The Prognostic Value of 18^{18}F-FDG PET Imaging at Staging in Patients with Malignant Pleural Mesothelioma: A Literature Review

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 $^{18}$F-Fluoro-deoxy-glucose ($^{18}$F-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

Application of Artificial Neural Network to Preoperative 18F-FDG PET/CT for Predicting Pathological Nodal Involvement in Non-small-cell Lung Cancer Patients

Purpose: To evaluate the performance of artificial neural networks (aNN) applied to preoperative 18F-FDG PET/CT for predicting nodal involvement in non-small-cell lung cancer (NSCLC) patients. Methods: We retrospectively analyzed data from 540 clinically resectable NSCLC patients (333 M; 67.4 \ub1 9 years) undergone preoperative 18F-FDG PET/CT and pulmonary resection with hilo-mediastinal lymphadenectomy. A 3-layers NN model was applied (dataset randomly splitted into 2/3 training and 1/3 testing). Using histopathological reference standard, NN performance for nodal involvement (N0/N+ patient) was calculated by ROC analysis in terms of: area under the curve (AUC), accuracy (ACC), sensitivity (SE), specificity (SP), positive and negative predictive values (PPV, NPV). Diagnostic performance of PET visual analysis (N+ patient: at least one node with uptake mediastinal blood-pool) and of logistic regression (LR) was evaluated. Results: Histology proved 108/540 (20%) nodal-metastatic patients. Among all collected data, relevant features selected as input parameters were: patients\u2019 age, tumor parameters (size, PET visual and semiquantitative features, histotype, grading), PET visual nodal result (patient-based, as N0/N+ and N0/N1/N2). Training and testing NN performance (AUC = 0.849, 0.769): ACC = 80 and 77%; SE = 72 and 58%; SP = 81 and 81%; PPV = 50 and 44%; NPV = 92 and 89%, respectively. Visual PET performance: ACC = 82%, SE = 32%, SP = 94%; PPV = 57%, NPV = 85%. Training and testing LR performance (AUC = 0.795, 0.763): ACC = 75 and 77%; SE = 68 and 55%; SP = 77 and 82%; PPV = 43 and 43%; NPV = 90 and 88%, respectively..Conclusions: aNN application to preoperative 18F-FDG PET/CT provides overall good performance for predicting nodal involvement in NSCLC patients candidate to surgery, especially for ruling out nodal metastases, being NPV the best diagnostic result; a high NPV was also reached by PET qualitative assessment. Moreover, in such population with low a priori nodal involvement probability, aNN better identify the relatively few and unexpected nodal-metastatic patients than PET analysis, so supporting the additional aNN use in case of PET-negative images

Cavernous Hemangioma: A Potential Pitfall at Delayed 18F-FDG PET/CT Scan

: We report the case of a 72-year-old woman who underwent neoadjuvant chemotherapy, right quadrantectomy (invasive ductal carcinoma, G3, pT2pN1pMx), and adjuvant radiotherapy. Two years later, a follow-up CT revealed a hepatic nodule of approximately 1 cm suspected for metastasis. 18F-FDG PET/CT was performed for restaging. Standard total-body 18F-FDG PET/CT acquisition showed no abnormal 18F-FDG uptake in the hepatic nodule. A delayed 18F-FDG PET/CT acquisition of upper abdomen was performed at 180 minutes postradiopharmaceutical injection and showed increased 18F-FDG uptake in the hepatic nodule. After nodule resection, the histological examination proved a cavernous hemangioma

A bio-imaging signature as a predictor of clinical outcomes in locally advanced pancreatic cancer

Purpose: To evaluate the predictive value of $^{18}$F-FDG PET/CT semiquantitative parameters of the primary tumour and CA 19-9 levels assessed before treatment in patients with locally advanced pancreatic cancer (LAPC). Methods: Among one-hundred twenty patients with LAPC treated at our institution with initial chemotherapy followed by curative chemoradiotherapy (CRT) from July 2013 to January 2019, a secondary analysis with baseline $^{18}$F-FDG PET/CT was conducted in fifty-eight patients. Pre-treatment CA 19-9 level and the maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV) and total lesion glycolysis (TLG) of primary tumour were measured. The receiving operating characteristics (ROC) analysis was performed to define the cut-off point of SUVmax, MTV, TLG and CA 19-9 values to use in prediction of early progression (EP), local progression (LP) and overall survival (OS). Areas under the curve (AUCs) were assessed for all variables. Post-test probability was calculated to evaluate the advantage for parameters combination. Results: For EP, CA 19-9 level > 698 U/mL resulted the best marker to identify patient at higher risk with OR of 5.96 (95% CI, 1.66-19.47; p = 0.005) and a Positive Predictive Value (PPV) of 61%. For LP, the most significant parameter was TLG (OR 9.75, 95% CI, 1.64-57.87, p = 0.012), with PPV of 83%. For OS, the most significant parameter was MTV (OR 3.12, 95% CI, 0.9-10.83, p = 0.07) with PPV of 88%. Adding consecutively each of the other parameters, PPV to identify patients at risk resulted further increased (>90%). Conclusions: Pre-treatment CA 19-9 level, as well as MTV and TLG values of primary tumour at baseline $^{18}$F-FDG PET/CT and their combination, may represent significant predictors of EP, LP and OS in LAPC patients

Short 2-[18F]Fluoro-2-Deoxy-D-Glucose PET Dynamic Acquisition Protocol to Evaluate the Influx Rate Constant by Regional Patlak Graphical Analysis in Patients With Non-Small-Cell Lung Cancer

Purpose: To test a short 2-[18F]Fluoro-2-deoxy-D-glucose (2-[18F]FDG) PET dynamic acquisition protocol to calculate Ki 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), Ki 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 Ki,s using IDIFFitted 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 IDIFFitted 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 Ki and Ki,s. Finally, Ki,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 Ki and Ki,s were 0.0442 ± 0.0302 and 0.33 ± 0.0298, respectively (R 2 = 0.9970). The Passing-Bablok regression for comparison between Ki and Ki,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 Ki estimation. Keywords: 2-[18F]Fluoro-2-deoxy-D-glucose; PET dynamic acquisition; Patlak graphical analysis; influx rate constant; non-small-cell lung cancer

The kinetics of 18F-FDG in lung cancer: compartmental models and voxel analysis

Abstract Background The validation of the most appropriate compartmental model that describes the kinetics of a specific tracer within a specific tissue is mandatory before estimating quantitative parameters, since the behaviour of a tracer can be different among organs and diseases, as well as between primary tumours and metastases. The aims of our study were to assess which compartmental model better describes the kinetics of 18F-Fluorodeoxygluxose(18F-FDG) in primary lung cancers and in metastatic lymph nodes; to evaluate whether quantitative parameters, estimated using different innovative technologies, are different between lung cancers and lymph nodes; and to evaluate the intra-tumour inhomogeneity. Results Twenty-one patients (7 females; 71 ± 9.4 years) with histologically proved lung cancer, prospectively evaluated, underwent 18F-FDG PET-CT for staging. Spectral analysis iterative filter (SAIF) method was used to design the most appropriate compartmental model. Among the compartmental models arranged using the number of compartments suggested by SAIF results, the best one was selected according to Akaike information criterion (AIC). Quantitative analysis was performed at the voxel level. K 1, V b and K i were estimated with three advanced methods: SAIF approach, Patlak analysis and the selected compartmental model. Pearson’s correlation and non-parametric tests were used for statistics. SAIF showed three possible irreversible compartmental models: Tr-1R, Tr-2R and Tr-3R. According to well-known 18F-FDG physiology, the structure of the compartmental models was supposed to be catenary. AIC indicated the Sokoloff’s compartmental model (3K) as the best one. Excellent correlation was found between K i estimated by Patlak and by SAIF (R 2 = 0.97, R 2 = 0.94, at the global and the voxel level respectively), and between K i estimated by 3K and by SAIF (R 2 = 0.98, R 2 = 0.95, at the global and the voxel level respectively). Using the 3K model, the lymph nodes showed higher mean and standard deviation of V b than lung cancers (p < 0.0014, p < 0.0001 respectively) and higher standard deviation of K 1 (p < 0.005). Conclusions One-tissue reversible plus one-tissue irreversible compartmental model better describes the kinetics of 18F-FDG in lung cancers, metastatic lymph nodes and normal lung tissues. Quantitative parameters, estimated at the voxel level applying different advanced approaches, show the inhomogeneity of neoplastic tissues. Differences in metabolic activity and in vascularization, highlighted among all cancers and within each individual cancer, confirm the wide variability in lung cancers and metastatic lymph nodes. These findings support the need of a personalization of therapeutic approaches

Teaching cases in Nuclear Medicine: Non-oncological Applications.

Learning Objectives \u2022 Understand how radionuclide imaging is employed in the clinical routine as an important aid for better functional characterization of a variety of non-oncological diseases. \u2022 Understand the added value of radionuclide imaging for the diagnosis and functional characterization of a variety of non-oncological conditions upon which to base choice of optimal treatment for each condition. \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with diseases of the brain including dementias and movement disorders. \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with diseases of the cardiovascular system includ ing coronary artery disease, infective endocarditis, large-vessel vasculitis, and cardiac amyloidosis. \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with non-oncological diseases of the musculoskeletal system including metabolic diseases and infection/inflammation. \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with parathyroid adenoma(s). \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with various conditions of the nephro-urinary tract. \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with various functional conditions leading to altered transit through the gastrointestinal tract. \u2022 Provide practical examples derived from the clinical routine illustrating how radionuclide imaging contributes to the diagnosis and choice of optimal treatment in patients with secondary peripheral lymphedema

The predictive value of 18F-FDG PET-CT for assessing the clinical outcomes in locally advanced NSCLC patients after a new induction treatment: low-dose fractionated radiotherapy with concurrent chemotherapy.

BACKGROUND: 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. METHODS: Forty-four consecutive patients (35males, mean age: 66\u2009\ub1\u20097.8 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. RESULTS: 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\u2009=\u20090.004, p\u2009=\u20090.0002, respectively) decreased after IC-LDRT with a further reduction after CCRT (p\u2009=\u20090.0006, p\u2009=\u20090.02, 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\u2009 64\u20090.01). Early metabolic response was predictive factor for loco-regional, distant and global PFS (p\u2009=\u20090.02, p\u2009=\u20090.01, p\u2009=\u20090.005, respectively); surgery for loco-regional and global PFS (p\u2009=\u20090.03, p\u2009=\u20090.009, respectively). CONCLUSIONS: 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

Dynamic 11C-Methionine PET-CT: Prognostic Factors for Disease Progression and Survival in Patients with Suspected Glioma Recurrence

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 (SUVmaxTTP) 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 &lt; 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 &lt; 0.001); T/B was associated with OS (p = 0.031). Regarding kinetic analyses, recurrence (27/46) and deceased (14/46) patients had higher SUVmaxTTP (p = 0.02, p = 0.01, respectively). SUVmaxTTP was the only dynamic parameter associated with PFS (p = 0.02) and OS (p = 0.006). At univariate analysis, SUVmax, SUVmean, T/B and SUVmaxTTP were predictive for PFS (all p &lt; 0.05); SUVmaxTTP was predictive for OS (p = 0.02). At multivariate analysis, SUVmaxTTP remained significant for PFS (p = 0.03). Conclusion: Semiquantitative parameters and SUVmaxTTP 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

Is 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography useful to discriminate metachronous lung cancer from metastasis in patients with oncological history?

BACKGROUND: Solitary pulmonary nodules detected during follow-up in patients with previous cancer history have a high probability of malignancy being either a metachronous lung cancer or a metastasis. This distinction represents a crucial issue in the perspective of "personalized medicine", implying different treatments and prognosis. Aim - to evaluate the role of 18F-Fluorodeoxyglucose (18F-FDG) Positron Emission Tomography/Computed Tomography (PET/CT) in distinguishing whether solitary pulmonary nodules are metachronous cancers or metastases and the relationship between the nodule's characteristics and their nature. METHODS: From a single-institution database, we retrospectively selected all patients with a previous cancer history who performed 18F-FDG PET/CT to evaluate pulmonary nodules detected during follow-up, ranging from 5mm to 40mm, and histologically diagnosed as malignant. RESULTS: Between September 2009 and August 2017, 127 patients (80 males; mean age=70.2\ub18.5years) with 127 malignant nodules were included: 103/127 (81%) metachronous cancers, 24/127 (19%) metastases. In both groups, PET/CT provided good and equivalent detection rate of malignancy (81% vs 83%). No differences between metachronous cancers and metastases were found in: patient's age (70.3\ub18.1years vs 69.5\ub19.7years), gender (males=63.1% vs 62.5%), interval between previous cancer diagnosis and nodules' detection (median time=4years vs 4.5years), location (right-lung=55% vs 54%; upper-lobes=64% vs 67%; central-site=31% vs 25%), size (median size=17mm vs 19.5mm), 18F-FDG standardized uptake value (median SUVmax=5.2 vs 5.9). CONCLUSIONS: In oncological patients, despite its high detection rate, 18F-FDG PET/CT, as well as any other clinico-anatomical features, cannot distinguish whether a malignant solitary pulmonary nodule is a metachronous lung cancer or a metastasis, supporting the need of histological differential diagnosis