4-D segmentation and normalization of 3He MR images for intrasubject assessment of ventilated lung volumes

Benjamin Contrella; Nicholas J. Tustison; Talissa A. Altes; Brian B. Avants; John P. Mugler III; Eduard E. de Lange

doi:10.1117/12.911032

16 April 2012 4-D segmentation and normalization of 3He MR images for intrasubject assessment of ventilated lung volumes

Benjamin Contrella, Nicholas J. Tustison, Talissa A. Altes, Brian B. Avants, John P. Mugler III, Eduard E. de Lange

Author Affiliations +

Proceedings Volume 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging; 83171D (2012) https://doi.org/10.1117/12.911032
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Although 3He MRI permits compelling visualization of the pulmonary air spaces, quantitation of absolute ventilation is difficult due to confounds such as field inhomogeneity and relative intensity differences between image acquisition; the latter complicating longitudinal investigations of ventilation variation with respiratory alterations. To address these potential difficulties, we present a 4-D segmentation and normalization approach for intra-subject quantitative analysis of lung hyperpolarized 3He MRI. After normalization, which combines bias correction and relative intensity scaling between longitudinal data, partitioning of the lung volume time series is performed by iterating between modeling of the combined intensity histogram as a Gaussian mixture model and modulating the spatial heterogeneity tissue class assignments through Markov random field modeling. Evaluation of the algorithm was retrospectively applied to a cohort of 10 asthmatics between 19-25 years old in which spirometry and 3He MR ventilation images were acquired both before and after respiratory exacerbation by a bronchoconstricting agent (methacholine). Acquisition was repeated under the same conditions from 7 to 467 days (mean ± standard deviation: 185 ± 37.2) later. Several techniques were evaluated for matching intensities between the pre and post-methacholine images with the 95th percentile value histogram matching demonstrating superior correlations with spirometry measures. Subsequent analysis evaluated segmentation parameters for assessing ventilation change in this cohort. Current findings also support previous research that areas of poor ventilation in response to bronchoconstriction are relatively consistent over time.

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Benjamin Contrella, Nicholas J. Tustison, Talissa A. Altes, Brian B. Avants, John P. Mugler III, and Eduard E. de Lange "4-D segmentation and normalization of 3He MR images for intrasubject assessment of ventilated lung volumes", Proc. SPIE 8317, Medical Imaging 2012: Biomedical Applications in Molecular, Structural, and Functional Imaging, 83171D (16 April 2012); https://doi.org/10.1117/12.911032

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KEYWORDS

Image segmentation

Lung

Magnetic resonance imaging

Spirometry

Tissues

Data modeling

3D modeling

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