[HTML][HTML] [18F] FDG-PET/CT radiomics and artificial intelligence in lung cancer: technical aspects and potential clinical applications

R Manafi-Farid, E Askari, I Shiri, C Pirich… - Seminars in nuclear …, 2022 - Elsevier
Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …

Clinical application of AI-based PET images in oncological patients

J Dai, H Wang, Y Xu, X Chen, R Tian - Seminars in Cancer Biology, 2023 - Elsevier
Based on the advantages of revealing the functional status and molecular expression of
tumor cells, positron emission tomography (PET) imaging has been performed in numerous …

Multiparametric MRI-based radiomics nomogram for preoperative prediction of lymphovascular invasion and clinical outcomes in patients with breast invasive ductal …

J Zhang, G Wang, J Ren, Z Yang, D Li, Y Cui… - European Radiology, 2022 - Springer
Objective To develop a multiparametric MRI-based radiomics nomogram for predicting
lymphovascular invasion (LVI) status and clinical outcomes in patients with breast invasive …

Deep learning signatures reveal multiscale intratumor heterogeneity associated with biological functions and survival in recurrent nasopharyngeal carcinoma

X Zhao, YJ Liang, X Zhang, DX Wen, W Fan… - European Journal of …, 2022 - Springer
Purpose How to discriminate different risks of recurrent nasopharyngeal carcinoma (rNPC)
patients and guide individual treatment has become of great importance. This study aimed to …

Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI

Y Han, T Wang, P Wu, H Zhang, H Chen… - Magnetic Resonance …, 2021 - Elsevier
Purpose We aimed to develop a radiomics model to predict the histopathological grading of
meningiomas by magnetic resonance imaging (MRI) before surgery. Methods We recruited …

A CT-based deep learning radiomics nomogram outperforms the existing prognostic models for outcome prediction in clear cell renal cell carcinoma: A multicenter …

P Nie, G Yang, Y Wang, Y Xu, L Yan, M Zhang… - European …, 2023 - Springer
Objectives To develop and validate a CT-based deep learning radiomics nomogram (DLRN)
for outcome prediction in clear cell renal cell carcinoma (ccRCC), and its performance was …

The radiomics-based tumor heterogeneity adds incremental value to the existing prognostic models for predicting outcome in localized clear cell renal cell carcinoma …

G Yang, P Nie, L Yan, M Zhang, Y Wang… - European journal of …, 2022 - Springer
Purpose Tumor heterogeneity, which is associated with poor outcomes, has not been
exhibited in the University of California, Los Angeles, Integrated Staging System (UISS), and …

[HTML][HTML] Development and Validation of a Radiomics Model Based on 18F-FDG PET of Primary Gastric Cancer for Predicting Peritoneal Metastasis

B Xue, J Jiang, L Chen, S Wu, X Zheng, X Zheng… - Frontiers in …, 2021 - frontiersin.org
Objectives The aim of this study was to develop a preoperative positron emission
tomography (PET)-based radiomics model for predicting peritoneal metastasis (PM) of …

The value of 18F-FDG PET/CT-based radiomics in predicting perineural invasion and outcome in non-metastatic colorectal cancer

J Ma, D Guo, W Miao, Y Wang, L Yan, F Wu… - Abdominal …, 2022 - Springer
Purpose Perineural invasion (PNI) has been recognized as an important prognosis factor in
patients with colorectal cancer (CRC). The purpose of this retrospective study was to …

[HTML][HTML] The role of 18F-FDG PET/CT in guiding precision medicine for invasive bladder carcinoma

A Girard, H Vila Reyes, H Shaish, JF Grellier… - Frontiers in …, 2020 - frontiersin.org
Bladder cancer (BC) is the 10th most common cancer worldwide. Approximately one quarter
of patients with BC have muscle-invasive disease (MIBC). Muscle-invasive disease carries a …