Development of Virtual Patients with Neurological Diseases from CT Images of Cadavers
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Abstract
BACKGROUND: In many medical schools Cadavers form the initial “patient” contact and there is very little information available about these “patients” due to the Health Insurance Portability and Accountability Act (HIPAA) of 1996. Most of the cadavers we dissect are from individuals in their 70s, 80s, and even 90s, therefore it must be assumed that each patient had other medical conditions during their lifetime. Consequently, we decided to develop VP from the cadavers and by undertaking CT imagery on many of the bodies prior to their dissection to more fully determine their medical history as radiological analysis offers more information than “cause of death (COD)” could ever offer.
METHODS: A total of 44 bodies were imaged on a CT prior to their dissection in the gross lab, and from these cases we have developed interactive Virtual Patients (VP) with diseases of the CNS. These VP were created by a team of basic scientists and clinical scientists. Anatomical models were created for each of these cases from the stacks of DICOM collected from the Siemens Somatom Sensation 64 slice dual energy Computer Tomographic Imaging scanner. The OsiriX and OsiriX -MD program on a Mac Pro computer were used to create anatomical models and videos to illustrate the major findings in each VP.
RESULTS: From these cadavers, we created Virtual Patients by combining the COD and the results of the radiological analysis with the clinical expertise of the development team. Finally using cutting-edge medical imaging technology, we produced interactive VP with self-assessment quizzes and anatomical models demonstrating the anatomical and pathological findings in each case.
CONCLUSIONS: With the aid of a team of basic scientists and clinical scientist and with the cooperation of a Department of Radiology one can develop VP which demonstrate the effects of disease in the CNS.
Key Words: Anatomical models, Cadavers, Interactive Cases, OsiriX and OsiriX-MD, Virtual Patients, Videos
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