Automatic Quantification of Pulmonary Fissure Integrity: A Repeatability Analysis

The pulmonary fissures divide the lungs into lobes and can vary widely in shape, appearance, and completeness. Fissure completeness, or integrity, has been studied to assess relationships with airway function measurements, chronic obstructive pulmonary disease (COPD) progression, and collateral ventilation between lobes. Fissure integrity measured from computed tomography (CT) images is already used as a non-invasive method to screen emphysema patients for endobronchial valve treatment, as the procedure is not effective when collateral ventilation is present. We describe a method for automatically computing fissure integrity from lung CT images. Our method is tested using 60 subjects from a COPD study. We examine the repeatability of fissure integrity measurements across inspiration and expiration images, assess changes in fissure integrity over time using a longitudinal dataset, and explore fissure integrity's relationship with COPD severity.

[1]  A. Aziz,et al.  High Resolution CT Anatomy of the Pulmonary Fissures , 2004, Journal of thoracic imaging.

[2]  F. Martinez,et al.  Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. , 2007, American journal of respiratory and critical care medicine.

[3]  S Meenakshi,et al.  Morphological variations of the lung fissures and lobes. , 2004, The Indian journal of chest diseases & allied sciences.

[4]  David Couper,et al.  SPIROMICS Protocol for Multicenter Quantitative Computed Tomography to Phenotype the Lungs. , 2016, American journal of respiratory and critical care medicine.

[5]  Gary E. Christensen,et al.  FissureNet: A Deep Learning Approach For Pulmonary Fissure Detection in CT Images , 2019, IEEE Transactions on Medical Imaging.

[6]  Daniela Gompelmann,et al.  Endoscopic bronchial valve treatment: patient selection and special considerations , 2015, International journal of chronic obstructive pulmonary disease.

[7]  David Gur,et al.  Computerized assessment of pulmonary fissure integrity using high resolution CT. , 2010, Medical physics.

[8]  Zuzana Heřmanová,et al.  Incomplete and accessory fissures of the lung evaluated by high-resolution computed tomography. , 2014, European journal of radiology.

[9]  D. Slebos,et al.  The fissure: interlobar collateral ventilation and implications for endoscopic therapy in emphysema , 2016, International journal of chronic obstructive pulmonary disease.

[10]  Joseph M. Reinhardt,et al.  Pulmonary Lobe Segmentation Using A Sequence of Convolutional Neural Networks For Marginal Learning , 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

[11]  Lisa M LaVange,et al.  Design of the Subpopulations and Intermediate Outcomes in COPD Study (SPIROMICS) , 2013, Thorax.

[12]  E. V. van Rikxoort,et al.  Predicting Lung Volume Reduction after Endobronchial Valve Therapy Is Maximized Using a Combination of Diagnostic Tools , 2016, Respiration.

[13]  Jiantao Pu,et al.  Pulmonary Fissure Integrity and Collateral Ventilation in COPD Patients , 2014, PloS one.

[14]  Bincy M. George,et al.  Morphological variations of the lungs: a study conducted on Indian cadavers , 2014, Anatomy & cell biology.

[15]  B. van Ginneken,et al.  Chest , 2009, Indian Journal of Radiology and Imaging.