Evaluation of a synthetic single-crystal diamond detector for relative dosimetry on the Leksell Gamma Knife Perfexion radiosurgery system

Purpose: To evaluate the new commercial PTW-60019 synthetic single-crystal microDiamond detector (PTW, Freiburg, Germany) for relative dosimetry measurements on a clinical Leksell Gamma Knife Perfexion radiosurgery system. Methods: Detector output ratios (DORs) for 4 and 8 mm beams were measured using a micro- Diamond (PTW-60019), a stereotactic unshielded diode [IBA stereotactic field detector (SFD)], a shielded diode (IBA photon field detector), and GafChromic EBT3 films. Both parallel and transversal acquisition directions were considered for PTW-60019 measurements. Measured DORs were compared to the new output factor reference values for Gamma Knife Perfexion (0.814 and 0.900 for 4 and 8 mm, respectively). Profiles in the three directions were also measured for the 4 mm beam to evaluate full width at half maximum (FWHM) and penumbra and to compare them with the corresponding Leksell GammaPlan profiles. Results: FWHM and penumbra for PTW-60019 differed from the calculated values by less than 0.2 and 0.3 mm, for the parallel and transversal acquisitions, respectively. GafChromic films showed FWHM and penumbra within 0.1 mm. The output ratio obtained with the PTW-60019 for the 4 mm field was 1.6% greater in transverse direction compared to the nominal value. Comparable differences up to 0.8% and 1.0% for, respectively, GafChromic films and SFD were found. Conclusions: The microDiamond PTW-60019 is a suitable detector for commissioning and routine use of Gamma Knife with good agreement of both DORs and profiles in the three directions

Central Precocious Puberty in Italian Boys: Data From a Large Nationwide Cohort

Context: There are only a few nationwide studies on boys with central precocious puberty (CPP) and the last Italian study is a case series of 45 boys that dates back to 2000. Objective: We aimed to evaluate the causes of CPP in boys diagnosed during the last 2 decades in Italy and the relative frequency of forms with associated central nervous system (CNS) abnormalities on magnetic resonance imaging (MRI) compared to idiopathic ones. Methods: We performed a national multicenter retrospective study collecting data from 193 otherwise normal healthy boys with a diagnosis of CPP. Based on MRI findings, the patients were divided into: Group 1, no CNS abnormalities; Group 2, mild abnormalities (incidental findings) unrelated to CPP; and Group 3, causal pathological CNS abnormalities. Results: The MRI findings show normal findings in 86%, mild abnormalities (incidental findings) in 8.3%, and causal pathological CNS abnormalities in 5.7% of the cases. In Group 3, we found a higher proportion of patients with chronological age at diagnosis < 7 years (P = .00001) and body mass index greater than +2 SDS (P < .01). Gonadotropin-releasing hormone analogue therapy was started in 183/193 subjects. The final height appeared in the range of the target height in all groups and in 9 patients in whom the therapy was not started. Conclusion: In our study on a large nationwide cohort of boys referred for precocious puberty signs, the percentage of forms associated with CNS abnormalities was one of the lowest reported in the literature

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

The unveiling of a dynamic duo: hydrodynamic cavitation and cold plasma for the degradation of furosemide in wastewater

Abstract The degradation in water of furosemide (FUR), a widely used diuretic drug, was herein reported. The method entails an integrated approach based on the hybridisation of hydrodynamic cavitation (HC) with electrical discharge (ED) plasma technology. This dynamic duo could increase the production of oxidising compounds in water, in particular hydroxyl radicals (OH radicals), by triggering the rapid homolytic decomposition of water molecules and avoiding the addition of external oxidants. This study clearly emphasises the effectiveness of an integrated approach to improve the degradation of pollutants in wastewater originating from active pharmaceutical ingredients (APIs). The results of HC/ED-assisted FUR degradation in the presence of radical scavengers highlight the predominant role of the radical oxidation mechanism at the gas–liquid interface of the cavitation bubble during HC/ED treatment. A comparative analysis of the three technologies—HC alone, HC/ED and UV alone—emphasised the promising potential of hybrid HC/ED as a scalable industrial technology. This is demonstrated by the higher degradation rates (100%, 10 min) when treating large volumes (5L) of wastewater contaminated with FUR (50 mg/L), even in the presence of other APIs

Telemedicine in the COVID-19 era: Taking care of children with obesity and diabetes mellitus

Severe acute respiratory syndrome coronavirus 2 infection was declared a pandemic in January 2020. Since then, several measures to limit virus transmission have been imposed; among them, home confinement has been the most severe, with drastic changes in the daily routines of the general population. The "stay at home" rule has impaired healthcare service access, and patients with chronic conditions were the most exposed to the negative effects of this limitation. There is strong evidence of the worsening of obesity and diabetes mellitus in children during this period. To overcome these issues, healthcare providers have changed their clinical practice to ensure follow-up visits and medical consultation though the use of telemedicine. Telemedicine, including telephone calls, videocalls, data platforms of shared telemedicine data platforms mitigated the negative effect of pandemic restrictions. Published evidence has documented good metabolic control and weight management outcomes in centers that performed extensive telemedicine services last year during the pandemic. This review discusses studies that investigated the use of telemedicine tools for the management of pediatric obesity and diabetes