ArticleEJNMMI physics2021
Automatic delineation and quantification of pulmonary vascular obstruction index in patients with pulmonary embolism using Perfusion SPECT-CT: a simulation study.
Article in EJNMMI physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Does pulmonary embolism guideline increase the pulmonary vascular obstruction index and help to elucidate the severity of pulmonary embolism?Journal of thoracic disease · 2024Article
- Quantification of the pulmonary vascular obstruction index on ventilation/perfusion lung scintigraphy: Comparison of a segmental visual scoring to the Meyer score.Frontiers in medicine · 2022Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundIn patients with pulmonary embolism (PE), there is a growing interest in quantifying the pulmonary vascular obtruction index (PVOI), which may be an independent risk factor for PE recurrence. Perfusion SPECT/CT is a very attractive tool to provide an accurate quantification of the PVOI. However, there is currently no reliable method to automatically delineate and quantify it. The aim of this phantom study was to assess and compare 3 segmentation methods for PVOI quantification with perfusion SPECT/CT imaging.
methodsThree hundred ninety-six SPECT/CT scans, with various PE scenarios (n = 44), anterior to posterior perfusion gradients (n = 3), and lung volumes (n = 3) were simulated using Simind software. Three segmentation methods were assesssed: (1) using an intensity threshold expressed as a percentage of the maximal voxel value (MaxTh), (2) using a Z-score threshold (ZTh) after building a Z-score parametric lung map, and (3) using a relative difference threshold (RelDiffTh) after building a relative difference parametric map. Ninety randomly selected simulations were used to define the optimal threshold, and 306 simulations were used for the complete analysis. Spacial correlation between PE volumes from the phantom data and the delineated PE volumes was assessed by computing DICE
resultsMean DICE
conclusionIn this phantom study, a delineation method based on a relative difference parametric map provided a good estimation of the PVOI, regardless of the extent of PE, the intensity of the anterior to posterior gradient, and the whole lung volumes.
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