| Autor: |
Lin Li, Rakesh Shiradkar, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, Pingfu Fu, Amr Mahran, Christina Buzzy, Phillip D. Stricker, Ardeshir R. Rastinehad, Cristina Magi-Galluzzi, Lee Ponsky, Eric Klein, Andrei S. Purysko, Anant Madabhushi |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
European Journal of Radiology Open, Vol 10, Iss , Pp 100496- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2352-0477 |
| DOI: |
10.1016/j.ejro.2023.100496 |
| Popis: |
Background: around one third of clinically significant prostate cancer (CsPCa) foci are reported to be MRI non-visible (MRI─). Objective: To quantify the differences between MR visible (MRI+) and MRI─ CsPCa using intra- and peri-lesional radiomic features on bi-parametric MRI (bpMRI). Methods: This retrospective and multi-institutional study comprised 164 patients with pre-biopsy 3T prostate multi-parametric MRI from 2014 to 2017. The MRI─ CsPCa referred to lesions with PI-RADS v2 score 1. Three experienced radiologists were involved in annotating lesions and PI-RADS assignment. The validation set (Dv) comprised 52 patients from a single institution, the remaining 112 patients were used for training (Dt). 200 radiomic features were extracted from intra-lesional and peri-lesional regions on bpMRI.Logistic regression with least absolute shrinkage and selection operator (LASSO) and 10-fold cross-validation was applied on Dt to identify radiomic features associated with MRI─ and MRI+ CsPCa to generate corresponding risk scores RMRI─ and RMRI+. RbpMRI was further generated by integrating RMRI─ and RMRI+. Statistical significance was determined using the Wilcoxon signed-rank test. Results: Both intra-lesional and peri-lesional bpMRI Haralick and CoLlAGe radiomic features were significantly associated with MRI─ CsPCa (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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