ArticleFrontiers in oncology2022
Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Magnetic Resonance Imaging-Based Artificial Intelligence in Predicting Prostate Cancer Biochemical Recurrence: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Radiomics as a tool for predicting biochemical recurrence after total prostatectomy: a systematic review and meta-analysis.International urology and nephrology · 2026Pooled it
- CardioMorph Atlas: a statistical approach to evaluate association between pulmonary tuberculosis and cardiac morphology from chest X-rays.EBioMedicine · 2026Article
- Artificial Intelligence in Prostate MRI: Addressing Current Limitations Through Emerging Technologies.Journal of magnetic resonance imaging : JMRI · 2026Review
- A novel structural modeling magnitude and orientation radiomic descriptor for evaluating response to neoadjuvant therapy in rectal cancers via MRI.NPJ precision oncology · 2025Article
- Development of a deep learning system for predicting biochemical recurrence in prostate cancer.BMC cancer · 2025Article
- Predicting Biochemical Recurrence of Prostate Cancer Post-Prostatectomy Using Artificial Intelligence: A Systematic Review.Cancers · 2024Review
- Integrating Whole-Slide Imaging and MRI Data for Outcome Prediction after Prostatectomy in Localized Prostate Cancer.Radiology. Imaging cancer · 2024Article
- Article
- Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer.Frontiers in oncology · 2024Article
- Multi-Institutional Development and Validation of a Radiomic Model to Predict Prostate Cancer Recurrence Following Radical Prostatectomy.Journal of clinical medicine · 2023Article
- "Shortcuts" Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation.Journal of the American College of Radiology : JACR · 2023Review
- Article
- The Use of MRI-Derived Radiomic Models in Prostate Cancer Risk Stratification: A Critical Review of Contemporary Literature.Diagnostics (Basel, Switzerland) · 2023Review
- Delta radiomic patterns on serial bi-parametric MRI are associated with pathologic upgrading in prostate cancer patients on active surveillance: preliminary findings.Frontiers in oncology · 2023Article
- Ten quick tips for computational analysis of medical images.PLoS computational biology · 2023Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To derive and evaluate the association of prostate shape distension descriptors from T2-weighted MRI (T2WI) with prostate cancer (PCa) biochemical recurrence (BCR) post-radical prostatectomy (RP) independently and in conjunction with texture radiomics of PCa. Methods: This retrospective study comprised 133 PCa patients from two institutions who underwent 3T-MRI prior to RP and were followed up with PSA measurements for ≥3 years. A 3D shape atlas-based approach was adopted to derive prostate shape distension descriptors from T2WI, and these descriptors were used to train a random forest classifier ( Results: Conclusions: Radiomic shape descriptors quantifying prostate surface distension complement texture radiomics of prostate cancer on MRI and result in an improved association with biochemical recurrence post-radical prostatectomy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.