The applicants proposed to provide new methods of vascular imaging which will increase both the accuracy and the speed with which the clinician is able to perceive complex vascular anatomy in 3-D. The proposed approach provides a tree-based vascular display, which permits the clinician to highlight any desired tree or subtree and to view it from any desired position or, alternatively, to delete any desired tree or subtree from display. The proposed approach also permits 3-D reconstruction of angiographic data so as to overcome the common problem of non-visualization of important vessels by standard 3-D imaging techniques. One of the goals is the creation of a multi-modality surgical planning tool which should permit improved 3-D visualization of complex vascular lesions, improved planning for embolization procedures, and better analysis of complex tumors. The proposed methods include segmentation of magnetic resonance angiograms (MRA) and tree creation from the segmented vessels. If more detail is required, the MRA is registered with two angiographic images and desired angiographic data is reconstructed into 3-D, building upon the base provided by the MRA. The 3-D reconstruction of angiographic data is a particularly difficult problem that has, heretofore, defied solution. The proposed approach to the problem is different from those of the past and uses both a new method of image analysis that permits point pairing on separated projection views so as to separate what can be determined from which cannot be known on projection images, and the new approach of core methodology for image segmentation and 2D-3D registration. Core-based methods can effectively segment 2- and 3-D images in the presence of noise and data obscuration. Preliminary data include results, some of immediate clinical utility, that no other group has been able to achieve. The applicants propose creation of a multi-modality surgical planning program that will be of use both for preoperative planning and intraoperative guidance. The clinical efficacy of our vascular display methods will be tested by measuring both the time it takes for clinicians to evaluate vascular anatomy and the depth of their understanding when either our planning tool or standard imaging data is used to provide vascular information. The proposed vascular display abilities are relevant to a range of surgical and radiosurgical procedures, affecting tens of thousands of patients in the United States each year. The segmentation and 2D-3D registration methods developed should provide a general set of tools of value to many different applications.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA067812-01A2
Application #
2008900
Study Section
Special Emphasis Panel (ZRG7-DMG (01))
Project Start
1997-02-15
Project End
2000-01-31
Budget Start
1997-02-15
Budget End
1998-01-31
Support Year
1
Fiscal Year
1997
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Surgery
Type
Schools of Medicine
DUNS #
078861598
City
Chapel Hill
State
NC
Country
United States
Zip Code
27599
Bullitt, Elizabeth; Ewend, Matthew G; Aylward, Stephen et al. (2004) Abnormal vessel tortuosity as a marker of treatment response of malignant gliomas: preliminary report. Technol Cancer Res Treat 3:577-84
Prastawa, Marcel; Bullitt, Elizabeth; Moon, Nathan et al. (2003) Automatic brain tumor segmentation by subject specific modification of atlas priors. Acad Radiol 10:1341-8
Bullitt, Elizabeth; Aylward, Stephen R (2002) Volume rendering of segmented image objects. IEEE Trans Med Imaging 21:998-1002
Aylward, Stephen R; Bullitt, Elizabeth (2002) Initialization, noise, singularities, and scale in height ridge traversal for tubular object centerline extraction. IEEE Trans Med Imaging 21:61-75
Bullitt, E; Aylward, S; Bernard Jr, E J et al. (2001) Computer-assisted visualization of arteriovenous malformations on the home personal computer. Neurosurgery 48:576-82; discussion 582-3
Bullitt, E; Aylward, S; Smith, K et al. (2001) Symbolic description of intracerebral vessels segmented from magnetic resonance angiograms and evaluation by comparison with X-ray angiograms. Med Image Anal 5:157-69
Bullitt, E; Liu, A; Aylward, S R et al. (1999) Registration of 3D cerebral vessels with 2D digital angiograms: clinical evaluation. Acad Radiol 6:539-46
Bullitt, E; Liu, A; Pizer, S M (1997) Three-dimensional reconstruction of curves from pairs of projection views in the presence of error. I. Algorithms. Med Phys 24:1671-8
Bullitt, E; Liu, A; Pizer, S M (1997) Three-dimensional reconstruction of curves from pairs of projection views in the presence of error. II. Analysis of error. Med Phys 24:1679-87