Literature DB >> 28598732

Pulmonary Function Tests for the Radiologist.

Hsiang-Jer Tseng1, Travis S Henry1, Srihari Veeraraghavan1, Pardeep K Mittal1, Brent P Little1.   

Abstract

Pulmonary function tests (PFTs) provide important quantitative information about lung function and can be used to elucidate pathologic conditions responsible for respiratory symptoms, assess the severity and course of disease, and evaluate the patient for suitability and timing for lung transplantation. They are typically used in tandem with chest imaging, along with other ancillary data, to arrive at a specific diagnosis. PFTs may provide the radiologist with clues to the diagnosis and grading of a wide variety of pulmonary diseases. In this review, the authors discuss the clinical use of PFTs, their major components, and important measurements and graphical representations that are essential for understanding and interpreting the results. The key components of PFT panels-static lung volumes, dynamic lung function (spirometry), and diffusion capacity-are explained. The authors present a general algorithmic approach for problem solving, with recognition of common patterns of results (obstructive, restrictive, mixed, nonspecific, and normal). Pulmonary diseases from each of the major patterns and chest imaging are illustrated, and correlations between particular PFT results and disease severity and morphology at imaging are examined. Common pitfalls encountered during interpretation are also highlighted. A basic understanding of the mechanics of PFTs, characteristic patterns in important diseases, and correlation between lung function and imaging findings may assist the radiologist in diagnosis and follow-up of key pulmonary diseases and strengthen the radiologist's role as part of a multidisciplinary diagnostic team. Online supplemental material is available for this article. ©RSNA, 2017.

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Year:  2017        PMID: 28598732     DOI: 10.1148/rg.2017160174

Source DB:  PubMed          Journal:  Radiographics        ISSN: 0271-5333            Impact factor:   5.333


  7 in total

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2.  Multi-scale models of lung fibrosis.

Authors:  Julie Leonard-Duke; Stephanie Evans; Riley T Hannan; Thomas H Barker; Jason H T Bates; Catherine A Bonham; Bethany B Moore; Denise E Kirschner; Shayn M Peirce
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3.  Imaging Dynamic Expiration: Feasibility of MRI Spirometry Using Hyperpolarized Xenon Gas.

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5.  Prediction of Obstructive Lung Disease from Chest Radiographs via Deep Learning Trained on Pulmonary Function Data.

Authors:  Joyce D Schroeder; Ricardo Bigolin Lanfredi; Tao Li; Jessica Chan; Clement Vachet; Robert Paine Iii; Vivek Srikumar; Tolga Tasdizen
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2021-01-05

6.  Instructional Training Compared with Self-Study for Pulmonary Function Test Interpretation.

Authors:  Silke Doris Braun; Mareen Clayton; Dirk Koschel; Claudia Prescher; Hermann Körndle; Susanne Narciss
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7.  Clinical implication of interstitial lung abnormality in elderly patients with early-stage non-small cell lung cancer.

Authors:  Seong Woo Cho; Won Gi Jeong; Jong Eun Lee; In-Jae Oh; Sang Yun Song; Hye Mi Park; Hyo-Jae Lee; Yun-Hyeon Kim
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  7 in total

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