Predicting response to therapy in pancreatic ductal adenocarcinoma using convolutional neural networks Conference Paper
| Authors: | Zhou, J.; Ali, D.; Mojtahedi, R.; Barekzai, A. B.; Chakraborty, J.; Khasawneh, H.; Vilela, C.; Horvat, N.; Miranda, J.; Wei, A. C.; Simpson, A. L. |
| Title: | Predicting response to therapy in pancreatic ductal adenocarcinoma using convolutional neural networks |
| Conference Title: | Medical Imaging 2025: Computer-Aided Diagnosis |
| Abstract: | Pancreatic cancer is a uniformly deadly disease. Prediction of response to neoadjuvant therapy is critical in determining which patients should undergo invasive surgery. Non-invasive biomarkers of response would address gaps in the management of patients. This study employs pre-trained convolutional neural networks (CNNs) to predict response from baseline computed tomography (CT) scans alone, prior to neoadjuvant therapy. ResNet50, InceptionV3, VGG16, and Xception were trained on a dataset of annotated CT scans of patients with pancreatic ductal adenocarcinoma (PDAC). Our results demonstrate that the ResNet50 model achieves the highest performance among the models predicting response, with an average (average ± margin of error at 95% confidence level) accuracy of 0.679 ± 0.057, an F1-score of 0.665 ± 0.072, recall of 0.717 ± 0.081, precision of 0.698 ± 0.074, and an area under the receiver operating characteristic curve (AUC-ROC) of 0.781 ± 0.162 across 5-fold cross-validation. These findings highlight the potential for non-invasive imaging biomarkers in predicting response to neoadjuvant therapy in PDAC. © 2025 SPIE. |
| Keywords: | neoadjuvant therapy; neurosurgery; computed tomography; recist criteria; computed tomography (ct); pancreatic ductal adenocarcinoma; ductal adenocarcinomas; pancreatic cancers; transplantation (surgical); transplants; noninvasive medical procedures; pancreatic ductal adenocarcinoma (pdac); computed tomography scan; deep learning; convolutional neural network; deep learning (dl); cardiovascular surgery; medical image classification |
| Journal Title | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
| Volume: | 13407 |
| Conference Dates: | 2025 Feb 17-20 |
| Conference Location: | San Diego, CA |
| ISBN: | 1605-7422 |
| Publisher: | SPIE |
| Date Published: | 2025-01-01 |
| Start Page: | 134071C |
| Language: | English |
| DOI: | 10.1117/12.3048961 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Conference paper -- ISBN: 9781510685901 -- Source: Scopus |
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197Wei -
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