Your browser doesn't support javascript.
loading
Using positron emission tomography - computed tomography imaging to distinguish of metastatic disease from second primary lung tumours in patients with non-small cell lung cancer
Article | IMSEAR | ID: sea-212275
ABSTRACT

Background:

In NSCLC patients with multiple lesions, the differentiation between metastases and second primary tumours has significant therapeutic and prognostic implications. The aim of this retrospective study was to investigate the potential of 18F-FDG PET to discriminate metastatic disease from second primary lung tumours.

Methods:

Of 318 NSCLC patients between November 2015 and October 2018 at Bach Mai hospital, patients with a synchronous second primary lung cancer were selected. Patients with metastatic disease involving the lungs served as the control group. Maximum standardized uptake values (SUVs) measured with 18F-FDG PET were determined for two tumours in each patient. The SUVmax was determined and compared between the second primary group and metastatic disease group. Receiver-operating characteristic (ROC) curve analysis was performed to determine the sensitivity and specificity of the SUVmax for an optimal cut-off value.

Results:

A total of 81 NSCLC patients (44 metastatic disease, 37 second primary cancer) were included for analysis. The SUVmax was significantly higher in patients with second primary cancer than in those with metastatic disease (7.53±4.33 vs 4.35±2.58, respectively, p<0.001). The area under the ROC curve was 0.81 and the odds ratio for the optimal cut-off was 7.52.

Conclusions:

SUVmax from 18F-FDG PET images can be helpful in differentiating metastatic disease from second primary tumours in patients with synchronous pulmonary lesions. Further studies are warranted to confirm the consistency of these results.

Full text: Available Index: IMSEAR (South-East Asia) Type of study: Observational study / Prognostic study Year: 2020 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: IMSEAR (South-East Asia) Type of study: Observational study / Prognostic study Year: 2020 Type: Article