ArticleFrontiers in oncology2021
MRI Radiomics in Prostate Cancer: A Reliability Study.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- [18F]F-DCFPyL PET/MRI radiomics for intraprostatic prostate cancer detection and metastases prediction using whole-gland segmentation.The British journal of radiology · 2025Trial
- Ultra-High-Frequency Ultrasound of Oral Cavity Lesions: A Retrospective Pictorial Study with Histopathologic and Clinical Correlation.Diagnostics (Basel, Switzerland) · 2026Article
- The Stalk Sign in Bladder Cancer: CEUS Versus MRI.Diagnostics (Basel, Switzerland) · 2026Article
- B-Mode Ultrasound Radiomics for Differentiating Benign and Malignant Small Hyperechoic Renal Masses: An Exploratory Single-Center Experience.Journal of imaging · 2026Article
- Article
- Habitat analysis based on magnetic resonance imaging for the prediction of prostate cancer: a dual-center study.Quantitative imaging in medicine and surgery · 2025Article
- Radiological Assessment After Pancreaticoduodenectomy for a Precision Approach to Managing Complications: A Narrative Review.Journal of personalized medicine · 2025Review
- Robustness of magnetic resonance imaging and positron emission tomography radiomic features in prostate cancer: Impact on recurrence prediction after radiation therapy.Physics and imaging in radiation oncology · 2024Article
- A comparative study of spinal cord compression management in metastatic prostate cancer: Teaching versus non-teaching hospitals in the United States.Cancer medicine · 2024Article
- Robustness of Radiomics in Pre-Surgical Computer Tomography of Non-Small-Cell Lung Cancer.Journal of personalized medicine · 2022Article
- Evaluation of the Efficiency of MRI-Based Radiomics Classifiers in the Diagnosis of Prostate Lesions.Frontiers in oncology · 2022Article
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13 authors.
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Abstract
backgroundRadiomics can provide quantitative features from medical imaging that can be correlated to clinical endpoints. The challenges relevant to robustness of radiomics features have been analyzed by many researchers, as it seems to be influenced by acquisition and reconstruction protocols, as well as by the segmentation of the region of interest (ROI). Prostate cancer (PCa) represents a difficult playground for this technique, due to discrepancies in the identification of the cancer lesion and the heterogeneity of the acquisition protocols. The aim of this study was to investigate the reliability of radiomics in PCa magnetic resonance imaging (MRI).
methodsA homogeneous cohort of patients with a PSA rise that underwent multiparametric MRI imaging of the prostate before biopsy was tested in this study. All the patients were acquired with the same MRI scanner, with a standardized protocol. The identification and the contouring of the region of interest (ROI) of an MRI suspicious cancer lesion were done by two radiologists with great experience in prostate cancer (>10 years). After the segmentation, the texture features were extracted with LIFEx. Texture features were then tested with intraclass coefficient correlation (ICC) analysis to analyze the reliability of the segmentation.
resultsForty-four consecutive patients were included in the present analysis. In 26 patients (59.1%), the prostate biopsy confirmed the presence of prostate cancer, which was scored as Gleason 6 in 6 patients (13.6%), Gleason 3 + 4 in 8 patients (18.2%), and Gleason 4 + 3 in 12 patients (27.3%). The reliability analysis conversely showed poor reliability in the majority of the MRI acquisition (61% in T2, 89% in DWI50, 44% in DWI400, and 83% in DWI1,500), with ADC acquisition only showing better reliability (poor reliability in only 33% of the texture features).
conclusionsThe low ratio of reliability in a monoinstitutional homogeneous cohort represents a significant alarm bell for the application of MRI radiomics in the field of prostate cancer. More work is needed in a clinical setting to further study the potential of MRI radiomics in prostate cancer.
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