholding alone. Using LR-, filtering improved outcome to 0.06 from baseline 0.25 with ADC thresholding alone. ADC thresholding showed a lower percentage of avoidable biopsies in our cohort than reported in prior studies. When ADC thresholding was supplemented with filtering, the percentage of avoidable biopsies exceeded those of prior studies., Data Conclusion: Supplementing ADC thresholding with filters excluding non-mass lesions and lesions with anisotropic characteristics on DWI can result in an increased number of avoidable biopsies., (© 2022. The Author(s).)- Published
- 2022
- Full Text
- View/download PDF
25. Physically implausible signals as a quantitative quality assessment metric in prostate diffusion-weighted MR imaging.
- Author
-
Szasz T, Lee G, Chatterjee A, Medved M, Devaraj A, Yousuf A, Fan X, Karczmar GS, and Oto A
- Subjects
- Aged, Diffusion Magnetic Resonance Imaging methods, Humans, Magnetic Resonance Imaging methods, Male, Middle Aged, Retrospective Studies, Prostate diagnostic imaging, Prostatic Neoplasms diagnostic imaging
- Abstract
Purpose: To provide a quantitative assessment of diffusion-weighted MR images of the prostate through identification of PIDS which clearly represents artifacts in the data. We calculated the percentage and distribution of PIDS in prostate DWI and compare the amount of PIDS between mpMRI images obtained with and without an endorectal coil., Methods: This IRB approved retrospective study (from 03/03/2014 to 03/10/2020), included 40 patients scanned with endorectal coil (ERC) and 40 without ER coil (NERC). PIDS contains any voxel where: (1) the diffusion signal increases despite an increase in b-value; and/or (2) apparent diffusion coefficient (ADC) is more than 3.0 μm
2 /ms (the ADC of pure water at 37 °C and it is physically implausible for any material to have a higher ADC). PIDS for transition zone (TZ) and peripheral zone (PZ) was calculated using an in-house MATLAB program. DWI images were quantitatively inspected for noise, motion, and distortion. T-test was used to compare the difference between PIDS levels in ERC versus NERC and ANOVA to compare the PIDS levels in the anatomic zones. The images were evaluated by a fellowship-trained radiologist in Abdominal Imaging with more than 10 years of experience in reading prostate MRI. This was tested only in prostate in this study., Results: 80 patients (58 ± 8 years old, 80 men) were evaluated. The percentage of voxels exhibiting PIDS was 17.1 ± 8.1% for the ERC cohort and 22.2 ± 15.5% for the NERC cohort. PIDS for NERC versus ERC were not significantly different (p = 0.14). The apex and base showed similar percentages of PIDS in ERC (p = 0.30) and NERC (p = 0.86). The mid (13.8 ± 8.6%) in ERC showed lower values (p = 0.02) of PIDS compared to apex (19.9 ± 11.1%) and base (17.5 ± 8.3%)., Conclusion: PIDS maps provide a spatially resolved quantitative quality assessment for prostate DWI. Average PIDS over the entire prostate were similar for the ERC and NERC cohorts, and did not differ significantly across prostate zones. However, for many of the patients, PIDS was focally much higher in specific prostate zones. PIDS assessment can guide Radiologist's evaluation of images and the development of improved DWI sequences., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)- Published
- 2022
- Full Text
- View/download PDF
26. Can Pre-treatment Quantitative Multi-parametric MRI Predict the Outcome of Radiotherapy in Patients with Prostate Cancer?
- Author
-
Chatterjee A, Turchan WT, Fan X, Griffin A, Yousuf A, Karczmar GS, Liauw SL, and Oto A
- Subjects
- Androgen Antagonists, Diffusion Magnetic Resonance Imaging, Humans, Male, Prostate pathology, Retrospective Studies, Multiparametric Magnetic Resonance Imaging, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms pathology, Prostatic Neoplasms radiotherapy
- Abstract
Rationale and Objectives: To investigate whether pre-treatment quantitative multiparametric MRI can predict biochemical outcome of prostate cancer (PCa) patients treated with primary radiotherapy (RT)., Materials and Methods: Fifty-one patients with biopsy confirmed PCa underwent prostate multiparametric MRI on 3T MR scanner prior to RT. Thirty-seven men (73%) were treated with external beam RT alone, 12 men (24%) were treated with brachytherapy monotherapy, and two men (4%) were treated with external beam RT with brachytherapy boost. The index lesion was outlined by a radiologist and quantitative apparent diffusion coefficient (ADC), T2 and DCE parameters were measured. Biochemical failure was defined using the Phoenix criteria., Results: After a median follow-up of 65 months, seven patients had biochemical failure. ADC had an area under the receiver operating characteristic curve of 0.71 for predicting RT outcome with significantly lower ADC (0.78 ± 0.17 vs 0.96 ± 0.26 µm
2 /ms, p = 0.04) of the index lesion in men with biochemical failure. Ideal ADC cutoff point (Youdens index) was 0.96 µm2 /ms which had a sensitivity of 100% and specificity of 48% for predicting biochemical failure. Kaplan-Meier analysis showed that lower ADC values were associated with significantly lower freedom from biochemical failure (FFBF, p = 0.03, no failures out of 20 men if ADC ≥ 0.96 µm2 /ms; seven of 31 with failures if ADC < 0.96 µm2 /ms). On multivariable analysis, ADC was associated with FFBF (HR 0.96 per increase in ADC of 0.01 um2 /ms [95% CI, 0.92-1.00]; p = 0.042) after accounting for National Comprehensive Cancer Network risk category (p = 0.064) and receipt of androgen deprivation therapy (p = 0.141). Quantitative T2 and DCE parameters were not associated with biochemical outcome., Conclusion: Our results suggest that quantitative ADC values of the index lesion may predict biochemical failure following primary radiotherapy in patients with PCa. Lower ADC values were associated with inferior biochemical control., (Copyright © 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)- Published
- 2022
- Full Text
- View/download PDF
27. Effectiveness of Dynamic Contrast Enhanced MRI with a Split Dose of Gadoterate Meglumine for Detection of Prostate Cancer.
- Author
-
Fan X, Chatterjee A, Pittman JM, Yousuf A, Antic T, Karczmar GS, and Oto A
- Subjects
- Humans, Magnetic Resonance Imaging methods, Male, Meglumine, Organometallic Compounds, Reproducibility of Results, Contrast Media, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms pathology
- Abstract
Rationale and Objectives: To evaluate whether dynamic contrast enhanced (DCE) MRI with a split injection of 30% followed by 70% of a standard dose (30PSD and 70PSD) of gadoterate meglumine (DOTAREM) can improve diagnosis of prostate cancer (PCa)., Materials and Methods: MRI for twenty patients was performed on a Philips Ingenia 3T scanner without an endorectal coil followed by subsequent radical prostatectomy. DCE 3D T1-FFE data were acquired with injection of 0.03 mmol/kg followed after 2 minutes by 0.07 mmol/kg of DOTAREM. Regions-of-interest on histologically verified PCa and normal tissue in different prostate zones and the iliac artery were drawn. Average signal intensity as function of time was calculated for each ROI and fitted by using the signal intensity form of the Tofts (SI-Tofts) model to extract physiological parameters (K
trans and ve ). In addition, the scaled arterial input function (AIF) obtained from 30PSD data was used to analyze 70PSD data., Results: The AIF obtained from 30PSD data showed both first and second passes clearly and had much higher peak magnitude than AIFs from 70PSD data. Ktrans was significantly (p < 0.05) larger in PCa than in normal tissue in peripheral zone (PZ) and central zone (CZ) for both 70PSD and 70PSD data analyzed with a scaled AIF. Ktrans in cancer overlapped with that of normal tissue in the transition zone (TZ). There was no statistical difference in ve between cancer and normal tissue. Receiver operating characteristic analysis showed that use of the AIF from 30PSD data to analyze 70PSD data increased the diagnostic efficacy of Ktrans in the PZ and CZ., Conclusion: The split dose protocol for injection of Dotarem increased diagnostic accuracy of quantitative analysis with the SI-Tofts model., (Copyright © 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)- Published
- 2022
- Full Text
- View/download PDF
28. Histological validation of prostate tissue composition measurement using hybrid multi-dimensional MRI: agreement with pathologists' measures.
- Author
-
Chatterjee A, Antic T, Gallan AJ, Paner GP, Lin LI, Karczmar GS, and Oto A
- Subjects
- Humans, Magnetic Resonance Imaging methods, Male, Pathologists, Prospective Studies, Prostatectomy, Prostate diagnostic imaging, Prostate pathology, Prostatic Neoplasms pathology
- Abstract
Purpose: To validate prostate tissue composition measured using hybrid multi-dimensional MRI (HM-MRI) by comparing with reference standard (ground truth) results from pathologists' interpretation of clinical histopathology slides following whole mount prostatectomy., Materials and Methods: 36 prospective participants with biopsy-confirmed prostate cancer underwent 3 T MRI prior to radical prostatectomy. Axial HM-MRI was acquired with all combinations of echo times of 57, 70, 150, 200 ms and b-values of 0, 150, 750, 1500 s/mm
2 and data were fitted using a 3-compartment signal model using custom software to generate volumes for each tissue component (stroma, epithelium, lumen). Three experienced genitourinary pathologists independently as well as in consensus reviewed each histology image and provide an estimate of percentage of epithelium and lumen for regions-of-interest corresponding to MRI (n = 165; 64 prostate cancers and 101 benign tissue). Agreement statistics using total deviation index (TDI0.9 ) was performed for tissue composition measured using HM-MRI and reference standard results from pathologists' consensus., Results: Based on the initial results showing typical variation among pathologists TDI0.9 = 25%, we determined we will declare acceptable agreement if the 95% one-sided upper confident limit of TDI0.9 is less than 30%. The results of tissue composition measurement from HM-MRI compared to ground truth results from the consensus of 3 pathologists, reveal that ninety percent of absolute paired differences (TDI0.9 ) were within 18.8% and 22.4% in measuring epithelium and lumen, respectively. We are 95% confident that 90% of absolute paired differences were within 20.6% and 24.2% in measuring epithelium and lumen, respectively. These were less than our criterion of 30% and inter-pathologists' agreement (22.3% for epithelium and 24.2% for lumen) and therefore we accept the agreement performance of HM-MRI. The results revealed excellent area under the ROC curve for differentiating cancer from benign tissue based on epithelium (HM-MRI: 0.87, pathologists: 0.97) and lumen volume (HM-MRI: 0.85, pathologists: 0.77)., Conclusion: The agreement in tissue composition measurement using hybrid multidimensional MRI and consensus of pathologists is on par with the inter-raters (pathologists) agreement., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)- Published
- 2022
- Full Text
- View/download PDF
29. Validation of Prostate Tissue Composition by Using Hybrid Multidimensional MRI: Correlation with Histologic Findings.
- Author
-
Chatterjee A, Mercado C, Bourne RM, Yousuf A, Hess B, Antic T, Eggener S, Oto A, and Karczmar GS
- Subjects
- Diagnosis, Differential, Humans, Male, Middle Aged, Prospective Studies, Prostate diagnostic imaging, Prostate pathology, Prostatectomy, Prostatic Neoplasms pathology, Prostatic Neoplasms surgery, Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging
- Abstract
Background Tissue estimates obtained by using microstructure imaging techniques, such as hybrid multidimensional (HM) MRI, may improve prostate cancer diagnosis but require histologic validation. Purpose To validate prostate tissue composition measured by using HM MRI, with quantitative histologic evaluation from whole-mount prostatectomy as the reference standard. Materials and Methods In this HIPAA-compliant study, from December 2016 to July 2018, prospective participants with biopsy-confirmed prostate cancer underwent 3-T MRI before radical prostatectomy. Axial HM MRI was performed with all combinations of echo times (57, 70, 150, and 200 msec) and b values (0, 150, 750, and 1500 sec/mm
2 ). Data were fitted by using a three-compartment signal model to generate volumes for each tissue component (stroma, epithelium, lumen). Quantitative histologic evaluation was performed to calculate volume fractions for each tissue component for regions of interest corresponding to MRI. Tissue composition measured by using HM MRI and quantitative histologic evaluation were compared (paired t test) and correlated (Pearson correlation coefficient), and agreement (concordance correlation) was assessed. Receiver operating characteristic curve analysis for cancer diagnosis was performed. Results Twenty-five participants (mean age, 60 years ± 7 [standard deviation]; 30 cancers and 45 benign regions of interest) were included. Prostate tissue composition measured with HM MRI and quantitative histologic evaluation did not differ (stroma, 45% ± 11 vs 44% ± 11 [ P = .23]; epithelium, 31% ± 15 vs 34% ± 15 [ P = .08]; and lumen, 24% ± 13 vs 22% ± 11 [ P = .80]). Between HM MRI and histologic evaluation, there was excellent correlation (Pearson r : overall, 0.91; stroma, 0.82; epithelium, 0.93; lumen, 0.90 [all P < .05]) and agreement (concordance correlation coefficient: overall, 0.91; stroma, 0.81; epithelium, 0.90; and lumen, 0.87). High areas under the receiver operating characteristic curve obtained with HM MRI (0.96 for epithelium and 0.94 for lumen, P < .001) and histologic evaluation (0.94 for epithelium and 0.88 for lumen, P < .001) were found for differentiation between benign tissue and prostate cancer. Conclusion Tissue composition measured by using hybrid multidimensional MRI had excellent correlation with quantitative histologic evaluation as the reference standard. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Muglia in this issue.- Published
- 2022
- Full Text
- View/download PDF
30. Enhancement-constrained acceleration: A robust reconstruction framework in breast DCE-MRI.
- Author
-
Easley TO, Ren Z, Kim B, Karczmar GS, Barber RF, and Pineda FD
- Subjects
- Computer Simulation, Female, Humans, Image Interpretation, Computer-Assisted, Algorithms, Breast pathology, Breast Neoplasms diagnosis, Contrast Media, Image Enhancement methods, Magnetic Resonance Imaging methods, Phantoms, Imaging
- Abstract
In patients with dense breasts or at high risk of breast cancer, dynamic contrast enhanced MRI (DCE-MRI) is a highly sensitive diagnostic tool. However, its specificity is highly variable and sometimes low; quantitative measurements of contrast uptake parameters may improve specificity and mitigate this issue. To improve diagnostic accuracy, data need to be captured at high spatial and temporal resolution. While many methods exist to accelerate MRI temporal resolution, not all are optimized to capture breast DCE-MRI dynamics. We propose a novel, flexible, and powerful framework for the reconstruction of highly-undersampled DCE-MRI data: enhancement-constrained acceleration (ECA). Enhancement-constrained acceleration uses an assumption of smooth enhancement at small time-scale to estimate points of smooth enhancement curves in small time intervals at each voxel. This method is tested in silico with physiologically realistic virtual phantoms, simulating state-of-the-art ultrafast acquisitions at 3.5s temporal resolution reconstructed at 0.25s temporal resolution (demo code available here). Virtual phantoms were developed from real patient data and parametrized in continuous time with arterial input function (AIF) models and lesion enhancement functions. Enhancement-constrained acceleration was compared to standard ultrafast reconstruction in estimating the bolus arrival time and initial slope of enhancement from reconstructed images. We found that the ECA method reconstructed images at 0.25s temporal resolution with no significant loss in image fidelity, a 4x reduction in the error of bolus arrival time estimation in lesions (p < 0.01) and 11x error reduction in blood vessels (p < 0.01). Our results suggest that ECA is a powerful and versatile tool for breast DCE-MRI., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2021
- Full Text
- View/download PDF
31. An in silico validation framework for quantitative DCE-MRI techniques based on a dynamic digital phantom.
- Author
-
Wu C, Hormuth DA 2nd, Easley T, Eijkhout V, Pineda F, Karczmar GS, and Yankeelov TE
- Subjects
- Computer Simulation, Humans, Image Processing, Computer-Assisted, Phantoms, Imaging, Contrast Media, Magnetic Resonance Imaging
- Abstract
Quantitative evaluation of an image processing method to perform as designed is central to both its utility and its ability to guide the data acquisition process. Unfortunately, these tasks can be quite challenging due to the difficulty of experimentally obtaining the "ground truth" data to which the output of a given processing method must be compared. One way to address this issue is via "digital phantoms", which are numerical models that provide known biophysical properties of a particular object of interest. In this contribution, we propose an in silico validation framework for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition and analysis methods that employs a novel dynamic digital phantom. The phantom provides a spatiotemporally-resolved representation of blood-interstitial flow and contrast agent delivery, where the former is solved by a 1D-3D coupled computational fluid dynamic system, and the latter described by an advection-diffusion equation. Furthermore, we establish a virtual simulator which takes as input the digital phantom, and produces realistic DCE-MRI data with controllable acquisition parameters. We assess the performance of a simulated standard-of-care acquisition (Protocol A) by its ability to generate contrast-enhanced MR images that separate vasculature from surrounding tissue, as measured by the contrast-to-noise ratio (CNR). We find that the CNR significantly decreases as the spatial resolution (SR
A , where the subscript indicates Protocol A) or signal-to-noise ratio (SNRA ) decreases. Specifically, with an SNRA / SRA = 75 dB / 30 μm, the median CNR is 77.30, whereas an SNRA / SRA = 5 dB / 300 μm reduces the CNR to 6.40. Additionally, we assess the performance of simulated ultra-fast acquisition (Protocol B) by its ability to generate DCE-MR images that capture contrast agent pharmacokinetics, as measured by error in the signal-enhancement ratio (SER) compared to ground truth (PESER ). We find that PESER significantly decreases the as temporal resolution (TRB ) increases. Similar results are reported for the effects of spatial resolution and signal-to-noise ratio on PESER . For example, with an SNRB / SRB / TRB = 5 dB / 300 μm / 10 s, the median PESER is 21.00%, whereas an SNRB / SRB / TRB = 75 dB / 60 μm / 1 s, yields a median PESER of 0.90%. These results indicate that our in silico framework can generate virtual MR images that capture effects of acquisition parameters on the ability of generated images to capture morphological or pharmacokinetic features. This validation framework is not only useful for investigations of perfusion-based MRI techniques, but also for the systematic evaluation and optimization new MRI acquisition, reconstruction, and image processing techniques., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)- Published
- 2021
- Full Text
- View/download PDF
32. High spectral and spatial resolution MRI of prostate cancer: a pilot study.
- Author
-
Medved M, Chatterjee A, Devaraj A, Harmath C, Lee G, Yousuf A, Antic T, Oto A, and Karczmar GS
- Subjects
- Humans, Male, Pilot Projects, Reproducibility of Results, Magnetic Resonance Imaging, Prostatic Neoplasms diagnostic imaging
- Abstract
Purpose: High spectral and spatial resolution (HiSS) MRI is a spectroscopic imaging method focusing on water and fat resonances that has good diagnostic utility in breast imaging. The purpose of this work was to assess the feasibility and potential utility of HiSS MRI for the diagnosis of prostate cancer., Methods: HiSS MRI was acquired at 3 T from six patients who underwent prostatectomy, yielding a train of 127 phase-coherent gradient echo (GRE) images. In the temporal domain, changes in voxel intensity were analyzed and linear (R) and quadratic (R1, R2) quantifiers of signal logarithm decay were calculated. In the spectral domain, three signal scaling-independent parameters were calculated: water resonance peak width (PW), relative peak asymmetry (PRA), and relative peak distortion from ideal Lorentzian shape (PRD). Seven cancer and five normal tissue regions of interest were identified in correlation with pathology and compared., Results: HiSS-derived quantifiers, except R2, showed high reproducibility (coefficients of variation, 5%-14%). Spectral domain quantifiers performed better than temporal domain quantifiers, with receiver operator characteristic areas under the curve ranging from of 0.83 to 0.91. For temporal domain parameters, the range was 0.74 to 0.91. Low absolute values of the coefficients of correlation between monoexponential decay markers (R, PW) and resonance shape markers (PRA, PRD) were observed (range, 0.23-0.38)., Conclusion: The feasibility and potential diagnostic utility of HiSS MRI in the prostate at 3 T without an endorectal coil was confirmed. Weak correlation between well-performing markers indicates that complementary information could be leveraged to further improve diagnostic accuracy., (© 2021 International Society for Magnetic Resonance in Medicine.)
- Published
- 2021
- Full Text
- View/download PDF
33. Sensitivity to myelin using model-free analysis of the water resonance line-shape in postmortem mouse brain.
- Author
-
Foxley S, Wildenberg G, Sampathkumar V, Karczmar GS, Brugarolas P, and Kasthuri N
- Subjects
- Animals, Brain diagnostic imaging, Echo-Planar Imaging, Magnetic Resonance Imaging, Mice, Water, Myelin Sheath, White Matter diagnostic imaging
- Abstract
Purpose: Dysmyelinating diseases are characterized by abnormal myelin formation and function. Such microstructural abnormalities in myelin have been demonstrated to produce measurable effects on the MR signal. This work examines these effects on measurements of voxel-wise, high-resolution water spectra acquired using a 3D echo-planar spectroscopic imaging (EPSI) pulse sequence from both postmortem fixed control mouse brains and a dysmyelination mouse brain model., Methods: Perfusion fixed, resected control (n = 5) and shiverer (n = 4) mouse brains were imaged using 3D-EPSI with 100 µm isotropic resolution. The free induction decay (FID) was sampled every 2.74 ms over 192 echoes, for a total sampling duration of 526.08 ms. Voxel-wise FIDs were Fourier transformed to produce water spectra with 1.9 Hz resolution. Spectral asymmetry was computed and compared between the two tissue types., Results: The water resonance is more asymmetrically broadened in the white matter of control mouse brain compared with dysmyelinated white matter. In control brain, this is modulated by and consistent with previously reported orientationally dependent effects of white matter relative to B
0 . Similar sensitivity to orientation is observed in dysmyelinated white matter as well; however, the magnitude of the resonance asymmetry is much lower across all directions., Conclusion: Results demonstrate that components of the spectra are specifically differentially affected by myelin concentration. This suggests that water proton spectra may be sensitive to the presence of myelin, and as such, could serve as a MRI-based biomarker of dysmyelinating disease, free of mathematical models., (© 2020 International Society for Magnetic Resonance in Medicine.)- Published
- 2021
- Full Text
- View/download PDF
34. Signal intensity form of the Tofts model for quantitative analysis of prostate dynamic contrast enhanced MRI data.
- Author
-
Fan X, Chatterjee A, Medved M, Oto A, and Karczmar GS
- Subjects
- Computer Simulation, Humans, Image Enhancement, Male, Reproducibility of Results, Contrast Media, Magnetic Resonance Imaging, Prostatic Neoplasms diagnostic imaging, Signal-To-Noise Ratio
- Abstract
The aim of this study is to develop a signal intensity (S(t)) form of the standard Tofts pharmacokinetic model that avoids the need to calculate tissue contrast agent concentration (C(t)) as function of time (t). We refer to this as 'SI-Tofts' model. Physiological parameters (K
trans and ve ) calculated using the SI-Tofts and standard Tofts models were compared by using simulations and human prostate dynamic contrast enhanced (DCE) MRI data. This approach was also applied to the Patlak model to compare Ktrans values calculated from C(t) and S(t). Simulations were performed on DCE-MRI data from the quantitative imaging biomarkers alliance to validate SI-Tofts model. In addition, ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The C(t) was calculated for each ROI using the standard model with measured pre-contrast tissue T1 values. Both the simulation and clinical results showed strong correlation (r = 0.87-0.99, p < 0.001) for Ktrans and ve calculated from the SI-Tofts and standard Tofts models. The SI-Tofts model with a correction factor using the T1 ratio of blood to tissue significantly improved the Ktrans estimates. The correlation of Ktrans obtained from the Patlak model with C(t) vs S(t) was also strong (r = 0.95-0.99, p < 0.001). These preliminary results suggest that physiological parameters from DCE-MRI can be reliably estimated from the SI-Tofts model without contrast agent concentration calculation.- Published
- 2021
- Full Text
- View/download PDF
35. T2*-weighted MRI as a non-contrast-enhanced method for assessment of focal laser ablation zone extent in prostate cancer thermotherapy.
- Author
-
Sun C, Wang S, Chatterjee A, Medved M, Eggener S, Karczmar GS, and Oto A
- Subjects
- Humans, Magnetic Resonance Imaging, Male, Hyperthermia, Induced, Laser Therapy, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms surgery
- Abstract
Objectives: To evaluate utility of T2*-weighted (T2*W) MRI as a tool for intra-operative identification of ablation zone extent during focal laser ablation (FLA) of prostate cancer (PCa), as compared to the current standard of contrast-enhanced T1-weighted (T1W) MRI., Methods: Fourteen patients with biopsy-confirmed low- to intermediate-risk localized PCa received MRI-guided (1.5 T) FLA thermotherapy. Following FLA, axial multiple-TE T2*W images, diffusion-weighted images (DWI), and T2-weighted (T2W) images were acquired. Pre- and post-contrast T1W images were also acquired to assess ablation zone (n = 14) extent, as reference standard. Apparent diffusion coefficient (ADC) maps and subtracted contrast-enhanced T1W (sceT1W) images were calculated. Ablation zone regions of interest (ROIs) were outlined manually on all ablated slices. The contrast-to-noise ratio (CBR) of the ablation site ROI relative to the untreated contralateral prostate tissue was calculated on T2*W images and ADC maps and compared to that in sceT1W images., Results: CBRs in ablation ROIs on T2*W images (TE = 32, 63 ms) did not differ (p = 0.33, 0.25) from those in sceT1W images. Bland-Altman plots of ROI size and CBR in ablation sites showed good agreement between T2*W (TE = 32, 63 ms) and sceT1W images, with ROI sizes on T2*W (TE = 63 ms) strongly correlated (r = 0.64, p = 0.013) and within 15% of those in sceT1W images., Conclusions: In detected ablation zone ROI size and CBR, non-contrast-enhanced T2*W MRI is comparable to contrast-enhanced T1W MRI, presenting as a potential method for intra-procedural monitoring of FLA for PCa., Key Points: • T2*-weighted MR images with long TE visualize post-procedure focal laser ablation zone comparably to the contrast-enhanced T1-weighted MRI. • T2*-weighted MRI could be used as a plausible method for repeated intra-operative monitoring of thermal ablation zone in prostate cancer, avoiding potential toxicity due to heating of contrast agent.
- Published
- 2021
- Full Text
- View/download PDF
36. Comparison of DCE-MRI of murine model cancers with a low dose and high dose of contrast agent.
- Author
-
Zhou X, Fan X, Mustafi D, Pineda F, Markiewicz E, Zamora M, Sheth D, Olopade OI, Oto A, and Karczmar GS
- Subjects
- Animals, Disease Models, Animal, Female, Image Enhancement, Magnetic Resonance Imaging, Mice, Mice, Inbred C3H, Contrast Media, Neoplasms
- Abstract
There are increasing concerns regarding intracellular accumulation of gadolinium (Gd) after multiple dynamic contrast enhanced (DCE) MRI scans. We investigated whether a low dose (LD) of Gd-based contrast agent is as effective as a high dose (HD) for quantitative analysis of DCE-MRI data, and evaluated the use of a split dose protocol to obtain new diagnostic parameters. Female C3H mice (n = 6) were injected with mammary carcinoma cells in the hind leg. MRI experiments were performed on 9.4 T scanner. DCE-MRI data were acquired with 1.5 s temporal resolution before and after a LD (0.04 mmol/kg), then again after 30 min followed by a HD (0.2 mmol/kg) bolus injection of Omniscan. The standard Tofts model was used to extract physiological parameters (K
trans and ve ) with the arterial input function derived from muscle reference tissue. In addition, an empirical mathematical model was used to characterize maximum contrast agent uptake (A), contrast agent uptake rate (α) and washout rate (β and γ). There were moderate to strong correlations (r = 0.69-0.97, p < 0001) for parameters Ktrans , ve , A, α and β from LD versus HD data. On average, tumor parameters obtained from LD data were significantly larger (p < 0.05) than those from HD data. The parameter ratios, Ktrans , ve , A and α calculated from the LD data divided by the HD data, were all significantly larger than 1.0 (p < 0.003) for tumor. T2 * changes following contrast agent injection affected parameters calculated from HD data, but this was not the case for LD data. The results suggest that quantitative analysis of LD data may be at least as effective for cancer characterization as quantitative analysis of HD data. In addition, the combination of parameters from two different doses may provide useful diagnostic information., (Copyright © 2020 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)- Published
- 2021
- Full Text
- View/download PDF
37. Effect of Echo Times on Prostate Cancer Detection on T2-Weighted Images.
- Author
-
Chatterjee A, Nolan P, Sun C, Mathew M, Dwivedi D, Yousuf A, Antic T, Karczmar GS, and Oto A
- Subjects
- Humans, Magnetic Resonance Imaging, Male, Prostatectomy, Sensitivity and Specificity, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms surgery
- Abstract
Purpose: To compare the effect of different echo times (TE) on the detection of prostate cancer (PCa) on T2-weighted MR images., Materials and Methods: This study recruited patients (n = 38) with histologically confirmed PCa who underwent preoperative 3T MRI. Three radiologists independently marked region on interests (ROIs) on suspected PCa lesions on T2-weighted images at different TEs: 90, 150, and 180 ms obtained with Turbo Spin Echo imaging protocol with multiple echoes. The ROIs were assigned a value 1-5 indicating the reviewer's confidence in accurately detecting PCa. These ROIs were compared to histologically confirmed PCa (n = 95) on whole mount prostatectomy sections to calculate sensitivity, positive predictive value (PPV), and confidence score., Results: Two radiologists (R1, R2) showed significantly increased sensitivity for PCa detection at 180 ms TE compared to 90 ms (R1: 43.2, 50.5, 50.5%, R2: 45.3, 44.2, 53.7% at TE of 90, 150, 180 ms, respectively) (p = 0.048, 0.033 for R1 and R2). Sensitivity was similar for radiologist 3 (45.3%-46.3%) at different TE values (p = 0.953). No significant difference in the PPV (R1: 64.1%-70.6%, R2: 46.7%-56.0%, R3: 70.5%-81.5%) and the confidence score assigned (R1: 4.6-4.8, R2: 4.6-4.8 R3: 4.3-4.4) was found for either of the radiologists., Conclusion: Our results suggest improved detection of PCa with similar PPV and confidence scores when higher TE values are utilized for T2-weighted image acquisition., (Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)
- Published
- 2020
- Full Text
- View/download PDF
38. Magnetic resonance angiography reveals increased arterial blood supply and tumorigenesis following high fat feeding in a mouse model of triple-negative breast cancer.
- Author
-
Mustafi D, Valek R, Fitch M, Werner V, Fan X, Markiewicz E, Fernandez S, Zamora M, Mueller J, Olopade OI, Conzen SD, Brady MJ, and Karczmar GS
- Subjects
- Animals, Disease Models, Animal, Female, Imaging, Three-Dimensional, Mammary Glands, Animal diagnostic imaging, Mammary Glands, Animal pathology, Mammary Neoplasms, Animal diagnostic imaging, Mammary Neoplasms, Animal pathology, Mice, Neoplasm Invasiveness, Organ Size, Regional Blood Flow, Tumor Burden, Arteries diagnostic imaging, Carcinogenesis pathology, Diet, High-Fat, Feeding Behavior, Magnetic Resonance Angiography, Triple Negative Breast Neoplasms diagnostic imaging, Triple Negative Breast Neoplasms pathology
- Abstract
Breast cancer is the second most commonly diagnosed malignancy among women globally. Past MRI studies have linked a high animal fat diet (HAFD) to increased mammary cancer risk in the SV40Tag mouse model of triple-negative breast cancer. Here, serial MRI examines tumor progression and measures the arterial blood volume feeding mammary glands in low fat diet (LFD) or HAFD fed mice. Virgin female C3(1)SV40Tag mice (n = 8), weaned at 3 weeks old, were assigned to an LFD (n = 4, 3.7 kcal/g, 17.2% kcal from vegetable oil) or an HAFD (n = 4, 5.3 kcal/g, 60% kcal from lard) group. From ages 8 to 12 weeks, weekly fast spin echo MR images and time-of-flight (TOF) MR angiography of inguinal mammary glands were acquired at 9.4 T. Following in vivo MRI, mice were sacrificed. Inguinal mammary glands were excised and fixed for ex vivo MRI and histology. Tumor, blood, and mammary gland volumes for each time point were measured from manually traced regions of interest; tumors were classified as invasive by histopathology-blinded observers. Our analysis confirmed a strong correlation between total tumor volume and blood volume in the mammary gland. Tumor growth rates from weeks 8-12 were twice as high in HAFD-fed mice (0.42 ± 0.14/week) as in LFD-fed mice (0.21 ± 0.03/week), p < 0.004. Mammary gland blood volume growth rate was 2.2 times higher in HAFD mice (0.29 ± 0.11/week) compared with LFD mice (0.13 ± 0.06/week), p < 0.02. The mammary gland growth rate of HAFD-fed mice (0.071 ± 0.011/week) was 2.7 times larger than that of LFD-fed mice (0.026 ± 0.009/week), p < 0.01. This is the first non-invasive, in vivo MRI study to demonstrate a strong correlation between an HAFD and increased cancer burden and blood volume in mammary cancer without using contrast agents, strengthening the evidence supporting the adverse effects of an HAFD on mammary cancer. These results support the potential future use of TOF angiography to evaluate vasculature of suspicious lesions., (© 2020 John Wiley & Sons, Ltd.)
- Published
- 2020
- Full Text
- View/download PDF
39. Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics.
- Author
-
Wu C, Hormuth DA, Oliver TA, Pineda F, Lorenzo G, Karczmar GS, Moser RD, and Yankeelov TE
- Subjects
- Breast diagnostic imaging, Contrast Media, Diffusion Magnetic Resonance Imaging, Female, Hemodynamics, Humans, Hydrodynamics, Magnetic Resonance Imaging, ROC Curve, Retrospective Studies, Sensitivity and Specificity, Breast Neoplasms diagnostic imaging
- Abstract
The overall goal of this study is to employ quantitative magnetic resonance imaging (MRI) data to constrain a patient-specific, computational fluid dynamics (CFD) model of blood flow and interstitial transport in breast cancer. We develop image processing methodologies to generate tumor-related vasculature-interstitium geometry and realistic material properties, using dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted MRI (DW-MRI) data. These data are used to constrain CFD simulations for determining the tumor-associated blood supply and interstitial transport characteristics unique to each patient. We then perform a proof-of-principle statistical comparison between these hemodynamic characteristics in 11 malignant and 5 benign lesions from 12 patients. Significant differences between groups (i.e., malignant versus benign) were observed for the median of tumor-associated interstitial flow velocity ( P = 0.028 ), and the ranges of tumor-associated blood pressure (P = 0.016) and vascular extraction rate (P = 0.040). The implication is that malignant lesions tend to have larger magnitude of interstitial flow velocity, and higher heterogeneity in blood pressure and vascular extraction rate. Multivariable logistic models based on combinations of these hemodynamic data achieved excellent differentiation between malignant and benign lesions with an area under the receiver operator characteristic curve of 1.0, sensitivity of 1.0, and specificity of 1.0. This image-based model system is a fundamentally new way to map flow and pressure fields related to breast tumors using only non-invasive, clinically available imaging data and established laws of fluid mechanics. Furthermore, the results provide preliminary evidence for this methodology's utility for the quantitative characterization of breast cancer.
- Published
- 2020
- Full Text
- View/download PDF
40. Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images.
- Author
-
Penn AI, Medved M, Dialani V, Pisano ED, Cole EB, Brousseau D, Karczmar GS, Gao G, Reich BD, and Abe H
- Subjects
- Breast pathology, Breast Density, Diagnosis, Differential, Diffusion Magnetic Resonance Imaging, Female, Humans, Observer Variation, Sensitivity and Specificity, Breast diagnostic imaging, Breast Neoplasms diagnostic imaging, Radiographic Image Interpretation, Computer-Assisted methods
- Abstract
Background: There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts., Methods: We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.50 cm
2 were excluded, resulting in analysis of 50 cases with 63 lesions (29 benign, 34 cancers). Spin-echo echo-planar imaging DWI was acquired at 1.5 T and 3 T. Data from three diffusion encoding gradient directions were exported and processed independently. Lesion ROIs were hand-drawn on DWI images by two radiologists. A region growing algorithm generated 3D lesion models on augmented apparent-diffusion coefficient (ADC) maps and defined lesion core and lesion periphery sub-ROIs. A lesion-core and a lesion-periphery feature were defined and combined into an overall classifier whose performance was compared to that of mean ADC using receiver operating characteristic (ROC) analysis. Inter-observer variability in ROI definition was measured using Dice Similarity Coefficient (DSC)., Results: The region-growing algorithm for 3D lesion model generation improved inter-observer variability over hand drawn ROIs (DSC: 0.66 vs 0.56 (p < 0.001) with substantial agreement (DSC > 0.8) in 46% vs 13% of cases, respectively (p < 0.001)). The overall classifier improved discrimination over mean ADC, (ROC- area under the curve (AUC): 0.85 vs 0.75 and 0.83 vs 0.74 respectively for the two readers)., Conclusions: A classifier generated from directional DWI information using lesion core and lesion periphery information separately can improve lesion discrimination in dense breasts over mean ADC and should be considered for inclusion in computer-aided diagnosis algorithms. Our model-based ROIs could facilitate standardization of breast MRI computer-aided diagnostics (CADx).- Published
- 2020
- Full Text
- View/download PDF
41. Low-dose imaging technique (LITE) MRI: initial experience in breast imaging.
- Author
-
Pineda F, Sheth D, Abe H, Medved M, and Karczmar GS
- Subjects
- Adolescent, Adult, Contrast Media administration & dosage, Contrast Media pharmacokinetics, Dose-Response Relationship, Drug, Female, Gadolinium administration & dosage, Gadolinium pharmacokinetics, Humans, Magnetic Resonance Imaging methods, Middle Aged, Signal-To-Noise Ratio, Young Adult, Breast Neoplasms diagnosis, Fibroadenoma diagnosis
- Abstract
Objectives: To compare a low-dose dynamic contrast-enhanced breast MRI protocol (LITE MRI) to standard-dosage using a dual-dose injection technique., Methods: 8 females with a total of 10 lesions with imaging features compatible with fibroadenoma were imaged using a dual-dose dynamic contrast-enhanced-MRI (DCE-MRI) technique. After pre-contrast scans, 15% of a standard dose of contrast was administered; approximately 10 min later, the remaining 85% of the standard dose was administered. Enhancement kinetic parameters, conspicuity and signal-to-noise ratio were measured quantitatively., Results: One lesion showed no enhancement in either DCE series. All nine of the enhancing lesions were visualized in both the low-dose and standard-dose images. While the (low-to-standard) ratio of contrast doses was roughly 0.18, this did not match the ratios of kinetic parameters. Lesion conspicuity and enhancement rate were both higher in the low-dose images, with (low-to-standard) ratios 1.5 ± 0.1 and 1.2 ± 0.4, respectively. The upper limit of enhancement (ratio 0.3 ± 0.1) and signal-to-noise ratio (ratio 0.5 ± 0.1) were higher in the standard-dose images, but less than expected based on the ratio of the doses., Conclusions: This preliminary study demonstrates that LITE MRI has the potential to match standard DCE-MRI in the detection of enhancing lesions. Additionally, LITE MRI may enhance sensitivity to contrast media dynamics., Advances in Knowledge: Lower doses of MRI contrast media may be equally effective in the detection of breast lesions, and increase sensitivity to contrast media dynamics. LITE MRI may help increase screening compliance and long-term patient safety.
- Published
- 2019
- Full Text
- View/download PDF
42. A compact solution for estimation of physiological parameters from ultrafast prostate dynamic contrast enhanced MRI.
- Author
-
He D, Fan X, Chatterjee A, Wang S, Medved M, Pineda FD, Yousuf A, Antic T, Oto A, and Karczmar GS
- Subjects
- Humans, Magnetic Resonance Imaging standards, Male, Middle Aged, Reproducibility of Results, Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging
- Abstract
The Tofts pharmacokinetic model requires multiple calculations for analysis of dynamic contrast enhanced (DCE) MRI. In addition, the Tofts model may not be appropriate for the prostate. This can result in error propagation that reduces the accuracy of pharmacokinetic measurements. In this study, we present a compact solution allowing estimation of physiological parameters K
trans and ve from ultrafast DCE acquisitions, without fitting DCE-MRI data to the standard Tofts pharmacokinetic model. Since the standard Tofts model can be simplified to the Patlak model at early times when contrast efflux from the extravascular extracellular space back to plasma is negligible, Ktrans can be solved explicitly for a specific time. Further, ve can be estimated directly from the late steady-state signal using the derivative form of Tofts model. Ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The contrast media concentration as function of time was calculated over each ROI using gradient echo signal equation with pre-contrast tissue T1 values, and using the 'reference tissue' model with a linear approximation. There was strong correlation (r = 0.88-0.91, p < 0.0001) between Ktrans extracted from the Tofts model and Ktrans estimated from the compact solution for prostate cancer and normal tissue. Additionally, there was moderate correlation (r = 0.65-0.73, p < 0.0001) between extracted versus estimated ve . Bland-Altman analysis showed moderate to good agreement between physiological parameters extracted from the Tofts model and those estimated from the compact solution with absolute bias less than 0.20 min-1 and 0.10 for Ktrans and ve , respectively. The compact solution may decrease systematic errors and error propagation, and could increase the efficiency of clinical workflow. The compact solution requires high temporal resolution DCE-MRI due to the need to adequately sample the early phase of contrast media uptake.- Published
- 2019
- Full Text
- View/download PDF
43. Diagnosis of Prostate Cancer by Use of MRI-Derived Quantitative Risk Maps: A Feasibility Study.
- Author
-
Chatterjee A, He D, Fan X, Antic T, Jiang Y, Eggener S, Karczmar GS, and Oto A
- Subjects
- Aged, Biopsy, Contrast Media, Diffusion Magnetic Resonance Imaging, Feasibility Studies, Humans, Male, Middle Aged, Neoplasm Grading, Prostatectomy, Prostatic Neoplasms pathology, Prostatic Neoplasms surgery, Retrospective Studies, Risk Assessment, Sensitivity and Specificity, Image Processing, Computer-Assisted methods, Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging
- Abstract
OBJECTIVE. The purpose of this study was to develop a new quantitative image analysis tool for estimating the risk of cancer of the prostate by use of quantitative multiparametric MRI (mpMRI) metrics. MATERIALS AND METHODS. Thirty patients with biopsy-confirmed prostate cancer (PCa) who underwent preoperative 3-T mpMRI were included in the study. Quantitative mpMRI metrics-apparent diffusion coefficient (ADC), T2, and dynamic contrast-enhanced (DCE) signal enhancement rate (α)-were calculated on a voxel-by-voxel basis for the whole prostate and coregistered. A normalized risk value (0-100) for each mpMRI parameter was obtained, with high risk values associated with low T2 and ADC and high signal enhancement rate. The final risk score was calculated as a weighted sum of the risk scores (ADC, 40%; T2, 40%; DCE, 20%). Data from five patients were used as training set to find the threshold for predicting PCa. In the other 25 patients, any region with a minimum of 30 con-joint voxels (≈ 4.8 mm
2 ) with final risk score above the threshold was considered positive for cancer. Lesion-based and sector-based analyses were performed by matching prostatectomyverified malignancy and PCa predicted with the risk analysis tool. RESULTS. The risk map tool had sensitivity of 76.6%, 89.2%, and 100% for detecting all lesions, clinically significant lesions (≥ Gleason 3 + 4), and index lesions, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for PCa detection for all lesions in the sector-based analysis were 78.9%, 88.5%, 84.4%, and 84.1%, respectively, with an ROC AUC of 0.84. CONCLUSION. The risk analysis tool is effective for detecting clinically significant PCa with reasonable sensitivity and specificity in both peripheral and transition zones.- Published
- 2019
- Full Text
- View/download PDF
44. Ultrafast Dynamic Contrast-Enhanced Breast MRI: Kinetic Curve Assessment Using Empirical Mathematical Model Validated with Histological Microvessel Density.
- Author
-
Mori N, Abe H, Mugikura S, Takasawa C, Sato S, Miyashita M, Mori Y, Pineda FD, Karczmar GS, Tamura H, Takahashi S, and Takase K
- Subjects
- Adult, Aged, Aged, 80 and over, Breast diagnostic imaging, Breast pathology, Breast Neoplasms pathology, Female, Humans, Kinetics, Middle Aged, Models, Theoretical, Reproducibility of Results, Retrospective Studies, Breast Neoplasms diagnostic imaging, Contrast Media, Image Enhancement methods, Image Interpretation, Computer-Assisted methods, Magnetic Resonance Imaging methods, Microvessels diagnostic imaging
- Abstract
Rationale and Objectives: To evaluate whether parameters from empirical mathematical model (EMM) for ultrafast dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) correlate with histological microvessel density (MVD) in invasive breast cancer., Materials and Methods: Ninety-eight consecutive patients with invasive breast cancer underwent an institutional review board-approved ultrafast DCE-MRI including a pre- and 18 postcontrast whole breast ultrafast scans (3 seconds) followed by four standard scans (60 seconds) using a 3T system. Region of interest was placed within each lesion where the highest signal increase was observed on ultrafast DCE-MRI, and the increase rate of enhancement was calculated as follows: ΔS = (SIpost - SIpre)/SIpre. The kinetic curve obtained from ultrafast DCE-MRI was analyzed using a truncated EMM: ΔS(t) = A(1 - e
- αt ), where A is the upper limit of the signal intensity, α (min-1 ) is the rate of signal increase. The initial slope of the kinetic curve is given by Aα. Initial area under curve (AUC30) and time of initial enhancement was calculated. From the standard DCE-MRI, the initial enhancement rate (IER) and the signal enhancement ratio (SER) were calculated as follows: IER = (SIearly - SIpre)/SIpre, SER = (SIearly - SIpre)/(SIdelayed - SIpre). The parameters were compared to MVD obtained from surgical specimens., Results: A, α, Aα, AUC30, and time of initial enhancement significantly correlated with MVD (r = 0.29, 0.40, 0.51, 0.43, and -0.32 with p = 0.0027, p < 0.0001, p < 0.0001, p < 0.0001, and p = 0.0012, respectively), whereas IER and SER from standard DCE-MRI did not., Conclusion: The parameters of the EMM, especially the initial slope or Aα, for ultrafast DCE-MRI correlated with MVD in invasive breast cancer., (Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)- Published
- 2019
- Full Text
- View/download PDF
45. Use of Indicator Dilution Principle to Evaluate Accuracy of Arterial Input Function Measured With Low-Dose Ultrafast Prostate Dynamic Contrast-Enhanced MRI.
- Author
-
Wang S, Fan X, Zhang Y, Medved M, He D, Yousuf A, Jamison E, Oto A, and Karczmar GS
- Subjects
- Aged, Humans, Indicator Dilution Techniques, Male, Middle Aged, Prostate diagnostic imaging, Reproducibility of Results, Contrast Media administration & dosage, Image Enhancement methods, Image Interpretation, Computer-Assisted methods, Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging
- Abstract
Accurately measuring arterial input function (AIF) is essential for quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI). We used the indicator dilution principle to evaluate the accuracy of AIF measured directly from an artery following a low-dose contrast media ultrafast DCE-MRI. In total, 15 patients with biopsy-confirmed localized prostate cancers were recruited. Cardiac MRI (CMRI) and ultrafast DCE-MRI were acquired on a Philips 3 T Ingenia scanner. The AIF was measured at iliac arties following injection of a low-dose (0.015 mmol/kg) gadolinium (Gd) contrast media. The cardiac output (CO) from CMRI (CO
CMRI ) was calculated from the difference in ventricular volume at diastole and systole measured on the short axis of heart. The CO from DCE-MRI (CODCE ) was also calculated from the AIF and dose of the contrast media used. A correlation test and Bland-Altman plot were used to compare COCMRI and CODCE . The average (±standard deviation [SD]) area under the curve measured directly from local AIF was 0.219 ± 0.07 mM·min. The average (±SD) COCMRI and CODCE were 6.52 ± 1.47 L/min and 6.88 ± 1.64 L/min, respectively. There was a strong positive correlation ( r = 0.82, P < .01) and good agreement between COCMRI and CODCE . The CODCE is consistent with the reference standard COCMRI . This indicates that the AIF can be measured accurately from an artery with ultrafast DCE-MRI following injection of a low-dose contrast media., Competing Interests: Conflict of Interest: The authors have no conflict of interest to declare.- Published
- 2019
- Full Text
- View/download PDF
46. Revisiting quantitative multi-parametric MRI of benign prostatic hyperplasia and its differentiation from transition zone cancer.
- Author
-
Chatterjee A, Gallan AJ, He D, Fan X, Mustafi D, Yousuf A, Antic T, Karczmar GS, and Oto A
- Subjects
- Adult, Aged, Contrast Media, Diagnosis, Differential, Diffusion Magnetic Resonance Imaging, Humans, Male, Middle Aged, Prostatectomy, Prostatic Hyperplasia surgery, Prostatic Neoplasms surgery, Retrospective Studies, Magnetic Resonance Imaging methods, Prostatic Hyperplasia diagnostic imaging, Prostatic Neoplasms diagnostic imaging
- Abstract
Purpose: This study investigates the multiparametric MRI (mpMRI) appearance of different types of benign prostatic hyperplasia (BPH) and whether quantitative mpMRI is effective in differentiating between prostate cancer (PCa) and BPH., Materials and Methods: Patients (n = 60) with confirmed PCa underwent preoperative 3T MRI. T2-weighted, multi-echo T2-weighted, diffusion weighted and dynamic contrast enhanced images (DCE) were obtained prior to undergoing prostatectomy. PCa and BPH (cystic, glandular or stromal) were identified in the transition zone and matched with MRI. Quantitative mpMRI metrics: T2, ADC and DCE-MRI parameters using an empirical mathematical model were measured., Results: ADC values were significantly lower (p < 0.001) in PCa compared to all BPH types and can differentiate between PCa and BPH with high accuracy (AUC = 0.87, p < 0.001). T2 values were significantly lower (p < 0.001) in PCa compared to cystic BPH only, while glandular (p = 0.27) and stromal BPH (p = 0.99) showed no significant difference from PCa. BPH mimics PCa in the transition zone on DCE-MRI evidenced by no significant difference between them. mpMRI values of glandular (ADC = 1.31 ± 0.22 µm
2 /ms, T2 = 115.7 ± 37.3 ms) and cystic BPH (ADC = 1.92 ± 0.43 µm2 /ms, T2 = 242.8 ± 117.9 ms) are significantly different. There was no significant difference in ADC (p = 0.72) and T2 (p = 0.46) between glandular and stromal BPH., Conclusions: Multiparametric MRI and specifically quantitative ADC values can be used for differentiating PCa and BPH, improving PCa diagnosis in the transition zone. However, DCE-MRI metrics are not effective in distinguishing PCa and BPH. Glandular BPH are not hyperintense on ADC and T2 as previously thought and have similar quantitative mpMRI measurements to stromal BPH. Glandular and cystic BPH appear differently on mpMRI and are histologically different.- Published
- 2019
- Full Text
- View/download PDF
47. Quantitative analysis of vascular properties derived from ultrafast DCE-MRI to discriminate malignant and benign breast tumors.
- Author
-
Wu C, Pineda F, Hormuth DA 2nd, Karczmar GS, and Yankeelov TE
- Subjects
- Adult, Aged, Area Under Curve, Contrast Media, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted methods, Image Processing, Computer-Assisted, Imaging, Three-Dimensional, Logistic Models, Microcirculation, Middle Aged, Multivariate Analysis, ROC Curve, Regression Analysis, Time Factors, Breast diagnostic imaging, Breast Neoplasms blood supply, Breast Neoplasms diagnostic imaging, Magnetic Resonance Imaging
- Abstract
Purpose: We propose a novel methodology to integrate morphological and functional information of tumor-associated vessels to assist in the diagnosis of suspicious breast lesions., Theory and Methods: Ultrafast, fast, and high spatial resolution DCE-MRI data were acquired on 15 patients with suspicious breast lesions. Segmentation of the vasculature from the surrounding tissue was performed by applying a Hessian filter to the enhanced image to generate a map of the probability for each voxel to belong to a vessel. Summary measures were generated for vascular morphology, as well as the inputs and outputs of vessels physically connected to the tumor. The ultrafast DCE-MRI data was analyzed by a modified Tofts model to estimate the bolus arrival time, K
trans (volume transfer coefficient), and vp (plasma volume fraction). The measures were compared between malignant and benign lesions via the Wilcoxon test, and then incorporated into a logistic ridge regression model to assess their combined diagnostic ability., Results: A total of 24 lesions were included in the study (13 malignant and 11 benign). The vessel count, Ktrans , and vp showed significant difference between malignant and benign lesions (P = 0.009, 0.034, and 0.010, area under curve [AUC] = 0.76, 0.63, and 0.70, respectively). The best multivariate logistic regression model for differentiation included the vessel count and bolus arrival time (AUC = 0.91)., Conclusion: This study provides preliminary evidence that combining quantitative characterization of morphological and functional features of breast vasculature may provide an accurate means to diagnose breast cancer., (© 2018 International Society for Magnetic Resonance in Medicine.)- Published
- 2019
- Full Text
- View/download PDF
48. Comparison of T2-Weighted Imaging, DWI, and Dynamic Contrast-Enhanced MRI for Calculation of Prostate Cancer Index Lesion Volume: Correlation With Whole-Mount Pathology.
- Author
-
Sun C, Chatterjee A, Yousuf A, Antic T, Eggener S, Karczmar GS, and Oto A
- Subjects
- Aged, Correlation of Data, Humans, Male, Middle Aged, Retrospective Studies, Tumor Burden, Contrast Media, Magnetic Resonance Imaging methods, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms pathology
- Abstract
Objective: The objective of our study was to investigate the comparative effectiveness of different MRI sequences for the estimation of index lesion volume in patients with prostate cancer (PCa) compared with ground truth volume measured on whole-mount pathology., Materials and Methods: Patients with PCa underwent multiparametric MRI (mpMRI) on a 3-T MRI scanner before radical prostatectomy. Forty PCa index lesions were identified and outlined on histology by a pathologist. Two radiologists who were informed about the presence of PCa but were not aware of lesion outlines on histology worked in consensus to delineate PCa lesions on T2-weighted imaging, apparent diffusion coefficient (ADC) maps, and early-phase dynamic contrast-enhanced MRI (DCE-MRI). The lesion volumes from different mpMRI sequences and the percentage of volume underestimation compared with pathology were calculated and correlated with volume at pathology. The repeated-measures ANOVA with the posthoc Bonferroni test was performed to evaluate whether the difference between the estimated tumor volumes was statistically significant., Results: The mean PCa lesion volume estimated from pathology, T2-weighted imaging, DWI (ADC maps), and DCE-MRI were 4.61 ± 4.99 (SD) cm
3 , 2.03 ± 2.96 cm3 , 1.81 ± 2.76 cm3 , and 3.48 ± 4.06 cm3 , respectively. The lesion volumes on T2-weighted images (p = 0.000002), ADC maps (p = 0.000003), and DCE-MR images (p = 0.004412) were significantly lower than those from pathology. PCa lesion volume was significantly underestimated on T2-weighted images, ADC maps, and DCE-MR images compared with pathology by 54.98% ± 22.60% (mean ± SD), 58.59% ± 18.58%, and 18.33% ± 30.11%, respectively; underestimation using T2-weighted imaging (p = 1.01 × 10-11 ) and DWI (p = 2.94 × 10-11 ) was significantly higher than underestimation using DCE-MRI. Correlations between lesion volume estimated on T2-weighted images, ADC maps, and DCE-MR images with pathology were 0.91 (p = 9.03 × 10-16 ), 0.86 (p = 7.32 × 10-13 ), and 0.93 (p = 8.22 × 10-18 ), respectively., Conclusion: DCE-MRI performed better than T2-weighted imaging and DWI for estimation of index PCa volume and therefore can be preferred over these other two sequences for volume estimation.- Published
- 2019
- Full Text
- View/download PDF
49. Magnetic Resonance Angiography Shows Increased Arterial Blood Supply Associated with Murine Mammary Cancer.
- Author
-
Mustafi D, Leinroth A, Fan X, Markiewicz E, Zamora M, Mueller J, Conzen SD, and Karczmar GS
- Abstract
Breast cancer is a major cause of morbidity and mortality in Western women. Tumor neoangiogenesis, the formation of new blood vessels from pre-existing ones, may be used as a prognostic marker for cancer progression. Clinical practice uses dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to detect cancers based on increased blood flow and capillary permeability. However, DCE-MRI requires repeated injections of contrast media. Therefore we explored the use of noninvasive time-of-flight (TOF) MR angiography for serial studies of mouse mammary glands to measure the number and size of arteries feeding mammary glands with and without cancer. Virgin female C3(1) SV40 TAg mice (n=9), aged 18-20 weeks, were imaged on a 9.4 Tesla small animal scanner. Multislice T
2 -weighted (T2W) images and TOF-MRI angiograms were acquired over inguinal mouse mammary glands. The data were analyzed to determine tumor burden in each mammary gland and the volume of arteries feeding each mammary gland. After in vivo MRI, inguinal mammary glands were excised and fixed in formalin for histology. TOF angiography detected arteries with a diameter as small as 0.1 mm feeding the mammary glands. A significant correlation (r=0.79; p< 0.0001) was found between tumor volume and the arterial blood volume measured in mammary glands. Mammary arterial blood volumes ranging from 0.08 mm3 to 3.81 mm3 were measured. Tumors and blood vessels found on in vivo T2W and TOF images, respectively, were confirmed with ex vivo histological images. These results demonstrate increased recruitment of arteries to mammary glands with cancer, likely associated with neoangiogenesis. Neoangiogenesis may be detected by TOF angiography without injection of contrast agents. This would be very useful in mouse models where repeat placement of I.V. lines is challenging. In addition, analogous methods could be tested in humans to evaluate the vasculature of suspicious lesions without using contrast agents.- Published
- 2019
- Full Text
- View/download PDF
50. The effects of variations in tissue microstructure from postmortem rat brain on the asymmetry of the water proton resonance.
- Author
-
Foxley S, Karczmar GS, and Takahashi K
- Subjects
- Animals, Anisotropy, Brain pathology, Gray Matter diagnostic imaging, Hippocampus diagnostic imaging, Imaging, Three-Dimensional, Protons, Rats, Spectrophotometry, Water chemistry, White Matter diagnostic imaging, Brain diagnostic imaging, Echo-Planar Imaging, Magnetic Resonance Spectroscopy
- Abstract
Purpose: This work was performed to investigate the effects of tissue microstructure from postmortem rat brain on the shape of the water proton spectrum., Methods: Perfusion-fixed, resected rat brains (N = 4) were imaged at 9.4T. 3D DTI and 3D echo-planar spectroscopic imaging (EPSI) data were acquired with 150 μm isotropic resolution. DTI data were acquired over 60 directions with b = 3000 s/mm
2 . Water spectra were produced from EPSI data acquired over 128 echoes, with 2.9 Hz spectral resolution. A voxel-wise metric reflecting spectral asymmetry about the peak of the resonance was computed and compared with orientation estimates from DTI data by fitting data with the susceptibility anisotropy model., Results: Asymmetric broadening of the water resonance was computed for mixed populations of grey and/or white matter as determined by thresholding the fractional anisotropy. Asymmetry was shown to be differentially affected by tract orientation relative to B0 in high FA voxels, whereas low FA voxels exhibited little sensitivity. Anatomic structures in the hippocampus were also found to produce distinct changes in the water resonance., Conclusion: Present results demonstrate that structural variations in tissue architecture cause characteristic, reproducible changes in the water resonance shape. This suggests that water spectra are sensitive to cytoarchitectural variations in brain tissue., (© 2018 International Society for Magnetic Resonance in Medicine.)- Published
- 2019
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.