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Deep-Learning-based Automated Identification of Ventriculoperitoneal-Shunt Valve Models from Skull X-rays.

Clin Neuroradiol

January 2025

Department of Diagnostic and Interventional Radiology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany.

Introduction: Ventriculoperitoneal shunts (VPS) are an essential part of the treatment of hydrocephalus, with numerous valve models available with different ways of indicating pressure levels. The model types often need to be identified on X‑rays to assess pressure levels using a matching template. Artificial intelligence (AI), in particular deep learning, is ideally suited to automate repetitive tasks such as identifying different VPS valve models.

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Pulmonary atresia with ventricular septal defect (PA-VSD) is usually diagnosed by transthoracic or fetal echocardiography, with the prenatal diagnosis being feasible and accurate if fetal cardiology services are available. The limitations of transthoracic echocardiography (TTE) in the evaluation of PA-VSD include the complete evaluation of the pulmonary arteries and patent ductus arteriosus, quantitative evaluation of the right ventricle size and function, and delineation of associated cardiac anomalies such as coronary artery anomalies, anomalies of systemic or pulmonary venous return, and complex arch anomalies. Echocardiography also has limitations in evaluating hemodynamics such as flow volumes, shunts, and regurgitant fraction.

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The simulation of ideal and non-ideal conditions using the SCAPS-1D simulator for novel structure Ag/FTO/CuBiO/GQD/Au was done for the first time. The recombination of charge carriers in CuBiO is an inherent problem due to very low hole mobility and polaron transport in the valence band. The in-depth analysis of the simulation result revealed that Graphene Quantum Dots (GQDs) can act as an appropriate hole transport layer (HTL) and can enhance hole transportation.

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Purpose: Long axial field-of-view (LAFOV) positron emission tomography/computed tomography (PET/CT) scanners enable high sensitivity and wide anatomical coverage. Therefore, they seem ideal to perform post-selective internal radiation therapy (SIRT) Y scans, which are needed, to confirm that the dose is delivered to the tumors and that healthy organs are spared. However, it is unclear to what extent the use of LAFOV PET is feasible and which dosimetry approaches results in accurate measurements.

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Objectives: This study aimed to evaluate the performance of virtual portal pressure gradient (vPPG) and its associated hemodynamic parameters of 3-dimensional (3D) model in patients with cirrhosis.

Methods: Seventy cirrhotic patients who underwent both hepatic venous pressure gradient (HVPG) measurement and vPPG calculation were prospectively collected. The ideal-state model (ISM; n = 44) was defined by sinusoidal PH without hepatic vein shunt or portal vein thrombosis, whereas those not conforming to the criteria were classified as non-ISM (n = 26).

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