Prostate Core

Clare Tempany Kemal Tuncali Fiona Fennessy Junichi Tokuda Andrey Fedorov
Clare M. Tempany, MD
Core Lead
Kemal Tuncali, MD
Co-Investigator
Fiona Fennessy, MD, PhD
Project Lead
Junichi Tokuda, PhD
Project Lead
Andriy Fedorov, PhD
Project Lead

There are two complex issues that drive the clinical need to change current paradigms for prostate cancer (PCa): The inability to predict aggressiveness of a given cancer, which in turn leads to over treatment, and the increasing evidence that disease progression in men with seemingly low-risk PCa is due to inadequate biopsy sampling. Recent trends indicate that the treatment of patients with localized PCa is shifting more and more towards either active surveillance or focal therapy. Technical solutions to address these challenges, and their validation in clinic, are lacking. We are working to address these challenges by integrating innovative MR image acquisition and analysis with the MR targeted biopsy platform we developed in the previous cycle. We are developing a diagnostic biomedical imaging platform to detect, characterize and diagnose prostate cancer and will provide new opportunities to understand the aggressiveness and heterogeneity of prostate cancer and ultimately allow for development and testing of new predictive markers in focal therapy. Our projects are:

Platform for validating novel imaging biomarkers with molecular and routine pathology.  We are developing methods of assessment of tumor heterogeneity by supplementing mpMRI with new hypoxia and multi b value MR imaging and add molecular profiling to the pathology options for core biopsy tissue, thus provide a unique platform for imaging, biopsy and both routine and molecular pathology. We will correlate genomic diversity with MR imaging parameters. We will propose novel motion compensation techniques combined with hypoxia imaging that will be applied jointly with the multi-b-value diffusion weighted imaging (DWI) for improved characterization of PCa. These novel-imaging approaches will be validated in biopsy and cryotherapy patient cohorts. (Contact: Clare M. Tempany, Fiona Fennessy)

Platform for focal cryoablation of PCa with accurate temperature mapping and motion compensation. Our goal is to develop and evaluate thermometry methods to monitor MR-guided focal cryoablation for localized prostate cancer, by internal ice ball thermometry using a “voxelwise thermal history” method. We will develop and test a new method for tracking the prostate gland motion, using active MR tracking coils embedded in a urethral warming catheter, investigate Ultrashort TE (UTE) MRI to monitor the internal thermal dosimetry within the ice-ball, and develop and evaluate software for voxel-wise thermal history tracking during all stages of the procedure. (Contact: Junichi Tokuda)

Informatics solution in support of targeted prostate biopsy and focal therapy for localized prostate cancer. This aim will have three tasks: 1) develop software tools to support structured PCa reporting and image registration for biopsy and focal therapy applications; 2) investigate and implement improved practices for structured data collection and provenance, prepare and disseminate curated validation datasets to facilitate validation of the role of mpMRI in cancer characterization and the evaluation of image registration accuracy/reliability; 3) investigate methods for non-rigid registration to enable recovery of prostate gland deformation for treatment response assessment and propose and apply methodologies for statistical assessment of the reliability of the registration tools. All three projects are interconnected, and leverage unique resources provided by this Center. In addition to developing novel technologies, we are creating a platform for collecting validation imaging datasets annotated with the analysis results, molecular and pathology markers, to build a unique resource for investigating the role of imaging and development of novel image analysis tools for prostate cancer. (Contact: Andriy Fedorov)

Software and Documentation

3D Slicer, a comprehensive open source platform for medical image analysis, contains several modules that have been contributed by us for Image-Guided Prostate Interventions. These include:

Data

Presentations

These presentations have been selected as tutorials for readers interested in learning about the clinical science and technology of the Prostate Core.

Links

Full Publication List

In NIH/NLM database and in our Abstracts Database

Select Recent Publications

Alessandrino F, Taghipour M, Hassanzadeh E, Ziaei A, Vangel M, Fedorov A, Tempany CM, Fennessy FM. Predictive Role of PI-RADSv2 and ADC Parameters in Differentiating Gleason Pattern 3 + 4 and 4 + 3 Prostate Cancer. Abdom Radiol (NY). 2018.Abstract
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), ADC of adjacent normal tissue (ADC), and ADC (ADC/ADC) were calculated. Stepwise regression analysis using tumor location, ADC and ADC, 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 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 (p = 0.03) and ADC (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.
King MT, Nguyen PL, Boldbaatar N, Tempany CM, Cormack RA, Beard CJ, Hurwitz MD, Suh WW, D'Amico AV, Orio PF. Long-Term Outcomes of Partial Prostate Treatment with Magnetic Resonance Imaging-Guided Brachytherapy for Patients with Favorable-Risk Prostate Cancer. Cancer. 2018.Abstract
BACKGROUND: Partial prostate treatment has emerged as a potential method for treating patients with favorable-risk prostate cancer while minimizing toxicity. The authors previously demonstrated poor rates of biochemical disease control for patients with National Comprehensive Cancer Network (NCCN) intermediate-risk disease using partial gland treatment with brachytherapy. The objective of the current study was to estimate the rates of distant metastasis and prostate cancer-specific mortality (PCSM) for this cohort. METHODS: Between 1997 and 2007, a total of 354 men with clinical T1c disease, a prostate-specific antigen (PSA) level < 15 ng/mL, and Gleason grade ≤3 + 4 prostate cancer underwent partial prostate treatment with brachytherapy to the peripheral zone under 0.5-Tesla magnetic resonance guidance. The cumulative incidences of metastasis and PCSM for the NCCN very low-risk, low-risk, and intermediate-risk groups were estimated. Fine and Gray competing risk regression was used to evaluate clinical factors associated with time to metastasis. RESULTS: A total of 22 patients developed metastases at a median of 11.0 years (interquartile range, 6.9-13.9 years). The 12-year metastasis rates for patients with very low-risk, low-risk, and intermediate-risk disease were 0.8% (95% confidence interval [95% CI], 0.1%-4.4%), 8.7% (95% CI, 3.4%-17.2%), and 15.7% (95% CI, 5.7%-30.2%), respectively, and the 12-year PCSM estimates were 1.6% (95% CI, 0.1%-7.6%), 1.4% (95% CI, 0.1%-6.8%), and 8.2% (95% CI, 1.9%-20.7%), respectively. On multivariate analysis, NCCN risk category (low risk: hazard ratio, 6.34 [95% CI, 1.18-34.06; P = .03] and intermediate risk: hazard ratio, 6.98 [95% CI, 1.23-39.73; P = .03]) was found to be significantly associated with the time to metastasis. CONCLUSIONS: Partial prostate treatment with brachytherapy may be associated with higher rates of distant metastasis and PCSM for patients with intermediate-risk disease after long-term follow-up. Treatment of less than the full gland may not be appropriate for this cohort. Cancer 2018. © 2018 American Cancer Society.
van Beek EJR, Kuhl C, Anzai Y, Desmond P, Ehman RL, Gong Q, Gold G, Gulani V, Hall-Craggs M, Leiner T, et al. Value of MRI in Medicine: More Than Just Another Test?. J Magn Reson Imaging. 2018.Abstract
There is increasing scrutiny from healthcare organizations towards the utility and associated costs of imaging. MRI has traditionally been used as a high-end modality, and although shown extremely important for many types of clinical scenarios, it has been suggested as too expensive by some. This editorial will try and explain how value should be addressed and gives some insights and practical examples of how value of MRI can be increased. It requires a global effort to increase accessibility, value for money, and impact on patient management. We hope this editorial sheds some light and gives some indications of where the field may wish to address some of its research to proactively demonstrate the value of MRI. LEVEL OF EVIDENCE: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018.
Langkilde F, Kobus T, Fedorov A, Dunne R, Tempany C, Mulkern RV, Maier SE. Evaluation of Fitting Models for Prostate Tissue Characterization using Extended-range b-factor Diffusion-weighted Imaging. Magn Reson Med. 2018;79 (4) :2346-58.Abstract
PURPOSE: To compare the fitting and tissue discrimination performance of biexponential, kurtosis, stretched exponential, and gamma distribution models for high b-factor diffusion-weighted images in prostate cancer. METHODS: Diffusion-weighted images with 15 b-factors ranging from b = 0 to 3500 s/mmwere obtained in 62 prostate cancer patients. Pixel-wise signal decay fits for each model were evaluated with the Akaike Information Criterion (AIC). Parameter values for each model were determined within normal prostate and the index lesion. Their potential to differentiate normal from cancerous tissue was investigated through receiver operating characteristic analysis and comparison with Gleason score. RESULTS: The biexponential slow diffusion fraction f, the apparent kurtosis diffusion coefficient ADC, and the excess kurtosis factor K differ significantly among normal peripheral zone (PZ), normal transition zone (TZ), tumor PZ, and tumor TZ. Biexponential and gamma distribution models result in the lowest AIC, indicating a superior fit. Maximum areas under the curve (AUCs) of all models ranged from 0.93 to 0.96 for the PZ and from 0.95 to 0.97 for the TZ. Similar AUCs also result from the apparent diffusion coefficient (ADC) of a monoexponential fit to a b-factor sub-range up to 1250 s/mm. For kurtosis and stretched exponential models, single parameters yield the highest AUCs, whereas for the biexponential and gamma distribution models, linear combinations of parameters produce the highest AUCs. Parameters with high AUC show a trend in differentiating low from high Gleason score, whereas parameters with low AUC show no such ability. CONCLUSION: All models, including a monoexponential fit to a lower-b sub-range, achieve similar AUCs for discrimination of normal and cancer tissue. The biexponential model, which is favored statistically, also appears to provide insight into disease-related microstructural changes. Magn Reson Med 79:2346-2358, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Hassanzadeh E, Glazer DI, Dunne RM, Fennessy FM, Harisinghani MG, Tempany CM. Prostate Imaging Reporting and Data System Version 2 (PI-RADS v2): A Pictorial Review. Abdom Radiol (NY). 2017;42 (1) :278-89.Abstract

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.

Verma S, Choyke PL, Eberhardt SC, Oto A, Tempany CM, Turkbey B, Rosenkrantz AB. The Current State of MR Imaging-targeted Biopsy Techniques for Detection of Prostate Cancer. Radiology. 2017;285 (2) :343-56.Abstract
Systematic transrectal ultrasonography (US)-guided biopsy is the standard approach for histopathologic diagnosis of prostate cancer. However, this technique has multiple limitations because of its inability to accurately visualize and target prostate lesions. Multiparametric magnetic resonance (MR) imaging of the prostate is more reliably able to localize significant prostate cancer. Targeted prostate biopsy by using MR imaging may thus help to reduce false-negative results and improve risk assessment. Several commercial devices are now available for targeted prostate biopsy, including in-gantry MR imaging-targeted biopsy and real-time transrectal US-MR imaging fusion biopsy systems. This article reviews the current status of MR imaging-targeted biopsy platforms, including technical considerations, as well as advantages and challenges of each technique.
Fedorov A, Vangel MG, Tempany CM, Fennessy FM. Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Invest Radiol. 2017;52 (9) :538-46.Abstract
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.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
Velez E, Fedorov A, Tuncali K, Olubiyi O, Allard CB, Kibel AS, Tempany CM. Pathologic Correlation of Transperineal In-Bore 3-Tesla Magnetic Resonance Imaging-Guided Prostate Biopsy Samples with Radical Prostatectomy Specimen. Abdom Radiol (NY). 2017;42 (8) :2154-9.Abstract

PURPOSE: To determine the accuracy of in-bore transperineal 3-Tesla (T) magnetic resonance (MR) imaging-guided prostate biopsies for predicting final Gleason grades in patients who subsequently underwent radical prostatectomy (RP). METHODS: A retrospective review of men who underwent transperineal MR imaging-guided prostate biopsy (tpMRGB) with subsequent radical prostatectomy within 1 year was conducted from 2010 to 2015. All patients underwent a baseline 3-T multiparametric MRI (mpMRI) with endorectal coil and were selected for biopsy based on MR findings of a suspicious prostate lesion and high degree of clinical suspicion for cancer. Spearman correlation was performed to assess concordance between tpMRGB and final RP pathology among patients with and without previous transrectal ultrasound (TRUS)-guided biopsies. RESULTS: A total of 24 men met all eligibility requirements, with a median age of 65 years (interquartile range [IQR] 11.7). The median time from biopsy to RP was 85 days (IQR 50.5). Final pathology revealed Gleason 3 + 4 = 7 in 12 patients, 4 + 3 = 7 in 10 patients, and 4 + 4 = 8 in 2 patients. A strong correlation (ρ: +0.75, p < 0.001) between tpMRGB and RP results was observed, with Gleason scores concordant in 17 cases (71%). 16 of the 24 patients underwent prior TRUS biopsies. Subsequent tpMRGB revealed Gleason upgrading in 88% of cases, which was concordant with RP Gleason scores in 69% of cases (ρ: +0.75, p < 0.001). CONCLUSION: Final Gleason scores diagnosed by tpMRGB at 3-T correlate strongly with final RP surgical pathology. This may facilitate prostate cancer diagnosis, particularly in patients with negative or low-grade TRUS biopsy results in whom clinically significant cancer is suspected or detected on mpMRI.

Glazer DI, Mayo-Smith WW, Sainani NI, Sadow CA, Vangel MG, Tempany CM, Dunne RM. Interreader Agreement of Prostate Imaging Reporting and Data System Version 2 Using an In-Bore MRI-Guided Prostate Biopsy Cohort: A Single Institution's Initial Experience. AJR Am J Roentgenol. 2017;209 (3) :W145-51.Abstract
OBJECTIVE: The purpose of this study is to determine the interobserver agreement of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) for diagnosing prostate cancer using in-bore MRI-guided prostate biopsy as the reference standard. MATERIALS AND METHODS: Fifty-nine patients underwent in-bore MRI-guided prostate biopsy between January 21, 2010, and August 21, 2013, and underwent diagnostic multiparametric MRI 6 months or less before biopsy. A single index lesion per patient was selected after retrospective review of MR images. Three fellowship-trained abdominal radiologists (with 1-11 years' experience) blinded to clinical information interpreted all studies according to PI-RADSv2. Interobserver agreement was assessed using Cohen kappa statistics. RESULTS: Thirty-eight lesions were in the peripheral zone and 21 were in the transition zone. Cancer was diagnosed in 26 patients (44%). Overall PI-RADS scores were higher for all biopsy-positive lesions (mean ± SD, 3.9 ± 1.1) than for biopsy-negative lesions (3.1 ± 1.0; p < 0.0001) and for clinically significant lesions (4.2 ± 1.0) than for clinically insignificant lesions (3.1 ± 1.0; p < 0.0001). Overall suspicion score interobserver agreement was moderate (κ = 0.45). There was moderate interobserver agreement among overall PI-RADS scores in the peripheral zone (κ = 0.46) and fair agreement in the transition zone (κ = 0.36). CONCLUSION: PI-RADSv2 scores were higher in the biopsy-positive group. PI-RADSv2 showed moderate interobserver agreement among abdominal radiologists with no prior experience using the scoring system.
Hassanzadeh E, Alessandrino F, Olubiyi OI, Glazer DI, Mulkern RV, Fedorov A, Tempany CM, Fennessy FM. Comparison of Quantitative Apparent Diffusion Coefficient Parameters with Prostate Imaging Reporting and Data System V2 Assessment for Detection of Clinically Significant Peripheral Zone Prostate Cancer. Abdom Radiol (NY). 2018;43 (5) :1237-44.Abstract
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 ADCT, mean ADCN, ADCratio (ADCT/ADCN) 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) ADCT (0.83) was higher than PI-RADSv2 (0.65, p = 0.006); (B) ADCT (0.86) was higher than ADCratio (0.68, p < 0.001), and PI-RADSv2 (0.70, p = 0.04); (C) PI-RADSv2 (0.73) performed better than ADCratio (0.56, p = 0.02). ADCT performance was higher when csPC was defined by A or B versus C (p = 0.038 and p = 0.01, respectively). ADCratio 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 ADCT providing best result. When csPC was defined by MRI-calculated volume, PI-RADSv2 provided better discrimination than ADCratio. csPC definition did not affect PI-RADSv2 diagnostic performance.