TY - JOUR
T1 - Methods to Measure the Broncho-Arterial Ratio and Wall Thickness in the Right Lower Lobe for Defining Radiographic Reversibility of Bronchiectasis
AU - Beeravolu, Abhijith R.
AU - Masters, Ian Brent
AU - Jonkman, Mirjam
AU - Yeo, Kheng Cher
AU - Prountzos, Spyridon
AU - Thomas, Rahul J.
AU - Ignatious, Eva
AU - Azam, Sami
AU - McCallum, Gabrielle B.
AU - Alexopoulou, Efthymia
AU - Chang, Anne B.
AU - Boer, Friso De
PY - 2024/10
Y1 - 2024/10
N2 - 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.
AB - 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.
KW - Airway
KW - Artery
KW - Bronchiectasis
KW - Broncho-Arterial Ratio
KW - Pediatrics
KW - Wall Thickness
UR - http://www.scopus.com/inward/record.url?scp=85207350801&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2024.3476436
DO - 10.1109/ACCESS.2024.3476436
M3 - Article
AN - SCOPUS:85207350801
SN - 2169-3536
VL - 12
SP - 152108
EP - 152121
JO - IEEE Access
JF - IEEE Access
ER -