S116 - A Novel Approach for Assessment of Clonal Hematopoiesis of Indeterminate Potential Using Deep Neural Networks
Sangeon Ryu, Shawn Ahn, Jeacy Espinoza, Alokkumar Jha, Stephanie Halene, James s Duncan, Jennifer Kwan, Nicha C Dvornek
We propose a novel diagnostic method for clonal hematopoiesis of indeterminate potential (CHIP), a condition characterized by the presence of somatic mutations in hematopoietic stem cells without detectable hematologic malignancy, using deep-learning techniques. We developed a convolutional neural network (CNN) to predict CHIP status using 4 different views from standard delayed gadolinium-enhanced cardiac MRI. We used 5-fold cross validation on 82 patients to assess the performance of our model. Different algorithms were compared to find the optimal patient-level prediction method using the image-level CNN predictions. We found that the best model had an AUC of 0.85 and an accuracy of 82%. We conclude that a deep learning-based diagnostic approach for CHIP is promising.
Schedule: Wednesday, July 12: Posters — 10:15–12:00 & 15:00–16:00
Poster location: W12