Rationale and Objectives
Histological variant (HV) of bladder urothelial carcinoma (UC) is a significant factor
for therapy management. We aim to assess the predictive performance of machine learning
(ML)-based Computed Tomography radiomics of UC for HV.
Materials and Methods
Volume of interest of 37 bladder UC tumors, of which 21 were pure and 16 were HV,
were manually segmented. The extracted first- and second-order texture features (n = 117)
using 3-D Slicer radiomics were compared to the radical cystectomy histopathological
results. ML algorithms were performed to determine the significant models using Python
2.3, Pycaret library. The sample size was increased to 74 by synthetic data generation,
and three outliers from the training set were removed (training dataset; n = 52, test
dataset; n = 19). The predictive performances of 15 ML algorithms were compared. Then,
the best two models were evaluated on the test set and ensembled by Voting Classifier.
Results
The ML algorithms demonstrated area under curve (AUC) and accuracy ranging 0.79-0.97
and 50%-90%, respectively on the train set. The best models were Gradient Boosting
Classifier (AUC: 0.95, accuracy: 90%) and CatBoost Classifier (AUC: 0.97, accuracy:
85%). On the test set; the Voting Classifier of these two models demonstrated AUC,
accuracy, recall, precision, and F1 scores as follows; 0.93, 79%, 86%, 67%, and 75%,
respectively.
Conclusion
ML-based Computed Tomography radiomics of UC can predict HV, a prognostic factor that
is indeterminable by qualitative radiological evaluation and can be missed in the
preoperative histopathological specimens.
Key Words
Abbreviations:
AUC (Area under curve), ChT (Chemotherapy), CT (Computed Tomography), catboost (CatBoost classifier), gbc (Gradient Boosting classifier), GLCM (Gray-level co-occurrence matrix), GLDM (Gray-level difference method), GLRLM (Gray-level run-length matrix), GLSZM (Gray-level size zone), HV (Histological variant), ML (Machine learning), NGTDM (Neighbouring gray tone difference matrix), ROC (Receiver operating characteristic), RT (Radiotherapy), TUR-BT (Transurethral resection of bladder tumor), UC (Urothelial carcinoma)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: March 26, 2022
Accepted:
February 6,
2022
Received in revised form:
February 2,
2022
Received:
January 3,
2022
Identification
Copyright
© 2022 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
