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http://dx.doi.org/10.1148/ryct.2020200411 | DOI Listing |
Insights Imaging
January 2025
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Objectives: The aim of this study was to determine the status of tertiary lymphoid structures (TLSs) using radiomic features in patients with invasive pulmonary adenocarcinoma (IA).
Methods: In this retrospective study, patients with IA from November 2015 to March 2024 were recruited from two independent centers (center 1, training and internal test data set; center 2, external test data set). TLS was divided into two groups according to hematoxylin-eosin staining.
Background: Radiomics provides quantitative features of pulmonary nodules (PNs) which could aid lung cancer diagnosis, but medical image acquisition variability is an obstacle to clinical application. Acquisition effects may differ between radiomic features from benign vs. malignant PNs.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Background: Preoperative assessment of lymph node status is critical in managing lung cancer, as it directly impacts the surgical approach and treatment planning. However, in clinical stage I lung adenocarcinoma (LUAD), determining lymph node metastasis (LNM) is often challenging due to the limited sensitivity of conventional imaging modalities, such as computed tomography (CT) and positron emission tomography/CT (PET/CT). This study aimed to establish an effective radiomics prediction model using multicenter data for early assessment of LNM risk in patients with clinical stage I LUAD.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Department of Radiology, Second Affiliated Hospital of Naval Medical University, Shanghai, China.
Background: Spread through air spaces (STAS) in lung adenocarcinoma (LUAD) is a distinct pattern of intrapulmonary metastasis where tumor cells disseminate within the pulmonary parenchyma beyond the primary tumor margins. This phenomenon was officially included in the World Health Organization (WHO)'s classification of lung tumors in 2015. STAS is characterized by the spread of tumor cells in three forms: single cells, micropapillary clusters, and solid nests.
View Article and Find Full Text PDFPhys Med Biol
January 2025
Radiological Sciences, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, California, 90095, UNITED STATES.
Objective: The study aims to systematically characterize the effect of CT parameter variations on images and lung radiomic and deep features, and to evaluate the ability of different image harmonization methods to mitigate the observed variations.
Approach: A retrospective in-house sinogram dataset of 100 low-dose chest CT scans was reconstructed by varying radiation dose (100%, 25%, 10%) and reconstruction kernels (smooth, medium, sharp). A set of image processing, convolutional neural network (CNNs), and generative adversarial network-based (GANs) methods were trained to harmonize all image conditions to a reference condition (100% dose, medium kernel).
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