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Rapid Path Planning Algorithm for Percutaneous Rigid Needle Biopsy Based on Optical Illumination Principles.

Jian Liu1, Shuai Kang2, Juan Ren2

  • 1School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 201100, China.

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Summary

This study presents a novel computer-aided method for rapid and accurate biopsy needle trajectory planning. The approach significantly reduces planning time, enhancing safety and efficiency in medical procedures.

Keywords:
biopsy path planningclinical evaluationgraphics processing unit (GPU) optimizationmachine learningoptical accelerationsegmentation

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Area of Science:

  • Medical Imaging and Image-Guided Interventions
  • Computational Anatomy and Biomechanics
  • Surgical Planning and Navigation

Background:

  • Accurate needle trajectory planning is crucial for biopsy procedures, relying on preoperative CT imaging.
  • Traditional methods are time-consuming and struggle with complex anatomical structures, increasing risks.
  • Delays in planning can lead to patient movement, invalidating planned trajectories.

Purpose of the Study:

  • To develop a novel, rapid, and accurate method for biopsy needle trajectory planning.
  • To reframe trajectory planning as an optimal puncture site identification problem using optical principles and computer rendering.
  • To create a decision-support tool that improves biopsy safety and efficiency.

Main Methods:

  • Reconstruction of 3D anatomical models from CT images and segmentation using SegResNet.
  • Simulation of a virtual light source and diffuse reflection to generate a skin surface grayscale map of candidate puncture sites.
  • Application of a random forest model to analyze the grayscale distribution and select the optimal needle path and entry point.

Main Results:

  • Achieved an average computation time of 1.905 seconds per sample, significantly faster than traditional methods.
  • Clinical assessment by a thoracic surgeon indicated that 78% of recommended paths met clinical standards, with 0% unsatisfactory.
  • The method demonstrated high accuracy in anatomical model segmentation (average Dice similarity coefficient of 0.9122).

Conclusions:

  • The novel method offers a rapid, intuitive, and reliable decision-support tool for biopsy trajectory planning.
  • This approach enhances the safety and efficiency of percutaneous biopsy procedures.
  • The findings suggest a significant advancement in computer-aided surgical planning for minimally invasive interventions.