Ghost reduction in echo-planar imaging by joint reconstruction of images and line-to-line delays and phase errors.

PURPOSE: To correct line-to-line delays and phase errors in echo-planar imaging (EPI). THEORY AND METHODS: EPI-trajectory auto-corrected image reconstruction (EPI-TrACR) is an iterative maximum-likelihood technique that exploits data redundancy provided by multiple receive coils between nearby lines of k-space to determine and correct line-to-line trajectory delays and phase errors that cause ghosting artifacts. EPI-TrACR was efficiently implemented using a segmented FFT and was applied to in vivo brain data acquired at 7 T across acceleration (1×-4×) and multishot factors (1-4 shots), and in a time series. RESULTS: EPI-TrACR reduced ghosting across all acceleration factors and multishot factors, compared to conventional calibrated reconstructions and the PAGE method. It also achieved consistently lower ghosting in the time series. Averaged over all cases, EPI-TrACR reduced root-mean-square ghosted signal outside the brain by 27% compared to calibrated reconstruction, and by 40% compared to PAGE. CONCLUSION: EPI-TrACR automatically corrects line-to-line delays and phase errors in multishot, accelerated, and dynamic EPI. While the method benefits from additional calibration data for initialization, it was not a requirement for most reconstructions. Magn Reson Med 79:3114-3121, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Incorporating dixon multi-echo fat water separation for novel quantitative magnetization transfer of the human optic nerve in vivo.

PURPOSE: The optic nerve (ON) represents the sole pathway between the eyes and brain; consequently, diseases of the ON can have dramatic effects on vision. However, quantitative magnetization transfer (qMT) applications in the ON have been limited to ex vivo studies, in part because of the fatty connective tissue that surrounds the ON, confounding the magnetization transfer (MT) experiment. Therefore, the aim of this study was to implement a multi-echo Dixon fat-water separation approach to remove the fat component from MT images. METHODS: MT measurements were taken in a single slice of the ON and frontal lobe using a three-echo Dixon readout, and the water and out-of-phase images were applied to a two-pool model in ON tissue and brain white matter to evaluate the effectiveness of using Dixon fat-water separation to remove fatty tissue from MT images. RESULTS: White matter data showed no significant differences between image types; however, there was a significant increase (p < 0.05) in variation in the out-of-phase images in the ON relative to the water images. CONCLUSIONS: The results of this study demonstrate that Dixon fat-water separation can be robustly used for accurate MT quantification of anatomies susceptible to partial volume effects resulting from fat. Magn Reson Med 77:707-716, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom.

PURPOSE: To evaluate the accuracy and reproducibility of quantitative chemical shift-encoded (CSE) MRI to quantify proton-density fat-fraction (PDFF) in a fat-water phantom across sites, vendors, field strengths, and protocols. METHODS: Six sites (Philips, Siemens, and GE Healthcare) participated in this study. A phantom containing multiple vials with various oil/water suspensions (PDFF:0%-100%) was built, shipped to each site, and scanned at 1.5T and 3T using two CSE protocols per field strength. Confounder-corrected PDFF maps were reconstructed using a common algorithm. To assess accuracy, PDFF bias and linear regression with the known PDFF were calculated. To assess reproducibility, measurements were compared across sites, vendors, field strengths, and protocols using analysis of covariance (ANCOVA), Bland-Altman analysis, and the intraclass correlation coefficient (ICC). RESULTS: PDFF measurements revealed an overall absolute bias (across sites, field strengths, and protocols) of 0.22% (95% confidence interval, 0.07%-0.38%) and R2 > 0.995 relative to the known PDFF at each site, field strength, and protocol, with a slope between 0.96 and 1.02 and an intercept between -0.56% and 1.13%. ANCOVA did not reveal effects of field strength (P = 0.36) or protocol (P = 0.19). There was a significant effect of vendor (F = 25.13, P = 1.07 × 10-10 ) with a bias of -0.37% (Philips) and -1.22% (Siemens) relative to GE Healthcare. The overall ICC was 0.999. CONCLUSION: CSE-based fat quantification is accurate and reproducible across sites, vendors, field strengths, and protocols. Magn Reson Med 77:1516-1524, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Characterizing active and inactive brown adipose tissue in adult humans using PET-CT and MR imaging.

Activated brown adipose tissue (BAT) plays an important role in thermogenesis and whole body metabolism in mammals. Positron emission tomography (PET)-computed tomography (CT) imaging has identified depots of BAT in adult humans, igniting scientific interest. The purpose of this study is to characterize both active and inactive supraclavicular BAT in adults and compare the values to those of subcutaneous white adipose tissue (WAT). We obtained [(18)F]fluorodeoxyglucose ([(18)F]FDG) PET-CT and magnetic resonance imaging (MRI) scans of 25 healthy adults. Unlike [(18)F]FDG PET, which can detect only active BAT, MRI is capable of detecting both active and inactive BAT. The MRI-derived fat signal fraction (FSF) of active BAT was significantly lower than that of inactive BAT (means ± SD; 60.2 ± 7.6 vs. 62.4 ± 6.8%, respectively). This change in tissue morphology was also reflected as a significant increase in Hounsfield units (HU; -69.4 ± 11.5 vs. -74.5 ± 9.7 HU, respectively). Additionally, the CT HU, MRI FSF, and MRI R2* values are significantly different between BAT and WAT, regardless of the activation status of BAT. To the best of our knowledge, this is the first study to quantify PET-CT and MRI FSF measurements and utilize a semiautomated algorithm to identify inactive and active BAT in the same adult subjects. Our findings support the use of these metrics to characterize and distinguish between BAT and WAT and lay the foundation for future MRI analysis with the hope that some day MRI-based delineation of BAT can stand on its own.

Whole-body continuously moving table fat-water MRI with dynamic B0 shimming at 3 Tesla.

PURPOSE: The purpose of this work was to develop a rapid and robust whole-body fat-water MRI (FWMRI) method using a continuously moving table (CMT) with dynamic field corrections at 3 Tesla. METHODS: CMT FWMRI was developed at 3 Tesla with a multiecho golden angle (GA) radial trajectory and dynamic B0 field shimming. Whole-body imaging was performed with 4 echoes and superior-inferior coverage of 1.8 meters without shims in 90 s. 716 axial images were reconstructed with GA profile binning followed by B0 field map generation using fast three-point seeded region growing fat-water separation and slice-specific 0(th) and 1(st) order shim calculation. Slice-specific shims were applied dynamically in a repeated CMT FWMRI scan in the same session. The resulting images were evaluated for field homogeneity improvements and quality of fat-water separation with a whole-image energy optimized algorithm. RESULTS: GA sampling allowed high quality whole-body FWMRI from multiecho CMT data. Dynamic B0 shimming greatly improved field homogeneity in the body and produced high quality water and fat only images as well as fat signal fraction and R2 * relaxivity maps. CONCLUSION: A rapid and robust technique for whole-body fat-water quantification has been developed with CMT MRI with dynamic B0 field correction. Magn Reson Med 76:183-190, 2016. © 2015 Wiley Periodicals, Inc.

Continuously moving table MRI with golden angle radial sampling.

PURPOSE: Continuously moving table (CMT) MRI is a high throughput technique that has multiple applications in whole-body imaging. In this work, CMT MRI based on golden angle (GA, 111.246° azimuthal step) radial sampling is developed at 3 Tesla (T), with the goal of increased flexibility in image reconstruction using arbitrary profile groupings. THEORY AND METHODS: CMT MRI with GA and linear angle (LA) schemes were developed for whole-body imaging at 3T with a table speed of 20 mm/s. Imaging was performed in phantoms and a human volunteer with extended z fields of view of up to 1.8 meters. Four separate LA and a single GA scan were performed to enable slice reconstructions at four different thicknesses. RESULTS: GA CMT MRI produced high image quality in phantoms and humans and allowed complete flexibility in reconstruction of slices with arbitrary slice thickness and position from a single data set. LA CMT MRI was constrained by predetermined parameters, required multiple scans and suffered from stair step artifacts that were not present in GA images. CONCLUSION: GA sampling provides a robust flexible approach to CMT whole-body MRI with the ability to reconstruct slices at arbitrary positions and thicknesses from a single scan.

Prospective real-time head motion correction using inductively coupled wireless NMR probes.

PURPOSE: Head motion continues to be a major source of artifacts and data quality degradation in MRI. The goal of this work was to develop and demonstrate a novel technique for prospective, 6 degrees of freedom (6DOF) rigid body motion estimation and real-time motion correction using inductively coupled wireless nuclear magnetic resonance (NMR) probe markers. METHODS: Three wireless probes that are inductively coupled with the scanner's RF setup serve as fiducials on the subject's head. A 12-ms linear navigator module is interleaved with the imaging sequence for head position estimation, and scan geometry is updated in real time for motion compensation. Flip angle amplification in the markers allows the use of extremely small navigator flip angles (∼1°). A novel algorithm is presented to identify marker positions in the absence of marker specific receive channels. Motion correction is demonstrated in high resolution 2D and 3D gradient recalled echo experiments in a phantom and humans. RESULTS: Significant improvement of image quality is demonstrated in phantoms and human volunteers under different motion conditions. CONCLUSION: A novel real-time 6DOF head motion correction technique based on wireless NMR probes is demonstrated in high resolution imaging at 7 Tesla.

Multi-parametric MRI characterization of healthy human thigh muscles at 3.0 T - relaxation, magnetization transfer, fat/water, and diffusion tensor imaging.

Muscle diseases commonly have clinical presentations of inflammation, fat infiltration, fibrosis, and atrophy. However, the results of existing laboratory tests and clinical presentations are not well correlated. Advanced quantitative MRI techniques may allow the assessment of myo-pathological changes in a sensitive and objective manner. To progress towards this goal, an array of quantitative MRI protocols was implemented for human thigh muscles; their reproducibility was assessed; and the statistical relationships among parameters were determined. These quantitative methods included fat/water imaging, multiple spin-echo T2 imaging (with and without fat signal suppression, FS), selective inversion recovery for T1 and quantitative magnetization transfer (qMT) imaging (with and without FS), and diffusion tensor imaging. Data were acquired at 3.0 T from nine healthy subjects. To assess the repeatability of each method, the subjects were re-imaged an average of 35 days later. Pre-testing lifestyle restrictions were applied to standardize physiological conditions across scans. Strong between-day intra-class correlations were observed in all quantitative indices except for the macromolecular-to-free water pool size ratio (PSR) with FS, a metric derived from qMT data. Two-way analysis of variance revealed no significant between-day differences in the mean values for any parameter estimate. The repeatability was further assessed with Bland-Altman plots, and low repeatability coefficients were obtained for all parameters. Among-muscle differences in the quantitative MRI indices and inter-class correlations among the parameters were identified. There were inverse relationships between fractional anisotropy (FA) and the second eigenvalue, the third eigenvalue, and the standard deviation of the first eigenvector. The FA was positively related to the PSR, while the other diffusion indices were inversely related to the PSR. These findings support the use of these T1 , T2 , fat/water, and DTI protocols for characterizing skeletal muscle using MRI. Moreover, the data support the existence of a common biophysical mechanism, water content, as a source of variation in these parameters.

Canine body composition quantification using 3 tesla fat-water MRI.

PURPOSE: To test the hypothesis that a whole-body fat-water MRI (FWMRI) protocol acquired at 3 Tesla combined with semi-automated image analysis techniques enables precise volume and mass quantification of adipose, lean, and bone tissue depots that agree with static scale mass and scale mass changes in the context of a longitudinal study of large-breed dogs placed on an obesogenic high-fat, high-fructose diet. MATERIALS AND METHODS: Six healthy adult male dogs were scanned twice, at weeks 0 (baseline) and 4, of the dietary regiment. FWMRI-derived volumes of adipose tissue (total, visceral, and subcutaneous), lean tissue, and cortical bone were quantified using a semi-automated approach. Volumes were converted to masses using published tissue densities. RESULTS: FWMRI-derived total mass corresponds with scale mass with a concordance correlation coefficient of 0.931 (95% confidence interval = [0.813, 0.975]), and slope and intercept values of 1.12 and -2.23 kg, respectively. Visceral, subcutaneous and total adipose tissue masses increased significantly from weeks 0 to 4, while neither cortical bone nor lean tissue masses changed significantly. This is evidenced by a mean percent change of 70.2% for visceral, 67.0% for subcutaneous, and 67.1% for total adipose tissue. CONCLUSION: FWMRI can precisely quantify and map body composition with respect to adipose, lean, and bone tissue depots. The described approach provides a valuable tool to examine the role of distinct tissue depots in an established animal model of human metabolic disease.

Quantitative effects of inclusion of fat on muscle diffusion tensor MRI measurements.

PURPOSE: To determine the minimum water percentage in a muscle region of interest that would allow diffusion tensor (DT-) MRI data to reflect the diffusion properties of pure muscle accurately. MATERIALS AND METHODS: Proton density-weighted images with and without fat saturation were obtained at the mid-thigh in four subjects. Co-registered DT-MR images were used to calculate the diffusion tensor's eigenvalues and fractional anisotropy. RESULTS: The eigenvalues transitioned monotonically as a function of water signal percentage from values near to those expected for pure fat to those for pure muscle. Also, the fractional anisotropy transitioned monotonically from 0.50 (fat) to 0.20 (muscle). For water signal percentages >55%, none of the diffusion indices differed significantly from those for regions of >90% muscle. CONCLUSION: Accounting for the T1 and T2 values of muscle and fat and the pulse sequence properties, it is concluded that, as a conservative estimate, regions must contain at least 76% muscle tissue to reflect the diffusion properties of pure muscle accurately.

Statistical comparison of dynamic contrast-enhanced MRI pharmacokinetic models in human breast cancer.

By fitting dynamic contrast-enhanced MRI data to an appropriate pharmacokinetic model, quantitative physiological parameters can be estimated. In this study, we compare four different models by applying four statistical measures to assess their ability to describe dynamic contrast-enhanced MRI data obtained in 28 human breast cancer patient sets: the chi-square test (χ(2)), Durbin-Watson statistic, Akaike information criterion, and Bayesian information criterion. The pharmacokinetic models include the fast exchange limit model with (FXL_v(p)) and without (FXL) a plasma component, and the fast and slow exchange regime models (FXR and SXR, respectively). The results show that the FXL_v(p) and FXR models yielded the smallest χ(2) in 45.64 and 47.53% of the voxels, respectively; they also had the smallest number of voxels showing serial correlation with 0.71 and 2.33%, respectively. The Akaike information criterion indicated that the FXL_v(p) and FXR models were preferred in 42.84 and 46.59% of the voxels, respectively. The Bayesian information criterion also indicated the FXL_v(p) and FXR models were preferred in 39.39 and 45.25% of the voxels, respectively. Thus, these four metrics indicate that the FXL_v(p) and the FXR models provide the most complete statistical description of dynamic contrast-enhanced MRI time courses for the patients selected in this study.

Caloric Restriction and Weight Loss Are Primary Factors in the Early Tissue-Specific Metabolic Changes After Bariatric Surgery.

OBJECTIVE: To evaluate changes in insulin sensitivity, hormone secretion, and hepatic steatosis immediately after caloric restriction, vertical sleeve gastrectomy (VSG), and Roux-en-Y gastric bypass (RYGB). RESEARCH DESIGN AND METHODS: Obese subjects were assessed for 1) insulin sensitivity with hyperinsulinemic-euglycemic clamp with glucose tracer infusion, 2) adipokine concentrations with serum and subcutaneous adipose interstitial fluid sampling, and 3) hepatic fat content with MRI before and 7-10 days after VSG, RYGB, or supervised caloric restriction. RESULTS: Each group exhibited an ∼5% total body weight loss, accompanied by similar improvements in hepatic glucose production and hepatic, skeletal muscle, and adipose tissue insulin sensitivity. Leptin concentrations in plasma and adipose interstitial fluid were equally decreased, and reductions in hepatic fat were similar. CONCLUSIONS: The improvements in insulin sensitivity and adipokine secretion observed early after bariatric surgery are replicated by equivalent caloric restriction and weight loss.

Bedside detection of intracranial midline shift using portable magnetic resonance imaging.

Neuroimaging is crucial for assessing mass effect in brain-injured patients. Transport to an imaging suite, however, is challenging for critically ill patients. We evaluated the use of a low magnetic field, portable MRI (pMRI) for assessing midline shift (MLS). In this observational study, 0.064 T pMRI exams were performed on stroke patients admitted to the neuroscience intensive care unit at Yale New Haven Hospital. Dichotomous (present or absent) and continuous MLS measurements were obtained on pMRI exams and locally available and accessible standard-of-care imaging exams (CT or MRI). We evaluated the agreement between pMRI and standard-of-care measurements. Additionally, we assessed the relationship between pMRI-based MLS and functional outcome (modified Rankin Scale). A total of 102 patients were included in the final study (48 ischemic stroke; 54 intracranial hemorrhage). There was significant concordance between pMRI and standard-of-care measurements (dichotomous, κ = 0.87; continuous, ICC = 0.94). Low-field pMRI identified MLS with a sensitivity of 0.93 and specificity of 0.96. Moreover, pMRI MLS assessments predicted poor clinical outcome at discharge (dichotomous: adjusted OR 7.98, 95% CI 2.07-40.04, p = 0.005; continuous: adjusted OR 1.59, 95% CI 1.11-2.49, p = 0.021). Low-field pMRI may serve as a valuable bedside tool for detecting mass effect.

Development of chemical exchange saturation transfer at 7 T.

Chemical exchange saturation transfer (CEST) MRI is a molecular imaging method that has previously been successful at reporting variations in tissue protein and glycogen contents and pH. We have implemented amide proton transfer (APT), a specific form of chemical exchange saturation transfer imaging, at high field (7 T) and used it to study healthy human subjects and patients with multiple sclerosis. The effects of static field inhomogeneities were mitigated using a water saturation shift referencing method to center each z-spectrum on a voxel-by-voxel basis. Contrary to results obtained at lower fields, APT imaging at 7 T revealed significant contrast between white and gray matters, with a higher APT signal apparent within the white matter. Preliminary studies of multiple sclerosis showed that the APT asymmetry varied with the type of lesion examined. An increase in APT asymmetry relative to healthy tissue was found in some lesions. These results indicate the potential utility of APT at high field as a noninvasive biomarker of white matter pathology, providing complementary information to other MRI methods in current clinical use.

Integration of diffusion-weighted MRI data and a simple mathematical model to predict breast tumor cellularity during neoadjuvant chemotherapy.

Diffusion-weighted magnetic resonance imaging data obtained early in the course of therapy can be used to estimate tumor proliferation rates, and the estimated rates can be used to predict tumor cellularity at the conclusion of therapy. Six patients underwent diffusion-weighted magnetic resonance imaging immediately before, after one cycle, and after all cycles of neoadjuvant chemotherapy. Apparent diffusion coefficient values were calculated for each voxel and for a whole tumor region of interest. Proliferation rates were estimated using the apparent diffusion coefficient data from the first two time points and then used with the logistic model of tumor growth to predict cellularity after therapy. The predicted number of tumor cells was then correlated to the corresponding experimental data. Pearson's correlation coefficient for the region of interest analysis yielded 0.95 (P = 0.004), and, after applying a 3 × 3 mean filter to the apparent diffusion coefficient data, the voxel-by-voxel analysis yielded a Pearson correlation coefficient of 0.70 ± 0.10 (P < 0.05).

Quantitative magnetization transfer imaging in human brain at 3 T via selective inversion recovery.

Quantitative magnetization transfer imaging yields indices describing the interactions between free water protons and immobile, macromolecular protons-including the macromolecular to free pool size ratio (PSR) and the rate of magnetization transfer between pools k(mf) . This study describes the first implementation of the selective inversion recovery quantitative magnetization transfer method on a clinical 3.0-T scanner in human brain in vivo. Selective inversion recovery data were acquired at 16 different inversion times in nine healthy subjects and two patients with relapsing remitting multiple sclerosis. Data were collected using a fast spin-echo readout and reduced repetition time, resulting in an acquisition time of 4 min for a single slice. In healthy subjects, excellent intersubject and intrasubject reproducibilities (assessed via repeated measures) were demonstrated. Furthermore, PSR values in white (mean ± SD = 11.4 ± 1.2%) and gray matter (7.5 ± 0.7%) were consistent with previously reported values, while k(mf) values were approximately 2-fold slower in both white (11 ± 2 s(-1) ) and gray matter (15 ± 6 s(-1) ). In relapsing remitting multiple sclerosis patients, quantitative magnetization transfer indices were sensitive to pathological changes in lesions and in normal appearing white matter.

Motion correction in diffusion-weighted MRI of the breast at 3T.

PURPOSE: To provide a quantitative assessment of motion and distortion correction of diffusion-weighted images (DWIs) of the breast and to evaluate the effects of registration on the mean apparent diffusion coefficient (mADC). MATERIALS AND METHODS: Eight datasets from four patients with breast cancer and eight datasets from six healthy controls were acquired on a 3T scanner. A 3D affine registration was used to align each set of images and principal component analysis was used to assess the results. Variance in tumor ADC measurements, tumor mADC values, and voxel-wise tumor mADC values were compared before and after registration for each patient. RESULTS: Image registration significantly (P = 0.008) improved image alignment for both groups and significantly (P < 0.001) reduced the variance across individual tumor ADC measurements. While misalignment led to potential under- and overestimation of mADC values for individual voxels, average tumor mADC values did not significantly change (P > 0.09) after registration. CONCLUSION: 3D affine registration improved the alignment of DWIs of the breast and reduced the variance between ADC measurements. Although the reduced variance did not significantly change tumor region-of-interest measures of mADC, it may have a significant impact on voxel-based analyses.

Portable, bedside, low-field magnetic resonance imaging for evaluation of intracerebral hemorrhage.

Radiological examination of the brain is a critical determinant of stroke care pathways. Accessible neuroimaging is essential to detect the presence of intracerebral hemorrhage (ICH). Conventional magnetic resonance imaging (MRI) operates at high magnetic field strength (1.5-3 T), which requires an access-controlled environment, rendering MRI often inaccessible. We demonstrate the use of a low-field MRI (0.064 T) for ICH evaluation. Patients were imaged using conventional neuroimaging (non-contrast computerized tomography (CT) or 1.5/3 T MRI) and portable MRI (pMRI) at Yale New Haven Hospital from July 2018 to November 2020. Two board-certified neuroradiologists evaluated a total of 144 pMRI examinations (56 ICH, 48 acute ischemic stroke, 40 healthy controls) and one ICH imaging core lab researcher reviewed the cases of disagreement. Raters correctly detected ICH in 45 of 56 cases (80.4% sensitivity, 95%CI: [0.68-0.90]). Blood-negative cases were correctly identified in 85 of 88 cases (96.6% specificity, 95%CI: [0.90-0.99]). Manually segmented hematoma volumes and ABC/2 estimated volumes on pMRI correlate with conventional imaging volumes (ICC = 0.955, p = 1.69e-30 and ICC = 0.875, p = 1.66e-8, respectively). Hematoma volumes measured on pMRI correlate with NIH stroke scale (NIHSS) and clinical outcome (mRS) at discharge for manual and ABC/2 volumes. Low-field pMRI may be useful in bringing advanced MRI technology to resource-limited settings.

Validation of an algorithm for the nonrigid registration of longitudinal breast MR images using realistic phantoms.

PURPOSE: The authors present a method to validate coregistration of breast magnetic resonance images obtained at multiple time points during the course of treatment. In performing sequential registration of breast images, the effects of patient repositioning, as well as possible changes in tumor shape and volume, must be considered. The authors accomplish this by extending the adaptive bases algorithm (ABA) to include a tumor-volume preserving constraint in the cost function. In this study, the authors evaluate this approach using a novel validation method that simulates not only the bulk deformation associated with breast MR images obtained at different time points, but also the reduction in tumor volume typically observed as a response to neoadjuvant chemotherapy. METHODS: For each of the six patients, high-resolution 3D contrast enhanced T1-weighted images were obtained before treatment, after one cycle of chemotherapy and at the conclusion of chemotherapy. To evaluate the effects of decreasing tumor size during the course of therapy, simulations were run in which the tumor in the original images was contracted by 25%, 50%, 75%, and 95%, respectively. The contracted area was then filled using texture from local healthy appearing tissue. Next, to simulate the post-treatment data, the simulated (i.e., contracted tumor) images were coregistered to the experimentally measured post-treatment images using a surface registration. By comparing the deformations generated by the constrained and unconstrained version of ABA, the authors assessed the accuracy of the registration algorithms. The authors also applied the two algorithms on experimental data to study the tumor volume changes, the value of the constraint, and the smoothness of transformations. RESULTS: For the six patient data sets, the average voxel shift error (mean +/- standard deviation) for the ABA with constraint was 0.45 +/- 0.37, 0.97 +/- 0.83, 1.43 +/- 0.96, and 1.80 +/- 1.17 mm for the 25%, 50%, 75%, and 95% contraction simulations, respectively. In comparison, the average voxel shift error for the unconstrained ABA was 0.46 +/- 0.29, 1.13 +/- 1.17, 2.40 +/- 2.04, and 3.53 +/- 2.89 mm, respectively. These voxel shift errors translate into compression of the tumor volume: The ABA with constraint returned volumetric errors of 2.70 +/- 4.08%, 7.31 +/- 4.52%, 9.28 +/- 5.55%, and 13.19 +/- 6.73% for the 25%, 50%, 75%, and 95% contraction simulations, respectively, whereas the unconstrained ABA returned volumetric errors of 4.00 +/- 4.46%, 9.93 +/- 4.83%, 19.78 +/- 5.657%, and 29.75 +/- 15.18%. The ABA with constraint yields a smaller mean shift error, as well as a smaller volume error (p = 0.031 25 for the 75% and 95% contractions), than the unconstrained ABA for the simulated sets. Visual and quantitative assessments on experimental data also indicate a good performance of the proposed algorithm. CONCLUSIONS: The ABA with constraint can successfully register breast MR images acquired at different time points with reasonable error. To the best of the authors' knowledge, this is the first report of an attempt to quantitatively assess in both phantoms and a set of patients the accuracy of a registration algorithm for this purpose.