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.

Comparing Radiologist Performance in Diagnosing Clinically Significant Prostate Cancer with Multiparametric versus Hybrid Multidimensional MRI.

Background Variability of acquisition and interpretation of prostate multiparametric MRI (mpMRI) persists despite implementation of the Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 due to the range of reader experience and subjectivity of lesion characterization. A quantitative method, hybrid multidimensional MRI (HM-MRI), may introduce objectivity. Purpose To compare performance, interobserver agreement, and interpretation time of radiologists using mpMRI versus HM-MRI to diagnose clinically significant prostate cancer. Materials and Methods In this retrospective analysis, men with prostatectomy or MRI-fused transrectal US biopsy-confirmed prostate cancer underwent mpMRI (triplanar T2-weighted, diffusion-weighted, and dynamic contrast-enhanced imaging) and HM-MRI (with multiple echo times and b value combinations) from August 2012 to February 2020. Four readers with 1-20 years of experience interpreted mpMRI and HM-MRI examinations independently, with a 4-week washout period between interpretations. PI-RADS score, lesion location, and interpretation time were recorded. mpMRI and HM-MRI interpretation time, interobserver agreement (Cronbach alpha), and performance of area under the receiver operating characteristic curve (AUC) analysis were compared for each radiologist with use of bootstrap analysis. Results Sixty-one men (mean age, 61 years ± 8 [SD]) were evaluated. Per-patient AUC was higher for HM-MRI for reader 4 compared with mpMRI (AUCs for readers 1-4: 0.61, 0.71, 0.59, and 0.64 vs 0.66, 0.60, 0.50, and 0.46; P = .57, .20, .32, and .04, respectively). Per-patient specificity was higher for HM-MRI for readers 2-4 compared with mpMRI (specificity for readers 1-4: 48%, 78%, 48%, and 46% vs 37%, 26%, 0%, and 7%; P = .34, P < .001, P < .001, and P < .001, respectively). Diagnostic performance improved for the reader least experienced with HM-MRI, reader 4 (AUC, 0.64 vs 0.46; P = .04). HM-MRI interobserver agreement (Cronbach alpha = 0.88 [95% CI: 0.82, 0.92]) was higher than that of mpMRI (Cronbach alpha = 0.26 [95% CI: 0.10, 0.52]; α > .60 indicates reliability; P = .03). HM-MRI mean interpretation time (73 seconds ± 43 [SD]) was shorter than that of mpMRI (254 seconds ± 133; P = .03). Conclusion Radiologists had similar or improved diagnostic performance, higher interobserver agreement, and lower interpretation time for clinically significant prostate cancer with hybrid multidimensional MRI than multiparametric MRI. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Validation of Prostate Tissue Composition by Using Hybrid Multidimensional MRI: Correlation with Histologic Findings.

Background Tissue estimates obtained by using microstructure imaging techniques, such as hybrid multidimensional (HM) MRI, may improve prostate cancer diagnosis but require histologic validation. Purpose To validate prostate tissue composition measured by using HM MRI, with quantitative histologic evaluation from whole-mount prostatectomy as the reference standard. Materials and Methods In this HIPAA-compliant study, from December 2016 to July 2018, prospective participants with biopsy-confirmed prostate cancer underwent 3-T MRI before radical prostatectomy. Axial HM MRI was performed with all combinations of echo times (57, 70, 150, and 200 msec) and b values (0, 150, 750, and 1500 sec/mm2). Data were fitted by using a three-compartment signal model to generate volumes for each tissue component (stroma, epithelium, lumen). Quantitative histologic evaluation was performed to calculate volume fractions for each tissue component for regions of interest corresponding to MRI. Tissue composition measured by using HM MRI and quantitative histologic evaluation were compared (paired t test) and correlated (Pearson correlation coefficient), and agreement (concordance correlation) was assessed. Receiver operating characteristic curve analysis for cancer diagnosis was performed. Results Twenty-five participants (mean age, 60 years ± 7 [standard deviation]; 30 cancers and 45 benign regions of interest) were included. Prostate tissue composition measured with HM MRI and quantitative histologic evaluation did not differ (stroma, 45% ± 11 vs 44% ± 11 [P = .23]; epithelium, 31% ± 15 vs 34% ± 15 [P = .08]; and lumen, 24% ± 13 vs 22% ± 11 [P = .80]). Between HM MRI and histologic evaluation, there was excellent correlation (Pearson r: overall, 0.91; stroma, 0.82; epithelium, 0.93; lumen, 0.90 [all P < .05]) and agreement (concordance correlation coefficient: overall, 0.91; stroma, 0.81; epithelium, 0.90; and lumen, 0.87). High areas under the receiver operating characteristic curve obtained with HM MRI (0.96 for epithelium and 0.94 for lumen, P < .001) and histologic evaluation (0.94 for epithelium and 0.88 for lumen, P < .001) were found for differentiation between benign tissue and prostate cancer. Conclusion Tissue composition measured by using hybrid multidimensional MRI had excellent correlation with quantitative histologic evaluation as the reference standard. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Muglia in this issue.

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.

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.

Magnetic Resonance Imaging-Guided Transurethral Ultrasound Ablation of Prostate Cancer.

PURPOSE: Magnetic resonance imaging-guided transurethral ultrasound ablation uses directional thermal ultrasound under magnetic resonance imaging thermometry feedback control for prostatic ablation. We report 12-month outcomes from a prospective multicenter trial (TACT). MATERIALS AND METHODS: A total of 115 men with favorable to intermediate risk prostate cancer across 13 centers were treated with whole gland ablation sparing the urethra and apical sphincter. The co-primary 12-month endpoints were safety and efficacy. RESULTS: In all, 72 (63%) had grade group 2 and 77 (67%) had NCCN® intermediate risk disease. Median treatment delivery time was 51 minutes with 98% (IQR 95-99) thermal coverage of target volume and spatial ablation precision of ±1.4 mm on magnetic resonance imaging thermometry. Grade 3 adverse events occurred in 9 (8%) men. The primary endpoint (U.S. Food and Drug Administration mandated) of prostate specific antigen reduction ≥75% was achieved in 110 of 115 (96%) with median prostate specific antigen reduction of 95% and nadir of 0.34 ng/ml. Median prostate volume decreased from 37 to 3 cc. Among 68 men with pretreatment grade group 2 disease, 52 (79%) were free of grade group 2 disease on 12-month biopsy. Of 111 men with 12-month biopsy data, 72 (65%) had no evidence of cancer. Erections (International Index of Erectile Function question 2 score 2 or greater) were maintained/regained in 69 of 92 (75%). Multivariate predictors of persistent grade group 2 at 12 months included intraprostatic calcifications at screening, suboptimal magnetic resonance imaging thermal coverage of target volume and a PI-RADS™ 3 or greater lesion at 12-month magnetic resonance imaging (p <0.05). CONCLUSIONS: The TACT study of magnetic resonance imaging-guided transurethral ultrasound whole gland ablation in men with localized prostate cancer demonstrated effective tissue ablation and prostate specific antigen reduction with low rates of toxicity and residual disease.

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.

MRI Targeted Prostate Biopsy Techniques: AJR Expert Panel Narrative Review.

Prostate cancer is the second most common malignancy in men worldwide. Systematic transrectal prostate biopsy is commonly used to obtain tissue to establish the diagnosis. In recent years, however, more clinically significant cancer and less clinically insignificant cancer have been detected with MRI targeted biopsy (on the basis of an MRI examination performed before consideration of biopsy) than with systematic biopsy. This approach of performing MRI before biopsy has become, or is becoming, a standard of practice in centers throughout the world. This growing use of an MRI-directed pathway is leading to performance of a larger volume of MRI targeted prostate biopsies. The three common MRI targeted biopsy techniques are cognitive biopsy, MRI-ultrasound software fusion biopsy, and MRI in-bore guided biopsy. These techniques for using MRI information at biopsy can be performed via a transrectal or transperineal approach. The purpose of this review is to describe the three MRI targeted biopsy techniques and their advantages and shortcomings. Comparisons among the techniques are summarized on the basis of the available evidence. Studies to date have had heterogeneous results, and the preferred technique remains debated.

PI-RADS Committee Position on MRI Without Contrast Medium in Biopsy-Naive Men With Suspected Prostate Cancer: Narrative Review.

The steadily increasing demand for diagnostic prostate MRI has led to concerns regarding the lack of access to and the availability of qualified MRI scanners and sufficiently experienced radiologists, radiographers, and technologists to meet the demand. Solutions must enhance operational benefits without compromising diagnostic performance, quality, and delivery of service. Solutions should also mitigate risks such as decreased reader confidence and referrer engagement. One approach may be the implementation of MRI without the use gadolinium-based contrast medium (bipara-metric MRI), but only if certain prerequisites such as high-quality imaging, expert interpretation quality, and availability of patient recall or on-table monitoring are mandated. Alternatively, or in combination, a clinical risk-based approach could be used for protocol selection, specifically, which biopsy-naive men need MRI with contrast medium (multiparametric MRI). There is a need for prospective studies in which biopsy decisions are made according to MRI without contrast enhancement. Such studies must define clinical and operational benefits and identify which patient groups can be scanned successfully without contrast enhancement. These higher-quality data are needed before the Prostate Imaging Reporting and Data System (PI-RADS) Committee can make evidence-based recommendations about MRI without contrast enhancement as an initial diagnostic approach for prostate cancer workup.

Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel.

Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown. Purpose To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers. Materials and Methods This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2-5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range. Results The authors evaluated 3449 men (mean age, 65 years ± 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%-44% and 27%-48%, respectively. Conclusion The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Milot in this issue.

Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model.

OBJECTIVE. Deep learning applications in radiology often suffer from overfitting, limiting generalization to external centers. The objective of this study was to develop a high-quality prostate segmentation model capable of maintaining a high degree of performance across multiple independent datasets using transfer learning and data augmentation. MATERIALS AND METHODS. A retrospective cohort of 648 patients who underwent prostate MRI between February 2015 and November 2018 at a single center was used for training and validation. A deep learning approach combining 2D and 3D architecture was used for training, which incorporated transfer learning. A data augmentation strategy was used that was specific to the deformations, intensity, and alterations in image quality seen on radiology images. Five independent datasets, four of which were from outside centers, were used for testing, which was conducted with and without fine-tuning of the original model. The Dice similarity coefficient was used to evaluate model performance. RESULTS. When prostate segmentation models utilizing transfer learning were applied to the internal validation cohort, the mean Dice similarity coefficient was 93.1 for whole prostate and 89.0 for transition zone segmentations. When the models were applied to multiple test set cohorts, the improvement in performance achieved using data augmentation alone was 2.2% for the whole prostate models and 3.0% for the transition zone segmentation models. However, the best test-set results were obtained with models fine-tuned on test center data with mean Dice similarity coefficients of 91.5 for whole prostate segmentation and 89.7 for transition zone segmentation. CONCLUSION. Transfer learning allowed for the development of a high-performing prostate segmentation model, and data augmentation and fine-tuning approaches improved performance of a prostate segmentation model when applied to datasets from external centers.

Evaluation of Focal Laser Ablation of Prostate Cancer Using High Spectral and Spatial Resolution Imaging: A Pilot Study.

BACKGROUND: Focal laser ablation (FLA) is a minimally invasive thermal ablation, guided by MRI through an optical fiber, to induce coagulative necrosis in cancer. PURPOSE: To evaluate the feasibility of high spectral and spatial resolution imaging using multiecho gradient echo (MEGE) MRI for identification of ablation zones, after FLA of prostate cancers. STUDY TYPE: Prospective. POPULATION: Fourteen patients with biopsy-confirmed localized prostate cancers. FIELD STRENGTH/SEQUENCE: FLA was performed under monitored conscious sedation with a 1.5T MRI scanner. Axial MEGE images were acquired before and after the last FLA. Pre- and postcontrast enhanced T1 -weighted (pT1 W) images were acquired to assess the FLA zone as a reference standard. ASSESSMENT: The T 2 * maps and water resonance peak height (WPH) images were calculated from the MEGE data. Ablation area was outlined using an active contour method. The maximum ablation area and total ablation volume were calculated from T 2 * and WPH images, and compared with the sizes measured from pT1 W images. STATISTICAL TESTS: Nonparametric Kruskal-Wallis tests were performed to determine whether there was significant difference in calculated ablation areas and volumes between T 2 * , WPH, and pT1 W images. RESULTS: Average T 2 * (38.9 ± 14.1 msec) in the ablation area was significantly shorter (P = 0.03) than the preablation area T 2 * (57.8 ± 25.3 msec). The normalized WPH value over the ablation area (1.3 ± 0.6) was significantly decreased (P = 0.02) more than the preablation area (2.0 ± 0.9). The maximum ablation areas measured by T 2 * (295.7 ± 96.4 mm2 ), WPH (312.2 ± 63.0 mm2 ), and pT1 W (320.3 ± 82.9 mm2 ) images were all similar. Furthermore, there was no significant difference (P = 0.31) for measured ablation volumes 3310.5 ± 649.5, 3406.4 ± 684.9, and 3672.5 ± 832.4 mm3 between T 2 * , WPH, and pT1 W images, respectively. DATA CONCLUSION: T 2 * and WPH images provide acceptable measurements of ablation zones during FLA treatment of prostate cancers without the need for contrast agent injection. This might allow repeated assessment following each heating period so that subsequent ablations can be optimized. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;49:1374-1380.

Comparison of T2-Weighted Imaging, DWI, and Dynamic Contrast-Enhanced MRI for Calculation of Prostate Cancer Index Lesion Volume: Correlation With Whole-Mount Pathology.

OBJECTIVE: The objective of our study was to investigate the comparative effectiveness of different MRI sequences for the estimation of index lesion volume in patients with prostate cancer (PCa) compared with ground truth volume measured on whole-mount pathology. MATERIALS AND METHODS: Patients with PCa underwent multiparametric MRI (mpMRI) on a 3-T MRI scanner before radical prostatectomy. Forty PCa index lesions were identified and outlined on histology by a pathologist. Two radiologists who were informed about the presence of PCa but were not aware of lesion outlines on histology worked in consensus to delineate PCa lesions on T2-weighted imaging, apparent diffusion coefficient (ADC) maps, and early-phase dynamic contrast-enhanced MRI (DCE-MRI). The lesion volumes from different mpMRI sequences and the percentage of volume underestimation compared with pathology were calculated and correlated with volume at pathology. The repeated-measures ANOVA with the posthoc Bonferroni test was performed to evaluate whether the difference between the estimated tumor volumes was statistically significant. RESULTS: The mean PCa lesion volume estimated from pathology, T2-weighted imaging, DWI (ADC maps), and DCE-MRI were 4.61 ± 4.99 (SD) cm3, 2.03 ± 2.96 cm3, 1.81 ± 2.76 cm3, and 3.48 ± 4.06 cm3, respectively. The lesion volumes on T2-weighted images (p = 0.000002), ADC maps (p = 0.000003), and DCE-MR images (p = 0.004412) were significantly lower than those from pathology. PCa lesion volume was significantly underestimated on T2-weighted images, ADC maps, and DCE-MR images compared with pathology by 54.98% ± 22.60% (mean ± SD), 58.59% ± 18.58%, and 18.33% ± 30.11%, respectively; underestimation using T2-weighted imaging (p = 1.01 × 10-11) and DWI (p = 2.94 × 10-11) was significantly higher than underestimation using DCE-MRI. Correlations between lesion volume estimated on T2-weighted images, ADC maps, and DCE-MR images with pathology were 0.91 (p = 9.03 × 10-16), 0.86 (p = 7.32 × 10-13), and 0.93 (p = 8.22 × 10-18), respectively. CONCLUSION: DCE-MRI performed better than T2-weighted imaging and DWI for estimation of index PCa volume and therefore can be preferred over these other two sequences for volume estimation.

Diagnosis of Prostate Cancer by Use of MRI-Derived Quantitative Risk Maps: A Feasibility Study.

OBJECTIVE. The purpose of this study was to develop a new quantitative image analysis tool for estimating the risk of cancer of the prostate by use of quantitative multiparametric MRI (mpMRI) metrics. MATERIALS AND METHODS. Thirty patients with biopsy-confirmed prostate cancer (PCa) who underwent preoperative 3-T mpMRI were included in the study. Quantitative mpMRI metrics-apparent diffusion coefficient (ADC), T2, and dynamic contrast-enhanced (DCE) signal enhancement rate (α)-were calculated on a voxel-by-voxel basis for the whole prostate and coregistered. A normalized risk value (0-100) for each mpMRI parameter was obtained, with high risk values associated with low T2 and ADC and high signal enhancement rate. The final risk score was calculated as a weighted sum of the risk scores (ADC, 40%; T2, 40%; DCE, 20%). Data from five patients were used as training set to find the threshold for predicting PCa. In the other 25 patients, any region with a minimum of 30 con-joint voxels (≈ 4.8 mm2) with final risk score above the threshold was considered positive for cancer. Lesion-based and sector-based analyses were performed by matching prostatectomyverified malignancy and PCa predicted with the risk analysis tool. RESULTS. The risk map tool had sensitivity of 76.6%, 89.2%, and 100% for detecting all lesions, clinically significant lesions (≥ Gleason 3 + 4), and index lesions, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for PCa detection for all lesions in the sector-based analysis were 78.9%, 88.5%, 84.4%, and 84.1%, respectively, with an ROC AUC of 0.84. CONCLUSION. The risk analysis tool is effective for detecting clinically significant PCa with reasonable sensitivity and specificity in both peripheral and transition zones.

Multiparametric MRI Features and Pathologic Outcome of Wedge-Shaped Lesions in the Peripheral Zone on T2-Weighted Images of the Prostate.

OBJECTIVE: This study investigates the multiparametric MRI (mpMRI) characteristics and pathologic outcome of wedge-shaped lesions observed on T2-weighted images. MATERIALS AND METHODS: Seventy-six patients with histologically confirmed prostate cancer underwent preoperative 3-T MRI before undergoing radical prostatectomy. Two radiologists worked in consensus to mark wedge-shaped regions of hypointensity on T2-weighted images and assess their appearance on apparent diffusion coefficient (ADC) maps (to determine the degree of hypointensity) and dynamic contrast-enhanced (DCE) MRI (DCE-MRI) (to assess whether they showed early enhancement). The pathologic outcome of wedge-shaped lesions was assessed by matching MR images with whole-mount histologic specimens retrospectively. The difference in quantitative ADC values between malignant and benign wedge-shaped lesions was assessed using a t test. RESULTS: Thirty-five wedge-shaped regions were identified, 12 (34%) of which were found be malignant. Most malignant wedge-shaped regions were highly hypointense (10/12; 83%) on ADC maps and showed early enhancement on DCE-MRI (7/12; 58%). However, benign wedge-shaped lesions were predominantly mildly hypointense (13/23; 57%) on ADC maps and showed no early enhancement (15/23; 65%). Histologic correlates of the benign wedge-shaped regions showed prostatitis (acute inflammation [7/23; 30%] or chronic inflammation [9/23; 39%]), hemosiderin-laden macrophages (6/23; 26%), prominent blood vessels (7/23; 30%), intraluminal blood (6/23; 26%), and nonspecific atrophy (6/23; 26%). The mean (± SD) quantitative ADC value of malignant wedge-shaped regions (1.13 ± 0.11 µm2/ms) was significantly lower (p = 0.0001) than that of benign wedge-shaped regions (1.52 ± 0.27 µm2/ms). CONCLUSION: This study shows that a greater percentage of wedge-shaped features are malignant than was previously thought. Of importance, mpMRI (specifically, ADC maps) can distinguish between malignant and benign wedge-shaped features.

Diagnosis of Prostate Cancer with Noninvasive Estimation of Prostate Tissue Composition by Using Hybrid Multidimensional MR Imaging: A Feasibility Study.

Purpose To evaluate whether compartmental analysis by using hybrid multidimensional magnetic resonance (MR) imaging can be used to diagnose prostate cancer and determine its aggressiveness. Materials and Methods Twenty-two patients with prostate cancer underwent preoperative 3.0-T MR imaging. Axial images were obtained with hybrid multidimensional MR imaging by using all combinations of echo times (47, 75, 100 msec) and b values of 0, 750, 1500 sec/mm2, resulting in a 3 × 3 array of data associated with each voxel. Volumes of the tissue components stroma, epithelium, and lumen were calculated by fitting the hybrid data to a three-compartment signal model, with distinct, paired apparent diffusion coefficient (ADC) and T2 values associated with each compartment. Volume fractions and conventional ADC and T2 were measured for regions of interest in sites of prostatectomy-verified malignancy (n = 28) and normal tissue (n = 71). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of various parameters in differentiating prostate cancer from benign tissue. Results Compared with normal tissue, prostate cancer showed significantly increased fractional volumes of epithelium (23.2% ± 7.1 vs 48.8% ± 9.2, respectively) and reduced fractional volumes of lumen (26.4% ± 14.1 vs 14.0% ± 5.2) and stroma (50.5% ± 15.7 vs 37.2% ± 9.1) by using hybrid multidimensional MR imaging. The fractional volumes of tissue components show a significantly higher Spearman correlation coefficient with Gleason score (epithelium: ρ = 0.652, P = .0001; stroma: ρ = -0.439, P = .020; lumen: ρ = -0.390, P = .040) compared with traditional T2 values (ρ = -0.292, P = .132) and ADCs (ρ = -0.315, P = .102). The area under the ROC curve for differentiation of cancer from normal prostate was highest for fractional volume of epithelium (0.991), followed by fractional volumes of lumen (0.800) and stroma (0.789). Conclusion Fractional volumes of prostatic lumen, stroma, and epithelium change significantly when cancer is present. These parameters can be measured noninvasively by using hybrid multidimensional MR imaging and have the potential to improve the diagnosis of prostate cancer and determine its aggressiveness. © RSNA, 2018 Online supplemental material is available for this article.

Magnetic Resonance Imaging and Molecular Characterization of a Hormone-Mediated Murine Model of Prostate Enlargement and Bladder Outlet Obstruction.

Urinary complications resulting from benign prostatic hyperplasia and bladder outlet obstruction continue to be a serious health problem. Novel animal model systems and imaging approaches are needed to understand the mechanisms of disease initiation, and to develop novel therapies for benign prostatic hyperplasia. Long-term administration of both estradiol and testosterone in mice can result in prostatic enlargement and recapitulate several clinical components of lower urinary tract symptoms. Herein, we use longitudinal magnetic resonance imaging and histological analyses to quantify changes in prostatic volume, urethral volume, and genitourinary vascularization over time in response to estradiol-induced prostatic enlargement. Our data demonstrate significant prostatic enlargement by 12 weeks after treatment, with no detectable immune infiltration by macrophages or T- or B-cell populations. Importantly, the percentage of cell death, as measured by terminal deoxynucleotidyl transferase dUTP nick-end labeling, was significantly decreased in the prostatic epithelium of treated animals as compared to controls. We found no significant change in prostate cell proliferation in treated mice when compared to controls. These studies highlight the utility of magnetic resonance imaging to quantify changes in prostatic and urethral volumes over time. In conjunction with histological analyses, this approach has the high potential to enable mechanistic studies of initiation and progression of clinically relevant lower urinary tract symptoms. In addition, this model is tractable for investigation and testing of therapeutic interventions to ameliorate or potentially reverse prostatic enlargement.

MRI Findings After MRI-Guided Focal Laser Ablation of Prostate Cancer.

OBJECTIVE: The purpose of this study is to describe the quantitative and qualitative findings of multiparametric prostate MRI performed after MRI-guided focal laser ablation of prostate cancer. MATERIALS AND METHODS: A total of 27 consenting patients met the study inclusion criteria, which included but were not limited to the presence of clinical category T1c-T2a prostate cancer with a Gleason score of 7 or less, having undergone prostate biopsy before and after focal laser ablation, and having undergone MRI before ablation, immediately after ablation, and 3 and 12 months after ablation. Signal changes were evaluated both qualitatively and quantitatively and were then correlated with the results of subsequent biopsy performed at 3 and 12 months after ablation. RESULTS: MRI performed immediately after ablation revealed a hypovascular defect in the ablation zone, with patchy or bandlike decreased T2 signal most commonly noted at 3 months (in 66.7% of ablated lesions) and T2 scarring observed in most lesions (66.7%) at 12 months. Patchy or bandlike decreased apparent diffusion coefficient signal and scarlike changes were most prevalent at 3 months after ablation (50.0% of lesions), and these features remained the most commonly observed findings at 12 months after ablation (27.8% of lesions). At 12 months after ablation, 10 patients were found to have recurrent tumor, with three patients found to have persistent cancer when biopsy was performed at the ablation site. All postablation biopsy cases with positive results showed suspicious T2 and apparent diffusion coefficient characteristics, which were considered to be a well-defined nodular intermediate signal on both of these sequences. Two of the patients for whom positive biopsy findings were noted had focal enhancement of the ablation zone. A significant reduction in the forward volume transfer constant after ablation was found at the ablation site on follow-up examination. CONCLUSION: Multiparametric MRI can reveal postablation changes in the prostate and can be a valuable tool for monitoring patients who have undergone MRI-guided focal laser ablation.

Multiparametric MR Imaging of the Prostate after Treatment of Prostate Cancer.

The use of multiparametric magnetic resonance (MR) imaging in prostate cancer therapy is increasing, as newer treatment methods and management approaches emerge. The mainstays of therapy-radiation and surgery-are being supplemented (and even replaced) by novel focal therapy methods. Laser and ultrasonographic ablation, photodynamic therapy, electroporation, and cryoablation are the most common focal therapies, each with its own imaging findings. Typical ablation zones have a central focus of enhancement with peripheral rim enhancement; thus, dynamic contrast material-enhanced (DCE) MR imaging is the most important sequence for evaluation of treatment in the immediate posttherapeutic setting. Detection of recurrence can initiate salvage therapy, but recurrence can be difficult to detect on T2-weighted images, again necessitating DCE MR imaging and also diffusion-weighted imaging. Furthermore, the location of recurrence can vary depending on the therapy. With radiation therapy, the most common site of recurrence is the prior tumor site, whereas after prostatectomy, the recurrence usually occurs around the vesicoureteral anastomosis. Regarding management, there is an increased emphasis on watchful waiting and active surveillance, for which MR imaging has a critical role in both selection and follow-up of patients who undergo active surveillance. As MR imaging is being increasingly used for imaging suspected recurrence, it is important for radiologists to be familiar with the normal posttreatment findings and patterns and MR imaging findings of recurrence. ©RSNA, 2018.