Abstract
PurposeTo propose and evaluate habitat imaging-based 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) radiomics for preoperatively discriminating non-small cell lung cancer (NSCLC) and benign inflammatory diseases (BIDs).MethodsThree hundred seventeen 18F-FDG PET/CT scans were acquired from patients who underwent aspiration biopsy or surgical resection. All volumes of interest (VOIs) were semiautomatically segmented. Each VOI was separated into variant subregions, namely, habitat imaging, based on our adapted clustering-based habitat generation method. Radiomics features were extracted from these subregions. Three feature selection methods and six classifiers were applied to construct the habitat imaging-based radiomics models for fivefold cross-validation. The radiomics models whose features extracted by conventional habitat-based methods and nonhabitat method were also constructed. For comparison, the performances were evaluated in the validation set in terms of the area under the receiver operating characteristic curve (AUC). Pairwise t-test was applied to test the significant improvement between the adapted habitat-based method and the conventional methods.ResultsA total of 1,858 radiomics features were extracted. After feature selection, habitat imaging-based 18F-FDG PET/CT radiomics models were constructed. The AUC of the adapted clustering-based habitat radiomics was 0.7270 ± 0.0147, which showed significantly improved discrimination performance compared to the conventional methods (p <.001). Furthermore, the combination of features extracted by our adaptive habitat imaging-based method and non-habitat method showed the best performance than the other combinations.ConclusionHabitat imaging-based 18F-FDG PET/CT radiomics shows potential as a biomarker for discriminating NSCLC and BIDs, which indicates that the microenvironmental variations in NSCLC and BID can be captured by PET/CT.
Highlights
Lung cancer is one of the most fatal and widespread diseases, with a poor 5-year survival rate [1]
The vertical and horizontal axes represent the occurrence of a specific habitat and the proportion of the habitat size and the whole tumor size, respectively
The size proportion represents the ratio of the size of habitat to the size of whole volume of interest (VOI)
Summary
Lung cancer is one of the most fatal and widespread diseases, with a poor 5-year survival rate [1]. Non-small cell lung cancer (NSCLC) accounts for 80–85% of lung cancers [2]. The histopathological subtypes of NSCLC include large cell carcinoma, adenocarcinoma (ADC), squamous cell carcinoma (SCC), and adenosquamous carcinoma (ASC). Among these subtypes, ASC is a relatively rare NSCLC histopathological subtype whose malignancy contains components of ADC and SCC. The treatment of early-stage NSCLC is normally surgical resection. Since aspiration biopsy cannot provide 100% sensitivity, several studies have reported that the resection of benign tissue is prevalent because of the aggressive diagnosis and treatment of NSCLC [3,4,5]. Aspiration biopsy causes a certain of trauma to patient
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