Evidence map›Paper›PMID 34328596›Full record

ArticleInternational journal of computer assisted radiology and surgery2022

Automatic triangulated mesh generation of pulmonary airways from segmented lung 3DCTs for computational fluid dynamics.

Michael Lauria, Kamal Singhrao, Bradley Stiehl, Daniel Low, Jonathan Goldin, Igor Barjaktarevic, Anand Santhanam

Abstract read
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Article in International journal of computer assisted radiology and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 20% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
4 · The record

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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

7 authors at 1 institution in 1 country.

Michael LauriaUniversity of California, Los Angeles, CA, 90095, USA. mlauria@mednet.ucla.edu.ORCID http://orcid.org/0000-0003-1194-0148
Kamal SinghraoUniversity of California, Los Angeles, CA, 90095, USA.
Bradley StiehlUniversity of California, Los Angeles, CA, 90095, USA.
Daniel LowUniversity of California, Los Angeles, CA, 90095, USA.
Jonathan GoldinUniversity of California, Los Angeles, CA, 90095, USA.
Igor BarjaktarevicUniversity of California, Los Angeles, CA, 90095, USA.
Anand SanthanamUniversity of California, Los Angeles, CA, 90095, USA.
University of California, Los Angeles · US

Funding

Flow Structure Interaction Model for COPDR56HL139767 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SANTHANAM, ANAND PRASAD · 2018 to 2018
$369k
NIH HHS R56 1R56HL139767-01A1Tobacco-Related Disease Research Program 27IR-0056
6 · The paper itself

Abstract

purposeComputational fluid dynamics (CFD) of lung airflow during normal and pathophysiological breathing provides insight into regional pulmonary ventilation. By integrating CFD methods with 4D lung imaging workflows, regions of normal pulmonary function can be spared during treatment planning. To facilitate the use of CFD simulations in a clinical setup, a robust, automated, and CFD-compliant airway mesh generation technique is necessary.

methodsWe define a CFD-compliant airway mesh to be devoid of blockages of airflow and leaks in the airway path, both of which are caused by airway meshing errors that occur when using conventional meshing techniques. We present an algorithm to create a CFD-compliant airway mesh in an automated manner. Beginning with a medial skeleton of the airway segmentation, the branches were tracked, and 3D points at which bifurcations occur were identified. Airway branches and bifurcation features were isolated to allow for automated and careful meshing that considered their anatomical nature.

resultsWe present the meshing results from three state-of-the-art tools and compare them with the meshes generated by our algorithm. The results show that fully CFD-compliant meshes were automatically generated for an ideal geometry and patient-specific CT scans. Using an open-source smoothed-particle hydrodynamics CFD implementation, we compared the airflow using our approach and conventionally generated airway meshes.

conclusionOur meshing algorithm was able to successfully generate a CFD-compliant mesh from pre-segmented lung CT scans, providing an automatic meshing approach that enables interventional CFD simulations to guide lung procedures such as radiotherapy or lung volume reduction surgery.

Indexed as

HydrodynamicsSurgical MeshComputer SimulationHumansLungRespiration3D triangulationComputational fluid dynamicsLung airways

Identifiers

PMID34328596
OpenAlexW3183553418

What OpenQuestion holds

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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.