دورية أكاديمية
أعرض في EDS

Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer.

التفاصيل البيبلوغرافية
العنوان: Development and External Validation of a PET Radiomic Model for Prognostication of Head and Neck Cancer.
المؤلفون: Noortman WA; Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.; TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands., Aide N; Nuclear Medicine Department, Centre Hospitalier Universitaire de Caen, 14000 Caen, France., Vriens D; Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands., Arkes LS; Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.; Technical Medicine, Delft University of Technology, 2628 CD Delft, The Netherlands., Slump CH; TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands., Boellaard R; Amsterdam University Medical Center, 1081 HV Amsterdam, The Netherlands., Goeman JJ; Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, The Netherlands., Deroose CM; Nuclear Medicine and Molecular Imaging, Department of Imaging & Pathology, University Hospitals Leuven, KU Leuven, 3000 Leuven, Belgium., Machiels JP; Department of Medical Oncology, Institut Roi Albert II, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium.; Institute for Experimental and Clinical Research (IREC, pôle MIRO), Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium., Licitra LF; Department of Head and Neck Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, University of Milan, 20133 Milan, Italy., Lhommel R; Division of Nuclear Medicine, Institut de Recherche Clinique, Cliniques Universitaires Saint Luc, 1200 Brussels, Belgium., Alessi A; Department of Nuclear Medicine-PET Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy., Woff E; Nuclear Medicine Department, Institut Jules Bordet, Université Libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (H.U.B.), 1070 Bruxelles, Belgium., Goffin K; Nuclear Medicine and Molecular Imaging, Department of Imaging & Pathology, University Hospitals Leuven, KU Leuven, 3000 Leuven, Belgium., Le Tourneau C; Department of Drug Development and Innovation, Institut Curie, Paris-Saclay University, 75005 Paris, France., Gal J; Epidemiology and Biostatistics Department, Centre Antoine Lacassagne, University Côte d'Azur, 06100 Nice, France., Temam S; Department of Head and Neck Surgery Gustave Roussy, 94805 Villejuif, France., Delord JP; Department of Medical Oncology, IUCT-Oncopole, 31100 Toulouse, France., van Velden FHP; Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands., de Geus-Oei LF; Section of Nuclear Medicine, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.; TechMed Centre, University of Twente, 7522 NB Enschede, The Netherlands.; Department of Radiation Science & Technology, Delft University of Technology, 2628 CD Delft, The Netherlands.
المصدر: Cancers [Cancers (Basel)] 2023 May 09; Vol. 15 (10). Date of Electronic Publication: 2023 May 09.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101526829 Publication Model: Electronic Cited Medium: Print ISSN: 2072-6694 (Print) Linking ISSN: 20726694 NLM ISO Abbreviation: Cancers (Basel) Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI
مستخلص: Aim: To build and externally validate an [ 18 F]FDG PET radiomic model to predict overall survival in patients with head and neck squamous cell carcinoma (HNSCC).
Methods: Two multicentre datasets of patients with operable HNSCC treated with preoperative afatinib who underwent a baseline and evaluation [ 18 F]FDG PET/CT scan were included (EORTC: n = 20, Unicancer: n = 34). Tumours were delineated, and radiomic features were extracted. Each cohort served once as a training and once as an external validation set for the prediction of overall survival. Supervised feature selection was performed using variable hunting with variable importance, selecting the top two features. A Cox proportional hazards regression model using selected radiomic features and clinical characteristics was fitted on the training dataset and validated in the external validation set. Model performances are expressed by the concordance index (C-index).
Results: In both models, the radiomic model surpassed the clinical model with validation C-indices of 0.69 and 0.79 vs. 0.60 and 0.67, respectively. The model that combined the radiomic features and clinical variables performed best, with validation C-indices of 0.71 and 0.82.
Conclusion: Although assessed in two small but independent cohorts, an [ 18 F]FDG-PET radiomic signature based on the evaluation scan seems promising for the prediction of overall survival for HNSSC treated with preoperative afatinib. The robustness and clinical applicability of this radiomic signature should be assessed in a larger cohort.
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معلومات مُعتمدة: none Boerhinger Ingelheim France
فهرسة مساهمة: Keywords: [18F]FDG PET/CT; afatinib; head and neck squamous cell carcinoma; machine learning; overall survival; radiomics
تواريخ الأحداث: Date Created: 20230622 Latest Revision: 20230701
رمز التحديث: 20230701
مُعرف محوري في PubMed: PMC10216021
DOI: 10.3390/cancers15102681
PMID: 37345017
قاعدة البيانات: MEDLINE
الوصف
تدمد:2072-6694
DOI:10.3390/cancers15102681