A CT-based radiomics nomogram for differentiation of renal oncocytoma and chromophobe renal cell carcinoma with a central scar-matched study
| Autor: | Xiaoli Li, Cheng Dong, Qianli Ma, Pei Nie, Ying-Mei Zheng, Wenjian Xu |
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| Rok vydání: | 2022 |
| Předmět: |
Male
2019-20 coronavirus outbreak Pathology medicine.medical_specialty Coronavirus disease 2019 (COVID-19) Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Chromophobe Renal Cell Carcinoma Diagnosis Differential Radiomics Adenoma Oxyphilic Humans Medicine Central Scar Radiology Nuclear Medicine and imaging Renal oncocytoma Carcinoma Renal Cell Aged Retrospective Studies Full Paper business.industry General Medicine Middle Aged Nomogram medicine.disease Kidney Neoplasms Nomograms Female Tomography X-Ray Computed business |
| Zdroj: | Br J Radiol |
| ISSN: | 1748-880X 0007-1285 |
| DOI: | 10.1259/bjr.20210534 |
| Popis: | Objective:Pre-operative differentiation between renal oncocytoma (RO) and chromophobe renal cell carcinoma (chRCC) is critical due to their different clinical behavior and different clinical treatment decisions. The aim of this study was to develop and validate a CT-based radiomics nomogram for the pre-operative differentiation of RO from chRCC.Methods:A total of 141 patients (84 in training data set and 57 in external validation data set) with ROs (n = 47) or chRCCs (n = 94) were included. Radiomics features were extracted from tri-phasic enhanced-CT images. A clinical model was developed based on significant patient characteristics and CT imaging features. A radiomics signature model was developed and a radiomics score (Rad-score) was calculated. A radiomics nomogram model incorporating the Rad-score and independent clinical factors was developed by multivariate logistic regression analysis. The diagnostic performance was evaluated and validated in three models using ROC curves.Results:Twelve features from CT images were selected to develop the radiomics signature. The radiomics nomogram combining a clinical factor (segmental enhancement inversion) and radiomics signature showed an AUC value of 0.988 in the validation set. Decision curve analysis revealed that the diagnostic performance of the radiomics nomogram was better than the clinical model and the radiomics signature.Conclusions:The radiomics nomogram combining clinical factors and radiomics signature performed well for distinguishing RO from chRCC.Advances in knowledge:Differential diagnosis between renal oncocytoma (RO) and chromophobe renal cell carcinoma (chRCC) is rather difficult by conventional imaging modalities when a central scar was present. A radiomics nomogram integrated with the radiomics signature, demographics, and CT findings facilitates differentiation of RO from chRCC with improved diagnostic efficacy. The CT-based radiomics nomogram might spare unnecessary surgery for RO. |
| Databáze: | OpenAIRE |
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