Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images

Christopher P. Favazza, Krzysztof R. Gorny, Matthew R Callstrom, Anil N. Kurup, Michael Washburn, Pamela S. Trester, Charles L. Fowler, Nicholas J. Hangiandreou

Research output: Contribution to journalArticle

Abstract

We present the development of a two-component magnetic resonance (MR) fiducial system, that is, a fiducial marker device combined with an auto-segmentation algorithm, designed to be paired with existing ultrasound probe tracking and image fusion technology to automatically fuse MR and ultrasound (US) images. The fiducial device consisted of four ~6.4 mL cylindrical wells filled with 1 g/L copper sulfate solution. The algorithm was designed to automatically segment the device in clinical abdominal MR images. The algorithm's detection rate and repeatability were investigated through a phantom study and in human volunteers. The detection rate was 100% in all phantom and human images. The center-of-mass of the fiducial device was robustly identified with maximum variations of 2.9 mm in position and 0.9° in angular orientation. In volunteer images, average differences between algorithm-measured inter-marker spacings and actual separation distances were 0.53 ± 0.36 mm. "Proof-of-concept" automatic MR-US fusions were conducted with sets of images from both a phantom and volunteer using a commercial prototype system, which was built based on the above findings. Image fusion accuracy was measured to be within 5 mm for breath-hold scanning. These results demonstrate the capability of this approach to automatically fuse US and MR images acquired across a wide range of clinical abdominal pulse sequences.

Original languageEnglish (US)
JournalJournal of Applied Clinical Medical Physics
DOIs
StateAccepted/In press - Jan 1 2018

    Fingerprint

Keywords

  • MRI
  • Auto-registration
  • Fiducial marker
  • Image fusion
  • Ultrasound

ASJC Scopus subject areas

  • Radiation
  • Instrumentation
  • Radiology Nuclear Medicine and imaging

Cite this

Favazza, C. P., Gorny, K. R., Callstrom, M. R., Kurup, A. N., Washburn, M., Trester, P. S., Fowler, C. L., & Hangiandreou, N. J. (Accepted/In press). Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images. Journal of Applied Clinical Medical Physics. https://doi.org/10.1002/acm2.12352