Improved generalizability of PET hepatic lesion detection using Deep Learning Algorithms: Feasibility of noise matching between datasets using list mode reconstructions
xinyi Yang, Michael Silosky, Jonathan Wehrend, Daniel Litwiller, Muthiah Nachiappan, Scott Metzler, Bennett Chin, Debashis Ghosh, Fuyong Xing
Journal of Nuclear Medicine Jun 2024, 65 (supplement 2) 241010;
Detectability of Hepatic Lesions in DOTATATE PET: Investigation of Contrast to Noise Ratio threshold as a metric to support lesion detection in clinical practice
Muthiah Nachiappan, Anthony Cai, Michael Silosky, Bennett Chin
Journal of Nuclear Medicine Jun 2024, 65 (supplement 2) 242071;
Yang X, Silosky M, Wehrend J, Litwiller DV, Nachiappan M, Metzler SD, Ghosh D, Xing F, Chin BB. Improving Generalizability of PET DL Algorithms: List-Mode Reconstructions Improve DOTATATE PET Hepatic Lesion Detection Performance. Bioengineering (Basel). 2024 Feb 27;11(3). PubMed PMID: 38534501
https://doi.org/10.1182/blood-2022-162758
https://doi.org/10.7860/JCDR/2018/37299.12370
PET/CT-biomarkers enable risk stratification of patients with relapsed/refractory diffuse large B-cell lymphoma enrolled in the LOTIS-2 clinical trial
Abeloff's Clinical Oncology, 7e
Exploring improved prognostication using PET/CT radiomics in relapsed/refractory, TP53-aberrant diffuse large B-cell lymphoma (DLBCL).
Real-world evidence of a monoclonal anti-amyloid therapy program in a wide catchment specialty memory clinic