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Non-invasive Parenchymal, Vascular and Metabolic High-frequency Ultrasound and Photoacoustic Rat Deep Brain Imaging
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Label-free intraoperative imaging of hemodynamics using deep learning.

Yan Shi1, Denghui Zhao1, Jingyi Yu1

  • 1School of Biomedical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, China.

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|April 13, 2026
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Summary

This study introduces a novel label-free imaging method for real-time hemodynamic assessment during surgery. The technique significantly reduces imaging time and enhances visualization of blood flow, improving surgical guidance.

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Area of Science:

  • Medical Imaging
  • Biomedical Engineering
  • Neurosurgery

Background:

  • Intraoperative hemodynamic visualization is vital for surgical decisions.
  • Current standard, indocyanine green fluorescence imaging (ICG-FI), has limitations including time, waiting periods, and potential reactions.
  • Label-free methods like LSCI and WLI lack arterial-venous differentiation and flow directionality.

Purpose of the Study:

  • To develop a label-free imaging framework for synthesizing mean transition time (MTT) maps.
  • To enable real-time hemodynamic assessment, including artery-vein differentiation and flow direction inference.
  • To overcome limitations of existing intraoperative imaging techniques.

Main Methods:

  • A cross-modal generation framework was developed to synthesize MTT maps from laser speckle contrast imaging (LSCI) and white light imaging (WLI).
  • The framework was experimentally validated in rat brains.
  • The synthesized MTT maps were analyzed for vasculature delineation, artery-vein differentiation, and blood flow direction.

Main Results:

  • The proposed method successfully generated clear vasculature maps.
  • Accurate differentiation between arteries and veins was achieved.
  • Reliable blood flow direction decoding was demonstrated.
  • Total imaging time was reduced by 95.8% compared to conventional ICG protocols.

Conclusions:

  • The label-free cross-modal generation framework provides a fast and efficient solution for intraoperative hemodynamic assessment.
  • This approach offers contrast-free, continuous surgical guidance.
  • It overcomes key limitations of ICG-FI, enhancing surgical decision-making.