Endovascular surgery involves the insertion of a catheter into a leg vessel, and manipulation of the catheter through a complex network of connected vessels in order to reach a desired target. Once the catheter is in place, glue or particles are released in order to obstruct blood vessels supplying a tumor or vascular lesion. If the catheter is in incorrect position, the glue or particles will obstruct blood supply to normal brain, resulting in stroke. The risks are high, with major complications occurring in 5-10% of patients. 

Guidance of endovascular operations is generally done through intraoperative acquisition of digital subtraction angiograms (DSA); flat, projection images in which projection overlap makes it difficult to determine vascular parent-child relationships. It would be very useful to be able to interpret these DSAs within the context of three-dimensional vessel trees. 

All programs are cross-platform and run on a laptop PC. 

Examples of registration of vessel trees against a DSA in 3 different patients. The skeletons of the 3D vessels are projected in white against the DSA. 
 

Early example of a 3D, color-coded vessel tree in conjunction with a tumor segmented by Gerig et al. The patient is the same shown at right above. The 3D objects can be interactively viewed from any angle, and allow better interpretation of the DSA image. 
 

Simulation of catheter passage through a 3D tree. The tree is projected upon a DSA. The currently "picked" vessel is shown in pink, with a red ball at its tip indicating direction of blood flow. The subtree arising from the vessel is shown in blue. Point and click operations along the 3D branches allow experimentation with different catheter trajectories without subjecting the patient to additional contrast load and radiation. 
 

Surgical planning interface that models fluoroscopic motion, patient motion, and table motion. Vessels can be visualized as superimposed within the patient's head, as shown at right, or as registered with DSA views as shown in the images above. 

• Image-Guided Vascular Neurosurgery 

Bullitt E, Aylward S, Liu A, Stone J, Mukherji S, Coffey C, Gerig G, Pizer SM (1999) 3D graph description of the intracerebral vasculature from segmented MRA and tests of accuracy by comparison with x-ray angiograms IPMI 99 Lecture Notes in Computer Science 1613:308-321. 

Bullitt E, Liu A, Aylward S, Coffey C, Stone J, Mukherji SK, Muller K, Pizer SM (1999) Registration of 3D vessels with 2D digital angiograms. Clinical evaluation.. Academic Radiology 6: 539-546. 

Gerig G, Szekely G, Israel G, Berger G (1995) Detection and characterization of unsharp blobs by curve evolution. IPMI '95, Series on Computational Imaging and Vision, Kluwer Academic Publishers, pp. 165-176. 

G.Gerig, D. Welti, Ch. Guttmann, A. Colchester, G. Székely (1998) Exploring the discrimination power of the time domain for segmentation and characterization of lesions in serial MR data, Lecture Notes in Computer Science 1496, Proc. of MICCAI'98, editors: William M. Wells, Alan Colchester, Scott Delp, 469-480. 

Liu A, Bullitt E, Pizer SM (1998) 3D/2D registration using tubular anatomical structures as a basis. MICCAI 1998. Lecture Notes in Computer Science 1496: 952-963. 

Bullitt E, Liu A, Aylward SR, Soltys M, Boxwala A, Rosenman J, Pizer S (1997a) Methods for displaying intracerebral vascular anatomy. Am J Neuroradiol 18:417-420. 

Bullitt E, Aylward S, Liu A, Stone J, Mukherji S, Coffey C, Gerig G, Pizer SM (1999) 3D graph description of the intracerebral vasculature from segmented MRA and tests of accuracy by comparison with x-ray angiograms IPMI 99 Lecture Notes in Computer Science 1613:308-321. 

Bullitt E, Liu A, Aylward S, Coffey C, Stone J, Mukherji SK, Muller K, Pizer SM (1999) Registration of 3D vessels with 2D digital angiograms. Clinical evaluation.. Academic Radiology 6: 539-546. 

• Dr. Elizabeth Bullitt 
• Dr. Stephen R. Aylward 
• Dr. Guido Gerig 
• MIDAG 
• Ibanez
• Liu