Purpose: To assess to what extent radiomic features computed on high b-value DWI sequences (b=2000s/mm2) could reliably detect non-clinically significant (NCS) prostate cancer and reduce overtreatment. Materials and Methods: This study retrospectively enrolled 25 patients of our institution, randomly extracted from PACS with clinical suspicion of PCa who underwent prostate 3T-mpMRI. 10 patients reported NCS-PCa after TRUS biopsy, with Gleason Score (GS)≤3+3, 15 were CS-PCa. PCa Regions of Interest (ROIs) were outlined in all slices by two experienced radiologists in consensus and reported on the DWI sequences, when needed, where 84 radiomic features with the corresponding ROC curves were computed. In order to prevent overfitting, a one-only feature was selected yielding the highest AUC and p-value<0.001 at the one-tail Wilcoxon rank-sum test. Results: The dispersion of local skewness (LS) of DWI values is higher for CS-PCa (p-value~10-4) and AUC=0.92 (95%CI, 0.70-0.99). Sensitivity and specificity for NCS were 90% and 87%, respectively (1 FN and 2 FP), with False Omission Rate (FOR) equal to 7%, this representing a very low risk of overtreatment. Moreover, the two FPs have GS=3+4, the CS-PCa group closest to NCS one. Conclusions: Radiomic features extracted from high b-values DWI sequences allows highlighting non-visible image properties related to complexity of tumour habitat. The higher variability of LS hints at increasing heterogeneity of tumour micro-environment for CS-PCa. In addition, this excellent performance stresses the promising role of DWI-based radiomics in discriminating CS-PCa from NCS-PCa. Limitations: No clinical parameters were considered for differentiation. However, at most they could improve these results. In addition, the number of patients is limited, but uneven in their characteristics, since not derived from any dedicated study. Ethics committee approval: IRB approval, written informed consent was waived. Funding: No funding was received for this work.

Alessandro Bevilacqua, M.M. (2020). Radiomics in DW-MRI detects non-clinically significant prostate cancer and reduces overtreatment. INSIGHTS INTO IMAGING, 11(Suppl 1), 185-185.

Radiomics in DW-MRI detects non-clinically significant prostate cancer and reduces overtreatment

Alessandro Bevilacqua;Margherita Mottola;
2020

Abstract

Purpose: To assess to what extent radiomic features computed on high b-value DWI sequences (b=2000s/mm2) could reliably detect non-clinically significant (NCS) prostate cancer and reduce overtreatment. Materials and Methods: This study retrospectively enrolled 25 patients of our institution, randomly extracted from PACS with clinical suspicion of PCa who underwent prostate 3T-mpMRI. 10 patients reported NCS-PCa after TRUS biopsy, with Gleason Score (GS)≤3+3, 15 were CS-PCa. PCa Regions of Interest (ROIs) were outlined in all slices by two experienced radiologists in consensus and reported on the DWI sequences, when needed, where 84 radiomic features with the corresponding ROC curves were computed. In order to prevent overfitting, a one-only feature was selected yielding the highest AUC and p-value<0.001 at the one-tail Wilcoxon rank-sum test. Results: The dispersion of local skewness (LS) of DWI values is higher for CS-PCa (p-value~10-4) and AUC=0.92 (95%CI, 0.70-0.99). Sensitivity and specificity for NCS were 90% and 87%, respectively (1 FN and 2 FP), with False Omission Rate (FOR) equal to 7%, this representing a very low risk of overtreatment. Moreover, the two FPs have GS=3+4, the CS-PCa group closest to NCS one. Conclusions: Radiomic features extracted from high b-values DWI sequences allows highlighting non-visible image properties related to complexity of tumour habitat. The higher variability of LS hints at increasing heterogeneity of tumour micro-environment for CS-PCa. In addition, this excellent performance stresses the promising role of DWI-based radiomics in discriminating CS-PCa from NCS-PCa. Limitations: No clinical parameters were considered for differentiation. However, at most they could improve these results. In addition, the number of patients is limited, but uneven in their characteristics, since not derived from any dedicated study. Ethics committee approval: IRB approval, written informed consent was waived. Funding: No funding was received for this work.
2020
Alessandro Bevilacqua, M.M. (2020). Radiomics in DW-MRI detects non-clinically significant prostate cancer and reduces overtreatment. INSIGHTS INTO IMAGING, 11(Suppl 1), 185-185.
Alessandro Bevilacqua, Margherita Mottola, Fabio Ferroni, Giampaolo Gavelli, Domenico Barone
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/759082
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