Self-supervised multicontrast super-resolution for diffusion-weighted prostate MRI.

PURPOSE: This study addresses the challenge of low resolution and signal-to-noise ratio (SNR) in diffusion-weighted images (DWI), which are pivotal for cancer detection. Traditional methods increase SNR at high b-values through multiple acquisitions, but this results in diminished image resolution due to motion-induced variations. Our research aims to enhance spatial resolution by exploiting the global structure within multicontrast DWI scans and millimetric motion between acquisitions. METHODS: We introduce a novel approach employing a "Perturbation Network" to learn subvoxel-size motions between scans, trained jointly with an implicit neural representation (INR) network. INR encodes the DWI as a continuous volumetric function, treating voxel intensities of low-resolution acquisitions as discrete samples. By evaluating this function with a finer grid, our model predicts higher-resolution signal intensities for intermediate voxel locations. The Perturbation Network's motion-correction efficacy was validated through experiments on biological phantoms and in vivo prostate scans. RESULTS: Quantitative analyses revealed significantly higher structural similarity measures of super-resolution images to ground truth high-resolution images compared to high-order interpolation (p < $$ < $$ 0.005). In blind qualitative experiments, 96 . 1 % $$ 96.1\% $$ of super-resolution images were assessed to have superior diagnostic quality compared to interpolated images. CONCLUSION: High-resolution details in DWI can be obtained without the need for high-resolution training data. One notable advantage of the proposed method is that it does not require a super-resolution training set. This is important in clinical practice because the proposed method can easily be adapted to images with different scanner settings or body parts, whereas the supervised methods do not offer such an option.

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

PURPOSE: To evaluate and quantify inter-directional and inter-acquisition variation in diffusion-weighted imaging (DWI) and emphasize signals that report restricted diffusion to enhance cancer conspicuity, while reducing the effects of local microscopic motion and magnetic field fluctuations. METHODS: Ten patients with biopsy-proven prostate cancer were studied under an Institutional Review Board-approved protocol. Individual acquisitions of DWI signal intensities were reconstructed to calculate inter-acquisition distributions and their statistics, which were compared for healthy versus cancer tissue. A method was proposed to detect and filter the acquisitions affected by motion-induced signal loss. First, signals that reflect restricted diffusion were separated from the acquisitions that suffer from signal loss, likely due to microscopic motion, by imposing a cutoff value. Furthermore, corrected apparent diffusion coefficient maps were calculated by employing a weighted sum of the multiple acquisitions, instead of conventional averaging. These weights were calculated by applying a soft-max function to the set of acquisitions per-voxel, making the analysis immune to acquisitions with significant signal loss, even if the number of such acquisitions is high. RESULTS: Inter-acquisition variation is much larger than the Rician noise variance, local spatial variations, and the estimates of diffusion anisotropy based on the current data, as well as the published values of anisotropy. The proposed method increases the contrast for cancers and yields a sensitivity of 98 . 8 % $$ 98.8\% $$ with a false positive rate of 3 . 9 % $$ 3.9\% $$ . CONCLUSION: Motion-induced signal loss makes conventional signal-averaging suboptimal and can obscure signals from areas with restricted diffusion. Filtering or weighting individual acquisitions prior to image analysis can overcome this problem.

Safely reducing unnecessary benign breast biopsies by applying non-mass and DWI directional variance filters to ADC thresholding.

BACKGROUND: Thresholding apparent diffusion coefficient (ADC) maps obtained from Diffusion-Weighted-Imaging (DWI) has been proposed for identifying benign lesions that can safely avoid biopsy. The presence of malignancies with high ADC values leads to high thresholds, limiting numbers of avoidable biopsies. PURPOSE: We evaluate two previously reported methods for identifying avoidable biopsies: using case-set dependent ADC thresholds that assure 100% sensitivity and using negative likelihood ratio (LR-) with a fixed ADC threshold of 1.50 × 10-3 mm2/s. We evaluated improvements in efficacy obtained by excluding non-mass lesions and lesions with anisotropic intra-lesion morphologic characteristics. STUDY TYPE: Prospective. POPULATION: 55 adult females with dense breasts with 69 BI-RADS 4 or 5 lesions (38 malignant, 31 benign) identified on ultrasound and mammography and imaged with MRI prior to biopsy. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T. DWI. ASSESSMENT: Analysis of DWI, including directional images was done on an ROI basis. ROIs were drawn on DWI images acquired prior to biopsy, referencing all available images including DCE, and mean ADC was measured. Anisotropy was quantified via variation in ADC values in the lesion core across directional DWI images. STATISTICAL TESTS: Improvement in specificity at 100% sensitivity was evaluated with exact McNemar test with 1-sided p-value < 0.05 indicating statistical significance. RESULTS: Using ADC thresholding that assures 100% sensitivity, non-mass and directional variance filtering improved the percent of avoidable biopsies to 42% from baseline of 10% achieved with ADC thresholding alone. Using LR-, filtering improved outcome to 0.06 from baseline 0.25 with ADC thresholding alone. ADC thresholding showed a lower percentage of avoidable biopsies in our cohort than reported in prior studies. When ADC thresholding was supplemented with filtering, the percentage of avoidable biopsies exceeded those of prior studies. DATA CONCLUSION: Supplementing ADC thresholding with filters excluding non-mass lesions and lesions with anisotropic characteristics on DWI can result in an increased number of avoidable biopsies.

High spectral and spatial resolution MRI of prostate cancer: a pilot study.

PURPOSE: High spectral and spatial resolution (HiSS) MRI is a spectroscopic imaging method focusing on water and fat resonances that has good diagnostic utility in breast imaging. The purpose of this work was to assess the feasibility and potential utility of HiSS MRI for the diagnosis of prostate cancer. METHODS: HiSS MRI was acquired at 3 T from six patients who underwent prostatectomy, yielding a train of 127 phase-coherent gradient echo (GRE) images. In the temporal domain, changes in voxel intensity were analyzed and linear (R) and quadratic (R1, R2) quantifiers of signal logarithm decay were calculated. In the spectral domain, three signal scaling-independent parameters were calculated: water resonance peak width (PW), relative peak asymmetry (PRA), and relative peak distortion from ideal Lorentzian shape (PRD). Seven cancer and five normal tissue regions of interest were identified in correlation with pathology and compared. RESULTS: HiSS-derived quantifiers, except R2, showed high reproducibility (coefficients of variation, 5%-14%). Spectral domain quantifiers performed better than temporal domain quantifiers, with receiver operator characteristic areas under the curve ranging from of 0.83 to 0.91. For temporal domain parameters, the range was 0.74 to 0.91. Low absolute values of the coefficients of correlation between monoexponential decay markers (R, PW) and resonance shape markers (PRA, PRD) were observed (range, 0.23-0.38). CONCLUSION: The feasibility and potential diagnostic utility of HiSS MRI in the prostate at 3 T without an endorectal coil was confirmed. Weak correlation between well-performing markers indicates that complementary information could be leveraged to further improve diagnostic accuracy.

T2*-weighted MRI as a non-contrast-enhanced method for assessment of focal laser ablation zone extent in prostate cancer thermotherapy.

OBJECTIVES: To evaluate utility of T2*-weighted (T2*W) MRI as a tool for intra-operative identification of ablation zone extent during focal laser ablation (FLA) of prostate cancer (PCa), as compared to the current standard of contrast-enhanced T1-weighted (T1W) MRI. METHODS: Fourteen patients with biopsy-confirmed low- to intermediate-risk localized PCa received MRI-guided (1.5 T) FLA thermotherapy. Following FLA, axial multiple-TE T2*W images, diffusion-weighted images (DWI), and T2-weighted (T2W) images were acquired. Pre- and post-contrast T1W images were also acquired to assess ablation zone (n = 14) extent, as reference standard. Apparent diffusion coefficient (ADC) maps and subtracted contrast-enhanced T1W (sceT1W) images were calculated. Ablation zone regions of interest (ROIs) were outlined manually on all ablated slices. The contrast-to-noise ratio (CBR) of the ablation site ROI relative to the untreated contralateral prostate tissue was calculated on T2*W images and ADC maps and compared to that in sceT1W images. RESULTS: CBRs in ablation ROIs on T2*W images (TE = 32, 63 ms) did not differ (p = 0.33, 0.25) from those in sceT1W images. Bland-Altman plots of ROI size and CBR in ablation sites showed good agreement between T2*W (TE = 32, 63 ms) and sceT1W images, with ROI sizes on T2*W (TE = 63 ms) strongly correlated (r = 0.64, p = 0.013) and within 15% of those in sceT1W images. CONCLUSIONS: In detected ablation zone ROI size and CBR, non-contrast-enhanced T2*W MRI is comparable to contrast-enhanced T1W MRI, presenting as a potential method for intra-procedural monitoring of FLA for PCa. KEY POINTS: • T2*-weighted MR images with long TE visualize post-procedure focal laser ablation zone comparably to the contrast-enhanced T1-weighted MRI. • T2*-weighted MRI could be used as a plausible method for repeated intra-operative monitoring of thermal ablation zone in prostate cancer, avoiding potential toxicity due to heating of contrast agent.

Discrimination of benign from malignant breast lesions in dense breasts with model-based analysis of regions-of-interest using directional diffusion-weighted images.

BACKGROUND: There is an increasing interest in non-contrast-enhanced magnetic resonance imaging (MRI) for detecting and evaluating breast lesions. We present a methodology utilizing lesion core and periphery region of interest (ROI) features derived from directional diffusion-weighted imaging (DWI) data to evaluate performance in discriminating benign from malignant lesions in dense breasts. METHODS: We accrued 55 dense-breast cases with 69 lesions (31 benign; 38 cancer) at a single institution in a prospective study; cases with ROIs exceeding 7.50 cm2 were excluded, resulting in analysis of 50 cases with 63 lesions (29 benign, 34 cancers). Spin-echo echo-planar imaging DWI was acquired at 1.5 T and 3 T. Data from three diffusion encoding gradient directions were exported and processed independently. Lesion ROIs were hand-drawn on DWI images by two radiologists. A region growing algorithm generated 3D lesion models on augmented apparent-diffusion coefficient (ADC) maps and defined lesion core and lesion periphery sub-ROIs. A lesion-core and a lesion-periphery feature were defined and combined into an overall classifier whose performance was compared to that of mean ADC using receiver operating characteristic (ROC) analysis. Inter-observer variability in ROI definition was measured using Dice Similarity Coefficient (DSC). RESULTS: The region-growing algorithm for 3D lesion model generation improved inter-observer variability over hand drawn ROIs (DSC: 0.66 vs 0.56 (p < 0.001) with substantial agreement (DSC > 0.8) in 46% vs 13% of cases, respectively (p < 0.001)). The overall classifier improved discrimination over mean ADC, (ROC- area under the curve (AUC): 0.85 vs 0.75 and 0.83 vs 0.74 respectively for the two readers). CONCLUSIONS: A classifier generated from directional DWI information using lesion core and lesion periphery information separately can improve lesion discrimination in dense breasts over mean ADC and should be considered for inclusion in computer-aided diagnosis algorithms. Our model-based ROIs could facilitate standardization of breast MRI computer-aided diagnostics (CADx).

Fast bilateral breast coverage with high spectral and spatial resolution (HiSS) MRI at 3T.

PURPOSE: To develop and assess a full-coverage, sensitivity encoding (SENSE)-accelerated breast high spatial and spectral resolution (HiSS) magnetic resonance imaging (MRI) within clinically reasonable times as a potential nonenhanced MRI protocol for breast density measurement or breast cancer screening. MATERIALS AND METHODS: Sixteen women with biopsy-proven cancer or suspicious lesions, and 13 women who were healthy volunteers or were screened for breast cancer, received 3T breast MRI exams, including SENSE-accelerated HiSS MRI, which was implemented as a submillimeter spatial resolution echo-planar spectroscopic imaging (EPSI) sequence. In postprocessing, fat and water resonance peak height and integral images were generated from EPSI data. The postprocessing software was custom-designed, and new algorithms were developed to enable processing of whole-coverage axial HiSS datasets. Water peak height HiSS images were compared to pre- and postcontrast T1 -weighted images. Fat suppression was quantified as parenchymal-to-suppressed-fat signal ratio in HiSS water peak height and nonenhanced T1 -weighted images, and artifact levels were scored. RESULTS: Approximately a 4-fold decrease in acquisition speed, with a concurrent 2.5-fold decrease in voxel size, was achieved, with low artifact levels, and with spectral signal-to-noise ratio (SNR) of 45:1. Fat suppression was 1.9 times more effective (P < 0.001) in HiSS images than in T1 -weighted images (SPAIR), and HiSS images showed higher SNR in the axilla. HiSS MRI visualized 10 of 13 malignant lesions identified on dynamic contrast-enhanced (DCE)-MRI, and did not require skin removal in postprocessing to generate maximum intensity projection images. CONCLUSION: We demonstrate full-coverage, SENSE-accelerated breast HiSS MRI within clinically reasonable times, as a potential protocol for breast density measurement or breast cancer screening. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1341-1348.

B1 and T1 mapping of the breast with a reference tissue method.

PURPOSE: To develop a method for mapping the B1 field using a reference signal from a tissue with known T1. METHODS: Flip angle correction factors were calculated in a region with a known "gold standard" T1; by comparing T1 values from a variable flip angle (VFA) sequence to the "gold standard" and correcting the value of the Ernst angle. The resulting partial B1 map was interpolated for all other regions. In the breast, fat is an ideal reference tissue because its T1 is spatially homogeneous and interpatient variability is low. This method was tested with scans of phantoms and patients (n = 4) on a 3T magnet. The performance of the method was evaluated by comparing the results of VFA T1 mapping with and without B1 correction to inversion recovery (IR) T1 maps. RESULTS: Phantom data determined that a linear inverse distance weighted interpolation accurately recovered the full B1 map. Use of interpolated maps to correct the VFA data in vivo, reduced the average difference in the T1 of parenchyma between VFA and IR results from 58% to 8%. CONCLUSION: This proof-of-principle study showed that it is possible to recover a full and accurate map of the B1 field in the breast by using a reference tissue (fat) with an accurately measured T1.

Pilot Study of the Use of Hybrid Multidimensional T2-Weighted Imaging-DWI for the Diagnosis of Prostate Cancer and Evaluation of Gleason Score.

OBJECTIVE: The objective of our study was to evaluate the role of a hybrid T2-weighted imaging-DWI sequence for prostate cancer diagnosis and differentiation of aggressive prostate cancer from nonaggressive prostate cancer. MATERIALS AND METHODS: Twenty-one patients with prostate cancer who underwent preoperative 3-T MRI and prostatectomy were included in this study. Patients underwent a hybrid T2-weighted imaging-DWI examination consisting of DW images acquired with TEs of 47, 75, and 100 ms and b values of 0 and 750 s/mm(2). The apparent diffusion coefficient (ADC) and T2 were calculated for cancer and normal prostate ROIs at each TE and b value. Changes in ADC and T2 as a function of increasing the TE and b value, respectively, were analyzed. A new metric termed "PQ4" was defined as the percentage of voxels within an ROI that has increasing T2 with increasing b value and has decreasing ADC with increasing TE. RESULTS: ADC values were significantly higher in normal ROIs than in cancer ROIs at all TEs (p < 0.0001). With increasing TE, the mean ADC increased 3% in cancer ROIs and increased 12% in normal ROIs. T2 was significantly higher in normal ROIs than in cancer ROIs at both b values (p ≤ 0.0002). The mean T2 decreased with increasing b value in cancer ROIs (ΔT2 = -17 ms) and normal ROIs (ΔT2 = -52 ms). PQ4 clearly differentiated normal ROIs from prostate cancer ROIs (p = 0.0004) and showed significant correlation with Gleason score (ρ = 0.508, p < 0.0001). CONCLUSION: Hybrid MRI measures the response of ADC and T2 to changing TEs and b values, respectively. This approach shows promise for detecting prostate cancer and determining its aggressiveness noninvasively.

Short-term reproducibility of apparent diffusion coefficient estimated from diffusion-weighted MRI of the prostate.

PURPOSE: The purpose of the study is to determine short-term reproducibility of apparent diffusion coefficient (ADC) estimated from diffusion-weighted magnetic resonance (DW-MR) imaging of the prostate. METHODS: Fourteen patients with biopsy-proven prostate cancer were studied under an Institutional Review Board-approved protocol. Each patient underwent two, consecutive and identical DW-MR scans on a 3T system. ADC values were calculated from each scan and a deformable registration was performed to align corresponding images. The prostate and cancerous regions of interest (ROIs) were independently analyzed by two radiologists. The prostate volume was analyzed by sextant. Per-voxel absolute and relative percentage variations in ADC were compared between sextants. Per-voxel and per-ROI variations in ADC were calculated for cancerous ROIs. RESULTS: Per-voxel absolute difference in ADC in the prostate ranged from 0 to 1.60 × 10(-3) mm(2)/s (per-voxel relative difference 0% to 200%, mean 10.5%). Variation in ADC was largest in the posterior apex (0% to 200%, mean 11.6%). Difference in ADC variation between sextants was not statistically significant. Cancer ROIs' per-voxel variation in ADC ranged from 0.001 × 10(-3) to 0.841 × 10(-3) mm(2)/s (0% to 67.4%, mean 11.2%) and per-ROI variation ranged from 0 to 0.463 × 10(-3) mm(2)/s (mean 0.122 × 10(-3) mm(2)/s). CONCLUSIONS: Variation in ADC within the human prostate is reasonably small, and is on the order of 10%.

MR imaging of the prostate and adjacent anatomic structures before, during, and after ejaculation: qualitative and quantitative evaluation.

PURPOSE: To determine the possibility of obtaining high-quality magnetic resonance (MR) images before, during, and immediately after ejaculation and detecting measurable changes in quantitative MR imaging parameters after ejaculation. MATERIALS AND METHODS: In this prospective, institutional review board-approved, HIPAA-compliant study, eight young healthy volunteers (median age, 22.5 years), after providing informed consent, underwent MR imaging while masturbating to the point of ejaculation. A 1.5-T MR imaging unit was used, with an eight-channel surface coil and a dynamic single-shot fast spin-echo sequence. In addition, a quantitative MR imaging protocol that allowed calculation of T1, T2, and apparent diffusion coefficient (ADC) values was applied before and after ejaculation. Volumes of the prostate and seminal vesicles (SV) were calculated by using whole-volume segmentation on T2-weighted images, both before and after ejaculation. Pre- and postejaculation changes in quantitative MR parameters and measured volumes were evaluated by using the Wilcoxon signed rank test with Bonferroni adjustment. RESULTS: There was no significant change in prostate volumes on pre- and postejaculation images, while the SV contracted by 41% on average (median, 44.5%; P = .004). No changes before and after ejaculation were observed in T1 values or in T2 and ADC values in the central gland, while T2 and ADC values were significantly reduced in the peripheral zone by 12% and 14%, respectively (median, 13% and 14.5%, respectively; P = .004). CONCLUSION: Successful dynamic MR imaging of ejaculation events and the ability to visualize internal sphincter closure, passage of ejaculate, and significant changes in SV volumes were demonstrated. Significant changes in peripheral zone T2 and ADC values were observed.

Hybrid multidimensional T(2) and diffusion-weighted MRI for prostate cancer detection.

PURPOSE: To study the dependence of apparent diffusion coefficient (ADC) and T2 on echo time (TE) and b-value, respectively, in normal prostate and prostate cancer, using two-dimensional MRI sampling, referred to as "hybrid multidimensional imaging." MATERIALS AND METHODS: The study included 10 patients with biopsy-proven prostate cancer who underwent 3 Tesla prostate MRI. Diffusion-weighted MRI (DWI) data were acquired at b = 0, 750, and 1500 s/mm(2) . For each b-value, data were acquired at TEs of 47, 75, and 100 ms. ADC and T2 were measured as a function of b-value and TE, respectively, in 15 cancer and 10 normal regions of interest (ROIs). The Friedman test was used to test the significance of changes in ADC as a function of TE and of T2 as a function of b-value. RESULTS: In normal prostate ROIs, the ADC at TE of 47 ms is significantly smaller than ADC at TE of 100 ms (P = 0.0003) and T2 at b-value of 0 s/mm(2) is significantly longer than T2 at b-value of 1500 s/mm(2) (P = 0.001). In cancer ROIs, average ADC and T2 values do not change as a function of TE and b-value, respectively. However, in many cancer pixels, there are large decreases in the ADC as a function of TE and large increases in T2 as a function of b-value. Cancers are more conspicuous in ADC maps at longer TEs. CONCLUSION: Parameters derived from hybrid imaging that depend on coupled/associated values of ADC and T2 may improve the accuracy of MRI in diagnosing prostate cancer.

Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions.

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

High-resolution diffusion-weighted imaging of the prostate.

OBJECTIVE: The purpose of this study was to evaluate the effect of increasing the spatial resolution of the prostate DWI protocol on image quality and lesion conspicuity. SUBJECTS AND METHODS: Twenty-nine patients with biopsy-proven prostate cancer undergoing MRI examinations were imaged with two diffusion-weighted imaging (DWI) protocols: current standard clinical protocol (6.7 mm(3) voxels) and a new high-resolution protocol (3.1 mm(3) voxels). Diffusion-weighted images were independently and subjectively scored on lesion conspicuity, internal architecture definition, and overall image quality by two radiologists. Average apparent diffusion coefficient (ADC) values were measured in normal tissue and cancerous lesions on both sequences. Reader scores and ADC and contrast values were compared between the two protocols. Cancer ADC values were correlated with Gleason scores. RESULTS: The signal-to-noise ratio of the new high-resolution DWI protocol was 40% lower than that of the standard protocol. The reader scores were higher by 0.73 (range, 0.29-1.16) grades, or 19% (range, 7-32%), on average, for the new protocol, indicating better image quality. The average ADC values were 8% higher with the new protocol, with ADC contrast values between cancer and normal prostate unchanged. There was marginally significant correlation of cancer ADC values with Gleason scores (p = 0.05, r ≈ -0.36). CONCLUSION: We showed that for DWI of the prostate at 3-7 mm(3) voxel sizes the benefits of higher spatial resolution outweigh the effects of reduced signal-to-noise and contrast-to-noise ratios, potentially improving the sensitivity to small or sparse prostate cancers. Radiologists can consider using higher-spatial-resolution DWI sequences in their practices.

Multiparametric quantitative magnetic resonance imaging of uterine fibroids for prediction of growth rate-a pilot study.

Background: Uterine fibroid (UF) growth rate and future morbidity cannot be predicted. This can lead to sub-optimal clinical management, with women being lost to follow-up and later presenting with severe disease that may require hospitalization, transfusions, and urgent surgical interventions. Multi-parametric quantitative magnetic resonance imaging (MRI) could provide a biomarker to predict growth rate facilitating better-informed disease management and better clinical outcomes. We assessed the ability of putative quantitative and qualitative MRI predictive factors to predict UF growth rate. Methods: Twenty women with UFs were recruited and completed baseline and follow-up MRI exams, 1-2.5 years apart. The subjects filled out symptom severity and health-related quality of life questionnaires at each visit. A standard clinical pelvic MRI non-contrast exam was performed at each visit, followed by a contrast-enhanced multi-parametric quantitative MRI (mp-qMRI) exam with T2, T2*, and apparent diffusion coefficient (ADC) mapping and dynamic contrast-enhanced MRI. Up to 3 largest fibroids were identified and outlined on the T2-weighted sequence. Fibroid morphology and enhancement patterns were qualitatively assessed on dynamic contrast-enhanced MRI. The UFs' volumes and average T2, T2*, and ADC values were calculated. Pearson correlation coefficients were calculated between UF growth rate and T2, T2*, ADC, and baseline volume. Multiple logistic regression and receiver operating characteristic (ROC) analysis were performed to predict fast-growing UFs using combinations of up to 2 significant predictors. A significance level of alpha =0.05 was used. Results: Forty-four fibroids in 20 women had growth rate measurement available, and 36 fibroids in 16 women had follow-up quantitative MRI available. The distribution of fibroid growth rate was skewed, with approximately 20% of the fibroids exhibiting fast growth (>10 cc/year). However, there were no significant changes in median baseline and follow-up values of symptom severity and health-related quality of life scores. There was no change in average T2, T2*, and ADC at follow-up exams and there was a moderate to strong correlation to the fibroid growth rate in baseline volume and average T2 and ADC in slow-growing fibroids (<10 cc/year). A multiple logistic regression to identify fast growing UFs (>10 cc/year) achieved an area under the curve (AUC) of 0.80 with specificity of 69% at 100% sensitivity. Conclusions: The mp-qMRI parameters T2, ADC, and UF volume obtained at the time of initial fibroid diagnosis may be able to predict UF growth rate. Mp-qMRI could be integrated into the management of UFs, for individualized care and improved clinical outcomes.

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

Background: Imaging of peritoneal malignancies using conventional cross-sectional imaging is challenging, but accurate assessment of peritoneal disease burden could guide better selection for definitive surgery. Here we demonstrate feasibility of high-resolution, high-contrast magnetic resonance imaging (MRI) of peritoneal mesothelioma and explore optimal timing for delayed post-contrast imaging. Methods: Prospective data from inpatients with malignant peritoneal mesothelioma (MPM), imaged with a novel MRI protocol, were analyzed. The new sequences augmenting the clinical protocol were (I) pre-contrast coronal high-resolution T2-weighted single-shot fast spin echo (COR hr T2w SSH FSE) of abdomen and pelvis; and (II) post-contrast coronal high-resolution three-dimensional (3D) T1-weighted modified Dixon (COR hr T1w mDIXON) of abdomen, acquired at five delay times, up to 20 min after administration of a double dose of contrast agent. Quantitative analysis of contrast enhancement was performed using linear regression applied to normalized signal in lesion regions of interest (ROIs). Qualitative analysis was performed by three blinded radiologists. Results: MRI exams from 14 participants (age: mean ± standard deviation, 60±12 years; 71% male) were analyzed. The rate of lesion contrast enhancement was strongly correlated with tumor grade (cumulative nuclear score) (r=-0.65, P<0.02), with 'early' delayed phase (12 min post-contrast) and 'late' delayed phase (19 min post-contrast) performing better for higher grade and lower grade tumors, respectively, in agreement with qualitative scoring of image contrast. Conclusions: High-resolution, high-contrast MRI with extended post-contrast imaging is a viable modality for imaging peritoneal mesothelioma. Multiple, extended (up to 20 min post-contrast) delayed phases are necessary for optimal imaging of peritoneal mesothelioma, depending on the grade of disease.

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

Inhomogeneously broadened, non-Lorentzian water resonances have been observed in small image voxels of breast tissue. The non-Lorentzian components of the water resonance are probably produced by bulk magnetic susceptibility shifts caused by dense, deoxygenated tumor blood vessels (the 'blood oxygenation level-dependent' effect), but can also be produced by other characteristics of local anatomy and physiology, including calcifications and interfaces between different types of tissue. Here, we tested the hypothesis that the detection of non-Lorentzian components of the water resonance with high spectral and spatial resolution (HiSS) MRI allows the classification of breast lesions without the need to inject contrast agent. Eighteen malignant lesions and nine benign lesions were imaged with HiSS MRI at 1.5 T. A new algorithm was developed to detect non-Lorentzian (or off-peak) components of the water resonance. After a Lorentzian fit had been subtracted from the data, the largest peak in the residual spectrum in each voxel was identified as the major off-peak component of the water resonance. The difference in frequency between these off-peak components and the main water peaks, and their amplitudes, were measured in malignant lesions, benign lesions and breast fibroglandular tissue. Off-peak component frequencies were significantly different between malignant and benign lesions (p < 0.001). Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance of HiSS off-peak component analysis compared with dynamic contrast-enhanced (DCE) MRI parameters. The areas under the ROC curves for the 'DCE rapid uptake fraction', 'DCE washout fraction', 'off-peak component amplitude' and 'off-peak component frequency' were 0.75, 0.83, 0.50 and 0.86, respectively. These results suggest that water resonance lineshape analysis performs well in the classification of breast lesions without contrast injection and could improve the diagnostic accuracy of clinical breast MR examinations. In addition, this approach may provide an alternative to DCE MRI in women who are at risk for adverse reactions to contrast media.

Prostate volumes derived from MRI and volume-adjusted serum prostate-specific antigen: correlation with Gleason score of prostate cancer.

OBJECTIVE: The purpose of this article is to study relationships between MRI-based prostate volume and volume-adjusted serum prostate-specific antigen (PSA) concentration estimates and prostate cancer Gleason score. MATERIALS AND METHODS: The study included 61 patients with prostate cancer (average age, 63.3 years; range 52-75 years) who underwent MRI before prostatectomy. A semiautomated and MRI-based technique was used to estimate total and central gland prostate volumes, central gland volume fraction (central gland volume divided by total prostate volume), PSA density (PSAD; PSA divided by total prostate volume), and PSAD for the central gland (PSA divided by central gland volume). These MRI-based volume and volume-adjusted PSA estimates were compared with prostatectomy specimen weight and Gleason score by using Pearson (r) or Spearman (ρ) correlation coefficients. RESULTS: The estimated total prostate volume showed a high correlation with reference standard volume (r = 0.94). Of the 61 patients, eight (13.1%) had a Gleason score of 6, 40 (65.6%) had a Gleason score of 7, seven (11.5%) had a Gleason score of 8, and six (9.8%) had a Gleason score of 9 for prostate cancer. The Gleason score was significantly correlated with central gland volume fraction (ρ = -0.42; p = 0.0007), PSAD (ρ = 0.46; p = 0.0002), and PSAD for the central gland (ρ = 0.55; p = 0.00001). CONCLUSION: Central gland volume fraction, PSAD, and PSAD for the central gland estimated from MRI examinations show a modest but significant correlation with Gleason score and have the potential to contribute to personalized risk assessment for significant prostate cancer.

Characterization of Effects of Compressed Sensing on High Spectral and Spatial Resolution (HiSS) MRI with Comparison to SENSE.

High Spectral and Spatial resolution (HiSS) MRI shows high diagnostic performance in the breast. Acceleration methods based on k-space undersampling could allow stronger T2*-based image contrast and/or higher spectral resolution, potentially increasing diagnostic performance. An agar/oil phantom was prepared with water-fat boundaries perpendicular to the readout and phase encoding directions in a breast coil. HiSS MRI was acquired at 3T, at sensitivity encoding (SENSE) acceleration factors R of up to 10, and the R = 1 dataset was used to simulate corresponding compressed sensing (CS) accelerations. Image quality was evaluated by quantifying noise and artifact levels. Effective spatial resolution was determined via modulation transfer function analysis. Dispersion vs. absorption (DISPA) analysis and full width at half maximum (FWHM) quantified spectral lineshape changes. Noise levels remained constant with R for CS but amplified with SENSE. SENSE preserved the spatial resolution of HiSS MRI, while CS reduced it in the phase encoding direction. SENSE showed no effect on FWHM or DISPA markers, while CS increased FWHM. Thus, CS might perform better in noise-limited or geometrically constrained applications, but in geometric configurations specific to breast MRI, spectral analysis might be compromised, decreasing the diagnostic performance of HiSS MRI.

Standardization of Breast Dynamic Contrast-enhanced MRI Signal with Application to the Assessment of Background Parenchymal Enhancement Rate.

BACKGROUND: There is currently no clinically accepted method for quantifying background parenchymal enhancement (BPE), though a sensitive method might allow individualized risk management based on the response to cancer-preventative hormonal therapy. OBJECTIVE: The objective of this pilot study is to demonstrate the utility of linear modeling of standardized dynamic contrast-enhanced MRI (DCEMRI) signal for quantifying changes in BPE rates. METHODS: On a retrospective database search, 14 women with DCEMRI examinations pre- and post- treatment with tamoxifen were identified. DCEMRI signal was averaged over the parenchymal ROIs to obtain time-dependent signal curves S(t). The gradient echo signal equation was used to standardize scale S(t) to values of (FA) ̃ = 10° and (TR) ̃ = 5.5 ms, and obtain the standardized parameters of DCE-MRI signal S ̃_p (t). Relative signal enhancement (〖RSE〗_p ) ̃ was calculated from S ̃_p, and the reference tissue method for T1 calculation was used to standardize (〖RSE〗_p ) ̃ to gadodiamide as the contrast agent, obtaining (RSE) ̃. (RSE) ̃, in the first 6 minutes, post-contrast administration was fit to a linear model with the slope α ̃_RSE denoting the standardized rate relative BPE. RESULTS: Changes in α ̃_RSE were not found to be significantly correlated with the average duration of tamoxifen treatment, age at the initiation of preventative treatment, or pre-treatment BIRADS breast density category. The average change in α ̃_RSE showed a large effect size of -1.12, significantly higher than -0.86 observed without signal standardization (p < 0.01). CONCLUSION: Linear modeling of BPE in standardized DCEMRI can provide quantitative measurements of BPE rates, improving sensitivity to changes due to tamoxifen treatment.