Indocyanine green fluorescence angiography after full-thickness bowel resection for rectosigmoid endometriosis: A multicentric experience with quantitative analysis.

OBJECTIVE: To evaluate effectiveness and reproducibility of qualitative and quantitative near-infrared indocyanine green (NIR-ICG) analyses as a tool for anastomotic perfusion assessment after full-thickness bowel resection for rectosigmoid endometriosis (RSE). METHODS: Symptomatic women with RSE undergoing minimally invasive full-thickness surgical excision of RSE and NIR-ICG evaluation from November 2019 to July 2020 were included. Study outcomes were the accuracy of qualitative and quantitative NIR-ICG analyses in predicting bowel fistula and their reproducibility. NIR-ICG predictive accuracy was assessed by calculating sensitivity, specificity, and area under the curve on receiver operating characteristic curves with 95% confidence intervals (CI). NIR-ICG reproducibility was assessed through Cohen's k coefficient to determine interoperator agreement between two observers. RESULTS: Of 33 patients, 2 (6%) developed bowel fistula. In predicting bowel fistula, qualitative and quantitative NIR-ICG evaluations showed sensitivity of 100% and 100%, specificity of 71% and 93%, and area under the curve of 0.86 (95% CI 0.67-1.00) and 0.96 (95% CI 0-1.00), respectively. Regarding interoperator agreement rate, it was reported as excellent for the qualitative analysis and very good for the quantitative analysis. CONCLUSION: Qualitative and quantitative NIR-ICG evaluations might be effective and reproducible tools for anastomotic perfusion assessment after discoid or segmental resection for RSE. Quantitative evaluation might be even more effective than qualitative evaluation in predicting bowel fistula.

Computational Analysis of Mapping Catheter Geometry and Contact Quality Effects on Rotor Detection in Atrial Fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia and catheter mapping has been proved to be an effective approach for detecting AF drivers to be targeted by ablation. Among drivers, the so-called rotors have gained the most attention: their identification and spatial location could help to understand which patient-specific mechanisms are acting, and thus to guide the ablation execution. Since rotor detection by multi-electrode catheters may be influenced by several structural parameters including inter-electrode spacing, catheter coverage, and endocardium-catheter distance, in this study we proposed a tool for testing the ability of different catheter shapes to detect rotors in different conditions. An approach based on the solution of the monodomain equations coupled with a modified Courtemanche ionic atrial model, that considers an electrical remodeling, was applied to simulate spiral wave dynamics on a 2D model for 7.75 s. The developed framework allowed the acquisition of unipolar signals at 2 KHz. Two high-density multipolar catheters were simulated (Advisor™ HD Grid and PentaRay®) and placed in a 2D region in which the simulated spiral wave persists longer. The configuration of the catheters was then modified by changing the number of electrodes, inter-electrodes distance, position, and atrial-wall distance for assessing how they would affect the rotor detection. In contact with the wall and at 1 mm distance from it, all the configurations detected the rotor correctly, irrespective of geometry, coverage, and inter-electrode distance. In the HDGrid-like geometry, the increase of the inter-electrode distance from 3 to 6 mm caused rotor detection failure at 2 mm distance from the LA wall. In the PentaRay-like configuration, regardless of inter-electrode distance, rotor detection failed at 3 mm endocardium-catheter distance. The asymmetry of this catheter resulted in rotation-dependent rotor detection. To conclude, the computational framework we developed is based on realistic catheter shapes designed with parameter configurations which resemble clinical settings. Results showed it is well suited to investigate how mapping catheter geometry and location affect AF driver detection, therefore it is a reliable tool to design and test new mapping catheters.

Effect of High-Titer Convalescent Plasma on Progression to Severe Respiratory Failure or Death in Hospitalized Patients With COVID-19 Pneumonia: A Randomized Clinical Trial.

Importance: Convalescent plasma (CP) has been generally unsuccessful in preventing worsening of respiratory failure or death in hospitalized patients with COVID-19 pneumonia. Objective: To evaluate the efficacy of CP plus standard therapy (ST) vs ST alone in preventing worsening respiratory failure or death in patients with COVID-19 pneumonia. Design, Setting, and Participants: This prospective, open-label, randomized clinical trial enrolled (1:1 ratio) hospitalized patients with COVID-19 pneumonia to receive CP plus ST or ST alone between July 15 and December 8, 2020, at 27 clinical sites in Italy. Hospitalized adults with COVID-19 pneumonia and a partial pressure of oxygen-to-fraction of inspired oxygen (Pao2/Fio2) ratio between 350 and 200 mm Hg were eligible. Interventions: Patients in the experimental group received intravenous high-titer CP (≥1:160, by microneutralization test) plus ST. The volume of infused CP was 200 mL given from 1 to a maximum of 3 infusions. Patients in the control group received ST, represented by remdesivir, glucocorticoids, and low-molecular weight heparin, according to the Agenzia Italiana del Farmaco recommendations. Main Outcomes and Measures: The primary outcome was a composite of worsening respiratory failure (Pao2/Fio2 ratio <150 mm Hg) or death within 30 days from randomization. Results: Of the 487 randomized patients (241 to CP plus ST; 246 to ST alone), 312 (64.1%) were men; the median (IQR) age was 64 (54.0-74.0) years. The modified intention-to-treat population included 473 patients. The primary end point occurred in 59 of 231 patients (25.5%) treated with CP and ST and in 67 of 239 patients (28.0%) who received ST (odds ratio, 0.88; 95% CI, 0.59-1.33; P = .54). Adverse events occurred more frequently in the CP group (12 of 241 [5.0%]) compared with the control group (4 of 246 [1.6%]; P = .04). Conclusions and Relevance: In patients with moderate to severe COVID-19 pneumonia, high-titer anti-SARS-CoV-2 CP did not reduce the progression to severe respiratory failure or death within 30 days. Trial Registration: ClinicalTrials.gov Identifier: NCT04716556.

A fully automated left atrium segmentation approach from late gadolinium enhanced magnetic resonance imaging based on a convolutional neural network.

BACKGROUND: Several studies suggest that the evaluation of left atrial (LA) fibrosis is a relevant information for the assessment of the appropriate strategy in catheter ablation in atrial fibrillation (AF). Late gadolinium enhanced (LGE) cardiac magnetic resonance imaging (MRI) is a non-invasive technique, which might be employed for the non-invasive quantification of LA myocardial fibrotic tissue in patients with AF. Nowadays, the analysis of LGE MRI relies on manual tracing of LA boundaries and this procedure is time-consuming and prone to high inter-observer variability given the different degrees of observers' experience, LA wall thickness and data resolution. Therefore, an automated segmentation approach of the atrial cavity for the quantification of scar tissue would be highly desirable. METHODS: This study focuses on the design of a fully automated LGE MRI segmentation pipeline which includes a convolutional neural network (CNN) based on the successful architecture U-Net. The CNN was trained, validated and tested end-to-end with the data available from the Statistical Atlases and Computational Modelling of the Heart 2018 Atrial Segmentation Challenge (100 cardiac data). Two different approaches were tested: using both stacks of 2-D axial slices and using 3-D data (with the appropriate changes in the baseline architecture). In the latter approach, thanks to the 3-D convolution operator, all the information underlying 3-D data can be exploited. Once the training was completed using 80 cardiac data, a post-processing step was applied on 20 predicted segmentations belonging to the test set. RESULTS: By applying the 2-D and 3-D approaches, average Dice coefficient and mean Hausdorff distances were 0.896, 0.914, and 8.98 mm, 8.34 mm, respectively. Volumes of the anatomical LA meshes from the automated analysis were highly correlated with the volumes from ground truth [2-D: r=0.978, y=0.94x+0.07, bias=3.5 ml (5.6%), SD=5.3 mL (8.5%); 3-D: r=0.982, y=0.92x+2.9, bias=2.1 mL (3.5%), SD=5.2 mL (8.4%)]. CONCLUSIONS: These results suggest the proposed approach is feasible and provides accurate results. Despite the increase of the number of trainable parameters, the proposed 3-D CNN learns better features leading to higher performance, feasible for a real clinical application.

Dynamics of Clostridium genus and hard-cheese spoiling Clostridium species in anaerobic digesters treating agricultural biomass.

Biogas plants are a widespread renewable energy technology. However, the use of digestate for agronomic purposes has often been a matter of concern. It is controversial whether biogas plants might harbor some pathogenic clostridial species, which represent a biological risk. Moreover, the inhabitance of Clostridium hard-cheese spoiling species in anaerobic digesters can be problematic for hard-cheese manufacturing industries, due to the issue of cheese blowing defects. This study investigated the effect of mesophilic anaerobic digestion processes on the Clostridium consortia distribution over time. Specifically, three lab-scale CSTRs treating agricultural biomass were characterized by considering both the whole microbial community and the cultivable clostridial spores. It is assessed an overall reduction of the Clostridium genus during the anaerobic digestion process. Moreover, it was evidenced a slight, but steady decrease of the cultivable clostridial spores, mainly represented by two pathogenic species, C. perfringens and C. bifermentans, and one hard-cheese spoiling species, C. butyricum. Thus, it is revealed an overall reduction of the clostridial population abundance after the mesophilic anaerobic digestion treatment of agricultural biomass.

Methodological approach for trace elements supplementation in anaerobic digestion: Experience from full-scale agricultural biogas plants.

Trace metals play a very important role on the performance and stability of agricultural biogas digesters. The purpose of this study was to develop a methodological approach to quickly detect limiting conditions due to Trace Elements (TE) concentration in full-scale biogas plants. The work was based on long-term process monitoring in two full-scale agricultural biogas plants and on the correlation between their performance and TE concentration in the digesters. Monitoring and analysis of data from two different case studies allowed to understand the effect of the TE added on biogas plant performance. Furthermore, over-dosage has been avoided, minimizing the risk of biological inhibition and excess of heavy metal concentration in the effluent digestate according to regulation for land fertilization. TE supplementation has been successfully applied to optimize the biogas production, when a slight volatile organic acid accumulation has been detected (from about 3515 mg CH3COOHeq L-1 to 4530 mg CH3COOHeq L-1), and to recover the biogas production after a strong organic acid accumulation (up to 7779 mgCH3COOHeq L-1). Molybdenum, nickel, cobalt, and selenium concentrations above the stimulatory level identified in this study showed similar effects in both case studies: a temporary increase of the methane content in the biogas by 15 - 20% and a provisional improvement of the specific methane production. This allowed to decrease the organic loading rate by 10 - 20%, due to rapid degradation of accumulated volatile organic acids. Further, the residual methane potential of the biogas plant in TE limiting conditions reached values up to 4.8% in comparison to the 1.3% residual methane potential achieved when TE concentration was not a limiting factor, proving that a proper use of TE could help in reducing greenhouse gases emission.

3D patient-specific models for left atrium characterization to support ablation in atrial fibrillation patients.

BACKGROUND: Radiofrequency ablation (RFA) is an important and promising therapy for atrial fibrillation (AF) patients. Optimization of patient selection and the availability of an accurate anatomical guide could improve RFA success rate. In this study we propose a unified, fully automated approach to build a 3D patient-specific left atrium (LA) model including pulmonary veins (PVs) in order to provide an accurate anatomical guide during RFA and without PVs in order to characterize LA volumetry and support patient selection for AF ablation. METHODS: Magnetic resonance data from twenty-six patients referred for AF RFA were processed applying an edge-based level set approach guided by a phase-based edge detector to obtain the 3D LA model with PVs. An automated technique based on the shape diameter function was designed and applied to remove PVs and compute LA volume. 3D LA models were qualitatively compared with 3D LA surfaces acquired during the ablation procedure. An expert radiologist manually traced the LA on MR images twice. LA surfaces from the automatic approach and manual tracing were compared by mean surface-to-surface distance. In addition, LA volumes were compared with volumes from manual segmentation by linear and Bland-Altman analyses. RESULTS: Qualitative comparison of 3D LA models showed several inaccuracies, in particular PVs reconstruction was not accurate and left atrial appendage was missing in the model obtained during RFA procedure. LA surfaces were very similar (mean surface-to-surface distance: 2.3±0.7mm). LA volumes were in excellent agreement (y=1.03x-1.4, r=0.99, bias=-1.37ml (-1.43%) SD=2.16ml (2.3%), mean percentage difference=1.3%±2.1%). CONCLUSIONS: Results showed the proposed 3D patient-specific LA model with PVs is able to better describe LA anatomy compared to models derived from the navigation system, thus potentially improving electrograms and voltage information location and reducing fluoroscopic time during RFA. Quantitative assessment of LA volume derived from our 3D LA model without PVs is also accurate and may provide important information for patient selection for RFA.

Monitoring of full-scale hydrodynamic cavitation pretreatment in agricultural biogas plant.

The implementation of hydrodynamic cavitation (HC) pretreatment for enhancing the methane potential from agricultural biomasses was evaluated in a full scale agricultural biogas plant, with molasses and corn meal as a supplementary energy source. HC batch tests were run to investigate the influence on methane production, particle size and viscosity of specific energy input. 470kJ/kgTS was chosen for the full-scale implementation. Nearly 6-months of operational data showed that the HC pretreatment maximized the specific methane production of about 10%, allowing the biogas plant to get out of the fluctuating markets of supplementary energy sources and to reduce the methane emissions. HC influenced viscosity and particle size of digestate, contributing to reduce the energy demand for mixing, heating and pumping. In the light of the obtained results the HC process appears to be an attractive and energetically promising alternative to other pretreatments for the degradation of biomasses in biogas plant.

Anaerobic Digestion of Cattle Manure Influenced by Swirling Jet Induced Hydrodynamic Cavitation.

In this work, a modified swirling jet-induced cavitation has been employed for increasing anaerobic digestion efficiency of cattle manure. The hydrodynamic cavitation (HC) treatment improved the organic matter solubilization and the anaerobic biodegradability of cattle manure. The degree of disintegration increased by 5.8, 8.9, and 15.8% after the HC treatment at 6.0, 7.0, and 8.0 bars, respectively. However, the HC treatment at 7.0 bars had better results in terms of methane production. This result may be attributed to the possible formation of toxic and refractory compounds at higher inlet pressures, which could inhibit the methanization process. Further, total Kjeldahl nitrogen content was found to decrease with increasing inlet pressures, as the pH and the turbulent mixing favored the ammonia stripping processes. HC treatment decreased the viscosity of the treated cattle manure, favoring the manure pumping and mixing. Considerations on the energy input due to the HC pre-treatment and the energy output due to the enhanced methane yield have been presented. A positive energy balance can be obtained looking at the improved operational practices in the anaerobic digesters after the implementation of the HC pre-treatment.