Inter-reader agreement of the prostate imaging reporting and data system version v2.1 for detection of prostate cancer: A systematic review and meta-analysis

Deep learning image reconstruction of diffusion-weighted imaging in evaluation of prostate cancer focusing on its clinical implications

Background

Image-based assessment of prostate cancer (PCa) is increasingly emphasized in the diagnostic workflow for selecting biopsy targets and possibly predicting clinically significant prostate cancer (csPCa). Assessment is based on Prostate Imaging-Reporting and Data System (PI-RADS) which is largely dependent on T2-weighted image (T2WI) and diffusion weighted image (DWI). This study aims to determine whether deep learning reconstruction (DLR) can improve the image quality of DWI and affect the assessment of PI-RADS ≥4 in patients with PCa.

Methods

In this retrospective study, 3.0T post-biopsy prostate magnetic resonance imaging (MRI) of 70 patients with PCa in Korea University Ansan Hospital from November 2021 to July 2022 was reconstructed with and without using DLR. Four DWI image sets were made: (I) conventional DWI (CDWI): DWI with acceleration factor 2 and conventional parallel imaging reconstruction, (II) DL1: DWI with acceleration factor 2 using DLR, (III) DL2: DWI with acceleration factor 3 using DLR, and (IV) DL3: DWI with acceleration factor 3 and half average b-value using DLR. Apparent diffusion coefficient (ADC) value, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured by one reviewer, while two reviewers independently assessed overall image quality, noise, and lesion conspicuity using a four-point visual scoring system from each DWI image set. Two reviewers also performed PI-RADSv2.1 scoring on lesions suspected of malignancy.

Results

A total of 70 patients (mean age, 70.8±9.7 years) were analyzed. The image acquisition time was 4:46 min for CDWI and DL1, 3:40 min for DL2, and 2:00 min for DL3. DL1 and DL2 images resulted in better lesion conspicuity compared to CDWI images assessed by both readers (P<0.05). DLR resulted in a significant increase in SNR, from 38.4±14.7 in CDWI to 56.9±21.0 in DL1. CNR increased from 25.1±11.5 in CDWI to 43.1±17.8 in DL1 (P<0.001). PI-RADS v2.1 scoring for PCa lesions was more agreeable with the DL1 reconstruction method than with CDWI (κ value CDWI, DL1; 0.40, 0.61, respectively). A statistically significant number of lesions were upgraded from PI-RADS <4 in CDWI image to PI-RADS ≥4 in DL1 images for both readers (P<0.05). Most of the PI-RADS upgraded lesions were from higher than unfavorable intermediate-risk groups according to the 2023 National Comprehensive Cancer Network guidelines with statistically significant difference of marginal probability in DL1 and DL2 for both readers (P<0.05).

Conclusions

DLR in DWI for PCa can provide options for improving image quality with a significant impact on PI-RADS evaluation or about a 23% reduction in acquisition time without compromising image quality.

Evaluating Diagnostic Accuracy and Inter-reader Agreement of the Prostate Imaging After Focal Ablation Scoring System

Background and objective

Focal therapy (FT) is increasingly recognized as a promising approach for managing localized prostate cancer (PCa), notably reducing treatment-related morbidities. However, post-treatment anatomical changes present significant challenges for surveillance using current imaging techniques. This study aimed to evaluate the inter-reader agreement and efficacy of the Prostate Imaging after Focal Ablation (PI-FAB) scoring system in detecting clinically significant prostate cancer (csPCa) on post-FT multiparametric magnetic resonance imaging (mpMRI).

Methods

A retrospective cohort study was conducted involving patients who underwent primary FT for localized csPCa between 2013 and 2023, followed by post-FT mpMRI and a prostate biopsy. Two expert genitourinary radiologists retrospectively evaluated post-FT mpMRI using PI-FAB. The key measures included inter-reader agreement of PI-FAB scores, assessed by quadratic weighted Cohen's kappa (κ), and the system's efficacy in predicting in-field recurrence of csPCa, with a PI-FAB score cutoff of 3. Additional diagnostic metrics including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy were also evaluated.

Key findings and limitations

Scans from 38 patients were analyzed, revealing a moderate level of agreement in PI-FAB scoring (κ = 0.56). Both radiologists achieved sensitivity of 93% in detecting csPCa, although specificity, PPVs, NPVs, and accuracy varied.

Conclusions and clinical implications

The PI-FAB scoring system exhibited high sensitivity with moderate inter-reader agreement in detecting in-field recurrence of csPCa. Despite promising results, its low specificity and PPV necessitate further refinement. These findings underscore the need for larger studies to validate the clinical utility of PI-FAB, potentially aiding in standardizing post-treatment surveillance.

Patient summary

Focal therapy has emerged as a promising approach for managing localized prostate cancer, but limitations in current imaging techniques present significant challenges for post-treatment surveillance. The Prostate Imaging after Focal Ablation (PI-FAB) scoring system showed high sensitivity for detecting in-field recurrence of clinically significant prostate cancer. However, its low specificity and positive predictive value necessitate further refinement. Larger, more comprehensive studies are needed to fully validate its clinical utility.

Population-based Organised Prostate Cancer Testing: Results from the First Invitation of 50-year-old Men

BACKGROUND

The European Union recently recommended evaluation of the feasibility of organised prostate cancer screening. In Sweden, regional population-based organised prostate cancer testing (OPT) programmes were introduced in 2020.

OBJECTIVE

To describe initial participation rates and diagnostic outcomes.

DESIGN, SETTING, AND PARTICIPANTS

The three most populated Swedish regions invited all men aged 50 yr to OPT by a letter in 2020-2022. Men with prostate-specific antigen (PSA) ≥3 ng/ml were referred for prostate magnetic resonance imaging (MRI). PSA assays differed across regions. Men with Prostate Imaging Reporting and Data System (PI-RADS) 1-3 and PSA density ≥0.15 ng/ml/cm3 or PI-RADS 4-5 were referred for a biopsy. Data were obtained from the Swedish Register for Organised Prostate Cancer Testing.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Overall and regional participation rates, PSA distributions, PI-RADS score distributions, cancer detection, and treatment were evaluated.

RESULTS AND LIMITATIONS

A total of 23 855 (35%) of 68 060 invited men participated; 696 (2.9%) had PSA ≥3 ng/ml, and of them, 306 (44%) had a biopsy indication and 221 (32%) had a biopsy. On biopsy, 93 (42%) had Gleason grade group ≥2 (0.39% of PSA-tested men) and 44 (20%) Gleason grade group 1 cancer. Most men with cancer had treatment with curative intent (70%) or were under active surveillance (28%). Across regions, proportions of men with PSA ≥3 ng/ml ranged from 2.3% to 4.0%, and those with PI-RADS score 4-5 ranged from 12% to 21%. A limitation is that results are applicable only to first testing of men in their early 50s.

CONCLUSIONS

The OPT programmes are feasible with good compliance to the diagnostic pathway. The use of MRI and PSA density avoided a biopsy for over half of the men with PSA ≥3 ng/ml. Inter-regional differences in diagnostic outcomes show a need for standardisation of the diagnostic pathway's components.

PATIENT SUMMARY

We report the diagnostic outcomes of inviting 68 000 50-yr-old men to organised prostate cancer testing.

The role of gadolinium-based contrast agents in magnetic resonance imaging structured reporting and data systems (RADS)

Among the 28 reporting and data systems (RADS) available in the literature, we identified 15 RADS that can be used in Magnetic Resonance Imaging (MRI). Performing examinations without using gadolinium-based contrast agents (GBCA) has benefits, but GBCA administration is often required to achieve an early and accurate diagnosis. The aim of the present review is to summarize the current role of GBCA in MRI RADS. This overview suggests that GBCA are today required in most of the current RADS and are expected to be used in most MRIs performed in patients with cancer. Dynamic contrast enhancement is required for correct scores calculation in PI-RADS and VI-RADS, although scientific evidence may lead in the future to avoid the GBCA administration in these two RADS. In Bone-RADS, contrast enhancement can be required to classify an aggressive lesion. In RADS scoring on whole body-MRI datasets (MET-RADS-P, MY-RADS and ONCO-RADS), in NS-RADS and in Node-RADS, GBCA administration is optional thanks to the intrinsic high contrast resolution of MRI. Future studies are needed to evaluate the impact of the high T1 relaxivity GBCA on the assignment of RADS scores.

Application of Advanced Imaging to Prostate Cancer Diagnosis and Management: A Narrative Review of Current Practice and Unanswered Questions

Major advances in prostate cancer diagnosis, staging, and management have occurred over the past decade, largely due to our improved understanding of the technical aspects and clinical applications of advanced imaging, specifically magnetic resonance imaging (MRI) and prostate-cancer-specific positron emission tomography (PET). Herein, we review the established utility of these important and exciting technologies, as well as areas of controversy and uncertainty that remain important areas for future study. There is strong evidence supporting the utility of MRI in guiding initial biopsy and assessing local disease. There is debate, however, regarding how to best use the imaging modality in risk stratification, treatment planning, and assessment of biochemical failure. Prostate-cancer-specific PET is a relatively new technology that provides great value to the evaluation of newly diagnosed, treated, and recurrent prostate cancer. However, its ideal use in treatment decision making, staging, recurrence detection, and surveillance necessitates further research. Continued study of both imaging modalities will allow for an improved understanding of their best utilization in improving cancer care.

Update on Optimization of Prostate MR Imaging Technique and Image Quality

Prostate MR imaging quality has improved dramatically over recent times, driven by advances in hardware, software, and improved functional imaging techniques. MRI now plays a key role in prostate cancer diagnostic work-up, but outcomes of the MRI-directed pathway are heavily dependent on image quality and optimization. MR sequences can be affected by patient-related degradations relating to motion and susceptibility artifacts which may enable only partial mitigation. In this Review, we explore issues relating to prostate MRI acquisition and interpretation, mitigation strategies at a patient and scanner level, PI-QUAL reporting, and future directions in image quality, including artificial intelligence solutions.

Prediction of Significant Prostate Cancer in Equivocal Magnetic Resonance Imaging Lesions: A High-volume International Multicenter Study

BACKGROUND

Decision of performing prostate biopsy in men with Prostate Imaging Reporting and Data System (PI-RADS) 3 findings in prostate magnetic resonance imaging (MRI) is challenging as they have a low but still relevant risk of harboring significant prostate cancer (sPC).

OBJECTIVE

To identify clinical predictors of sPC in men with PI-RADS 3 lesions in prostate MRI and to analyze the hypothetical effect of incorporating prostate-specific antigen density (PSAD) into biopsy decision.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed a retrospective multinational cohort from ten academic centers comprising 1476 men who underwent a combined prostate biopsy (MRI targeted plus systematic biopsy) between February 2012 and April 2021 due to a PI-RADS 3 lesion in prostate MRI.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The primary outcome was the detection of sPC (ISUP ≥2) in a combined biopsy. Predictors were identified by a regression analysis. Descriptive statistics were applied to evaluate the hypothetical effect of involving PSAD into biopsy decision.

RESULTS AND LIMITATIONS

Of all patients, 273/1476 (18.5%) were diagnosed with sPC. MRI-targeted biopsy diagnosed fewer sPC cases than combined strategy: 183/1476 (12.4%) versus 273/1476 (18.5%), p < 0.01. Age (odds ratio [OR] 1.10 [95% confidence interval {CI}: 1.05-1.15], p < 0.001), prior negative biopsy (OR 0.46 [0.24-0.89], p = 0.022), and PSAD (p < 0.001) were found to be independent predictors of sPC. Applying a PSAD cutoff of 0.15, 817/1398 (58.4%) biopsies would have been avoided at the cost of missing sPC in 91 (6.5%) men. Limitations were the retrospective design, heterogeneity of the study cohort due to the long inclusion period, and no central revision of MRI.

CONCLUSIONS

Age, previous biopsy status, and PSAD were found to be independent predictors of sPC in men with equivocal prostate MRI. Implementation of PSAD into biopsy decision can avoid unnecessary biopsies. Clinical parameters such as PSAD need validation in a prospective setting.

PATIENT SUMMARY

In this study, we looked for clinical predictors of significant prostate cancer in men with Prostate Imaging Reporting and Data System 3 lesions in prostate magnetic resonance imaging. We identified age, previous biopsy status, and especially prostate-specific antigen density as independent predictors.

Biparametric MRI-based radiomics classifiers for the detection of prostate cancer in patients with PSA serum levels of 4∼10 ng/mL

Purpose

To investigate the predictive performance of the combined model by integrating clinical variables and radiomic features for the accurate detection of prostate cancer (PCa) in patients with prostate-specific antigen (PSA) serum levels of 4-10 ng/mL.

Methods

A retrospective study of 136 males (mean age, 67.3 ± 8.4 years) with Prostate Imaging-Reporting and Data System (PI-RADS) v2.1 category ≤3 lesions and PSA serum levels of 4-10 ng/mL were performed. All patients underwent multiparametric MRI at 3.0T and transrectal ultrasound-guided systematic prostate biopsy in their clinical workup. Radiomic features were extracted from axial T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps of each patient using PyRadiomics. Pearson correlation coefficient (PCC) and recursive feature elimination (RFE) were implemented to identify the most significant radiomic features. Independent clinic-radiological factors were identified via univariate and multivariate regression analyses. Seven machine-learning algorithms were compared to construct a single-layered radiomic score (ie, radscore) and multivariate regression analysis was applied to construct the fusion radscore. Finally, the radiomic nomogram was further developed by integrating useful clinic-radiological factors and fusion radscore using multivariate regression analysis. The discriminative power of the nomogram was evaluated by area under the curve (AUC), DeLong test, calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC).

Results

The transitional zone-specific antigen density was identified as the only independent clinic-radiological factor, which yielded an AUC of 0.592 (95% confidence interval [CI]: 0.527-0.657). The ADC radscore based on six features and Naive Bayes achieved an AUC of 0.779 (95%CI: 0.730-0.828); the T2WI radscore based on 13 features and Support Vector Machine yielded an AUC of 0.808 (95%CI: 0.761-0.855). The fusion radscore obtained an improved AUC of 0.844 (95%CI: 0.801-0.887), which was higher than the single-layered radscores (both P<0.05). The radiomic nomogram achieved the highest value among all models (all P<0.05), with an AUC of 0.872 (95%CI: 0.835-0.909). Calibration curve showed good agreement and DCA together with CIC confirmed the clinical benefits of the radiomic nomogram.

Conclusion

The radiomic nomogram holds the potential for accurate and noninvasive identification of PCa in patients with PI-RADS ≤3 lesions and PSA of 4-10 ng/mL, which could reduce unnecessary biopsy.