Diffusion Tensor Imaging of the Knee to Predict Childhood Growth.

ABSTRACT

Background Accurate and precise methods to predict growth remain lacking. Diffusion tensor imaging (DTI) depicts the columnar structure of the physis and metaphyseal spongiosa and provides measures of tract volume and length that may help predict growth. Purpose To validate physeal DTI metrics as predictors of height velocity (1-year height gain from time of MRI examination) and total height gain (height gain from time of MRI examination until growth stops) and compare the prediction accuracy with bone age-based models. Materials and Methods Femoral DTI studies (b values = 0 and 600 sec/mm2; directions = 20) of healthy children who underwent MRI of the knee between February 2012 and December 2016 were retrospectively analyzed. Children with height measured at MRI and either 1 year later (height velocity) or after growth cessation (total height gain, mean = 34 months from MRI) were included. Physeal DTI tract volume and length were correlated with height velocity and total height gain. Multilinear regression was used to assess the potential of DTI metrics in the prediction of both parameters. Bland-Altman plots were used to compare root mean square error (RMSE) and bias in height prediction using DTI versus bone age methods. Results Eighty-nine children (mean age, 13 years ± 3 [SD]; 47 boys) had height velocity measured, and 70 (mean age, 14 years ± 1; 36 girls) had total height gain measured. Tract volumes correlated with height velocity (r2 = 0.49) and total height gain (r2 = 0.46) (P < .001 for both) after controlling for age and sex. Tract volume was the strongest predictor for height velocity and total height gain. An optimal multilinear model including tract volume improved prediction of height velocity (R2 = 0.63, RMSE = 1.7 cm) and total height gain (R2 = 0.59, RMSE = 1.8 cm) compared with bone age-based methods (height velocity R2 = 0.32, RMSE = 2.9 cm; total height gain R2 = 0.42, RMSE = 5.0 cm). Conclusion Models using tract volume derived from diffusion tensor imaging may perform better than bone age-based models in children for the prediction of height velocity and total height gain. © RSNA, 2022.