Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning.

Autor: Al Hasan MM; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Electrical and Computer Engineering, University of Florida College of Medicine, Gainesville, FL, USA., Ghazimoghadam S; Augmented Intelligence and Precision Health Laboratory, Research Institute of the McGill University Health Centre, Montreal, QC, Canada., Tunlayadechanont P; Augmented Intelligence and Precision Health Laboratory, Research Institute of the McGill University Health Centre, Montreal, QC, Canada.; Department of Diagnostic and Therapeutic Radiology and Research, Faculty of Medicine Ramathibodi Hospital, Ratchathewi, Bangkok, Thailand., Mostafiz MT; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Electrical and Computer Engineering, University of Florida College of Medicine, Gainesville, FL, USA., Gupta M; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA., Roy A; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Electrical and Computer Engineering, University of Florida College of Medicine, Gainesville, FL, USA., Peters K; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Radiology, University of Florida College of Medicine, Gainesville, FL, USA., Hochhegger B; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Radiology, University of Florida College of Medicine, Gainesville, FL, USA., Mancuso A; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Radiology, University of Florida College of Medicine, Gainesville, FL, USA., Asadizanjani N; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA.; Department of Electrical and Computer Engineering, University of Florida College of Medicine, Gainesville, FL, USA., Forghani R; Radiomics and Augmented Intelligence Laboratory (RAIL), Department of Radiology and the Norman Fixel Institute for Neurological Diseases, University of Florida College of Medicine, 1600 SW Archer Road, Gainesville, FL, 32610-0374, USA. r.forghani@ufl.edu.; Department of Radiology, University of Florida College of Medicine, Gainesville, FL, USA. r.forghani@ufl.edu.; Division of Medical Physics, University of Florida College of Medicine, Gainesville, FL, USA. r.forghani@ufl.edu.; Department of Neurology, Division of Movement Disorders, University of Florida College of Medicine, Gainesville, FL, USA. r.forghani@ufl.edu.; Augmented Intelligence and Precision Health Laboratory, Research Institute of the McGill University Health Centre, Montreal, QC, Canada. r.forghani@ufl.edu.
Jazyk: angličtina
Zdroj: Journal of imaging informatics in medicine [J Imaging Inform Med] 2024 Dec; Vol. 37 (6), pp. 2955-2966. Date of Electronic Publication: 2024 Jun 27.
DOI: 10.1007/s10278-024-01114-w
Abstrakt: Early and accurate detection of cervical lymph nodes is essential for the optimal management and staging of patients with head and neck malignancies. Pilot studies have demonstrated the potential for radiomic and artificial intelligence (AI) approaches in increasing diagnostic accuracy for the detection and classification of lymph nodes, but implementation of many of these approaches in real-world clinical settings would necessitate an automated lymph node segmentation pipeline as a first step. In this study, we aim to develop a non-invasive deep learning (DL) algorithm for detecting and automatically segmenting cervical lymph nodes in 25,119 CT slices from 221 normal neck contrast-enhanced CT scans from patients without head and neck cancer. We focused on the most challenging task of segmentation of small lymph nodes, evaluated multiple architectures, and employed U-Net and our adapted spatial context network to detect and segment small lymph nodes measuring 5-10 mm. The developed algorithm achieved a Dice score of 0.8084, indicating its effectiveness in detecting and segmenting cervical lymph nodes despite their small size. A segmentation framework successful in this task could represent an essential initial block for future algorithms aiming to evaluate small objects such as lymph nodes in different body parts, including small lymph nodes looking normal to the naked human eye but harboring early nodal metastases.
Competing Interests: Declarations. Competing Interests: R.F. has had a research collaboration/grant and has acted as consultant and/or speaker for Nuance Communications/Microsoft Inc., Canon Medical Systems Inc., and GE Healthcare. R.F. is also a co-investigator on a National Institutes of Health STTR grant subaward and a co-principal investigator on a National Science Foundation grant. K.P. has a research collaboration/grant from Canon Medical Systems Inc. B.H. has had a research collaboration/grant and has acted as consultant and/or speaker for Brainomix Inc., Canon Medical Systems Inc., and Roche Inc.
(© 2024. The Author(s).)
Databáze: MEDLINE
Externí odkaz: