Evidence map›Paper›PMID 38705940›Full record

ArticleEuropean radiology experimental2024

Reproducibility of a semiautomatic lobar lung tissue assignment technique on noncontrast CT scans: a study on swine animal model.

Nile Luu, Nathan Van, Alireza Shojazadeh, Yixiao Zhao, Sabee Molloi

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Article in European radiology experimental, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Nile LuuDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Nathan VanDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Alireza ShojazadehDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Yixiao ZhaoDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Sabee MolloiDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA. symolloi@uci.edu.ORCID http://orcid.org/0000-0003-1852-4913

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6 · The paper itself

Abstract

backgroundTo evaluate the reproducibility of a vessel-specific minimum cost path (MCP) technique used for lobar segmentation on noncontrast computed tomography (CT).

methodsSixteen Yorkshire swine (49.9 ± 4.7 kg, mean ± standard deviation) underwent a total of 46 noncontrast helical CT scans from November 2020 to May 2022 using a 320-slice scanner. A semiautomatic algorithm was employed by three readers to segment the lung tissue and pulmonary arterial tree. The centerline of the arterial tree was extracted and partitioned into six subtrees for lobar assignment. The MCP technique was implemented to assign lobar territories by assigning lung tissue voxels to the nearest arterial tree segment. MCP-derived lobar mass and volume were then compared between two acquisitions, using linear regression, root mean square error (RMSE), and paired sample t-tests. An interobserver and intraobserver analysis of the lobar measurements was also performed.

resultsThe average whole lung mass and volume was 663.7 ± 103.7 g and 1,444.22 ± 309.1 mL, respectively. The lobar mass measurements from the initial (MLobe1) and subsequent (MLobe2) acquisitions were correlated by MLobe1 = 0.99 MLobe2 + 1.76 (r = 0.99, p = 0.120, RMSE = 7.99 g). The lobar volume measurements from the initial (VLobe1) and subsequent (VLobe2) acquisitions were correlated by VLobe1 = 0.98VLobe2 + 2.66 (r = 0.99, p = 0.160, RSME = 15.26 mL).

conclusionsThe lobar mass and volume measurements showed excellent reproducibility through a vessel-specific assignment technique. This technique may serve for automated lung lobar segmentation, facilitating clinical regional pulmonary analysis. RELEVANCE STATEMENT: Assessment of lobar mass or volume in the lung lobes using noncontrast CT may allow for efficient region-specific treatment strategies for diseases such as pulmonary embolism and chronic thromboembolic pulmonary hypertension. KEY POINTS: • Lobar segmentation is essential for precise disease assessment and treatment planning. • Current methods for segmentation using fissure lines are problematic. • The minimum-cost-path technique here is proposed and a swine model showed excellent reproducibility for lobar mass measurements. • Interobserver agreement was excellent, with intraclass correlation coefficients greater than 0.90.

Indexed as

LungAlgorithmsAnimalsModels, AnimalReproducibility of ResultsSwineTomography, X-Ray ComputedAnimalsLungObserver variationSwineTomography (x-ray computed)

Identifiers

PMID38705940
PMCPMC11070405

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