False Positive Multiparametric Magnetic Resonance Imaging Phenotypes in the Biopsy-naïve Prostate: Are They Distinct from Significant Cancer-associated Lesions? Lessons from PROMIS

Abstract

Background False positive multiparametric magnetic resonance imaging (mpMRI) phenotypes prompt unnecessary biopsies. The Prostate MRI Imaging Study (PROMIS) provides a unique opportunity to explore such phenotypes in biopsy-naïve men with raised prostate-specific antigen (PSA) and suspected cancer. Objective To compare mpMRI lesions in men with/without significant cancer on transperineal mapping biopsy (TPM). Design, setting, and participants PROMIS participants ( n = 235) underwent mpMRI followed by a combined biopsy procedure at University College London Hospital, including 5-mm TPM as the reference standard. Patients were divided into four mutually exclusive groups according to TPM findings: (1) no cancer, (2) insignificant cancer, (3) definition 2 significant cancer (Gleason ≥3 + 4 of any length and/or maximum cancer core length ≥4 mm of any grade), and (4) definition 1 significant cancer (Gleason ≥4 + 3 of any length and/or maximum cancer core length ≥6 mm of any grade). Outcome measurements and statistical analysis Index and/or additional lesions present in 178 participants were compared between TPM groups in terms of number, conspicuity, volume, location, and radiological characteristics. Results and limitations Most lesions were located in the peripheral zone. More men with significant cancer had two or more lesions than those without significant disease (67% vs 37%; p < 0.001). In the former group, index lesions were larger (mean volume 0.68 vs 0.50 ml; p < 0.001, Wilcoxon test), more conspicuous (Likert 4–5: 79% vs 22%; p < 0.001), and diffusion restricted (mean apparent diffusion coefficient [ADC]: 0.73 vs 0.86; p < 0.001, Wilcoxon test). In men with Likert 3 index lesions, log 2 PSA density and index lesion ADC were significant predictors of definition 1/2 disease in a logistic regression model (mean cross-validated area under the receiver-operator characteristic curve: 0.77 [95% confidence interval: 0.67–0.87]). Conclusions Significant cancer-associated MRI lesions in biopsy-naïve men have clinical-radiological differences, with lesions seen in prostates without significant disease. MRI-calculated PSA density and ADC could predict significant cancer in those with indeterminate MRI phenotypes. Patient summary Magnetic resonance imaging (MRI) lesions that mimic prostate cancer but are, in fact, benign prompt unnecessary biopsies in thousands of men with raised prostate-specific antigen. In this study we found that, on closer look, such false positive lesions have different features from cancerous ones. This means that doctors could potentially develop better tools to identify cancer on MRI and spare some patients from unnecessary biopsies.

Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models

“…We also observed that the VERDICT maps emphasize the true positive lesion in comparison to the surrounding tissue most clearly. Our finding of significantly decreased ADC values in true positives agrees with work by Stavrinides et al, who concluded that ADC could predict clinically significant PCa in biopsy-naive men with indeterminate lesions [ 46 ]. Falaschi et al similarly found a lower ADC ratio in tumors than false positives; however, they could not draw any firm conclusions about the usefulness of the ADC ratio in detecting cancer [ 47 ].…”

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

“…The PRECISION trial showed an inverse association of negative MRI-targeted biopsies with lesion conspicuity reported by the PI-RADS v2.0 criteria [ 29 ]. Starvrinides and colleagues attempted to capture the characteristics of false-positive MRI lesions, which are distinct from clinically significant diseases [ 30 ]. The authors highlighted the use of MRI-calculated PSA density (PSAD) and apparent diffusion coefficient (ADC) as potential predictors of significant disease, a finding verified by the literature [ 30 , 31 , 32 ].…”

“…Starvrinides and colleagues attempted to capture the characteristics of false-positive MRI lesions, which are distinct from clinically significant diseases [ 30 ]. The authors highlighted the use of MRI-calculated PSA density (PSAD) and apparent diffusion coefficient (ADC) as potential predictors of significant disease, a finding verified by the literature [ 30 , 31 , 32 ]. Although ADC was incorporated in the PI-RADS v2.0 criteria, benign diseases such as prostatitis and prostatic atrophy are known to decrease the signal on the ADC map.…”

Artificial Intelligence Compared to Radiologists for the Initial Diagnosis of Prostate Cancer on Magnetic Resonance Imaging: A Systematic Review and Recommendations for Future Studies

“…Remarkably, only two studies used clinical data outside of the imaging and radiologist score [31,45]. Although the focus is often on the available MR data, non-imaging biomarkers such as PSA density have been shown to be useful predictors of clinically significant cancer; incorporating such data when available, alongside MR data, may enhance algorithms [49,50].…”