Abstract Archives of the RSNA, 2011
Visual Data Integration for Imaging-based Planning in Human Craniofacial Transplantation
Scientific Formal (Paper) Presentations
Presented on November 27, 2011
Presented as part of SSA15: Neuroradiology (Advanced Imaging)
Darren Smith MD, Presenter: Nothing to Disclose
Joseph E Losee MD, Abstract Co-Author: Nothing to Disclose
Vijay Saradhi Gorantla MD, PhD, Abstract Co-Author: Nothing to Disclose
Human face transplantation is a clinical reality with 13 procedures performed worldwide. Sophisticated imaging modalities could be important in surgical planning for three-dimensionally complex composite craniofacial defects. Aesthetic and functional outcomes can thus be optimized. Skeletal, soft tissue, and neurovascular structures can be imaged via sophisticated modalities ranging from MRI to 3DCT to tractography. These data, however, are relegated to separate platforms and are often not compatible with real-time user interaction and modification. Our goal was to integrate data from multiple imaging sources into a single 3D representation of donor or recipient anatomy that supports real-time user interaction and modification.
Models of craniofacial skeleton and skin were generated as polygonal frameworks from thresholding and "stacking" dicom images from CT scans. Muscles were extracted from the same dicom dataset as the bone data (if CT failed to capture muscle data in sufficient detail, MRI data sets were utilized). Key slices were manually segmented by outlining the structures of interest in 2D and lofting between 2D planes to build 3D meshes. If data quality permitted, blood vessels relevant to the model were extracted by thresholding dicoms from a CT angiogram. If the dataset was not of sufficient quality for this approach, key slices were imported into a 3D package and models manually segmented as above. Nerves were modeled as non-uniform rational basis splines based on tractography data.
We successfully integrated disparate and unwieldy CT, surface scan, CTA, MRI and tractography data into detailed 3D anatomical polygonal meshes compatible with real-time end-user manipulation and modification.
Craniofacial transplantation is a complex procedure. Critical insight into 3D anatomy is afforded by powerful imaging techniques. Herein we integrate classically disparate data into a single interactive 3D representation of donor or recipient anatomy compatible with real-time user interaction and modification. Procedural planning may be enhanced by allowing preoperative virtual interaction with patient skeletal, soft tissue, and neurovascular anatomy.
Devastating, non-reconstructible facial injuries can benefit from face transplantation. 3D multimodality imaging reconstruction can help in planning of donor and recipient surgery.
Visual Data Integration for Imaging-based Planning in Human Craniofacial Transplantation. Radiological Society of North America 2011 Scientific Assembly and Annual Meeting, November 26 - December 2, 2011 ,Chicago IL. http://archive.rsna.org/2011/11014434.html