Literature DB >> 32494778

A CT Scan Harmonization Technique to Detect Emphysema and Small Airway Diseases.

Gonzalo Vegas-Sánchez-Ferrero1, Raúl San Estépar José1.   

Abstract

Recent studies have suggested the central role of small airway destruction in the pathogenesis of COPD leading to further parenchymal destruction. This evidence has sparked the interest in in-vivo assessment of small airway disease overall at the early onset of the disease. The parametric response mapping (PRM) technique has been proposed to distinguish gas trapping due to small airway disease from low attenuation areas due to emphysema. Despite its success, the PRM technique shows some limitations that are precluding the interpretation of its results. The density value used to assess gas trapping highly depends on acquisition parameters, such as dose and reconstruction kernel, and changes in body size, that introduce inhomogeneous photon absorption patterns. In particular, many studies using PRM employ inspiratory and expiratory images that are obtained at different dose levels. Emphysema impact in early disease may be confounded with the gas trapping due to the noise introduced by differences in the acquisition during the PRM. In this work, we propose a CT harmonization technique to remove the nuisance factors to distinguish between small airway disease and emphysema. Our results show that the measurements based on CT harmonization provide an increase in the detection of both emphysema and airway disease, resulting in a statistically significant impact of both components and a better association with lung function measures.

Entities:  

Keywords:  CT scans; Emphysema; Lung disease; Statistical characterization

Year:  2018        PMID: 32494778      PMCID: PMC7269187          DOI: 10.1007/978-3-030-00946-5_19

Source DB:  PubMed          Journal:  Image Anal Mov Organ Breast Thorac Images (2018)


  17 in total

1.  Improved correlation between CT emphysema quantification and pulmonary function test by density correction of volumetric CT data based on air and aortic density.

Authors:  Song Soo Kim; Joon Beom Seo; Namkug Kim; Eun Jin Chae; Young Kyung Lee; Yeon Mok Oh; Sang Do Lee
Journal:  Eur J Radiol       Date:  2012-05-20       Impact factor: 3.528

2.  Adaptive nonlocal means filtering based on local noise level for CT denoising.

Authors:  Zhoubo Li; Lifeng Yu; Joshua D Trzasko; David S Lake; Daniel J Blezek; Joel G Fletcher; Cynthia H McCollough; Armando Manduca
Journal:  Med Phys       Date:  2014-01       Impact factor: 4.071

3.  Standardizing CT lung density measure across scanner manufacturers.

Authors:  Huaiyu Heather Chen-Mayer; Matthew K Fuld; Bernice Hoppel; Philip F Judy; Jered P Sieren; Junfeng Guo; David A Lynch; Antonio Possolo; Sean B Fain
Journal:  Med Phys       Date:  2017-02-21       Impact factor: 4.071

4.  Denoising of polychromatic CT images based on their own noise properties.

Authors:  Ji Hye Kim; Yongjin Chang; Jong Beom Ra
Journal:  Med Phys       Date:  2016-05       Impact factor: 4.071

5.  A concordance correlation coefficient to evaluate reproducibility.

Authors:  L I Lin
Journal:  Biometrics       Date:  1989-03       Impact factor: 2.571

6.  Quantitative assessment of air trapping in chronic obstructive pulmonary disease using inspiratory and expiratory volumetric MDCT.

Authors:  Shin Matsuoka; Yasuyuki Kurihara; Kunihiro Yagihashi; Makoto Hoshino; Naoto Watanabe; Yasuo Nakajima
Journal:  AJR Am J Roentgenol       Date:  2008-03       Impact factor: 3.959

7.  "Density mask". An objective method to quantitate emphysema using computed tomography.

Authors:  N L Müller; C A Staples; R R Miller; R T Abboud
Journal:  Chest       Date:  1988-10       Impact factor: 9.410

8.  Autocalibration method for non-stationary CT bias correction.

Authors:  Gonzalo Vegas-Sánchez-Ferrero; Maria J Ledesma-Carbayo; George R Washko; Raúl San José Estépar
Journal:  Med Image Anal       Date:  2017-12-08       Impact factor: 8.545

9.  The nature of small-airway obstruction in chronic obstructive pulmonary disease.

Authors:  James C Hogg; Fanny Chu; Soraya Utokaparch; Ryan Woods; W Mark Elliott; Liliana Buzatu; Ruben M Cherniack; Robert M Rogers; Frank C Sciurba; Harvey O Coxson; Peter D Paré
Journal:  N Engl J Med       Date:  2004-06-24       Impact factor: 91.245

10.  Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression.

Authors:  Craig J Galbán; Meilan K Han; Jennifer L Boes; Komal A Chughtai; Charles R Meyer; Timothy D Johnson; Stefanie Galbán; Alnawaz Rehemtulla; Ella A Kazerooni; Fernando J Martinez; Brian D Ross
Journal:  Nat Med       Date:  2012-10-07       Impact factor: 53.440

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