| Autor: |
Abhijith Reddy Beeravolu, Ian Brent Masters, Mirjam Jonkman, Kheng Cher Yeo, Spyridon Prountzos, Rahul J. Thomas, Eva Ignatious, Sami Azam, Gabrielle B. Mccallum, Efthymia Alexopoulou, Anne B. Chang, Friso De Boer |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 12, Pp 152108-152121 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3476436 |
| Popis: |
Bronchiectasis is a chronic respiratory disorder characterized by the dilation and damage of bronchial walls due to recurrent and prolonged episodes of inflammation and infection. The diagnosis of bronchiectasis requires objective measurement of abnormal bronchial dilation. It is confirmed radiologically using a chest tomography (C.T.). scan where the pathognomonic feature is increased broncho-arterial ratio (BAR) (>0.8 in children) and, often accompanied by other features such as bronchial wall thickening (W.T.). Developing image processing-based methods facilitates quicker interpretation of the scans and enable detailed evaluations according to the lobes and segments. However, challenges, such as inclined and oblique orientations of structures, and partial volume effect, can complicate accurate measurements in the upper and middle lobes using the same algorithms. Therefore, the accurate detection and measurement of airway and artery regions for BAR and wall thickness in each lobe require specialized image processing/machine learning methods and approaches. Here, we adopt a step-by-step approach and propose methods for three steps: 1. Separating right lower lobe (RLL) region from full-length C.T. scans using tracheal bifurcation (Carina) point as a central marker; 2. Updated technique to locate inner diameter of airways and outer diameter of arteries for BAR measurement; and 3. Measuring airway wall thickness (W.T.) by identifying the outer and inner diameter of airway boundaries (perimeter). Our analysis of 13 high resolution C.T. scans (HRCT) with varying thicknesses (0.67mm, 1mm, 2mm) demonstrates that the frame containing the tracheal bifurcation can be detected accurately in most cases, with a deviation of ±2 frames in some cases. Similarly, a Windows app is developed for measuring inner airway diameter, artery diameter, BAR, and wall thickness, allowing users to draw bounding around visible discrete B.A. pairs in the RLL region. Measurements of 10 B.A. pairs revealed accurate results comparable to those of a human reader, with deviations of ±0.10-0.15mm observed across all measurements. Additional studies and validation are necessary to consolidate inter- and intra-rater variability and enhance the proposed methods. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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