TY - JOUR
T1 - Solitary pulmonary nodules differentiated by Dynamic F-18 FDG PET in a region with high prevalence of granulomatous disease
AU - Huang, Yu Erh
AU - Lu, Hung I.
AU - Liu, Feng Yuan
AU - Huang, Yu Jie
AU - Lin, Meng Chih
AU - Chen, Chin Feng
AU - Wang, Pei Wen
PY - 2012/3
Y1 - 2012/3
N2 - This study determined whether dynamic F-18 FDG PET imaging could differentiate benign from malignant solitary pulmonary nodules (SPNs). Histopathologically confirmed SPNs (10-35 mm), 24 malignant and 10 benign, from 34 patients were studied through both dynamic and static F-18 FDG PET imaging of all patients. Volumes of interest (VOIs) were placed over the pulmonary nodules using a 50% maximum pixel value threshold. The arterial input function was estimated from a left ventricle-defined VOL Based on Patlak analysis, we calculated the net FDG phosphorylation rate (K1) and glucose metabolic rate (MRGlu) of each nodule. The slope values of the time-activity curves (TACs) of the nodules were also determined. Based on the static PET images, maximum and mean standardized uptake values (SUVmax and SUVmean, respectively) were calculated. Benign and malignant SPNs had significantly different values for SUVmax, SUVmean, Kj, MRGlu, and TAC slope, with area under the receiver operating characteristic curves distinguishing benign from malignant nodules. McNemar's test of marginal homogeneity found all the predictors helpful to detect malignant nodules (all, p > 0.05), and combining Ki and MRGlu, which were generated by dynamic study, yielded a higher specificity of 90%, and a sensitivity of 79%. Among the 10 benign nodules, static SUV imaging correctly classified seven, while dynamic F-18 PET imaging correctly classified nine. Dynamic F-18 FDG PET imaging is valuable in differentiating benign from malignant SPNs, particularly for granulomatous disease.
AB - This study determined whether dynamic F-18 FDG PET imaging could differentiate benign from malignant solitary pulmonary nodules (SPNs). Histopathologically confirmed SPNs (10-35 mm), 24 malignant and 10 benign, from 34 patients were studied through both dynamic and static F-18 FDG PET imaging of all patients. Volumes of interest (VOIs) were placed over the pulmonary nodules using a 50% maximum pixel value threshold. The arterial input function was estimated from a left ventricle-defined VOL Based on Patlak analysis, we calculated the net FDG phosphorylation rate (K1) and glucose metabolic rate (MRGlu) of each nodule. The slope values of the time-activity curves (TACs) of the nodules were also determined. Based on the static PET images, maximum and mean standardized uptake values (SUVmax and SUVmean, respectively) were calculated. Benign and malignant SPNs had significantly different values for SUVmax, SUVmean, Kj, MRGlu, and TAC slope, with area under the receiver operating characteristic curves distinguishing benign from malignant nodules. McNemar's test of marginal homogeneity found all the predictors helpful to detect malignant nodules (all, p > 0.05), and combining Ki and MRGlu, which were generated by dynamic study, yielded a higher specificity of 90%, and a sensitivity of 79%. Among the 10 benign nodules, static SUV imaging correctly classified seven, while dynamic F-18 PET imaging correctly classified nine. Dynamic F-18 FDG PET imaging is valuable in differentiating benign from malignant SPNs, particularly for granulomatous disease.
KW - F-18 fluorodeoxyglucose
KW - Kinetic analysis
KW - Positron emission tomography
KW - Solitary pulmonary nodules
UR - https://www.scopus.com/pages/publications/84863496831
U2 - 10.1269/jrr.11089
DO - 10.1269/jrr.11089
M3 - 文章
AN - SCOPUS:84863496831
SN - 0449-3060
VL - 53
SP - 306
EP - 312
JO - Journal of Radiation Research
JF - Journal of Radiation Research
IS - 2
ER -