Purpose or Case Report: Diffusion tensor imaging (DTI) depicts the anisotropic motion of water molecules limited by tissue microstructure. Images of tractography provide qualitative information about complex tissue architecture, so that diffusion metrics reflect physeal activity.
DTI’s main clinical application is on brain white matter, but it can be used in any tissue in which there is organized tissue structure. Our research group has used tractography of the knee to study the structure of the physis and adjacent metaphysis and investigated the potential of DTI metrics as biomarkers predictive of skeletal growth. DTI parameters include tract count, tract length and tract volume and fractional anisotropy (FA). They can help distinguish between a normal and a dysfunctional physis, predict post-imaging growth and physeal closure, and possibly determine response to growth hormone treatment.
We will demonstrate the techniques for data acquisition, preprocessing, and analysis, and the basis for interpretation, based on our experience of performing DTI in over 900 knees. Each step has its own challenges for the standardization and optimization of DTI of the physis. The goal of this poster is to showcase our experience with the establishment of an efficient DTI pipeline. We will: 1) Discuss the impact of variation of DTI acquisition parameters (e.g. Time to Echo (TE), number of directions, b-value, voxel size…); 2) Describe programs for distortion correction and denoising , as well as the required post-processing software programs; 3) Discuss approaches to standardize the acquisition in the different anatomic areas and cross vendors; 4) Discuss the normal change of tractography data and physeal DTI metrics with age, sex and specific knee physis. We will show how DTI changes due to physeal dysfunction in different pathologies, such as growth hormone deficiency, trauma, arthritis, metabolic disorders and chemotherapy and radiation therapy. Finally, we will show how DTI can be used to predict height gain and final height compared to conventional bone age-based methods and standard growth charts, which are inaccurate and not generalizable to the current child/adolescent population.
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