Background: The clinical features and traditional semantic imaging characteristics of -mutated non-small cell lung cancer (NSCLC) have been previously reported. The radiomic features of -mutated NSCLC and their role in predicting cancer stage, however, have yet to be investigated. This study's goal is to assess the differences in CT radiomic features of primary NSCLC driven by mutation and stratified by tumor-node-metastasis (TNM) staging.
Methods: Our IRB approved study included 62 patients with mutations (V600 in 27 and non-V600 in 35 patients), who underwent contrast-enhanced chest CT. Tumor stage was determined based on the 8 edition of TNM staging. Two thoracic radiologists assessed the primary tumor imaging features such, including tumor size (maximum and minimum dimensions) and density (Hounsfield units, HU). De-identified transverse CT images (DICOM) were processed with 3D slicer (Version 4.7) for manual lesion segmentation and estimation of radiomic features. Descriptive statistics, multivariate logistic regression, and receiver operating characteristics (ROC) were performed.
Results: There were significant differences in the radiomic features based on cancer stages I-IV with the most significant differences between stage IV and stage I lesions [AUC 0.94 (95% CI: 0.86-0.99), P<0.04]. There were also significant differences in radiomic features between stage IV and combined stages I-III [40/113 radiomic features; AUC 0.71 (95% CI: 0.59-0.85); P<0.04-0.0001]. None of the clinical (0/6) or imaging (0/3) features were significantly different between stage IV and combined stages I-III.
Conclusions: The radiomic features of primary tumor in driven NSCLC significantly vary with cancer stage, independent of standard imaging and clinical features.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7481629 | PMC |
http://dx.doi.org/10.21037/tlcr-20-347 | DOI Listing |
Front Oncol
January 2025
Medical Imaging Center, The First Hospital of Kunming, Kunming, China.
Objective: The invasiveness of pituitary neuroendocrine tumor is an important basis for formulating individualized treatment plans and improving the prognosis of patients. Radiomics can predict invasiveness preoperatively. To investigate the value of multiparameter magnetic resonance imaging (mpMRI) radiomics in predicting pituitary neuroendocrine tumor invasion into the cavernous sinus (CS) before surgery.
View Article and Find Full Text PDFFront Cell Dev Biol
January 2025
Department of Medical Informatics, Nantong University, Nantong, Jiangsu, China.
Introduction: Diabetic retinopathy (DR) has long been recognized as a common complication of diabetes, making accurate automated grading of its severity essential. Color fundus photographs play a crucial role in the grading of DR. With the advancement of artificial intelligence technologies, numerous researchers have conducted studies on DR grading based on deep features and radiomic features extracted from color fundus photographs.
View Article and Find Full Text PDFTzu Chi Med J
September 2024
Department of Medical Imaging and Radiological Sciences, Tzu Chi University, Hualien, Taiwan.
Currently, the second most commonly diagnosed cancer in the world is lung cancer, and 85% of cases are non-small cell lung cancer (NSCLC). With growing knowledge of oncogene drivers and cancer immunology, several novel therapeutics have emerged to improve the prognostic outcomes of NSCLC. However, treatment outcomes remain diverse, and an accurate tool to achieve precision medicine is an unmet need.
View Article and Find Full Text PDFEur J Radiol Open
June 2025
Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China.
Purpose: The aim of this study was to explore and develop a preoperative and noninvasive model for predicting spread through air spaces (STAS) status in lung adenocarcinoma (LUAD) with diameter ≤ 3 cm.
Methods: This multicenter retrospective study included 640 LUAD patients. Center I included 525 patients (368 in the training cohort and 157 in the validation cohort); center II included 115 patients (the test cohort).
BMC Cancer
January 2025
Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, Jiangsu, 210029, People's Republic of China.
Background: Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide. Various factors in the tumor environment (TME) can lead to the activation of endoplasmic reticulum stress (ERS), thereby affecting the occurrence and development of tumors. The objective of our study was to develop and validate a radiogenomic signature based on ERS to predict prognosis and systemic combination therapy response.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!