(18)F-FDG-PET/CT in the assessment of pulmonary solitary nodules: comparison of different analysis methods and risk variables in the prediction of malignancy.

OBJECTIVE: To compare the diagnostic performance of different metabolical, morphological and clinical criteria for correct presurgical classification of the solitary pulmonary nodule (SPN). METHODS: Fifty-five patients, with SPN were retrospectively analyzed. All patients underwent preoperative (18)F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT). Maximum diameter in CT, maximum standard uptake value (SUVmax), histopathologic result, age, smoking history and gender were obtained. Different criteria were established to classify a SPN as malignant: (I) visually detectable metabolism, (II) SUVmax >2.5 regardless of SPN diameter, (III) SUVmax threshold depending of SPN diameter, and (IV) ratio SUVmax/diameter greater than 1. For each criterion, statistical diagnostic parameters were obtained. Receiver operating characteristic (ROC) analysis was performed to select the best diagnostic SUVmax and SUVmax/diameter cutoff. Additionally, a predictive model of malignancy of the SPN was derived by multivariate logistic regression. RESULTS: Fifteen SPN (27.3%) were benign and 40 (72.7%) malignant. The mean values ± standard deviation (SD) of SPN diameter and SUVmax were 1.93±0.57 cm and 3.93±2.67 respectively. Sensitivity (Se) and specificity (Sp) of the different diagnostic criteria were (I): 97.5% and 13.1%; (II) 67.5% and 53.3%; (III) 70% and 53.3%; and (IV) 85% and 33.3%, respectively. The SUVmax cut-off value with the best diagnostic performance was 1.95 (Se: 80%; Sp: 53.3%). The predictive model had a Se of 87.5% and Sp of 46.7%. The SUVmax was independent variables to predict malignancy. CONCLUSIONS: The assessment by semiquantitative methods did not improve the Se of visual analysis. The limited Sp was independent on the method used. However, the predictive model combining SUVmax and age was the best diagnostic approach.

Heterogeneity in [18F]fluorodeoxyglucose positron emission tomography/computed tomography of non-small cell lung carcinoma and its relationship to metabolic parameters and pathologic staging.

To investigate the relationships between tumor heterogeneity, assessed by texture analysis of [18F]fluorodeoxyglucose-positron emission tomography (FDG-PET) images, metabolic parameters, and pathologic staging in patients with non-small cell lung carcinoma (NSCLC). A retrospective analysis of 38 patients with histologically confirmed NSCLC who underwent staging FDG-PET/computed tomography was performed. Tumor images were segmented using a standardized uptake value (SUV) cutoff of 2.5. Five textural features, related to the heterogeneity of gray-level distribution, were computed (energy, entropy, contrast, homogeneity, and correlation). Additionally, metabolic parameters such as SUVmax, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), as well as pathologic staging, histologic subtype, and tumor diameter, were obtained. Finally, a correlation analysis was carried out. Of 38 tumors, 63.2% were epidermoid and 36.8% were adenocarcinomas. The mean ± standard deviation values of MTV and TLG were 30.47 ± 25.17 mL and 197.81 ± 251.11 g, respectively. There was a positive relationship of all metabolic parameters (SUVmax, SUVmean, MTV, and TLG) with entropy, correlation, and homogeneity and a negative relationship with energy and contrast. The T component of the pathologic TNM staging (pT) was similarly correlated with these textural parameters. Textural features associated with tumor heterogeneity were shown to be related to global metabolic parameters and pathologic staging.

Glycolytic activity with 18F-FDG PET/CT predicts final neoadjuvant chemotherapy response in breast cancer.

The purpose of the present study is to explore the relation between glycolytic metabolism assessed by (18)F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) and final neoadjuvant chemotherapy (NC) response in locally advanced breast tumors. Of women with breast cancer, 126 were prospectively evaluated. All patients underwent (18)F-FDG PET/CT previous to NC. Standard uptake value (SUV) max was calculated in the primary tumor. After NC, residual primary tumor specimen was histopathologically classified according to Miller and Payne tumor regression grades (TRG), from G1 to G5 and in response groups as good responders (G4 or G5), partial responders (G2 or G3), and non-responders (G1). Furthermore, residual lesions were classified following a binary assessment as responders (G4 or G5) and non-responders (the rest of cases). The relationship between SUV max with TRG and response groups was evaluated. Of tumors, 127 were assessed (a patient had bilateral breast lesions). TRG were as follows: G1 (27), G2 (27), G3 (32), G4 (11), and G5 (30). Forty-one were classified as good responders, 59 as partial responders, and 27 as non-responders. For the binary assessment, 41 lesions were classified as responders and 86 as non-responders. We found statistical differences (p=0.02) between the mean SUV max and TRG with greater SUV values for G5 compared to the other TRG. Good responders showed greater mean SUV max ± SD compared to partial responders and non-responders (10.51 ± 6.64 for good responders, 6.94 ± 5.81 for partial responders, and 5.23 ± 2.76 for non-responders; p=0.001). Baseline tumor metabolism assessing by FDG PET/CT was associated with the final histopathologic status after neoadjuvant chemotherapy, with greater SUV max values for good responders compared to the less responder cancers.

Heterogeneity in [¹8F]fluorodeoxyglucose positron emission tomography/computed tomography of non-small cell lung carcinoma and its relationship to metabolic parameters and pathologic staging.

To investigate the relationships between tumor heterogeneity, assessed by texture analysis of [18F]fluorodeoxyglucose-positron emission tomography (FDG-PET) images, metabolic parameters, and pathologic staging in patients with non-small cell lung carcinoma (NSCLC). A retrospective analysis of 38 patients with histologically confirmed NSCLC who underwent staging FDG-PET/computed tomography was performed. Tumor images were segmented using a standardized uptake value (SUV) cutoff of 2.5. Five textural features, related to the heterogeneity of gray-level distribution, were computed (energy, entropy, contrast, homogeneity, and correlation). Additionally, metabolic parameters such as SUVmax, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), as well as pathologic staging, histologic subtype, and tumor diameter, were obtained. Finally, a correlation analysis was carried out. Of 38 tumors, 63.2% were epidermoid and 36.8% were adenocarcinomas. The mean ± standard deviation values of MTV and TLG were 30.47 ± 25.17 mL and 197.81 ± 251.11 g, respectively. There was a positive relationship of all metabolic parameters (SUVmax, SUVmean, MTV, and TLG) with entropy, correlation, and homogeneity and a negative relationship with energy and contrast. The T component of the pathologic TNM staging (pT) was similarly correlated with these textural parameters. Textural features associated with tumor heterogeneity were shown to be related to global metabolic parameters and pathologic staging.