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PURPOSE This study aimed to evaluate the diagnostic value of a support vector machine (SVM) model built with texture features based on standard 2-[F]fluoro-2-deoxy-D-glucose (F-FDG) PET in patients with solitary pulmonary nodules (SPNs) at a volume larger than 5 mL. PATIENTS AND METHODS The PET results of 82 patients diagnosed with SPNs between 2014 and 2018 were retrospectively analysed. The volumes of interest (VOIs) of the SPNs were automatically segmented using threshold techniques from the standard PET imaging. Then, a large number of texture features were extracted from the VOIs using texture-analysis software. Next, an optimized SVM machine-learning model that was trained on standard PET images using texture features was employed to identify the optimal discrimination between malignant and benign nodules. Diagnostic models based on the maximum standardized uptake value (SUVmax) and the metabolic tumour volume (MTV) were compared with the SVM model with regard to the SPN diagnostic power. RESULTS Compared with the SUVmax and MTV models, the texture-based SVM model provided an improvement of approximately 20% in diagnostic accuracy, positive predictive value, negative predictive value and the area under the operating characteristic curve. The receiver operating characteristic curve of the SVM model showed a significant improvement compared with the MTV model (P = 0.0345

Objective To compare the predictive value of European Organization for Research and Treatment of Cancer (EORTC) criteria and PET Response Criteria in Solid Tumors (PERCIST), for the pathological response and prognosis of patients with breast cancer receiving neoadjuvant chemotherapy (NAC). Methods Consecutive PET/computed tomography scans in 128 operable female patients at baseline and after two courses of NAC were performed. Patients were categorized by complete metabolic response (CMR) and non-CMR groups using 2 PET criteria. CMR and non-CMR were used to predict pathological complete response (pCR) by diagnostic test evaluation, and to predict progression-free survival (PFS) using Kaplan-Meier plots and Cox proportional hazards regression. Results Ninety-two patients were finally analyzed. The sensitivity, specificity, and accuracy for pCR prediction were 69.7, 76.3, and 73.9% with EORTC criteria, and 69.7, 77.9, and 75.0% with PERCIST, respectively. Peak standardized uptake value normalized to lean body mass (SULpeak), maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were pCR response with accuracy of 70.7, 60.0, 75.0, and 71.4%, respectively. CMR by the EORTC (P = 0.021) and PERCIST (P = 0.007) was significantly related to a longer PFS. The univariate and multivariate analysis suggested that CMR by PERCIST was an independent predictor of recurrence (P = 0.008). Conclusion EORTC criteria and PERCIST had early predictive value to long-term outcome, but moderate value for pCR. Furthermore, PERCIST might show more potential than the EORTC criteria and conventional PET-based parameters to predict prognosis in breast cancer patients following two cycles of neoadjuvant chemotherapy.Video abstract: see http://links.lww.com/NMC/A162.

BACKGROUND Microvascular invasion (MVI) is very important in the evaluation of hepatocellular carcinoma (HCC), but diagnosis is determined by postoperative pathology; thus, preoperative noninvasive methods will play an active role. The purpose of the study was to assess the performance of metabolic parameters of preoperative 18F-fluorodeoxyglucose PET/computerized tomography (18F-FDG PET/CT) in the prediction of MVI and postoperative recurrence in primary hepatocellular carcinoma. METHODS We retrospectively collected 72 patients with HCC who have performed 18F-FDG PET/CT scan before partial hepatectomy between 2016 and 2019. We used both normal liver tissue and inferior vena cava as the reference background and combined with clinicopathological features, 18F-FDG PET/CT metabolic and volumetric indices to predict MVI and postoperative recurrence of primary HCC before surgery. RESULTS Twenty-one of the 72 patients recurred, in recurrent cases showed higher maximum standard uptake value (SUVmax), TNR (ratio of tumor SUVmax to mean SUV [SUVmean] of the background tissue), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) than nonrecurrence cases (P < 0.001). All 18F-FDG PET metabolic and volumetric indices for predicting postoperative HCC recurrence were significant on receiver-operating-characteristic (ROC) curve analyses (P < 0.05). TNRIVC, TNRNL, MTVIVC, MTVNL TLGIVC and TLGNL were significant factors for predicting MVI in HCC (P < 0.05). On multivariate analyses, MVI, SUVmax, TNRIVC, TNRNL, MTVIVC, MTVNL, TLGIVC and TLGNL (P < 0.05) are independent risk factors for predicting postoperative HCC recurrence. TNRIVC is the most relevant PET/CT parameter for predicting MVI in HCC, and MTVIVC is the most valuable for predicting postoperative HCC recurrence. Moreover, the PET/CT parameters are more accurate for prognosis with inferior vena cava as a reference background than with normal liver tissue. CONCLUSION 18F-FDG PET/CT metabolic and volumetric indices are effective predictors, and could noninvasively provide more comprehensive predictive information on MVI and postoperative recurrence of primary HCC before surgery.

OBJECTIVE To investigate the eradicate effect of Helicobacter pylori in differentiated thyroid cancer patients who underwent I therapy. MATERIALS AND METHODS A total of 130 patients with differentiated thyroid cancer underwent I treatment. None of the patients had a history of stomach-related diseases. The C-urea breath test (UBT) was carried out for H. pylori examination before I treatment. The cut-off value for C-UBT was 4%. For H. pylori test-positive patients, a second C-UBT was performed 4-6 weeks after I treatment. T-tests were used to compare the difference before and 4-6 weeks after I treatment. RESULTS A total of 42 of 130 (32.31%) patients were H. pylori positive. The average value of H. pylori was 28.36% before I, whereas the value was 18.18% after I therapy. A significant decrease in C-UBT was found after I treatment compared with before therapy (P

The role of fluorine-18 fluorodeoxyglucose PET (F-FDG PET) in prognostic evaluation of pre-stem cell transplantation (SCT) and post-SCT is still uncertain. A systematic review and meta-analysis were carried out to detect the prognostic power of F-FDG PET. 'PubMed', EMBASE, and Springer were searched for relevant articles. Subgroup analysis was carried out to evaluate the F-FDG PET in predicting the prognosis between Hodgkin lymphoma (HL) and non-Hodgkin lymphoma. Finally, 17 studies that included 1192 patients were eligible, 16 studies for progression-free survival (PFS) and 12 studies for overall survival (OS). For the pre-SCT PET or PET/computed tomography scan, the combined hazard ratios (HRs) of PET for PFS and OS were 2.32 and 2.64, respectively. Subgroup analysis showed that the HRs of PFS for HL and non-Hodgkin lymphoma were 3.28 and 2.00, respectively. For the post-SCT PET scan, the combined HR for PFS was 4.61. The sensitivity analysis showed that exlcusion of any single study had no significant effect on HR. We found that F-FDG PET was especially effective in predicting pre-STC and post-STC prognosis. The patients with a negative PET scan had a better prognosis compared with those with a positive scan in PFS and OS. In the subgroup analysis, F-FDG PET had a higher value in predicting prognosis before SCT for HL patients.

The ability to identify potential responders to neoadjuvant treatment may improve patient selection or surgery and may help in the development of response criteria suitable for routine monitoring of response. The aim of this study was to evaluate the value of PET in predicting the pathological tumour response of non-small-cell lung cancer (NSCLC) to neoadjuvant therapy using a meta-analysis.All available published studies investigating the value of PET in predicting the pathological response of NSCLC to neoadjuvant therapy were collected. Pooled sensitivity and specificity data were obtained using statistical software. Subgroup analysis was performed to explore the sources of heterogeneity.A total of 13 studies comprising 414 patients with NSCLC were included in the meta-analysis. Pooled sensitivity, specificity, positive predictive value and negative predictive value for PET-predicted response was 83% [95% confidence interval (CI); 76-89%], 84% (95% CI; 79-88%), 74% (95% CI; 67-81%) and 91% (95% CI; 87-94%), respectively. Significant heterogeneity (P0.05) was observed. On the basis of our subgroup analyses, methodological quality could be responsible for this heterogeneity in our metaregression. The predictive value of PET in NSCLC patients with pathological response (considered the gold standard) was significantly higher than that of computed tomography (P0.05).PET scanning has an important role in predicting nonresponders to neoadjuvant therapy in cases of NSCLC, and the predictive value of PET for evaluating pathologically documented responses is superior to that of computed tomography. However, additional evaluations using prospective clinical trials will be required to assess the clinical benefit of this strategy.