Evidence map›Paper›PMID 36911244›Full record

ArticleApplied sciences (Basel, Switzerland)2022

Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications.

Johane H Bracamonte, Sarah K Saunders, John S Wilson, Uyen T Truong, Joao S Soares

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Article in Applied sciences (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. AI-powered in silico twins: redefining precision medicine through simulation, personalization, and predictive healthcare.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Johane H BracamonteDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.ORCID 0000-0002-2359-4361
Sarah K SaundersDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.
John S WilsonDepartment of Biomedical Engineering and Pauley Heart Center, Virginia Commonwealth University, Richmond, VA 23219, USA.ORCID 0000-0001-5406-1261
Uyen T TruongDepartment of Pediatrics, School of Medicine, Children's Hospital of Richmond at Virginia Commonwealth University, Richmond, VA 23219, USA.
Joao S SoaresDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.

Funding

Non-invasive Assessment of Pulmonary Vascular Structure/Function by MRI in Children with Pulmonary Arterial HypertensionK23HL135352 · NHLBI · VIRGINIA COMMONWEALTH UNIVERSITY · PI TRUONG, UYEN T · 2017 to 2021
$849k
NHLBI NIH HHS K23 HL135352
6 · The paper itself

Abstract

Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.

Indexed as

biomechanicscardiovascular imagingdata assimilationhemodynamicsimage-based kinematicsinverse modelspatient-specific modelstissue mechanics

Identifiers

PMID36911244
PMCPMC10004130

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.