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4. Quantitative Multi-Parametric MRI of the Prostate Reveals Racial Differences.

Author

Chatterjee, Aritrick, Fan, Xiaobing, Slear, Jessica, Asare, Gregory, Yousuf, Ambereen N., Medved, Milica, Antic, Tatjana, Eggener, Scott, Karczmar, Gregory S., and Oto, Aytekin

Subjects
REFERENCE values, AFRICAN Americans, RESEARCH funding, PROSTATE tumors, MAGNETIC resonance imaging, WHITE people, CANCER patients, QUANTITATIVE research, TUMOR grading, DESCRIPTIVE statistics, PROSTATE, RACE, EPITHELIUM, HISTOLOGICAL techniques, COMPARATIVE studies
Abstract

Simple Summary: This study investigated whether quantitative MRI and histology of the prostate reveal differences between races that can affect diagnosis. The cancer signal enhancement rate (α) on dynamic contrast-enhanced MRI (DCE-MRI) was significantly higher for African Americans (AAs) compared to Caucasian Americans (CAs). The signal washout rate (β) was significantly lower in benign tissue in AAs and significantly elevated in cancers in AAs. However, no significant differences were found for ADC and T2. The ROC analysis showed that the apparent diffusion coefficient (ADC) and T2 are slightly less effective in AAs compared to CAs. 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 that cancers have a greater proportion of epithelium and lower lumen in AAs compared to CAs. This study shows that the different races have different quantitative MRI values and histologic makeup. Quantitative DCE-MRI is highly effective and improves PCa diagnosis in African Americans. 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. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Implementation of a high-resolution, high-contrast magnetic resonance imaging protocol with extended delayed phases for peritoneal mesothelioma

Author

Medved, Milica, primary, Witmer, Hunter D. D., additional, Dhiman, Ankit, additional, Berger, Yaniv, additional, Sherman, Scott K., additional, Hindi, Enal S., additional, Armato III, Samuel G., additional, Reiser, Ingrid S., additional, Oto, Aytekin, additional, Engelmann, Roger M., additional, Kindler, Hedy L., additional, Oren, Nisa C., additional, Harmath, Carla B., additional, and Turaga, Kiran K., additional

Published
2024
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10. Residual analysis of the water resonance signal in breast lesions imaged with high spectral and spatial resolution (HiSS) MRI: A pilot study

Author

Weiss, William A, Medved, Milica, Karczmar, Gregory S, and Giger, Maryellen L

Subjects
Cancer, Breast Cancer, Bioengineering, Networking and Information Technology R&D (NITRD), Biomedical Imaging, Good Health and Well Being, Breast Neoplasms, Magnetic Resonance Imaging, Pilot Projects, Signal-To-Noise Ratio, Other Physical Sciences, Biomedical Engineering, Oncology and Carcinogenesis, Nuclear Medicine & Medical Imaging
Abstract

PurposeHigh spectral and spatial resolution magnetic resonance imaging (HiSS MRI) yields information on the local environment of suspicious lesions. Previous work has demonstrated the advantages of HiSS (complete fat-suppression, improved image contrast, no required contrast agent, etc.), leading to initial investigations of water resonance lineshape for the purpose of breast lesion classification. The purpose of this study is to investigate a quantitative imaging biomarker, which characterizes non-Lorentzian components of the water resonance in HiSS MRI datasets, for computer-aided diagnosis (CADx).MethodsThe inhomogeneous broadening and non-Lorentzian or "off-peak" components seen in the water resonance of proton spectra of breast HiSS images are analyzed by subtracting a Lorentzian fit from the water peak spectra and evaluating the difference spectrum or "residual." The maxima of these residuals (referred to hereafter as "off-peak components") tend to be larger in magnitude in malignant lesions, indicating increased broadening in malignant lesions. The authors considered only those voxels with the highest magnitude off-peak components in each lesion, with the number of selected voxels dependent on lesion size. Our voxel-based method compared the magnitudes and frequencies of off-peak components of all voxels from all lesions in a database that included 15 malignant and 8 benign lesions (yielding ≈ 3900 voxels) based on the lesions' biopsy-confirmed diagnosis. Lesion classification was accomplished by comparing the average off-peak component magnitudes and frequencies in malignant and benign lesions. The area under the ROC curve (AUC) was used as a figure of merit for both the voxel-based and lesion-based methods.ResultsIn the voxel-based task of distinguishing voxels from malignant and benign lesions, off-peak magnitude yielded an AUC of 0.88 (95% confidence interval [0.84, 0.91]). In the lesion-based task of distinguishing malignant and benign lesions, average off-peak magnitude yielded an AUC 0.83 (95% confidence interval [0.61, 0.98]).ConclusionsThese promising AUC values suggest that analysis of the water-resonance in each HiSS image voxel using "residual analysis" could have high diagnostic utility and could be used to enhance current CADx methods and allow detection of breast cancer without the need to inject contrast agents.

Published
2014

19. Directional and inter‐acquisition variability in diffusion‐weighted imaging and editing for restricted diffusion

Author

Gundogdu, Batuhan, primary, Pittman, Jay M., additional, Chatterjee, Aritrick, additional, Szasz, Teodora, additional, Lee, Grace, additional, Giurcanu, Mihai, additional, Medved, Milica, additional, Engelmann, Roger, additional, Guo, Xiaodong, additional, Yousuf, Ambereen, additional, Antic, Tatjana, additional, Devaraj, Ajit, additional, Fan, Xiaobing, additional, Oto, Aytekin, additional, and Karczmar, Gregory S., additional

Published
2022
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24. Development of a standardized MRI protocol for pancreas assessment in humans

Author

Virostko, John, primary, Craddock, Richard C., additional, Williams, Jonathan M., additional, Triolo, Taylor M., additional, Hilmes, Melissa A., additional, Kang, Hakmook, additional, Du, Liping, additional, Wright, Jordan J., additional, Kinney, Mara, additional, Maki, Jeffrey H., additional, Medved, Milica, additional, Waibel, Michaela, additional, Kay, Thomas W. H., additional, Thomas, Helen E., additional, Greeley, Siri Atma W., additional, Steck, Andrea K., additional, Moore, Daniel J., additional, and Powers, Alvin C., additional

Published
2021
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38. Final analysis of a phase II study of MRI based functional imaging of bone metastases in men with metastatic castrate-resistant prostate cancer (mCRPC) receiving cabozantinib.

Author

Desai, Arpita, primary, Brewer, Jamie Renee, additional, Medved, Milica, additional, Oto, Aytekin, additional, Gao, Guimin, additional, Karrison, Theodore, additional, Shevrin, Daniel H., additional, Karczmar, Greg S., additional, Stadler, Walter Michael, additional, and Szmulewitz, Russell Zelig, additional

Published
2019
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39. Comparison of arterial input functions measured from ultra-fast dynamic contrast enhanced MRI and dynamic contrast enhanced computed tomography in prostate cancer patients

Author

Wang, Shiyang, primary, Lu, Zhengfeng, additional, Fan, Xiaobing, additional, Medved, Milica, additional, Jiang, Xia, additional, Sammet, Steffen, additional, Yousuf, Ambereen, additional, Pineda, Federico, additional, Oto, Aytekin, additional, and Karczmar, Gregory S, additional

Published
2018
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43. Potential of Computer-aided Diagnosis of High Spectral and Spatial (HiSS) MRI in the Classification of Breast Lesions

Author

Bhooshan, Neha, Giger, Maryellen, Medved, Milica, Li, Hui, Wood, Abbie, Yuan, Yading, Lan, Li, Marquez, Angelica, Karczmar, Greg, and Newstead, Gillian

Subjects
Contrast Media, Reproducibility of Results, Bayes Theorem, Breast Neoplasms, Pilot Projects, Magnetic Resonance Imaging, Article, Pattern Recognition, Automated, Liver, ROC Curve, Area Under Curve, Image Interpretation, Computer-Assisted, Image Processing, Computer-Assisted, Humans, Female, Diagnosis, Computer-Assisted, Neural Networks, Computer, Algorithms
Abstract

To compare the performance of computer-aided diagnosis (CADx) analysis of precontrast high spectral and spatial resolution (HiSS) MRI to that of clinical dynamic contrast-enhanced MRI (DCE-MRI) in the diagnostic classification of breast lesions.Thirty-four malignant and seven benign lesions were scanned using two-dimensional (2D) HiSS and clinical 4D DCE-MRI protocols. Lesions were automatically segmented. Morphological features were calculated for HiSS, whereas both morphological and kinetic features were calculated for DCE-MRI. After stepwise feature selection, Bayesian artificial neural networks merged selected features, and receiver operating characteristic (ROC) analysis evaluated the performance with leave-one-lesion-out validation.AUC (area under the ROC curve) values of 0.92 ± 0.06 and 0.90 ± 0.05 were obtained using CADx on HiSS and DCE-MRI, respectively, in the task of classifying benign and malignant lesions. While we failed to show that the higher HiSS performance was significantly better than DCE-MRI, noninferiority testing confirmed that HiSS was not worse than DCE-MRI.CADx of HiSS (without contrast) performed similarly to CADx on clinical DCE-MRI; thus, computerized analysis of HiSS may provide sufficient information for diagnostic classification. The results are clinically important for patients in whom contrast agent is contra-indicated. Even in the limited acquisition mode of 2D single slice HiSS, by using quantitative image analysis to extract characteristics from the HiSS images, similar performance levels were obtained as compared with those from current clinical 4D DCE-MRI. As HiSS acquisitions become possible in 3D, CADx methods can also be applied. Because HiSS and DCE-MRI are based on different contrast mechanisms, the use of the two protocols in combination may increase diagnostic accuracy.

Published
2013

44. Classification of breast lesions pre-contrast injection using water resonance lineshape analysis

Author

Wood, Abbie M., Medved, Milica, Bacchus, Ian D., Al-Hallaq, Hania A., Shimauchi, Akiko, Newstead, Gillian M., Olopade, Olufunmilayo I., Venkataraman, Srirama S., Ivancevic, Marko K., and Karczmar, Greg S.

Subjects
Adult, ROC Curve, Contrast Media, Humans, Water, Breast Neoplasms, Female, Breast, Middle Aged, Magnetic Resonance Imaging, Article, Aged
Abstract

Inhomogeneously broadened, non-Lorentzian water resonances have been observed in small image voxels of breast tissue. The non-Lorentzian components of the water resonance are probably produced by bulk magnetic susceptibility shifts caused by dense, deoxygenated tumor blood vessels (the 'blood oxygenation level-dependent' effect), but can also be produced by other characteristics of local anatomy and physiology, including calcifications and interfaces between different types of tissue. Here, we tested the hypothesis that the detection of non-Lorentzian components of the water resonance with high spectral and spatial resolution (HiSS) MRI allows the classification of breast lesions without the need to inject contrast agent. Eighteen malignant lesions and nine benign lesions were imaged with HiSS MRI at 1.5 T. A new algorithm was developed to detect non-Lorentzian (or off-peak) components of the water resonance. After a Lorentzian fit had been subtracted from the data, the largest peak in the residual spectrum in each voxel was identified as the major off-peak component of the water resonance. The difference in frequency between these off-peak components and the main water peaks, and their amplitudes, were measured in malignant lesions, benign lesions and breast fibroglandular tissue. Off-peak component frequencies were significantly different between malignant and benign lesions (p0.001). Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance of HiSS off-peak component analysis compared with dynamic contrast-enhanced (DCE) MRI parameters. The areas under the ROC curves for the 'DCE rapid uptake fraction', 'DCE washout fraction', 'off-peak component amplitude' and 'off-peak component frequency' were 0.75, 0.83, 0.50 and 0.86, respectively. These results suggest that water resonance lineshape analysis performs well in the classification of breast lesions without contrast injection and could improve the diagnostic accuracy of clinical breast MR examinations. In addition, this approach may provide an alternative to DCE MRI in women who are at risk for adverse reactions to contrast media.

Published
2012

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