Cluster analysis of autoencoder-extracted FDG PET/CT features identifies multiple myeloma patients with poor prognosis

• Published in: Scientific reports Vol. 13; no. 1; pp. 7881 - 12
• Main Authors: Lee, Hyunjong, Hyun, Seung Hyup, Cho, Young Seok, Moon, Seung Hwan, Choi, Joon Young, Kim, Kihyun, Lee, Kyung-Han
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15.05.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 692/4028; 692/4028/67/1990; 692/4028/67/2321; Algorithms; Artificial Intelligence; Cluster Analysis; Computed tomography; Fluorodeoxyglucose F18; Humanities and Social Sciences; Humans; Medical prognosis; multidisciplinary; Multiple myeloma; Multiple Myeloma - diagnostic imaging; Multiple Myeloma - metabolism; Positron emission tomography; Positron Emission Tomography Computed Tomography - methods; Prognosis; Radiopharmaceuticals; Regression analysis; Retrospective Studies; Science; Science (multidisciplinary); Survival; Tomography; Tumor Burden

F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) is a robust imaging modality used for staging multiple myeloma (MM) and assessing treatment responses. Herein, we extracted features from the FDG PET/CT images of MM patients using an artificial intelligence autoen...