Literature DB >> 28410141

FDG PET/CT as theranostic imaging in diagnosis of non-small cell lung cancer.

Margarita Kirienko1, Francesca Gallivanone2, Martina Sollini3, Giulia Veronesi4, Emanuele Voulaz4, Lidjia Antunovic5, Lorenzo Leonardi5, Giorgio Testanera5, Isabella Castiglioni2, Arturo Chiti6.   

Abstract

Objective of this work was to evaluate the role of 18F-fluorodeoxyglucose (FDG) positron-emission tomography features as theranostic imaging biomarkers in non-small cell lung cancer. In a retrospective protocol, 31 stage I-III NSCLC patients were enrolled. Patients underwent FDG PET/CT for staging purposes before surgery and were followed for two years after surgery. PET images were quantitatively analyzed. For the primary lesion, metabolic tumour volume, maximum standardized uptake value (SUV), SUV corrected for partial volume effect, total lesion glycolysis, 14 histogram and four shape-and-size features were extracted as PET imaging features. PET features were correlated with histology and 2-year disease-free survival (DFS). Significant correlations were found between grading, T parameter, N status, pathological stage and different FDG PET features. Histogram-based features "energy" and "kurtosis" resulted to be predictive for DFS. The cut-off value identified for "kurtosis" was able to separate the adenocarcinoma patients with different outcomes. FDG PET features are able to characterize lung cancer lesions, suggesting the possibility of reliable "imaging biopsy", and have a predictive role in adenocarcinoma patients undergoing surgery.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28410141     DOI: 10.2741/4567

Source DB:  PubMed          Journal:  Front Biosci (Landmark Ed)        ISSN: 2768-6698


  4 in total

1.  Ability of FDG PET and CT radiomics features to differentiate between primary and metastatic lung lesions.

Authors:  Margarita Kirienko; Luca Cozzi; Alexia Rossi; Emanuele Voulaz; Lidija Antunovic; Antonella Fogliata; Arturo Chiti; Martina Sollini
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-04-06       Impact factor: 9.236

2.  Integrative nomogram of CT imaging, clinical, and hematological features for survival prediction of patients with locally advanced non-small cell lung cancer.

Authors:  Linlin Wang; Taotao Dong; Bowen Xin; Chongrui Xu; Meiying Guo; Huaqi Zhang; Dagan Feng; Xiuying Wang; Jinming Yu
Journal:  Eur Radiol       Date:  2019-01-14       Impact factor: 5.315

3.  Value of 18F-FDG PET/CT-Based Radiomics Nomogram to Predict Survival Outcomes and Guide Personalized Targeted Therapy in Lung Adenocarcinoma With EGFR Mutations.

Authors:  Bin Yang; Hengshan Ji; Jing Zhong; Lu Ma; Jian Zhong; Hao Dong; Changsheng Zhou; Shaofeng Duan; Chaohui Zhu; Jiahe Tian; Longjiang Zhang; Feng Wang; Hong Zhu; Guangming Lu
Journal:  Front Oncol       Date:  2020-11-11       Impact factor: 6.244

4.  AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients.

Authors:  Pablo Borrelli; John Ly; Reza Kaboteh; Johannes Ulén; Olof Enqvist; Elin Trägårdh; Lars Edenbrandt
Journal:  EJNMMI Phys       Date:  2021-03-25
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.