The Multimodal Hormonal Therapy Response Prediction (MHTRP) framework integrates MRI scans (T2, DWI), PSA, GS, and age to predict hormonal therapy response. It employs le...
Abstract:
Accurately predicting the impact of hormonal therapy on Prostate Cancer (PC) lesions is paramount for effective treatment planning and monitoring. This study proposes a c...Show MoreMetadata
Abstract:
Accurately predicting the impact of hormonal therapy on Prostate Cancer (PC) lesions is paramount for effective treatment planning and monitoring. This study proposes a comprehensive framework, termed Multimodal Hormonal Therapy Response Prediction (MHTRP), that integrates Magnetic Resonance Imaging (MRI) imaging markers, pathology markers (i.e., Gleason score), clinical markers (Prostate-Specific Antigen (PSA)), and demographic markers (patient age). The integration of these diverse markers leverages existing literature and clinical recommendations to construct a robust, personalized prediction system for hormonal therapy outcomes in PC. To extract imaging markers, the proposed framework employs a series of preprocessing steps, including prostate delineation, lesion segmentation, super-resolution, and other techniques, to prepare the data for analysis by our Deep Learning (DL)-based Multibranch Multimodality MRI Feature Extractor (M3FE). The M3FE comprises multiple branches, each employing a dedicated DL model to extract features from a specific modality. Subsequently, a fully connected classifier is utilized to discern crucial features from the extracted characteristics. Incorporating clinical, pathology, and demographic markers alongside extracted imaging markers, we performed ensemble fusion using a weighted sum fusion algorithm to predict the hormonal therapy effect on PC. Testing was conducted on a cohort of 39 patients stratified by PSA levels. Our system demonstrated high efficacy, achieving an impressive overall accuracy, with a sensitivity of 97.5% and a specificity of 100%. Despite the small cohort size, these results are encouraging and indicate that the combination of radiomic features with other markers significantly enhances the prediction of hormone treatment outcomes in PC, potentially paving the way for more personalized management strategies.
The Multimodal Hormonal Therapy Response Prediction (MHTRP) framework integrates MRI scans (T2, DWI), PSA, GS, and age to predict hormonal therapy response. It employs le...
Published in: IEEE Access ( Volume: 12)