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An automatic method for PET target segmentation using a lookup table based on volume and concentration ratio.

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  • 1Department of Radiation Oncology, Case Western Reserve University, School of Medicine B181, 11000 Euclid Avenue, Cleveland, OH 44106, USA. yiran.zheng@case.edu

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Area of Science:

  • Medical Imaging
  • Radiation Oncology
  • Image Segmentation

Background:

  • Accurate target volume delineation is crucial for effective radiation therapy planning.
  • Current methods often rely on scanner-specific calibration or complex fitting curves.
  • Standardization and accuracy in PET/CT volumetrics are needed for consistent treatment planning.

Purpose of the Study:

  • To develop a rapid, accurate, and scanner-independent PET image segmentation method for target volume assessment.
  • To create a universal thresholding approach for radiation therapy planning.
  • To evaluate the method's accuracy using phantom studies and clinical application in lung metastases.

Main Methods:

  • A three-step segmentation method utilizing PET image intensity information alone was developed.
  • Involved mean intensity segmentation, partial volume effect compensation using recovery coefficient curves, and a threshold lookup table.
  • A level set method refined the target contour, reducing global thresholding limitations.

Main Results:

  • The method achieved consistent segmentation for spheres >2.5 mL with an average uncertainty of 11.2% in phantom studies.
  • Segmented volumes showed comparable accuracy to contrast-oriented and iterative threshold methods.
  • Clinical application in ten patients demonstrated PET segmented volumes within 8.0% of CT volumes.

Conclusions:

  • The developed PET segmentation method offers accurate and universal application in radiation therapy planning.
  • It eliminates the need for fitted threshold curves or prior knowledge of CT/MRI target volumes.
  • The method is valuable for rapid identification and assessment of plans with multiple targets.