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Reliability of Quantitative 18F-FDG PET/CT Imaging Biomarkers for Classifying Early Response to Chemoradiotherapy in Patients With Locally Advanced Non-Small Cell Lung Cancer.
Horn, Kevin P; Thomas, Hannah M T; Vesselle, Hubert J; Kinahan, Paul E; Miyaoka, Robert S; Rengan, Ramesh; Zeng, Jing; Bowen, Stephen R.
Afiliación
  • Horn KP; From the Division of Nuclear Medicine, Department of Radiology.
  • Thomas HMT; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA.
  • Vesselle HJ; From the Division of Nuclear Medicine, Department of Radiology.
  • Kinahan PE; From the Division of Nuclear Medicine, Department of Radiology.
  • Miyaoka RS; From the Division of Nuclear Medicine, Department of Radiology.
  • Rengan R; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA.
  • Zeng J; Department of Radiation Oncology, University of Washington School of Medicine, Seattle, WA.
Clin Nucl Med ; 46(11): 861-871, 2021 Nov 01.
Article en En | MEDLINE | ID: mdl-34172602
PURPOSE OF THE REPORT: We evaluated the reliability of 18F-FDG PET imaging biomarkers to classify early response status across observers, scanners, and reconstruction algorithms in support of biologically adaptive radiation therapy for locally advanced non-small cell lung cancer. PATIENTS AND METHODS: Thirty-one patients with unresectable locally advanced non-small cell lung cancer were prospectively enrolled on a phase 2 trial (NCT02773238) and underwent 18F-FDG PET on GE Discovery STE (DSTE) or GE Discovery MI (DMI) PET/CT systems at baseline and during the third week external beam radiation therapy regimens. All PET scans were reconstructed using OSEM; GE-DMI scans were also reconstructed with BSREM-TOF (block sequential regularized expectation maximization reconstruction algorithm incorporating time of flight). Primary tumors were contoured by 3 observers using semiautomatic gradient-based segmentation. SUVmax, SUVmean, SUVpeak, MTV (metabolic tumor volume), and total lesion glycolysis were correlated with midtherapy multidisciplinary clinical response assessment. Dice similarity of contours and response classification areas under the curve were evaluated across observers, scanners, and reconstruction algorithms. LASSO logistic regression models were trained on DSTE PET patient data and independently tested on DMI PET patient data. RESULTS: Interobserver variability of PET contours was low for both OSEM and BSREM-TOF reconstructions; intraobserver variability between reconstructions was slightly higher. ΔSUVpeak was the most robust response predictor across observers and image reconstructions. LASSO models consistently selected ΔSUVpeak and ΔMTV as response predictors. Response classification models achieved high cross-validated performance on the DSTE cohort and more variable testing performance on the DMI cohort. CONCLUSIONS: The variability FDG PET lesion contours and imaging biomarkers was relatively low across observers, scanners, and reconstructions. Objective midtreatment PET response assessment may lead to improved precision of biologically adaptive radiation therapy.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Pulmón de Células no Pequeñas / Neoplasias Pulmonares Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Clin Nucl Med Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Pulmón de Células no Pequeñas / Neoplasias Pulmonares Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Clin Nucl Med Año: 2021 Tipo del documento: Article Pais de publicación: Estados Unidos