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Vol.2 , No. 2, Publication Date: Sep. 21, 2016, Page: 33-45
| [1] | Stanley Jacobson, Department of Integrative Physiology and Pathobiology Tufts University School of Medicine, Boston, Massachusetts, USA. |
| [2] | Scott K. Epstein, Departments of Educational Affairs and Medicine, Tufts University School of Medicine and Tufts Medical Center, Boston Massachusetts, USA. |
| [3] | Samuel S. Giles, Department of Medicine, St. Elizabeth’s Hospital, Boston, Massachusetts, USA. |
| [4] | Susan Albright, Tufts University Science Knowledge Base (TUSK), Tufts University School of Medicine, Boston, Massachusetts, USA. |
| [5] | Eileen A. McGarry, Department of Integrative Physiology and Pathobiology Tufts University School of Medicine, Boston, Massachusetts, USA. |
| [6] | Veronica Coppersmith, Department of Medicine, St. Luke’s University Health Network, Bethlehem, Pennsylvania, USA. |
| [7] | Jeffrey Griffiths, Departments of Public Health and Community Medicine, Nutrition, Engineering, Tufts University School of Medicine, Boston, Massachusetts, USA. |
| [8] | Joseph F. Polak, Department of Radiology, Tufts University School of Medicine and Tufts Medical Center, Boston, Massachusetts, USA. |
Our aim in this study is to extend the value of an Anatomical Gift Program beyond a one-time laboratory dissection by digitizing the images from each cadaver prior to their dissection and then forming anatomical models and Virtual Patients from these images which can be stored on a website. We imaged 44 cadavers from the Tufts University Anatomical Gift Program on a Siemens Somatom Sensation 64 slice CT. All imaged cadavers came with only a listing of the “cause of death”. To complete this goal, we first formed a team of basic scientists, clinical scientists and information technologist. After the imaging the radiologist listed the pathological conditions seen which include many unexpected abnormalities that are not identified in the “cause of death”. Then an internist based on the radiologists’ analysis and his clinical expertise developed a Virtual Patient from each case. Finally using state-of-the-art image processing, and computer modeling the basic scientist and the information technologist developed anatomical models and virtual patients in a digital format from each case using the OsiriX image analysis system. In some cases, the pathology was directly associated with the reported cause of death, however, the majority of the pathological findings were unexpected. We also noted that many of the normal anatomical relationships were well demonstrated. We believe that developing in a digital format Virtual Patients and anatomical models further extends the value of this program and enhances learning and integration in the clinical and basic sciences.
Keywords
Anatomical Models, Cadavers, CT Imaging, Digitization, OsiriX, Virtual Patient
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