Unknown

Dataset Information

0

Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact.


ABSTRACT:

Background

Pure ground-glass nodules (pGGNs) with pleural contact (P-pGGNs) comprise not only invasive adenocarcinoma (IAC), but also minimally invasive adenocarcinoma (MIA). Radiomics recognizes complex patterns in imaging data by extracting high-throughput features of intra-tumor heterogeneity in a non-invasive manner. In this study, we sought to develop and validate a radiomics signature to identify IAC and MIA presented as P-pGGNs.

Methods

In total, 100 patients with P-pGGNs (69 training samples and 31 testing samples) were retrospectively enrolled from December 2012 to May 2018. Imaging and clinical findings were also analyzed. In total, 106 radiomics features were extracted from the 3D region of interest (ROI) using computed tomography (CT) imaging. Univariate analyses were used to identify independent risk factors for IAC. The least absolute shrinkage and selection operator (LASSO) method with 10-fold cross-validation was used to generate predictive features to build a radiomics signature. Receiver-operator characteristic (ROC) curves and calibration curves were used to evaluate the predictive accuracy of the radiomics signature. Decision curve analyses (DCA) were also conducted to evaluate whether the radiomics signature was sufficiently robust for clinical practice.

Results

Univariate analysis showed significant differences between MIA (N = 47) and IAC (N = 53) groups in terms of patient age, lobulation signs, spiculate margins, tumor size, CT values and relative CT values (all P ConclusionsOur radiomics signature exhibited good discriminative performance in differentiating IAC from MIA in P-pGGNs, and may offer a crucial reference point for follow-up and selective surgical management.

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC7788838 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

altmetric image

Publications

Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact.

Jiang Yining Y   Che Siyu S   Ma Shuangchun S   Liu Xinyan X   Guo Yan Y   Liu Ailian A   Li Guosheng G   Li Zhiyong Z  

Cancer imaging : the official publication of the International Cancer Imaging Society 20210106 1


<h4>Background</h4>Pure ground-glass nodules (pGGNs) with pleural contact (P-pGGNs) comprise not only invasive adenocarcinoma (IAC), but also minimally invasive adenocarcinoma (MIA). Radiomics recognizes complex patterns in imaging data by extracting high-throughput features of intra-tumor heterogeneity in a non-invasive manner. In this study, we sought to develop and validate a radiomics signature to identify IAC and MIA presented as P-pGGNs.<h4>Methods</h4>In total, 100 patients with P-pGGNs (  ...[more]

Similar Datasets

| S-EPMC7305264 | biostudies-literature
| S-EPMC7393870 | biostudies-literature
| S-EPMC8482342 | biostudies-literature
| S-EPMC7432133 | biostudies-literature
| S-EPMC4125172 | biostudies-literature
| S-EPMC9447332 | biostudies-literature
| S-EPMC10996418 | biostudies-literature
| S-EPMC10993960 | biostudies-literature
| S-EPMC7267037 | biostudies-literature
| S-EPMC10868041 | biostudies-literature