Literature DB >> 35751660

Quantitative Computed Tomography: What Clinical Questions Can it Answer in Chronic Lung Disease?

Marcelo Cardoso Barros1, Stephan Altmayer2, Alysson Roncally Carvalho3, Rosana Rodrigues3, Matheus Zanon4, Tan-Lucien Mohammed5, Pratik Patel5, Al-Ani Mohammad6, Borna Mehrad6, Jose Miguel Chatkin4, Bruno Hochhegger5.   

Abstract

Quantitative computed tomography (QCT) has recently gained an important role in the functional assessment of chronic lung disease. Its capacity in diagnostic, staging, and prognostic evaluation in this setting is similar to that of traditional pulmonary function testing. Furthermore, it can demonstrate lung injury before the alteration of pulmonary function test parameters, and it enables the classification of disease phenotypes, contributing to the customization of therapy and performance of comparative studies without the intra- and inter-observer variation that occurs with qualitative analysis. In this review, we address technical issues with QCT analysis and demonstrate the ability of this modality to answer clinical questions encountered in daily practice in the management of patients with chronic lung disease.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Chronic lung disease; Functional CT; Quantitative CT

Mesh:

Year:  2022        PMID: 35751660      PMCID: PMC9378468          DOI: 10.1007/s00408-022-00550-1

Source DB:  PubMed          Journal:  Lung        ISSN: 0341-2040            Impact factor:   3.777


  46 in total

1.  Quantitative Low-Dose Computed Tomography of the Lung Parenchyma and Airways for the Differentiation between Chronic Obstructive Pulmonary Disease and Asthma Patients.

Authors:  Huai Chen; Qing-Si Zeng; Min Zhang; Rong-Chang Chen; Ting-Ting Xia; Wei Wang; Xiaoyin Xu; Yubao Guan
Journal:  Respiration       Date:  2017-07-25       Impact factor: 3.580

2.  Lung CT Densitometry in Idiopathic Pulmonary Fibrosis for the Prediction of Natural Course, Severity, and Mortality.

Authors:  Benjamin Loeh; Lukas T Brylski; Daniel von der Beck; Werner Seeger; Ekaterina Krauss; Philippe Bonniaud; Bruno Crestani; Carlo Vancheri; Athol U Wells; Philipp Markart; Andreas Breithecker; Andreas Guenther
Journal:  Chest       Date:  2019-02-08       Impact factor: 9.410

3.  Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

Authors:  Esther Pompe; Craig J Galbán; Brian D Ross; Leo Koenderman; Nick Ht Ten Hacken; Dirkje S Postma; Maarten van den Berge; Pim A de Jong; Jan-Willem J Lammers; Firdaus Aa Mohamed Hoesein
Journal:  Respir Med       Date:  2016-11-25       Impact factor: 3.415

4.  Comparison of low- and ultralow-dose computed tomography protocols for quantitative lung and airway assessment.

Authors:  Emily Hammond; Chelsea Sloan; John D Newell; Jered P Sieren; Melissa Saylor; Craig Vidal; Shayna Hogue; Frank De Stefano; Alexa Sieren; Eric A Hoffman; Jessica C Sieren
Journal:  Med Phys       Date:  2017-08-02       Impact factor: 4.071

5.  CT-quantified emphysema in male heavy smokers: association with lung function decline.

Authors:  Firdaus A A Mohamed Hoesein; Bartjan de Hoop; Pieter Zanen; Hester Gietema; Cas L J J Kruitwagen; Bram van Ginneken; Ivana Isgum; Christian Mol; Rob J van Klaveren; Akkelies E Dijkstra; Harry J M Groen; H Marike Boezen; Dirkje S Postma; Mathias Prokop; Jan-Willem J Lammers
Journal:  Thorax       Date:  2011-04-07       Impact factor: 9.139

6.  Quantitative CT detects progression in COPD patients with severe emphysema in a 3-month interval.

Authors:  Philip Konietzke; Mark O Wielpütz; Willi L Wagner; Felix Wuennemann; Hans-Ulrich Kauczor; Claus P Heussel; Monika Eichinger; Ralf Eberhardt; Daniela Gompelmann; Oliver Weinheimer
Journal:  Eur Radiol       Date:  2020-01-21       Impact factor: 5.315

7.  Machine learning for lung CT texture analysis: Improvement of inter-observer agreement for radiological finding classification in patients with pulmonary diseases.

Authors:  Yoshiharu Ohno; Kota Aoyagi; Daisuke Takenaka; Takeshi Yoshikawa; Aina Ikezaki; Yasuko Fujisawa; Kazuhiro Murayama; Hidekazu Hattori; Hiroshi Toyama
Journal:  Eur J Radiol       Date:  2020-11-12       Impact factor: 3.528

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

Authors:  Stephen M Humphries; Kunihiro Yagihashi; Jason Huckleberry; Byung-Hak Rho; Joyce D Schroeder; Matthew Strand; Marvin I Schwarz; Kevin R Flaherty; Ella A Kazerooni; Edwin J R van Beek; David A Lynch
Journal:  Radiology       Date:  2017-05-10       Impact factor: 11.105

9.  Relationship between Emphysema Progression at CT and Mortality in Ever-Smokers: Results from the COPDGene and ECLIPSE Cohorts.

Authors:  Samuel Y Ash; Raúl San José Estépar; Sean B Fain; Ruth Tal-Singer; Robert A Stockley; Lars H Nordenmark; Stephen Rennard; MeiLan K Han; Debora Merrill; Stephen M Humphries; Alejandro A Diaz; Stefanie E Mason; Farbod N Rahaghi; Carrie L Pistenmaa; Frank C Sciurba; Gonzalo Vegas-Sánchez-Ferrero; David A Lynch; George R Washko
Journal:  Radiology       Date:  2021-02-16       Impact factor: 11.105

10.  Normal lung attenuation distribution and lung volume on computed tomography in a Chinese population.

Authors:  Ting Cheng; Yong Li; Shuai Pang; HuanYing Wan; GuoChao Shi; QiJian Cheng; QingYun Li; ZiLai Pan; ShaoGuang Huang
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2019-07-24
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