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Development and Validation of a Model Using Radiomics Features from an Apparent Diffusion Coefficient Map to Diagnose Local Tumor Recurrence in Patients Treated for Head and Neck Squamous Cell Carcinoma

Authors
 Minjae Kim  ;  Jeong Hyun Lee  ;  Leehi Joo  ;  Boryeong Jeong  ;  Seonok Kim  ;  Sungwon Ham  ;  Jihye Yun  ;  NamKug Kim  ;  Sae Rom Chung  ;  Young Jun Choi  ;  Jung Hwan Baek  ;  Ji Ye Lee  ;  Ji-Hoon Kim 
Citation
 KOREAN JOURNAL OF RADIOLOGY, Vol.23(11) : 1078-1088, 2022-11 
Journal Title
KOREAN JOURNAL OF RADIOLOGY
ISSN
 1229-6929 
Issue Date
2022-11
MeSH
Diffusion Magnetic Resonance Imaging / methods ; Head and Neck Neoplasms* / diagnostic imaging ; Head and Neck Neoplasms* / therapy ; Humans ; Magnetic Resonance Imaging / methods ; Male ; Neoplasm Recurrence, Local* / diagnostic imaging ; Retrospective Studies ; Squamous Cell Carcinoma of Head and Neck / diagnostic imaging
Keywords
Diffusion-weighted imaging ; Head and neck squamous cell carcinoma ; Magnetic resonance imaging ; Radiomics
Abstract
Objective: To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC).

Materials and methods: This retrospective study included 285 patients (mean age ± standard deviation, 62 ± 12 years; 220 male, 77.2%), including 215 for training (n = 161) and internal validation (n = 54) and 70 others for external validation, with newly developed contrast-enhancing lesions at the primary cancer site on the surveillance MRI following definitive treatment of HNSCC between January 2014 and October 2019. Of the 215 and 70 patients, 127 and 34, respectively, had local tumor recurrence. Radiomics models using radiomics scores were created separately for T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and ADC maps using non-zero coefficients from the least absolute shrinkage and selection operator in the training set. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each radiomics score and known clinical parameter (age, sex, and clinical stage) in the internal and external validation sets.

Results: Five radiomics features from T2WI, six from CE-T1WI, and nine from ADC maps were selected and used to develop the respective radiomics models. The area under ROC curve (AUROC) of ADC radiomics score was 0.76 (95% confidence interval [CI], 0.62-0.89) and 0.77 (95% CI, 0.65-0.88) in the internal and external validation sets, respectively. These were significantly higher than the AUROC values of T2WI (0.53 [95% CI, 0.40-0.67], p = 0.006), CE-T1WI (0.53 [95% CI, 0.40-0.67], p = 0.012), and clinical parameters (0.53 [95% CI, 0.39-0.67], p = 0.021) in the external validation set.

Conclusion: The radiomics model using ADC maps exhibited higher diagnostic performance than those of the radiomics models using T2WI or CE-T1WI and clinical parameters in the diagnosis of local tumor recurrence in HNSCC following definitive treatment.
Files in This Item:
T9992022807.pdf Download
DOI
10.3348/kjr.2022.0299
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Min Jae(김민재)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/193903
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