Quantitative Prostate MRI, From the AJR Special Series on Quantitative Imaging.

Prostate MRI has traditionally relied on qualitative interpretation. However, quantitative components hold the potential to markedly improve performance. The ADC from DWI is probably the most widely recognized quantitative MRI biomarker and has shown strong discriminatory value for clinically significant prostate cancer (csPCa) as well as for recurrent cancer after treatment. Advanced diffusion techniques, including intravoxel incoherent motion, diffusion kurtosis, diffusion tensor imaging, and specific implementations such as restriction spectrum imaging, purport even better discrimination, but are more technically challenging. The inherent T1 and T2 of tissue also provide diagnostic value, with more advanced techniques deriving luminal water imaging and hybrid-multidimensional MRI. Dynamic contrast-enhanced imaging, primarily using a modified Tofts model, also shows independent discriminatory value. Finally, quantitative size and shape features can be combined with the aforementioned techniques and be further refined using radiomics, texture analysis, and artificial intelligence. Which technique will ultimately find widespread clinical use will depend on validation across a myriad of platforms use-cases.

Management of Patients With a Negative Multiparametric Prostate MRI Examination: AJR Expert Panel Narrative Review.

Multiparametric prostate MRI (mpMRI) aids risk stratification of patients with elevated PSA levels. While most clinically significant prostate cancers are detected by mpMRI, insignificant cancers are less evident. Thus, multiple international prostate cancer guidelines now endorse routine use of prostate MRI as a secondary screening test before prostate biopsy. Nonetheless, management of patients with negative mpMRI results (defined as PI-RADS category 1 or 2) remains unclear. This AJR Expert Panel Narrative Review summarizes the available literature on patients with an elevated screening PSA level and a negative prostate mpMRI, and provides guidance for these patients' management. Systematic biopsy should not be routinely performed after a negative mpMRI in patients at average risk but should be considered in patients at high risk. In patients who undergo PSA screening rather than systematic biopsy after negative mpMRI, clear triggers should be established for when to perform a repeat MRI. Patients with negative MRI followed by negative biopsy should follow their healthcare practitioners' preferred guidelines concerning subsequent PSA screening for the patient's risk level. Insufficient high-level data exist to support routine use of adjunctive serum or urine biomarkers, artificial intelligence, or PSMA PET to determine the need for prostate biopsy after negative mpMRI.

Variability of Prostate MRI Charges Among U.S. Hospital-Based Facilities.

The Premier Healthcare Database was used to assess charge variation for prostate MRI examinations in U.S. hospitals from January 2010 to March 2020. In 552 facilities performing 37,073 examinations, the median charge per examination was $4419 with 26-fold variation between the lowest ($593) and highest ($15,150) median facility charges. In multilevel linear regression analysis, interfacility variation explained 63.9% of charge variation. Patients may be charged vastly different prices for prostate MRI depending on the facility.

Pilot study of the diagnostic utility of 89 Zr-df-IAB2M and 68 Ga-PSMA-11 PET imaging and multiparametric MRI in localized prostate cancer.

BACKGROUND: Accurate diagnosis of localized prostate cancer (PCa) is limited by inadequacy of multiparametric (mp) MRI to fully identify and differentiate localized malignant tissue from benign pathologies. Prostate-specific membrane antigen (PSMA) represents an excellent target for molecular imaging. IAB2M, an 85-kD minibody derived from a de-immunized monoclonal antibody directed at the extracellular domain of human PSMA (huJ591), and PSMA-11, a small molecule ligand have been previously tested as probes for visualization of recurrent/metastatic PCa with PET/CT. This pilot, non-randomized trial studied their diagnostic utility in patients (pts) with localized PCa. METHODS: Pts planned for radical prostatectomy (RP) were enrolled and underwent mpMRI and PET/CT imaging with 89 Zr-df-IAB2M and/or 68 Ga-PSMA-PET/CT. Image results were read by a radiologist blinded to clinical information and pathology results, mapped and compared to corresponding histopathology findings from all lesions, both clinically significant and nonsignificant. The detection rates of all three imaging modalities were measured and correlated. RESULTS: 20 pts with median age of 64.5 (46-79) years and PSA level of 7.5 (1.6-36.56) ng/ml were enrolled. 19 pts underwent RP and were imaged pre-operatively with 89 Zr-Df-IAB2M PET/CT and mpMRI. Nine of those were imaged using 68 Ga-PSMA-11 as well. Out of 48 intraprostatic lesions verified on surgical pathology, IAB2M PET/CT was able to detect 36 (75%). A similar proportion of pathologically confirmed, clinically significant lesions (22/29, 76%) was detected. IAB2M PET/CT was also able to identify 14/19 (74%) extraprostatic lesions. The performance of mpMRI was inferior, with 24/48 detectable lesions (50%) and 18/29 clinically significant intraprostatic lesions (62%). Compared to the current standard (mpMRI), IAB2M PET/CT had a sensitivity of 88%, specificity 38%, positive predictive value 58%, and accuracy 63%. In 9 pts who underwent Ga-PSMA-11 as well, the latter yielded a detection rate of 70% (14/20), which was also seen in clinically significant lesions (10/14, 71%). Ga-PSMA-11 PET/CT also detected 4/6 (67%) extraprostatic lesions. CONCLUSIONS: In this pilot study, the performance of 89 Zr-df-IAB2M was superior to mpMRI and similar to 68 Ga-PSMA-11 PET/CT. The higher detection rate of PSMA-PET supports its use as a diagnostic tool with consequent management change implications in men with localized PCa.

Magnetic Resonance Imaging Radiomics-Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions.

BACKGROUND: While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions typically warrant prostate biopsy and PI-RADS 1 and 2 lesions may be safely observed, PI-RADS 3 lesions are equivocal. PURPOSE: To construct and cross-validate a machine learning model based on radiomics features from T2 -weighted imaging (T2 WI) of PI-RADS 3 lesions to identify clinically significant prostate cancer (csPCa), that is, pathological Grade Group ≥ 2. STUDY TYPE: Single-center retrospective study. POPULATION: A total of 240 patients were included (training cohort, n = 188, age range 43-82 years; test cohort, n = 52, age range 41-79 years). Eligibility criteria were 1) magnetic resonance imaging (MRI)-targeted biopsy between 2015 and 2020; 2) PI-RADS 3 index lesion identified on multiparametric MRI; (3) biopsy performed within 1 year of MRI. The percentages of csPCa lesions were 10.6% and 15.4% in the training and test cohorts, respectively. FIELD STRENGTH/SEQUENCE: A 3 T; T2 WI turbo-spin echo, diffusion-weighted spin-echo echo planar imaging, dynamic contrast-enhanced MRI with time-resolved T1-weighted imaging. ASSESSMENT: Multislice volumes-of-interest (VOIs) were drawn in the PI-RADS 3 index lesions on T2 WI. A total of 107 radiomics features (first-order histogram and second-order texture) were extracted from the segmented lesions. STATISTICAL TESTS: A random forest classifier using the radiomics features as input was trained and validated for prediction of csPCa. The performance of the machine learning classifier, prostate specific antigen (PSA) density, and prostate volume for csPCa prediction was evaluated using receiver operating characteristic (ROC) analysis. RESULTS: The trained random forest classifier constructed from the T2 WI radiomics features good and statistically significant area-under-the-curves (AUCs) of 0.76 (P = 0.022) for prediction of csPCa in the test set. Prostate volume and PSA density showed moderate and nonsignificant performance (AUC 0.62, P = 0.275 and 0.61, P = 0.348, respectively) for csPCa prediction in the test set. CONCLUSION: The machine learning classifier based on T2 WI radiomic features demonstrated good performance for prediction of csPCa in PI-RADS 3 lesions. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: 2.

Practice Patterns and Challenges of Performing and Interpreting Prostate MRI: A Survey by the Society of Abdominal Radiology Prostate Disease-Focused Panel.

OBJECTIVE. The purpose of this study was to report on the practice patterns and challenges of performing and interpreting prostate MRI. SUBJECTS AND METHODS. An electronic survey regarding prostate MRI practice patterns and challenges was sent to members of the Society of Abdominal Radiology. RESULTS. The response rate was 15% (212/1446). Most (65%) of the respondents were academic abdominal radiologists with 1-5 (52%), 6-10 (20%), 11-20 (15%), and more than 20 (5%) years of experience in reporting prostate MRI. The numbers of prostate MRI examinations reported per week were 0-5 (43%), 6-10 (38%), 11-20 (12%), 21-30 (5%), and more than 30 (2%). Imaging was performed at 3 T (58%), 1.5 T (20%), or either (21%), and most examinations (83%) were performed without an endorectal coil. Highest b values ranged from 800 to 5000 s/mm2; 1400 s/mm2 (26%) and 1500 s/mm2 (30%) were the most common. Most respondents (79%) acquired dynamic contrast-enhanced images with temporal resolution of less than 10 seconds. Most (71%) of the prostate MRI studies were used for fusion biopsy. PI-RADS version 2 was used by 92% of the respondents and template reporting by 80%. Challenges to performing and interpreting prostate MRI were scored on a 1-5 Likert scale (1, easy; 2, somewhat easy; 3, neutral; 4, somewhat difficult; 5, very difficult). The median scores were 2 or 3 for patient preparatory factors. Image acquisition and reporting factors were scored 1-2, except for performing spectroscopy or using an endorectal coil, both of which scored 4. Acquiring patient history scored 2 and quality factors scored 3. CONCLUSION. Most radiologists perform prostate MRI at 3 T without an endorectal coil and interpret the images using PI-RADS version 2. Challenges include obtaining quality images, acquiring feedback, and variability in the interpretation of PI-RADS scores.

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.

Influence of the Location and Zone of Tumor in Prostate Cancer Detection and Localization on 3-T Multiparametric MRI Based on PI-RADS Version 2.

OBJECTIVE. The objective of our study was to determine the performance of 3-T multiparametric MRI (mpMRI) for prostate cancer (PCa) detection and localization, stratified by anatomic zone and level, using Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) and whole-mount histopathology (WMHP) as reference. MATERIALS AND METHODS. Multiparametric MRI examinations of 415 consecutive men were compared with thin-section WMHP results. A genitourinary radiologist and pathologist collectively determined concordance. Two radiologists assigned PI-RADSv2 scores and sector location to all detected foci by consensus. Tumor detection rates were calculated for clinical and pathologic (tumor location and zone) variables. Both rigid and adjusted sector-matching models were used to account for fixation-related issues. RESULTS. Of 863 PCa foci in 16,185 prostate sectors, the detection of overall and index PCa lesions in the midgland, base, and apex was 54.9% and 83.1%, 42.1% and 64.0% (p = 0.04, p = 0.02), and 41.9% and 71.4% (p = 0.001, p = 0.006), respectively. Tumor localization sensitivity was highest in the midgland compared with the base and apex using an adjusted match compared with a rigid match (index lesions, 71.3% vs 43.7%; all lesions, 70.8% vs 36.0%) and was greater in the peripheral zone (PZ) than in the transition zone. Three-Tesla mpMRI had similarly high specificity (range, 93.8-98.3%) for overall and index tumor localization when using both rigid and adjusted sector-matching approaches. CONCLUSION. For 3-T mpMRI, the highest sensitivity (83.1%) for detection of index PCa lesions was in the midgland, with 98.3% specificity. Multiparametric MRI performance for sectoral localization of PCa within the prostate was moderate and was best for index lesions in the PZ using an adjusted model.

Components of Radiologic Progressive Disease Defined by RECIST 1.1 in Patients with Metastatic Clear Cell Renal Cell Carcinoma.

Background Progression-free survival (PFS) determined by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) is the reference standard to assess efficacy of treatments in patients with clear cell renal cell carcinoma. Purpose To assess the most common components of radiologic progressive disease as defined by RECIST 1.1 in patients with clear cell renal cell carcinoma and how the progression events impact PFS. Materials and Methods This secondary analysis of the phase III METEOR trial conducted between 2013 and 2014 included patients with metastatic clear cell renal cell carcinoma, with at least one target lesion at baseline and one follow-up time point, who were determined according to RECIST 1.1 to have progressive disease. A chest, abdominal, and pelvic scan were acquired at each time point. Kruskal-Wallis analysis was used to test differences in median PFS among the RECIST 1.1 progression events. The Holm-Bonferroni method was used to compare the median PFS of the progression events for the family-wise error rate of 5% to adjust P values for multiple comparisons. Results Of the 395 patients (296 men, 98 women, and one patient with sex not reported; mean age, 61 years ± 10), 73 (18.5%) had progression due to non-target disease, 105 (26.6%) had new lesions, and 126 (31.9%) had progression of target lesions (defined by an increase in the sum of diameters). Patients with progression of non-target disease and those with new lesions had shorter PFS than patients with progression defined by the target lesions (median PFS, 2.8 months [95% confidence interval {CI}: 1.9 months, 3.7 months] and 3.6 months [95% CI: 3.3 months, 3.7 months] vs 5.4 months [95% CI: 5.0 months, 5.5 months], respectively [P < .01]). Conclusion The most common causes for radiologic progression of renal cell carcinoma were based on non-target disease and new lesions rather than change in target lesions, despite this being considered uncommon in the Response Evaluation Criteria in Solid Tumors version 1.1 literature. © RSNA, 2019 See also the editorial by Kuhl in this issue.

Detection and Localization of Prostate Cancer at 3-T Multiparametric MRI Using PI-RADS Segmentation.

OBJECTIVE. The purpose of this study is to determine the overall and sector-based performance of 3-T multiparametric MRI for prostate cancer (PCa) detection and localization by using Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2) scoring and segmentation compared with whole-mount histopathologic analysis. MATERIALS AND METHODS. Multiparametric 3-T MRI examinations of 415 consecutive men were compared with thin-section whole-mount histopathologic analysis. A genitourinary radiologist and pathologist collectively determined concordance. Two radiologists assigned PI-RADSv2 categories and sectoral location to all detected foci by consensus. Tumor detection rates were calculated for clinical and pathologic (Gleason score) variables. Both rigid and adjusted sector-matching models were used to account for fixation-related issues. RESULTS. The 415 patients had 863 PCa foci (52.7% had a Gleason score ≥ 7, 61.9% were ≥ 1 cm, and 90.4% (375/415) of index lesions were ≥ 1 cm) and 16,185 prostate sectors. Multiparametric MRI enabled greater detection of PCa lesions 1 cm or larger (all lesions vs index lesions, 61.6% vs 81.6%), lesions with Gleason score greater than or equal to 7 (all lesions vs index lesions, 71.4% vs 80.9%), and index lesions with both Gleason score greater than or equal to 7 and size 1 cm or larger (83.3%). Higher sensitivity was obtained for adjusted versus rigid tumor localization for all lesions (56.0% vs 28.5%), index lesions (55.4% vs 34.3%), lesions with Gleason score greater than or equal to 7 (55.7% vs 36.0%), and index lesions 1 cm or larger (56.1% vs 35.0%). Multiparametric 3-T MRI had similarly high specificity (96.0-97.9%) for overall and index tumor localization with adjusted and rigid sector-matching approaches. CONCLUSION. Using 3-T multiparametric MRI and PI-RADSv2, we achieved the highest sensitivity (83.3%) for the detection of lesions 1 cm or larger with Gleason score greater than or equal to 7. Sectoral localization of PCa within the prostate was moderate and was better with an adjusted model than with a rigid model.

Utility of Restriction Spectrum Imaging Among Men Undergoing First-Time Biopsy for Suspected Prostate Cancer.

OBJECTIVE. The purpose of this article is to evaluate restriction spectrum imaging (RSI) in men undergoing MRI-ultrasound fusion biopsy for suspected prostate cancer (PCa) and to compare the performance of RSI with that of conventional DWI. MATERIALS AND METHODS. One hundred ninety-eight biopsy-naïve men enrolled in a concurrent prospective clinical trial evaluating MRI-targeted prostate biopsy underwent multiparametric MRI with RSI. Clinical and imaging features were compared between men with and without clinically significant (CS) PCa (MRI-ultrasound fusion biopsy Gleason score ≥ 3 + 4). RSI z score and apparent diffusion coefficient (ADC) were correlated, and their diagnostic performances were compared. RESULTS. CS PCa was detected in 109 of 198 men (55%). Using predefined thresholds of ADC less than or equal to 1000 µm2/s and RSI z score greater than or equal to 3, sensitivity and specificity for CS PCa were 86% and 38%, respectively, for ADC and 61% and 70%, respectively, for RSI. In the transition zone (n = 69), the sensitivity and specificity were 94% and 17%, respectively, for ADC and 59% and 69%, respectively, for RSI. Among lesions with CS PCa, RSI z score and ADC were significantly inversely correlated in the peripheral zone (ρ = -0.4852; p < 0.01) but not the transition zone (ρ = -0.2412; p = 0.17). Overall diagnostic accuracies of RSI and DWI were 0.70 and 0.68, respectively (p = 0.74). CONCLUSION. RSI and DWI achieved equivalent diagnostic performance for PCa detection in a large population of men undergoing first-time prostate biopsy for suspected PCa, but RSI had superior specificity for transition zone lesions.

Focal Therapy Eligibility Determined by Magnetic Resonance Imaging/Ultrasound Fusion Biopsy.

PURPOSE: We assessed focal therapy eligibility in men who underwent multiparametric magnetic resonance imaging and targeted biopsy with correlation to whole mount histology after radical prostatectomy. MATERIALS AND METHODS: Subjects were selected from among the 454 men in whom targeted biopsy proven prostate cancer was derived from regions of interest on multiparametric magnetic resonance imaging from 2010 to 2016. Focal therapy eligibility was limited to a maximum Gleason score of 4 + 3 in regions of interest with or without other foci of low risk prostate cancer (Gleason score 3 + 3 and less than 4 mm). Men who did not meet NCCN® intermediate risk criteria were classified as ineligible for focal therapy. Of the 454 men 64 underwent radical prostatectomy and biopsy findings were compared to final pathology findings. RESULTS: Of the 454 men with a biopsy proven region of interest 175 (38.5%) were eligible for focal therapy. Fusion biopsy, which combined targeted and template biopsy, had 80.0% sensitivity (12 of 15 cases), 73.5% specificity (36 of 49) and 75.0% accuracy (48 of 64) for focal therapy eligibility. Targeted cores alone yielded 73.3% sensitivity (11 of 15 cases), 47.9% specificity (23 of 48) and 54.7% accuracy (35 of 64). Gleason score and extension across the midline differed in 4 and 9, respectively, of the 13 cases that showed discordant biopsy and whole mount histology. CONCLUSIONS: Using intermediate risk eligibility criteria more than a third of men with a targeted biopsy proven lesion identified on multiparametric magnetic resonance imaging would have been eligible for focal therapy. Eligibility determined by fusion biopsy was concordant with whole mount histology in 75% of cases. Improved selection criteria are needed to reliably determine focal therapy eligibility.

In-Bore 3-T MR-guided Transrectal Targeted Prostate Biopsy: Prostate Imaging Reporting and Data System Version 2-based Diagnostic Performance for Detection of Prostate Cancer.

Purpose To determine the diagnostic yield of in-bore 3-T magnetic resonance (MR) imaging-guided prostate biopsy and stratify performance according to Prostate Imaging Reporting and Data System (PI-RADS) versions 1 and 2. Materials and Methods This study was HIPAA compliant and institution review board approved. In-bore 3-T MR-guided prostate biopsy was performed in 134 targets in 106 men who (a) had not previously undergone prostate biopsy, (b) had prior negative biopsy findings with increased prostate-specific antigen (PSA) level, or (c) had a prior history of prostate cancer with increasing PSA level. Clinical, diagnostic 3-T MR imaging was performed with in-bore guided prostate biopsy, and pathology data were collected. The diagnostic yields of MR-guided biopsy per patient and target were analyzed, and differences between biopsy targets with negative and positive findings were determined. Results of logistic regression and areas under the curve were compared between PI-RADS versions 1 and 2. Results Prostate cancer was detected in 63 of 106 patients (59.4%) and in 72 of 134 targets (53.7%) with 3-T MR imaging. Forty-nine of 72 targets (68.0%) had clinically significant cancer (Gleason score ≥ 7). One complication occurred (urosepsis, 0.9%). Patients who had positive target findings had lower apparent diffusion coefficient values (875 × 10-6 mm2/sec vs 1111 × 10-6 mm2/sec, respectively; P < .01), smaller prostate volume (47.2 cm3 vs 75.4 cm3, respectively; P < .01), higher PSA density (0.16 vs 0.10, respectively; P < .01), and higher proportion of PI-RADS version 2 category 3-5 scores when compared with patients with negative target findings. MR targets with PI-RADS version 2 category 2, 3, 4, and 5 scores had a positive diagnostic yield of three of 23 (13.0%), six of 31 (19.4%), 39 of 50 (78.0%), and 24 of 29 (82.8%) targets, respectively. No differences were detected in areas under the curve for PI-RADS version 2 versus 1. Conclusion In-bore 3-T MR-guided biopsy is safe and effective for prostate cancer diagnosis when stratified according to PI-RADS versions 1 and 2. ©RSNA, 2016.

Focal Laser Ablation of Prostate Cancer: Feasibility of Magnetic Resonance Imaging-Ultrasound Fusion for Guidance.

PURPOSE: Focal laser ablation is a potential treatment in some men with prostate cancer. Currently focal laser ablation is performed by radiologists in a magnetic resonance imaging unit (in bore). We evaluated the safety and feasibility of performing focal laser ablation in a urology clinic (out of bore) using magnetic resonance imaging-ultrasound fusion for guidance. MATERIALS AND METHODS: A total of 11 men with intermediate risk prostate cancer were enrolled in this prospective, institutional review board approved pilot study. Magnetic resonance imaging-ultrasound fusion was used to guide laser fibers transrectally into regions of interest harboring intermediate risk prostate cancer. Thermal probes were inserted for real-time monitoring of intraprostatic temperatures during laser activation. Multiparametric magnetic resonance imaging (3 Tesla) was done immediately after treatment and at 6 months along with comprehensive fusion biopsy. RESULTS: Ten of 11 patients were successfully treated while under local anesthesia. Mean procedure time was 95 minutes (range 71 to 105). Posttreatment magnetic resonance imaging revealed a confined zone of nonperfusion in all 10 men. Mean zone volume was 4.3 cc (range 2.1 to 6.0). No CTCAE grade 3 or greater adverse events developed and no changes were observed in urinary or sexual function. At 6 months magnetic resonance imaging-ultrasound fusion biopsy of the treatment site showed no cancer in 3 patients, microfocal Gleason 3 + 3 in another 3 and persistent intermediate risk prostate cancer in 4. CONCLUSIONS: Focal laser ablation of prostate cancer appears safe and feasible with the patient under local anesthesia in a urology clinic using magnetic resonance imaging-ultrasound fusion for guidance and thermal probes for monitoring. Further development is necessary to refine out of bore focal laser ablation and additional studies are needed to determine appropriate treatment margins and oncologic efficacy.

Partial gland ablation in the management of prostate cancer: a review.

PURPOSE OF REVIEW: The index lesion theory has created a strong interest in partial gland ablation for men with prostate cancer. By only treating the focus of clinically significant disease and avoidance of surrounding periprostatic tissue, one may provide adequate oncologic control with minimal side effects. Accurate identification of the index lesion and effective ablation are critical for satisfactory oncologic outcomes. Herein, we review key ablative techniques used in partial gland ablation. RECENT FINDINGS: Increasing accuracy in identifying localized prostate cancer enabled the emergence of partial gland ablation, which appears to have acceptable short-term oncologic control with minimal side effects. Cryoablation, high-intensity focused ultrasound, focal laser ablation, and irreversible electroporation are emerging technologies that are demonstrating their utility in partial gland ablation. These different ablative techniques offer unique advantages and drawbacks in partial gland ablation of prostate cancer. SUMMARY: Prostate imaging continues to scale the challenge of accurately identifying clinically significant prostate cancer. Ablative techniques demonstrate acceptable short-term oncologic outcomes but will require longer follow-up to determine true oncologic efficacy. There are no randomized trial comparisons to conventional radical prostatectomy or radiotherapy, and there is limited oncologic follow-up beyond 5 years. The type of ablation technique used will likely depend on many factors such as tumor volume, tumor location, and patient characteristics. Oncologic efficacy, health-related quality of life, and advantages and limitations of each technique will be reviewed.

Prostate cancer detection with magnetic resonance-ultrasound fusion biopsy: The role of systematic and targeted biopsies.

BACKGROUND: The current study was conducted to evaluate the performance of magnetic resonance (MR)-ultrasound-guided fusion biopsy in diagnosing clinically significant prostate cancer (csCaP). METHODS: A total of 1042 men underwent multiparametric MR imaging (mpMRI) and fusion biopsy consecutively in a prospective trial (2009-2014). An expert reader graded mpMRI regions of interest (ROIs) as 1 to 5 using published protocols. The fusion biopsy device was used to obtain targeted cores from ROIs (when present) followed by a fusion image-guided, 12-core systematic biopsy in all men, even if no suspicious ROI was noted. The primary endpoint of the study was the detection of csCaP (ie, Gleason score ≥ 7). RESULTS: Among 825 men with ≥ 1 suspicious ROI of ≥ grade 3, 289 (35%) were found to have csCaP. Powerful predictors of csCaP were ROI grade (grade 5 vs grade 3: odds ratio, 6.5 [P<.01]) and prostate-specific antigen density (each increase of 0.05 ng/mL/cc: odds ratio, 1.4 [P<.01]). Combining systematic and targeted biopsies resulted in the detection of more patients with csCaP (289 patients) than targeting (229 patients) or systematic (199 patients) biopsy alone. Among patients with no suspicious ROI, 35 (16%) were found to have csCaP on systematic biopsy. CONCLUSIONS: In this prospective trial, MR-ultrasound fusion biopsy allowed for the detection of csCaP, with a direct relationship noted with ROI grade and prostate-specific antigen density. The combination of targeted and systematic biopsy detected more csCaP than either modality alone; systematic biopsies revealed csCaP in 16% of men with no suspicious MRI target. The advantages of this new biopsy method are apparent, but issues of cost, training, and reliability await resolution before its widespread adoption.