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EnglishRadiomic features (RFs) based on multiparametric MRI (mpMRI) seem promising biomarkers of prostate cancer (PCa), although working with multiple mpMRI sequences makes standardization and proving RFs clinical reliability more challenging. Our study aims at investigating whether local RFs based on one-only high b-value Diffusion Weighted (DW) sequence can stratify patients according to four classes with progressive PCa risk levels. 42 biopsy-proven patients were enrolled, including patients with negative biopsy and either negative (n=7) or positive (n=10) mpMRI, NCS-PCa (n=10), and CS-PCa (n=15). 84 RFs measuring local heterogeneity were extracted from DWIb2000, ranked based on Kruskal-Wallis (p<0.001) and one-tail Wilcoxon rank-sum test (p≤0.05) for multi- and pair-wise comparisons. RFs stability was assessed as segmentations varied. The Spearman index (ρs) assessed the rank correlation between RFs and risk levels. One RF, CVL-m, stratifies patients in 4 progressive classes with ρs=0.81, thus suggesting that a progressive local tissue heterogeneity can predict PCa prognosis.
| Titolo: | Prostate cancer staging based on high b-value diffusion weighted magnetic resonance imaging | |
| Autore/i: | Margherita Mottola; Alessandro Bevilacqua; Fabio Ferroni; Giampaolo Gavelli; Domenico Barone | |
| Autore/i Unibo: | ||
| Anno: | 2021 | |
| Titolo del libro: | Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI 2021) | |
| Pagina iniziale: | 1386 | |
| Pagina finale: | 1389 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/ISBI48211.2021.9434118 | |
| Abstract: | Radiomic features (RFs) based on multiparametric MRI (mpMRI) seem promising biomarkers of prostate cancer (PCa), although working with multiple mpMRI sequences makes standardization and proving RFs clinical reliability more challenging. Our study aims at investigating whether local RFs based on one-only high b-value Diffusion Weighted (DW) sequence can stratify patients according to four classes with progressive PCa risk levels. 42 biopsy-proven patients were enrolled, including patients with negative biopsy and either negative (n=7) or positive (n=10) mpMRI, NCS-PCa (n=10), and CS-PCa (n=15). 84 RFs measuring local heterogeneity were extracted from DWIb2000, ranked based on Kruskal-Wallis (p<0.001) and one-tail Wilcoxon rank-sum test (p≤0.05) for multi- and pair-wise comparisons. RFs stability was assessed as segmentations varied. The Spearman index (ρs) assessed the rank correlation between RFs and risk levels. One RF, CVL-m, stratifies patients in 4 progressive classes with ρs=0.81, thus suggesting that a progressive local tissue heterogeneity can predict PCa prognosis. | |
| Data stato definitivo: | 4-giu-2021 | |
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