Prognostic value of interim CT-based peritumoral and intratumoral radiomics in laryngeal and hypopharyngeal cancer patients undergoing definitive radiotherapy

Lin, Chia-Hsin; Yan, Jiun-Lin; Yap, Wing-Keen; Kang, Chung-Jan; Chang, Yun-Chen; Tsai, Tsung-You; Chang, Kai-Ping; Liao, Chun-Ta; Hsu, Cheng-Lung; Chou, Wen-Chi; Wang, Hung-Ming; Huang, Pei-Wei; Fan, Kang-Hsing; Huang, Bing-Shen; Tung-Chieh Chang, Joseph; Tu, Shu-Ju; Lin, Chien-Yu

doi:10.1016/j.radonc.2023.109938

Cited by 5 publications

(2 citation statements)

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“…Each patient's radiomics score (Rad-score) was a linear combination of the radiomic features and associated weights. 20,21…”

Section: Radiomic Features Extraction/selection and Radscore Construc...mentioning

confidence: 99%

The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy

Guo,

Liu,

Geng

et al. 2024

Thoracic Cancer

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BackgroundThe spleen plays an important role in systemic antitumor immune response, but whether spleen imaging features have predictive effect for prognosis and immune status was unknown. The aim of this study was to investigate computed tomography (CT)‐based spleen radiomics to predict the prognosis of patients with esophageal squamous cell carcinoma (ESCC) underwent definitive radiotherapy (dRT) and to try to find its association with systemic immunity.MethodsThis retrospective study included 201 ESCC patients who received dRT. Patients were randomly divided into training (n = 142) and validation (n = 59) groups. The pre‐ and delta‐radiomic features were extracted from enhanced CT images. LASSO‐Cox regression was used to select the radiomics signatures most associated with progression‐free survival (PFS) and overall survival (OS). Independent prognostic factors were identified by univariate and multivariate Cox analyses. The ROC curve and C‐index were used to evaluate the predictive performance. Finally, the correlation between spleen radiomics and immune‐related hematological parameters was analyzed by spearman correlation analysis.ResultsIndependent prognostic factors involved TNM stage, treatment regimen, tumor location, pre‐ or delta‐Rad‐score. The AUC of the delta‐radiomics combined model was better than other models in the training and validation groups in predicting PFS (0.829 and 0.875, respectively) and OS (0.857 and 0.835, respectively). Furthermore, some spleen delta‐radiomic features are significantly correlated with delta‐ALC (absolute lymphocyte count) and delta‐NLR (neutrophil‐to‐lymphocyte ratio).ConclusionsSpleen radiomics is expected to be a useful noninvasive tool for predicting the prognosis and evaluating systemic immune status for ESCC patients underwent dRT.

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“…Each patient's radiomics score (Rad-score) was a linear combination of the radiomic features and associated weights. 20,21…”

Section: Radiomic Features Extraction/selection and Radscore Construc...mentioning

confidence: 99%

The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy

Guo,

Liu,

Geng

et al. 2024

Thoracic Cancer

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“…Over the past few years, we have observed an increasing trend of publications on radiomic approaches in oncology [11], especially for predicting diagnosis [12][13][14] and treatment response [15][16][17][18][19], as well as tumor molecular profiles [20,21]. In particular, in patients with HNSCC, different radiomic features extracted from computed tomography (CT) imaging, which is routinely performed in this setting, were significantly associated with clinical (local control, tumor failure, lymph node metastasis, extranodal extension, overall survival, human papillomavirus (HPV) status) and histological (differentiation grade, perineural and lymphovascular invasion) parameters as well as molecular features, especially some specific somatic mutations, in patients with head and neck cancer [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

A Radiomics Approach to Identify Immunologically Active Tumor in Patients with Head and Neck Squamous Cell Carcinomas

Nguyen,

Bertolus,

Giraud

et al. 2023

Cancers

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Background: We recently developed a gene-expression-based HOT score to identify the hot/cold phenotype of head and neck squamous cell carcinomas (HNSCCs), which is associated with the response to immunotherapy. Our goal was to determine whether radiomic profiling from computed tomography (CT) scans can distinguish hot and cold HNSCC. Method: We included 113 patients from The Cancer Genome Atlas (TCGA) and 20 patients from the Groupe Hospitalier Pitié-Salpêtrière (GHPS) with HNSCC, all with available pre-treatment CT scans. The hot/cold phenotype was computed for all patients using the HOT score. The IBEX software (version 4.11.9, accessed on 30 march 2020) was used to extract radiomic features from the delineated tumor region in both datasets, and the intraclass correlation coefficient (ICC) was computed to select robust features. Machine learning classifier models were trained and tested in the TCGA dataset and validated using the area under the receiver operator characteristic curve (AUC) in the GHPS cohort. Results: A total of 144 radiomic features with an ICC >0.9 was selected. An XGBoost model including these selected features showed the best performance prediction of the hot/cold phenotype with AUC = 0.86 in the GHPS validation dataset. Conclusions and Relevance: We identified a relevant radiomic model to capture the overall hot/cold phenotype of HNSCC. This non-invasive approach could help with the identification of patients with HNSCC who may benefit from immunotherapy.

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Computer Vision—Radiomics & Pathognomics

Bourdillon

2024

Otolaryngologic Clinics of North America

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Prognostic value of interim CT-based peritumoral and intratumoral radiomics in laryngeal and hypopharyngeal cancer patients undergoing definitive radiotherapy

Cited by 5 publications

References 53 publications

The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy

The role of spleen radiomics model for predicting prognosis in esophageal squamous cell carcinoma patients receiving definitive radiotherapy

A Radiomics Approach to Identify Immunologically Active Tumor in Patients with Head and Neck Squamous Cell Carcinomas

Computer Vision—Radiomics & Pathognomics

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