Automatic Detection of Visceral Arterial Aneurysms on Computed Tomography Angiography Using Artificial Intelligence Based Segmentation of the Vascular System.

Introduction: Visceral arterial aneurysms (VAAs) are life threatening. Due to the paucity of symptoms and rarity of the disease, VAAs are underdiagnosed and underestimated. Artificial intelligence (AI) offers new insights into segmentation of the vascular system, and opportunities to better detect VAAs.

A Monte Carlo-Based Strategy to Assess Complex Kinetics: Application of the Null-Reaction Method to DAEM.

The distributed activation energy model (DAEM) is widely used in chemical kinetics to statistically describe the occurrence of numerous independent parallel reactions. In this article, we suggest a rethink in the context of a Monte Carlo integral formulation to compute the conversion rate at any time without approximation. After the basics of the DAEM are introduced, the considered equations (under isothermal and dynamic conditions) are respectively expressed into expected values, which in turn are transcribed into Monte Carlo algorithms.

Applications of artificial intelligence for patients with peripheral artery disease.

Objective: Applications of artificial intelligence (AI) have been reported in several cardiovascular diseases but its interest in patients with peripheral artery disease (PAD) has been so far less reported. The aim of this review was to summarize current knowledge on applications of AI in patients with PAD, to discuss current limits, and highlight perspectives in the field.

Methods: We performed a narrative review based on studies reporting applications of AI in patients with PAD.

Automatic Measurement of Vascular Calcifications in Patients with Aorto-Iliac Occlusive Disease to Predict the Risk of Re-intervention After Endovascular Repair.

Background: There is currently a lack of consensus and tools to easily measure vascular calcification using computed tomography angiography (CTA). The aim of this study was to develop a fully automatic software to measure calcifications and to evaluate the interest as predictive factor in patients with aorto-iliac occlusive disease.

Methods: This study retrospectively included 171 patients who had endovascular repair of an aorto-iliac occlusive lesion at the University Hospital of Nice between January 2011 and December 2019.

Applications of Artificial Intelligence in Non-cardiac Vascular Diseases: A Bibliographic Analysis.

Research output related to artificial intelligence (AI) in vascular diseases has been poorly investigated. The aim of this study was to evaluate scientific publications on AI in non-cardiac vascular diseases. A systematic literature search was conducted using the PubMed database and a combination of keywords and focused on three main vascular diseases (carotid, aortic and peripheral artery diseases).

Automatic Measurement of Maximal Diameter of Abdominal Aortic Aneurysm on Computed Tomography Angiography Using Artificial Intelligence.

Introduction: The treatment of abdominal aortic aneurysm relies on surgical repair and the indication mainly depends on its size evaluated by the maximal diameter (Dmax). The aim of this study was to evaluate a new automatic method based on artificial intelligence to measure the Dmax on computed tomography angiography.

Methods: A fully automatic segmentation of the vascular system was performed using a hybrid method combining expert system with supervised deep learning.

Automated Segmentation of the Human Abdominal Vascular System Using a Hybrid Approach Combining Expert System and Supervised Deep Learning.

Background: Computed tomography angiography (CTA) is one of the most commonly used imaging technique for the management of vascular diseases. Here, we aimed to develop a hybrid method combining a feature-based expert system with a supervised deep learning (DL) algorithm to enable a fully automatic segmentation of the abdominal vascular tree.

Methods: We proposed an algorithm based on the hybridization of a data-driven convolutional neural network and a knowledge-based model dedicated to vascular system segmentation.

Applications of Head-Mounted Displays and Smart Glasses in Vascular Surgery.

Objectives: Advances in virtual, augmented and mixed reality have led to the development of wearable technologies including head mounted displays (HMD) and smart glasses. While there is a growing interest on their potential applications in health, only a few studies have addressed so far their use in vascular surgery. The aim of this review was to summarize the fundamental notions associated with these technologies and to discuss potential applications and current limits for their use in vascular surgery.

Artificial intelligence in abdominal aortic aneurysm.

Objective: Abdominal aortic aneurysm (AAA) is a life-threatening disease, and the only curative treatment relies on open or endovascular repair. The decision to treat relies on the evaluation of the risk of AAA growth and rupture, which can be difficult to assess in practice. Artificial intelligence (AI) has revealed new insights into the management of cardiovascular diseases, but its application in AAA has so far been poorly described.

Fundamentals in Artificial Intelligence for Vascular Surgeons.

Artificial intelligence (AI) corresponds to a broad discipline that aims to design systems, which display properties of human intelligence. While it has led to many advances and applications in daily life, its introduction in medicine is still in its infancy. AI has created interesting perspectives for medical research and clinical practice but has been sometimes associated with hype leading to a misunderstanding of its real capabilities.

A fully automated pipeline for mining abdominal aortic aneurysm using image segmentation.

Imaging software have become critical tools in the diagnosis and the treatment of abdominal aortic aneurysms (AAA). The aim of this study was to develop a fully automated software system to enable a fast and robust detection of the vascular system and the AAA. The software was designed from a dataset of injected CT-scans images obtained from 40 patients with AAA.

Chemical and structural characterization of char development during lignocellulosic biomass pyrolysis.

The chemical and structural changes of three lignocellulosic biomass samples during pyrolysis were investigated using both conventional and advanced characterization techniques. The use of ATR-FTIR as a characterization tool is extended by the proposal of a method to determine aromaticity, the calculation of both CH/CH ratio and the degree of aromatic ring condensation ((R/C)). With increasing temperature, the H/C and O/C ratios, X and CH/CH ratio decreased, while (R/C) and aromaticity increased.

Quantitative Insights into the Fast Pyrolysis of Extracted Cellulose, Hemicelluloses, and Lignin.

The transformation of lignocellulosic biomass into bio-based commodity chemicals is technically possible. Among thermochemical processes, fast pyrolysis, a relatively mature technology that has now reached a commercial level, produces a high yield of an organic-rich liquid stream. Despite recent efforts to elucidate the degradation paths of biomass during pyrolysis, the selectivity and recovery rates of bio-compounds remain low.

Structural and chemical modifications of typical South African biomasses during torrefaction.

Torrefaction experiments were carried out for three typical South African biomass samples (softwood chips, hardwood chips and sweet sorghum bagasse) to a weight loss of 30 wt.%. During torrefaction, moisture, non-structural carbohydrates and hemicelluloses were reduced, resulting in a structurally modified torrefaction product.

Impact of the lignocellulosic material on fast pyrolysis yields and product quality.

The paper describes the fast pyrolysis conversion of lignocellulosic materials inside a bubbling fluidized bed. The impact of biopolymers distribution in the biomass feed, namely hemicelluloses, cellulose and lignin, on the yields and properties of pyrolytic bio-oils and chars was investigated. Although it is not possible to deconvoluate chemical phenomena from transfer phenomena using bubbling fluidized bed reactors, the key role of hemicelluloses in biomass feedstocks was illustrated by: (i) its influence on the production of pyrolytic water, (ii) its impact on the production of organics, apparently due to its bonding relationship with the lignin and (iii) its ability to inhibit the development of chars porosity, while the cellulose appeared to be the precursor for the microporous character of the biochars.

Photocatalytic degradation of diuron: experimental analyses and simulation of HO degrees radical attacks by density functional theory calculations.

The photocatalytic oxidation of diuron has been performed in presence of TiO(2) suspensions. To better understand the mechanistic details of the hydroxyl radical attack on diuron, computational methods were carried out. The combination of experimental and computational methods has been employed to establish the main degradation pathways of diuron.