Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach

Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach

Background: The modern approach to treating rectal cancer, which involves total mesorectal excision directed by imaging assessments, has significantly enhanced patient outcomes. However, locally recurrent rectal cancer (LRRC) continues to be a significant clinical issue. Identifying LRRC through ima...

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Main Authors: Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Heliyon
Subjects:
Rectal cancer
Recurrence
Machine learning
Radiomics
PET
CT
Online Access:http://www.sciencedirect.com/science/article/pii/S240584402417435X
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