Validation study of an interpolation method for calculating whole lung volumes and masses from reduced numbers of CT-images in ponies.
Abstract: Quantitative computer tomographic analysis (qCTA) is an accurate but time intensive method used to quantify volume, mass and aeration of the lungs. The aim of this study was to validate a time efficient interpolation technique for application of qCTA in ponies. Forty-one thoracic computer tomographic (CT) scans obtained from eight anaesthetised ponies positioned in dorsal recumbency were included. Total lung volume and mass and their distribution into four compartments (non-aerated, poorly aerated, normally aerated and hyperaerated; defined based on the attenuation in Hounsfield Units) were determined for the entire lung from all 5 mm thick CT-images, 59 (55-66) per animal. An interpolation technique validated for use in humans was then applied to calculate qCTA results for lung volumes and masses from only 10, 12, and 14 selected CT-images per scan. The time required for both procedures was recorded. Results were compared statistically using the Bland-Altman approach. The bias ± 2 SD for total lung volume calculated from interpolation of 10, 12, and 14 CT-images was -1.2 ± 5.8%, 0.1 ± 3.5%, and 0.0 ± 2.5%, respectively. The corresponding results for total lung mass were -1.1 ± 5.9%, 0.0 ± 3.5%, and 0.0 ± 3.0%. The average time for analysis of one thoracic CT-scan using the interpolation method was 1.5-2 h compared to 8 h for analysis of all images of one complete thoracic CT-scan. The calculation of pulmonary qCTA data by interpolation from 12 CT-images was applicable for equine lung CT-scans and reduced the time required for analysis by 75%.
Copyright © 2014 Elsevier Ltd. All rights reserved.
Publication Date: 2014-10-22 PubMed ID: 25458887DOI: 10.1016/j.tvjl.2014.10.019Google Scholar: Lookup
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- Journal Article
- Validation Study
Summary
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The research article discusses the validation of a time-effective interpolation technique for quantitative computer tomographic analysis (qCTA) used in the evaluation of lung volumes and masses in ponies.
Objective and Methodology
- The primary aim of the study was to authenticate a quicker, more efficient interpolation method for handling qCTA in ponies.
- The researchers used forty-one thoracic computer tomographic (CT) scans taken from eight anaesthetised ponies in dorsal recumbency (lying on their back).
- The total lung volume and mass, and their distribution into four compartments, based on the attenuation in Hounsfield Units, were identified for the entire lung from all 5 mm thick CT-images, approximately 59 (55-66) per animal.
Implementation of Interpolation Technique
- An interpolation technique previously validated for use in humans was applied to calculate qCTA results for lung volumes and masses from only 10, 12, and 14 selected CT-images per scan.
- The duration required for both procedures was recorded to ascertain the efficiency of the new method.
Results and Statistical Analysis
- The findings were analysed statistically using the Bland-Altman approach, a statistical method that compares two measurements techniques by plotting the difference against the average.
- The bias ± 2 SD (standard deviation) for total lung volume calculated from interpolation of 10, 12, and 14 CT-images was recorded as -1.2 ± 5.8%, 0.1 ± 3.5%, and 0.0 ± 2.5%, respectively.
- The corresponding results for total lung mass were -1.1 ± 5.9%, 0.0 ± 3.5%, and 0.0 ± 3.0%.
Time Efficiency
- The average time for analysing one thoracic CT-scan using the interpolation method was estimated to be between 1.5-2 h, in comparison to the 8 h required for analysis of all images of one complete thoracic CT-scan.
- Therefore, this interpolation method reduced the time required for analysis by an impressive 75%.
In conclusion, the article presents the implementation and validation of a time-efficient interpolation method for qCTA in ponies that significantly reduced the time required for analysing lung volumes and masses.
Cite This Article
APA
Reich H, Moens Y, Braun C, Kneissl S, Noreikat K, Reske A.
(2014).
Validation study of an interpolation method for calculating whole lung volumes and masses from reduced numbers of CT-images in ponies.
Vet J, 202(3), 603-607.
https://doi.org/10.1016/j.tvjl.2014.10.019 Publication
Researcher Affiliations
- Anaesthesiology and Perioperative Intensive Care Medicine, Department for Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210 Wien, Austria. Electronic address: heidi.reich@vetmeduni.ac.at.
- Anaesthesiology and Perioperative Intensive Care Medicine, Department for Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210 Wien, Austria.
- Anaesthesiology and Perioperative Intensive Care Medicine, Department for Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210 Wien, Austria.
- Diagnostic Imaging, Department for Companion Animals and Horses, University of Veterinary Medicine Vienna, Veterinärplatz 1, 1210 Wien, Austria.
- Department of Anaesthesiology and Intensive Care, University Hospital Leipzig, Liebigstr.20, 04103 Leipzig, Germany.
- Department of Anaesthesiology and Intensive Care, University Hospital Leipzig, Liebigstr.20, 04103 Leipzig, Germany.
MeSH Terms
- Animals
- Horses
- Image Processing, Computer-Assisted / methods
- Lung / diagnostic imaging
- Lung / physiology
- Lung Volume Measurements / veterinary
- Reproducibility of Results
- Tidal Volume
- Tomography, X-Ray Computed / veterinary
Citations
This article has been cited 4 times.- Raidal SL, Catanchin M, Sacks M, Carstens A, Quinn C, Mosing M. Effects of 2 modes of positive pressure ventilation on respiratory mechanics and gas exchange in foals.. J Vet Intern Med 2023 May-Jun;37(3):1233-1242.
- Camara JA, Pujol A, Jimenez JJ, Donate J, Ferrer M, Vande Velde G. Lung Volume Calculation in Preclinical MicroCT: A Fast Geometrical Approach.. J Imaging 2022 Jul 22;8(8).
- Ball L, Vercesi V, Costantino F, Chandrapatham K, Pelosi P. Lung imaging: how to get better look inside the lung.. Ann Transl Med 2017 Jul;5(14):294.
- Ball L, Braune A, Corradi F, Brusasco C, Garlaschi A, Kiss T, Bluth T, Simonassi F, Bergamaschi A, Kotzerke J, Schultz MJ, de Abreu MG, Pelosi P. Ultra-low-dose sequential computed tomography for quantitative lung aeration assessment-a translational study.. Intensive Care Med Exp 2017 Dec;5(1):19.
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