Biologic Significance of Magnetic Resonance Imaging Invisibility in Localized Prostate Cancer

Molecular Correlates of Prostate Cancer Visibility on Multiparametric Magnetic Resonance Imaging: A Systematic Review

BACKGROUND AND OBJECTIVE

Although prostate magnetic resonance imaging (MRI) is increasingly used to diagnose and stage prostate cancer (PCa), the biologic and clinical significance of MRI visibility of the disease is unclear. Our aim was to examine the existing knowledge regarding the molecular correlates of MRI visibility of PCa.

METHODS

The PubMed, Scopus, and Web of Science databases were queried through November 2023. We defined MRI-visible and MRI-invisible lesions based on the Prostate Imaging Reporting and Data System (PI-RADS) score, and compared these based on the genomic, transcriptomic, and proteomic characteristics.

KEY FINDINGS AND LIMITATIONS

From 2015 individual records, 25 were selected for qualitative data synthesis. Current evidence supports the polygenic nature of MRI visibility, primarily influenced by genes related to stroma, adhesion, and cellular organization. Several gene signatures related to MRI visibility were associated with oncologic outcomes, which support that tumors appearing as PI-RADS 4-5 lesions harbor lethal disease. Accordingly, MRI-invisible tumors detected by systematic biopsies were, generally, less aggressive and had a more favorable prognosis; however, some MRI-invisible tumors harbored molecular features of biologically aggressive PCa. Among the commercially available prognostic gene panels, only Decipher was strongly associated with MRI visibility.

CONCLUSIONS AND CLINICAL IMPLICATIONS

High PI-RADS score is associated with biologically and clinically aggressive PCa molecular phenotypes, and could potentially be used as a biomarker. However, MRI-invisible lesions can harbor adverse features, advocating the continued use of systemic biopsies. Further research to refine the integration of imaging data to prognostic assessment is warranted.

PATIENT SUMMARY

Magnetic resonance imaging visibility of prostate cancer is a polygenic trait. Higher Prostate Imaging Reporting and Data System scores are associated with features of biologically and clinically aggressive cancer.

Development and Validation of an 18-Gene Urine Test for High-Grade Prostate Cancer

Importance

Benefits of prostate cancer (PCa) screening with prostate-specific antigen (PSA) alone are largely offset by excess negative biopsies and overdetection of indolent cancers resulting from the poor specificity of PSA for high-grade PCa (ie, grade group [GG] 2 or greater).

Objective

To develop a multiplex urinary panel for high-grade PCa and validate its external performance relative to current guideline-endorsed biomarkers.

Design, Setting, and Participants

RNA sequencing analysis of 58 724 genes identified 54 markers of PCa, including 17 markers uniquely overexpressed by high-grade cancers. Gene expression and clinical factors were modeled in a new urinary test for high-grade PCa (MyProstateScore 2.0 [MPS2]). Optimal models were developed in parallel without prostate volume (MPS2) and with prostate volume (MPS2+). The locked models underwent blinded external validation in a prospective National Cancer Institute trial cohort. Data were collected from January 2008 to December 2020, and data were analyzed from November 2022 to November 2023.

Exposure

Protocolized blood and urine collection and transrectal ultrasound-guided systematic prostate biopsy.

Main Outcomes and Measures

Multiple biomarker tests were assessed in the validation cohort, including serum PSA alone, the Prostate Cancer Prevention Trial risk calculator, and the Prostate Health Index (PHI) as well as derived multiplex 2-gene and 3-gene models, the original 2-gene MPS test, and the 18-gene MPS2 models. Under a testing approach with 95% sensitivity for PCa of GG 2 or greater, measures of diagnostic accuracy and clinical consequences of testing were calculated. Cancers of GG 3 or greater were assessed secondarily.

Results

Of 761 men included in the development cohort, the median (IQR) age was 63 (58-68) years, and the median (IQR) PSA level was 5.6 (4.6-7.2) ng/mL; of 743 men included in the validation cohort, the median (IQR) age was 62 (57-68) years, and the median (IQR) PSA level was 5.6 (4.1-8.0) ng/mL. In the validation cohort, 151 (20.3%) had high-grade PCa on biopsy. Area under the receiver operating characteristic curve values were 0.60 using PSA alone, 0.66 using the risk calculator, 0.77 using PHI, 0.76 using the derived multiplex 2-gene model, 0.72 using the derived multiplex 3-gene model, and 0.74 using the original MPS model compared with 0.81 using the MPS2 model and 0.82 using the MPS2+ model. At 95% sensitivity, the MPS2 model would have reduced unnecessary biopsies performed in the initial biopsy population (range for other tests, 15% to 30%; range for MPS2, 35% to 42%) and repeat biopsy population (range for other tests, 9% to 21%; range for MPS2, 46% to 51%). Across pertinent subgroups, the MPS2 models had negative predictive values of 95% to 99% for cancers of GG 2 or greater and of 99% for cancers of GG 3 or greater.

Conclusions and Relevance

In this study, a new 18-gene PCa test had higher diagnostic accuracy for high-grade PCa relative to existing biomarker tests. Clinically, use of this test would have meaningfully reduced unnecessary biopsies performed while maintaining highly sensitive detection of high-grade cancers. These data support use of this new PCa biomarker test in patients with elevated PSA levels to reduce the potential harms of PCa screening while preserving its long-term benefits.

Quality checkpoints in the MRI-directed prostate cancer diagnostic pathway

Multiparametric MRI of the prostate is now recommended as the initial diagnostic test for men presenting with suspected prostate cancer, with a negative MRI enabling safe avoidance of biopsy and a positive result enabling MRI-directed sampling of lesions. The diagnostic pathway consists of several steps, from initial patient presentation and preparation to performing and interpreting MRI, communicating the imaging findings, outlining the prostate and intra-prostatic target lesions, performing the biopsy and assessing the cores. Each component of this pathway requires experienced clinicians, optimized equipment, good inter-disciplinary communication between specialists, and standardized workflows in order to achieve the expected outcomes. Assessment of quality and mitigation measures are essential for the success of the MRI-directed prostate cancer diagnostic pathway. Quality assurance processes including Prostate Imaging-Reporting and Data System, template biopsy, and pathology guidelines help to minimize variation and ensure optimization of the diagnostic pathway. Quality control systems including the Prostate Imaging Quality scoring system, patient-level outcomes (such as Prostate Imaging-Reporting and Data System MRI score assignment and cancer detection rates), multidisciplinary meeting review and audits might also be used to provide consistency of outcomes and ensure that all the benefits of the MRI-directed pathway are achieved.

Comparison of Multiparametric Magnetic Resonance Imaging with Prostate-Specific Membrane Antigen Positron-Emission Tomography Imaging in Primary Prostate Cancer Diagnosis: A Systematic Review and Meta-Analysis

Multiparametric magnetic-resonance imaging (mpMRI) has proven utility in diagnosing primary prostate cancer. However, the diagnostic potential of prostate-specific membrane antigen positron-emission tomography (PSMA PET) has yet to be established. This study aims to systematically review the current literature comparing the diagnostic performance of mpMRI and PSMA PET imaging to diagnose primary prostate cancer. A systematic literature search was performed up to December 2021. Quality analyses were conducted using the QUADAS-2 tool. The reference standard was whole-mount prostatectomy or prostate biopsy. Statistical analysis involved the pooling of the reported diagnostic performances of each modality, and differences in per-patient and per-lesion analysis were compared using a Fisher’s exact test. Ten articles were included in the meta-analysis. At a per-patient level, the pooled values of sensitivity, specificity, and area under the curve (AUC) for mpMRI and PSMA PET/CT were 0.87 (95% CI: 0.83−0.91) vs. 0.93 (95% CI: 0.90−0.96, p < 0.01); 0.47 (95% CI: 0.23−0.71) vs. 0.54 (95% CI: 0.23−0.84, p > 0.05); and 0.84 vs. 0.91, respectively. At a per-lesion level, the pooled sensitivity, specificity, and AUC value for mpMRI and PSMA PET/CT were lower, at 0.63 (95% CI: 0.52−0.74) vs. 0.79 (95% CI: 0.62−0.92, p < 0.001); 0.88 (95% CI: 0.81−0.95) vs. 0.71 (95% CI: 0.47−0.90, p < 0.05); and 0.83 vs. 0.84, respectively. High heterogeneity was observed between studies. PSMA PET/CT may better confirm the presence of prostate cancer than mpMRI. However, both modalities appear comparable in determining the localisation of the lesions.

Identifying Risk Factors for MRI-Invisible Prostate Cancer in Patients Undergoing Transperineal Saturation Biopsy

Purpose

Prostatic multi-parametric magnetic resonance imaging (mpMRI) has markedly improved the assessment of men with suspected prostate cancer (PCa). Nevertheless, as mpMRI exhibits a high negative predictive value, a negative MRI may represent a diagnostic dilemma. The aim of this study was to evaluate the incidence of positive transperineal saturation biopsy in men who have negative mpMRI and to analyse the factors associated with positive biopsy in this scenario.

Patients and Methods

A retrospective study of men with normal mpMRI and suspicion of PCa who underwent saturation biopsy (≥20 cores) was carried out. A total of 580 patients underwent transperineal MRI/transrectal ultrasound fusion targeted biopsies or saturation prostate biopsies from January 2017 to September 2020. Of them, 73 had a pre-biopsy negative mpMRI (with Prostate Imaging – Reporting and Data System, PI-RADS, ≤2) and were included in this study. Demographics, clinical characteristics, data regarding biopsy results and potential predictive factors of positive saturation biopsy were collected. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for MRI-invisible PCa.

Results

The detection rate of PCa with saturation biopsy in patients with negative MRI was 34/73 (46.58%). Out of 34 MRI-invisible prostate cancers detected, 12 (35.29%) were clinically significant PCa (csPCa) forms. Regarding factors of positive biopsy, in univariate analysis, the use of 5-alpha reductase inhibitors and free:total prostate-specific antigen (PSA) ratio were associated with the result of the saturation biopsy. In multivariate analysis, only an unfavourable free:total PSA ratio remained a risk factor (OR 11.03, CI95% 1.93–63.15, p=0.01). Furthermore, multivariate logistic analysis demonstrated that prostate volume >50mL significantly predicts the absence of csPCa on saturation biopsy (OR 0.11, 95% CI 0.01–0.94, p=0.04).

Conclusion

A free:total PSA ratio <20% is a risk factor for MRI-invisible PCa. Saturation biopsy could be considered in patients with suspected PCa, despite having a negative MRI.

Use of the MyProstateScore Test to Rule Out Clinically Significant Cancer: Validation of a Straightforward Clinical Testing Approach

PURPOSE

The MyProstateScore test was validated for improved detection of clinically significant (grade group ≥2) prostate cancer relative to prostate specific antigen based risk calculators. We sought to validate an optimal MyProstateScore threshold for clinical use in ruling out grade group ≥2 cancer in men referred for biopsy.

MATERIALS AND METHODS

Biopsy naïve men provided post-digital rectal examination urine prior to biopsy. MyProstateScore was calculated using the validated, locked multivariable model including only serum prostate specific antigen, urinary prostate cancer antigen 3 and urinary TMPRSS2:ERG. The MyProstateScore threshold approximating 95% sensitivity for grade group ≥2 cancer was identified in a training cohort, and performance was measured in 2 external validation cohorts. We assessed the 1) overall biopsy referral population and 2) population meeting guideline based testing criteria (ie, prostate specific antigen 3-10, or <3 with suspicious digital rectal examination).

RESULTS

Validation cohorts were prospectively enrolled from academic (977 patients, median prostate specific antigen 4.5, IQR 3.1-6.0) and community (548, median prostate specific antigen 4.9, IQR 3.7-6.8) settings. In the overall validation population (1,525 patients), 338 men (22%) had grade group ≥2 cancer on biopsy. The MyProstateScore threshold of 10 provided 97% sensitivity and 98% negative predictive value for grade group ≥2 cancer. MyProstateScore testing would have prevented 387 unnecessary biopsies (33%), while missing only 10 grade group ≥2 cancers (3.0%). In 1,242 patients meeting guideline based criteria, MyProstateScore ≤10 provided 96% sensitivity and 97% negative predictive value, and would have prevented 32% of unnecessary biopsies, missing 3.7% of grade group ≥2 cancers.

CONCLUSIONS

In a large, clinically pertinent biopsy referral population, MyProstateScore ≤10 provided exceptional sensitivity and negative predictive value for ruling out grade group ≥2 cancer. This straightforward secondary testing approach would reduce the use of more costly and invasive procedures after screening with prostate specific antigen.

Magnetic Resonance Imaging Based Radiomic Models of Prostate Cancer: A Narrative Review

Simple Summary

The increasing interest in implementing artificial intelligence in radiomic models has occurred alongside advancement in the tools used for computer-aided diagnosis. Such tools typically apply both statistical and machine learning methodologies to assess the various modalities used in medical image analysis. Specific to prostate cancer, the radiomics pipeline has multiple facets that are amenable to improvement. This review discusses the steps of a magnetic resonance imaging based radiomics pipeline. Present successes, existing opportunities for refinement, and the most pertinent pending steps leading to clinical validation are highlighted.

Abstract

The management of prostate cancer (PCa) is dependent on biomarkers of biological aggression. This includes an invasive biopsy to facilitate a histopathological assessment of the tumor’s grade. This review explores the technical processes of applying magnetic resonance imaging based radiomic models to the evaluation of PCa. By exploring how a deep radiomics approach further optimizes the prediction of a PCa’s grade group, it will be clear how this integration of artificial intelligence mitigates existing major technological challenges faced by a traditional radiomic model: image acquisition, small data sets, image processing, labeling/segmentation, informative features, predicting molecular features and incorporating predictive models. Other potential impacts of artificial intelligence on the personalized treatment of PCa will also be discussed. The role of deep radiomics analysis-a deep texture analysis, which extracts features from convolutional neural networks layers, will be highlighted. Existing clinical work and upcoming clinical trials will be reviewed, directing investigators to pertinent future directions in the field. For future progress to result in clinical translation, the field will likely require multi-institutional collaboration in producing prospectively populated and expertly labeled imaging libraries.

Genetic Landscape of Prostate Cancer Conspicuity on Multiparametric Magnetic Resonance Imaging: A Systematic Review and Bioinformatic Analysis

Context

Multiparametric magnetic resonance imaging (mpMRI) detects most, but not all, clinically significant prostate cancer. The genetic basis of prostate cancer visibility and invisibility on mpMRI remains uncertain.

Objective

To systematically review the literature on differential gene expression between mpMRI-visible and mpMRI-invisible prostate cancer, and to use bioinformatic analysis to identify enriched processes or cellular components in genes validated in more than one study.

Evidence acquisition

We performed a systematic literature search of the Medline, EMBASE, PubMed, and Cochrane databases up to January 2020 in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. The primary endpoint was differential genetic features between mpMRI-visible and mpMRI-invisible tumours. Secondary endpoints were explanatory links between gene function and mpMRI conspicuity, and the prognostic value of differential gene enrichment.

Evidence synthesis

We retrieved 445 articles, of which 32 met the criteria for inclusion. Thematic synthesis from the included studies showed that mpMRI-visible cancer tended towards enrichment of molecular features associated with increased disease aggressivity, including phosphatase and tensin homologue (PTEN) loss and higher genomic classifier scores, such as Oncotype and Decipher. Three of the included studies had accompanying publicly available data suitable for further bioinformatic analysis. An over-representation analysis of these datasets revealed increased expression of genes associated with extracellular matrix components in mpMRI-visible tumours.

Conclusions

Prostate cancer that is visible on mpMRI is generally enriched with molecular features of tumour development and aggressivity, including activation of proliferative signalling, DNA damage, and inflammatory processes. Additionally, there appears to be concordant cellular components and biological processes associated with mpMRI conspicuity, as highlighted by bioinformatic analysis of large genetic datasets.

Patient summary

Prostate cancer that is detected by magnetic resonance imaging (MRI) tends to have genetic features that are associated with more aggressive disease. This suggests that MRI can be used to assess the likelihood of aggressive prostate cancer, based on tumour visibility.

The Precision Prostatectomy: an IDEAL Stage 0, 1 and 2a Study

Objective

This study aimed to develop a preclinical model of prostate cancer (CaP) for studying focal/hemiablation of the prostate (IDEAL stage 0), and to use the information from the stage 0 investigation to design a novel focal surgical treatment approach—the precision prostatectomy (IDEAL stage 1/2a).

Methods

The IDEAL stage 0 study included simulation of focal/hemiablation in whole-mount prostate specimens obtained from 100 men who had undergone radical prostatectomies, but met the criteria for focal/hemiablation. The IDEAL stage 1/2a was a prospective, single-arm, Institutional Review Board-approved study of precision prostatectomy undertaken in eight men, who met the predetermined criteria. Criteria for both stages included (1) prostate-specific antigen (PSA) ≤15 ng/mL, (2) stage ≤cT2, (3) dominant unilateral lesion with Gleason ≤4+3 with any number of cores or % cores involved ipsilaterally on transrectal biopsy, (4) no primary Gleason ≥4 contralaterally on transrectal biopsy, and (5) preoperative erectile function score (International Index of Erectile Function (IIEF)-5) of ≥17 (out of 25) without PDE-5i (applicable only to the stage 1/2a study participants). Feasibility and safety of the precision prostatectomy technique, and short-term urinary, sexual and oncological outcomes were studied.

Results

Analysis of whole-mount specimens in the 100 men showed an index lesion (>1 cm in diameter) in all. Ninety-eight men had satellite lesions smaller than 0.5 cm∧3 in volume—46 on the side of the dominant lesions and 52 in the contralateral lobe. If the men in this modeling cohort had undergone focal ablation with a 5–10 mm untreated margin, all except one would have had at least Gleason 6 residual cancer. If they had undergone hemiablation with no untreated tissue on the ablated side, 56 men would have had residual cancer on the contralateral side, of whom 21 would have had clinically significant cancer (Gleason 7 or higher). If these men had undergone precision prostatectomy, with preservation of 5–10 mm of tissue on the non-dominant side, 10% and 4% would have had Gleason 3+4 and Gleason 4+3 disease left behind, respectively. For the stage 1/2a study, the median (IQR) age, PSA and IIEF-5 scores at the time of surgery were 54 (52–57) years, 4.4 (3.8–6.1) ng/mL and 24 (23-25), respectively. All eight patients were continent and sexually active at 12 months with a median IIEF-5 score of 21 (out of 25). At 24–30 months from surgery, the median PSA was 0.2 (range 0.1–0.7) ng/mL. Six men had undergone follow-up protocol biopsies, two, with undetectable PSA, had refused. Two men had residual Gleason 3+3 cancer, with PSA of 0.7 and 0.4 ng/mL, and remain on active surveillance. No man has undergone secondary whole-gland therapy.

Conclusions

Examination of whole-mount radical prostatectomy specimens in men who fit the conventional criteria of focal/hemiablation showed that approximately 21%–68% of men would have clinically significant CaP in the untreated tissue. In a small development cohort, precision prostatectomy was technically feasible, with excellent postoperative functional recovery. At 30 months of follow-up, no patient had clinically significant residual cancer or required secondary treatment. Pending long-term follow-up, a risk-stratified surgical approach may avoid whole-gland therapy and preserve erectile function in the majority of men with intermediate-risk CaP.