Biparametric versus multiparametric magnetic resonance imaging of the prostate: detection of clinically significant cancer in a perfect match group

Could Biparametric MRI Replace Multiparametric MRI in the Management of Prostate Cancer?

Prostate cancer (PCa) is a worldwide epidemiological problem, since it is one of the most prevalent types of neoplasia among men, and the third-leading cause of cancer-related deaths, after lung and colorectal tumors. Unfortunately, the early stages of PCa have a wide range of unspecific symptoms. For these reasons, early diagnosis and accurate evaluation of suspicious lesions are crucial. Multiparametric MRI (mpMRI) is currently the imaging modality of choice for diagnostic screening and local staging of PCa, but also has a leading role in guiding biopsies and in treatment biparametric MRI (bpMRI) could partially replace mpMRI due to its lack of adverse reactions caused by contrast agents, relatively lower costs, and shorter acquisition time. Further, 31 relevant articles regarding the advantages and disadvantages of the aforementioned imaging techniques were scanned. As a result, while bpMRI has comparable accuracy in detecting PCa, its roles in the other steps of PCa management are limited.

Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy

BACKGROUND

Biologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level.

METHODS

Seventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov-Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen's d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone.

RESULTS

All MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours.

CONCLUSIONS

Incorporating DCE MRI parameters with DWI and T2w gives improved accuracy for tumour detection at a voxel level. DCE MRI parameters should be used to spatially characterise tumour biology for biologically targeted radiation therapy treatment planning.

Temporal changes of PIRADS scoring by radiologists and correlation to radical prostatectomy pathological outcomes

Purpose

To assess temporal improvement of prostate image reporting and data system (PIRADS) 3-5 lesion correlation to histopathologic findings from radical prostatectomy (RP) in prostate cancer (PCa).

Materials and methods

A total of 1481 patients who underwent RP for biopsy-proven PCa between 2015 and 2019 were divided into 14 groups of 100 sequential readings for the evaluation of histopathological correlation with PIRADS readings. Temporal trends of PIRADS distribution and predictive performance for RP pathology were evaluated to assess underlying changes in prostate magnetic resonance imaging (MRI) interpretation by radiologists.

Results

PIRADS 4-5 lesions were significantly correlated with the increasing rates of Gleason Group (GG) upgrade (p = 0.044) and decreasing rate of GG downgrade (p = 0.016) over time. PIRADS ≥3 lesions read after median 2 years of experience were shown to independently predict intermediate-high-risk (GG ≥ 3) PCa (odds ratio 2.93, 95% confidence interval 1.00-8.54; P= 0.049) in RP pathology. Preoperative GG ≥ 3 biopsy lesions with PIRADS 4-5 lesions were significantly more susceptible to GG upgrade (P= 0.035) and GG ≥ 4 RP pathology (p = 0.003) in experienced reads, in contrast to insignificant findings in early readings (p = 0.588 and 0.248, respectively).

Conclusion

Preoperative MRI reports matched with RP pathology suggest an improved prediction of adverse pathology in PIRADS 3-5 lesions over time, suggesting a temporal change in PIRADS interpretation and predictive accuracy. Institutions with low volume experience should use caution in solely relying on MRI for predicting tumor characteristics. Future prospective trials and larger scale assessments are required to further validate our results.

Current Status of Biparametric MRI in Prostate Cancer Diagnosis: Literature Analysis

The role of multiparametric MRI (mpMRI) in the detection of prostate cancer is well-established. Based on the limited role of dynamic contrast enhancement (DCE) in PI-RADS v2.1, the risk of potential side effects, and the increased cost and time, there has been an increase in studies advocating for the omission of DCE from MRI assessments. Per PI-RADS v2.1, DCE is indicated in the assessment of PI-RADS 3 lesions in the peripheral zone, with its most pronounced effect when T2WI and DWI are of insufficient quality. The aim of this study was to evaluate the methodology and reporting in the literature from the past 5 years regarding the use of DCE in prostate MRI, especially with respect to the indications for DCE as stated in PI-RADS v2.1, and to describe the different approaches used across the studies. We searched for studies investigating the use of bpMRI and/or mpMRI in the detection of clinically significant prostate cancer between January 2017 and April 2022 in the PubMed, Web of Science, and Google Scholar databases. Through the search process, a total of 269 studies were gathered and 41 remained after abstract and full-text screening. The following information was extracted from the eligible studies: general clinical and technical characteristics of the studies, the number of PI-RADS 3 lesions, different definitions of clinically significant prostate cancer (csPCa), biopsy thresholds, reference standard methods, and number and experience of readers. Forty-one studies were included in the study. Only 51% (21/41) of studies reported the prevalence of csPCa in their equivocal lesion (PI-RADS category 3 lesions) subgroups. Of the included studies, none (0/41) performed a stratified sub-analysis of the DCE benefit versus MRI quality and 46% (19/41) made explicit statements about removing MRI scans based on a range of factors including motion, noise, and image artifacts. Furthermore, the number of studies investigating the role of DCE using readers with varying experience was relatively low. This review demonstrates that a high proportion of the studies investigating whether bpMRI can replace mpMRI did not transparently report information inherent to their study design concerning the key indications of DCE, such as the number of clinically insignificant/significant PI-RADS 3 lesions, nor did they provide any sub-analyses to test image quality, with some removing bad quality MRI scans altogether, or reader-experience-dependency indications for DCE. For the studies that reported on most of the DCE indications, their conclusions about the utility of DCE were heavily definition-dependent (with varying definitions of csPCa and of the PI-RADS category biopsy significance threshold). Reporting the information inherent to the study design and related to the specific indications for DCE as stated in PI-RADS v2.1 is needed to determine whether DCE is helpful or not. With most of the recent literature being retrospective and not including the data related to DCE indications in particular, the ongoing dispute between bpMRI and mpMRI is likely to linger.

Current Value of Biparametric Prostate MRI with Machine-Learning or Deep-Learning in the Detection, Grading, and Characterization of Prostate Cancer: A Systematic Review

Prostate cancer detection with magnetic resonance imaging is based on a standardized MRI-protocol according to the PI-RADS guidelines including morphologic imaging, diffusion weighted imaging, and perfusion. To facilitate data acquisition and analysis the contrast-enhanced perfusion is often omitted resulting in a biparametric prostate MRI protocol. The intention of this review is to analyze the current value of biparametric prostate MRI in combination with methods of machine-learning and deep learning in the detection, grading, and characterization of prostate cancer; if available a direct comparison with human radiologist performance was performed. PubMed was systematically queried and 29 appropriate studies were identified and retrieved. The data show that detection of clinically significant prostate cancer and differentiation of prostate cancer from non-cancerous tissue using machine-learning and deep learning is feasible with promising results. Some techniques of machine-learning and deep-learning currently seem to be equally good as human radiologists in terms of classification of single lesion according to the PIRADS score.

Diagnostic value of integrated 18F-PSMA-1007 PET/MRI Compared with that of Biparametric MRI for the detection of Prostate Cancer

Objective

Materials and methods

Results

Conclusion

The value of magnetic resonance imaging and ultrasonography (MRI/US)-fusion biopsy in clinically significant prostate cancer detection in patients with biopsy-naïve men according to PSA levels: A propensity score matching analysis

Objectives

Materials and methods

Results

Conclusions

Comparison between biparametric and multiparametric MR imaging of Prostate Imaging Reporting and Data System Version 2.1 in detection of prostate cancer

Background

Prostate cancer (PCa) is considered to be the commonest cancer among males. Early and precise diagnosis of PCa is essential for adequate treatment. Multiparametric MR imaging (mpMRI) is actually the most precise imaging technique used for early diagnosis of PCa. The aim of this work was to assess the diagnostic capability of biparametric MRI (bpMRI) and multiparametric MRI (mpMRI) of PI-RADS V2.1 in detection of prostate cancer (PCa). This prospective study was carried on 60 male patients with high PSA. bpMRI and mpMRI were performed for all patients using a 3-T MRI scanner. The diagnostic performance of bpMRI of PI-RADS V2.1 was compared to that of mpMRI of PI-RADS V 2.1. The diagnosis of Pca was confirmed by transrectal ultrasound-guided biopsy and the results of open prostatectomy specimens.

Results

When considering PI-RADS categories 1, 2, and 3 as benign and categories 4 and 5 as malignant, mpMRI had higher sensitivity and diagnostic accuracy when compared with bpMRI (sensitivity was 88.6% for mpMRI versus 60% for bpMRI and diagnostic accuracy was 91.7% for mpMRI versus 75% for bpMRI). When considering PI-RADS categories 1 and 2 as benign and PI-RADS categories 3.4 and 5 as malignant, the sensitivity and diagnostic accuracy of bpMRI and mpMRI were comparable (sensitivity was 94.3% for both bpMRI and mpMRI and diagnostic accuracy was 86.7% for both bpMRI and mpMRI).

Conclusion

Considering PI-RADS scores 4 and 5 as malignant, mpMRI had higher sensitivity and diagnostic accuracy when compared with bpMRI; however, when considering PI-RADS scores 3, 4, and 5 as malignant, both bpMRI and mpMRI had similar diagnostic accuracy.