Soo Jin Kwon 1 , Joo Hyun O 1 , Ie Ryung Yoo 1 Show Affiliations »
Abstract
PURPOSE: The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). METHODS: Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass (SULpeak) of up-to-5 hottest target lesions was measured at each time point. The percent changes of SULpeak of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of SULpeak values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in SULpeak; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. RESULTS: A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson's r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). CONCLUSION: Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13139-021-00697-4. © Korean Society of Nuclear Medicine 2021.
PURPOSE: The optimal number of lesions to measure for response assessment from fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is not validated for lung cancer. We compared 1 lesion and up-to-5 lesion measurements for response assessment in lung cancer per PET Response Criteria in Solid Tumors (PERCIST). METHODS: Patients with lung cancer with pre- and post-treatment PET/CT images were included. The standard uptake value corrected for lean body mass (SULpeak) of up-to-5 hottest target lesions was measured at each time point. The percent changes of SULpeak of the single hottest lesion and the sum of up-to-5 hottest lesions were computed. Pearson correlation coefficient evaluated the strength of association between the percent changes of SULpeak values from the 1 lesion and up-to-5 lesion analyses. Response categories were complete metabolic response (CMR) with no perceptible lesion; partial metabolic response (PMR), stable metabolic disease (SMD), or progressive metabolic disease (PMD) using the threshold of 30% and 0.8 unit change in SULpeak; and unequivocal new lesion meant PMD. The concordance for response categorization was assessed by kappa statistics. RESULTS: A total of 40 patients (25 non-small cell lung cancer; 15 small cell lung cancer) were analyzed, all with 18F-FDG-avid lung cancer. Average of 3 target lesions were measured for up-to-5 lesion analysis. Pearson's r was 0.74 (P < 0.001) and increased to 0.96 (P < 0.001) when two outliers were excluded. Response categorization with 1 lesion and up-to-5 lesion analyses was concordant in 37 patients (92.5%, weighted kappa = 0.89). CONCLUSION: Analyzing 1 lesion and up-to-5 lesions for response assessment by PERCIST showed high concordance in patients with lung cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13139-021-00697-4. © Korean Society of Nuclear Medicine 2021.
Entities: Chemical
Keywords:
Lung cancer; PERCIST; PET/CT; Response assessment
Year: 2021
PMID： 34093892 PMCID： PMC8140042 DOI： 10.1007/s13139-021-00697-4
Source DB: PubMed Journal: Nucl Med Mol Imaging ISSN： 1869-3474