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Simple Summary: This study aims to evaluate the reliability of qualitative and semiquantitative parameters of 18F-FDG PET-CT, and eventually a correlation between them, in predicting the risk of malignancy in patients with solitary pulmonary nodule (SPN) before the diagnosis of lung cancer. Qualitative and semiquantitative parameters can be considered reliable tools in patients with SPN, since cut-offs for SUVmax, SUVmean, TLG and MTV showed good sensitivity and specificity in predicting malignancy. This study aims to evaluate the reliability of qualitative and semiquantitative parameters of 18F-FDG PET-CT, and eventually a correlation between them, in predicting the risk of malignancy in patients with solitary pulmonary nodules (SPNs) before the diagnosis of lung cancer. A total of 146 patients were retrospectively studied according to their pre-test probability of malignancy (all patients were intermediate risk), based on radiological features and risk factors, and qualitative and semiquantitative parameters, such as SUVmax, SUVmean, TLG, and MTV, which were obtained from the FDG PET-CT scan of such patients before diagnosis. It has been observed that visual analysis correlates well with the risk of malignancy in patients with SPN; indeed, only 20% of SPNs in which FDG uptake was low or absent were found to be malignant at the cytopathological examination, while 45.45% of SPNs in which FDG uptake was moderate and 90.24% in which FDG uptake was intense were found to be malignant. The same trend was observed evaluating semiquantitative parameters, since increasing values of SUVmax, SUVmean, TLG, and MTV were observed in patients whose cytopathological examination of SPN showed the presence of lung cancer. In particular, in patients whose SPN was neoplastic, we observed a median (MAD) SUVmax of 7.89 (±2.24), median (MAD) SUVmean of 3.76 (±2.59), median (MAD) TLG of 16.36 (±15.87), and a median (MAD) MTV of 3.39 (±2.86). In contrast, in patients whose SPN was non-neoplastic, the SUVmax was 2.24 (±1.73), SUVmean 1.67 (±1.15), TLG 1.63 (±2.33), and MTV 1.20 (±1.20). Optimal cut-offs were drawn for semiquantitative parameters considered predictors of malignancy. Nodule size correlated significantly with FDG uptake intensity and with SUVmax. Finally, age and nodule size proved significant predictors of malignancy. In conclusion, considering the pre-test probability of malignancy, qualitative and semiquantitative parameters can be considered reliable tools in patients with SPN, since cut-offs for SUVmax, SUVmean, TLG, and MTV showed good sensitivity and specificity in predicting malignancy. [ABSTRACT FROM AUTHOR]

Background: A primary progressive aphasia (PPA) diagnosis is generally based on clinical criteria, but often symptoms and signs may overlap in the different forms. Recent data have evidenced that brain 18fluoro-deoxy-glucose positron emission tomography (18F-FDG PET) could support the clinical diagnosis, since specific metabolic patterns are described for the different variants. Aims: We further evaluated the usefulness of 18F-FDG PET, by both visual qualitative (QL) and quantitative (QN) methods in the initial diagnosis of PPA, focusing on the classification of different variants. Moreover, we also analyzed the role of 18F-FDG PET in clarifying the association of PPA with the early phase of Alzheimer's disease (AD) or frontotemporal (FTD) dementias. Methods: We consecutively enrolled 35 patients with clinical symptoms of aphasia, suspect of or attributable to PPA. Patients were classified into two groups: 18 cases with clinical symptoms of aphasia but normal neuropsychological tests and an unclear classification of a specific PPA variant (group A) and 17 cases with clinical and neuropsychological signs attributable to PPA with an uncertain differential diagnosis between AD and FTD (group B). All patients underwent brain 18F-FDG PET/CT, and images were evaluated both by QL and QN, the latter applying an automated analysis program that produced brain regional metabolicmaps and normal age-matched control group comparative analysis (zscore). Results: 18F-FDG PET showed different patterns of bilateral cortical hypometabolism in the two groups. The combined use of QL and QN permitted to achieved a correct PPA variant diagnosis in 8 of 18 (44.4%) cases of group A and in 14 of 17 (82.3%) of group B, while only QN could support the correct classification of PPA variants in 10 of 18 (55.6%) cases of group A and in 3 of 17 (17.7%) cases of group B in whom the procedure better localized the hypometabolic areas. Conclusions: Brain 18F-FDG PET had an elevated performance in the early diagnosis of PPA variants and in the advanced PPA AD/FTD classification. QL clarified the development of AD or FTD in advanced PPA cases and supported the differential diagnosis of a PPA variant in a few early cases. QN 18F-FDG PET evaluation better contributed to the early diagnosis of an unclear metabolic pattern. To correctly identify all cases, patients with diffuse cortical hypometabolism were also included. Larger series are necessary to confirm these data. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the role of shape and texture features from 18F-FDG PET/CT to discriminate between benign and malignant solitary pulmonary nodules. To this end, we retrospectively evaluated cross-sectional data from 111 patients (64 males, 47 females, age = 67.5 ± 11.0) all with histologically confirmed benign (n=39) or malignant (n=72) solitary pulmonary nodules. Eighteen three-dimensional imaging features, including conventional, texture, and shape features from PET and CT were tested for significant differences (Wilcoxon-Mann-Withney) between the benign and malignant groups. Prediction models based on different feature sets and three classification strategies (Classification Tree, k-Nearest Neighbours, and Naïve Bayes) were also evaluated to assess the potential benefit of shape and texture features compared with conventional imaging features alone. Eight features from CT and 15 from PET were significantly different between the benign and malignant groups. Adding shape and texture features increased the performance of both the CT-based and PET-based prediction models with overall accuracy gain being 3.4-11.2 pp and 2.2-10.2 pp, respectively. In conclusion, we found that shape and texture features from 18F-FDG PET/CT can lead to a better discrimination between benign and malignant lung nodules by increasing the accuracy of the prediction models by an appreciable margin.