Serial changes in tumour measurements and apparent diffusion coefficients in prostate cancer patients on active surveillance with and without histopathological progression

Abstract

Objective: To analyse serial changes in MRI-derived tumour measurements and apparent diffusion coefficient (ADC) values in prostate cancer (PCa) patients on active surveillance (AS) with and without histopathological disease progression. Methods: This study included AS patients with biopsy-proven PCa with a minimum of two consecutive MR examinations and at least one repeat targeted biopsy. Tumour volumes, largest axial two-dimensional (2D) surface areas, and maximum diameters were measured on T2 weighted images (T2WI). ADC values were derived from the whole lesions, 2D areas, and small-volume regions of interest (ROIs) where tumours were most conspicuous. Areas under the ROC curve (AUCs) were calculated for combinations of T2WI and ADC parameters with optimal specificity and sensitivity. Results: 60 patients (30 progressors and 30 non-progressors) were included. In progressors, T2WI-derived tumour volume, 2D surface area, and maximum tumour diameter had a median increase of +99.5%,+55.3%, and +21.7% compared to +29.2%,+8.1%, and +6.9% in non-progressors (p < 0.005 for all). Follow-up whole-volume and small-volume ROIs ADC values were significantly reduced in progressors (−11.7% and −9.5%) compared to non-progressors (−6.1% and −1.6%) (p < 0.05 for both). The combined AUC of a relative increase in maximum tumour diameter by 20% and reduction in small-volume ADC by 10% was 0.67. Conclusion: AS patients show significant differences in tumour measurements and ADC values between those with and without histopathological disease progression. Advances in knowledge: This paper proposes specific clinical cut-offs for T2WI-derived maximum tumour diameter (+20%) and small-volume ADC (−10%) to predict histopathological PCa progression on AS and supplement subjective serial MRI assessment.

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance

“…As a result, the AUC of the most holistic model combining TSR and time series PSAd was the closest to that of an expert-derived PRECISE assessment, and it was also considerably higher than previously reported serial MRI performance pooled across different centres [ 7 ]. Finally, some radiomic features that passed the robustness analysis including Maximum 2D Diameter Row and Surface Area directly correspond to previously identified tumour measurements that are known to differ between progressors and non-progressors [ 32 , 33 ]. These findings suggest that TSR with or without the addition of time series PSAd may offer a quantitative and interpretable solution to standardising serial MRI assessment in AS, with potential to increase radiologists’ confidence and improve performance across centres and healthcare systems by achieving the expert-derived PRECISE standard.…”

The Role of Magnetic Resonance Imaging (MRI) and MRI-Targeted Biopsy for Active Surveillance

“…In patients undergoing AS, there were no significant differences in the growth rates of PCa tumors between grade I and grade II (18% vs. 23%, p=0.16), as determined by mpMRI [34]. However, another study identified tumor diameter and small-volume ADC as significant predictors of pathological progression during AS [35]. Specifically, a 20% increase in tumor diameter and a 10% decrease in small-volume ADC were proposed as threshold values.…”

Stability of Multi-Parametric Prostate MRI Radiomic Features to Variations in Segmentation

“…Algohary, Ahmad, et al [14] evaluated the performance of radiomics in identifying the presence of clinically significant PCa in AS patients. A few other studies [15,16] focused on clinical features and/or a chosen set of shape and firstorder features extracted from MRI sequences for progression prediction. Albeit, these studies only included patients with MRI visible lesions wherein lesions served as the ROI for extracting radiomics features.…”