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Aim: To determine the role of serial apparent diffusion coefficient (ADC) as a biomarker for response to neoadjuvant androgen deprivation therapy (nADT) followed by external beam radiation therapy (EBRT) in intermediate- to high-risk prostate cancer (PCa) patients., Methods: This Health Insurance Portability and Accountability Act (HIPAA)-compliant, institutional review board (IRB)-approved prospective study included 12 patients with intermediate- to high-risk PCa patients prior to nADT and EBRT, who underwent serial serum prostate-specific antigen (PSA) and multiparametric prostate magnetic resonance imaging (mpMRI) at baseline (BL), 8-weeks after nADT initiation (time point [TP]1), 6-weeks into EBRT delivery (TP2), and 6-months after nADT initiation (TP3). Tumour volume (tVOL) and tumour and normal tissue ADC (tADC and nlADC) were determined at all TPs. tADC and nlADC dynamics were correlated with post-treatment PSA using Pearson's correlation coefficient. Paired t-tests compared pre/post-treatment ADC., Results: There was a sequential decrease in PSA at all TPs, reaching their lowest values at TP3 post-treatment completion. Mean tADC increased significantly from baseline to TP1 (917.8 ± 107.7 × 10 -6 versus 1033.8 ± 139.3 × 10 -6 mm 2 /s; p<0.01), with no subsequent change at TP2 or TP3. Both percentage and absolute change in tADC from BL to TP1 correlated with post-treatment PSA (r=-0.666, r=-0.674; p=0.02). Post-treatment PSA in good responders (<0.1 ng/ml) versus poor responders (≥ 0.1 ng/ml) was associated with a greater increase in tADC from BL to TP1 (169.2 ± 122.4 × 10 -6 versus 22.9 ± 75.5 × 10 -6 mm 2 /s, p=0.03)., Conclusion: This pilot study demonstrates the potential for early ADC metrics as a biomarker of response to nADT and EBRT in intermediate to high-risk PCA., (Copyright © 2024 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.)

Accurate determination of the local stage of prostate cancer is crucial for treatment planning and prognosis. The primary objective of local staging is to distinguish between organ-confined and locally advanced disease, with the latter carrying a worse clinical prognosis. The presence of locally advanced disease features of prostate cancer, such as extra-prostatic extension, seminal vesicle invasion, and positive surgical margin, can impact the choice of treatment. Over the past decade, multiparametric MRI (mpMRI) has become the preferred imaging modality for the local staging of prostate cancer and has been shown to provide accurate information on the location and extent of disease. It has demonstrated superior performance compared to staging based on traditional clinical nomograms. Despite being a relatively new technique, mpMRI has garnered considerable attention and ongoing investigations. Therefore, in this review, we will discuss the current use of mpMRI on prostate cancer local staging., (Published by Elsevier Inc.)

Diffusion-weighted imaging is a dependable method for detection of clinically significant prostate cancer. In prostate tissue, there are several compartments that can be distinguished from each other, based on different water diffusion decay signals observed. Alterations in cell architecture, such as a relative increase in tumor infiltration and decrease in stroma, will influence the observed diffusion signal in a voxel due to impeded random motion of water molecules. The amount of restricted diffusion can be assessed quantitatively by measuring the apparent diffusion coefficient (ADC) value. This is traditionally calculated using a monoexponential decay formula represented by the slope of a line produced between the logarithm of signal intensity decay plotted against selected b-values. However, the choice and number of b-values and their distribution, has a significant effect on the measured ADC values. There have been many models that attempt to use higher-order functions to better describe the observed diffusion signal decay, requiring an increased number and range of b-values. While ADC can probe heterogeneity on a macroscopic level, there is a need to optimize advanced diffusion techniques to better interrogate prostate tissue microstructure. This could be of benefit in clinical challenges such as identifying sparse tumors in normal prostate tissue or better defining tumor margins. This paper reviews the principles of diffusion MRI and novel higher order diffusion signal analysis techniques to improve the detection of prostate cancer., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Fiona Fennessy receives support from: NIH (R01CA241817 and P41EB 028741), Stephan Maier receives support from: NIH (R01CA241817 and P41EB 028741), the Swedish Cancer Society; the Swedish Research Council (Vetenskapsrådet); the Swedish state under an agreement between the Swedish government and the country councils: the ALF agreement (ALFGBG-932648)., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Objectives: The Prostate Imaging Quality (PI-QUAL) score is a new metric to evaluate the diagnostic quality of multiparametric magnetic resonance imaging (MRI) of the prostate. This study assesses the impact of an intervention, namely a prostate MRI quality training lecture, on the participant's ability to apply PI-QUAL., Methods: Sixteen participants (radiologists, urologists, physicists, and computer scientists) of varying experience in reviewing diagnostic prostate MRI all assessed the image quality of ten examinations from different vendors and machines. Then, they attended a dedicated lecture followed by a hands-on workshop on MRI quality assessment using the PI-QUAL score. Five scans assessed by the participants were evaluated in the workshop using the PI-QUAL score for teaching purposes. After the course, the same participants evaluated the image quality of a new set of ten scans applying the PI-QUAL score. Results were assessed using receiver operating characteristic analysis. The reference standard was the PI-QUAL score assessed by one of the developers of PI-QUAL., Results: There was a significant improvement in average area under the curve for the evaluation of image quality from baseline (0.59 [95 % confidence intervals: 0.50-0.66]) to post-teaching (0.96 [0.92-0.98]), an improvement of 0.37 [0.21-0.41] (p < 0.001)., Conclusions: A teaching course (dedicated lecture + hands-on workshop) on PI-QUAL significantly improved the application of this scoring system to assess the quality of prostate MRI examinations., Key Points: • A significant improvement in the application of PI-QUAL for the assessment of prostate MR image quality was observed after an educational intervention. • Appropriate training on image quality can be delivered to those involved in the acquisition and interpretation of prostate MRI. • Further investigation will be needed to understand the impact on improving the acquisition of high-quality diagnostic prostate MR examinations., (© 2022. The Author(s).)

Objective: Assess radiologists' contribution to variation in clinically significant prostate cancer (csPCa) detection in patients with elevated prostate-specific antigen (PSA) and multiparametric MRI (mpMRI)., Methods: This institutional review board-approved, retrospective cohort study was performed at a tertiary, academic, National Cancer Institute-designated Comprehensive Cancer Center with a multidisciplinary prostate cancer program. Men undergoing mpMRI examinations from January 1, 2015, to December 31, 2019, with elevated PSA (≥4 ng/mL) and biopsy within 6 months pre- or post-MRI or prostatectomy within 6 months post-mpMRI were included. Univariate and multivariable hierarchical logistic regression assessed impact of patient, provider, mpMRI examination, mpMRI report, and pathology factors on the diagnosis of Grade Group ≥ 2 csPCa., Results: Study cohort included 960 MRIs in 928 men, mean age 64.0 years (SD ± 7.4), and 59.8% (555 of 928) had csPCa. Interpreting radiologist was not significant individually (P > .999) or combined with mpMRI ordering physician and physician performing biopsy or prostatectomy (P = .41). Prostate Imaging Reporting and Data System (PI-RADS) category 2 (odds ratio [OR] 0.18, P = .04), PI-RADS category 4 (OR 2.52, P < .001), and PI-RADS category 5 (OR 4.99, P < .001) assessment compared with no focal lesion; PSA density of 0.1 to 0.15 ng/mL/cc (OR 2.46, P < .001), 0.15 to 0.2 ng/mL/cc (OR 2.77, P < .001), or ≥0.2 ng/mL/cc (OR 4.52, P < .001); private insurance (reference = Medicare, OR 0.52, P = .001), and unambiguous extraprostatic extension on mpMRI (OR 2.94, P = .01) were independently associated with csPCa. PI-RADS 3 assessment (OR 1.18, P = .56), age (OR 0.99, P = .39), and African American race (OR 0.90, P = .75) were not., Discussion: Although there is known in-practice variation in radiologists' interpretation of mpMRI, in our multidisciplinary prostate cancer program we found no significant radiologist-attributable variation in csPCa detection., (Copyright © 2022 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

The role of multiparametric MRI in diagnosis, staging and treatment planning for prostate cancer is well established. However, there remain several challenges to widespread adoption. One such challenge is the duration and cost of the examination. Abbreviated exams omitting contrast-enhanced sequences may help address this challenge. In this review, we will discuss the rationale for biparametric MRI for detection and characterization of clinically significant prostate cancer prior to biopsy and synthesize the published literature. We will weigh up the advantages and disadvantages to this approach and lay out a conceptual cost/benefit analysis regarding adoption of biparametric MRI.

Objectives: The objectives of this exploratory study were to investigate the feasibility of multidimensional diffusion magnetic resonance imaging (MddMRI) in assessing diffusion heterogeneity at both a macroscopic and microscopic level in prostate cancer (PCa)., Materials and Methods: Informed consent was obtained from 46 subjects who underwent 3.0-T prostate multiparametric MRI, complemented with a prototype spin echo-based MddMRI sequence in this institutional review board-approved study. Prostate cancer tumors and comparative normal tissue from each patient were contoured on both apparent diffusion coefficient and MddMRI-derived mean diffusivity (MD) maps (from which microscopic diffusion heterogeneity [MKi] and microscopic diffusion anisotropy were derived) using 3D Slicer. The discriminative ability of MddMRI-derived parameters to differentiate PCa from normal tissue was determined using the Friedman test. To determine if tumor diffusion heterogeneity is similar on macroscopic and microscopic scales, the linear association between SD of MD and mean MKi was estimated using robust regression (bisquare weighting). Hypothesis testing was 2 tailed; P values less than 0.05 were considered statistically significant., Results: All MddMRI-derived parameters could distinguish tumor from normal tissue in the fixed-effects analysis (P < 0.0001). Tumor MKi was higher (P < 0.05) compared with normal tissue (median, 0.40; interquartile range, 0.29-0.52 vs 0.20-0.18; 0.25), as was tumor microscopic diffusion anisotropy (0.55; 0.36-0.81 vs 0.20-0.15; 0.28). The MKi could not be predicted (no significant association) by SD of MD. There was a significant correlation between tumor volume and SD of MD (R2 = 0.50, slope = 0.008 μm2/ms per millimeter, P < 0.001) but not between tumor volume and MKi., Conclusions: This explorative study demonstrates that MddMRI provides novel information on MKi and microscopic anisotropy, which differ from measures at the macroscopic level. MddMRI has the potential to characterize tumor tissue heterogeneity at different spatial scales., Competing Interests: Conflicts of interest and sources of funding: F.M.F., C.M.T., and S.E.M. are funded through NIH P41EB 015898, NIH P41EB 028741, and NIH R01CA241817. F.S. and C.-F.W. are funded through NIH P41EB 015902. For the remaining authors, no conflicts or sources of funding were declared., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: This multicenter randomized phase 2 trial investigates the impact of intense androgen deprivation on radical prostatectomy pathologic response and radiographic and tissue biomarkers in localized prostate cancer (NCT02903368)., Materials and Methods: Eligible patients had a Gleason score ≥4+3=7, prostate specific antigen >20 ng/mL or T3 disease and lymph nodes <20 mm. In Part 1, patients were randomized 1:1 to apalutamide, abiraterone acetate, prednisone and leuprolide (AAPL) or abiraterone, prednisone, leuprolide (APL) for 6 cycles (1 cycle=28 days) followed by radical prostatectomy. Surgical specimens underwent central review. The primary end point was the rate of pathologic complete response or minimum residual disease (minimum residual disease, tumor ≤5 mm). Secondary end points included prostate specific antigen response, positive margin rate and safety. Magnetic resonance imaging and tissue biomarkers of pathologic outcomes were explored., Results: The study enrolled 118 patients at 4 sites. Median age was 61 years and 94% of patients had high-risk disease. The combined pathologic complete response or minimum residual disease rate was 22% in the AAPL arm and 20% in the APL arm (difference: 1.5%; 1-sided 95% CI -11%, 14%; 1-sided p=0.4). No new safety signals were observed. There was low concordance and correlation between posttherapy magnetic resonance imaging assessed and pathologically assessed tumor volume. PTEN-loss, ERG positivity and presence of intraductal carcinoma were associated with extensive residual tumor., Conclusions: Intense neoadjuvant hormone therapy in high-risk prostate cancer resulted in favorable pathologic responses (tumor < 5 mm) in 21% of patients. Pathologic responses were similar between treatment arms. Part 2 of this study will investigate the impact of adjuvant hormone therapy on biochemical recurrence.

Currently there is a lot of interest in the use of a "biparametric" or "abbreviated" prostate MR protocol, which usually refers to removal of the dynamic contrast-enhanced (DCE) MRI, in the detection of clinically significant prostate cancer. In this article we describe the benefits of DCE as part of the PI-RADS lexicon, with particular reference to its role in PI-RADS V2 category 3 peripheral zone lesions. We also discuss the benefits of triplanar T2-weighted images, and finally discuss how a mpMRI protocol is of benefit in prostate cancer staging, in evaluating for local disease recurrence, and as a biomarker for neoadjuvant therapy response.

Rationale and Objectives: To explore a role for multiparametric MRI (mpMRI) as a biomarker of response to neoadjuvant androgen deprivation therapy (ADT) for prostate cancer (PCa)., Materials and Methods: This prospective study was approved by the institutional review board and was HIPAA compliant. Eight patients with localized PCa had a baseline mpMRI, repeated after 6-months of ADT, followed by prostatectomy. mpMRI indices were extracted from tumor and normal regions of interest (TROI/NROI). Residual cancer burden (RCB) was measured on mpMRI and on the prostatectomy specimen. Paired t-tests compared TROI/NROI mpMRI indices and pre/post-treatment TROI mpMRI indices. Spearman's rank tested for correlations between MRI/pathology-based RCB, and between pathological RCB and mpMRI indices., Results: At baseline, TROI apparent diffusion coefficient (ADC) was lower and dynamic contrast enhanced (DCE) metrics were higher, compared to NROI (ADC: 806 ± 137 × 10 -6 vs. 1277 ± 213 × 10 -6 mm 2 /sec, p = 0.0005; K trans : 0.346 ± 0.16 vs. 0.144 ± 0.06 min -1 , p = 0.002; AUC 90 : 0.213 ± 0.08 vs. 0.11 ± 0.03, p = 0.002). Post-treatment, there was no change in TROI ADC, but a decrease in TROI K trans (0.346 ± 0.16 to 0.188 ± 0.08 min -1 ; p = 0.02) and AUC 90 (0.213 ± 0.08 to 0.13 ± 0.06; p = 0.02). Tumor volume decreased with ADT. There was no difference between mpMRI-based and pathology-based RCB, which positively correlated (⍴ = 0.74-0.81, p < 0.05). Pathology-based RCB positively correlated with post-treatment DCE metrics (⍴ = 0.76-0.70, p < 0.05) and negatively with ADC (⍴ = -0.79, p = 0.03)., Conclusion: Given the heterogeneity of PCa, an individualized approach to ADT may maximize potential benefit. This pilot study suggests that mpMRI may serve as a biomarker of ADT response and as a surrogate for RCB at prostatectomy., (Copyright © 2019 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Aim: To compare the diagnostic performance of prostate magnetic resonance imaging (MRI) with an endorectal coil (ERC) to performance without an ERC using either body-array (BAC) or pelvic phased-array coil (PAC) in staging T3 prostate cancer., Materials and Methods: An electronic search of the PUBMED and EMBASE databases was performed until 10 October 2018 to identify studies performing a head-to-head comparison of prostate MRI using a 1.5 or 3 T magnet with an ERC and with a BAC/PAC for staging T3 prostate cancer. Pooled sensitivity and specificity of all studies were plotted in a hierarchical summary receiver operating characteristic plot. The diagnostic performance of the two techniques in staging T3 disease was evaluated using bivariate random-effects meta-analysis., Results: Eight studies comparing head-to-head prostate MRI with an ERC and with a BAC/PAC were identified of which six studies compared the diagnostic performance. The pooled sensitivity and specificity of MRI with an ERC for detecting T3a, T3b and T3a+b was 53% and 95%; 52% and 92%; 72% and 65% respectively. For MRI with a BAC/PAC these were 34%, and 95%; 45% and 94%; 70% and 66%. There was no statistical difference between an ERC and a BAC/PAC in terms of sensitivity (p=0.41) and specificity (p=0.63) for T3a. The area under the receiver operating characteristic (AUROC) curve for T3a, T3b and T3a+b was 0.830, 0.901, 0.741 for an ERC and 0.790, 0.645, 0.711 for BAC, respectively., Conclusion: There is no significant difference in the diagnostic performance of MRI of prostate with an ERC and with a BAC/PAC in staging T3 prostate cancer., (Copyright © 2019 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.)

Objective: Accurate biopsy sampling of the suspected lesions is critical for the diagnosis and clinical management of prostate cancer. Transperineal in-bore MRI-guided prostate biopsy (tpMRgBx) is a targeted biopsy technique that was shown to be safe, efficient, and accurate. Our goal was to develop an open source software platform to support evaluation, refinement, and translation of this biopsy approach., Methods: We developed SliceTracker, a 3D Slicer extension to support tpMRgBx. We followed modular design of the implementation to enable customization of the interface and interchange of image segmentation and registration components to assess their effect on the processing time, precision, and accuracy of the biopsy needle placement. The platform and supporting documentation were developed to enable the use of software by an operator with minimal technical training to facilitate translation. Retrospective evaluation studied registration accuracy, effect of the prostate segmentation approach, and re-identification time of biopsy targets. Prospective evaluation focused on the total procedure time and biopsy targeting error (BTE)., Results: Evaluation utilized data from 73 retrospective and ten prospective tpMRgBx cases. Mean landmark registration error for retrospective evaluation was 1.88 ± 2.63 mm, and was not sensitive to the approach used for prostate gland segmentation. Prospectively, we observed target re-identification time of 4.60 ± 2.40 min and BTE of 2.40 ± 0.98 mm., Conclusion: SliceTracker is modular and extensible open source platform for supporting image processing aspects of the tpMRgBx procedure. It has been successfully utilized to support clinical research procedures at our site.

Rationale and Objectives: Analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging is notable for the variability of calculated parameters. The purpose of this study was to evaluate the level of measurement variability and error/variability due to modeling in DCE magnetic resonance imaging parameters., Materials and Methods: Two prostate DCE scans were performed on 11 treatment-naïve patients with suspected or confirmed prostate peripheral zone cancer within an interval of less than two weeks. Tumor-suspicious and normal-appearing regions of interest (ROI) in the prostate peripheral zone were segmented. Different Tofts-Kety based models and different arterial input functions, with and without bolus arrival time (BAT) correction, were used to extract pharmacokinetic parameters. The percent repeatability coefficient (%RC) of fitted model parameters K trans , v e , and k ep was calculated. Paired t-tests comparing parameters in tumor-suspicious ROIs and in normal-appearing tissue evaluated each parameter's sensitivity to pathology., Results: Although goodness-of-fit criteria favored the four-parameter extended Tofts-Kety model with the BAT correction included, the simplest two-parameter Tofts-Kety model overall yielded the best repeatability scores. The best %RC in the tumor-suspicious ROI was 63% for k ep , 28% for v e , and 83% for K trans . The best p values for discrimination between tissues were p <10 -5 for k ep and K trans , and p = 0.11 for v e . Addition of the BAT correction to the models did not improve repeatability., Conclusion: The parameter k ep , using an arterial input functions directly measured from blood signals, was more repeatable than K trans . Both K trans and k ep values were highly discriminatory between healthy and diseased tissues in all cases. The parameter v e had high repeatability but could not distinguish the two tissue types., (Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

In this study we assessed the repeatability of radiomics features on small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of radiomics is that quantitative image-based features can serve as biomarkers for detecting and characterizing disease. For such biomarkers to be useful, repeatability is a basic requirement, meaning its value must remain stable between two scans, if the conditions remain stable. We investigated repeatability of radiomics features under various preprocessing and extraction configurations including various image normalization schemes, different image pre-filtering, and different bin widths for image discretization. Although we found many radiomics features and preprocessing combinations with high repeatability (Intraclass Correlation Coefficient > 0.85), our results indicate that overall the repeatability is highly sensitive to the processing parameters. Neither image normalization, using a variety of approaches, nor the use of pre-filtering options resulted in consistent improvements in repeatability. We urge caution when interpreting radiomics features and advise paying close attention to the processing configuration details of reported results. Furthermore, we advocate reporting all processing details in radiomics studies and strongly recommend the use of open source implementations.

Diagnosis of prostate cancer is based on histologic evaluation of tumor architecture using a system known as the "Gleason score." This diagnostic paradigm, while the standard of care, is time-consuming, shows intraobserver variability, and provides no information about the altered metabolic pathways, which result in altered tissue architecture. Characterization of the molecular composition of prostate cancer and how it changes with respect to the Gleason score (GS) could enable a more objective and faster diagnosis. It may also aid in our understanding of disease onset and progression. In this work, we present mass spectrometry imaging for identification and mapping of lipids and metabolites in prostate tissue from patients with known prostate cancer with GS from 6 to 9. A gradient of changes in the intensity of various lipids was observed, which correlated with increasing GS. Interestingly, these changes were identified in both regions of high tumor cell density, and in regions of tissue that appeared histologically benign, possibly suggestive of precancerous metabolomic changes. A total of 31 lipids, including several phosphatidylcholines, phosphatidic acids, phosphatidylserines, phosphatidylinositols, and cardiolipins were detected with higher intensity in GS (4+3) compared with GS (3+4), suggesting they may be markers of prostate cancer aggression. Results obtained through mass spectrometry imaging studies were subsequently correlated with a fast, ambient mass spectrometry method for potential use as a clinical tool to support image-guided prostate biopsy. IMPLICATIONS: In this study, we suggest that metabolomic differences between prostate cancers with different Gleason scores can be detected by mass spectrometry imaging., (©2019 American Association for Cancer Research.)

Purpose: PI-RADS v2 dictates that dynamic contrast-enhanced (DCE) imaging be used to further classify peripheral zone (PZ) cases that receive a diffusion-weighted imaging equivocal score of three (DWI3), a positive DCE resulting in an increase in overall assessment score to a four, indicative of clinically significant prostate cancer (csPCa). However, the accuracy of DCE in predicting csPCa in DWI3 PZ cases is unknown. This study sought to determine the frequency with which DCE changes the PI-RADS v2 DWI3 assessment category, and to determine the overall accuracy of DCE-MRI in equivocal PZ DWI3 lesions., Materials and Methods: This is a retrospective study of patients with pathologically proven PCa who underwent prostate mpMRI at 3T and subsequent radical prostatectomy. PI-RADS v2 assessment categories were determined by a radiologist, aware of a diagnosis of PCa, but blinded to final pathology. csPCa was defined as a Gleason score ≥ 7 or extra prostatic extension at pathology review. Performance characteristics and diagnostic accuracy of DCE in assigning a csPCa assessment in PZ lesions were calculated., Results: A total of 271 men with mean age of 59 ± 6 years mean PSA 6.7 ng/mL were included. csPCa was found in 212/271 (78.2%) cases at pathology, 209 of which were localized in the PZ. DCE was necessary to further classify (45/209) of patients who received a score of DWI3. DCE was positive in 29/45 cases, increasing the final PI-RADS v2 assessment category to a category 4, with 16/45 having a negative DCE. When compared with final pathology, DCE was correct in increasing the assessment category in 68.9% ± 7% (31/45) of DWI3 cases., Conclusion: DCE increases the accuracy of detection of csPCa in the majority of PZ lesions that receive an equivocal PI-RADS v2 assessment category using DWI.

Purpose: To compare the predictive roles of qualitative (PI-RADSv2) and quantitative assessment (ADC metrics), in differentiating Gleason pattern (GP) 3 + 4 from the more aggressive GP 4 + 3 prostate cancer (PCa) using radical prostatectomy (RP) specimen as the reference standard., Methods: We retrospectively identified treatment-naïve peripheral (PZ) and transitional zone (TZ) Gleason Score 7 PCa patients who underwent multiparametric 3T prostate MRI (DWI with b value of 0,1400 and where unavailable, 0,500) and subsequent RP from 2011 to 2015. For each lesion identified on MRI, a PI-RADSv2 score was assigned by a radiologist blinded to pathology data. A PI-RADSv2 score ≤ 3 was defined as "low risk," a PI-RADSv2 score ≥ 4 as "high risk" for clinically significant PCa. Mean tumor ADC (ADC T ), ADC of adjacent normal tissue (ADC N ), and ADC ratio (ADC T /ADC N ) were calculated. Stepwise regression analysis using tumor location, ADC T and ADC ratio , b value, low vs. high PI-RADSv2 score was performed to differentiate GP 3 + 4 from 4 + 3., Results: 119 out of 645 cases initially identified met eligibility requirements. 76 lesions were GP 3 + 4, 43 were 4 + 3. ADC ratio was significantly different between the two GP groups (p = 0.001). PI-RADSv2 score ("low" vs. "high") was not significantly different between the two GP groups (p = 0.17). Regression analysis selected ADC T (p = 0.03) and ADC ratio (p = 0.0007) as best predictors to differentiate GP 4 + 3 from 3 + 4. Estimated sensitivity, specificity, and accuracy of the predictive model in differentiating GP 4 + 3 from 3 + 4 were 37, 82, and 66%, respectively., Conclusions: ADC metrics could differentiate GP 3 + 4 from 4 + 3 PCa with high specificity and moderate accuracy while PI-RADSv2, did not differentiate between these patterns.

Purpose: To compare diagnostic performance of PI-RADSv2 with ADC parameters to identify clinically significant prostate cancer (csPC) and to determine the impact of csPC definitions on diagnostic performance of ADC and PI-RADSv2., Methods: We retrospectively identified treatment-naïve pathology-proven peripheral zone PC patients who underwent 3T prostate MRI, using high b-value diffusion-weighted imaging from 2011 to 2015. Using 3D slicer, areas of suspected tumor (T) and normal tissue (N) on ADC (b = 0, 1400) were outlined volumetrically. Mean ADC T , mean ADC N , ADC ratio (ADC T /ADC N ) were calculated. PI-RADSv2 was assigned. Three csPC definitions were used: (A) Gleason score (GS) ≥ 4 + 3; (B) GS ≥ 3 + 4; (C) MRI-based tumor volume >0.5 cc. Performances of ADC parameters and PI-RADSv2 in identifying csPC were measured using nonparametric comparison of receiver operating characteristic curves using the area under the curve (AUC)., Results: Eighty five cases met eligibility requirements. Diagnostic performances (AUC) in identifying csPC using three definitions were: (A) ADC T (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) ADC T (0.86) was higher than ADC ratio (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than ADC ratio (0.56, p = 0.02). ADC T performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). ADC ratio performed better when csPC was defined by A versus C (p = 0.01). PI-RADSv2 performance was not affected by csPC definition., Conclusions: When csPC was defined by GS, ADC parameters provided better csPC discrimination than PI-RADSv2, with ADC T providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than ADC ratio . csPC definition did not affect PI-RADSv2 diagnostic performance.

Objectives: The aim of this study was to evaluate the repeatability of a region of interest (ROI) volume and mean apparent diffusion coefficient (ADC) in standard-of-care 3 T multiparametric magnetic resonance imaging (mpMRI) of the prostate obtained with the use of endorectal coil., Materials and Methods: This prospective study was Health Insurance Portability and Accountability Act compliant, with institutional review board approval and written informed consent. Men with confirmed or suspected treatment-naive prostate cancer scheduled for mpMRI were offered a repeat mpMRI within 2 weeks. Regions of interest corresponding to the whole prostate gland, the entire peripheral zone (PZ), normal PZ, and suspected tumor ROI (tROI) on axial T2-weighted, dynamic contrast-enhanced subtract, and ADC images were annotated and assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2. Repeatability of the ROI volume for each of the analyzed image types and mean ROI ADC was summarized with repeatability coefficient (RC) and RC%., Results: A total of 189 subjects were approached to participate in the study. Of 40 patients that gave initial agreement, 15 men underwent 2 mpMRI examinations and completed the study. Peripheral zone tROIs were identified in 11 subjects. Tumor ROI volume was less than 0.5 mL in 8 of 11 subjects. PI-RADS categories were identical between baseline-repeat studies in 11/15 subjects and differed by 1 point in 4/15. Peripheral zone tROI volume RC (RC%) was 233 mm (71%) on axial T2-weighted, 422 mm (112%) on ADC, and 488 mm (119%) on dynamic contrast-enhanced subtract. Apparent diffusion coefficient ROI mean RC (RC%) were 447 × 10 mm/s (42%) in PZ tROI and 471 × 10 mm/s (30%) in normal PZ. Significant difference in repeatability of the tROI volume across series was observed (P < 0.005). The mean ADC RC% was lower than volume RC% for tROI ADC (P < 0.05)., Conclusions: PI-RADS v2 overall assessment was highly repeatable. Multiparametric magnetic resonance imaging sequences differ in volume measurement repeatability. The mean tROI ADC is more repeatable compared with tROI volume in ADC. Repeatability of prostate ADC is comparable with that in other abdominal organs.

Objective: To determine if tumor cell density and percentage of Gleason pattern within an outlined volumetric tumor region of interest (TROI) on whole-mount pathology (WMP) correlate with apparent diffusion coefficient (ADC) values on corresponding TROIs outlined on pre-operative MRI., Methods: Men with biopsy-proven prostate adenocarcinoma undergoing multiparametric MRI (mpMRI) prior to prostatectomy were consented to this prospective study. WMP and mpMRI images were viewed using 3D Slicer and each TROI from WMP was contoured on the high b-value ADC maps (b0, 1400). For each TROI outlined on WMP, TCD (tumor cell density) and the percentage of Gleason pattern 3, 4, and 5 were recorded. The ADC mean , ADC 10th percentile , ADC 90th percentile , and ADC ratio were also calculated in each case from the ADC maps using 3D Slicer., Results: Nineteen patients with 21 tumors were included in this study. ADC mean values for TROIs were 944.8 ± 327.4 vs. 1329.9 ± 201.6 mm 2 /s for adjacent non-neoplastic prostate tissue (p < 0.001). ADC mean , ADC 10th percentile , and ADC ratio values for higher grade tumors were lower than those of lower grade tumors (mean 809.71 and 1176.34 mm 2 /s, p = 0.014; 10th percentile 613.83 and 1018.14 mm 2 /s, p = 0.009; ratio 0.60 and 0.94, p = 0.005). TCD and ADC mean (ρ = -0.61, p = 0.005) and TCD and ADC 10th percentile (ρ = -0.56, p = 0.01) were negatively correlated. No correlation was observed between percentage of Gleason pattern and ADC values., Conclusion: DWI MRI can characterize focal prostate cancer using ADC ratio , ADC 10th percentile , and ADC mean , which correlate with pathological tumor cell density.

The most recent edition of the prostate imaging reporting and data system (PI-RADS version 2) was developed based on expert consensus of the international working group on prostate cancer. It provides the minimum acceptable technical standards for MR image acquisition and suggests a structured method for multiparametric prostate MRI (mpMRI) reporting. T1-weighted, T2-weighted (T2W), diffusion-weighted (DWI), and dynamic contrast-enhanced (DCE) imaging are the suggested sequences to include in mpMRI. The PI-RADS version 2 scoring system enables the reader to assess and rate all focal lesions detected at mpMRI to determine the likelihood of a clinically significant cancer. According to PI-RADS v2, a lesion with a Gleason score ≥7, volume >0.5 cc, or extraprostatic extension is considered clinically significant. PI-RADS v2 uses the concept of a dominant MR sequence based on zonal location of the lesion rather than summing each component score, as was the case in version 1. The dominant sequence in the peripheral zone is DWI and the corresponding apparent diffusion coefficient (ADC) map, with a secondary role for DCE in equivocal cases (PI-RADS score 3). For lesions in the transition zone, T2W images are the dominant sequence with DWI/ADC images playing a supporting role in the case of an equivocal lesion., Competing Interests: The authors declare no conflict of interest.

A biomarker of cancer aggressiveness, such as hypoxia, could substantially impact treatment decisions in the prostate, especially radiation therapy, by balancing treatment morbidity (urinary incontinence, erectile dysfunction, etc.) against mortality. R2 (*) mapping with Mono-Exponential (ME) decay modeling has shown potential for identifying areas of prostate cancer hypoxia at 1.5T. However, Gaussian deviations from ME decay have been observed in other tissues at 3T. The purpose of this study is to assess whether gradient-echo signal decays are better characterized by a standard ME decay model, or a Gaussian Augmentation of the Mono-Exponential (GAME) decay model, in the prostate at 3T. Multi-gradient-echo signals were acquired on 20 consecutive patients with a clinical suspicion of prostate cancer undergoing MR-guided prostate biopsies. Data were fitted with both ME and GAME models. The information contents of these models were compared using Akaike's information criterion (second order, AICC ), in skeletal muscle, the prostate central gland (CG), and peripheral zone (PZ) regions of interest (ROIs). The GAME model had higher information content in 30% of the prostate on average (across all patients and ROIs), covering up to 67% of cancerous PZ ROIs, and up to 100% of cancerous CG ROIs (in individual patients). The higher information content of GAME became more prominent in regions that would be assumed hypoxic using ME alone, reaching 50% of the PZ and 70% of the CG as ME R2 (*) approached 40 s(-1) . R2 (*) mapping may have important applications in MRI; however, information lost due to modeling could mask differences in parameters due to underlying tissue anatomy or physiology. The GAME model improves characterization of signal behavior in the prostate at 3T, and may increase the potential for determining correlates of fit parameters with biomarkers, for example of oxygenation status., (Copyright © 2016 John Wiley & Sons, Ltd.)

Accurate pharmacokinetic (PK) modeling of dynamic contrast enhanced MRI (DCE-MRI) in prostate cancer (PCa) requires knowledge of the concentration time course of the contrast agent in the feeding vasculature, the so-called arterial input function (AIF). The purpose of this study was to compare AIF choice in differentiating peripheral zone PCa from non-neoplastic prostatic tissue (NNPT), using PK analysis of high temporal resolution prostate DCE-MRI data and whole-mount pathology (WMP) validation. This prospective study was performed in 30 patients who underwent multiparametric endorectal prostate MRI at 3.0T and WMP validation. PCa foci were annotated on WMP slides and MR images using 3D Slicer. Foci ≥0.5cm(3) were contoured as tumor regions of interest (TROIs) on subtraction DCE (early-arterial - pre-contrast) images. PK analyses of TROI and NNPT data were performed using automatic AIF (aAIF) and model AIF (mAIF) methods. A paired t-test compared mean and 90th percentile (p90) PK parameters obtained with the two AIF approaches. Receiver operating characteristic (ROC) analysis determined diagnostic accuracy (DA) of PK parameters. Logistic regression determined correlation between PK parameters and histopathology. Mean TROI and NNPT PK parameters were higher using aAIF vs. mAIF (p<0.05). There was no significant difference in DA between AIF methods: highest for p90 volume transfer constant (K(trans)) (aAIF differences in the area under the ROC curve (Az) = 0.827; mAIF Az=0.93). Tumor cell density correlated with aAIF K(trans) (p=0.03). Our results indicate that DCE-MRI using both AIF methods is excellent in discriminating PCa from NNPT. If quantitative DCE-MRI is to be used as a biomarker in PCa, the same AIF method should be used consistently throughout the study., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objectives: To evaluate the performance of T2 mapping in discriminating prostate cancer from normal prostate tissue in the peripheral zone using a practical reduced field-of-view MRI sequence requiring less than 3 minutes of scan time., Materials and Methods: Thirty-six patients with biopsy-proven peripheral zone prostate cancer without prior treatment underwent routine multiparametric MRI at 3.0T with an endorectal coil. An Inner-Volume Carr-Purcell-Meiboom-Gill imaging sequence that required 2.8 minutes to obtain data for quantitative T2 mapping covering the entire prostate gland was added to the routine multiparametric protocol. Suspected cancer (SC) and suspected healthy (SH) tissue in the peripheral zone were identified in consensus by three radiologists and were correlated with available biopsy results. Differences in mean T2 values in SC and SH regions-of-interest (ROIs) were tested for significance using unpaired Student's two-tailed t-test. The area under the receiver operating characteristic curve was used to assess the optimal threshold T2 value for cancer discrimination., Results: ROI analyses revealed significantly (p<0.0001) shorter T2 values in SC (85.4±12.3ms) compared to SH (169.6±38.7ms). An estimated T2 threshold of 99ms yielded a sensitivity of 92% and a specificity of 97% for prostate cancer discrimination., Conclusions: Quantitative values derived from this clinically practical T2-mapping sequence allow high precision discrimination between healthy and cancerous peripheral zone in the prostate., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Rationale and Objectives: Development of imaging biomarkers often relies on their correlation with histopathology. Our aim was to compare two approaches for correlating pathology to multiparametric magnetic resonance (MR) imaging (mpMRI) for localization and quantitative assessment of prostate cancer (PCa) index tumor using whole mount (WM) pathology (WMP) as the reference., Materials and Methods: Patients (N = 30) underwent mpMRI that included diffusion-weighted imaging and dynamic contrast-enhanced (DCE) MRI at 3 T before radical prostatectomy (RP). RP specimens were processed using WM technique (WMP) and findings summarized in a standard surgical pathology report (SPR). Histology index tumor volumes (HTVs) were compared to MR tumor volumes (MRTVs) using two approaches for index lesion identification on mpMRI using annotated WMP slides as the reference (WMP) and using routine SPR as the reference. Consistency of index tumor localization, tumor volume, and mean values of the derived quantitative parameters (mean apparent diffusion coefficient [ADC], K(trans), and ve) were compared., Results: Index lesions from 16 of 30 patients met the selection criteria. There was WMP/SRP agreement in index tumor in 13 of 16 patients. ADC-based MRTVs were larger (P < .05) than DCE-based MRTVs. ADC MRTVs were smaller than HTV (P < .005). There was a strong correlation between HTV and MRTV (Pearson ρ > 0.8; P < .05). No significant differences were observed in the mean values of K(trans) and ADC between the WMP and SPR., Conclusions: WMP correlation is superior to SPR for accurate localization of all index lesions. The use of WMP is however not required to distinguish significant differences of mean values of quantitative MRI parameters within tumor volume., (Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.)

Purpose: To determine the detection rate, clinical relevance, Gleason grade, and location of prostate cancer ( PCa prostate cancer ) diagnosed with and the safety of an in-bore transperineal 3-T magnetic resonance (MR) imaging-guided prostate biopsy in a clinically heterogeneous patient population., Materials and Methods: This prospective retrospectively analyzed study was HIPAA compliant and institutional review board approved, and informed consent was obtained. Eighty-seven men (mean age, 66.2 years ± 6.9) underwent multiparametric endorectal prostate MR imaging at 3 T and transperineal MR imaging-guided biopsy. Three subgroups of patients with at least one lesion suspicious for cancer were included: men with no prior PCa prostate cancer diagnosis, men with PCa prostate cancer who were undergoing active surveillance, and men with treated PCa prostate cancer and suspected recurrence. Exclusion criteria were prior prostatectomy and/or contraindication to 3-T MR imaging. The transperineal MR imaging-guided biopsy was performed in a 70-cm wide-bore 3-T device. Overall patient biopsy outcomes, cancer detection rates, Gleason grade, and location for each subgroup were evaluated and statistically compared by using χ(2) and one-way analysis of variance followed by Tukey honestly significant difference post hoc comparisons., Results: Ninety biopsy procedures were performed with no serious adverse events, with a mean of 3.7 targets sampled per gland. Cancer was detected in 51 (56.7%) men: 48.1% (25 of 52) with no prior PCa prostate cancer , 61.5% (eight of 13) under active surveillance, and 72.0% (18 of 25) in whom recurrence was suspected. Gleason pattern 4 or higher was diagnosed in 78.1% (25 of 32) in the no prior PCa prostate cancer and active surveillance groups. Gleason scores were not assigned in the suspected recurrence group. MR targets located in the anterior prostate had the highest cancer yield (40 of 64, 62.5%) compared with those for the other parts of the prostate (P < .001)., Conclusion: In-bore 3-T transperineal MR imaging-guided biopsy, with a mean of 3.7 targets per gland, allowed detection of many clinically relevant cancers, many of which were located anteriorly.

Background: Prostate volume can affect whether patients qualify for brachytherapy (desired size ≥20 mL and ≤60 mL) and/or active surveillance (desired PSA density ≤0.15 for very low risk disease). This study examines variability in prostate volume measurements depending on imaging modality used (ultrasound versus MRI) and volume calculation technique (contouring versus ellipsoid) and quantifies the impact of this variability on treatment recommendations for men with favorable-risk prostate cancer., Methods: We examined 70 patients who presented consecutively for consideration of brachytherapy for favorable-risk prostate cancer who had volume estimates by three methods: contoured axial ultrasound slices, ultrasound ellipsoid (height × width × length × 0.523) calculation, and endorectal coil MRI (erMRI) ellipsoid calculation., Results: Average gland size by the contoured ultrasound, ellipsoid ultrasound, and erMRI methods were 33.99, 37.16, and 39.62 mLs, respectively. All pairwise comparisons between methods were statistically significant (all p < 0.015). Of the 66 patients who volumetrically qualified for brachytherapy on ellipsoid ultrasound measures, 22 (33.33%) did not qualify on ellipsoid erMRI or contoured ultrasound measures. 38 patients (54.28%) had PSA density ≤0.15 ng/dl as calculated using ellipsoid ultrasound volumes, compared to 34 (48.57%) and 38 patients (54.28%) using contoured ultrasound and ellipsoid erMRI volumes, respectively., Conclusions: The ultrasound ellipsoid and erMRI ellipsoid methods appeared to overestimate ultrasound contoured volume by an average of 9.34% and 16.57% respectively. 33.33% of those who qualified for brachytherapy based on ellipsoid ultrasound volume would be disqualified based on ultrasound contoured and/or erMRI ellipsoid volume. As treatment recommendations increasingly rely on estimates of prostate size, clinicians must consider method of volume estimation.

Multi-parametric Magnetic Resonance Imaging, and specifically Dynamic Contrast Enhanced (DCE) MRI, play increasingly important roles in detection and staging of prostate cancer (PCa). One of the actively investigated approaches to DCE MRI analysis involves pharmacokinetic (PK) modeling to extract quantitative parameters that may be related to microvascular properties of the tissue. It is well-known that the prescribed arterial blood plasma concentration (or Arterial Input Function, AIF) input can have significant effects on the parameters estimated by PK modeling. The purpose of our study was to investigate such effects in DCE MRI data acquired in a typical clinical PCa setting. First, we investigated how the choice of a semi-automated or fully automated image-based individualized AIF (iAIF) estimation method affects the PK parameter values; and second, we examined the use of method-specific averaged AIF (cohort-based, or cAIF) as a means to attenuate the differences between the two AIF estimation methods. Two methods for automated image-based estimation of individualized (patient-specific) AIFs, one of which was previously validated for brain and the other for breast MRI, were compared. cAIFs were constructed by averaging the iAIF curves over the individual patients for each of the two methods. Pharmacokinetic analysis using the Generalized kinetic model and each of the four AIF choices (iAIF and cAIF for each of the two image-based AIF estimation approaches) was applied to derive the volume transfer rate (K(trans)) and extravascular extracellular volume fraction (ve) in the areas of prostate tumor. Differences between the parameters obtained using iAIF and cAIF for a given method (intra-method comparison) as well as inter-method differences were quantified. The study utilized DCE MRI data collected in 17 patients with histologically confirmed PCa. Comparison at the level of the tumor region of interest (ROI) showed that the two automated methods resulted in significantly different (p<0.05) mean estimates of ve, but not of K(trans). Comparing cAIF, different estimates for both ve, and K(trans) were obtained. Intra-method comparison between the iAIF- and cAIF-driven analyses showed the lack of effect on ve, while K(trans) values were significantly different for one of the methods. Our results indicate that the choice of the algorithm used for automated image-based AIF determination can lead to significant differences in the values of the estimated PK parameters. K(trans) estimates are more sensitive to the choice between cAIF/iAIF as compared to ve, leading to potentially significant differences depending on the AIF method. These observations may have practical consequences in evaluating the PK analysis results obtained in a multi-site setting., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Background: Intermediate end points are desirable to expedite the integration of neoadjuvant systemic therapy into the treatment strategy for high-risk localized prostate cancer. Endorectal magnetic resonance imaging at 1.5 Tesla (1.5T erMRI) response has been utilized as an end point in neoadjuvant trials but has not been correlated with clinical outcomes., Methods: Data were pooled from two trials exploring neoadjuvant chemotherapy in high-risk localized prostate cancer. Trial 1 explored docetaxel for 6 months and Trial 2 explored docetaxel plus bevacizumab for 4.5 months, both before radical prostatectomy. erMRI was done at baseline and end of chemotherapy. 1.5T erMRI response, based upon T2W sequences, was recorded. Multivariable Cox regression was undertaken to evaluate the association between clinical parameters and biochemical recurrence., Results: There were 53 evaluable patients in the combined analysis: 20 (33%) achieved a PSA response, 16 (27%) achieved an erMRI partial response and 24 (40%) achieved an erMRI minor response. Median follow-up was 4.2 years, and 33 of 53 evaluable (62%) patients developed biochemical recurrence. On multivariable analysis, PSA response did not correlate with biochemical recurrence (hazard ratio=0.58, 95% confidence interval (CI) 0.25-1.33) and paradoxically erMRI response was associated with a significantly shorter time to biochemical recurrence (hazard ratio=2.47, 95% CI 1.00-6.13)., Conclusions: Response by 1.5T erMRI does not correlate with a decreased likelihood of biochemical recurrence in patients with high-risk localized prostate cancer treated with neoadjuvant docetaxel and may be associated with inferior outcomes. These data do not support the use of 1.5T erMRI response as a primary end point in neoadjuvant chemotherapy trials.

Magnetic resonance (MR) examinations of men with prostate cancer are most commonly performed for detecting, characterizing, and staging the extent of disease to best determine diagnostic or treatment strategies, which range from biopsy guidance to active surveillance to radical prostatectomy. Given both the exam's importance to individual treatment plans and the time constraints present for its operation at most institutions, it is essential to perform the study effectively and efficiently. This article reviews the most commonly employed modern techniques for prostate cancer MR examinations, exploring the relevant signal characteristics from the different methods discussed and relating them to intrinsic prostate tissue properties. Also, a review of recent articles using these methods to enhance clinical interpretation and assess clinical performance is provided. J. Magn. Reson. Imaging 2013;37:1035-1054. © 2013 Wiley Periodicals, Inc., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: To investigate whether 3-T esla (3T) multiparametric endorectal MRI (erMRI) can add information to established predictors regarding occult extraprostatic or high-grade prostate cancer (PC) in men with clinically localized PC., Methods and Materials: At a single academic medical center, this retrospective study's cohort included 118 men with clinically localized PC who underwent 3T multiparametric erMRI followed by radical prostatectomy, from 2008 to 2011. Multivariable logistic regression analyses in all men and in 100 with favorable-risk PC addressed whether erMRI evidence of T3 disease was associated with prostatectomy T3 or Gleason score (GS) 8-10 (in patients with biopsy GS ≤7) PC, adjusting for age, prostate-specific antigen level, clinical T category, biopsy GS, and percent positive biopsies., Results: The accuracy of erMRI prediction of extracapsular extension and seminal vesicle invasion was 75% and 95%, respectively. For all men, erMRI evidence of a T3 lesion versus T2 was associated with an increased odds of having pT3 disease (adjusted odds ratio [AOR] 4.81, 95% confidence interval [CI] 1.36-16.98, P=.015) and pGS 8-10 (AOR 5.56, 95% CI 1.10-28.18, P=.038). In the favorable-risk population, these results were AOR 4.14 (95% CI 1.03-16.56), P=.045 and AOR 7.71 (95% CI 1.36-43.62), P=.021, respectively., Conclusions: Three-Tesla multiparametric erMRI in men with favorable-risk PC provides information beyond that contained in known preoperative predictors about the presence of occult extraprostatic and/or high-grade PC. If validated in additional studies, this information can be used to counsel men planning to undergo radical prostatectomy or radiation therapy about the possible need for adjuvant radiation therapy or the utility of adding hormone therapy, respectively., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Purpose: This study introduces a probabilistic nonrigid registration method for use in image-guided prostate brachytherapy. Intraoperative imaging for prostate procedures, usually transrectal ultrasound (TRUS), is typically inferior to diagnostic-quality imaging of the pelvis such as endorectal magnetic resonance imaging (MRI). MR images contain superior detail of the prostate boundaries and provide substructure features not otherwise visible. Previous efforts to register diagnostic prostate images with the intraoperative coordinate system have been deterministic and did not offer a measure of the registration uncertainty. The authors developed a Bayesian registration method to estimate the posterior distribution on deformations and provide a case-specific measure of the associated registration uncertainty., Methods: The authors adapted a biomechanical-based probabilistic nonrigid method to register diagnostic to intraoperative images by aligning a physician's segmentations of the prostate in the two images. The posterior distribution was characterized with a Markov Chain Monte Carlo method; the maximum a posteriori deformation and the associated uncertainty were estimated from the collection of deformation samples drawn from the posterior distribution. The authors validated the registration method using a dataset created from ten patients with MRI-guided prostate biopsies who had both diagnostic and intraprocedural 3 Tesla MRI scans. The accuracy and precision of the estimated posterior distribution on deformations were evaluated from two predictive distance distributions: between the deformed central zone-peripheral zone (CZ-PZ) interface and the physician-labeled interface, and based on physician-defined landmarks. Geometric margins on the registration of the prostate's peripheral zone were determined from the posterior predictive distance to the CZ-PZ interface separately for the base, mid-gland, and apical regions of the prostate., Results: The authors observed variation in the shape and volume of the segmented prostate in diagnostic and intraprocedural images. The probabilistic method allowed us to convey registration results in terms of posterior distributions, with the dispersion providing a patient-specific estimate of the registration uncertainty. The median of the predictive distance distribution between the deformed prostate boundary and the segmented boundary was ≤3 mm (95th percentiles within ±4 mm) for all ten patients. The accuracy and precision of the internal deformation was evaluated by comparing the posterior predictive distance distribution for the CZ-PZ interface for each patient, with the median distance ranging from -0.6 to 2.4 mm. Posterior predictive distances between naturally occurring landmarks showed registration errors of ≤5 mm in any direction. The uncertainty was not a global measure, but instead was local and varied throughout the registration region. Registration uncertainties were largest in the apical region of the prostate., Conclusions: Using a Bayesian nonrigid registration method, the authors determined the posterior distribution on deformations between diagnostic and intraprocedural MR images and quantified the uncertainty in the registration results. The feasibility of this approach was tested and results were positive. The probabilistic framework allows us to evaluate both patient-specific and location-specific estimates of the uncertainty in the registration result. Although the framework was tested on MR-guided procedures, the preliminary results suggest that it may be applied to TRUS-guided procedures as well, where the addition of diagnostic MR information may have a larger impact on target definition and clinical guidance.

There are many challenges in developing robust imaging biomarkers that can be reliably applied in a clinical trial setting. In the case of dynamic contrast-enhanced (DCE) MRI, one such challenge is to obtain accurate precontrast T(1) maps for subsequent use in two-compartment pharmacokinetic models commonly used to fit the MR enhancement time courses. In the prostate, a convenient and common approach for this task has been to use the same 3D spoiled gradient-echo sequence used to collect the DCE data, but with variable flip angles (VFAs) to collect data suitable for T(1) mapping prior to contrast injection. However, inhomogeneous radiofrequency conditions within the prostate have been found to adversely affect the accuracy of this technique. Herein we demonstrate the sensitivity of DCE pharmacokinetic parameters to precontrast T(1) values and examine methods to improve the accuracy of T(1) mapping with flip angle-corrected VFA SPGR methods, comparing T(1) maps from such methods with "gold standard" reference T(1) maps generated with saturation recovery experiments performed with fast spin-echo (FSE) sequences., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Background: Treatment of high-risk localized prostate cancer remains inadequate. The authors performed a phase 2 multicenter trial of neoadjuvant docetaxel plus bevacizumab before radical prostatectomy., Methods: Eligibility included any of the following: prostate-specific antigen (PSA) >20 ng/mL or PSA velocity >2 ng/mL/y, cT3 disease, any biopsy Gleason score 8 to 10, and Gleason score 7 with T3 disease by endorectal magnetic resonance imaging (MRI) at 1.5 T. Also, those with ≥50% biopsy cores involved and either Gleason score 7, PSA >10, or cT2 disease were eligible. Patients were treated with docetaxel 70 mg/m(2) every 3 weeks for 6 cycles and bevacizumab 15 mg/m(2) every 3 weeks for 5 cycles. The primary endpoint was partial response by endorectal MRI., Results: Forty-one patients were treated. Median age was 55 years (range, 40-66 years). Baseline characteristics included: median PSA, 10.1 ng/mL; cT2, 49%, cT3, 32%; and Gleason score 8 to 10, 73%. Thirty-eight of 41 (93%) patients completed all 6 cycles. Grade ≥3 adverse events were rare, although 3 of 41 (7%) experienced febrile neutropenia. Twelve patients (29%; 95% confidence interval [CI], 16%-45%) achieved a >50% reduction in tumor volume, and 9 patients (22%; 95% CI, 11%-38%) achieved a >50% post-treatment decline in PSA. Thirty-seven of the 41 patients underwent radical prostatectomy; there were no complete pathologic responses., Conclusions: Neoadjuvant docetaxel and bevacizumab is safe, and results in reductions in both tumor volume and serum PSA, in men with high-risk localized prostate cancer. The role of neoadjuvant chemotherapy in prostate cancer, and perioperative antiangiogenic therapy in general, requires further elucidation through ongoing and planned trials., (Copyright © 2012 American Cancer Society.)

Purpose: To develop and evaluate image registration methodology for automated re-identification of tumor-suspicious foci from preprocedural MR exams during MR-guided transperineal prostate core biopsy., Materials and Methods: A hierarchical approach for automated registration between planning and intra-procedural T2-weighted prostate MRI was developed and evaluated on the images acquired during 10 consecutive MR-guided biopsies. Registration accuracy was quantified at image-based landmarks and by evaluating spatial overlap for the manually segmented prostate and sub-structures. Registration reliability was evaluated by simulating initial mis-registration and analyzing the convergence behavior. Registration precision was characterized at the planned biopsy targets., Results: The total computation time was compatible with a clinical setting, being at most 2 min. Deformable registration led to a significant improvement in spatial overlap of the prostate and peripheral zone contours compared with both rigid and affine registration. Average in-slice landmark registration error was 1.3 ± 0.5 mm. Experiments simulating initial mis-registration resulted in an estimated average capture range of 6 mm and an average in-slice registration precision of ±0.3 mm., Conclusion: Our registration approach requires minimum user interaction and is compatible with the time constraints of our interventional clinical workflow. The initial evaluation shows acceptable accuracy, reliability and consistency of the method., (Copyright © 2012 Wiley Periodicals, Inc.)