ArticleMedicine2017
Comparison of different automated lesion delineation methods for metabolic tumor volume of 18F-FDG PET/CT in patients with stage I lung adenocarcinoma.
Article in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 22 citations in OpenAlex.
- Integrated primary tumor and all metastatic lymph nodes radiomics from 18 F-FDG PET/CT for precise M1 subclassification in nasopharyngeal carcinoma.BMC cancer · 2026Article
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- Characteristics of whole-body dynamicQuantitative imaging in medicine and surgery · 2024Article
- The Utility ofClinical Medicine Insights. Oncology · 2024Article
- Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [Sensors (Basel, Switzerland) · 2023Article
- Volumetric parameters of the primary tumor and whole-body tumor burden derived from baselineEuropean journal of hybrid imaging · 2022Article
- Breathing-induced Errors in Quantification and Description of Dominant Intra-Prostatic Lesions (Dils) in PET Images: A Simulation Study by Means of The 4D NCAT Phantom.Journal of biomedical physics & engineering · 2022Article
- Relationship betweenKorean journal of radiology · 2022Article
- The Utility of PET/CT Metabolic Parameters Measured Based on Fixed Percentage Threshold of SUVmax and Adaptive Iterative Algorithm in the New Revised FIGO Staging System for Stage III Cervical Cancer.Frontiers in medicine · 2021Article
- Correlation analysis between metabolic tumor burden measured by positron emission tomography/computed tomography and the 2015 World Health Organization classification of lung adenocarcinoma, with a risk prediction model of tumor spread through air spaces.Translational cancer research · 2020Article
- Metabolic tumor volume predicts overall survival in patients with primary pulmonary lymphoepithelioma-like carcinoma.Oncology letters · 2019Article
- Hybrid Imaging in Head and Neck Sarcoidosis.Journal of clinical medicine · 2019Article
- Metabolic tumour volume is prognostic in patients with non-small-cell lung cancer treated with stereotactic ablative radiotherapy.Current oncology (Toronto, Ont.) · 2019Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the study was to investigate the suitable segmentation method in small, low uptake and heterogeneous nodules of stage I lung adenocarcinoma.133 stage I lung adenocarcinoma patients with F-FDG PET/CT scans were enrolled in this retrospective study. All lesions were divided into different groups according to nodule density, nodule size, and the maximum standard uptake value (SUVmax) level. Four different PET segmentation methods were performed, including percentage threshold of SUVmax (T42% and T42% × RC), gradient-based threshold (adaptive iterative algorithm, AT-AIA), and background-related threshold (adaptive thresholding at 40% SUVmax, AT40%) approaches. The MTVs were evaluated and compared with CT volume (CTV). Percentage volume error (%VE) compared to CTV was calculated and the correlations between MTVs and CTV were analyzed.AT-AIA had the highest accuracy in large, high uptake, and solid nodules (72.5%, 72.4%, and 65.6%, respectively). AT40% had the highest accuracy in small, low uptake and nonsolid nodules (56.6%, 56.1%, and 62.6%, respectively). In part-solid nodules, the accuracy of AT-AIA (60.0%) and AT40% (56.7%) were higher than that of T42% and T42% × RC. The MTV of AT-AIA was in excellent correlation with the CTV in solid nodules (R = 0.831, P < .001) and in high uptake nodules (R = 0.830, P < .001). The MTV of AT40% was in good correlation with the CTV in nonsolid nodules (R = 0.686, P = .003) and in part-solid nodules (R = 0.731, P < .001).AT40% showed best performance in small, low uptake, nonsolid and part-solid lesions. AT-AIA was suitable for large, high uptake, and solid lesions.
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