Point-based registration for image-guided neurosurgery has become the industry standard. While the use of intrinsic
points is appealing because of its retrospective nature, affixing extrinsic objects to the head prior to scanning has
been demonstrated to provide much more accurate registrations. Points of reference between image space and
physical space are called fiducials. The extrinsic objects which generate those points are fiducial markers. The
markers can be broken down into two classifications: skin-mounted and bone-implanted. Each has distinct
advantages and disadvantages. Skin-mounted fiducials require simply sticking them on the patient in locations
suggested by the manufacturer, however, they can move with tractions placed on the skin, fall off and perhaps the
most dangerous problem, they can be replaced by the patient. Bone implanted markers being rigidly affixed to the
skull do not present such problems. However, a minor surgical intervention (analogous to dental work) must be
performed to implant the markers prior to surgery. Therefore marker type and use has become a decision point for
image-guided surgery. We have performed a series of experiments in an attempt to better quantify aspects of the two
types of markers so that better informed decisions can be made. We have created a phantom composed of a full-size
plastic skull [Wards Scientific Supply] with a 500 ml bag of saline placed in the brain cavity. The skull was then
sealed. A skin mimicking material, DragonSkinTM [SmoothOn Company] was painted onto the surface and allowed
to dry. Skin mounted fiducials [Medtronic-SNT] and bone-implanted markers [Z-Kat]were placed on the phantom.
In addition, three additional bone-implanted markers were placed (two on the base of the skull and one in the eye
socket for use as targets). The markers were imaged in CT and 4 MRI sequences (T1-weighted, T2 weighted, SPGR,
and a functional series.) The markers were also located in physical space using an Optotrak 3020 [Northern Digital
Inc]. Registrations between image space and physical space were performed and fiducial and target registration
errors were determined. Finally the 5 bone-implanted makers which penetrated the skin were removed and a traction
equivalent to 25% of the weight of the average human head was applied to the “skin” surface. Target and fiducial
registrations were again performed.
Patient-specific mapping of point based cardiac data to a segmented heart surface requires accurate point-to-surface registration. The hypothesis is that anatomical movement that occurs between electrophysiological (E-P) data and cardiac image acquisition causes the pulmonary veins to have different orientations relative to the heart. We propose a piecewise registration of the atria and veins to produce a more accurate matching of these data sets. We developed phantoms and simulated clinical data accounting for noise and motion to demonstrate the robustness of the point-to-surface registration algorithm. Then three sets of patient data were used to evaluate rigid and piecewise registration, totaling three left atria and eight pulmonary veins. Analysis using the Student’s t-test showed the overall average chamfer distance for the three patients was significantly lower with piecewise registration compared to global rigid registration (p-values = 0.01, 0.05, 0.10). Visual analysis of the global and piecewise registered points confirms the importance of considering the plasticity and locomotion generally inherent in dynamic biological systems when attempting to match data sets acquired from such systems.
Delivery of gene therapy by injection remains governed by a limited diffusion distance. We propose the use of image-guidance to increase the accuracy of delivery, allowing for multiple delivery locations within the tumor. An outcome based approach to validation was developed. We have developed a series of optically tracked devices including an optically tracked syringe used for gene therapy delivery. Experiments were designed to quantify the accuracy in recording known points (fiducial localization error) and delivering a substance to a target within a phantom. The second experiment required the design of a rigid structure with mounted fiducials capable of securely holding an apple. This apparatus was CT scanned and targets in the apple we recorded and inserted in the images. The tracked syringe was guided to the target and a small amount of barium was injected. The apparatus was then re-imaged and the distal points of injections were determined. The mounted fiducials allow the two image sets to be registered and the distance between the targets and injection points to be calculated. This experiment was also performed on a rat carcass. The apple possesses no intrinsic traits possible to help guided the syringe to a known location, thus the validation process remains blind to the user.