Evidence map›Paper›PMID 38738252›Full record

ReviewJournal of thoracic disease2024

Blood flow assessment technology in aortic surgery: a narrative review.

Yu Hohri, Megan M Chung, Viswajit Kandula, Ilya Kim, Jay Leb, Hideyuki Hayashi, Adham Elmously, Thomas Fx O'Donnell, Virendra Patel, Vijay Vedula and 1 more

Abstract readReview
In one paragraph

Review in Journal of thoracic disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

11 authors.

Yu HohriDivision of Cardiothoracic Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Megan M ChungDivision of Cardiothoracic Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Viswajit KandulaDivision of Cardiothoracic Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Ilya KimDepartment of Medicine, New York-Presbyterian Hospital, Weill Cornell Medical Center, New York, NY, USA.
Jay LebDepartment of Radiology, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Hideyuki HayashiDivision of Cardiothoracic Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Adham ElmouslyDivision of Cardiothoracic Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Thomas Fx O'DonnellDivision of Vascular Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Virendra PatelDivision of Vascular Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.
Vijay VedulaDepartment of Mechanical Engineering, Columbia University in the City of New York, New York, NY, USA.
Hiroo TakayamaDivision of Cardiothoracic Surgery, Department of Surgery, New York-Presbyterian Hospital, Columbia University Medical Center, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: Blood flow assessment is an emerging technique that allows for assessment of hemodynamics in the heart and blood vessels. Recent advances in cardiovascular imaging technologies have made it possible for this technique to be more accessible to clinicians and researchers. Blood flow assessment typically refers to two techniques: measurement-based flow visualization using echocardiography or four-dimensional flow magnetic resonance imaging (4D flow MRI), and computer-based flow simulation based on computational fluid dynamics modeling. Using these methods, blood flow patterns can be visualized and quantitative measurements of mechanical stress on the walls of the ventricles and blood vessels, most notably the aorta, can be made. Thus, blood flow assessment has been enhancing the understanding of cardiac and aortic diseases; however, its introduction to clinical practice has been negligible yet. In this article, we aim to discuss the clinical applications and future directions of blood flow assessment in aortic surgery. We then provide our unique perspective on the technique's translational impact on the surgical management of aortic disease. Methods: Articles from the PubMed database and Google Scholar regarding blood flow assessment in aortic surgery were reviewed. For the initial search, articles published between 2013 and 2023 were prioritized, including original articles, clinical trials, case reports, and reviews. Following the initial search, additional articles were considered based on manual searches of the references from the retrieved literature. Key Content and Findings: In aortic root pathology and ascending aortic aneurysms, blood flow assessment can elucidate postoperative hemodynamic changes after surgical reconfiguration of the aortic valve complex or ascending aorta. In cases of aortic dissection, analysis of blood flow can predict future aortic dilatation. For complicated congenital aortic anomalies, surgeons may use preoperative imaging to perform "virtual surgery", in which blood flow assessment can predict postoperative hemodynamics for different surgical reconstructions and assist in procedural planning even before entering the operating room. Conclusions: Blood flow assessment and computational modeling can evaluate hemodynamics and flow patterns by visualizing blood flow and calculating biomechanical forces in patients with aortic disease. We anticipate that blood flow assessment will become an essential tool in the treatment planning and understanding of the progression of aortic disease.

Indexed as

aortic surgeryBlood flow assessmentcomputational fluid dynamics (CFDs)four-dimensional flow magnetic resonance imaging (4D flow MRI)vector flow mapping (VFM)

Identifiers

PMID38738252
PMCPMC11087597

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.