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Intraoperative blood vessel detection and quantification: a Monte Carlo study.

Amal Chaturvedi1, Shetha A Shukair1, Mayank Vijayvergia1

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Minimally invasive surgery (MIS) lacks tactile feedback, risking accidental blood vessel cuts. New laparoscopic graspers with near-infrared sensors can now detect hidden blood vessels, improving surgical safety.

Keywords:
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Area of Science:

  • Biomedical Engineering
  • Surgical Technology

Background:

  • Minimally invasive surgery (MIS) offers benefits like faster recovery and reduced scarring.
  • A key limitation of MIS is the loss of tactile feedback, preventing surgeons from palpating blood vessels.
  • Accidental intraoperative blood vessel injury during MIS can lead to severe complications.

Purpose of the Study:

  • To develop a novel method for detecting hidden blood vessels during MIS.
  • To enhance the safety of laparoscopic procedures by identifying subsurface vasculature.

Main Methods:

  • Integration of a near-infrared (NIR) light-emitting diode (LED) and a photodiode onto laparoscopic grasper jaws.
  • Utilizing Monte Carlo simulations to model light interaction with tissue and blood vessels.
  • Quantifying the detection capabilities for blood vessels of varying sizes and depths.

Main Results:

  • The developed laparoscopic graspers can detect blood vessels ranging from 3 to 6 mm in diameter.
  • Detection is feasible for vessels buried under up to 1 cm of tissue.
  • Monte Carlo simulations support the theoretical basis for this detection technology.

Conclusions:

  • This technology offers a potential solution to the challenge of subsurface blood vessel identification in MIS.
  • Adding NIR detection capabilities to existing laparoscopic tools can significantly improve surgical safety.
  • Further development could lead to widespread adoption in minimally invasive procedures.