Roadmap for an imaging and modelling paediatric study in rural NZ

Figures

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  FIGURE 1. Flowchart showing the overall study design and multiple stages.

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  FIGURE 2. Example of images used for one participant. AutoBind whole body images on the right and left was used for bones and muscle, top three pictures (Cine FIESTA, DTI and T1 MPRAGE) were used to model the brain, under the brain are two pictures of the sequences (Short Axis and Zero TE) used for the heart and lungs.

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  FIGURE 3. (Top and middle row) An exemplar case of child-specific brain model customized to an anatomical T1-weighted image and FE model overlaid. (Bottom row) Cross section of the diffusion tractography (DTI) images with FA-based heterogeneous material properties.

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  FIGURE 4. Cerebral dynamics measured from cardiac-gated sequences: (A) Mid-sagittal slice showing maximum difference map depicting mid-brain motion. Arrows showing motion in the Pons-CSF interface, Medula Oblongata CSF interface, brain stem motion, motion in the cerebellar tonsil and lateral ventricle CSF boundary. (B–C) Flow processing for one representative subject. Plots show blood flow over the cardiac cycle in the basilar artery (B), as well as CSF flow (C) over the cardiac cycle at the level of C2.

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  FIGURE 5. Child-specific cardiac ventricular model and extracted indices.

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  FIGURE 6. Flow chart showing the generation of child-specific airway and vascular geometries.

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  FIGURE 7. Reconstructed pelvis, femurs, tibias and fibulas from MRI and subsequently fitted with template meshes (left) to automatically compute bone torsional and linear measurements (right).

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  FIGURE 8. 3D volume rendering of the lower limb skeletal muscles and bones offers insight into the musculoskeletal structure of the patient. Volumes can be analyzed and compared against normative datasets to assess muscle size abnormality. 3D surface data offers information on muscle shape and can be used for statistical shape modeling.