Quantum characterization of superconducting photon counters

We address the quantum characterization of photon counters based on transition-edge sensors (TESs) and present the first experimental tomography of the positive operator-valued measure (POVM) of a TES. We provide the reliable tomographic reconstruction of the POVM elements up to 11 detected photons and M=100 incoming photons, demonstrating that it is a linear detector.Comment: 3 figures, NJP (to appear

The prognostic value of 18f-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 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

A Bio-Imaging Signature as a Predictor of Clinical Outcomes in Locally Advanced Pancreatic Cancer

Purpose: To evaluate the predictive value of 18F-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 18F-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 18F-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 (R2 = 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

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

Purpose: To evaluate the predictive value of18F-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 baseline18F-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\u201319.47; 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\u201357.87, p = 0.012), with PPV of 83%. For OS, the most significant parameter was MTV (OR 3.12, 95% CI, 0.9\u201310.83, 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 baseline18F-FDG PET/CT and their combination, may represent significant predictors of EP, LP and OS in LAPC patients

Dynamic11 c-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 of11 C-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 < 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 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 < 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

Automated detection and classification of tumor histotypes on dynamic PET imaging data through machine-learning driven voxel classification

2-deoxy-2-fluorine-(18F)fluoro-D-glucose Positron Emission Tomography/Computed Tomography (18F-FDG-PET/CT) is widely used in oncology mainly for diagnosis and staging of various cancer types, including lung cancer, which is the most common cancer worldwide. Since histopathologic subtypes of lung cancer show different degree of 18F-FDG uptake, to date there are some diagnostic limits and uncertainties, hindering an 18F-FDG-PET-driven classification of histologic subtypes of lung cancers. On the other hand, since activated macrophages, neutrophils, fibroblasts and granulation tissues also show an increased 18F-FDG activity, infectious and/or inflammatory processes and post-surgical and post-radiation changes may cause false-positive results, especially for lymph-nodes assessment. Here we propose a model-free, machine-learning based algorithm for the automated classification of adenocarcinoma, the most common type of lung cancer, and other types of tumors. Input for the algorithm are dynamic acquisitions of PET data (dPET), providing for a spatially and temporally resolved characterization of the uptake kinetic. The algorithm consists in a trained Random Forest classifier which, relying contextually on several spatial and temporal features of 18F-FDG uptake, generates as an outcome probability maps allowing to distinguish adenocarcinoma from other lung histotype and to identify metastatic lymph-nodes, ultimately increasing the specificity of the technique. Its performance, evaluated on a dPET dataset of 19 patients affected by primary lung cancer, provides a probability 0.943 ± 0.090 for the detection of adenocarcinoma. The use of this algorithm will guarantee an automatic and more accurate localization and discrimination of tumors, also providing a powerful tool for detecting at which extent tumor has spread beyond a primary tumor into lymphatic system

ATHENA X-IFU Demonstration Model: First Joint Operation of the Main TES Array and its Cryogenic AntiCoincidence Detector (CryoAC)

The X-IFU is the cryogenic spectrometer onboard the future ATHENA X-ray observatory. It is based on a large array of TES microcalorimeters, which work in combination with a Cryogenic AntiCoincidence detector (CryoAC). This is necessary to reduce the particle background level thus enabling part of the mission science goals. Here we present the first joint test of X-IFU TES array and CryoAC Demonstration Models, performed in a FDM setup. We show that it is possible to operate properly both detectors, and we provide a preliminary demonstration of the anti-coincidence capability of the system achieved by the simultaneous detection of cosmic muons

Composite-Based Path Modeling for Conditional Quantiles Prediction. An Application to Assess Health Differences at Local Level in a Well-Being Perspective

Quantile composite-based path modeling is a recent extension to the conventional partial least squares path modeling. It estimates the effects that predictors exert on the whole conditional distributions of the outcomes involved in path models and provides a comprehensive view on the structure of the relationships among the variables. This method can also be used in a predictive way as it estimates model parameters for each quantile of interest and provides conditional quantile predictions for the manifest variables of the outcome blocks. Quantile composite-based path modeling is shown in action on real data concerning well-being indicators. Health outcomes are assessed taking into account the effects of Economic well-being and Education. In fact, to support an accurate evaluation of the regional performances, the conditions within the outcomes arise should be properly considered. Assessing health inequalities in this multidimensional perspective can highlight the unobserved heterogeneity and contribute to advances in knowledge about the dynamics producing the well-being outcomes at local level

Superconducting MgB2 nanostructures fabricated by electron beam lithography

MgB2 meander lines with width ranging from 250 to 500 nm have been fabricated by electron beam lithography (EBL)-based technique. Magnesium diboride films grown by all-in-situ method have been used. A critical current density of 8 MA cm2 was measured for meander with width down to 300 nm. For sake of comparison the measurements have been performed as well on 10 μm wide strip patterned on the same sample. The results show that the nanostructuring process doesn’t affect the superconducting properties of the structure. The flexibility of the EBL approach makes it interesting in view of fabrication of MgB2 superconducting devices, such as photon detectors