Artificial Intelligence Improves the Ability of Physicians to Identify Prostate Cancer Extent.

PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians' performance using artificial intelligence (AI) vs standard-of-care methods for tumor delineation. MATERIALS AND METHODS: Cases were interpreted by 7 urologists and 3 radiologists from 5 institutions with 2 to 23 years of experience. Each reader evaluated 50 prostatectomy cases retrospectively eligible for focal therapy. Each case included a T2-weighted MRI, contours of the prostate and region(s) of interest suspicious for cancer, and a biopsy report. First, readers defined cancer contours cognitively, manually delineating tumor boundaries to encapsulate all clinically significant disease. Then, after ≥ 4 weeks, readers contoured the same cases using AI software. Using tumor boundaries on whole-mount histopathology slides as ground truth, AI-assisted, cognitively-defined, and hemigland cancer contours were evaluated. Primary outcome measures were the accuracy and negative margin rate of cancer contours. All statistical analyses were performed using generalized estimating equations. RESULTS: The balanced accuracy (mean of voxel-wise sensitivity and specificity) of AI-assisted cancer contours (84.7%) was superior to cognitively-defined (67.2%) and hemigland contours (75.9%; P < .0001). Cognitively-defined cancer contours systematically underestimated cancer extent, with a negative margin rate of 1.6% compared to 72.8% for AI-assisted cancer contours (P < .0001). CONCLUSIONS: AI-assisted cancer contours reduce underestimation of prostate cancer extent, significantly improving contouring accuracy and negative margin rate achieved by physicians. This technology can potentially improve outcomes, as accurate contouring informs patient management strategy and underpins the oncologic efficacy of treatment.

Magnetic Resonance Imaging-Guided Biopsy in Active Surveillance of Prostate Cancer.

PURPOSE: The underlying premise of prostate cancer active surveillance (AS) is that cancers likely to metastasize will be recognized and eliminated before cancer-related disease can ensue. Our study was designed to determine the prostate cancer upgrading rate when biopsy guided by magnetic resonance imaging (MRGBx) is used before entry and during AS. MATERIALS AND METHODS: The cohort included 519 men with low- or intermediate-risk prostate cancer who enrolled in prospective studies (NCT00949819 and NCT00102544) between February 2008 and February 2020. Subjects were preliminarily diagnosed with Gleason Grade Group (GG) 1 cancer; AS began when subsequent MRGBx confirmed GG1 or GG2. Participants underwent confirmatory MRGBx (targeted and systematic) followed by surveillance MRGBx approximately every 12 to 24 months. The primary outcome was tumor upgrading to ≥GG3. RESULTS: Upgrading to ≥GG3 was found in 92 men after a median followup of 4.8 years (IQR 3.1-6.5) after confirmatory MRGBx. Upgrade-free probability after 5 years was 0.85 (95% CI 0.81-0.88). Cancer detected in a magnetic resonance imaging lesion at confirmatory MRGBx increased risk of subsequent upgrading during AS (HR 2.8; 95% CI 1.3-6.0), as did presence of GG2 (HR 2.9; 95% CI 1.1-8.2) In men who upgraded ≥GG3 during AS, upgrading was detected by targeted cores only in 27%, systematic cores only in 25% and both in 47%. In 63 men undergoing prostatectomy, upgrading from MRGBx was found in only 5 (8%). CONCLUSIONS: When AS begins and follows with MRGBx (targeted and systematic), upgrading rate (≥GG3) is greater when tumor is initially present within a magnetic resonance imaging lesion or when pathology is GG2 than when these features are absent.

Optimizing Spatial Biopsy Sampling for the Detection of Prostate Cancer.

PURPOSE: The appropriate number of systematic biopsy cores to retrieve during magnetic resonance imaging (MRI)-targeted prostate biopsy is not well defined. We aimed to demonstrate a biopsy sampling approach that reduces required core count while maintaining diagnostic performance. MATERIALS AND METHODS: We collected data from a cohort of 971 men who underwent MRI-ultrasound fusion targeted biopsy for suspected prostate cancer. A regional targeted biopsy (RTB) was evaluated retrospectively; only cores within 2 cm of the margin of a radiologist-defined region of interest were considered part of the RTB. We compared detection rates for clinically significant prostate cancer (csPCa) and cancer upgrading rate on final whole mount pathology after prostatectomy between RTB, combined, MRI-targeted, and systematic biopsy. RESULTS: A total of 16,459 total cores from 971 men were included in the study data sets, of which 1,535 (9%) contained csPCa. The csPCa detection rates for systematic, MRI-targeted, combined, and RTB were 27.0% (262/971), 38.3% (372/971), 44.8% (435/971), and 44.0% (427/971), respectively. Combined biopsy detected significantly more csPCa than systematic and MRI-targeted biopsy (p <0.001 and p=0.004, respectively) but was similar to RTB (p=0.71), which used on average 3.8 (22%) fewer cores per patient. In 102 patients who underwent prostatectomy, there was no significant difference in upgrading rates between RTB and combined biopsy (p=0.84). CONCLUSIONS: A RTB approach can maintain state-of-the-art detection rates while requiring fewer retrieved cores. This result informs decision making about biopsy site selection and total retrieved core count.

Prostate Microstructure in Prostate Cancer Using 3-T MRI with Diffusion-Relaxation Correlation Spectrum Imaging: Validation with Whole-Mount Digital Histopathology.

Background Microstructural MRI has the potential to improve diagnosis and characterization of prostate cancer (PCa), but validation with histopathology is lacking. Purpose To validate ex vivo diffusion-relaxation correlation spectrum imaging (DR-CSI) in the characterization of microstructural tissue compartments in prostate specimens from men with PCa by using registered whole-mount digital histopathology (WMHP) as the reference standard. Materials and Methods Men with PCa who underwent 3-T MRI and robotic-assisted radical prostatectomy between June 2018 and January 2019 were prospectively studied. After prostatectomy, the fresh whole prostate specimens were imaged in patient-specific three-dimensionally printed molds by using 3-T MRI with DR-CSI and were then sliced to create coregistered WMHP slides. The DR-CSI spectral signal component fractions (fA, fB, fC) were compared with epithelial, stromal, and luminal area fractions (fepithelium, fstroma, flumen) quantified in PCa and benign tissue regions. A linear mixed-effects model assessed the correlations between (fA, fB, fC) and (fepithelium, fstroma, flumen), and the strength of correlations was evaluated by using Spearman correlation coefficients. Differences between PCa and benign tissues in terms of DR-CSI signal components and microscopic tissue compartments were assessed using two-sided t tests. Results Prostate specimens from nine men (mean age, 65 years ± 7 [standard deviation]) were evaluated; 20 regions from 17 PCas, along with 20 benign tissue regions of interest, were analyzed. Three DR-CSI spectral signal components (spectral peaks) were consistently identified. The fA, fB, and fC were correlated with fepithelium, fstroma, and flumen (all P < .001), with Spearman correlation coefficients of 0.74 (95% confidence interval [CI]: 0.62, 0.83), 0.80 (95% CI: 0.66, 0.89), and 0.67 (95% CI: 0.51, 0.81), respectively. PCa exhibited differences compared with benign tissues in terms of increased fA (PCa vs benign, 0.37 ± 0.05 vs 0.27 ± 0.06; P < .001), decreased fC (PCa vs benign, 0.18 ± 0.06 vs 0.31 ± 0.13; P = .01), increased fepithelium (PCa vs benign, 0.44 ± 0.13 vs 0.26 ± 0.16; P < .001), and decreased flumen (PCa vs benign, 0.14 ± 0.08 vs 0.27 ± 0.18; P = .004). Conclusion Diffusion-relaxation correlation spectrum imaging signal components correlate with microscopic tissue compartments in the prostate and differ between cancer and benign tissue. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Lee and Hectors in this issue.

Risk of Prostate Cancer after a Negative Magnetic Resonance Imaging Guided Biopsy.

PURPOSE: Magnetic resonance imaging guided biopsy which reveals no cancer may impart reassurance beyond that offered by ultrasound guided biopsy. However, followup of men after a negative magnetic resonance imaging guided biopsy has been mostly by prostate specific antigen testing and reports of followup tissue confirmation are few. We investigated the incidence of clinically significant prostate cancer in such men who, because of persistent cancer suspicion, subsequently underwent a repeat magnetic resonance imaging guided biopsy. MATERIALS AND METHODS: Subjects were all men with a negative initial magnetic resonance imaging guided biopsy who underwent at least 1 further magnetic resonance imaging guided biopsy due to continued clinical suspicion of clinically significant prostate cancer (September 2009 to July 2019). Biopsies were magnetic resonance imaging-ultrasound fusion with targeted and systematic cores. Regions of interest from initial magnetic resonance imaging and any new regions of interest at followup magnetic resonance imaging guided biopsy were targeted. The primary end point was detection of clinically significant prostate cancer (Gleason Grade Group 2 or greater). RESULTS: Of 2,716 men 733 had a negative initial magnetic resonance imaging guided biopsy. Study subjects were 73/733 who underwent followup magnetic resonance imaging guided biopsy. Median (IQR) age and prostate specific antigen density were 64 years (59-67) and 0.12 ng/ml/cc (0.08-0.17), respectively. Baseline PI-RADS® scores were 3 or greater in 74%. At followup magnetic resonance imaging guided biopsy (median 2.4 years, IQR 1.3-3.6), 17/73 (23%) were diagnosed with clinically significant prostate cancer. When followup magnetic resonance imaging revealed a lesion (PI-RADS 3 or greater), clinically significant prostate cancer was found in 17/53 (32%). When followup magnetic resonance imaging was negative (PI-RADS less than 3), cancer was not found (0/20) (p <0.01). Overall 54% of men with PI-RADS 5 at followup magnetic resonance imaging guided biopsy were found to have clinically significant prostate cancer. CONCLUSIONS: Men with negative magnetic resonance imaging following an initial negative magnetic resonance imaging guided biopsy are unlikely to harbor clinically significant prostate cancer and may avoid repeat biopsy. However, when lesions are seen on followup magnetic resonance imaging, repeat magnetic resonance imaging guided biopsy is warranted.

Using spatial tracking with magnetic resonance imaging/ultrasound-guided biopsy to identify unilateral prostate cancer.

OBJECTIVES: To create reliable predictive metrics of unilateral disease using spatial tracking from a fusion device, thereby improving patient selection for hemi-gland ablation of prostate cancer. PATIENTS AND METHODS: We identified patients who received magnetic resonance imaging (MRI)/ultrasound-guided biopsy and radical prostatectomy at a single institution between 2011 and 2018. In addition to standard clinical features, we extracted quantitative features related to biopsy core and MRI target locations predictive of tumour unilaterality. Classification and Regression Tree (CART) analysis was used to create a decision tree (DT) for identifying cancer laterality. We evaluated concordance of model-determined laterality with final surgical pathology. RESULTS: A total of 173 patients were identified with biopsy coordinates and surgical pathology available. Based on CART analysis, in addition to biopsy- and MRI-confirmed disease unilaterality, patients should be further screened for cancer detected within 7 mm of midline in a 40 mL prostate, which equates to the central third of any-sized prostate by radius. The area under the curve for this DT was 0.82. Standard diagnostics and the DT correctly identified disease laterality in 73% and 80% of patients, respectively (P = 0.13). Of the patients identified as unilateral by standard diagnostics, 47% had undetected contralateral disease or were otherwise incorrectly identified. This error rate was reduced to 17% (P = 0.01) with the DT. CONCLUSION: Using spatial tracking from fusion devices, a DT was more reliable for identifying laterality of prostate cancer compared to standard diagnostics. Patients with cancer detected within the central third of the prostate by radius are poor hemi-gland ablation candidates due to the risk of midline extension of tumour.

Do contemporary imaging and biopsy techniques reliably identify unilateral prostate cancer? Implications for hemiablation patient selection.

BACKGROUND: Hemiablation is a less morbid treatment alternative for appropriately selected patients with unilateral prostate cancer (PCa). However, to the authors' knowledge, traditional diagnostic techniques inadequately identify appropriate candidates. In the current study, the authors quantified the accuracy for identifying hemiablation candidates using contemporary diagnostic techniques, including multiparametric magnetic resonance imaging (mpMRI) and MRI-fusion with complete systematic template biopsy. METHODS: A retrospective analysis of patients undergoing MRI and MRI-fusion prostate biopsy, including full systematic template biopsy, prior to radical prostatectomy in a single tertiary academic institution between June 2010 and February 2018 was performed. Hemiablation candidates had unilateral intermediate-risk PCa (Gleason score [GS] of 3+4 or 4+3, clinical T classification ≤T2, and prostate-specific antigen level <20 ng/dL) on MRI-fusion biopsy and 2) no contralateral highly or very highly suspicious Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) MRI lesions. Hemiablation candidates were inappropriately selected if pathologists identified contralateral GS ≥3+4 or high-risk ipsilateral PCa on prostatectomy. The authors tested a range of hemiablation inclusion criteria and performed multivariable analysis of preoperative predictors of undetected contralateral disease. RESULTS: Of 665 patients, 92 met primary hemiablation criteria. Of these 92 patients, 44 (48%) were incorrectly identified due to ipsilateral GS ≥3+4 tumors crossing the midline (21 patients), undetected distinct contralateral GS ≥3+4 tumors (20 patients), and/or ipsilateral high-risk PCa (3 patients) on prostatectomy. The rate of undetected contralateral disease ranged from 41% to 48% depending on inclusion criteria. On multivariable analysis, men with anterior index tumors were found to be 2.4 times more likely to harbor undetected contralateral GS ≥3+4 PCa compared with men with posterior lesions (P < .05). CONCLUSIONS: Clinicians and patients must weigh the risk of inadequate oncologic treatment against the functional benefits of hemiablation. Further investigation into methods for improving patient selection for hemiablation is necessary.

SPARED Collaboration: Patient Selection for Partial Gland Ablation in Men with Localized Prostate Cancer.

PURPOSE: The SPARED CRN (Study of Prostate Ablation Related Energy Devices Coordinated Registry Network) is a private-public partnership between academic and community urologists, the FDA (U.S. Food and Drug Administration), the Medical Device Epidemiology Network and device manufacturers to examine the safety and effectiveness of technologies for partial gland ablation in men with localized prostate cancer. MATERIALS AND METHODS: We report on a recent workshop at the FDA with thought leaders to discuss a critical framework for partial gland ablation, focusing on patient selection, surgical planning, followup, study design and appropriate comparators in terms of adverse events and cancer control outcomes. We summarize salient points from experts in urology, oncology and epidemiology that were presented and discussed in an open forum. RESULTS: Given the challenges in achieving patient and physician equipoise to perform a randomized trial, as well as an inherent paradigm shift when comparing partial gland ablation (inability to assess prostate specific antigen recurrence) to whole gland treatments, the group focused on objective performance criteria and goals as a platform to guide the creation of single arm studies in the SPARED CRN. CONCLUSIONS: This summit lays the foundation for prospective, multi-center data collection and evaluation of novel medical devices and drug/device combinations for partial gland ablation.

A system using patient-specific 3D-printed molds to spatially align in vivo MRI with ex vivo MRI and whole-mount histopathology for prostate cancer research.

BACKGROUND: Patient-specific 3D-printed molds and ex vivo MRI of the resected prostate have been two important strategies to align MRI with whole-mount histopathology (WMHP) for prostate cancer (PCa) research, but the combination of these two strategies has not been systematically evaluated. PURPOSE: To develop and evaluate a system that combines patient-specific 3D-printed molds with ex vivo MRI (ExV) to spatially align in vivo MRI (InV), ExV, and WMHP in PCa patients. STUDY TYPE: Prospective cohort study. POPULATION: Seventeen PCa patients who underwent 3T MRI and robotic-assisted laparoscopic radical prostatectomy (RALP). FIELD STRENGTH/SEQUENCES: T2 -weighted turbo spin-echo sequences at 3T. ASSESSMENT: Immediately after RALP, the fresh whole prostate specimens were imaged in patient-specific 3D-printed molds by 3T MRI and then sectioned to create WMHP slides. The time required for ExV was measured to assess impact on workflow. InV, ExV, and WMHP images were registered. Spatial alignment was evaluated using: slide offset (mm) between ExV slice locations and WMHP slides; overlap of the 3D prostate contour on InV versus ExV using Dice's coefficient (0 to 1); and 2D target registration error (TRE, mm) between corresponding landmarks on InV, ExV, and WMHP. Data are reported as mean ± standard deviation (SD). STATISTICAL TESTING: Differences in 2D TRE before versus after registration were compared using the Wilcoxon signed-rank test (P < 0.05 considered significant). RESULTS: ExV (duration 115 ± 15 min) was successfully incorporated into the workflow for all cases. Absolute slide offset was 1.58 ± 1.57 mm. Dice's coefficient was 0.865 ± 0.035. 2D TRE was significantly reduced after registration (P < 0.01) with mean (±SD of per patient means) of 1.9 ± 0.6 mm for InV versus ExV, 1.4 ± 0.5 mm for WMHP versus ExV, and 2.0 ± 0.5 mm for WMHP versus InV. DATA CONCLUSION: The proposed system combines patient-specific 3D-printed molds with ExV to achieve spatial alignment between InV, ExV, and WMHP with mean 2D TRE of 1-2 mm. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:270-279.

Cancer core length from targeted biopsy: an index of prostate cancer volume and pathological stage.

OBJECTIVE: To study the relationship of maximum cancer core length (MCCL), on targeted biopsy (TB) of magnetic resonance imaging (MRI)-visible index lesions, to volume of that tumour found at radical prostatectomy (RP). PATIENTS AND METHODS: In all, 205 men undergoing fusion biopsy and RP were divided into two groups: 136 in whom the MCCL came from an index MRI-visible lesion (TB) and 69 in whom MCCL came from a non-targeted lesion (non-targeted biopsy [NTB]). MRI was 3-T multi-parametric and biopsy was via MRI-ultrasonography fusion. RESULTS: In the TB group, MCCL correlated with volume of clinically significant index tumours (ρ = 0.44-0.60, P < 0.01). The correlation was similar for first and repeat biopsy and for transition and peripheral zone lesions (ρ = 0.42-0.49, P < 0.01). No correlations were found in the NTB group. TB MCCL (6-10 and >10 mm) and MRI lesion diameter (>20 mm) were independently associated with tumour volume. TB MCCLs >10 mm and Gleason scores >7 were each associated with pathological T3 disease (odds ratios 5.73 and 5.04, respectively), but MRI lesion diameter lesion was not. CONCLUSIONS: MCCL on a TB from an MRI-visible lesion is an independent predictor of both cancer volume and pathological stage. This relationship does not exist for MCCL from a NTB core. Quantifying CCL on MRI-TBs may have a value, not previously described, to risk-stratify patients with prostate cancer before treatment.

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.

Magnetic Resonance Imaging Underestimation of Prostate Cancer Geometry: Use of Patient Specific Molds to Correlate Images with Whole Mount Pathology.

PURPOSE: We evaluated the accuracy of magnetic resonance imaging in determining the size and shape of localized prostate cancer. MATERIALS AND METHODS: The subjects were 114 men who underwent multiparametric magnetic resonance imaging before radical prostatectomy with patient specific mold processing of the specimen from 2013 to 2015. T2-weighted images were used to contour the prostate capsule and cancer suspicious regions of interest. The contours were used to design and print 3-dimensional custom molds, which permitted alignment of excised prostates with magnetic resonance imaging scans. Tumors were reconstructed in 3 dimensions from digitized whole mount sections. Tumors were then matched with regions of interest and the relative geometries were compared. RESULTS: Of the 222 tumors evident on whole mount sections 118 had been identified on magnetic resonance imaging. For the 118 regions of interest mean volume was 0.8 cc and the longest 3-dimensional diameter was 17 mm. However, for matched pathological tumors, of which most were Gleason score 3 + 4 or greater, mean volume was 2.5 cc and the longest 3-dimensional diameter was 28 mm. The median tumor had a 13.5 mm maximal extent beyond the magnetic resonance imaging contour and 80% of cancer volume from matched tumors was outside region of interest boundaries. Size estimation was most accurate in the axial plane and least accurate along the base-apex axis. CONCLUSIONS: Magnetic resonance imaging consistently underestimates the size and extent of prostate tumors. Prostate cancer foci had an average diameter 11 mm longer and a volume 3 times greater than T2-weighted magnetic resonance imaging segmentations. These results may have important implications for the assessment and treatment of prostate cancer.

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.

Focal Laser Ablation of Prostate Cancer: Phase I Clinical Trial.

PURPOSE: Focal laser ablation is an investigational technique to treat prostate cancer in a region confined manner via coagulative necrosis. This phase I trial primarily examines the safety of transrectal magnetic resonance imaging guided (in-bore) focal laser ablation in men with intermediate risk prostate cancer. An exploratory end point is cancer control after 6 months. MATERIALS AND METHODS: In an institutional review board approved trial we studied focal laser ablation in 8 men with intermediate risk prostate cancer diagnosed using magnetic resonance-ultrasound fusion. Focal laser ablation was performed by inserting a cylindrically diffusing, water cooled laser fiber into magnetic resonance visible regions of interest, followed by interstitial heating at 10 to 15 W for up to 3 minutes. Secondary safety monitors (thermal probes) were inserted to assess the accuracy of magnetic resonance thermometry. Comprehensive magnetic resonance-ultrasound fusion biopsy was performed after 6 months. Adverse events and health related quality of life questionnaires were recorded. RESULTS: Focal laser ablation was successfully performed in all 8 subjects. No grade 3 or greater adverse events occurred and no changes in International Prostate Symptom Score or International Index of Erectile Function 5 were observed. Ablation zones, as measured by posttreatment magnetic resonance imaging, had a median volume of 3 cc or 7.7% of prostate volume. Prostate specific antigen decreased in 7 men (p <0.01). At followup magnetic resonance-ultrasound fusion biopsy cancer was not detected in the ablation zone in 5 men but was present outside the treatment margin in 6 men. CONCLUSIONS: Focal laser ablation of the prostate is feasible and safe in men with intermediate risk prostate cancer without serious adverse events or changes in urinary or sexual function at 6 months. Comprehensive biopsy followup indicates that larger treatment margins than previously thought necessary may be required for complete tumor ablation.

Evaluation of prostate cancer detection using micro-ultrasound versus MRI through co-registration to whole-mount pathology.

Micro-ultrasound has recently been introduced as a low-cost alternative to multi-parametric MRI for imaging prostate cancer. Early clinical studies have demonstrated promising results; however, robust validation via comparison with whole-mount pathology has yet to be achieved. Due to micro-ultrasound probe design and tissue deformation during scanning, it is difficult to accurately correlate micro-ultrasound imaging planes with ground truth whole-mount pathology slides. In this study, we developed a multi-step methodology to co-register micro-ultrasound and MRI to whole-mount pathology. The three-step process had a registration error of 3.90 ± 0.11 mm and consists of: (1) micro-ultrasound image reconstruction, (2) 3D landmark registration of micro-ultrasound to MRI, and (3) 2D capsule registration of MRI to whole-mount pathology. This process was then used in a preliminary reader study to compare the diagnostic accuracy of micro-ultrasound and MRI in 15 patients who underwent radical prostatectomy for prostate cancer. Micro-ultrasound was found to have equivalent performance to retrospective MRI review for index lesion detection (91.7% vs. 80%), while demonstrating an increased detection of tumor extent (52.5% vs. 36.7%) with similar false positive regions-of-interest (38.3% vs. 40.8%). Prospective MRI review had reduced detection of index lesions (73.3%) and tumor extent (18.9%) but improved false positive regions-of-interest (22.7%) relative to micro-ultrasound and retrospective MRI. Further evaluation is needed with a larger sample size.

Extracapsular extension risk assessment using an artificial intelligence prostate cancer mapping algorithm.

Objective: The objective of this study is to compare detection rates of extracapsular extension (ECE) of prostate cancer (PCa) using artificial intelligence (AI)-generated cancer maps versus MRI and conventional nomograms. Materials and methods: We retrospectively analysed data from 147 patients who received MRI-targeted biopsy and subsequent radical prostatectomy between September 2016 and May 2022. AI-based software cleared by the United States Food and Drug Administration (Unfold AI, Avenda Health) was used to map 3D cancer probability and estimate ECE risk. Conventional ECE predictors including MRI Likert scores, capsular contact length of MRI-visible lesions, PSMA T stage, Partin tables, and the "PRedicting ExtraCapsular Extension" nomogram were used for comparison.Postsurgical specimens were processed using whole-mount histopathology sectioning, and a genitourinary pathologist assessed each quadrant for ECE presence. ECE predictors were then evaluated on the patient (Unfold AI versus all comparators) and quadrant level (Unfold AI versus MRI Likert score). Receiver operator characteristic curves were generated and compared using DeLong's test. Results: Unfold AI had a significantly higher area under the curve (AUC = 0.81) than other predictors for patient-level ECE prediction. Unfold AI achieved 68% sensitivity, 78% specificity, 71% positive predictive value, and 75% negative predictive value. At the quadrant level, Unfold AI exceeded the AUC of MRI Likert scores for posterior (0.89 versus 0.82, p = 0.003), anterior (0.84 versus 0.80, p = 0.34), and all quadrants (0.89 versus 0.82, p = 0.002). The false negative rate of Unfold AI was lower than MRI in both the anterior (-60%) and posterior prostate (-40%). Conclusions: Unfold AI accurately predicted ECE risk, outperforming conventional methodologies. It notably improved ECE prediction over MRI in posterior quadrants, with the potential to inform nerve-spare technique and prevent positive margins. By enhancing PCa staging and risk stratification, AI-based cancer mapping may lead to better oncological and functional outcomes for patients.

Prediction and Mapping of Intraprostatic Tumor Extent with Artificial Intelligence.

Background: Magnetic resonance imaging (MRI) underestimation of prostate cancer extent complicates the definition of focal treatment margins. Objective: To validate focal treatment margins produced by an artificial intelligence (AI) model. Design setting and participants: Testing was conducted retrospectively in an independent dataset of 50 consecutive patients who had radical prostatectomy for intermediate-risk cancer. An AI deep learning model incorporated multimodal imaging and biopsy data to produce three-dimensional cancer estimation maps and margins. AI margins were compared with conventional MRI regions of interest (ROIs), 10-mm margins around ROIs, and hemigland margins. The AI model also furnished predictions of negative surgical margin probability, which were assessed for accuracy. Outcome measurements and statistical analysis: Comparing AI with conventional margins, sensitivity was evaluated using Wilcoxon signed-rank tests and negative margin rates using chi-square tests. Predicted versus observed negative margin probability was assessed using linear regression. Clinically significant prostate cancer (International Society of Urological Pathology grade ≥2) delineated on whole-mount histopathology served as ground truth. Results and limitations: The mean sensitivity for cancer-bearing voxels was higher for AI margins (97%) than for conventional ROIs (37%, p < 0.001), 10-mm ROI margins (93%, p = 0.24), and hemigland margins (94%, p < 0.001). For index lesions, AI margins were more often negative (90%) than conventional ROIs (0%, p < 0.001), 10-mm ROI margins (82%, p = 0.24), and hemigland margins (66%, p = 0.004). Predicted and observed negative margin probabilities were strongly correlated (R2 = 0.98, median error = 4%). Limitations include a validation dataset derived from a single institution's prostatectomy population. Conclusions: The AI model was accurate and effective in an independent test set. This approach could improve and standardize treatment margin definition, potentially reducing cancer recurrence rates. Furthermore, an accurate assessment of negative margin probability could facilitate informed decision-making for patients and physicians. Patient summary: Artificial intelligence was used to predict the extent of tumors in surgically removed prostate specimens. It predicted tumor margins more accurately than conventional methods.

Cryotherapy for partial gland ablation of prostate cancer: Oncologic and safety outcomes.

BACKGROUND: Partial gland ablation (PGA) is a new option for treatment of prostate cancer (PCa). Cryotherapy, an early method of PGA, has had favorable evaluations, but few studies have employed a strict protocol using biopsy endpoints in men with clinically significant prostate cancer (csPCa). METHODS: 143 men with unilateral csPCa were enrolled in a prospective, observational trial of outpatient PGA-cryotherapy. Treatment was a 2-cycle freeze of the affected prostate part. Participants were evaluated with MRI-guided biopsy (MRGB) at baseline and at 6 months and 18 months after treatment. Absence of csPCa upon MRGB was the primary endpoint; quality-of-life at baseline and at 6 months after treatment was assessed by EPIC-CP questionnaires in the domains of urinary and sexual function. RESULTS: Of the 143 participants, 136 (95%) completed MRGB at 6 months after treatment. In 103/136 (76%), the biopsy revealed no csPCa. Of the 103, 71 subsequently had an 18-month comprehensive biopsy; of the 71 with 18-month biopsies, 46 (65%) were found to have no csPCa. MRI lesions became undetectable in 96/130 (74%); declines in median serum PSA levels (6.9 to 2.5 ng/mL), PSA density (0.15 to 0.07), and prostate volume (42 to 34cc) were observed (all p < 0.01). Neither lesion disappearance on MRI nor PSA decline correlated with biopsy outcome. Urinary function was affected only slightly and sexual function moderately. CONCLUSION: In the near to intermediate term, partial gland ablation with cryotherapy was found to be a safe and moderately effective treatment of intermediate-risk prostate cancer. Eradication of cancer was better determined by MRI-guided biopsy than by MRI or PSA.