Development of a pulmonary imaging biomarker pipeline for phenotyping of chronic lung disease

Fumin Guo; Dante Capaldi; Miranda Kirby; Khadija Sheikh; Sarah Svenningsen; David G. McCormack; Aaron Fenster; Grace Parraga

doi:10.1117/1.JMI.5.2.026002

28 June 2018 Development of a pulmonary imaging biomarker pipeline for phenotyping of chronic lung disease

Fumin Guo, Dante Capaldi, Miranda Kirby, Khadija Sheikh, Sarah Svenningsen, David G. McCormack, Aaron Fenster, Grace Parraga

Author Affiliations +

Journal of Medical Imaging, Vol. 5, Issue 2, 026002 (June 2018). https://doi.org/10.1117/1.JMI.5.2.026002

Abstract

We designed and generated pulmonary imaging biomarker pipelines to facilitate high-throughput research and point-of-care use in patients with chronic lung disease. Image processing modules and algorithm pipelines were embedded within a graphical user interface (based on the .NET framework) for pulmonary magnetic resonance imaging (MRI) and x-ray computed-tomography (CT) datasets. The software pipelines were generated using C++ and included: (1) inhaled He3 / Xe129 MRI ventilation and apparent diffusion coefficients, (2) CT-MRI coregistration for lobar and segmental ventilation and perfusion measurements, (3) ultrashort echo-time H1 MRI proton density measurements, (4) free-breathing Fourier-decomposition H1 MRI ventilation/perfusion and free-breathing H1 MRI specific ventilation, (5) multivolume CT and MRI parametric response maps, and (6) MRI and CT texture analysis and radiomics. The image analysis framework was implemented on a desktop workstation/tablet to generate biomarkers of regional lung structure and function related to ventilation, perfusion, lung tissue texture, and integrity as well as multiparametric measures of gas trapping and airspace enlargement. All biomarkers were generated within 10 min with measurement reproducibility consistent with clinical and research requirements. The resultant pulmonary imaging biomarker pipeline provides real-time and automated lung imaging measurements for point-of-care and high-throughput research.

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Fumin Guo, Dante Capaldi, Miranda Kirby, Khadija Sheikh, Sarah Svenningsen, David G. McCormack, Aaron Fenster, and Grace Parraga "Development of a pulmonary imaging biomarker pipeline for phenotyping of chronic lung disease," Journal of Medical Imaging 5(2), 026002 (28 June 2018). https://doi.org/10.1117/1.JMI.5.2.026002

Received: 14 December 2017; Accepted: 15 June 2018; Published: 28 June 2018

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