Accurate Image-guided (Re)Placement of NIRS Probes

Shin Ting Wu*, José Angel Iván Rubianes Silva, Sergio Luiz Novi, Nicolas Gabriel S.R. de Souza, Edwin Johan Forero, Rickson C. Mesquita

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Background and Objective: Functional near-infrared spectroscopy (fNIRS) has become an attractive choice to neuroscience because of its high temporal resolution, ease of use, non-invasiveness, and affordability. With the advent of wearable fNIRS technology, on-the-spot studies of brain function have become viable. However, the lack of within-subject reproducibility is one of the barriers to the full acceptability of fNIRS. To support the validation of the claim that within-subject reproducibility of fNIRS could benefit from accurate anatomical information, we present in this paper a method to develop an image-based system that improves the placement of the sensors on the scalp at interactive rates.

Methods: The proposed solution consists of an electromagnetic digitizer and an interactive visualization system that allows monitoring the movements of the digitizer on a real head with respect to the underlying cerebral cortical structures. GPU-based volume raycasting rendering is applied to unveil these structures from the corresponding magnetic resonance imaging volume. Scalp and cortical surface are estimated from the scanned volume to improve depth perception. An alignment algorithm between the real and scanned heads is devised to visually feedback the position of the stylus of the digitizer. Off-screen rendering of the depthmaps of the visible surfaces makes spatial positioning of a 2D interaction pointer possible.

Results: We evaluated the alignment accuracy using four to eight anatomical landmarks and found seven to be a good compromise between precision and efficiency. Next, we evaluated reproducibility in positioning five arbitrarily chosen points on three volunteers by four operators over five sessions. In every session, seven anatomical landmarks were applied in the alignment of the real and the scanned head. For the same volunteer, one-way analysis of variance (ANOVA) revealed no significant differences within the five points digitized by the same operator over five sessions (α = 0.05). In addition, preliminary study of motor cortex activation by right-hand finger tapping showed the potential of our approach to increase functional fNIRS reproducibility.

Conclusions: Results of experiments suggest that the enhancement of the visualization of the location of the probes on the scalp, relative to the underlying cortical structures, improves reproducibility of fNIRS measurements. As further work, we plan to study the fNIRS reproducibility in other cortical regions and in clinical settings using the proposed system.

Original languageEnglish
Article number105844
Number of pages10
JournalComputer Methods and Programs in Biomedicine
Volume200
Early online date21 Nov 2020
DOIs
Publication statusPublished - Mar 2021

Bibliographical note

Funding Information:
The authors would like to acknowledge Prof. Fernando Cendes for the magnetic resonance imaging volumes and the anonymous reviewers whose comments and suggestions helped improve and clarify this manuscript. This research was supported by the FAPESP-Brazil grant #2013/07559-3 to the Research, Innovation and Dissemination Center BRAINN at the University of Campinas. Individually, J. A. I. Rubianes Silva was supported by the National Council for Scientific and Technological Development (CNPq) through 142018/2017-1. S. L. Novi Junior was supported by FAPESP through 2019/21962-1 and 2016/22990-0. N. G. S. R. de Souza was supported by PIBIC/CNPq. E. J. Forero was supported by Coordination for the Improvement of Higher Education Personnel (CAPES) through 88882.329008/2019-01. This work also received support from FAPESP #2012/02500-8 (R.C. Mesquita).

Publisher Copyright:
© 2020 Elsevier B.V.

Keywords

  • fNIRS
  • Image-guided placement system
  • Probe placement
  • Reproducibility of measures

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Health Informatics

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