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Mathematica has been used to generate animations to facilitate training in magnetic resonance (MR) imaging. MR imaging has become an essential diagnostic tool, and clinical staff must undergo extensive training before they are able to confidently employ this imaging modality. The MR process is complex and requires understanding at two levels. At the physical level the intern must understand proton precession, resonant excitation, spin dephasing, and de-excitation processes. At the imaging level the interplay between intrinsic tissue characteristics (T1, T2, rho) and extrinsic acquisition parameters (TR, TE, etc.) gives rise to a bewildering range of possible combinations with dramatically different tissue-contrast images. Ultimately, the intern must be capable of determining the required acquisition setting to generate an image that displays optimal lesion detection.
Mathematica was used to model the Carr-Purcell-Bloch equations applied to an anthropomorphic head phantom showing normal and pathological neuroanatomy. This enables a simulated MR image to be produced for any possible combination of intrinsic and extrinsic factors and can be used to determine optimal acquisition parameters to demonstrate a specific disease. Animations that show the changes in tissue contrast, as acquisition settings are altered, have been produced. The contrast changes can be observed to correspond to crossing of the magnetization growth and decay curves for the normal tissues and lesion. The animations are fully interactive and are used by clinical staff in conjunction with an activity/MCQ sheet for continuing education credits. The physical processes have also been animated and explicitly show hydrogen nuclei magnetic vectors precessing in the ground state, undergoing radio frequency excitation into the excited state with precessional coherence and decay of transverse magnetization due to de-excitation. The animations have proved very successful in improving comprehension of the MR imaging process.
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