Hybrid imaging system for developing novel neural contrast agents

Russell S Witte, Sheng Wen Huang, Shai Ashkenazi, Matthew O'Donnell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Neural contrast agents have a vast array of applications from molecular imaging to mapping membrane potential. We describe a hybrid neural recording system capable of ultrasonic, photoacoustic and optical imaging designed to develop and test the next-generation of neural contrast agents. Photoacoustic imaging (PA), in particular, provides optical contrast with good penetration and high spatial resolution, making it an attractive tool for noninvasive neural imaging. To demonstrate the system, we chose a commercial dye (NK2761) commonly used for optical imaging of neural tissue to enhance PA images of live lobster nerve cord. The abdominal segment was excised, stained and placed in a custom neural chamber. Photoacoustic and ultrasound images were collected using a clinical ultrasound scanner and a 10-MHz linear probe. A wavelength-tunable pulsed laser source (5 nsec, ̃15 mJ) operating at 20 Hz produced PA waves. Longitudinal scans of the nerve cord were collected and displayed every 7 seconds. Without a contrast agent, the peak PA signal was 5 dB over noise. An additional 29 dB was achieved after the nerve was submerged in dye for 20 minutes. The contrast enhancement was consistent with the measured optical absorbance of the stained nerve. Photoacoustic images approached 200-μm spatial resolution. The hybrid system provided several hours of imaging, electrical stimulation and recording, serving as a robust testbed for developing novel contrast for neural applications.

Original languageEnglish (US)
Title of host publicationProceedings of the 3rd International IEEE EMBS Conference on Neural Engineering
Pages229-232
Number of pages4
DOIs
StatePublished - 2007
Externally publishedYes
Event3rd International IEEE EMBS Conference on Neural Engineering - Kohala Coast, HI, United States
Duration: May 2 2007May 5 2007

Other

Other3rd International IEEE EMBS Conference on Neural Engineering
CountryUnited States
CityKohala Coast, HI
Period5/2/075/5/07

Fingerprint

Multimodal Imaging
Photoacoustic effect
Imaging systems
Contrast Media
Optical Imaging
Imaging techniques
Coloring Agents
Molecular Imaging
Membrane Potentials
Electric Stimulation
Noise
Ultrasonics
Ultrasonography
Lasers
Dyes
Molecular imaging
Testbeds
Hybrid systems
Pulsed lasers
Acoustic noise

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Neuroscience (miscellaneous)

Cite this

Witte, R. S., Huang, S. W., Ashkenazi, S., & O'Donnell, M. (2007). Hybrid imaging system for developing novel neural contrast agents. In Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering (pp. 229-232). [4227258] https://doi.org/10.1109/CNE.2007.369653

Hybrid imaging system for developing novel neural contrast agents. / Witte, Russell S; Huang, Sheng Wen; Ashkenazi, Shai; O'Donnell, Matthew.

Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering. 2007. p. 229-232 4227258.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Witte, RS, Huang, SW, Ashkenazi, S & O'Donnell, M 2007, Hybrid imaging system for developing novel neural contrast agents. in Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering., 4227258, pp. 229-232, 3rd International IEEE EMBS Conference on Neural Engineering, Kohala Coast, HI, United States, 5/2/07. https://doi.org/10.1109/CNE.2007.369653
Witte RS, Huang SW, Ashkenazi S, O'Donnell M. Hybrid imaging system for developing novel neural contrast agents. In Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering. 2007. p. 229-232. 4227258 https://doi.org/10.1109/CNE.2007.369653
Witte, Russell S ; Huang, Sheng Wen ; Ashkenazi, Shai ; O'Donnell, Matthew. / Hybrid imaging system for developing novel neural contrast agents. Proceedings of the 3rd International IEEE EMBS Conference on Neural Engineering. 2007. pp. 229-232
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