Malignant pleural mesothelioma (MPM) is an aggressive malignancy, frequently diagnosed at locally-advanced/metastatic stages. Due to a very poor prognosis and limited treatment options, the need to identify new prognostic markers represents a great clinical challenge. The prognostic role of metabolic information derived from Positron Emission Tomography (PET) with ¹⁸F-Fluoro-deoxy-glucose (¹⁸F-FDG) has been investigated in different MPM settings, however with no definitive consensus. In this comprehensive review, the prognostic value of FDG-PET imaging exclusively performed at staging in MPM patients was evaluated, conducting a literature search on PubMed/MEDLINE from 2010 to 2020. From the 19 selected studies, despite heterogeneity in several aspects, staging FDG-PET imaging emerges as a valuable prognostic biomarker, with higher tumor uptake predictive of worse prognosis, and with volumetric metabolic parameters like Metabolic Tumor Volume, (MTV) and Total Lesion Glycolisis (TLG) performing better than SUVmax. However, PET uptake parameters were not always confirmed as independent prognostic factors, especially in patients previously treated with pleurodesis and with a non-epithelioid histotype. Future prospective studies in larger and clinically homogeneous populations, and using more standardized methods of PET images analysis, are needed to further validate the value of staging FDG-PET in the prognostic MPM stratification, with a potential impact on better patient-tailored treatment planning, in the perspective of personalized medicine.

Patients with locally advanced non-small-cell lung cancer (LA-NSCLC) have poor prognosis despite several multimodal approaches. Recently, low-dose fractionated radiotherapy concurrent to the induction chemotherapy (IC-LDRT) has been proposed to further improve the effects of chemotherapy and prognosis. Until now, the predictive value of metabolic response after IC-LDRT has not yet been investigated. Aim: to evaluate whether the early metabolic response, assessed by 18F-fluoro-deoxyglucose positron emission-computed tomography (18F-FDG PET-CT), could predict the prognosis in LA-NSCLC patients treated with a multimodal approach, including IC-LDRT. Forty-four consecutive patients (35males, mean age: 66 ± 7.8 years) with stage IIIA/IIIB NSCLC were retrospectively evaluated. Forty-four patients underwent IC-LDRT (2 cycles of chemotherapy, 40 cGy twice daily), 26/44 neo-adjuvant chemo-radiotherapy (CCRT: 50.4Gy), and 20/44 surgery. 18F-FDG PET-CT was performed before (baseline), after IC-LDRT (early) and after CCRT (final), applying PET response criteria in solid tumours (PERCIST). Patients with complete/partial metabolic response were classified as responders; patients with stable/progressive disease as non-responders. Progression free survival (PFS) and overall survival (OS) were assessed using Kaplan-Meyer analysis; the relationship between clinical factors and survivals were assessed using uni-multivariate regression analysis. Forty-four out of 44, 42/44 and 23/42 patients underwent baseline, early and final PET-CT, respectively. SULpeak of primary tumour and lymph-node significantly (p = 0.004, p = 0.0002, respectively) decreased after IC-LDRT with a further reduction after CCRT (p = 0.0006, p = 0.02, respectively). At early PET-CT, 20/42 (47.6%) patients were classified as responders, 22/42 (52.3%) as non-responders. At final PET-CT, 19/23 patients were classified as responders (12 responders and 7 non-responders at early PET-CT), and 4/23 as non-responders (all non-responders at early PET-CT). Early responders had better PFS and OS than early non-responders (p ≤ 0.01). Early metabolic response was predictive factor for loco-regional, distant and global PFS (p = 0.02, p = 0.01, p = 0.005, respectively); surgery for loco-regional and global PFS (p = 0.03, p = 0.009, respectively). In LA-NSCLC patients, 18F-FDG metabolic response assessed after only two cycles of IC-LDRT predicts the prognosis. The early evaluation of metabolic changes could allow to personalize therapy. This multimodality approach, including both low-dose radiotherapy that increases the effects of induction chemotherapy, and surgery that removes the disease, improved clinical outcomes. Further prospective investigation of this new induction approach is warranted.

Purpose: The prognostic evaluation of glioma recurrence patients is important in the therapeutic management. We investigated the prognostic value of ¹¹C-methionine PET-CT (MET-PET) dynamic and semiquantitative parameters in patients with suspected glioma recurrence. Methods: Sixty-seven consecutive patients who underwent MET-PET for suspected glioma recurrence at MR were retrospectively included. Twenty-one patients underwent static MET-PET; 46/67 underwent dynamic MET-PET. In all patients, SUVmax, SUVmean and tumour-to-background ratio (T/B) were calculated. From dynamic acquisition, the shape and slope of time-activity curves, time-to-peak and its SUVmax (SUVmax_TTP) were extrapolated. The prognostic value of PET parameters on progression-free (PFS) and overall survival (OS) was evaluated using Kaplan–Meier survival estimates and Cox regression. Results: The overall median follow-up was 19 months from MET-PET. Recurrence patients (38/67) had higher SUVmax (p = 0.001), SUVmean (p = 0.002) and T/B (p < 0.001); deceased patients (16/67) showed higher SUVmax (p = 0.03), SUVmean (p = 0.03) and T/B (p = 0.006). All static parameters were associated with PFS (all p < 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmax_TTP (p = 0.02, p = 0.01, respectively). SUVmax_TTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmax_TTP were predictive for PFS (all p < 0.05); SUVmax_TTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmax_TTP remained significant for PFS (p = 0.03). Conclusion: Semiquantitative parameters and SUVmax_TTP were associated with clinical outcomes in patients with suspected glioma recurrence. Dynamic PET-CT acquisition, with static and kinetic parameters, can be a valuable non-invasive prognostic marker, identifying patients with worse prognosis who require personalised therapy.

Purpose: To test a short 2-[¹⁸F]Fluoro-2-deoxy-D-glucose (2-[¹⁸F]FDG) PET dynamic acquisition protocol to calculate K_i using regional Patlak graphical analysis in patients with non-small-cell lung cancer (NSCLC).Methods: 24 patients with NSCLC who underwent standard dynamic 2-[¹⁸F]FDG acquisitions (60 min) were randomly divided into two groups. In group 1 (n = 10), a population-based image-derived input function (pIDIF) was built using a monoexponential trend (10–60 min), and a leave-one-out cross-validation (LOOCV) method was performed to validate the pIDIF model. In group 2 (n = 14), K_i was obtained by standard regional Patlak plot analysis using IDIF (0–60 min) and tissue response (10–60 min) curves from the volume of interests (VOIs) placed on descending thoracic aorta and tumor tissue, respectively. Moreover, with our method, the Patlak analysis was performed to obtain K_i,s using IDIF_Fitted curve obtained from PET counts (0–10 min) followed by monoexponential coefficients of pIDIF (10–60 min) and tissue response curve obtained from PET counts at 10 min and between 40 and 60 min, simulating two short dynamic acquisitions. Both IDIF and IDIF_Fitted curves were modeled to assume the value of 2-[¹⁸F]FDG plasma activity measured in the venous blood sampling performed at 45 min in each patient. Spearman's rank correlation, coefficient of determination, and Passing–Bablok regression were used for the comparison between K_i and K_i,s. Finally, K_i,s was obtained with our method in a separate group of patients (group 3, n = 8) that perform two short dynamic acquisitions.Results: Population-based image-derived input function (10–60 min) was modeled with a monoexponential curve with the following fitted parameters obtained in group 1: a = 9.684, b = 16.410, and c = 0.068 min⁻¹. The LOOCV error was 0.4%. In patients of group 2, the mean values of K_i and K_i,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R² = 0.9970). The Passing–Bablok regression for comparison between K_i and K_i,s showed a slope of 0.992 (95% CI: 0.94–1.06) and intercept value of −0.0003 (95% CI: −0.0033–0.0011).Conclusions: Despite several practical limitations, like the need to position the patient twice and to perform two CT scans, our method contemplates two short 2-[¹⁸F]FDG dynamic acquisitions, a population-based input function model, and a late venous blood sample to obtain robust and personalized input function and tissue response curves and to provide reliable regional K_i estimation.