Predictive haemodynamics in a one-dimensional human carotid artery bifurcation. Part II: application to graft design

A Bayesian surrogate modelling technique is proposed that may be able to predict an optimal bypass graft configuration for patients suffering with stenosis in the internal carotid artery (ICA). At the outset, this statistical technique is considered as a means for identifying key geometric parameters influencing haemodynamics in the human carotid bifurcation. This methodology uses a design of experiments (DoE) technique to generate candidate geometries for flow analysis. A pulsatile one dimensional Navier-Stokes solver incorporating fluid-wall interactions for a Newtonian fluid which predicts pressure and flow in the carotid bifurcation (comprising a stenosed segment in the internal carotid artery) is used for the numerical simulations. Two metrics, pressure variation factor (PVF) and maximum pressure (pm) are employed to directly compare the global and local effects, respectively, of variations in the geometry. The values of PVF and pm are then used to construct two Bayesian surrogate models. These models are statistically analysed to visualise how each geometric parameter influences PVF and pm. Percentage of stenosis is found to influence these pressure based metrics more than any other geometric parameter. Later, we identify bypass grafts with optimal geometric and material properties which have low values of PVF on five test cases with 70%, 75%, 80%, 85% and 90% stenosis in the ICA, respectively

Predictive haemodynamics in a one-dimensional human carotid artery bifurcation. Part 1: application to stent design

A diagnostic technique is proposed to identify patients with carotid stenosis who could most benefit from angioplasty followed by stent implantation. This methodology involves performing a parametric study to investigate the haemodynamic behavior due to alterations in the stenosis shapes in the internal carotid artery (ICA). A pulsatile 1-D Navier-Stokes solver incorporating fluid-wall interactions for a Newtonian fluid which predicts pressure and flow in the human carotid artery bifurcation is used for the numerical simulations. In order to assess the performance of each individual geometry, we introduce pressure variation factor as a metric to directly compare the global effect of variations in the geometry. It is shown that the probability of an overall catastrophic effect is higher when the stenosis is present in the upstream segment of the ICA. Furthermore, maximum pressure is used to quantify the local effects of geometry changes. The location of the peak and extent of stenosis are found not to influence maximum pressure. We also show how these metrics respond after stent deployment into the stenosed part of the ICA. In particular, it is found that localized pressure peaks do not depend on the length of a stent. Finally, we demonstrate how these metrics may be applied to cost-effectively predict the benefit of stenting

Impact of flow pulsatility on arterial drug distribution in stent-based therapy

Drug-eluting stents reside in a dynamic fluid environment where the extent to which drugs are distributed within the arterial wall is critically modulated by the blood flowing through the arterial lumen. Yet several factors associated with the pulsatile nature of blood flow and their impact on arterial drug deposition have not been fully investigated. We employed an integrated framework comprising bench-top and computational models to explore the factors governing the time-varying fluid dynamic environment within the vasculature and their effects on arterial drug distribution patterns. A custom-designed bench-top framework comprising a model of a single drug-eluting stent strut and a poly-vinyl alcohol-based hydrogel as a model tissue bed simulated fluid flow and drug transport under fully apposed strut settings. Bench-top experiments revealed a relative independence between drug distribution and the factors governing pulsatile flow and these findings were validated with the in silico model. Interestingly, computational models simulating suboptimal deployment settings revealed a complex interplay between arterial drug distribution, Womersley number and the extent of malapposition. In particular, for a stent strut offset from the wall, total drug deposition was sensitive to changes in the pulsatile flow environment, with this dependence increasing with greater wall displacement. Our results indicate that factors governing pulsatile luminal flow on arterial drug deposition should be carefully considered in conjunction with device deployment settings for better utilization of drug-eluting stent therapy.National Institutes of Health (U.S.) (grant NIH R01 GM-49039

Thermal Analysis of Radiator Core In Heavy Duty Automobile

ABSTRACT Background: Heat dissipation is one of the most critical considerations in engine design and with an efficient cooling system; performance of the engine can be dramatically improved. All internal combustion engines convert chemical energy into mechanical power. Around 70% of the energy is converted into heat and therefore, the primary job of the cooling system is to keep the engine from overheating by transferring this heat to the air. A radiator transfer's heat from the hot coolant to the air and an effective design of radiator will ultimately lead to enhanced engine performance by reducing the heating effect. Methods and results: A mathematical expression for the rate of heat dissipation from the radiator core was derived and a modification in the design was proposed in the radiator core by changing the structure of the tubes from cylindrical to helical. The rate of heat dissipation for both designs was compared with similar boundary conditions by varying the magnitude of all design parameters in a specific range that have same magnitude of area of cross section, length of the radiator core and coefficient of thermal conductivity for the tube. Enhanced rate of heat dissipation for helical structure confirms the efficacy of the proposed design

Stent Thrombogenicity Early in High Risk Interventional Settings is Driven by Stent Design and Deployment, and Protected by Polymer-Drug Coatings

Author Manuscript: 2012 April 5Background—Stent thrombosis is a lethal complication of endovascular intervention. Concern has been raised about the inherent risk associated with specific stent designs and drug-eluting coatings, yet clinical and animal support is equivocal. Methods and Results—We examined whether drug-eluting coatings are inherently thrombogenic and if the response to these materials was determined to a greater degree by stent design and deployment with custom-built stents. Drug/polymer coatings uniformly reduce rather than increase thrombogenicity relative to matched bare metal counterparts (0.65-fold; P=0.011). Thick-strutted (162 μm) stents were 1.5-fold more thrombogenic than otherwise identical thin-strutted (81 μm) devices in ex vivo flow loops (P<0.001), commensurate with 1.6-fold greater thrombus coverage 3 days after implantation in porcine coronary arteries (P=0.004). When bare metal stents were deployed in malapposed or overlapping configurations, thrombogenicity increased compared with apposed, length-matched controls (1.58-fold, P=0.001; and 2.32-fold, P<0.001). The thrombogenicity of polymer-coated stents with thin struts was lowest in all configurations and remained insensitive to incomplete deployment. Computational modeling–based predictions of stent-induced flow derangements correlated with spatial distribution of formed clots. Conclusions—Contrary to popular perception, drug/polymer coatings do not inherently increase acute stent clotting; they reduce thrombosis. However, strut dimensions and positioning relative to the vessel wall are critical factors in modulating stent thrombogenicity. Optimal stent geometries and surfaces, as demonstrated with thin stent struts, help reduce the potential for thrombosis despite complex stent configurations and variability in deployment

Smartphone-based neuropsychological assessment in Parkinson's disease: feasibility, validity, and contextually driven variability in cognition

OBJECTIVES: The prevalence of neurodegenerative disorders demands methods of accessible assessment that reliably captures cognition in daily life contexts. We investigated the feasibility of smartphone cognitive assessment in people with Parkinson's disease (PD), who may have cognitive impairment in addition to motor-related problems that limit attending in-person clinics. We examined how daily-life factors predicted smartphone cognitive performance and examined the convergent validity of smartphone assessment with traditional neuropsychological tests. METHODS: Twenty-seven nondemented individuals with mild-moderate PD attended one in-lab session and responded to smartphone notifications over 10 days. The smartphone app queried participants 5x/day about their location, mood, alertness, exercise, and medication state and administered mobile games of working memory and executive function. RESULTS: Response rate to prompts was high, demonstrating feasibility of the approach. Between-subject reliability was high on both cognitive games. Within-subject variability was higher for working memory than executive function. Strong convergent validity was seen between traditional tests and smartphone working memory but not executive function, reflecting the latter's ceiling effects. Participants performed better on mobile working memory tasks when at home and after recent exercise. Less self-reported daytime sleepiness and lower PD symptom burden predicted a stronger association between later time of day and higher smartphone test performance. CONCLUSIONS: These findings support feasibility and validity of repeat smartphone assessments of cognition and provide preliminary evidence of the effects of context on cognitive variability in PD. Further development of this accessible assessment method could increase sensitivity and specificity regarding daily cognitive dysfunction for PD and other clinical populations.RF1 AG062109 - NIA NIH HHSPublished versio

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach

INTRODUCTION: Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. METHODS: A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects' neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants' demographic characteristics. RESULTS: Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. DISCUSSION: The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.AG054156 - NIA NIH HHS; RF1 AG062109 - NIA NIH HHS; AG049810 - NIA NIH HHS; U19 AG068753 - NIA NIH HHS; HHSN268201500001I - NHLBI NIH HHS; R01 AG016495 - NIA NIH HHS; UL54 TR004130 - NIH HHS; R01 GM135930 - NIGMS NIH HHS; RF1 AG072654 - NIA NIH HHS; AARG-NTF-20-643020 - Alzheimer's Association; R21-CA253498 - NIH HHS; AG033040 - NIA NIH HHS; AG068753 - NIA NIH HHS; R01-HL159620 - NIH HHS; AG016495 - NIA NIH HHS; R01 GM135930 - NIH HHS; AG008122 - NIA NIH HHS; R01 AG033040 - NIA NIH HHS; R56 AG062109 - NIA NIH HHS; AG062109 - NIA NIH HHS; CCF-2200052 - National Science Foundation; IIS-1914792 - National Science Foundation; DMS-1664644 - National Science FoundationAccepted manuscrip

Deep-learning-driven quantification of interstitial fibrosis in digitized kidney biopsies

Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA estimation using computational techniques can reduce this variability and provide quantitative assessment. Using trichrome-stained whole-slide images (WSIs) processed from human renal biopsies, we developed a deep-learning framework that captured finer pathologic structures at high resolution and overall context at the WSI level to predict IFTA grade. WSIs (n = 67) were obtained from The Ohio State University Wexner Medical Center. Five nephropathologists independently reviewed them and provided fibrosis scores that were converted to IFTA grades: ≤10% (none or minimal), 11% to 25% (mild), 26% to 50% (moderate), and >50% (severe). The model was developed by associating the WSIs with the IFTA grade determined by majority voting (reference estimate). Model performance was evaluated on WSIs (n = 28) obtained from the Kidney Precision Medicine Project. There was good agreement on the IFTA grading between the pathologists and the reference estimate (κ = 0.622 ± 0.071). The accuracy of the deep-learning model was 71.8% ± 5.3% on The Ohio State University Wexner Medical Center and 65.0% ± 4.2% on Kidney Precision Medicine Project data sets. Our approach to analyzing microscopic- and WSI-level changes in renal biopsies attempts to mimic the pathologist and provides a regional and contextual estimation of IFTA. Such methods can assist clinicopathologic diagnosis.U01 DK085660 - NIDDK NIH HHS; RF1 AG062109 - NIA NIH HHS; R21 CA253498 - NCI NIH HHS; R21 DK119751 - NIDDK NIH HHS; R01 HL132325 - NHLBI NIH HHS; UL1 TR001430 - NCATS NIH HHS; R56 AG062109 - NIA NIH HHS; R21 DK119740 - NIDDK NIH HHShttps://www.medrxiv.org/content/10.1101/2021.01.03.21249179v1.full.pd

Galectin-3 is associated with stage B metabolic heart disease and pulmonary hypertension in young obese patients

Background Obesity is a precursor to heart failure with preserved ejection fraction. Biomarkers that identify preclinical metabolic heart disease ( MHD ) in young obese patients would help identify high-risk individuals for heart failure prevention strategies. We assessed the predictive value of GAL3 (galectin-3), FSTL3 (follistatin-like 3 peptide), and NT-proBNP (N-terminal pro-B-type natriuretic peptide) to identify stage B MHD in young obese participants free of clinically evident cardiovascular disease. Methods and Results Asymptomatic obese patients (n=250) and non-obese controls (n=21) underwent echocardiographic cardiac phenotyping. Obese patients were classified as MHD positive ( MHD - POS ; n=94) if they had abnormal diastolic function or left ventricular hypertrophy and had estimated pulmonary artery systolic pressure ≥35 mm Hg. Obese patients without such abnormalities were classified as MHD negative (MHD-NEG; n=52). Serum biomarkers timed with echocardiography. MHD - POS and MHD-NEG individuals were similarly obese, but MHD - POS patients were older, with more diabetes mellitus and metabolic syndrome. Right ventricular coupling was worse in MHD - POS patients ( P<0.001). GAL 3 levels were higher in MHD - POS versus MHD -NEG patients (7.7±2.3 versus 6.3±1.9 ng/mL, respectively; P<0.001). Both GAL 3 and FSTL 3 levels correlated with diastolic dysfunction and increased pulmonary artery systolic pressure but not with left ventricular mass. In multivariate models including all 3 biomarkers, only GAL 3 remained associated with MHD (odds ratio: 1.30; 95% CI , 1.01-1.68; P=0.04). Conclusions In young obese individuals without known cardiovascular disease, GAL 3 is associated with the presence of preclinical MHD . GAL 3 may be useful in screening for preclinical MHD and identifying individuals with increased risk of progression to obesity-related heart failure with preserved ejection fraction.Deepa M. Gopal, Nir Ayalon, Yi, Chih Wang, Deborah Siwik, Aaron Sverdlov, Courtney Donohue ... et al