Literature DB >> 28493789

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.

Stephen M Humphries1, Kunihiro Yagihashi1, Jason Huckleberry1, Byung-Hak Rho1, Joyce D Schroeder1, Matthew Strand1, Marvin I Schwarz1, Kevin R Flaherty1, Ella A Kazerooni1, Edwin J R van Beek1, David A Lynch1.   

Abstract

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ2 tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.

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Year:  2017        PMID: 28493789      PMCID: PMC5621716          DOI: 10.1148/radiol.2017161177

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  26 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.  High-resolution computed tomography in idiopathic pulmonary fibrosis: diagnosis and prognosis.

Authors:  David A Lynch; J David Godwin; Sharon Safrin; Karen M Starko; Phil Hormel; Kevin K Brown; Ganesh Raghu; Talmadge E King; Williamson Z Bradford; David A Schwartz; W Richard Webb
Journal:  Am J Respir Crit Care Med       Date:  2005-05-13       Impact factor: 21.405

3.  A controlled trial of sildenafil in advanced idiopathic pulmonary fibrosis.

Authors:  David A Zisman; Marvin Schwarz; Kevin J Anstrom; Harold R Collard; Kevin R Flaherty; Gary W Hunninghake
Journal:  N Engl J Med       Date:  2010-05-18       Impact factor: 91.245

4.  A computer-aided diagnosis system for quantitative scoring of extent of lung fibrosis in scleroderma patients.

Authors:  H G Kim; D P Tashkin; P J Clements; G Li; M S Brown; R Elashoff; D W Gjertson; F Abtin; D A Lynch; D C Strollo; J G Goldin
Journal:  Clin Exp Rheumatol       Date:  2010-11-03       Impact factor: 4.473

5.  Assessment of prognosis of patients with idiopathic pulmonary fibrosis by computer-aided analysis of CT images.

Authors:  Tae Iwasawa; Akira Asakura; Fumikazu Sakai; Tetu Kanauchi; Toshiyuki Gotoh; Takashi Ogura; Takuya Yazawa; Junichi Nishimura; Tomio Inoue
Journal:  J Thorac Imaging       Date:  2009-08       Impact factor: 3.000

6.  Classification of parenchymal abnormality in scleroderma lung using a novel approach to denoise images collected via a multicenter study.

Authors:  Hyun J Kim; Gang Li; David Gjertson; Robert Elashoff; Sumit K Shah; Robert Ochs; Fah Vasunilashorn; Fereidoun Abtin; Matthew S Brown; Jonathan G Goldin
Journal:  Acad Radiol       Date:  2008-08       Impact factor: 3.173

7.  Quantitative assessment of change in regional disease patterns on serial HRCT of fibrotic interstitial pneumonia with texture-based automated quantification system.

Authors:  Ra Gyoung Yoon; Joon Beom Seo; Namkug Kim; Hyun Joo Lee; Sang Min Lee; Young Kyung Lee; Jae Woo Song; Jin Woo Song; Dong Soon Kim
Journal:  Eur Radiol       Date:  2012-08-24       Impact factor: 5.315

8.  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

9.  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

10.  Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis.

Authors:  Fabien Maldonado; Teng Moua; Srinivasan Rajagopalan; Ronald A Karwoski; Sushravya Raghunath; Paul A Decker; Thomas E Hartman; Brian J Bartholmai; Richard A Robb; Jay H Ryu
Journal:  Eur Respir J       Date:  2013-04-05       Impact factor: 16.671

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  31 in total

1.  MUC5B variant is associated with visually and quantitatively detected preclinical pulmonary fibrosis.

Authors:  Susan K Mathai; Stephen Humphries; Jonathan A Kropski; Timothy S Blackwell; Julia Powers; Avram D Walts; Cheryl Markin; Julia Woodward; Jonathan H Chung; Kevin K Brown; Mark P Steele; James E Loyd; Marvin I Schwarz; Tasha Fingerlin; Ivana V Yang; David A Lynch; David A Schwartz
Journal:  Thorax       Date:  2019-09-26       Impact factor: 9.139

2.  Toward Early Identification of Clinically Relevant Interstitial Lung Disease.

Authors:  Margaret L Salisbury; David A Lynch
Journal:  Am J Respir Crit Care Med       Date:  2017-12-01       Impact factor: 21.405

3.  Development and Progression of Radiologic Abnormalities in Individuals at Risk for Familial Interstitial Lung Disease.

Authors:  Margaret L Salisbury; Justin C Hewlett; Guixiao Ding; Cheryl R Markin; Katrina Douglas; Wendi Mason; Adam Guttentag; John A Phillips; Joy D Cogan; Sara Reiss; Daphne B Mitchell; Pingsheng Wu; Lisa R Young; Lisa H Lancaster; James E Loyd; Stephen M Humphries; David A Lynch; Jonathan A Kropski; Timothy S Blackwell
Journal:  Am J Respir Crit Care Med       Date:  2020-05-15       Impact factor: 21.405

4.  Interstitial lung abnormalities detected incidentally on CT: a Position Paper from the Fleischner Society.

Authors:  Hiroto Hatabu; Gary M Hunninghake; Luca Richeldi; Kevin K Brown; Athol U Wells; Martine Remy-Jardin; Johny Verschakelen; Andrew G Nicholson; Mary B Beasley; David C Christiani; Raúl San José Estépar; Joon Beom Seo; Takeshi Johkoh; Nicola Sverzellati; Christopher J Ryerson; R Graham Barr; Jin Mo Goo; John H M Austin; Charles A Powell; Kyung Soo Lee; Yoshikazu Inoue; David A Lynch
Journal:  Lancet Respir Med       Date:  2020-07       Impact factor: 30.700

Review 5.  Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.

Authors:  Mario Silva; Gianluca Milanese; Valeria Seletti; Alarico Ariani; Nicola Sverzellati
Journal:  Br J Radiol       Date:  2018-01-12       Impact factor: 3.039

6.  Impact of advanced detector technology and iterative reconstruction on low-dose quantitative assessment of lung computed tomography density in a biological lung model.

Authors:  E Hammond; K S Chan; J C Ames; N Stoyles; C M Sloan; J Guo; J D Newell; E A Hoffman; J C Sieren
Journal:  Med Phys       Date:  2018-06-21       Impact factor: 4.071

Review 7.  Approaching Clinical Trials in Childhood Interstitial Lung Disease and Pediatric Pulmonary Fibrosis.

Authors:  Robin R Deterding; Emily M DeBoer; Michal J Cidon; Terry E Robinson; David Warburton; Gail H Deutsch; Lisa R Young
Journal:  Am J Respir Crit Care Med       Date:  2019-11-15       Impact factor: 21.405

Review 8.  CT Radiomics in Thoracic Oncology: Technique and Clinical Applications.

Authors:  Geewon Lee; So Hyeon Bak; Ho Yun Lee
Journal:  Nucl Med Mol Imaging       Date:  2017-12-18

9.  Predicting Outcome in Idiopathic Pulmonary Fibrosis: Addition of Fibrotic Score at Thin-Section CT of the Chest to Gender, Age, and Physiology Score Improves the Prediction Model.

Authors:  Anurag Chahal; Roozbeh Sharif; Jubal Watts; Joao de Andrade; Tracy Luckhardt; Young-Il Kim; Rekha Ramchandran; Sushilkumar Sonavane
Journal:  Radiol Cardiothorac Imaging       Date:  2019-06-27

10.  Traction Bronchiectasis/Bronchiolectasis is Associated with Interstitial Lung Abnormality Mortality.

Authors:  Tomoyuki Hida; Mizuki Nishino; Takuya Hino; Junwei Lu; Rachel K Putman; Elias F Gudmundsson; Tetsuro Araki; Vladimir I Valtchinov; Osamu Honda; Masahiro Yanagawa; Yoshitake Yamada; Akinori Hata; Masahiro Jinzaki; Noriyuki Tomiyama; Hiroshi Honda; Raul San Jose Estepar; George R Washko; Takeshi Johkoh; David C Christiani; David A Lynch; Vilmundur Gudnason; Gunnar Gudmundsson; Gary M Hunninghake; Hiroto Hatabu
Journal:  Eur J Radiol       Date:  2020-05-18       Impact factor: 3.528

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