Prostate Cancer Staging Based On High B-Value Diffusion Weighted Magnetic Resonance Imaging

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 DW$\mathrm{I}_{b2000}$, ranked based on Kruskal-Wallis (p$\lt$0.001) and one-tail Wilcoxon rank-sum test (p$\leq$0.05) for multi- and pair-wise comparisons. RFs stability was assessed as segmentations varied. The Spearman index $(\rho_{\mathrm{s}})$ assessed the rank correlation between RFs and risk levels. One RF, CVL-m, stratifies patients in 4 progressive classes with $\rho_{\mathrm{s}}=0.81$, thus suggesting that a progressive local tissue heterogeneity can predict PCa prognosis.

[1]  H. G. van der Poel,et al.  Can active surveillance really reduce the harms of overdiagnosing prostate cancer? A reflection of real life clinical practice in the PRIAS study , 2018, Translational andrology and urology.

[2]  Katarzyna J Macura,et al.  Synopsis of the PI-RADS v2 Guidelines for Multiparametric Prostate Magnetic Resonance Imaging and Recommendations for Use. , 2016, European urology.

[3]  Agostino Gibaldi,et al.  Effects of guided random sampling of TCCs on blood flow values in CT perfusion studies of lung tumors. , 2015, Academic radiology.

[4]  Alessandro Bevilacqua,et al.  A novel approach for semi-quantitative assessment of reliability of blood flow values in DCE-CT perfusion , 2017, Biomed. Signal Process. Control..

[5]  B. Delahunt,et al.  The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System , 2015, The American journal of surgical pathology.

[6]  D. Margolis,et al.  Developments in MRI-targeted prostate biopsy. , 2020, Current opinion in urology.

[7]  H. G. van der Poel,et al.  EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent. , 2017, European urology.

[8]  Amy Kaczmarowski,et al.  Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging , 2017, Journal of medical imaging.

[9]  Michael Götz,et al.  Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values. , 2018, Radiology.

[10]  A. Jemal,et al.  Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries , 2018, CA: a cancer journal for clinicians.

[11]  Chris Metcalfe,et al.  Short term outcomes of prostate biopsy in men tested for cancer by prostate specific antigen: prospective evaluation within ProtecT study , 2012, BMJ : British Medical Journal.

[12]  H. Hricak,et al.  Characterization of prostate cancer with MR spectroscopic imaging and diffusion-weighted imaging at 3 Tesla. , 2019, Magnetic resonance imaging.

[13]  A. Evans,et al.  Prostate tissue composition and MR measurements: investigating the relationships between ADC, T2, K(trans), v(e), and corresponding histologic features. , 2010, Radiology.