Adapted Linear Binning Method to Assess Pulmonary Ventilation and Perfusion in Children Using Lung Matrix Pencil Decomposition (
MP
)‐
MRI
Marion Curdy, Carmen Streibel, Oliver Bieri, Elisabeth Kieninger, Florian Wyler, Lukas Ebner, Grzegorz Bauman, Philipp Latzin ABSTRACT
Purpose
To adapt and validate a linear binning technique, developed for hyper‐polarized 129Xe MRI, for functional lung MRI with matrix‐pencil decomposition (MP)‐MRI.
Methods
First, a dedicated normalization was applied to the perfusion‐weighted and the ventilation‐weighted map histograms. Then, using 154 MP‐MRI scans of healthy children, reference bins were defined around the peak of the averaged histogram as normal (±1 SD), high (> 1 SD), low (between −1 SD and −2 SD), and defect (< −2 SD), and subsequently applied to a validation dataset comprising healthy children (HC, N = 41) and children with cystic fibrosis (CF, N = 30) to evaluate the accuracy of the classification and its discriminatory power. Furthermore, a third dataset comprising children with CF pre and post elexacaftor/tezacaftor/ivacaftor (ETI) therapy ( N = 24) was binned to evaluate the method's sensitivity to treatment effects. Standard outcome parameters, computed with a median threshold, served as a comparison.
Results
The adapted linear binning resulted in significantly higher defect and low percentages for perfusion and ventilation between children with CF and HC ( p values < 0.0001) with high discrimination (AUCs > 0.85). This was comparable to the standard median‐threshold method. Two illustrative cases were included to demonstrate the complementary granularity of the linear binning method. Although standard thresholding indicated improvement in both ventilation and perfusion defects pre and post ETI, linear binning showed that perfusion improvement was restricted to the low category.
Conclusion
A linear binning method for MP‐MRI was developed and validated, providing a healthy reference based on a large dataset and advancing functional lung image processing.