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3 April 2024 The pancreas is all you need: fusion models for opportunistic screening of diabetes using pancreatic CT volumes
Abhinav Suri, Pritam Mukherjee, Ronald M. Summers
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Proceedings Volume 12927, Medical Imaging 2024: Computer-Aided Diagnosis; 129271E (2024) https://doi.org/10.1117/12.3006053
Event: SPIE Medical Imaging, 2024, San Diego, California, United States
Abstract
Diabetes is a disease that affects hundreds of millions of people worldwide. While many people are diagnosed via a blood test during a routine visit, millions of people go undiagnosed due to inability to access primary care. Opportunistic screening of CT imaging offers an opportunity to predict and diagnose diabetes on imaging, opening an avenue to decrease the undiagnosed rates. Current literature in utilizing imaging for the prediction of diabetes from CT scans has shown that markers of adiposity are strong predictors of diabetes; however, we aim to determine if the pancreas alone is sufficient to diagnose diabetes. We trained a neural network to predict and diagnose diabetes from abdominal CT scans using just a segmentation of the pancreas. We found that we were able to match the performance of state of the art algorithms using less information and we could predict diabetes status in patient populations without comorbid markers of increased fat. This study opens the opportunity for further analysis of deep learning derived imaging biomarkers in the assessment of diabetes status and disease course.
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Abhinav Suri, Pritam Mukherjee, and Ronald M. Summers "The pancreas is all you need: fusion models for opportunistic screening of diabetes using pancreatic CT volumes", Proc. SPIE 12927, Medical Imaging 2024: Computer-Aided Diagnosis, 129271E (3 April 2024); https://doi.org/10.1117/12.3006053
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KEYWORDS
Pancreas
Computed tomography
Education and training
Image segmentation
Neurological disorders
Convolutional neural networks
Diagnostics
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