Literature DB >> 33496812

[Radiological features of interstitial lung diseases].

Sabine Dettmer1, Sarah Scharm2, Hoen-Oh Shin2.   

Abstract

In addition to pneumology and pathology, radiology is an essential discipline in the interdisciplinary diagnosis of interstitial lung diseases (ILDs). The gold standard for diagnosis of ILD is computed tomography. Diagnostic findings are based on specific radiological signs such as interlobular septal thickening and nodular changes. From these signs and their distribution within the lung, radiological patterns can be derived, e.g., usual interstitial pneumonia, nonspecific interstitial pneumonia, or organizing pneumonia. Various differential diagnoses result from the radiological pattern, which can then be further limited in an interdisciplinary manner with the clinic and pathology and, if necessary, trigger further diagnostics.The visual assessment of interstitial lung changes requires experience and training and is nevertheless error-prone with high inter- and intraobserver variabilities. Recently, therefore, computer-aided analysis of ILDs has been increasingly promoted. These computer programs analyze the density distribution of the lung parenchyma using parameters such as mean lung density, skewness, and kurtosis thus enabling the quantification and assessment of the course of disease. Furthermore, texture analysis and artificial intelligence are used to characterize parenchymal changes and differentiate between regions of ground glass, reticulation, and honeycombing. Modern dual-energy CT methods allow a combined, regional recording of both the morphology and the function and provide information about regional ventilation and perfusion.

Entities:  

Keywords:  Artificial intelligence; Computed tomography; Computer-aided analysis; Pulmonary fibrosis; Radiology

Year:  2021        PMID: 33496812     DOI: 10.1007/s00292-020-00906-5

Source DB:  PubMed          Journal:  Pathologe        ISSN: 0172-8113            Impact factor:   1.011


  17 in total

1.  Quantitative CT indexes in idiopathic pulmonary fibrosis: relationship with physiologic impairment.

Authors:  Alan C Best; Anne M Lynch; Carmen M Bozic; David Miller; Gary K Grunwald; David A Lynch
Journal:  Radiology       Date:  2003-06-11       Impact factor: 11.105

2.  Fleischner Society: glossary of terms for thoracic imaging.

Authors:  David M Hansell; Alexander A Bankier; Heber MacMahon; Theresa C McLoud; Nestor L Müller; Jacques Remy
Journal:  Radiology       Date:  2008-01-14       Impact factor: 11.105

Review 3.  Is Progression of Pulmonary Fibrosis due to Ventilation-induced Lung Injury?

Authors:  Richard K Albert; Bradford Smith; Carrie E Perlman; David A Schwartz
Journal:  Am J Respir Crit Care Med       Date:  2019-07-15       Impact factor: 21.405

4.  Pulmonary fibrosis: tissue characterization using late-enhanced MRI compared with unenhanced anatomic high-resolution CT.

Authors:  Lisa P Lavelle; Darragh Brady; Sinead McEvoy; David Murphy; Brian Gibney; Annika Gallagher; Marcus Butler; Fionnula Shortt; Marie McMullen; Aurelie Fabre; David A Lynch; Michael P Keane; Jonathan D Dodd
Journal:  Diagn Interv Radiol       Date:  2017 Mar-Apr       Impact factor: 2.630

5.  Alveolar Micromechanics in Bleomycin-induced Lung Injury.

Authors:  Lars Knudsen; Elena Lopez-Rodriguez; Lennart Berndt; Lilian Steffen; Clemens Ruppert; Jason H T Bates; Matthias Ochs; Bradford J Smith
Journal:  Am J Respir Cell Mol Biol       Date:  2018-12       Impact factor: 6.914

6.  Stress distribution in lungs: a model of pulmonary elasticity.

Authors:  J Mead; T Takishima; D Leith
Journal:  J Appl Physiol       Date:  1970-05       Impact factor: 3.531

7.  Idiopathic pulmonary fibrosis: physiologic tests, quantitative CT indexes, and CT visual scores as predictors of mortality.

Authors:  Alan C Best; Jiangfeng Meng; Anne M Lynch; Carmen M Bozic; David Miller; Gary K Grunwald; David A Lynch
Journal:  Radiology       Date:  2008-01-30       Impact factor: 11.105

8.  Automated Quantitative Computed Tomography Versus Visual Computed Tomography Scoring in Idiopathic Pulmonary Fibrosis: Validation Against Pulmonary Function.

Authors:  Joseph Jacob; Brian J Bartholmai; Srinivasan Rajagopalan; Maria Kokosi; Arjun Nair; Ronald Karwoski; Sushravya M Raghunath; Simon L F Walsh; Athol U Wells; David M Hansell
Journal:  J Thorac Imaging       Date:  2016-09       Impact factor: 3.000

9.  Densitometric and local histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis.

Authors:  Samuel Y Ash; Rola Harmouche; Diego Lassala Lopez Vallejo; Julian A Villalba; Kris Ostridge; River Gunville; Carolyn E Come; Jorge Onieva Onieva; James C Ross; Gary M Hunninghake; Souheil Y El-Chemaly; Tracy J Doyle; Pietro Nardelli; Gonzalo V Sanchez-Ferrero; Hilary J Goldberg; Ivan O Rosas; Raul San Jose Estepar; George R Washko
Journal:  Respir Res       Date:  2017-03-07

10.  Classification of Interstitial Lung Abnormality Patterns with an Ensemble of Deep Convolutional Neural Networks.

Authors:  David Bermejo-Peláez; Samuel Y Ash; George R Washko; Raúl San José Estépar; María J Ledesma-Carbayo
Journal:  Sci Rep       Date:  2020-01-15       Impact factor: 4.379

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