Margin assessment in soft tissue sarcomas: review of the literature

A Sambri, E Caldari, M Fiore, R Zucchini, C Giannini… - Cancers, 2021 - mdpi.com
Simple Summary Many classifications to assess margins status for soft tissue sarcomas are
reported in the literature. Most of the series are heterogeneous and variable in size, making …

[HTML][HTML] Radiomics in early lung cancer diagnosis: from diagnosis to clinical decision support and education

YJ Wu, FZ Wu, SC Yang, EK Tang, CH Liang - Diagnostics, 2022 - mdpi.com
Lung cancer is the most frequent cause of cancer-related death around the world. With the
recent introduction of low-dose lung computed tomography for lung cancer screening, there …

Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans

H Cho, HY Lee, E Kim, G Lee, J Kim, J Kwon… - Communications …, 2021 - nature.com
Deep learning (DL) is a breakthrough technology for medical imaging with high sample size
requirements and interpretability issues. Using a pretrained DL model through a radiomics …

Tumor microenvironment, radiology, and artificial intelligence: should we consider tumor periphery?

A Mohammadi… - … of Ultrasound in …, 2022 - Wiley Online Library
Objectives The tumor microenvironment (TME) consists of cellular and noncellular
components which enable the tumor to interact with its surroundings and plays an important …

Deciphering the tumor microenvironment through radiomics in non-small cell lung cancer: Correlation with immune profiles

HJ Yoon, J Kang, H Park, I Sohn, SH Lee, HY Lee - PloS one, 2020 - journals.plos.org
Growing evidence suggests that the efficacy of immunotherapy in non-small cell lung
cancers (NSCLCs) is associated with the immune microenvironment within the tumor. We …

A computerized tomography-based radiomic model for assessing the invasiveness of lung adenocarcinoma manifesting as ground-glass opacity nodules

M Zhu, Z Yang, M Wang, W Zhao, Q Zhu, W Shi… - Respiratory …, 2022 - Springer
Background Clinically differentiating preinvasive lesions (atypical adenomatous
hyperplasia, AAH and adenocarcinoma in situ, AIS) from invasive lesions (minimally …

An integrated nomogram combined semantic-radiomic features to predict invasive pulmonary adenocarcinomas in subjects with persistent subsolid nodules

FZ Wu, YJ Wu, EK Tang - Quantitative Imaging in Medicine …, 2022 - pmc.ncbi.nlm.nih.gov
Background Patients with persistent pulmonary subsolid nodules have a relatively high
incidence of lung adenocarcinoma. Preoperative early diagnosis of invasive pulmonary …

Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics

HJ Yoon, H Park, HY Lee, I Sohn, J Ahn… - Thoracic …, 2020 - Wiley Online Library
Background Because shape or irregularity along the tumor perimeter can result from
interactions between the tumor and the surrounding parenchyma, there could be a …

Machine learning in lung cancer radiomics

J Li, Z Li, L Wei, X Zhang - Machine Intelligence Research, 2023 - Springer
Lung cancer is the leading cause of cancer-related deaths worldwide. Medical imaging
technologies such as computed tomography (CT) and positron emission tomography (PET) …