Literature DB >> 22404955

The value of positron emission tomography in early detection of lung cancer in high-risk population: a systematic review.

Cheng-Yu Chang1, Shu-Ju Chang, Shih-Chieh Chang, Mei-Kang Yuan.   

Abstract

BACKGROUND: Early detection trials with chest radiography and sputum cytology were ineffective in decreasing lung cancer mortality. The advent of low-dose spiral chest computed tomography (LDCT) provided clinicians with a new tool that could be with early diagnosis; however, this also raised significant concerns regarding the systematic use of LDCT with its high false-positive rate for benign nodules. At this time, there is limited information about the true role of PET (positron emission tomography) for early detection of lung cancer.
METHODS: We used systematic methods, including Preferred Reporting Items for Systematic reviews and Meta-Analyses statement, to identify relevant studies, assess study eligibility, evaluate study methodological quality, and summarize findings regarding diagnostic accuracy and outcome.
RESULTS: In total, only seven eligible studies were selected from 82 potentially relevant studies. The sensitivity of 18F-FDG-PET for the detection of T1 lung cancers ranged between 68% and 95%. The rate of detection tended to be lower for carcinoid tumors, adenocarcinoma and bronchoalveolar cell carcinomas. FDG-PET using SUV (standardized uptake value) level can predict the outcome of the screening detected lung cancer. A combination of FDG-PET and LDCT may improve screening for lung cancer in high-risk patients.
CONCLUSIONS: PET or PET/CT may be used as a useful tool for early detection of lung cancer in high-risk population based on the existing information. However, there is still limited information with regards to evidence of survival benefits from PET screening in high-risk patients.
© 2012 Blackwell Publishing Ltd.

Entities:  

Mesh:

Year:  2012        PMID: 22404955     DOI: 10.1111/j.1752-699X.2012.00290.x

Source DB:  PubMed          Journal:  Clin Respir J        ISSN: 1752-6981            Impact factor:   2.570


  3 in total

Review 1.  Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML).

Authors:  Rima Hajjo; Dima A Sabbah; Sanaa K Bardaweel; Alexander Tropsha
Journal:  Diagnostics (Basel)       Date:  2021-04-21

2.  Simplified programming and control of automated radiosynthesizers through unit operations.

Authors:  Shane B Claggett; Kevin M Quinn; Mark Lazari; Melissa D Moore; R Michael van Dam
Journal:  EJNMMI Res       Date:  2013-07-15       Impact factor: 3.138

Review 3.  [(18)F]Fluorodeoxyglucose-positron emission tomography screening for lung cancer: a systematic review and meta-analysis.

Authors:  Chun-Ru Chien; Ji-An Liang; Jin-Hua Chen; Hsiao-Nin Wang; Cheng-Chieh Lin; Chih-Yi Chen; Pin-Hui Wang; Chia-Hung Kao; Jun-Jun Yeh
Journal:  Cancer Imaging       Date:  2013-12-14       Impact factor: 3.909

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.