Literature DB >> 33370365

Incorporating radiomic feature of pretreatment 18F-FDG PET improves survival stratification in patients with EGFR-mutated lung adenocarcinoma.

Yu-Hung Chen1,2, Tso-Fu Wang2,3, Sung-Chao Chu2,3, Chih-Bin Lin4, Ling-Yi Wang5, Kun-Han Lue6, Shu-Hsin Liu1,6, Sheng-Chieh Chan1,2.   

Abstract

BACKGROUND: To investigate the survival prognostic value of the radiomic features of 18F-FDG PET in patients who had EGFR (epidermal growth factor receptor) mutated lung adenocarcinoma and received targeted TKI (tyrosine kinase inhibitor) treatment.
METHODS: Fifty-one patients with stage III-IV lung adenocarcinoma and actionable EGFR mutation who received first-line TKI were retrospectively analyzed. All patients underwent pretreatment 18F-FDG PET/CT, and we calculated the PET-derived radiomic features. Cox proportional hazard model was used to examine the association between the radiomic features and the survival outcomes, including progression-free survival (PFS) and overall survival (OS). A score model was established according to the independent prognostic predictors and we compared this model to the TNM staging system using Harrell's concordance index (c-index).
RESULTS: Forty-eight patients (94.1%) experienced disease progression and 41 patients (80.4%) died. Primary tumor SUV entropy > 5.36, and presence of pleural effusion were independently associated with worse OS (both p < 0.001) and PFS (p = 0.001, and 0.003, respectively). We used these two survival predictors to devise a scoring system (score 0-2). Patients with a score of 1 or 2 had a worse survival than those with a score of 0 (HR for OS: 3.6, p = 0.006 for score 1, and HR: 21.8, p < 0.001 for score 2; HR for PFS: 2.2, p = 0.027 for score 1 and HR: 8.8, p < 0.001 for score 2). Our scoring system surpassed the TNM staging system (c-index = 0.691 versus 0.574, p = 0.013 for OS, and c-index = 0.649 versus 0.517, p = 0.004 for PFS).
CONCLUSIONS: In this preliminary study, combining PET radiomics with clinical risk factors may improve survival stratification in stage III-IV lung adenocarcinoma with actionable EFGR mutation. Our proposed scoring system may assist with optimization of individualized treatment strategies in these patients.

Entities:  

Year:  2020        PMID: 33370365     DOI: 10.1371/journal.pone.0244502

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  6 in total

1.  Tumor glycolytic heterogeneity improves detection of regional nodal metastasis in patients with lung adenocarcinoma.

Authors:  Kun-Han Lue; Sung-Chao Chu; Ling-Yi Wang; Yen-Chang Chen; Ming-Hsun Li; Bee-Song Chang; Sheng-Chieh Chan; Yu-Hung Chen; Chih-Bin Lin; Shu-Hsin Liu
Journal:  Ann Nucl Med       Date:  2021-11-24       Impact factor: 2.668

Review 2.  Radiomics in Oncological PET Imaging: A Systematic Review-Part 1, Supradiaphragmatic Cancers.

Authors:  David Morland; Elizabeth Katherine Anna Triumbari; Luca Boldrini; Roberto Gatta; Daniele Pizzuto; Salvatore Annunziata
Journal:  Diagnostics (Basel)       Date:  2022-05-27

3.  Current progress and quality of radiomic studies for predicting EGFR mutation in patients with non-small cell lung cancer using PET/CT images: a systematic review.

Authors:  Meilinuer Abdurixiti; Mayila Nijiati; Rongfang Shen; Qiu Ya; Naibijiang Abuduxiku; Mayidili Nijiati
Journal:  Br J Radiol       Date:  2021-05-12       Impact factor: 3.629

4.  Different Prognostic Values of Dual-Time-Point FDG PET/CT Imaging Features According to Treatment Modality in Patients with Non-Small Cell Lung Cancer.

Authors:  Su Jin Jang; Jeong Won Lee; Ji-Hyun Lee; In Young Jo; Sang Mi Lee
Journal:  Tomography       Date:  2022-04-08

5.  Systemic Inflammation Index and Tumor Glycolytic Heterogeneity Help Risk Stratify Patients with Advanced Epidermal Growth Factor Receptor-Mutated Lung Adenocarcinoma Treated with Tyrosine Kinase Inhibitor Therapy.

Authors:  Kun-Han Lue; Chun-Hou Huang; Tsung-Cheng Hsieh; Shu-Hsin Liu; Yi-Feng Wu; Yu-Hung Chen
Journal:  Cancers (Basel)       Date:  2022-01-08       Impact factor: 6.639

6.  The Role of Histogram-Based Textural Analysis of 18F-FDG PET/CT in Evaluating Tumor Heterogeneity and Predicting the Prognosis of Invasive Lung Adenocarcinoma.

Authors:  Hasan Önner; Nazım Coşkun; Mustafa Erol; Meryem İlkay Eren Karanis
Journal:  Mol Imaging Radionucl Ther       Date:  2022-02-02
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.