Τετάρτη 16 Μαρτίου 2022

Embedded Computational Heart Model for External Ventricular Assist Device Investigations

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Abstract

Purpose

External cardiac assist devices are based on a promising and simple concept for treating heart failure, but they are surprisingly difficult to design. Thus, a structured approach combining experiments with computer-based optimization is essential. The latter provides the motivation for the work presented in this paper.

Methods

We present a computational modeling framework for realistic representation of the heart's tissue structure, electrophysiology and actuation. The passive heart tissue is described by a nonlinear anisotropic material law, considering fiber and sheetlet directions. For muscle contraction, an orthotropic active-strain model is employed, initiated by a periodically propagating electrical potential. The model allows for boundary conditions at the epicardium accounting for external assist devices, and it is coupled to a circulation network providing appropriate pressure boundary conditions inside the ventricles.

Results

Simulated results from an unsupported healthy and a pathological heart model are presented and reproduce accurate deformations compared to phenomenological measurements. Moreover, cardiac output and ventricular pressure signals are in good agreement too. By investigating the impact of applying an exemplary external actuation to the pathological heart model, it shows that cardiac patches can restore a healthy blood flow.

Conclusion

We demonstrate that the devised computational modeling framework is capable of predicting characteristic trends (e.g. apex shortening, wall thickening and apex twisting) of a healthy heart, and that it can be used to study pathological hearts and external activation thereof.

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Gastric duplication cyst: a challenging EUS differential diagnosis between subepithelial gastric lesion and exophytic pancreatic cystic neoplasm—a case report and a literature review

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Abstract

Gastric duplication cysts are rare congenital malformation with a potential neoplastic progression and they may represent a challenge in differential diagnosis with exophytic pancreatic cyst neoplasm. We describe a case of a 38-year old man, complaining of recurrent epigastric pain due to a large abdominal mass, referred to our Hospital for EUS evaluation. Differential diagnosis was between gastric duplication cyst and exophytic pancreatic cyst because of FNA pointed out amylase 1280 UI/L and CEA 593.33 ng/mL. Despite antibiotic prophylaxis, an overinfection of the lesion occurred after the FNA, likely due to the technical failure to drain the cyst completely. Afterwards, the patient was referred to surgery and the pathologist confirmed the diagnosis of gastric duplication cyst. In this setting, EUS procedure has gained a leading play, complementary to traditional imaging tests, although its role has been not yet standardized in the reported literature. Here , we describe and discuss our demanding case, and we propose an algorithm to simplify and standardize the diagnostic workup.

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Real-time eye state recognition using dual convolutional neural network ensemble

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Abstract

Automatic recognition of the eye states is essential for diverse computer vision applications related to drowsiness detection, facial emotion recognition (FER), human–computer interaction (HCI), etc. Existing solutions for eye state detection are either parameter intensive or suffer from a low recognition rate. This paper presents the design and implementation of a vision-based system for real-time eye state recognition on a resource-constrained embedded platform to tackle these issues. The designed system uses an ensemble of two lightweight convolutional neural networks (CNN), each trained to extract relevant information from the eye patches. We adopted transfer-learning-based fine-tuning to overcome the over-fitting issues when training the CNNs on small sample eye state datasets. Once trained, these CNNs are integrated and jointly fine-tuned to achieve enhanced performance. Experimental results manifest the effectiveness of the proposed eye state recognizer that is robust and computationally efficient. On the ZJU dataset, the proposed DCNNE model delivered the state-of-the-art recognition accuracy of 97.99% and surpassed the prior best recognition accuracy of 97.20% by 0.79%. The designed model also achieved competitive results on the CEW and MRL datasets. Finally, the designed CNNs are optimized and ported on two different embedded platforms for real-world applications with real-time performance. The complete system runs at 62 frames per second (FPS) on an Nvidia Xavier device and 11 FPS on a low-cost Intel NCS2 embedded platform using a frame size of 640 \(\times\) 480 pixels resolution.

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Microglia phenotypes are associated with subregional patterns of concomitant tau, amyloid-β and α-synuclein pathologies in the hippocampus of patients with Alzheimer’s disease and dementia with Lewy bodies

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Abstract

The cellular alterations of the hippocampus lead to memory decline, a shared symptom between Alzheimer's disease (AD) and dementia with Lewy Bodies (DLB) patients. However, the subregional deterioration pattern of the hippocampus differs between AD and DLB with the CA1 subfield being more severely affected in AD. The activation of microglia, the brain immune cells, could play a role in its selective volume loss. How subregional microglia populations vary within AD or DLB and across these conditions remains poorly understood. Furthermore, how the nature of the hippocampal local pathological imprint is associated with microglia responses needs to be elucidated. To this purpose, we employed an automated pipeline for analysis of 3D confocal microscopy images to assess CA1, CA3 and DG/CA4 subfields microglia responses in post-mortem hippocampal samples from late-onset AD (n = 10), DLB (n = 8) and age-matched control (CTL) (n =� ��11) individuals. In parallel, we performed volumetric analyses of hyperphosphorylated tau (pTau), amyloid-β (Aβ) and phosphorylated α-synuclein (pSyn) loads. For each of the 32,447 extracted microglia, 16 morphological features were measured to classify them into seven distinct morphological clusters. Our results show similar alterations of microglial morphological features and clusters in AD and DLB, but with more prominent changes in AD. We identified two distinct microglia clusters enriched in disease conditions and particularly increased in CA1 and DG/CA4 of AD and CA3 of DLB. Our study confirms frequent concomitance of pTau, Aβ and pSyn loads across AD and DLB but reveals a specific subregional pattern for each type of pathology, along with a generally increased severity in AD. Furthermore, pTau and pSyn loads were highly correlated across subregions and conditions. We uncovered tight associations between microglial changes and the subfield pathological imprint. Our findi ngs suggest that combinations and severity of subregional pTau, Aβ and pSyn pathologies transform local microglia phenotypic composition in the hippocampus. The high burdens of pTau and pSyn associated with increased microglial alterations could be a factor in CA1 vulnerability in AD.

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Laser‐Assisted Sialolithotripsy: A Correlation of Objective and Subjective Outcomes

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Objective

To analyze the long-term symptomatic results of laser-assisted sialolithotripsy (LAS) in cases of obstructive sialolithiasis and correlate with objective criteria using diagnostic sialendoscopy (DS) as a method of examination.

Methods

This is a retrospective study comprising 50 consecutive patients who underwent holmium-YAG LAS and completed follow-up of at least 6 months. Symptom scoring and endoscopic scoring were done at 6 weeks and 6 months intervals for further study purposes.

Results

At the end of 6 weeks post-LAS, 70% patients were asymptomatic (A-sym) and only 30% had residual symptoms (Sym). However, obstructed duct (OB-duct) was observed on endoscopic scoring in 88% due to stenosis, residual stones, or both stenosis and residual stones. The obstructed ducts were treated in outpatient clinic and followed up over time, leading to 98% of patients being in A-sym group at the end of study period of 6 months. At the end of study, 82% of patients had clear duct (CL-duct).

Conclusion

Holmium LAS is a viable option for the management of intermediate-sized stones. LAS if used judiciously, and in properly selected cases, has high rate of stone fragmentation and symptom resolution. A vigilant postoperative protocol taking into account residual mealtime symptoms and altered salivary characteristics combined with early DS can help identify and treat patients with residual stone fragments and ductal stenosis.

Level of Evidence

3 Laryngoscope, 2022

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