The Evolution of Computational Hemodynamics as a Clinical Tool in Decision Making, Patient Specific Treatment and Clinical Management

Abstract Current computational tools for planning and simulation in plastic and reconstructive surgery lack sufficient precision and are time-consuming, thus resulting in limited adoption. Although computer-assisted surgical planning systems help to improve clinical outcomes, shorten operation time and reduce cost, they are often too complex and require extensive manual input, which ultimately limits their use in doctor-patient communication and clinical decision making. Here, we present the first large-scale clinical 3D morphable model, a machine-learning-based framework involving supervised learning for diagnostics, risk stratification, and treatment simulation. The model, trained and validated with 4,261 faces of healthy volunteers and orthognathic (jaw) surgery patients, diagnoses patients with 95.5% sensitivity and 95.2% specificity, and simulates surgical outcomes with a mean accuracy of 1.1 ± 0.3 mm. We demonstrate how this model could fully-automatically aid diagnosis and provide patient-specific treatment plans from a 3D scan alone, to help efficient clinical decision making and improve clinical understanding of face shape as a marker for primary and secondary surgery.

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Making Patient-Specific Treatment Decisions Using Prognostic Variables and Utilities of Clinical Outcomes

Cancers ◽

10.3390/cancers13112741 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2741

Author(s):

Pavlos Msaouel ◽

Juhee Lee ◽

Peter F. Thall

Keyword(s):

Decision Making ◽

Clinical Outcomes ◽

Specific Treatment ◽

Patient Specific ◽

Prognostic Information ◽

Cell Renal Cell Carcinoma ◽

Trade Offs ◽

Patient Heterogeneity ◽

Informed Patient

We argue that well-informed patient-specific decision-making may be carried out as three consecutive tasks: (1) estimating key parameters of a statistical model, (2) using prognostic information to convert these parameters into clinically interpretable values, and (3) specifying joint utility functions to quantify risk–benefit trade-offs between clinical outcomes. Using the management of metastatic clear cell renal cell carcinoma as our motivating example, we explain the role of prognostic covariates that characterize between-patient heterogeneity in clinical outcomes. We show that explicitly specifying the joint utility of clinical outcomes provides a coherent basis for patient-specific decision-making.

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Ranking and Selection with Covariates for Personalized Decision Making

INFORMS Journal on Computing ◽

10.1287/ijoc.2020.1009 ◽

2021 ◽

Author(s):

Haihui Shen ◽

L. Jeff Hong ◽

Xiaowei Zhang

Keyword(s):

Decision Making ◽

Treatment Regimen ◽

Personal Information ◽

Specific Treatment ◽

Ranking And Selection ◽

Correct Selection ◽

Patient Specific ◽

Life Years ◽

Average Probability ◽

Favorable Configuration

We consider a problem of ranking and selection via simulation in the context of personalized decision making, in which the best alternative is not universal, but varies as a function of some observable covariates. The goal of ranking and selection with covariates (R&S-C) is to use simulation samples to obtain a selection policy that specifies the best alternative with a certain statistical guarantee for subsequent individuals upon observing their covariates. A linear model is proposed to capture the relationship between the mean performance of an alternative and the covariates. Under the indifference-zone formulation, we develop two-stage procedures for both homoscedastic and heteroscedastic simulation errors, respectively, and prove their statistical validity in terms of average probability of correct selection. We also generalize the well-known slippage configuration and prove that the generalized slippage configuration is the least favorable configuration for our procedures. Extensive numerical experiments are conducted to investigate the performance of the proposed procedures, the experimental design issue, and the robustness to the linearity assumption. Finally, we demonstrate the usefulness of R&S-C via a case study of selecting the best treatment regimen in the prevention of esophageal cancer. We find that by leveraging disease-related personal information, R&S-C can substantially improve patients’ expected quality-adjusted life years by providing a patient-specific treatment regimen.

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Patient-specific treatment allocation for carotid artery disease

Interventional Cardiology ◽

10.2217/ica.09.8 ◽

2009 ◽

Vol 1 (1) ◽

pp. 41-49

Author(s):

Marc Bosiers ◽

Koen Deloose ◽

Jurgen Verbist ◽

Patrick Peeters

Keyword(s):

Carotid Artery ◽

Carotid Artery Disease ◽

Specific Treatment ◽

Patient Specific ◽

Treatment Allocation ◽

Artery Disease

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

Scientific Reports ◽

10.1038/s41598-021-95315-w ◽

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.

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Communication in decision aids for stage I–III colorectal cancer patients: a systematic review

BMJ Open ◽

10.1136/bmjopen-2020-044472 ◽

2021 ◽

Vol 11 (4) ◽

pp. e044472

Author(s):

Saar Hommes ◽

Ruben Vromans ◽

Felix Clouth ◽

Xander Verbeek ◽

Ignace de Hingh ◽

...

Keyword(s):

Colorectal Cancer ◽

Systematic Review ◽

Decision Making ◽

Systematic Reviews ◽

Decision Aids ◽

Specific Treatment ◽

Cochrane Library ◽

Plain Language ◽

Patient Decision

ObjectivesTo assess the communicative quality of colorectal cancer patient decision aids (DAs) about treatment options, the current systematic review was conducted.DesignSystematic review.Data sourcesDAs (published between 2006 and 2019) were identified through academic literature (MEDLINE, Embase, CINAHL, Cochrane Library and PsycINFO) and online sources.Eligibility criteriaDAs were only included if they supported the decision-making process of patients with colon, rectal or colorectal cancer in stages I–III.Data extraction and synthesisAfter the search strategy was adapted from similar systematic reviews and checked by a colorectal cancer surgeon, two independent reviewers screened and selected the articles. After initial screening, disagreements were resolved with a third reviewer. The review was conducted in concordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. DAs were assessed using the International Patient Decision Aid Standards (IPDAS) and Communicative Aspects (CA) checklist.ResultsIn total, 18 DAs were selected. Both the IPDAS and CA checklist revealed that there was a lot of variation in the (communicative) quality of DAs. The findings highlight that (1) personalisation of treatment information in DAs is lacking, (2) outcome probability information is mostly communicated verbally and (3) information in DAs is generally biased towards a specific treatment. Additionally, (4) DAs about colorectal cancer are lengthy and (5) many DAs are not written in plain language.ConclusionsBoth instruments (IPDAS and CA) revealed great variation in the (communicative) quality of colorectal cancer DAs. Developers of patient DAs should focus on personalisation techniques and could use both the IPDAS and CA checklist in the developmental process to ensure personalised health communication and facilitate shared decision making in clinical practice.

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Clinical Management of Hypertension, Inflammation and Thrombosis in Hospitalized COVID-19 Patients: Impact on Survival and Concerns

Journal of Clinical Medicine ◽

10.3390/jcm10051073 ◽

2021 ◽

Vol 10 (5) ◽

pp. 1073

Author(s):

Patricia Martínez-Botía ◽

Ángel Bernardo ◽

Andrea Acebes-Huerta ◽

Alberto Caro ◽

Blanca Leoz ◽

...

Keyword(s):

Arterial Hypertension ◽

Clinical Management ◽

Cox Regression ◽

Angiotensin Receptor Blockers ◽

Treatment Options ◽

Clinical Manifestations ◽

Specific Treatment ◽

Hospitalized Patients ◽

Thrombosis Prophylaxis ◽

The Impact

The most severe clinical manifestations of the Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), are due to an unbalanced immune response and a pro-thrombotic hemostatic disturbance, with arterial hypertension or diabetes as acknowledged risk factors. While waiting for a specific treatment, the clinical management of hospitalized patients is still a matter of debate, and the effectiveness of treatments to manage clinical manifestations and comorbidities has been questioned. In this study, we aim to assess the impact of the clinical management of arterial hypertension, inflammation and thrombosis on the survival of COVID-19 patients. The Spanish cohorts included in this observational retrospective study are from HM Hospitales (2035 patients) and from Hospital Universitario Central de Asturias (72 patients). Kaplan Meier survival curves, Cox regression and propensity score matching analyses were employed, considering demographic variables, comorbidities and treatment arms (when opportune) as covariates. The management of arterial hypertension with angiotensin-converting enzyme 2 (ACE2) inhibitors or angiotensin receptor blockers is not detrimental, as was initially reported, and neither was the use of non-steroidal anti-inflammatory drugs (NSAIDs). On the contrary, our analysis shows that the use on itself of corticosteroids is not beneficial. Importantly, the management of COVID-19 patients with low molecular weight heparin (LMWH) as an anticoagulant significantly improves the survival of hospitalized patients. These results delineate the current treatment options under debate, supporting the effectiveness of thrombosis prophylaxis on COVID-19 patients as a first-line treatment without the need for compromising the treatment of comorbidities, while suggesting cautiousness when administering corticosteroids.

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Developing an Evidence-Based Clinical Decision-Support System to Enhance Prosthetic Prescription

Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care ◽

10.1177/2327857921101116 ◽

2021 ◽

Vol 10 (1) ◽

pp. 121-125

Author(s):

Pratima Saravanan ◽

Jessica Menold

Keyword(s):

Decision Making ◽

Decision Support ◽

Decision Support System ◽

Gait Analysis ◽

Support System ◽

Patient Specific ◽

Evidence Based ◽

Extensive Literature ◽

Analysis Tool ◽

Care Providers

With the rapid increase in the global amputee population, there is a clear need to assist amputee care providers with their decision-making during the prosthetic prescription process. To achieve this, an evidence-based decision support system that encompasses existing literature, current decision-making strategies employed by amputee care providers and patient-specific factors is proposed. Based on an extensive literature review combined with natural language processing and expert survey, the factors influencing the current decision-making of amputee care providers in prosthetic prescription were identified. Following that, the decision-making strategies employed by expert and novice prosthetists were captured and analyzed. Finally, a fundamental understanding of the effect gait analysis has on the decision-making strategies of prosthetists was studied. Findings from this work lay the foundation for developing a real-time decision support system integrated with a portable gait analysis tool to enhance prescription processes. This is critical in the low-income countries where there is a scarcity of amputee care providers and resources for an appropriate prescription.

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Mathematical analysis of the influence of brain metabolism on the BOLD signal in Alzheimer’s disease

Journal of Cerebral Blood Flow & Metabolism ◽

10.1177/0271678x17693024 ◽

2017 ◽

Vol 38 (2) ◽

pp. 304-316 ◽

Cited By ~ 6

Author(s):

Felix Winter ◽

Catrin Bludszuweit-Philipp ◽

Olaf Wolkenhauer

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Resting State Fmri ◽

Blood Oxygen Level Dependent ◽

Peak Height ◽

Brain Dysfunction ◽

Patient Specific ◽

Theoretic Approach ◽

Hemodynamic Response Function ◽

Clinical Tool

Blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) is a standard clinical tool for the detection of brain activation. In Alzheimer’s disease (AD), task-related and resting state fMRI have been used to detect brain dysfunction. It has been shown that the shape of the BOLD response is affected in early AD. To correctly interpret these changes, the mechanisms responsible for the observed behaviour need to be known. The parameters of the canonical hemodynamic response function (HRF) commonly used in the analysis of fMRI data have no direct biological interpretation and cannot be used to answer this question. We here present a model that allows relating AD-specific changes in the BOLD shape to changes in the underlying energy metabolism. According to our findings, the classic view that differences in the BOLD shape are only attributed to changes in strength and duration of the stimulus does not hold. Instead, peak height, peak timing and full width at half maximum are sensitive to changes in the reaction rate of several metabolic reactions. Our systems-theoretic approach allows the use of patient-specific clinical data to predict dementia-driven changes in the HRF, which can be used to improve the results of fMRI analyses in AD patients.

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