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Background T2 mapping is of great interest in abdominal imaging but current methods are limited by low resolution, slice coverage, motion sensitivity, or lengthy acquisitions. Purpose Develop a radial turbo spin-echo technique with refocusing variable flip angles (RADTSE-VFA) for high spatiotemporal T2 mapping and efficient slice coverage within a breath-hold and compare to the constant flip angle counterpart (RADTSE-CFA). Study type Prospective technical efficacy. Subjects Testing performed on agarose phantoms and 12 patients. Focal liver lesion classification tested on malignant (N = 24) and benign (N = 11) lesions. Field strength/sequence 1.5 T/RADTSE-VFA, RADTSE-CFA. Assessment A constrained objective function was used to optimize the refocusing flip angles. Phantom and/or in vivo data were used to assess relative contrast, T2 estimation, specific absorption rate (SAR), and focal liver lesion classification. STATISTICAL TESTS: t-Tests or Mann-Whitney Rank Sum tests were used. Results Phantom data did not show significant differences in mean relative contrast (P = 0.10) and T2 accuracy (P = 0.99) between RADTSE-VFA and RADTSE-CFA. Adding noise caused T2 overestimation predominantly for RADTSE-CFA and low T2 values. In vivo results did not show significant differences in mean spleen-to-liver (P = 0.62) and kidney-to-liver (P = 0.49) relative contrast between RADTSE-VFA and RADTSE-CFA. Mean T2 values were not significantly different between the two techniques for spleen (T2VFA = 109.2 ± 12.3 msec; T2CFA = 110.7 ± 11.1 msec; P = 0.78) and kidney-medulla (T2VFA = 113.0 ± 8.7 msec; T2CFA = 114.0 ± 8.6 msec; P = 0.79). Liver T2 was significantly higher for RADTSE-CFA (T2VFA = 52.6 ± 6.6 msec; T2CFA = 60.4 ± 8.0 msec) consistent with T2 overestimation in the phantom study. Focal liver lesion classification had comparable T2 distributions for RADTSE-VFA and RADTSE-CFA for malignancies (P = 1.0) and benign lesions (P = 0.39). RADTSE-VFA had significantly lower SAR than RADTSE-CFA increasing slice coverage by 1.5. Data conclusion RADTSE-VFA provided noise-robust T2 estimation compared to the constant flip angle counterpart while generating T2-weighted images with comparable contrast. The VFA scheme minimized SAR improving slice efficiency for breath-hold imaging. Level of evidence 2 TECHNICAL EFFICACY STAGE: 1.

A deep learning MR parameter mapping framework which combines accelerated radial data acquisition with a multi-scale residual network (MS-ResNet) for image reconstruction is proposed. The proposed supervised learning strategy uses input image patches from multi-contrast images with radial undersampling artifacts and target image patches from artifact-free multi-contrast images. Subspace filtering is used during pre-processing to denoise input patches. For each anatomy and relaxation parameter, an individual network is trained. in vivo T(1) mapping results are obtained on brain and abdomen datasets and in vivo T(2) mapping results are obtained on brain and knee datasets. Quantitative results for the T(2) mapping of the knee show that MS-ResNet trained using either fully sampled or undersampled data outperforms conventional model-based compressed sensing methods. This is significant because obtaining fully sampled training data is not possible in many applications. in vivo brain and abdomen results for T(1) mapping and in vivo brain results for T(2) mapping demonstrate that MS-ResNet yields contrast-weighted images and parameter maps that are comparable to those achieved by model-based iterative methods while offering two orders of magnitude reduction in reconstruction times. The proposed approach enables recovery of high-quality contrast-weighted images and parameter maps from highly accelerated radial data acquisitions. The rapid image reconstructions enabled by the proposed approach makes it a good candidate for routine clinical use.

BACKGROUND AND PURPOSE: Fast and accurate quantification of globe volumes in the event of an ocular trauma can provide clinicians with valuable diagnostic information. In this work, an automated workflow using a deep learning-based convolutional neural network is proposed for prediction of globe contours and their subsequent volume quantification in CT images of the orbits. MATERIALS AND METHODS: An automated workflow using a deep learning -based convolutional neural network is proposed for prediction of globe contours in CT images of the orbits. The network, 2D Modified Residual UNET (MRes-UNET2D), was trained on axial CT images from 80 subjects with no imaging or clinical findings of globe injuries. The predicted globe contours and volume estimates were compared with manual annotations by experienced observers on 2 different test cohorts. RESULTS: On the first test cohort (n = 18), the average Dice, precision, and recall scores were 0.95, 96%, and 95%, respectively. The average 95% Hausdorff distance was only 1.5 mm, with a 5.3% error in globe volume estimates. No statistically significant differences (P = .72) were observed in the median globe volume estimates from our model and the ground truth. On the second test cohort (n = 9) in which a neuroradiologist and 2 residents independently marked the globe contours, MRes-UNET2D (Dice = 0.95) approached human interobserver variability (Dice = 0.94). We also demonstrated the utility of inter-globe volume difference as a quantitative marker for trauma in 3 subjects with known globe injuries. CONCLUSIONS: We showed that with fast prediction times, we can reliably detect and quantify globe volumes in CT images of the orbits across a variety of acquisition parameters.

PURPOSE: Obesity is a known risk factor for post-menopausal breast cancer and may increase risk for triple negative breast cancer in premenopausal women. Intervention strategies are clearly needed to reduce obesity-associated breast cancer risk. METHODS: We conducted a Phase II double-blind, randomized, placebo-controlled trial of metformin in overweight/obese premenopausal women with components of metabolic syndrome to assess the potential of metformin for primary breast cancer prevention. Eligible participants were randomized to receive metformin (850 mg BID, n = 76) or placebo (n = 75) for 12 months. Outcomes included breast density, assessed by fat/water MRI with change in percent breast density as the primary endpoint, anthropometric measures, and intervention feasibility. RESULTS: Seventy-six percent in the metformin arm and 83% in the placebo arm (p = 0.182) completed the 12-month intervention. Adherence to study agent was high with more than 80% of participants taking ≥80% assigned pills. The most common adverse events reported in the metformin arm were gastrointestinal in nature and subsided over time. Compared to placebo, metformin intervention led to a significant reduction in waist circumference (p

A growing body data indicates that extracranial carotid artery disease can contribute to cognitive impairment. However, there have been mixed reports regarding the benefit of carotid endarterectomy (CEA) as it relates to preserving cognitive function. In this work, diffusion magnetic resonance imaging (dMRI) is used to provide insight into structural brain changes that occur because of significant carotid artery stenosis, as well as changes that occur in response to CEA. The study design was a prospective, non-randomized, controlled study that enrolled patients with asymptomatic carotid stenosis. Fourteen subjects had severe ECAD ≥70% stenosis in at least one carotid artery and were scheduled to undergo surgery). Thirteen had ECAD with

PURPOSE: To develop a fast volumetric T(1) mapping technique. MATERIALS AND METHODS: A stack-of-stars (SOS) Look Locker technique based on the acquisition of undersampled radial data (>30X relative to Nyquist) and an efficient multi-slab excitation scheme is presented. A principal-component based reconstruction is used to reconstruct T(1) maps. Computer simulations were performed to determine the best choice of partitions per slab and degree of undersampling. The technique was validated in phantoms against reference T(1) values measured with a 2D Cartesian inversion-recovery spin-echo technique. The SOS Look Locker technique was tested in brain (n=4) and prostate (n=5). Brain T(1) mapping was carried out with and without k(z) acceleration and results between the two approaches were compared. Prostate T(1) mapping was compared to standard techniques. A reproducibility study was conducted in brain and prostate. Statistical analyses were performed using linear regression and Bland Altman analysis. RESULTS: Phantom T(1) values showed excellent correlations between SOS Look Locker and the inversion-recovery spin-echo reference (r(2)=0.9965; p

BACKGROUND AND PURPOSE: Accurate and reliable detection of white matter hyperintensities and their volume quantification can provide valuable clinical information to assess neurologic disease progression. In this work, a stacked generalization ensemble of orthogonal 3D convolutional neural networks, StackGen-Net, is explored for improving automated detection of white matter hyperintensities in 3D T2-FLAIR images. MATERIALS AND METHODS: Individual convolutional neural networks in StackGen-Net were trained on 2.5D patches from orthogonal reformatting of 3D-FLAIR (n = 21) to yield white matter hyperintensity posteriors. A meta convolutional neural network was trained to learn the functional mapping from orthogonal white matter hyperintensity posteriors to the final white matter hyperintensity prediction. The impact of training data and architecture choices on white matter hyperintensity segmentation performance was systematically evaluated on a test cohort (n = 9). The segmentation performance of StackGen-Net was compared with state-of-the-art convolutional neural network techniques on an independent test cohort from the Alzheimer’s Disease Neuroimaging Initiative-3 (n = 20). RESULTS: StackGen-Net outperformed individual convolutional neural networks in the ensemble and their combination using averaging or majority voting. In a comparison with state-of-the-art white matter hyperintensity segmentation techniques, StackGen-Net achieved a significantly higher Dice score (0.76 [SD, 0.08], F1-lesion (0.74 [SD, 0.13]), and area under precision-recall curve (0.84 [SD, 0.09]), and the lowest absolute volume difference (13.3% [SD, 9.1%]). StackGen-Net performance in Dice scores (median = 0.74) did not significantly differ (P = .22) from interobserver (median = 0.73) variability between 2 experienced neuroradiologists. We found no significant difference (P = .15) in white matter hyperintensity lesion volumes from StackGen-Net predictions and ground truth annotations. CONCLUSIONS: A stacked generalization of convolutional neural networks, utilizing multiplanar lesion information using 2.5D spatial context, greatly improved the segmentation performance of StackGen-Net compared with traditional ensemble techniques and some state-of-the-art deep learning models for 3D-FLAIR.

INTRODUCTION: The ability to assess skeletal muscle adipose tissue is important given the negative clinical implications associated with greater fat infiltration of the muscle. Computed tomography and magnetic resonance imaging (MRI) are highly accurate for measuring appendicular soft tissue and muscle composition, but have limitations. Peripheral quantitative computed tomography (pQCT) is an alternative that investigators find valuable because of its low radiation, fast scan time, and comparatively lower costs. The present investigation sought to assess the accuracy of pQCT-derived estimates of total-, subcutaneous-, skeletal muscle-, intermuscular-, and calculated intramuscular-adipose tissue areas, and muscle density in the mid-thigh of young girls using the gold standard, 3 T MRI, as the criterion. METHODOLOGY: Cross-sectional data were analyzed for 26 healthy girls aged 9 to 12 years. Mid-thigh soft tissue composition was assessed by both pQCT and 3 T MRI. Mean tissue area for corresponding adipose compartments by pQCT and MRI was compared using t-tests, regression analysis, and Bland-Altman plots. Muscle density was regressed on MRI skeletal muscle adipose tissue, intermuscular adipose tissue, and intra-muscular adipose tissue, each expressed as a percentage of total muscle area. RESULTS: Correlations were high between MRI and pQCT for total adipose tissue (r(2)=0.98), subcutaneous adipose tissue (r(2)=0.95), skeletal muscle adipose tissue (r(2)=0.83), and intermuscular adipose tissue (r(2)=0.82), and pQCT muscle density correlated well with both MRI skeletal muscle adipose tissue (r(2)=0.70) and MRI intermuscular adipose tissue (r(2)=0.70). There was a slight, but statistically significant underestimation by pQCT for total and subcutaneous adipose tissue, while no significant difference was observed for skeletal muscle adipose tissue. Both pQCT-estimated intramuscular adipose tissue and muscle density were weakly correlated with MRI-intramuscular adipose tissue. CONCLUSIONS: We conclude that pQCT is a valid measurement technique for estimating all adipose sub-compartments, except for intramuscular adipose tissue, for the mid-thigh region in young/adolescent girls.

Technology and Research Initiative Fund (TRIF) - Improving Health and Arizona Biomedical Research Commission (ABRC) [ADHS14-082996]

BACKGROUND Increased breast density is a significant independent risk factor for breast cancer, and recent studies show that this risk is modifiable. Hence, breast density measures sensitive to small changes are desired. PURPOSE Utilizing fat-water decomposition MRI, we propose an automated, reproducible breast density measurement, which is nonionizing and directly comparable to mammographic density (MD). STUDY TYPE Retrospective study. POPULATION The study included two sample sets of breast cancer patients enrolled in a clinical trial, for concordance analysis with MD (40 patients) and reproducibility analysis (10 patients). FIELD STRENGTH/SEQUENCE The majority of MRI scans (59 scans) were performed with a 1.5T GE Signa scanner using radial IDEAL-GRASE sequence, while the remaining (seven scans) were performed with a 3T Siemens Skyra using 3D Cartesian 6-echo GRE sequence with a similar fat-water separation technique. ASSESSMENT After automated breast segmentation, breast density was calculated using FraGW, a new measure developed to reliably reflect the amount of fibroglandular tissue and total water content in the entire breast. Based on its concordance with MD, FraGW was calibrated to MR-based breast density (MRD) to be comparable to MD. A previous breast density measurement, Fra80-the ratio of breast voxels with

Objective: Tamoxifen (TAM) lowers breast cancer recurrence by 40-50% with evidence of individual variability in responsiveness. A ≥10% decrease in mammography-determined breast density (BD) after 12–18 months of TAM use has been associated with clinical benefit. Early determination of changes in BD may offer a strategy to tailor hormone therapy in non-responders; for responders, it may encourage adherence. Fat-water decomposition MRI (FWD-MRI) is an accurate and fast (< 5 minutes) method for measuring BD without ionizing radiation or contrast agent. Here, we examined whether change in FWD-MRI-derived BD predicts decrease in BD at earlier time points than observable with a 12-month measure of BD. Methods: The study population included a subset of 44 pre- and post-menopausal women receiving TAM for treatment of early-stage breast cancer or prevention who were enrolled in a randomized, placebo-controlled trial of diindolylmethane. Eligibility for this analysis included participants with FWD-MRI scans at baseline, 6 and 12 months. Median time on TAM at baseline was 13 months (IQR, 5–26 months). All MRI images were acquired on a 1.5T GE Signa NV-CV/i scanner. Automated breast segmentation was performed using MATLAB software and validated against manual ROI drawings. MRI-based BD was calculated as the ratio of breast voxels with 2 times the test-retest variability of Fra80 (0.032). McNemar's test was used to test the association between change from baseline to 6 months and change from baseline to 12 months. Results and Discussion: At 12 months, 15 (34%) participants had a decrease in BD, whereas 29 (66%) remained unchanged or increased. Of these 29, 28 also had no decrease at 6 months (specificity = 97%), and 9 of the 15 women who showed a decrease at 12 months had a decrease at 6 months (sensitivity = 60%; McNemar's test, P = 0.06). Conversely, for those women with a measured decrease in BD from baseline to 6 months, 9 of 10 had a measured decrease at 12 months. A study limitation is inclusion of participants on TAM for varying duration as the greatest change in BD likely would have occurred earlier. Ongoing efforts will focus on FWD-MRI for measures of change in BD in patients initiating TAM. Conclusion: Use of the specified cut point would fail to detect a decrease in BD at 12 months in 40% of women. However, a decrease in BD from baseline to 6 months was highly associated with decrease from baseline to 12 months and in some women may be useful as an early biomarker of effect. Ongoing effort is needed to determine the impact of factors such as baseline BD, menopausal status, and time on TAM in misclassification of BD change using the 6-month measure. Acknowledgement: NIH grants CA149417, CA161534.Objective: Tamoxifen (TAM) lowers breast cancer recurrence by 40-50% with evidence of individual variability in responsiveness. A ≥10% decrease in mammography-determined breast density (BD) after 12–18 months of TAM use has been associated with clinical benefit. Early determination of changes in BD may offer a strategy to tailor hormone therapy in non-responders; for responders, it may encourage adherence. Fat-water decomposition MRI (FWD-MRI) is an accurate and fast (< 5 minutes) method for measuring BD without ionizing radiation or contrast agent. Here, we examined whether change in FWD-MRI-derived BD predicts decrease in BD at earlier time points than observable with a 12-month measure of BD. Methods: The study population included a subset of 44 pre- and post-menopausal women receiving TAM for treatment of early-stage breast cancer or prevention who were enrolled in a randomized, placebo-controlled trial of diindolylmethane. Eligibility for this analysis included participants with FWD-MRI scans at baseline, 6 and 12 months. Median time on TAM at baseline was 13 months (IQR, 5–26 months). All MRI images were acquired on a 1.5T GE Signa NV-CV/i scanner. Automated breast segmentation was performed using MATLAB software and validated against manual ROI drawings. MRI-based BD was calculated as the ratio of breast voxels with 2 times the test-retest variability of Fra80 (0.032). McNemar's test was used to test the association between change from baseline to 6 months and change from baseline to 12 months. Results and Discussion: At 12 months, 15 (34%) participants had a decrease in BD, whereas 29 (66%) remained unchanged or increased. Of these 29, 28 also had no decrease at 6 months (specificity = 97%), and 9 of the 15 women who showed a decrease at 12 months had a decrease at 6 months (sensitivity = 60%; McNemar's test, P = 0.06). Conversely, for those women with a measured decrease in BD from baseline to 6 months, 9 of 10 had a measured decrease at 12 months. A study limitation is inclusion of participants on TAM for varying duration as the greatest change in BD likely would have occurred earlier. Ongoing efforts will focus on FWD-MRI for measures of change in BD in patients initiating TAM. Conclusion: Use of the specified cut point would fail to detect a decrease in BD at 12 months in 40% of women. However, a decrease in BD from baseline to 6 months was highly associated with decrease from baseline to 12 months and in some women may be useful as an early biomarker of effect. Ongoing effort is needed to determine the impact of factors such as baseline BD, menopausal status, and time on TAM in misclassification of BD change using the 6-month measure. Acknowledgement: NIH grants CA149417, CA161534. Citation Format: Ding J, Thompson PA, Wertheim BC, Roe DJ, Marron MT, Altbach MI, Galons J-P, Wang F, Thomson CA, Huang C, Stopeck A. Breast density change at 6 months is associated with change at 12 months as measured by fat-water decomposition MRI in women on tamoxifen [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-09-19.

Subspace-constrained reconstruction methods restrict the relaxation signals (of size M) in the scene to a pre-determined subspace (of size K≪M) and allow multi-contrast imaging and parameter mapping from accelerated acquisitions. However, these constraints yield poor image quality at some imaging contrasts, which can impact the parameter mapping performance. Additional regularization such as the use of joint-sparse (JS) or locally-low-rank (LLR) constraints can help improve the recovery of these images but are not sufficient when operating at high acceleration rates. We propose a method, non-local rank 3D (NLR3D), that is built on block matching and transform domain low rank constraints to allow high quality recovery of subspace-coefficient images (SCI) and subsequent multi-contrast imaging and parameter mapping. The performance of NLR3D was evaluated using Monte-Carlo (MC) simulations and compared against the JS and LLR methods. In vivo T 2 mapping results are presented on brain and knee datasets. MC results demonstrate improved bias, variance, and MSE behavior in both the multi-contrast images and parameter maps when compared to the JS and LLR methods. In vivo brain and knee results at moderate and high acceleration rates demonstrate improved recovery of high SNR early TE images as well as parameter maps. No significant difference was found in the T2 values measured in ROIs between the NLR3D reconstructions and the reference images (Wilcoxon signed rank test). The proposed method, NLR3D, enables recovery of high-quality SCI and, consequently, the associated multi-contrast images and parameter maps.

PURPOSE: To design a pulse sequence for efficient 3D T2-weighted imaging and T2 mapping. METHODS: A stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles and a flexible pseudorandom view ordering is proposed for simultaneous T2-weighted imaging and T2 mapping. An analytical framework is introduced for the selection of refocusing flip angles to maximize relative tissue contrast while minimizing T2 estimation errors and maintaining low specific absorption rate. Images at different echo times are generated using a subspace constrained iterative reconstruction algorithm. T2 maps are obtained by modeling the signal evolution using the extended phase graph model. The technique is evaluated using phantoms and demonstrated in vivo for brain, knee, and carotid imaging. RESULTS: Numerical simulations demonstrate an improved point spread function with the proposed pseudorandom view ordering compared to golden angle view ordering. Phantom experiments show that T2 values estimated from the stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles have good concordance with spin echo reference values. In vivo results show the proposed pulse sequence can generate qualitatively comparable T2-weighted images as conventional Cartesian 3D SPACE in addition to simultaneously generating 3D T2 maps. CONCLUSION: The proposed stack-of-stars turbo spin echo pulse sequence with pseudorandom view ordering and variable refocusing flip angles allows high resolution isotropic T2 mapping in clinically acceptable scan times. The optimization framework for the selection of refocusing flip angles improves T2 estimation accuracy while generating T2-weighted contrast comparable to conventional Cartesian imaging.

Background Double inversion recovery (DIR) fast spin-echo (FSE) cardiovascular magnetic resonance (CMR) sequences are used clinically for black-blood T2-weighted imaging. However, these sequences suffer from slice inefficiency due to the non-selective inversion pulses. We propose a multi-band (MB) encoded DIR radial FSE (MB-DIR-RADFSE) technique to simultaneously excite two slices. This sequence has improved signal-to-noise ratio per unit time compared to a single slice excitation. It is also motion robust and enables the reconstruction of high-resolution black-blood T2-weighted images and T2 maps for the excited slices. Methods Hadamard encoded MB pulses were used in MB-DIR-RADFSE to simultaneously excite two slices. A principal component based iterative reconstruction was used to jointly reconstruct black-blood T2-weighted images and T2 maps. Phantom and in vivo experiments were performed to evaluate T2 mapping performance and results were compared to a T2-prepared balanced steady state free precession (bSSFP) method. The inter-segment variability of the T2 maps were assessed using data acquired on healthy subjects. A reproducibility study was performed to evaluate reproducibility of the proposed technique. Results Phantom experiments show that the T2 values estimated from MB-DIR-RADFSE are comparable to the spin-echo based reference, while T2-prepared bSSFP over-estimated T2 values. The relative contrast of the black-blood images from the multi-band scheme was comparable to those from a single slice acquisition. The myocardial segment analysis on 8 healthy subjects indicated a significant difference (p-value

PURPOSE: A new method for streak artifact reduction in radial MRI based on phased array filtering. THEORY: Radial imaging in applications that require large fields-of-view can be susceptible to streaking artifacts due to gradient nonlinearities. Coil removal methods prune the coils contributing the most to streaking artifacts at the expense of signal loss. Phased array beamforming is a form of spatial filtering used to suppress unwanted signals. The proposed method uses interference covariance generated from the streaking artifact samples which are manually extracted with phased array beamforming to suppress streaking in the images. METHODS: The performance of the proposed method was evaluated on abdomen radial fast spin echo images acquired on a 1.5T Siemens scanner and compared with previously proposed methods. RESULTS: Our results demonstrate that the proposed method can effectively suppress streaking artifacts without any noticeable loss in signal levels. Coil removal methods can suppress streaks as well but they may incur significant signal loss due to coil pruning. Quantitative metrics also demonstrate the superiority of the proposed method over earlier methods. CONCLUSION: The use of interference covariance with phased array beamforming can help reduce streaking artifacts.

Purpose Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. Methods A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Results Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Conclusion Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.

BACKGROUND: Increased breast density is a significant independent risk factor for breast cancer, and recent studies show that this risk is modifiable. Hence, breast density measures sensitive to small changes are desired. PURPOSE: Utilizing fat-water decomposition MRI, we propose an automated, reproducible breast density measurement, which is non-ionizing and directly comparable to mammographic density (MD). STUDY TYPE: Retrospective study. POPULATION: The study included two sample sets of breast cancer patients enrolled in a clinical trial, for concordance analysis with MD (40 patients) and reproducibility analysis (10 patients). FIELD STRENGTH/SEQUENCE: The majority of MRI scans (59 scans) were performed on a 1.5T GE Signa scanner using radial IDEAL-GRASE sequence, while the remaining (7 scans) were performed on a 3T Siemens Skyra using 3D Cartesian 6-echo GRE sequence with a similar fat-water separation technique. ASSESSMENT: After automated breast segmentation, breast density was calculated using FraGW, a new measure developed to reliably reflect the amount of fibroglandular tissue and total water content in the entire breast. Based on its concordance with MD, FraGW was calibrated to MR-based breast density (MRD) to be comparable to MD. A previous breast density measurement, Fra80—the ratio of breast voxels with

BACKGROUND: T(1) mapping is often used in some clinical protocols. Existing techniques are limited in slice coverage, and/or spatial-temporal resolution, or require long acquisitions. Here we present a multi-slice inversion-recovery (IR) radial steady-state free precession (radSSFP) pulse sequence combined with a principal component (PC) based reconstruction that overcomes these limitations. PURPOSE: To develop a fast technique for multi-slice high-resolution T(1) mapping. STUDY TYPE: Technical efficacy study done prospectively. PHANTOM/SUBJECTS: IR-radSSFP was tested in phantoms, five healthy volunteers, and four patients with abdominal lesions. FIELD STRENGTH/SEQUENCE: IR-radSSFP was implemented at 3T. ASSESSMENT: Computer simulations were performed to optimize the flip angle for T(1) estimation; testing was done in phantoms using as reference an IR spin-echo pulse sequence. T(1) mapping with IR-radSSFP was also assessed in vivo (brain and abdomen) and T(1) values were compared with literature. T(1) maps were also compared with a radial IR-FLASH technique. STATISTICAL TESTS: A two-tailed t-test was used to compare T(1) values in phantoms. A repeatability study was carried out in vivo using Bland-Altman analysis. RESULTS: Simulations and phantom experiments showed that a flip angle of 20° was optimal for T(1) mapping. When comparing single to multi-slice experiments in phantoms there were no significant differences between the means T(1) values (P = 0.0475). In vivo results show that T(1) maps with spatial resolution as high as 0.69 mm × 0.69 mm × 2.00 mm (brain) and 0.83 mm × 0.83 mm × 3.00 mm (abdomen) can be generated for 84 brain slices in 3 min and 10 abdominal slices in a breath-hold; T(1) values were comparable to those reported in literature. The coefficients of variation from the repeatability study were 1.7% for brain and 2.5–2.7% in the abdomen. DATA CONCLUSION: A multi-slice IR-radSSFP technique combined with a PC-based reconstruction was demonstrated for higher resolution T(1) mapping. This technique is fast, motion-insensitive and yields repeatable T(1) values comparable to those in literature. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1

BACKGROUND AND PURPOSE: TSE-based T2-weighted imaging of the spine has long scan times. This work proposes a fast imaging protocol using variable refocusing flip angles, optimized for blurring and specific absorption rate. MATERIALS AND METHODS: A variable refocusing flip angle echo-train was optimized for the spine to improve the point spread function and minimize the specific absorption rate, yielding images with improved spatial resolution and SNR compared with the constant flip angle sequence. Data were acquired from 51 patients (35 lumbar, 16 whole-spine) using conventional TSE and the proposed sequence, with a single-shot variant for whole-spine. Noninferiority analysis was performed to evaluate the efficiency of the proposed technique. RESULTS: The proposed multishot sequence resulted in a 2× shorter scan time with a >1.5× lower specific absorption rate. The variable flip angle sequence was noninferior to the conventional TSE (P < .025) for all image-quality and clinical criteria except signal-to-noise ratio for the lumbar spine protocol. However, mean image scores for the TSE-variable refocusing flip angle were ≥4.3 for all criteria, and concordance analysis showed high agreement (>90%) with the TSE, indicating clinical equivalence. The single-shot sequence resulted in 4× shorter whole-spine scans, and image scores were ≥4.4 for all criteria, attesting to its clinical utility. CONCLUSIONS: We present a fast T2-weighted spine protocol using variable refocusing flip angles, including a single-shot variant. The sequences have better point spread function behavior than their constant flip angle counterparts and, being faster, should be less sensitive to patient motion, often seen in the longer TSE scans.

PURPOSE: A new reconstruction method for multi-contrast imaging and parameter mapping based on a union of local subspaces constraint is presented. THEORY: Subspace constrained reconstructions use a predetermined subspace to explicitly constrain the relaxation signals. The choice of subspace size [Formula: see text] impacts the approximation error vs noise-amplification tradeoff associated with these methods. A different approach is used in the model consistency constraint (MOCCO) framework to leverage the subspace model to enforce a softer penalty. Our proposed method, MOCCO-LS, augments the MOCCO model with a union of local subspaces (LS) approach. The union of local subspaces model is coupled with spatial support constraints and incorporated into the MOCCO framework to regularize the contrast signals in the scene. METHODS: The performance of the MOCCO-LS method was evaluated in vivo on [Formula: see text] and [Formula: see text] mapping of the human brain and with Monte-Carlo simulations and compared against MOCCO and the explicit subspace constrained models. RESULTS: The results demonstrate a clear improvement in the multi-contrast images and parameter maps. We sweep across the model order space [Formula: see text] to compare the different reconstructions and demonstrate that the reconstructions have different preferential operating points. Experiments on [Formula: see text] mapping show that the proposed method yields substantial improvements in performance even when operating at very high acceleration rates. CONCLUSIONS: The use of a union of local subspace constraints coupled with a sparsity promoting penalty leads to improved reconstruction quality of multi-contrast images and parameter maps.

The four chamber plane is currently underutilized in the right ventricular segmentation community. Four chamber information can be useful to determine ventricular short axis stacks and provide a rough estimate of the right ventricle in short axis stacks. In this study, we develop and test a semi-automated technique for segmenting the right ventricle in four chamber cine cardiac magnetic resonance images. The three techniques that use minimum cost path algorithms were used. The algorithms are: Dijkstra's shortest path algorithm (Dijkstra), an A* algorithm that uses length, curvature and torsion into an active contour model (ALCT), and a variation of polar dynamic programming (PDP). The techniques are evaluated against the expert traces using 175 cardiac images from 7 patients. The evaluation first looks at mutual overlap metrics and then focuses on clinical measures such as fractional area change (FAC). The mean mutual overlap between the physician's traces ranged from 0.85 to 0.88. Using as reference physician 1's landmarks and traces (i.e., comparing the traces from physician 1 to the semi-automated segmentation using physician 1's landmarks), the PDP algorithm has a mean mutual overlap of 0.8970 compared to 0.8912 for ALCT and 0.8879 for Dijkstra. The mean mutual overlap between the BP regions generated by physician 1 and physician 2 landmarks are 0.9674, 0.9605 and 0.9531 for PDP, ALCT and Dijkstra, respectively. The FAC correlation coefficient between the physician's traces ranged from 0.73 to 0.93.

Diindolylmethane (DIM), a bioactive metabolite of indole-3-carbinol found in cruciferous vegetables, has proposed cancer chemoprevention activity in the breast. There is limited evidence of clinically relevant activity of DIM or long-term safety data of its regular use. A randomized, double-blind, placebo-controlled trial was conducted to determine the activity and safety of combined use of BioResponse DIM® (BR-DIM) with tamoxifen. Women prescribed tamoxifen (n = 130) were randomly assigned oral BR-DIM at 150 mg twice daily or placebo, for 12 months. The primary study endpoint was change in urinary 2/16α-hydroxyestrone (2/16α-OHE1) ratio. Changes in 4-hydroxyestrone (4-OHE1), serum estrogens, sex hormone-binding globulin (SHBG), breast density, and tamoxifen metabolites were assessed. Ninety-eight women (51 placebo, 47 DIM) completed intervention; compliance with treatment was >91%. BR-DIM increased the 2/16α-OHE1 ratio (+3.2 [0.8, 8.4]) compared to placebo (−0.7 [−1.7, 0.8], P

Two-thirds of U.S. adult women are overweight or obese. High body mass index (BMI) and adult weight gain are risk factors for a number of chronic diseases, including postmenopausal breast cancer. The higher postmenopausal breast cancer risk in women with elevated BMI is likely to be attributable to related metabolic disturbances including altered circulating sex steroid hormones and adipokines, elevated pro-inflammatory cytokines, and insulin resistance. Metformin is a widely used antidiabetic drug that has demonstrated favorable effects on metabolic disturbances and as such may lead to lower breast cancer risk in obese women. Further, the anti-proliferative effects of metformin suggest it may decrease breast density, an accepted biomarker of breast cancer risk. This is a Phase II randomized, double-blind, placebo-controlled trial of metformin in overweight/obese premenopausal women who have elements of metabolic syndrome. Eligible participants will be randomized to receive metformin 850 mg BID (n = 75) or placebo (n = 75) for 12 months. The primary endpoint is change in breast density, based on magnetic resonance imaging (MRI) acquired fat-water features. Secondary outcomes include changes in serum insulin levels, serum insulin-like growth factor (IGF)-1 to insulin-like growth factor binding protein (IGFBP)-3 ratio, serum IGF-2 levels, serum testosterone levels, serum leptin to adiponectin ratio, body weight, and waist circumference. Exploratory outcomes include changes in metabolomic profiles in plasma and nipple aspirate fluid. Changes in tissue architecture as well as cellular and molecular targets in breast tissue collected in a subgroup of participants will also be explored. The study will evaluate whether metformin can result in favorable changes in breast density, select proteins and hormones, products of body metabolism, and body weight and composition. The study should help determine the potential breast cancer preventive activity of metformin in a growing population at risk for multiple diseases. ClinicalTrials.gov Identifier: NCT02028221 . Registered on January 2, 2014. Grant #: 1R01CA172444-01A1 awarded on Sept 11, 2013.

Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. The current reference standard for diagnosing HF is biopsy followed by pathologist examination; however, this is limited by sampling error and carries a risk of complications. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically in the order of 1 to 5 mm, which approximates the resolution limit of in vivo gadolinium-enhanced magnetic resonance imaging in the delayed phase. We use MRI of formalin-fixed human ex vivo liver samples as phantoms that mimic the textural contrast of in vivo Gd-MRI. We have developed a local texture analysis that is applied to phantom images, and the results are used to train model observers to detect HF. The performance of the observer is assessed with the area-under-the-receiver–operator-characteristic curve (AUROC) as the figure-of-merit. To optimize the MRI pulse sequence, phantoms were scanned with multiple times at a range of flip angles. The flip angle that was associated with the highest AUROC was chosen as optimal for the task of detecting HF.

Purpose To develop an algorithm for fast and accurate T2 estimation from highly undersampled multi-echo spin-echo (MESE) data.

Reliable and fast separation of tissue water and lipid components is desired in many clinical applications to improve the diagnosis of disease. Conventional chemical-shift saturation techniques for suppressing the water or lipid component are problematic due to the presence of static field inhomogeneities (1-4). Chemical shift imaging based on phase sensitive methods has been widely investigated to overcome the problems in lipid-water imaging caused by field inhomogeneities. There have been many approaches, including the two-point method acquiring “in-phase” and “opposed-phase” images originally proposed by Dixon (5) and a refinement with possible phase correction due to field inhomogeneities (6,7). The two-point Dixon method was followed by the three-point Dixon approach with symmetric sampling (e.g., the acquisition of images with phase shifts between lipid and water of −π,0,π; 0,π,2π; or the more general scheme −α,0,α). The three points were used to resolve lipid and water and a field map (8-11). These methods relied on a phase unwrapping algorithm to estimate the field map which in many cases complicated the separation of lipid and water. As an alternative, Xiang et al introduced the use of asymmetric sampling with direct phase encoding to directly separate lipid and water without the need for an initial estimation of the field map (12,13). Another advantage of asymmetric sampling is that the redundancy of symmetrically sampled data is removed yielding a more efficient utilization of the data (13). Recently an iterative algorithm for the decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) was developed (14,15). IDEAL is also based on the asymmetric acquisition and requires at least three images to resolve the lipid and water images and the field map. In IDEAL the field map is calculated in an iterative fashion and does not require a specific algorithm to unwrap the phase. IDEAL has been implemented with FSE, gradient-echo (GRE), and steady-state free precession (SSFP) sequences (14-16) and is reported to yield robust lipid-water imaging for various clinical applications. In these applications the collection of the three phase-shifted echoes is done in separate TR periods. In FSE applications this results in long scan times, which is not adequate for imaging anatomic locations where fast imaging is required. In order to reduce scan time for lipid-water imaging in FSE acquisitions we developed the IDEAL Gradient and Spin Echo method (IDEAL-GRASE) (17) where multiple gradient echoes are collected within each spin-echo period so that the data with different phase-shifts for lipid-water imaging are obtained within the same TR period. The IDEAL-GRASE method was developed for conventional Cartesian data acquisition. The Cartesian IDEAL-GRASE technique was shown to produce comparable separation of lipid and water to IDEAL-FSE in 1/3 of the imaging time. Another method based on the collection of multiple echoes within a spin-echo (SE) period was also recently developed for fast lipid-water imaging by Ma et al (18). The acquisition of data using a radial k-space trajectory offers robustness to motion and flow (19-22). We have shown that radial MRI is a good alternative to Cartesian MRI for T2-weighted imaging where the image quality of the conventional Cartesian-based methods is deteriorated by motion and flow artifacts (22). Moreover, due to the oversampling in the center of k-space a single radial FSE or GRASE k-space data set can be processed to generate high resolution T2 maps (23-26). The T2 information obtained from radial FSE data successfully discriminated benign from malignant liver lesions (22,26). In this work, we describe a radial GRASE technique combined with the IDEAL algorithm (radial IDEAL-GRASE) to achieve time-efficient lipid-water decomposition as well as T2 mapping. The radial IDEAL-GRASE technique is demonstrated in phantoms and in vivo for applications including pelvic, cardiac, and abdominal imaging.

Background The abnormal signal intensity in cardiac T2-weighted images is associated with various pathologies including myocardial edema. However, the assessment of pathologies based on signal intensity is affected by the acquisition parameters and the sensitivities of the receiver coils. T2 mapping has been proposed to overcome limitations of T2-weighted imaging, but most methods are limited in spatial and/or temporal resolution. Here we present and evaluate a double inversion recovery radial fast spin-echo (DIR-RADFSE) technique that yields data with high spatiotemporal resolution for cardiac T2 mapping. Methods DIR-RADFSE data were collected at 1.5 T on phantoms and subjects with echo train length (ETL) = 16, receiver bandwidth (BW) = ±32 kHz, TR = 1RR, matrix size = 256 × 256. Since only 16 views per echo time (TE) are collected, two algorithms designed to reconstruct highly undersampled radial data were used to generate images for 16 time points: the Echo-Sharing (ES) and the CUrve Reconstruction via pca-based Linearization with Indirect Echo compensation (CURLIE) algorithm. T2 maps were generated via least-squares fitting or the Slice-resolved Extended Phase Graph (SEPG) model fitting. The CURLIE-SEPG algorithm accounts for the effect of indirect echoes. The algorithms were compared based on reproducibility, using Bland-Altman analysis on data from 7 healthy volunteers, and T2 accuracy (against a single-echo spin-echo technique) using phantoms. Results Both reconstruction algorithms generated in vivo images with high spatiotemporal resolution and showed good reproducibility. Mean T2 difference between repeated measures and the coefficient of repeatability were 0.58 ms and 2.97 for ES and 0.09 ms and 4.85 for CURLIE-SEPG. In vivo T2 estimates from ES were higher than those from CURLIE-SEPG. In phantoms, CURLIE-SEPG yielded more accurate T2s compared to reference values (error was 7.5-13.9% for ES and 0.6-2.1% for CURLIE-SEPG), consistent with the fact that CURLIE-SEPG compensates for the effects of indirect echoes. The potential of T2 mapping with CURLIE-SEPG is demonstrated in two subjects with known heart disease. Elevated T2 values were observed in areas of suspected pathology. Conclusions DIR-RADFSE yielded TE images with high spatiotemporal resolution. Two algorithms for generating T2 maps from highly undersampled data were evaluated in terms of accuracy and reproducibility. Results showed that CURLIE-SEPG yields T2 estimates that are reproducible and more accurate than ES.

RAD-GRASE is an MRI sequence that combines radial (RAD) k-space scanning with the gradient and spin-echo (GRASE) technique. RAD-GRASE has the advantages of all radial data acquisition methods in that it can reduce motion sensitivity and correct motion-induced data errors, which can be exploited to achieve high-resolution diffusion-weighted imaging (DWI). One can obtain different types of image contrast, including DWI, T(1), T(2), and T(2)*, in RAD-GRASE by controlling the magnetization preparation and sequence timing. Moreover, because there is oversampling of the low spatial frequencies inherent to radial sequences, partial data reconstruction can be used to achieve multiple forms of image contrast from a single acquired data set, and to generate parametric image maps of equilibrium magnetization, T(2), and T(2) (dagger). The RAD-GRASE technique can also be used to achieve fat-suppressed and/or separated fat and water images by choosing the appropriate timing parameters.

Radial MRI sequences are frequently used to obtain images with reduced sensitivity to motion. To decrease imaging time, multiple spin-echo acquisitions can be incorporated into radial sequences. In this case, different radial lines of Fourier data have different TE times and the resulting images can contain streaking artifacts due to T2 decay. The streaking is not only dependent on the T2 of the object and the timing of the data acquisition, but also on the order in which radial lines are collected (view order). The view ordering can easily be controlled to minimize artifacts due to T2 decay as well as motion. Four view-ordering techniques are presented and evaluated for the radial FSE sequence. Magn Reson Med 51:768–774, 2004. © 2004 Wiley-Liss, Inc.

JPEG2000 is the latest international standard for compression of still images. Although the JPEG2000 codec is designed to compress images, we illustrate that it can also be used to compress other signals. As an example, we illustrate how the JPEG2000 codec can be used to compress electrocardiogram (ECG) data. Experiments using the MIT-BIH arrhythmia database illustrate that the proposed approach outperforms many existing ECG compression schemes. The proposed scheme allows the use of existing hardware and software JPEG2000 codecs for ECG compression, and can be especially useful in eliminating the need for specialized hardware development. The desirable characteristics of the JPEG2000 codec, such as precise rate control and progressive quality, are retained in the presented scheme. The goal of this paper is to demonstrate the ECG application as an example. This example can be extended to other signals that exist within the consumer electronics realm.

Dietary supplement use is high among breast cancer survivors. One compound natural to cruciferous vegetables, diindolylmethane (DIM), is among the supplements commonly used. This bioactive compound has significant experimental evidence for bioactivity in breast chemoprevention. Sparse evidence in the form of well-designed human clinical trials exist to test its efficacy or safety. Methods: In this double-blind placebo-controlled study women taking tamoxifen for breast cancer primary or tertiary prevention were randomly assigned to receive 150 mg DIM (BioResponse(BR)-DIM) twice daily or a placebo for a minimum period of 12 months. Primary outcome was change in urinary estrogen metabolites 2-hydroxyestrone and 16α-hydroxyestrone (baseline to 6 weeks, 6 and 12 months). Secondary endpoints included breast density by mammogram and fat:water ratio MRI (baseline to 12 months) and serum estrogens (baseline to 6, 12 months). Safety data were also evaluated, including tamoxifen metabolites. Results: Adherence to study pills was >91% by pill count and urinary DIM metabolite assessment. In participants assigned DIM there was a significant and sustained shift in urinary estrogen metabolism favoring a higher 2-OH:16α-OH ratio; sex hormone binding globulin (SHBG) was also increased. No change in breast density was demonstrated. Safety analysis showed no appreciable differences in adverse events by treatment arm; however, tamoxifen metabolism for the parent compound as well as endoxifen and 4-OH endoxifen were appreciably reduced in women assigned to the DIM arm. Conclusions In this first large study of DIM in the setting of breast cancer chemoprevention, a favorable shift in estrogen metabolism and SHBG was demonstrated. However, the reduction in tamoxifen metabolites raises concern regarding the potential interaction between DIM and tamoxifen, an area in need of continued research. Impact Given the widespread and generally unsupported use of dietary supplementation by breast cancer survivors, these data will help to inform the use of DIM as a dietary supplement for breast cancer patients receiving tamoxifen.

Objective Breast density(BD) is a measure of the distribution of variable tissue types within the breast and higher BD has been shown to positively correlate with breast cancer risk. As such, the accurate measurement of BD has become a priority for risk assessment and for evaluating the effects of prevention strategies aimed at reducing BD. Mammography(MG) is the most common method of BD determination but is limited by the exposure to ionizing radiation, particularly for studies requiring repeated measures. BD derived from fat-water decomposition magnetic resonance imaging(FWMRI-BD) has been proposed as an alternative, safe, and quantitative method for BD. To optimize its use, we developed a new FWMRI-BD that is automated, more accurate and reliable. In this study, we compare our automated method to digital MG and a previous reported algorithm for MRI derived BD. Methods From a completed prevention trial, 42 pre- and post-menopausal patients receiving tamoxifen therapy for early stage breast cancer or as primary chemoprevention were identified. Patients had undergone prior digital MG within 6 months from the date of MRI scan and MG-BD was calculated using a well-established method(Cumulus). MRI scans were performed on a 1.5T GE Signa NV-CV/i scanner using an axial radial IDEAL-GRASE sequence to generate quantitative fat fraction maps of the entire breast. Total acquisition time was < 5 min and automated breast segmentation was applied to all scans. Only the contralateral, unaffected breast was analyzed. Pearson correlation analysis compared BD as measured by MG(range 0-100%) and FWMRI based methods. BD by FWMRI was initially calculated as the ratio of breast voxels with Results Table 1 shows the correlation and reliability analysis results between MG-BD and FWMRI-BD. Both FWMRI-BD measures(Fra80 and FraG+W) were strongly correlated with MG-BD. More importantly, they exhibit superior test-retest reliability(ICC>0.98) compared to MG-BD values from the literature(reported ICC range 0.91-0.95). FraG+W showed improvement over Fra80 in all measures tested including correlation to MG-BD, dynamic range, standard errors and ICC. Table 1. Accuracy and Reliability of the FWMRI-BD measuresFWMRI-BDFra80FraG+WPearson correlation coefficient* with MG-BDR=0.86R=0.94Test-retest reliabilitystandard error0.02300.0134dynamic range0.0902 – 0.65370.0736 – 0.6588standard error/ dynamic range4.1%2.3%ICC [95% confidence interval]0.985 [0.966,0.993]0.990 [0.976,0.995]* All P-values < 1e-10 Conclusion The refined and automated FWMRI-BD that quantifies the entire fibroglandular and water content of the breast(FraG+W) strongly correlates with MG-BD and is more accurate and reliable than previous FWMRI-BD method. Acknowledgement NIH grants CA149417, CA161534. Citation Format: Ding J, Thompson PA, Gao Y, Marron MT, Wertheim BC, Altbach MI, Galons J-P, Roe DJ, Wang F, Maskarinec G, Thomson CA, Stopeck A, Huang C. Accurate and reliable automated breast density measurements with no ionizing radiation using fat-water decomposition MRI [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-02-03.

Rationale and Objectives To develop and test an algorithm that outlines the breast boundaries using information from fat and water magnetic resonance images. Materials and Methods Three algorithms were implemented and tested using registered fat and water magnetic resonance images. Two of the segmentation algorithms are simple extensions of the techniques used for contrast-enhanced images: one algorithm uses clustering and local gradient (CLG) analysis and the other algorithm uses a Hessian-based sheetness filter (HSF). The third segmentation algorithm uses k-means++ and dynamic programming (KDP) for finding the breast pixels. All three algorithms separate the left and right breasts using either a fixed region or a morphological method. The performance is quantified using a mutual overlap (Dice) metric and a pectoral muscle boundary error. The algorithms are evaluated against three manual tracers using 266 breast images from 14 female subjects. Results The KDP algorithm has a mean overlap percentage improvement that is statistically significant relative to the HSF and CLG algorithms. When using a fixed region to remove the tissue between breasts with tracer 1 as a reference, the KDP algorithm has a mean overlap of 0.922 compared to 0.864 (P

Indirect echoes (such as stimulated echoes) are a source of signal contamination in a multi-echo spin-echo T2 quantification, and can lead to T2 overestimation if a conventional exponential T2 decay model is assumed. Recently, nonlinear least square fitting of a slice-resolve extended phase graph (SEPG) signal model has been shown to provide accurate T2 estimates with indirect echo compensation. However, the iterative nonlinear least square fitting is computationally expensive and the T2 map generation time is long. In this work, we present a pattern recognition T2 mapping technique based on the SEPG model that can be performed with a single pre-computed dictionary for any arbitrary echo spacing. Almost identical T2 and B1 maps were obtained from in vivo data using the proposed technique compared to conventional iterative nonlinear least square fitting, while the computation time was reduced by more than 14 fold.

In this work, we describe a method that uses the linear phase acquired during the readout period due to chemical shift to generate individual magnetic resonance (MR) images of chemically shifted species. The method utilizes sets of Fourier (or k-space) data acquired with different directions of the readout gradient and a postprocessing algorithm to generate chemical shift images. The methodology is developed for both Cartesian data acquisition and for radial data acquisition. The method is presented here for two chemically shifted species but it can be extended to more species. In this work, we present the theory, show the results in phantoms and in human images, and discuss the artifacts and signal-to-noise ratio of the images obtained with the technique.

T2 mapping provides a quantitative approach for focal liver lesion characterization. For small lesions, a biexponential model should be used to account for partial volume effects (PVE). However, conventional biexponential fitting suffers from large uncertainty of the fitted parameters when noise is present. The purpose of this work is to develop a more robust method to correct for PVE affecting small lesions.We developed a region of interest-based joint biexponential fitting (JBF) algorithm to estimate the T2 of lesions affected by PVE. JBF takes advantage of the lesion fraction variation among voxels within a region of interest. JBF is compared to conventional approaches using Cramér-Rao lower bound analysis, numerical simulations, phantom, and in vivo data.JBF provides more accurate and precise T2 estimates in the presence of PVE. Furthermore, JBF is less sensitive to region of interest drawing. Phantom and in vivo results show that JBF can be combined with a reconstruction method for highly undersampled data, enabling the characterization of small abdominal lesions from data acquired in a single breath hold.The JBF algorithm provides more accurate and stable T2 estimates for small structures than conventional techniques when PVE is present. It should be particularly useful for the characterization of small abdominal lesions.

A novel MRI method, DIFRAD-FSE (diffusion-weighted radial acquisition of data with fast spin-echo), is demonstrated that enables rapid, high-resolution multi-shot diffusion-weighted MRI without significant artifacts due to motion. Following a diffusion-weighting spin-echo preparation period, multiple radial lines of Fourier data are acquired using spin-echo refocusing. Images can be reconstructed from the radial data set using a magnitude-only filtered back-projection reconstruction algorithm that removes phase errors due to motion. Results from human brain imaging demonstrate the ability of DIFRAD-FSE to acquire multiple radial lines of Fourier data each TR period without significant artifacts due to relaxation and to produce high-resolution diffusion-weighted MRI images without significant artifacts from motion.

Diffuse liver disease is a widespread global healthcare burden, and the abnormal accumulation of lipid and/or iron is common to important disease processes. Developing the improved methods for detecting and quantifying liver lipid and iron is an important clinical need. The inherent risk, invasiveness, and sampling error of liver biopsy have prompted the development of noninvasive imaging methods for lipid and iron assessment. Ultrasonography and computed tomography have the ability to detect diffuse liver disease, but with limited accuracy. The purpose of this review is to describe the current state-of-the-art methods for quantifying liver lipid and iron using magnetic resonance imaging and spectroscopy, including their implementation, benefits, and potential pitfalls. Imaging- and spectroscopy-based methods are naturally suited for lipid and iron quantification. Lipid can be detected and decomposed from the inherent chemical shift between lipid and water signals, whereas iron imparts significant paramagnetic susceptibility to tissue, which accelerates proton relaxation. However, measurements of these biomarkers are confounded by technical and biological effects. Current methods must address these factors to allow a precise correlation between the lipid fraction and iron concentration. Although this correlation becomes increasingly challenging in the presence of combined lipid and iron accumulation, advanced techniques show promise for delineating these quantities through multi-lipid peak analysis, T2 water mapping, and fast single-voxel water-lipid spectroscopy.

To develop an algorithm for fast and accurate T2 estimation from highly undersampled multi-echo spin-echo data.The algorithm combines a model-based reconstruction with a signal decay based on the slice-resolved extended phase graph (SEPG) model with the goal of reconstructing T2 maps from highly undersampled radial multi-echo spin-echo data with indirect echo compensation. To avoid problems associated with the nonlinearity of the SEPG model, principal component decomposition is used to linearize the signal model. The proposed CUrve Reconstruction via principal component-based Linearization with Indirect Echo compensation (CURLIE) algorithm is used to estimate T2 curves from highly undersampled data. T2 maps are obtained by fitting the curves to the SEPG model.Results on phantoms showed T2 biases (1.9% to 18.4%) when indirect echoes are not taken into account. The T2 biases were reduced (3.2%) when the CURLIE reconstruction was performed along with SEPG fitting even for high degrees of undersampling (4% sampled). Experiments in vivo for brain, liver, and heart followed the same trend as the phantoms.The CURLIE reconstruction combined with SEPG fitting enables accurate T2 estimation from highly undersampled multi-echo spin-echo radial data thus, yielding a fast T2 mapping method without errors caused by indirect echoes.

Recently, there has been an increased interest in quantitative MR parameters to improve diagnosis and treatment. Parameter mapping requires multiple images acquired with different timings usually resulting in long acquisition times. While acquisition time can be reduced by acquiring undersampled data, obtaining accurate estimates of parameters from undersampled data is a challenging problem, in particular for structures with high spatial frequency content. In this work, Principal Component Analysis (PCA) is combined with a model-based algorithm to reconstruct maps of selected principal component coefficients from highly undersampled radial MRI data. This novel approach linearizes the cost function of the optimization problem yielding a more accurate and reliable estimation of MR parameter maps. The proposed algorithm - REconstruction of Principal COmponent coefficient Maps (REPCOM) using Compressed Sensing - is demonstrated in phantoms and in vivo and compared to two other algorithms previously developed for undersampled data.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly in use as an investigational biomarker of response in cancer clinical studies. Proper registration of images acquired at different time points is essential for deriving diagnostic information from quantitative pharmacokinetic analysis of these data. Motion artifacts in the presence of time-varying intensity due to contrast enhancement make this registration problem challenging. DCE-MRI of chest and abdominal lesions is typically performed during sequential breath-holds, which introduces misregistration due to inconsistent diaphragm positions and also places constraints on temporal resolution vis-a-vis free-breathing. In this work, we have employed a computer-generated DCE-MRI phantom to compare the performance of two published methods, Progressive Principal Component Registration and Pharmacokinetic Model-Driven Registration, with Sequential Elastic Registration (SER) to register adjacent time-sample images using a published general-purpose elastic registration algorithm. In all three methods, a 3D rigid-body registration scheme with a mutual information similarity measure was used as a preprocessing step. The DCE-MRI phantom images were mathematically deformed to simulate misregistration, which was corrected using the three schemes. All three schemes were comparably successful in registering large regions of interest (ROIs) such as muscle, liver, and spleen. SER was superior in retaining tumor volume and shape, and in registering smaller but important ROIs such as tumor core and tumor rim. The performance of SER on clinical DCE-MRI data sets is also presented.

Although magnetic resonance imaging (MRI) is routinely used in clinical practice, long acquisition times limit its practical utility in many applications. To increase the data acquisition speed of MRI, parallel MRI (pMRI) techniques have recently been proposed. These techniques utilize multi-channel receiver arrays and are based on simultaneous acquisition of data from multiple receiver coils. Recently, a novel framework called Compressed Sensing (CS) was introduced. Since this new framework illustrates how signals can be reconstructed from much fewer samples than suggested by the Nyquist theory, it has the potential to significantly accelerate data acquisition in MRI. This paper illustrates that CS and pMRI techniques can be combined and such joint processing yields results that are superior to those obtained from independent utilization of each technique.

Three-point Dixon techniques achieve good lipid-water separation by estimating the phase due to field inhomogeneities. Recently it was demonstrated that the combination of an iterative algorithm (iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL)) with a fast spin-echo (FSE) three-point Dixon method yielded robust lipid-water decomposition. As an alternative to FSE, the gradient- and spin-echo (GRASE) technique has been developed for efficient data collection. In this work we present a method for lipid-water separation by combining IDEAL with the GRASE technique. An approach to correct for errors in the lipid-water decomposition caused by phase distortions due to the switching of the readout gradient polarities inherent to GRASE is presented. The IDEAL-GRASE technique is demonstrated in phantoms and in vivo for various applications, including pelvic, musculoskeletal, and (breath-hold) cardiac imaging. Magn Reson Med 57:1047–1057, 2007. © 2007 Wiley-Liss, Inc.

Research Objectives and Rationale. Tamoxifen (TAM) use has been shown to reduce breast cancer recurrence with the benefit greater in patients who experience a TAM-associated decrease in percent mammographic density(PMD); findings that support PMD as a biomarker of response to TAM. PMD is a radiographic phenomenon of breast fibroglandular tissue that is associated with breast cancer risk. PMD is inversely associated with body mass index (BMI) and sparse data have shown a weak positive association with the sex hormone levels. Limited data exist evaluating the relationship between TAM, 2OHE1:16 a-OHE1 ratio (concentrations previously hypothesized to be associated with a reduced risk of breast cancer) and PBD. Methods. Using cross-sectional baseline breast density (BD) from an ongoing prevention trial of diindolylmethane (DIM) in 121 women receiving TAM, we evaluated BD in relation to circulating TAM metabolites [TAM, endoxifen, 4-OH TAM, ND TAM], estradiol (E2), sex hormone-binding globulin (SHBG) and urinary 2-OHE1 and 16α-OHE1. PMD was assessed by mammography (n=65; 54%) and also a novel, non-radiative, non-contrast magnetic resonance imaging-derived fat-water ratio (FWR-MRI) as the fat fraction (Fra)50 and 80 (n=53; 44%) developed for repeat BD assessment in short intervals. This is our first report that BD using digitized mammograms is correlated with FWR-MRI-derived measures designated Fra50 and Fra80; Spearman ρ = 0.90 and 0.86, respectively, p < 0.001. Results. As previously demonstrated, BMI was inversely correlated with all measures of BD. No association was shown between TAM and TAM metabolites and BD or urinary 2OHE1. Further, we found no relationship between circulating E2 or SHBG concentrations and BD. In contrast, urinary 2OHE1 levels were positively correlated with BD across all measures of density; 2OHE1 levels were most strongly correlated with BD measured by FW-MRI using Fra80 (Spearman ρFra80=0.483; p=0.001 compared to ρFra50 =0.431; p = 0.004 and ρPD=0.400; p=0.003). A significant, but weaker, correlation was observed for the 2OHE1:16OHE1 ratio and BD (ρ values 0.34-0.38). The magnitude of the relationship between 2OHE1 and BD was similar in pre and post-menopausal women despite lower PBD after menopause. Conclusions. Our results replicate earlier work from Maskarinec et al. wherein excreted 2OHE1 was an independent determinant of BD. These data challenge the hypothesis proposed by Yager and Liehr that higher urinary 2OHE1 to 16OHE1 ratio would be indicative of reduced hormone tumorigenesis. These results suggest a possible comparable binding affinity for the estrogen receptor that may modify endogenous steroid hormones and their effects on BD. Our findings strengthen the arguments favoring a better mechanistic understanding of BD, the biological determinants and their relationship to breast cancer. This is particularly timely given new mandates to provide BD measures to all women undergoing mammography and recent findings that while BD is associated with breast cancer risk high BD is not associated with greater breast cancer mortality. Citation Format: Cynthia A Thomson, Patricia A Thompson, Betsy C Wertheim, Denise Roe, Marilyn T Marron, John-Phillipe Galons, Matthew A Kupinski, Maria I Altbach, Gertraud Maskarinec, Alison Stopeck. 2-Hydroxyestrone is associated with breast density measured by mammography and fat:water ratio magnetic resonance imaging in women taking tamoxifen [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-01-18.

Radially acquired fast spin-echo data can be processed to obtain T2-weighted images and a T2 map from a single k-space data set. The general approach is to use data at a specific TE (or narrow TE range) in the center of k-space and data at other TE values in the outer part of k-space. With this method high-resolution T2-weighted images and T2 maps are obtained in a time efficient manner. The mixing of TE data, however, introduces errors in the T2-weighted images and T2 maps that affect the accuracy of the T2 estimates. In this work, various k-space data processing methods for reconstructing T2-weighted images and T2 maps from a single radial fast spin-echo k-space data set are analyzed in terms of the accuracy of T2 estimates. The analysis is focused on the effect of image artifacts, object dependency, and noise on the T2 estimates. Results are presented in computer-generated phantoms and in vivo.

Radial fast spin-echo (radial-FSE) methods enable multishot diffusion-weighted MRI (DWMRI) to be carried out without significant artifacts due to motion and/or susceptibility and can be used to generate DWMRI images with high spatial resolution. In this work, a novel method that allows isotropic diffusion weighting to be obtained in a single radial k-space data set is presented. This is accomplished by altering the direction of diffusion weighting gradients between groups of TR periods, which yield sets of radial lines that possess diffusion weighting sensitive to motion in different directions. By altering the diffusion weighting directions and controlling the view ordering appropriately within the sequence, an effectively isotropic diffusion-weighted image can be obtained within one radial-FSE scan. The order in which radial lines are acquired can also be controlled to yield data sets without significant artifacts due to motion, T2 decay, and/or diffusion anisotropy. Magn Reson Med 53:1347–1354, 2005. © 2005 Wiley-Liss, Inc.