On the Development of a Robust Deep Learning Synthetic CT Generation Method for MR-Guided Adaptive Radiation Therapy of Abdominal Tumors

Abstract

After downloading free apps to confirm capabilities, 33 apps were eligible for the study. Of the 33 included apps, 21 (63.60%) were general symptom trackers, and 12 (36.40%) were oncology specific. None of the oncology-specific symptom tracking apps were specific for radiation oncology, but 6 (50%) of the oncology-specific apps allowed for the addition of custom symptoms. Of the 12 oncologyspecific apps, 7 (58.3%) allowed for patient journaling, 3 (25%) could sync data from wearable devices, and 2 (16.7%) allowed for bi-directional communication between the patient and medical team. Of the 2 apps that included bi-directional communication, 1 (50%) app provided a chat function, and 1 (50%) app provided a video function. Comparisons of the prevalence of important functionalities between general symptom and oncology symptom trackers is shown in Table 1. Conclusion:We present a comprehensive characterization of oncologyspecific apps currently available. Apps focused on oncology are limited and largely unexplored. Future app development to optimize PRO collection, mobile sensor data assessment, and integration with telehealth encounters in needed. Such data can increase symptom recognition, provide timely feedback and improve quality of data collection for oncologists.