scholarly journals Multiscale modelling of Potts shunt as a potential palliative treatment for suprasystemic idiopathic pulmonary artery hypertension: a paediatric case study

2022 ◽  
Author(s):  
Sanjay Pant ◽  
Aleksander Sizarov ◽  
Angela Knepper ◽  
Gaëtan Gossard ◽  
Alberto Noferi ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Clinical Decision ◽  
Pulmonary Artery Hypertension ◽  
Linear Increase ◽  
Left Ventricular ◽  
Patient Specific ◽  
Predictive Tool ◽  
Shunt Flow

AbstractPotts shunt (PS) was suggested as palliation for patients with suprasystemic pulmonary arterial hypertension (PAH) and right ventricular (RV) failure. PS, however, can result in poorly understood mortality. Here, a patient-specific geometrical multiscale model of PAH physiology and PS is developed for a paediatric PAH patient with stent-based PS. In the model, 7.6mm-diameter PS produces near-equalisation of the aortic and PA pressures and $$Q_p/Q_s$$ Q p / Q s (oxygenated vs deoxygenated blood flow) ratio of 0.72 associated with a 16% decrease of left ventricular (LV) output and 18% increase of RV output. The flow from LV to aortic arch branches increases by 16%, while LV contribution to the lower body flow decreases by 29%. Total flow in the descending aorta (DAo) increases by 18% due to RV contribution through the PS with flow into the distal PA branches decreasing. PS induces 18% increase of RV work due to its larger stroke volume pumped against lower afterload. Nonetheless, larger RV work does not lead to increased RV end-diastolic volume. Three-dimensional flow assessment demonstrates the PS jet impinging with a high velocity and wall shear stress on the opposite DAo wall with the most of the shunt flow being diverted to the DAo. Increasing the PS diameter from 5mm up to 10mm results in a nearly linear increase in post-operative shunt flow and a nearly linear decrease in shunt pressure-drop. In conclusion, this model reasonably represents patient-specific haemodynamics pre- and post-creation of the PS, providing insights into physiology of this complex condition, and presents a predictive tool that could be useful for clinical decision-making regarding suitability for PS in PAH patients with drug-resistant suprasystemic PAH.

Right ventricle and pulmonary arterial pressure

2016 ◽  
Author(s):  
Annemien E. van den Bosch ◽  
Luigi P. Badano ◽  
Julia Grapsa
Keyword(s):  
Clinical Decision Making ◽  
Complex Geometry ◽  
Three Dimensional ◽  
Clinical Decision ◽  
Tissue Doppler ◽  
Left Ventricular ◽  
Doppler Imaging ◽  
Prognostic Information ◽  
Recent Developments ◽  
And Function

Right ventricular (RV) performance plays an important role in the morbidity and mortality of patients with left ventricular dysfunction, congenital heart disease, and pulmonary hypertension. Assessment of RV size, function, and haemodynamics has been challenging because of its complex geometry. Conventional two-dimensional echocardiography is the modality of choice for assessment of RV function in clinical practice. Recent developments in echocardiography have provided several new techniques for assessment of RV dimensions and function, include tissue Doppler imaging, speckle-tracking imaging, and volumetric three-dimensional imaging. However, specific training, expensive dedicated equipment, and extensive clinical validation are still required. Doppler methods interrogating tricuspid inflow and pulmonary artery flow velocities, which are influenced by changes in pre- and afterload conditions, may not provide robust prognostic information for clinical decision-making. This chapter addresses the role of the various echocardiographic modalities used to assess the RV and pulmonary circulation. Special emphasis has been placed on technical considerations, limitations, and pitfalls of image acquisition and analysis.

scholarly journals The effect of beta-blockers on hemodynamic parameters in patient-specific blood flow simulations of type-B aortic dissection: a virtual study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammad Amin Abazari ◽  
Deniz Rafieianzab ◽  
M. Soltani ◽  
Mona Alimohammadi
Keyword(s):  
Aortic Dissection ◽  
Clinical Decision Making ◽  
Beta Blockers ◽  
False Lumen ◽  
Specific Treatment ◽  
Left Ventricular ◽  
Patient Specific ◽  
Type B ◽  
Windkessel Model ◽  
Computed Tomography Images

AbstractAortic dissection (AD) is one of the fatal and complex conditions. Since there is a lack of a specific treatment guideline for type-B AD, a better understanding of patient-specific hemodynamics and therapy outcomes can potentially control the progression of the disease and aid in the clinical decision-making process. In this work, a patient-specific geometry of type-B AD is reconstructed from computed tomography images, and a numerical simulation using personalised computational fluid dynamics (CFD) with three-element Windkessel model boundary condition at each outlet is implemented. According to the physiological response of beta-blockers to the reduction of left ventricular contractions, three case studies with different heart rates are created. Several hemodynamic features, including time-averaged wall shear stress (TAWSS), highly oscillatory, low magnitude shear (HOLMES), and flow pattern are investigated and compared between each case. Results show that decreasing TAWSS, which is caused by the reduction of the velocity gradient, prevents vessel wall at entry tear from rupture. Additionally, with the increase in HOLMES value at distal false lumen, calcification and plaque formation in the moderate and regular-heart rate cases are successfully controlled. This work demonstrates how CFD methods with non-invasive hemodynamic metrics can be developed to predict the hemodynamic changes before medication or other invasive operations. These consequences can be a powerful framework for clinicians and surgical communities to improve their diagnostic and pre-procedural planning.

scholarly journals Telomere Architecture Correlates with Aggressiveness in Multiple Myeloma

Cancers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1969
Author(s):  
Aline Rangel-Pozzo ◽  
Pak Yu ◽  
Sadhana LaL ◽  
Yasmin Asbaghi ◽  
Luiza Sisdelli ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Disease Progression ◽  
Genomic Instability ◽  
Clinical Decision Making ◽  
Three Dimensional ◽  
Clinical Decision ◽  
Response To Treatment ◽  
Average Intensity ◽  
Patient Response ◽  
Smoldering Multiple Myeloma

The prognosis of multiple myeloma (MM), an incurable B-cell malignancy, has significantly improved through the introduction of novel therapeutic modalities. Myeloma prognosis is essentially determined by cytogenetics, both at diagnosis and at disease progression. However, for a large cohort of patients, cytogenetic analysis is not always available. In addition, myeloma patients with favorable cytogenetics can display an aggressive clinical course. Therefore, it is necessary to develop additional prognostic and predictive markers for this disease to allow for patient risk stratification and personalized clinical decision-making. Genomic instability is a prominent characteristic in MM, and we have previously shown that the three-dimensional (3D) nuclear organization of telomeres is a marker of both genomic instability and genetic heterogeneity in myeloma. In this study, we compared in a longitudinal prospective study blindly the 3D telomeric profiles from bone marrow samples of 214 initially treatment-naïve patients with either monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), or MM, with a minimum follow-up of 5 years. Here, we report distinctive 3D telomeric profiles correlating with disease aggressiveness and patient response to treatment in MM patients, and also distinctive 3D telomeric profiles for disease progression in smoldering multiple myeloma patients. In particular, lower average intensity (telomere length, below 13,500 arbitrary units) and increased number of telomere aggregates are associated with shorter survival and could be used as a prognostic factor to identify high-risk SMM and MM patients.

scholarly journals Quantifying the Impact of Patient-Specific Factors and Disease Severity on Clinical Decision Making in Cuff Tear Arthropathy: A Case-Based Survey

2019 ◽  
Vol 15 (3) ◽  
pp. 276-285
Author(s):  
Adam P. Schumaier ◽  
Yehia H. Bedeir ◽  
Joshua S. Dines ◽  
Keith Kenter ◽  
Lawrence V. Gulotta ◽  
...  
Keyword(s):  
Decision Making ◽  
Disease Severity ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Patient Specific ◽  
Cuff Tear Arthropathy ◽  
Cuff Tear ◽  
Specific Factors ◽  
The Impact ◽  
Case Based

Complementing sparse vascular imaging data by physiological adaptation rules

2020 ◽  
Author(s):  
Maarten H.G. Heusinkveld ◽  
Robert J. Holtackers ◽  
Bouke P. Adriaans ◽  
Jos Op't Roodt ◽  
Theo Arts ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Mechanical Load ◽  
Wall Stress ◽  
Clinical Decision ◽  
Physiological Adaptation ◽  
Patient Specific ◽  
Data Sets ◽  
Imaging Data ◽  
Artery Segment ◽  
Flow Waveforms

Introduction:Mathematical modeling of pressure and flow waveforms in blood vessels using pulse wave propagation (PWP)-models has tremendous potential to support clinical decision-making. For a personalized model outcome, measurements of all modeled vessel radii and wall thicknesses are required. In clinical practice, however, data sets are often incomplete. To overcome this problem, we hypothesized that the adaptive capacity of vessels in response to mechanical load could be utilized to fill in the gaps of incomplete patient-specific data sets. Methods:We implemented homeostatic feedback loops in a validated PWP model to allow adaptation of vessel geometry to maintain physiological values of wall stress and wall shear stress. To evaluate our approach, we gathered vascular MRI and ultrasound data sets of wall thicknesses and radii of central and arm arterial segments of ten healthy subjects. Reference models (i.e. termed RefModel, n=10) were simulated using complete data, whereas adapted models (AdaptModel, n=10) used data of one carotid artery segment only while the remaining geometries in this model were estimated using adaptation. We evaluated agreement between RefModel and AdaptModel geometries, as well as between pressure and flow waveforms of both models. Results:Limits of agreement (bias±2SD of difference) between AdaptModel and RefModel radii and wall thicknesses were 0.2±2.6 mm and -140±557 μm, respectively. Pressure and flow waveform characteristics of the AdaptModel better resembled those of the RefModels as compared to the model in which the vessels were not adapted.Conclusions:Our adaptation-based PWP-model enables personalization of vascular geometries even when not all required data is available.

Combination chemotherapy versus temozolomide (TMZ) for patients with MGMT methylated (m-MGMT) glioblastoma (GBM): Results of cellworks omics biosimulation—MyCare-015.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14501-e14501
Author(s):  
Michael Castro ◽  
Nirjhar Mundkur ◽  
Anusha Pampana ◽  
Aftab Alam ◽  
Aktar Alam ◽  
...  
Keyword(s):  
Combination Therapy ◽  
Clinical Decision Making ◽  
Drug Effects ◽  
Standard Of Care ◽  
Clinical Decision ◽  
Phase Iii ◽  
Patient Specific ◽  
Experimental Therapy ◽  
Newly Diagnosed ◽  
Current Standard

e14501 Background: UKT-03 evaluated TMZ plus Lomustine in a single arm phase II trial in newly diagnosed GBM patients. An overall survival of 23 months was a substantial improvement over historical experience. Patients with m-MGMT v. unmethylated tumors had a 2-yr survival of 75% and median survival not reached compared to 20% and 12.5 months, respectively. These data formed the basis for NOA-9, a randomized phase III trial in newly diagnosed, m-MGMT GBM which randomized 141 patients to standard therapy or experimental therapy with Lomustine and TMZ every 6 weeks. A superiority for the combination was observed: 48.1 v. 31.4 months for the standard arm in the ITT analysis. Nevertheless, many neurooncologists are reluctant to adopt this approach. The current standard of care uses single biomarker, m-MGMT, in contrast to comprehensive pathway analysis (CPA). We sought to determine if CPA could discriminate more effectively among each patient’s likelihood of benefiting from combination treatment. Methods: Cellworks Singula employs a novel Cellworks Omics Biology Model (CBM) to predict patient-specific biomarker and phenotype response of personalized GBM avatars to drug agents, radiation, and targeted therapies. The CBM was developed and validated using PubMed to generate protein network maps of patient-specific activated and inactivated disease pathways. CBM was used to simulate the TMZ and TMZ-Lomustine therapies for each patient in a TCGA cohort of 368 GBM patients. Omics data including methylation, whole exome sequencing, and copy number alterations were input into CBM. The Singula Composite Inhibition Score (CIS) was calculated based on the measured quantitative drug effects. Results: Though incremental gain from the combination was seen in all patients, CIS varied across the population with relative scores ranging from 32-82, with best responders have more than twice the benefit. Conclusions: CPA shows that m-MGMT is an excellent biomarker for determining the likelihood of benefit from TMZ and lomustine, with the caveat that CBM identifies 18% could be spared from TMZ exposure and would benefit from Lomustine alone. Otherwise, these data lend support for evolving the standard of care with combination therapy for patients with m-MGMT GBM and should help overcome a reluctance to employing combination therapy. Additionally, CBM has utility to individualize clinical decision making. [Table: see text]

scholarly journals Three-dimensional left ventricular segmentation from magnetic resonance imaging for patient-specific modelling purposes

EP Europace ◽  
2014 ◽  
Vol 16 (suppl 4) ◽  
pp. iv96-iv101 ◽  
Author(s):  
E. G. Caiani ◽  
A. Colombo ◽  
M. Pepi ◽  
C. Piazzese ◽  
F. Maffessanti ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Three Dimensional ◽  
Left Ventricular ◽  
Patient Specific ◽  
Resonance Imaging

scholarly journals Echocardiographic evaluation of normal adult left Ventricular geometry in a Nigerian population

2020 ◽  
Author(s):  
Daniel Chimuanya Ugwuanyi ◽  
Joseph Chukwuemeka Eze ◽  
Hyacienth Uche Chiegwu ◽  
Charles Ugwoke Eze ◽  
Chukwudi Thaddeus Nwagbara
Keyword(s):  
Clinical Decision Making ◽  
Interventricular Septum ◽  
Clinical Decision ◽  
Left Ventricular ◽  
Normal Adult ◽  
Left Ventricular Geometry ◽  
Ventricular Geometry ◽  
Probe Frequency ◽  
And Gender ◽  
Definition Of

AbstractBackgroundDifferences have shown to exist in some echocardiographic measurements that were attributed to racial, ethnic and gender. This study determined echocardiographic baseline data of normal adult left ventricular (LV) geometry in our locality.MethodsThe study was performed on 1,192 apparently healthy adults. Participants below the age of 18 years or those with congenital or acquired cardiac abnormalities and history of long-term regular physical training were excluded. Trans-thoracic echocardiography was performed with Vivid T8 GE dedicated echocardiography machine with probe frequency of 1.7 to 3.2 MHz with integrated electrocardiography (ECG) recording electrodes. The study determined normal dimensions of interventricular diamensions. All measurements were indexed to body surface area (BSA) to obtain echocardiographic baseline normal reference values.ResultsThe mean + SD values of LV parameters for male and female participants were: LVIDd (44.80 ± 5.71 mm vs 42.75 ± 5.21 mm), LVIDs (33.54 ± 5.37 mm vs 30.38 ± 4.81 mm), and LVPWd (8.32 ± 1.26 mm vs 7.51 ± 1.22 mm). Females had more statistically significant interventricular septum in diastole (IVSd) (8.20 ± 1.38 mm vs 7.05 ± 1.27 mm) and interventricular septum in systole (IVSs) (9.08 ± 1.42 mm vs 8.99 ± 1.33 mm) (P < 0.05).ConclusionThis research established echocardiographic baseline normal adult left ventricular geometry in the study population because in order to detect abnormalities, accurate definition of normal values of echocardiographic measurements is of utmost importance for a reliable clinical decision making.

scholarly journals SGPNet: A Three-Dimensional Multitask Residual Framework for Segmentation and IDH Genotype Prediction of Gliomas

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yao Wang ◽  
Yan Wang ◽  
Chunjie Guo ◽  
Shuangquan Zhang ◽  
Lili Yang
Keyword(s):  
Brain Tumor ◽  
Clinical Decision Making ◽  
Three Dimensional ◽  
Clinical Decision ◽  
Error Rates ◽  
The Cancer Genome Atlas ◽  
Classification Error ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
The Status

Glioma is the main type of malignant brain tumor in adults, and the status of isocitrate dehydrogenase (IDH) mutation highly affects the diagnosis, treatment, and prognosis of gliomas. Radiographic medical imaging provides a noninvasive platform for sampling both inter and intralesion heterogeneity of gliomas, and previous research has shown that the IDH genotype can be predicted from the fusion of multimodality radiology images. The features of medical images and IDH genotype are vital for medical treatment; however, it still lacks a multitask framework for the segmentation of the lesion areas of gliomas and the prediction of IDH genotype. In this paper, we propose a novel three-dimensional (3D) multitask deep learning model for segmentation and genotype prediction (SGPNet). The residual units are also introduced into the SGPNet that allows the output blocks to extract hierarchical features for different tasks and facilitate the information propagation. Our model reduces 26.6% classification error rates comparing with previous models on the datasets of Multimodal Brain Tumor Segmentation Challenge (BRATS) 2020 and The Cancer Genome Atlas (TCGA) gliomas’ databases. Furthermore, we first practically investigate the influence of lesion areas on the performance of IDH genotype prediction by setting different groups of learning targets. The experimental results indicate that the information of lesion areas is more important for the IDH genotype prediction. Our framework is effective and generalizable, which can serve as a highly automated tool to be applied in clinical decision making.

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