Predicting preoperative muscle invasion status for bladder cancer using computed tomography-based radiomics nomogram
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View abstract on PubMed
Summary
This summary is machine-generated.This study shows that a computed tomography (CT)-based radiomics nomogram accurately predicts muscle invasion in bladder cancer (BCa). The radiomics-clinical nomogram offers a valuable tool for quantitative assessment of BCa muscle invasion status.
Area Of Science
- Radiology
- Oncology
- Medical Imaging Analysis
Background
- Bladder cancer (BCa) muscle invasion is critical for treatment decisions.
- Accurate prediction of muscle invasion status is essential for effective BCa management.
Purpose Of The Study
- To evaluate the effectiveness of a computed tomography (CT)-based radiomics nomogram in predicting muscle invasion in bladder cancer (BCa).
- To assess the combined predictive power of radiomics and clinical features for BCa muscle invasion.
Main Methods
- Retrospective analysis of 196 patients with confirmed urothelial carcinoma of the bladder.
- Extraction and selection of 851 radiomics features using significance testing and LASSO.
- Development of clinical, radiomics, and radiomics-clinical nomogram models using logistic regression.
- Evaluation of models using receiver operating characteristic (ROC) curve analysis, including AUC, sensitivity, and specificity.
Main Results
- A radiomics-clinical nomogram incorporating radiomics score and histopathology grading demonstrated high predictive performance.
- The radiomics-clinical nomogram achieved an area under the curve (AUC) of 0.896 in the training cohort and 0.887 in the test cohort.
- The nomogram showed statistically significant improvement over the clinical model (p=0.015) and radiomics model (p=0.002) in the training cohort.
Conclusions
- A CT-based radiomics-clinical nomogram is a valuable tool for quantitative prediction of muscle invasion in bladder cancer.
- This approach can aid in improving the accuracy of staging and treatment planning for BCa patients.
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