Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI

This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction fic discriminated between Gleason 3 + 3 and 3 + 4 (p = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 (p = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition (p > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R2 = 0.79–0.98; CV = 1–7%; ICC = 92–98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3

Exploring patient views and acceptance of multiparametric magnetic resonance imaging for the investigation of suspected prostate cancer (the PACT Study): a mixed-methods study protocol

BACKGROUND: The introduction of multiparametric magnetic resonance imaging (mpMRI) has improved the diagnosis of suspected prostate cancer, accurately risk-stratifying men before a biopsy. However, pre-biopsy mpMRI represents a significant deviation from the traditional approach of prostate specific antigen testing with subsequent systematic transrectal ultrasound-guided prostate biopsy and we have not yet explored the views of men who experience this new pathway. The purpose of the PACT study (PAtient views and aCceptance of mulTiparametric MRI) is to explore men’s perceptions of mpMRI. METHODS: PACT will be conducted at teaching hospitals in which mpMRI is central to the prostate cancer diagnostic pathway using a two-phase, mixed-methods, quantitative and qualitative approach. In phase I, men referred with suspected prostate cancer will complete detailed surveys to explore their views on the mpMRI-directed pathway compared to the traditional pathway and on what constitutes ‘significant’ prostate cancer. In phase II, these themes will be expanded upon with in-depth, semi-structured interviews. Qualitative data will be transcribed and thematically analysed, and quantitative questionnaire responses will be analysed statistically. DISCUSSION: PACT will provide the first detailed insight into patient perceptions on the use and acceptability of mpMRI. Furthermore, results from PACT will help contribute to the resolution of outstanding controversies that surround this technology

Histopathological features of prostate cancer conspicuity on multiparametric MRI: protocol for a systematic review and meta-analysis

Introduction Multiparametric MRI (mpMRI) has improved risk stratification for men with suspected prostate cancer. Indeed, mpMRI-visible tumours tend to be larger and of higher pathological grade than mpMRI-invisible tumours; however, concern remains around significant cancer that is undetected by mpMRI. There has been considerable recent interest to investigate whether tumour conspicuity on mpMRI is associated with additional histopathological features (including cellular density, microvessel density and unusual prostate cancer subtypes), which may have important clinical implications in both diagnosis and prognosis. Furthermore, analysis of these features may help reveal the radiobiology that underpins the actual mechanisms of mpMRI visibility (and invisibility) of prostate tumours. Here, we describe a protocol for a systematic review of the histopathological basis of prostate cancer conspicuity on mpMRI. Methods and analysis A systematic search of the MEDLINE, PubMed, Embase and Cochrane databases will be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines will be used to guide screening, thematic reporting and conclusions drawn from all eligible studies. Included papers will be full-text, English-language articles, comparing the histopathological characteristics of mpMRI-visible lesions and mpMRI-invisible tumours. All studies published between January 1950 and January 2020 will be eligible for inclusion. Studies using confirmatory immunohistochemistry for the identification of immune subsets or structural components will be included. Study bias and quality will be assessed using a modified Newcastle-Ottawa scale. To ensure methodological rigour, this protocol is written in accordance with the PRISMA Protocol 2015 checklist. If appropriate, a meta-analysis will be conducted comparing histopathological feature frequency between mpMRI-visible and mpMRI-invisible disease. Ethics and dissemination No ethical approval will be required as this is an academic review of published literature. Findings will be disseminated through publications in peer-reviewed journals and presentations at national and international conferences

The Importance Of Multi-Reader Assessment For External Validation Of Prostate Lesion Classification Models Using Quantitative MpMRI

Machine learning for classifying prostate mpMRI lesions may help reduce unnecessary biopsies. However, external validation with multiple scanners and readers is required before the clinical adoption of such models can be considered. Two readers validated a previously published and well-performing logistic regression model on an external cohort. The model performance was not generalisable and offered no advantage to using PSAd cut-offs, and there was marked variation in model score related to contour differences from different readers. This potential variability should be investigated in future models which use quantitative MRI