Registration using 3D-printed rigid templates outperforms manually scanned surface matching in image-guided temporal bone surgery

Makoto Yamashita, Nozomu Matsumoto, Byunghyun Cho, Noritaka Komune, Shinya Onogi, Jongseung Lee, Jordan Bano, Tomohiko Akahoshi, Makoto Hashizume

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: Image-guided surgery (IGS) for otological procedures requires minimal invasiveness and a high degree of accuracy. We have recently developed a noninvasive registration method, the Surface Template-Assisted Marker Positioning (STAMP) method, which uses a rigid template of the surface of the temporal bone. However, the STAMP method is not applicable when the bony surface is not exposed, such as in endoscopic surgery. Thus, we extended our research to apply the STAMP method onto the skin and tested its feasibility in this study. Methods: We designed a phantom made of a rigid box and soft material for the study. The target registration error (TRE) was measured at preset measuring points in the phantom. We modified the STAMP method to be applicable for use on the skin around the ears (S-STAMP). The same phantom was also registered using the conventional, manually scanned surface matching method. We compared the TRE after the different registration methods. Results: The TRE after the S-STAMP registration method was significantly smaller than that of the conventional surface matching method at all error measurement points in the phantom. However, the TRE after the S-STAMP registration method was significantly larger than that of paired point registration using invasive fiducial markers. Conclusions: The S-STAMP method using a rigid template on the soft surface yields a significantly smaller TRE than that of conventional, manually scanned surface matching registration. This strategy provides an alternative option to improve the accuracy of IGS without loading patients with additional invasive procedures.

Original languageEnglish
Pages (from-to)2119-2127
Number of pages9
JournalInternational Journal of Computer Assisted Radiology and Surgery
Volume11
Issue number11
DOIs
Publication statusPublished - Nov 1 2016

All Science Journal Classification (ASJC) codes

  • Surgery
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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