Abstract #1609

A Segmentation Pipeline for Measuring Pulmonary Ventilation Suitable for Clinical Workflows and Decision-making

Fumin Guo¹, Khadija Sheikh¹, Rachel Eddy¹, Dante PI Capaldi¹, David G McCormack², Aaron Fenster¹, and Grace Parraga¹

¹Robarts Research Institute, The University of Western Ontario, London, ON, Canada, ²Department of Medicine, The University of Western Ontario, London, ON, Canada

Clinical translation of hyperpolarized ¹²⁹Xe MRI for large-scale and multi-centre applications requires image analysis tools that can provide clinically-acceptable measurements of pulmonary information. Here we proposed a pipeline that consists of ¹H-¹²⁹Xe registration, segmentation and ventilation defects generation for regional and quantitative evaluation of ¹²⁹Xe ventilation. ¹H-¹²⁹Xe registration was performed using a state-of-art registration approach. ¹H MRI segmentation was performed using primal-dual analysis methods and modern convex optimization techniques with incorporation of region information from ¹²⁹Xe MRI. We applied the pipeline across a range of pulmonary abnormalities and this computationally efficient pipeline demonstrated high agreement with reference standard, suggesting its suitability for efficient clinical workflows.

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