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Purpose: MRI is commonly used to aid breast cancer diagnosis and treatment evaluation. For patients with breast cancer, neoadjuvant chemotherapy aims to reduce the tumor size and extent of surgery necessary. The current clinical standard to measure breast tumor response on MRI uses the longest tumor diameter. Radiologists also account for other tissue properties including tumor contrast or pharmacokinetics in their assessment. Accurate longitudinal image registration of breast tissue is critical to properly compare response to treatment at different timepoints., Methods: In this study, a deformable Fast Longitudinal Image Registration (FLIRE) algorithm was optimized for breast tissue. FLIRE was then compared to the publicly available software packages with high accuracy (DRAMMS) and fast runtime (Elastix). Patients included in the study received longitudinal T 1 - weighted MRI without fat saturation at two to six timepoints as part of asymptomatic screening (n = 27) or throughout neoadjuvant chemotherapy treatment (n = 32). T 1 - weighted images were registered to the first timepoint with each algorithm., Results: Alignment and runtime performance were compared using two-way repeated measure ANOVAs (P < 0.05). Across all patients, Pearson's correlation coefficient across the entire image volume was slightly higher with statistical significance and had less variance for FLIRE (0.98 ± 0.01 stdev) compared to DRAMMS (0.97 ± 0.03 stdev) and Elastix (0.95 ± 0.03 stdev). Additionally, FLIRE runtime (10.0 mins) was 9.0 times faster than DRAMMS (89.6 mins) and 1.5 times faster than Elastix (14.5 mins) on a Linux workstation., Conclusion: FLIRE demonstrates promise for time-sensitive clinical applications due to its accuracy, robustness across patients and timepoints, and speed., Competing Interests: Declaration of competing interest Dr. Anders Dale is a Founder of and holds equity in CorTechs Labs, Inc., and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. He receives funding through research grants from GE Healthcare to the University of California San Diego (UCSD). Similarly, Dr. Rebecca Rakow-Penner is a consultant for Human Longevity, Inc. She also receives funding through research grants from GE Healthcare to UCSD.   She also has equity interest in CorTechs Labs and serves on its Scientific Advisory Board. She has stock options in CureMetrix. She is also on the Scientific Advisory board for Imagine Scientific. She reports honoraria from Bayer and consulted for Bayer. Dr. Tyler Seibert reports honoraria from Varian Medical Systems and WebMD; he has an equity interest in CorTechs Labs and serves on its Scientific Advisory Board. He also receives in-kind research support from GE Healthcare through agreements between GE Healthcare and UCSD., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: In breast diffusion-weighted imaging (DWI), distortion and physiologic artifacts affect clinical interpretation. Image quality can be optimized by addressing the effect of phase encoding (PE) direction on these artifacts., Purpose: To compare distortion artifacts in breast DWI acquired with different PE directions and polarities, and to discuss their clinical implications., Study Type: Prospective., Population: Eleven healthy volunteers (median age: 47 years old; range: 22-74 years old) and a breast phantom., Field Strength/sequence: Single-shot echo planar DWI and three-dimensional fast gradient echo sequences at 3 T., Assessment: All DWI data were acquired with left-right, right-left, posterior-anterior, and anterior-posterior PE directions. In phantom data, displacement magnitude was evaluated by comparing the location of landmarks in anatomical and DWI images. Three breast radiologists (5, 17, and 23 years of experience) assessed the presence or absence of physiologic artifacts in volunteers' DWI datasets and indicated their PE-direction preference., Statistical Tests: Analysis of variance with post-hoc tests were used to assess differences in displacement magnitude across DWI datasets and observers. A binomial test and a chi-squared test were used to evaluate if each in vivo DWI dataset had an equal probability (25%) of being preferred by radiologists. Inter-reader agreement was evaluated using Gwet's AC1 agreement coefficient. A P-value <0.05 was considered statistically significant., Results: In the phantom study, median displacement was the significantly largest in posterior-anterior data. While the displacement in the anterior-posterior and left-right data were equivalent (P = 0.545). In the in vivo data, there were no physiological artifacts observed in any dataset, regardless of PE direction. In the reader study, there was a significant preference for the posterior-anterior datasets which were selected 94% of the time. There was good agreement between readers (0.936)., Data Conclusion: This study showed the impact of PE direction on distortion artifacts in breast DWI. In healthy volunteers, the posterior-to-anterior PE direction was preferred by readers., Level of Evidence: 2 TECHNICAL EFFICACY: Stage 1., (© 2024 International Society for Magnetic Resonance in Medicine.)

Purpose: Dynamic contrast-enhanced MRI (DCE) and apparent diffusion coefficient (ADC) are currently used to evaluate treatment response of breast cancer. The purpose of the current study was to evaluate the three-component Restriction Spectrum Imaging model (RSI 3C ), a recent diffusion-weighted MRI (DWI)-based tumor classification method, combined with elastic image registration, to automatically monitor breast tumor size throughout neoadjuvant therapy., Experimental Design: Breast cancer patients ( n= 27) underwent multi-parametric 3T MRI at four time points during treatment. Elastically-registered DWI images were used to generate an automatic RSI 3C response classifier, assessed against manual DCE tumor size measurements and mean ADC values. Predictions of therapy response during treatment and residual tumor post-treatment were assessed using non-pathological complete response (non-pCR) as an endpoint., Results: Ten patients experienced pCR. Prediction of non-pCR using ROC AUC (95% CI) for change in measured tumor size from pre-treatment time point to early-treatment time point was 0.65 (0.38-0.92) for the RSI 3C classifier, 0.64 (0.36-0.91) for DCE, and 0.45 (0.16-0.75) for change in mean ADC. Sensitivity for detection of residual disease post-treatment was 0.71 (0.44-0.90) for the RSI 3C classifier, compared to 0.88 (0.64-0.99) for DCE and 0.76 (0.50-0.93) for ADC. Specificity was 0.90 (0.56-1.00) for the RSI 3C classifier, 0.70 (0.35-0.93) for DCE, and 0.50 (0.19-0.81) for ADC., Conclusion: The automatic RSI 3C classifier with elastic image registration suggested prediction of response to treatment after only three weeks, and showed performance comparable to DCE for assessment of residual tumor post-therapy. RSI 3C may guide clinical decision-making and enable tailored treatment regimens and cost-efficient evaluation of neoadjuvant therapy of breast cancer., Competing Interests: Author AMD is employed and holds equity in CorTechs Labs, Inc., and serves on its Scientific Advisory Board. He is a member of the Scientific Advisory Board of Human Longevity, Inc. Author RRP is a consultant of Human Longevity, Inc. She has equity interest in CorTechs Labs, Inc. and is on their Scientific Advisory Board, Inc. She has equity interest in Curemetrix and is on the Scientific Advisory Board of Imagine Scientific. Author TMS reports honoraria from Varian Medical Systems and WebMD; he has an equity interest in CorTechs Labs, Inc. and serves on its Scientific Advisory Board. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Andreassen, Loubrie, Tong, Fang, Seibert, Wallace, Zare, Ojeda-Fournier, Kuperman, Hahn, Jerome, Bathen, Rodríguez-Soto, Dale and Rakow-Penner.)

Background: To date, the accuracy and variability of diffusion-weighted MRI (DW-MRI) metrics have been reported in a limited number of scanner/protocol/coil combinations., Purpose: To evaluate the reproducibility of DW-MRI estimates across multiple scanners and DW-MRI protocols and to assess the effects of using an 8-channel vs. 16-channel breast coil in a breast phantom., Study Type: Prospective., Phantom: Breast phantom containing tubes of water and differing polyvinylpyrrolidone (PVP) concentrations with apparent diffusion coefficients (ADCs) matching breast tissue., Field Strength/sequence: 3 T (three standard and one wide bore), three DW-MRI single-shot echo planar imaging protocols of varying acquired spatial resolution., Assessment: Accuracy of estimated ADCs was assessed using percent differences (PD) relative to nuclear magnetic resonance spectroscopy-derived reference values. Coefficients of variation (CV) were calculated to determine variation across scanners. CVs based on the median standard deviation (CV M ) were used to evaluate tube-specific dispersion using 8- or 16-channel coils at a single scanner. ADCs of PVP-containing tubes were additionally normalized by the median water tube ADC to account for temperature effects., Statistical Tests: Two-way repeated measures analysis of variance and post hoc tests were used to evaluate differences in ADC, CV, and CV M across scanners and protocols (α = 0.05)., Results: ADCs were within 11% (interquartile range [IQR] 7%) of reference values and significantly improved to 2% (IQR 7%) after normalization to an internal water reference. Normalization significantly reduced interscanner variability of ADC estimates from 7% to 4%. DW-MRI protocol did not affect ADC accuracy; however, the clinical and higher-resolution clinical protocols resulted in the greatest (9%) and least (6%) interscanner variability, respectively. The 8- and 16-channel receive coils yielded similar accuracy (PD: 12% vs. 16%) and precision (CV M : 2.7% vs. 2.9%)., Data Conclusion: Normalization by an internal reference improved interscanner ADC reproducibility. High-resolution protocols yielded comparably accurate and significantly less variable ADCs compared to a clinical standard protocol., Evidence Level: 2 TECHNICAL EFFICACY: Stage 1., (© 2022 International Society for Magnetic Resonance in Medicine. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Purpose To develop a multicompartmental signal model for whole-body diffusion-weighted imaging (DWI) and apply it to study the diffusion properties of normal tissue and metastatic prostate cancer bone lesions in vivo. Materials and Methods This prospective study ( ClinicalTrials.gov : NCT03440554) included 139 men with prostate cancer (mean age, 70 years ± 9 [SD]). Multicompartmental models with two to four tissue compartments were fit to DWI data from whole-body scans to determine optimal compartmental diffusion coefficients. Bayesian information criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness of fit. Diffusion coefficients for the optimal model (having lowest BIC) were used to compute compartmental signal-contribution maps. The signal intensity ratio (SIR) of bone lesions to normal-appearing bone was measured on these signal-contribution maps and on conventional DWI scans and compared using paired t tests (α = .05). Two-sample t tests (α = .05) were used to compare compartmental signal fractions between lesions and normal-appearing bone. Results Lowest BIC was observed from the four-compartment model, with optimal compartmental diffusion coefficients of 0, 1.1 × 10 -3 , 2.8 × 10 -3 , and >3.0 ×10 -2 mm 2 /sec. Fitting residuals from this model were significantly lower than from conventional apparent diffusion coefficient mapping ( P < .001). Bone lesion SIR was significantly higher on signal-contribution maps of model compartments 1 and 2 than on conventional DWI scans ( P < .008). The fraction of signal from compartments 2, 3, and 4 was also significantly different between metastatic bone lesions and normal-appearing bone tissue ( P ≤ .02). Conclusion The four-compartment model best described whole-body diffusion properties. Compartmental signal contributions from this model can be used to examine prostate cancer bone involvement. Keywords: Whole-Body MRI, Diffusion-weighted Imaging, Restriction Spectrum Imaging, Diffusion Signal Model, Bone Metastases, Prostate Cancer Clinical trial registration no. NCT03440554 Supplemental material is available for this article. © RSNA, 2023 See also commentary by Margolis in this issue.

Background: Multiparametric magnetic resonance imaging (mpMRI) improves detection of clinically significant prostate cancer (csPCa), but the subjective Prostate Imaging Reporting and Data System (PI-RADS) system and quantitative apparent diffusion coefficient (ADC) are inconsistent. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted MRI technique that yields a quantitative imaging biomarker for csPCa called the RSI restriction score (RSI rs )., Objective: To evaluate RSI rs for automated patient-level detection of csPCa., Design Setting and Participants: We retrospectively studied all patients ( n  = 151) who underwent 3 T mpMRI and RSI (a 2-min sequence on a clinical scanner) for suspected prostate cancer at University of California San Diego during 2017-2019 and had prostate biopsy within 180 d of MRI., Intervention: We calculated the maximum RSI rs and minimum ADC within the prostate, and obtained PI-RADS v2.1 from medical records., Outcome Measurements and Statistical Analysis: We compared the performance of RSI rs , ADC, and PI-RADS for the detection of csPCa (grade group ≥2) on the best available histopathology (biopsy or prostatectomy) using the area under the curve (AUC) with two-tailed α  = 0.05. We also explored whether the combination of PI-RADS and RSI rs might be superior to PI-RADS alone and performed subset analyses within the peripheral and transition zones., Results and Limitations: AUC values for ADC, RSI rs , and PI-RADS were 0.48 (95% confidence interval: 0.39, 0.58), 0.78 (0.70, 0.85), and 0.77 (0.70, 0.84), respectively. RSI rs and PI-RADS were each superior to ADC for patient-level detection of csPCa ( p  < 0.0001). RSI rs alone was comparable with PI-RADS ( p  = 0.8). The combination of PI-RADS and RSI rs had an AUC of 0.85 (0.78, 0.91) and was superior to either PI-RADS or RSI rs alone ( p  < 0.05). Similar patterns were seen in the peripheral and transition zones., Conclusions: RSI rs is a promising quantitative marker for patient-level csPCa detection, warranting a prospective study., Patient Summary: We evaluated a rapid, advanced prostate magnetic resonance imaging technique called restriction spectrum imaging to see whether it could give an automated score that predicted the presence of clinically significant prostate cancer. The automated score worked about as well as expert radiologists' interpretation. The combination of the radiologists' scores and automated score might be better than either alone., (© 2022 The Authors.)

The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics., Competing Interests: RR-P: Human Longevity Inc: Consultant, Cortech Labs: Stock options, Curemetrix: Stock options, consultant. and GE: research agreement. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Mendez, Fang, Meriwether, Batasin, Loubrie, Rodríguez-Soto and Rakow-Penner.)

One promising approach for mapping CMRO 2 is dual-calibrated functional MRI (dc-fMRI). This method exploits the Fick Principle to combine estimates of CBF from ASL, and OEF derived from BOLD-ASL measurements during arterial O 2 and CO 2 modulations. Multiple gas modulations are required to decouple OEF and deoxyhemoglobin-sensitive blood volume. We propose an alternative single gas calibrated fMRI framework, integrating a model of oxygen transport, that links blood volume and CBF to OEF and creates a mapping between the maximum BOLD signal, CBF and OEF (and CMRO 2 ). Simulations demonstrated the method's viability within physiological ranges of mitochondrial oxygen pressure, P m O 2 , and mean capillary transit time. A dc-fMRI experiment, performed on 20 healthy subjects using O 2 and CO 2 challenges, was used to validate the approach. The validation conveyed expected estimates of model parameters (e.g., low P m O 2 ), with spatially uniform OEF maps (grey matter, GM, OEF spatial standard deviation ≈ 0.13). GM OEF estimates obtained with hypercapnia calibrated fMRI correlated with dc-fMRI (r = 0.65, p = 2·10 -3 ). For 12 subjects, OEF measured with dc-fMRI and the single gas calibration method were correlated with whole-brain OEF derived from phase measures in the superior sagittal sinus (r = 0.58, p = 0.048; r = 0.64, p = 0.025 respectively). Simplified calibrated fMRI using hypercapnia holds promise for clinical application.

Diffusion-weighted MRI (DW-MRI) offers a potential adjunct to dynamic contrast-enhanced MRI to discriminate benign from malignant breast lesions by yielding quantitative information about tissue microstructure. Multi-component modeling of the DW-MRI signal over an extended b -value range (up to 3000 s/mm 2 ) theoretically isolates the slowly diffusing (restricted) water component in tissues. Previously, a three-component restriction spectrum imaging (RSI) model demonstrated the ability to distinguish malignant lesions from healthy breast tissue. We further evaluated the utility of this three-component model to differentiate malignant from benign lesions and healthy tissue in 12 patients with known malignancy and synchronous pathology-proven benign lesions. The signal contributions from three distinct diffusion compartments were measured to generate parametric maps corresponding to diffusivity on a voxel-wise basis. The three-component model discriminated malignant from benign and healthy tissue, particularly using the restricted diffusion C 1 compartment and product of the restricted and intermediate diffusion compartments ( C 1 and C 2 ). However, benign lesions and healthy tissue did not significantly differ in diffusion characteristics. Quantitative discrimination of these three tissue types (malignant, benign, and healthy) in non-pre-defined lesions may enhance the clinical utility of DW-MRI in reducing excessive biopsies and aiding in surveillance and surgical evaluation without repeated exposure to gadolinium contrast.

Patients with obstructive sleep apnea (OSA) are at elevated risk of developing systemic vascular disease and cognitive dysfunction. Here, cerebral oxygen metabolism was assessed in patients with OSA by means of a magnetic resonance-based method involving simultaneous measurements of cerebral blood flow rate and venous oxygen saturation in the superior sagittal sinus for a period of 10 minutes at an effective temporal resolution of 1.3 seconds before, during, and after repeated 24-second breath-holds mimicking spontaneous apneas, yielding, along with pulse oximetry-derived arterial saturation, whole-brain CMRO 2 via Fick's Principle. Enrolled subjects were classified based on their apnea-hypopnea indices into OSA (N = 31) and non-sleep apnea reference subjects (NSA = 21), and further compared with young healthy subjects (YH, N = 10). OSA and NSA subjects were matched for age and body mass index. CMRO 2 was lower in OSA than in the YH group during normal breathing (105.6 ± 14.1 versus 123.7 ± 22.8 μmol O 2 /min/100g, P = 0.01). Further, the fractional change in CMRO 2 in response to a breath-hold challenge was larger in OSA than in the YH group (15.2 ± 9.2 versus 8.5 ± 3.4%, P = 0.04). However, there was no significant difference in CMRO 2 between OSA and NSA subjects. The data suggest altered brain oxygen metabolism in OSA and possibly in NSA as well.

Purpose: Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues., Methods: The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging., Results: A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D 1,3 = 0, D 2,3 = 1.5 × 10 -3 , and D 3,3 = 10.8 × 10 -3 mm 2 /s. The RSI-derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast-to-noise and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent., Conclusion: Breast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues., (© 2021 International Society for Magnetic Resonance in Medicine.)

Diffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy. Whole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T 2 -weighted images were annotated. Changes in distance between DWI- and T 2 -defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T 2 -weighted images of bone metastases after distortion correction were calculated. Distortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p < 10 -20 ). On average (± SD), participants' largest error reduction was 11.8 mm (± 3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI 5.0-7.2); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p < 10 -12 ). These findings support the use of distortion correction techniques to improve localization of bone on DWI., (© 2022. The Author(s).)

Background: Diffusion magnetic resonance imaging (MRI) is integral to detection of prostate cancer (PCa), but conventional apparent diffusion coefficient (ADC) cannot capture the complexity of prostate tissues and tends to yield noisy images that do not distinctly highlight cancer. A four-compartment restriction spectrum imaging (RSI 4 ) model was recently found to optimally characterize pelvic diffusion signals, and the model coefficient for the slowest diffusion compartment, RSI 4 -C 1 , yielded greatest tumor conspicuity., Purpose: To evaluate the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI 4 -C 1 ) as a quantitative voxel-level classifier of PCa., Study Type: Retrospective., Subjects: Forty-six men who underwent an extended MRI acquisition protocol for suspected PCa. Twenty-three men had benign prostates, and the other 23 men had PCa., Field Strength/sequence: A 3 T, multishell diffusion-weighted and axial T2-weighted sequences., Assessment: High-confidence cancer voxels were delineated by expert consensus, using imaging data and biopsy results. The entire prostate was considered benign in patients with no detectable cancer. Diffusion images were used to calculate RSI 4 -C 1 and conventional ADC. Classifier images were also generated., Statistical Tests: Voxel-level discrimination of PCa from benign prostate tissue was assessed via receiver operating characteristic (ROC) curves generated by bootstrapping with patient-level case resampling. RSI 4 -C 1 was compared to conventional ADC for two metrics: area under the ROC curve (AUC) and false-positive rate for a sensitivity of 90% (FPR 90 ). Statistical significance was assessed using bootstrap difference with two-sided α = 0.05., Results: RSI 4 -C 1 outperformed conventional ADC, with greater AUC (mean 0.977 [95% CI: 0.951-0.991] vs. 0.922 [0.878-0.948]) and lower FPR 90 (0.032 [0.009-0.082] vs. 0.201 [0.132-0.290]). These improvements were statistically significant (P < 0.05)., Data Conclusion: RSI 4 -C 1 yielded a quantitative, voxel-level classifier of PCa that was superior to conventional ADC. RSI classifier images with a low false-positive rate might improve PCa detection and facilitate clinical applications like targeted biopsy and treatment planning., Evidence Level: 3 TECHNICAL EFFICACY: Stage 2., (© 2021 International Society for Magnetic Resonance in Medicine.)

Background: Diffusion-weighted (DW) echo-planar imaging (EPI) is prone to geometric distortions due to B 0 inhomogeneities. Both prospective and retrospective approaches have been developed to decrease and correct such distortions., Purpose: The purpose of this work was to evaluate the performance of reduced-field-of-view (FOV) acquisition and retrospective distortion correction methods in decreasing distortion artifacts for breast imaging. Coverage of the axilla in reduced-FOV DW magnetic resonance imaging (MRI) and residual distortion were also assessed., Study Type: Retrospective., Population/phantom: Breast phantom and 169 women (52.4 ± 13.4 years old) undergoing clinical breast MRI., Field Strength/sequence: A 3.0 T/ full- and reduced-FOV DW gradient-echo EPI sequence., Assessment: Performance of reversed polarity gradient (RPG) and FSL topup in correcting breast full- and reduced-FOV EPI data was evaluated using the mutual information (MI) metric between EPI and anatomical images. Two independent breast radiologists determined if coverage on both EPI data sets was adequate to evaluate axillary nodes and identified residual nipple distortion artifacts., Statistical Tests: Two-way repeated-measures analyses of variance and post hoc tests were used to identify differences between EPI modality and distortion correction method. Generalized linear mixed effects models were used to evaluate differences in axillary coverage and residual nipple distortion., Results: In a breast phantom, residual distortions were 0.16 ± 0.07 cm and 0.22 ± 0.13 cm in reduced- and full-FOV EPI with both methods, respectively. In patients, MI significantly increased after distortion correction of full-FOV (11 ± 5% and 18 ± 9%, RPG and topup) and reduced-FOV (8 ± 4% both) EPI data. Axillary nodes were observed in 99% and 69% of the cases in full- and reduced-FOV EPI images. Residual distortion was observed in 93% and 0% of the cases in full- and reduced-FOV images., Data Conclusion: Minimal distortion was achieved with RPG applied to reduced-FOV EPI data. RPG improved distortions for full-FOV images but with more modest improvements and limited correction near the nipple., Evidence Level: 3 TECHNICAL EFFICACY: Stage 1., (© 2021 International Society for Magnetic Resonance in Medicine.)

Purpose: Diffusion-weighted MRI (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between predefined benign and malignant breast lesions. However, how well DW-MRI discriminates cancer from all other breast tissue voxels in a clinical setting is unknown. Here we explore the voxelwise ability to distinguish cancer from healthy breast tissue using signal contributions from the newly developed three-component multi-b-value DW-MRI model., Experimental Design: Patients with pathology-proven breast cancer from two datasets ( n = 81 and n = 25) underwent multi-b-value DW-MRI. The three-component signal contributions C 1 and C 2 and their product, C 1 C 2 , and signal fractions F 1 , F 2 , and F 1 F 2 were compared with the image defined on maximum b-value ( DWI max ), conventional apparent diffusion coefficient ( ADC ), and apparent diffusion kurtosis ( K app ). The ability to discriminate between cancer and healthy breast tissue was assessed by the false-positive rate given a sensitivity of 80% (FPR 80 ) and ROC AUC., Results: Mean FPR 80 for both datasets was 0.016 [95% confidence interval (CI), 0.008-0.024] for C 1 C 2 , 0.136 (95% CI, 0.092-0.180) for C 1 , 0.068 (95% CI, 0.049-0.087) for C 2 , 0.462 (95% CI, 0.425-0.499) for F 1 F 2 , 0.832 (95% CI, 0.797-0.868) for F 1 , 0.176 (95% CI, 0.150-0.203) for F 2 , 0.159 (95% CI, 0.114-0.204) for DWI max , 0.731 (95% CI, 0.692-0.770) for ADC , and 0.684 (95% CI, 0.660-0.709) for K app . Mean ROC AUC for C 1 C 2 was 0.984 (95% CI, 0.977-0.991)., Conclusions: The C 1 C 2 parameter of the three-component model yields a clinically useful discrimination between cancer and healthy breast tissue, superior to other DW-MRI methods and obliviating predefining lesions. This novel DW-MRI method may serve as noncontrast alternative to standard-of-care dynamic contrast-enhanced MRI., (©2020 American Association for Cancer Research.)

Functional MRI (fMRI) can identify active foci in response to stimuli through BOLD signal fluctuations, which represent a complex interplay between blood flow and cerebral metabolic rate of oxygen (CMRO 2 ) changes. Calibrated fMRI can disentangle the underlying contributions, allowing quantification of the CMRO 2 response. Here, whole-brain venous oxygen saturation ( Y v ) was computed alongside ASL-measured CBF and BOLD-weighted data to derive the calibration constant, M , using the proposed Y v -based calibration. Data were collected from 10 subjects at 3T with a three-part interleaved sequence comprising background-suppressed 3D-pCASL, 2D BOLD-weighted, and single-slice dual-echo GRE (to measure Y v via susceptometry-based oximetry) acquisitions while subjects breathed normocapnic/normoxic, hyperoxic, and hypercapnic gases, and during a motor task. M was computed via Y v -based calibration from both hypercapnia and hyperoxia stimulus data, and results were compared to conventional hypercapnia or hyperoxia calibration methods. Mean M in gray matter did not significantly differ between calibration methods, ranging from 8.5 ± 2.8% (conventional hyperoxia calibration) to 11.7 ± 4.5% (Y v -based calibration in response to hyperoxia), with hypercapnia-based M values between ( p  = 0.56). Relative CMRO 2 changes from finger tapping were computed from each M map. CMRO 2 increased by ∼20% in the motor cortex, and good agreement was observed between the conventional and proposed calibration methods.

Obstructive sleep apnea (OSA) is characterized by intermittent obstruction of the airways during sleep. Cerebrovascular reactivity (CVR) is an index of cerebral vessels' ability to respond to a vasoactive stimulus, such as increased CO 2 . We hypothesized that OSA alters CVR, expressed as a breath-hold index (BHI) defined as the rate of change in CBF or BOLD signal during a controlled breath-hold stimulus mimicking spontaneous apneas by being both hypercapnic and hypoxic. In 37 OSA and 23 matched non sleep apnea (NSA) subjects, we obtained high temporal resolution CBF and BOLD MRI data before, during, and between five consecutive BH stimuli of 24 s, each averaged to yield a single BHI value. Greater BHI was observed in OSA relative to NSA as derived from whole-brain CBF (78.6 ± 29.6 vs. 60.0 ± 20.0 mL/min 2 /100 g, P  = 0.010) as well as from flow velocity in the superior sagittal sinus (0.48 ± 0.18 vs. 0.36 ± 0.10 cm/s 2 , P  = 0.014). Similarly, BOLD-based BHI was greater in OSA in whole brain (0.19 ± 0.08 vs. 0.15 ± 0.03%/s, P  = 0.009), gray matter (0.22 ± 0.09 vs. 0.17 ± 0.03%/s, P  = 0.011), and white matter (0.14 ± 0.06 vs. 0.10 ± 0.02%/s, P  = 0.010). The greater CVR is not currently understood but may represent a compensatory mechanism of the brain to maintain oxygen supply during intermittent apneas.

Background The relationship between lumbar spine posture and muscle structure is not well understood. Objectives To investigate the predictive capacity of muscle structure on lumbar spine posture in active-duty Marines. Methods Forty-three Marines were scanned in this cross-sectional study, using an upright magnetic resonance imaging scanner while standing without load and standing, sitting, and prone on elbows with body armor. Cobb, horizontal, and sacral angles were measured. Marines were then scanned while unloaded in supine using a supine magnetic resonance imaging scanner. The imaging protocol consisted of T2 intervertebral disc mapping; high-resolution, anatomical, fat-water separation, and diffusion tensor imaging to quantify disc hydration and muscle volume, fat fraction, and restricted diffusion profiles in the lumbar muscles. A stepwise multiple linear regression model was used to identify physiological measures predictive of lumbar spine posture. Results The multiple regression model demonstrated that fractional anisotropy of the erector spinae was a significant predictor of lumbar posture for 7 of 18 dependent variables measured, and explained 20% to 35% of the variance in each model. Decreased fractional anisotropy of the erector spinae predicted decreased lordosis, lumbosacral extension, and anterior pelvic tilt. Conclusion Fractional anisotropy is inversely related with muscle fiber size, which is associated with the isometric force-generating capacity of a muscle fiber. This suggests that stronger erector spinae muscles predict decreased lordosis, lumbosacral extension, and anterior pelvic tilt in a highly trained population. J Orthop Sports Phys Ther 2018;48(8):613-621. Epub 17 May 2018. doi:10.2519/jospt.2018.7865.

Purpose: To establish a calibration equation to convert human blood T 2 to the full range of oxygen saturation levels (HbO 2 ) and physiologic hematocrit (Hct) values using a T 2 -prepared balanced steady-state free precession sequence (T 2 -SSFP) at 1.5T., Methods: Blood drawn from 10 healthy donors (29.1 ± 3.9 years old) was prepared into samples of varying HbO 2 and Hct (n = 79), and imaged using T 2 -SSFP sequence at 37°C and interrefocusing interval τ 180  = 12 ms. The relationship between blood T 2 , HbO 2 , and Hct was established based on the model R2=R2,plasma+Hct (R2,RBC-R2,plasma)+k·Hct·(1-Hct)·(1-HbO2)2. Measured R 2 and HbO 2 levels were fit by the model yielding values of R2,plasma, R2,RBC, and k. T 2 -SSFP and the established calibration equation were applied to extract HbO 2 at the superior sagittal sinus (SSS) in vivo and were compared with susceptometry-based oximetry., Results: Constants derived from the fit were: k = 74.2 [s -1 ], R2,plasma  = 1.5 [s -1 ], R2,RBC  = 11.6 [s -1 ], the R 2 of the fit was 0.95. Average HbO 2 at the SSS in seven healthy volunteers was 65% ± 7% and 66% ± 7% via T 2 - and susceptometry-based oximetry, respectively. Bland-Altman analysis indicated agreement between the two oximetric methods with no significant bias., Conclusion: The calibration constants presented here should ensure improved accuracy for whole-blood oximetry based on T 2 -SSFP at 1.5T. Magn Reson Med 79:1893-1900, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: To investigate the feasibility of estimating calibration constants (K and T 2o ) in vivo for converting whole-blood T 2 to blood hemoglobin oxygen saturation (HbO 2 ) according to the Luz-Meiboom model, 1/T2=1/T2o+K(1-HbO2)2, where K and T 2o are relaxivity and transverse relaxation time of fully saturated blood, respectively., Methods: A range of HbO 2 values was achieved in the superficial femoral vein with intermittent cuff occlusion in seven healthy adults (four males) to establish a calibration curve between blood T 2 and HbO 2 at 1.5T. HbO 2 was derived via MR susceptometry, a technique previously validated, and the transverse relaxation time was quantified with an optimized T 2 -prepared balanced steady-state free precession pulse sequence. To evaluate the accuracy of the in vivo calibration method, T 2 and HbO 2 were quantified in the superior sagittal sinus in six additional subjects and compared with susceptometry., Results: Two sets of gender-specific calibration constants were derived, one for each gender corresponding to hematocrits of 0.47 ± 0.02 for males and 0.38 ± 0.01 for females, yielding K/T 2o  = 41 Hz/260 ms and 26 Hz/280 ms, respectively. The in vivo calibration returned physiologically plausible superior sagittal sinus SvO 2 values (65 ± 5% HbO 2 ), and there was no significant difference between the results from the two methods (average difference -0.3% HbO 2 )., Conclusion: The results show feasibility of performing in vivo calibration for converting whole-blood T 2 to HbO 2 . The proposed approach bypasses the involved and cumbersome processes associated with in vitro calibration. Magn Reson Med 79:2290-2296, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Low back pain has a 70% higher prevalence in members of the armed forces than in the general population, possibly due to the loads and positions soldiers experience during training and combat. Although the influence of heavy load carriage on standing lumbar spine posture in this population is known, postures in other operationally relevant positions are unknown. Therefore, the purpose of this study was to characterize the effect of simulated military operational positions under relevant loading conditions on global and local lumbar spine postures in active duty male US Marines. Secondary objectives were to evaluate if intervertebral disc degeneration and low back pain affect lumbar spine postures. Magnetic resonance images were acquired on an upright scanner in the following operational positions: Natural standing with no external load, standing with body armor (11.3 kg), sitting with body armor, and prone on elbows with body armor. Custom software was used to measure global lumbar spine posture: Lumbosacral flexion, sacral slope, lordosis, local measures of intervertebral angles, and intervertebral distances. Sitting resulted in decreased lumbar lordosis at all levels of the spine except L1-L2. When subjects were prone on elbows, a significant increase in local lordosis was observed only at L5-S1 compared with all other positions. Marines with disc degeneration (77%) or history of low back pain (72%) had decreased lumbar range of motion and less lumbar extension than healthy Marines. These results indicate that a male Marine's pathology undergoes a stereotypic set of postural changes during functional tasks, which may impair performance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2145-2153, 2017., (© 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.)

Study Design: Repeated measures., Objective: The purpose of this study was to quantify the effect of operationally relevant loads and distributions on lumbar spine (LS) in a group of active-duty Marines., Summary of Background Data: Low-back pain has been associated with heavy load carriage among military personnel. Although there are data describing the LS posture in response to load, the effect of varying load characteristics on LS posture remains unknown., Methods: Magnetic resonance images of Marines (n = 12) were acquired when standing unloaded and when carrying 22, 33, and 45 kg of load distributed both 50% to 50% and 20% to 80% anteriorly and posteriorly. Images were used to measure LS and pelvic postures. Two-way repeated-measures ANOVA and posthoc tests were used to compare LS posture across load magnitudes and distributions (α = 0.05). This project was founded by the US Army Medical Research Acquisition Activity, Award No. W81XWH-13-2-0043, under Work Unit No. 1310., Results: No changes in LS posture were induced when load was evenly distributed. When load was carried in the 20% to 80% distribution lumbosacral flexion increased as a result of sacral anterior rotation and overall reduced lumbar lordosis. This pattern was greater as load was increased between 22 and 33 kg, but did not increase further between 33 and 45 kg. We observed that the inferior LS became uniformly less lordotic, independently of load magnitude. However, the superior LS became progressively more lordotic with increasing load magnitude CONCLUSION.: Postural adaptations were found only when load was carried with a posterior bias, suggesting that load-carriage limits based on postural changes are relevant when loads are nonuniformly distributed. Although the tendency would be to interpret that loads should be carried symmetrically to protect the spine, the relationship between postural changes and injury are not clear. Finally, the operational efficiency of carrying load in this distribution needs to be tested., Level of Evidence: 3.

Vertebral level-dependent, angular, and linear translations of the spine have been measured in 2D and 3D using several imaging methods to quantify postural changes due to loading conditions and tasks. Here, we propose and validate a semiautomated method for measuring lumbar intervertebral angles and translations from upright MRI images using an endplate-based, joint coordinate system (JCS). This method was validated using 3D printed structures, representing intervertebral discs (IVD) at predetermined angles and heights, which were positioned between adjacent cadaveric vertebrae as a gold standard. Excellent agreement between our measurements and the gold standard was found for intervertebral angles in all anatomical planes (ICC > .997) and intervertebral distance measurements (ICC > .949). The proposed endplate-based JCS was compared with the vertebral body-based JCS proposed by the International Society of Biomechanics (ISB) using the 3D printed structures placed between 3 adjacent vertebrae from a cadaver with scoliosis. The endplate-based method was found to have better agreement with angles in the sagittal plane (ICC = 0.985) compared with the vertebral body-based method (ICC = .280). Thus, this method is accurate for measuring 3D intervertebral angles in the healthy and diseased lumbar spine.

Study Design: Feasibility study on the acquisition of lumbar spine kinematic data from upright magnetic resonance images obtained under heavy load carrying conditions., Objective: To characterize the effect of the load on spinal kinematics of active Marines under typical load carrying conditions from a macroscopic and lumbar-level approach in active-duty US Marines., Summary of Background Data: Military personnel carry heavy loads of up to 68 kg depending on duty position and nature of the mission or training; these loads are in excess of the recommended assault loads. Performance and injury associated with load carriage have been studied; however, knowledge of lumbar spine kinematic changes is still not incorporated into training. These data would provide guidance for setting load and duration limits and a tool to investigate the potential contribution of heavy load carrying on lumbar spine pathologies., Methods: Sagittal T2 magnetic resonance images of the lumbar spine were acquired on a 0.6-T upright magnetic resonance imaging scanner for 10 active-duty Marines. Each Marine was scanned without load (UN1), immediately after donning load (LO2), after 45 minutes of standing (LO3) and walking (LO4) with load, and after 45 minutes of side-lying recovery (UN5). Custom-made software was used to measure whole spine angles, intervertebral angles, and regional disc heights (L1-S1). Repeated measurements analysis of variance and post hoc Sidak tests were used to identify significant differences between tasks (α = 0.05)., Results: The position of the spine was significantly (P < 0.0001) more horizontal relative to the external reference frame and lordosis was reduced during all tasks with load. Superior levels became more lordotic, whereas inferior levels became more kyphotic. Heavy load induced lumbar spine flexion and only anterior disc and posterior intervertebral disc height changes were observed. All kinematic variables returned to baseline levels after 45 minutes of side-lying recovery., Conclusion: Superior and inferior lumbar levels showed different kinematic behaviors under heavy load carrying conditions. These findings suggest a postural, lumbar flexion strategy aimed at centralizing a heavy posterior load over the base of support.

Objective: The objectives of this study were to perform a clinical study analyzing bone quality in multidetector computed tomographic images of the femur using bone mineral density (BMD), cortical thickness, and texture algorithms in differentiating osteoporotic fracture and control subjects; to differentiate fracture types., Methods: Femoral head, trochanteric, intertrochanteric, and upper and lower neck were segmented (fracture, n = 30; control, n = 10). Cortical thickness, BMD, and texture analysis were obtained using co-occurrence matrices, Minkowski dimension, and functional and scaling index method., Results: Bone mineral density and cortical thickness performed best in the neck region, and texture measures performed best in the trochanter. Only cortical thickness and texture measures differentiated femoral neck and intertrochanteric fractures., Conclusions: This study demonstrates that differentiation of osteoporotic fracture subjects and controls is achieved with texture measures, cortical thickness, and BMD; however, performance is region specific.