ArticleLa Radiologia medica2022
Performance of CT radiomics in predicting the overall survival of patients with stage III clear cell renal carcinoma after radical nephrectomy.
Article in La Radiologia medica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 3 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- CT acquisition protocols by pathology, SIRM position paper part 2 (Abdominal and Oncologic Imaging, Urology, Paediatric).La Radiologia medica · 2026Guideline
- Clinical application of radiomics for the prediction of treatment outcome and survival in patients with renal cell carcinoma: a systematic review.World journal of urology · 2024Pooled it
- Delta radiomics: an updated systematic review.La Radiologia medica · 2024Pooled it
- Review
- Multiphase CT-Based Tumor and Peritumoral Radiomics for Characterization of Clear Cell Renal Cell Carcinoma.Journal of imaging informatics in medicine · 2026Article
- Review
- Prediction study of surrounding tissue invasion in clear cell renal cell carcinoma based on multi-phase enhanced CT radiomics.Abdominal radiology (New York) · 2025Article
- Impact of contrast enhancement phase on CT-based radiomics analysis for predicting post-surgical recurrence in renal cell carcinoma.Japanese journal of radiology · 2025Article
- All You Need to Know About TACE: A Comprehensive Review of Indications, Techniques, Efficacy, Limits, and Technical Advancement.Journal of clinical medicine · 2025Review
- Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics.Journal of clinical medicine · 2024Review
- An Informative Review of Radiomics Studies on Cancer Imaging: The Main Findings, Challenges and Limitations of the Methodologies.Current oncology (Toronto, Ont.) · 2024Review
- Machine Learning and Radiomics Analysis for Tumor Budding Prediction in Colorectal Liver Metastases Magnetic Resonance Imaging Assessment.Diagnostics (Basel, Switzerland) · 2024Article
- Ferroptosis-associated genes and compounds in renal cell carcinoma.Frontiers in immunology · 2024Review
- An overview on multimodal imaging for the diagnostic workup of pleural mesothelioma.Japanese journal of radiology · 2024Review
- Radiomics in gastrointestinal stromal tumours: an up-to-date review.Japanese journal of radiology · 2023Review
- Predictive factors of selective transarterial embolization failure in acute renal bleeding: a single-center experience.Emergency radiology · 2023Article
- Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics.Diagnostics (Basel, Switzerland) · 2023Review
- Peritoneal Carcinosis: What the Radiologist Needs to Know.Diagnostics (Basel, Switzerland) · 2023Review
- Computed Tomography Urography: State of the Art and Beyond.Tomography (Ann Arbor, Mich.) · 2023Review
- Update on the Applications of Radiomics in Diagnosis, Staging, and Recurrence of Intrahepatic Cholangiocarcinoma.Diagnostics (Basel, Switzerland) · 2023Review
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5 authors.
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Abstract
purposeTo investigate the performance of CT radiomics in predicting the overall survival (OS) of patients with stage III clear cell renal carcinoma (ccRCC) after radical nephrectomy. MATERIALS AND
methodsThe 132 patients with stage III ccRCC undergoing radical nephrectomy were collected, and the patients were divided into training set (n = 79) and validation set (n = 53). The ccRCC was segmented and 396 radiomics features were extracted. After dimensionality reduction, radiomics score (RS) was obtained. COX regression was used to construct Model 1 (clinical variables + CT findings) and Model 2 (clinical variables + CT findings + RS) in the training set to predict the OS of patients, and then, the performance of the two models in the two data sets was compared.
resultsIn the training set, Akaike information criterion, C-index, and corrected C-index were 295.51, 0.744, and 0.728 for Model 1, and 271.78, 0.805, and 0.799 for Model 2, respectively. In the validation set, the corresponding values were 185.68, 0.701, and 0.699 for Model 1, and 175.99, 0.768, and 0.768 for Model 2. The calibration curves showed that both models had good calibration degrees in the validation set. Compared with Model 1, the continuous net reclassification index and integrated discrimination improvement index of Model 2 in the two data sets were positively improved.
conclusionThe two prediction models showed high performance in the evaluation of OS of stage III ccRCC patients after radical nephrectomy, among which Model 2 based on ISUP grade and RS was more concise and efficient.
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