Volume registration using needle paths and point landmarks for evaluation of interventional MRI treatments

Roee S. Lazebnik, Tanya L. Lancaster, Michael S. Breen, Jonathan S. Lewin, David L. Wilson

Research output: Contribution to journalArticlepeer-review

Abstract

We created a method for three-dimensional (3-D) registration of medical images (e.g., magnetic resonance imaging (MRI) or computed tomography) to images of physical tissue sections or to other medical images and evaluated its accuracy. Our method proved valuable for evaluation of animal model experiments on interventional-MRI guided thermal ablation and on a new localized drug delivery system. The method computes an optimum set of rigid body registration parameters by minimization of the Euclidean distances between automatically chosen correspondence points, along manually selected fiducial needle paths, and optional point landmarks, using the iterative closest point algorithm. For numerically simulated experiments, using two needle paths over a range of needle orientations, mean voxel displacement errors depended mostly on needle localization error when the angle between needles was at least 20°. For parameters typical of our in vivo experiments, the mean voxel displacement error was <0.35 mm. In addition, we determined that the distance objective function was a useful diagnostic for predicting registration quality. To evaluate the registration quality of physical specimens, we computed the misregistration for a needle not considered during the optimization procedure. We registered an ex vivo sheep brain MR volume with another MR volume and tissue section photographs, using various combinations of needle and point landmarks. Mean registration error was always ≤0.54 mm for MR-to-MR registrations and ≤0.52 mm for MR to tissue section registrations. We also applied the method to correlate MR volumes of radio-frequency induced thermal ablation lesions with actual tissue destruction. In this case, in vivo rabbit thigh volumes were registered to photographs of ex vivo tissue sections using two needle paths. Mean registration errors were between 0.7 and 1.36 mm over all rabbits, the largest error less than two MR voxel widths. We conclude that our method provides sufficient spatial correspondence to facilitate comparison of 3-D image data with data from gross pathology tissue sections and histology.

Original languageEnglish (US)
Pages (from-to)653-660
Number of pages8
JournalIEEE transactions on medical imaging
Volume22
Issue number5
DOIs
StatePublished - May 2003

Keywords

  • Image guided therapy
  • Interventional MRI
  • Medical image processing
  • Radio-frequency thermal ablation
  • Volume registration

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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