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Related Experiment Video

Updated: Jul 3, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

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Three-dimensional prostate position estimation with a single x-ray imager utilizing the spatial probability density.

Per Rugaard Poulsen1, Byungchul Cho, Katja Langen

  • 1Department of Radiation Oncology, Stanford University, Stanford, CA, USA. ppoulsen@stanford.edu

Physics in Medicine and Biology
|July 29, 2008
PubMed
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This study presents a new probability-based method to estimate 3D tumor motion from 2D X-ray images in radiotherapy, improving accuracy for monoscopic imaging systems.

Area of Science:

  • Medical Physics
  • Radiotherapy Technology
  • Image-Guided Interventions

Background:

  • Target motion during radiotherapy requires management via margins or intrafraction monitoring.
  • Stereoscopic imaging offers 3D position but is not widely available.
  • Monoscopic imaging provides 2D projections, necessitating estimation of the unobserved motion component.

Purpose of the Study:

  • To develop and validate a probability-based method for estimating the 3D target position from 2D monoscopic X-ray images.
  • To quantify the accuracy and uncertainty of this estimation method.

Main Methods:

  • Developed a mathematical framework using a 3D Gaussian probability density to estimate unresolved motion from projected motion.
  • Simulated monoscopic imaging of prostate motion using a dataset of 536 patient tracks.

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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
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Last Updated: Jul 3, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

  • Compared estimated 3D tracks with actual tracks to determine root-mean-square error.

    • Main Results:

    • The probability-based method reduced population root-mean-square error from 1.59 mm to 1.11 mm for vertical imaging.
    • Accuracy was limited by estimation uncertainty in continuous imaging.
    • Improvement was most significant for tracks with large unresolved motion.

    Conclusions:

    • The developed method effectively estimates 3D target position from 2D projections in monoscopic imaging.
    • This approach enhances radiotherapy accuracy, particularly for challenging motion cases.
    • The method offers a viable solution for systems lacking stereoscopic imaging capabilities.