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Segmentation of Brain Metastases Using Background Layer Statistics (BLAST).

Chris Heyn1,2, Alan R Moody3,2, Chia-Lin Tseng4

  • 1From the Department of Medical Imaging (C.H., A.R.M., E.W., T.K., A.K., P.H., P.M., S.S.), Sunnybrook Health Sciences Center, Toronto, Ontario, Canada chris.heyn@utoronto.ca.

AJNR. American Journal of Neuroradiology
|September 21, 2023
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Summary

Background Layer Statistics (BLAST) offers accurate and reproducible segmentation of brain metastases. This semiautomated algorithm shows potential for improving radiation planning and treatment response evaluation.

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Area of Science:

  • Medical imaging analysis
  • Neurosurgery and oncology
  • Radiology and radiation therapy

Background:

  • Accurate segmentation of brain metastases is crucial for effective treatment planning and response assessment.
  • Current segmentation methods may have limitations in precision and efficiency.
  • Novel algorithms are needed to improve the accuracy and speed of brain metastases segmentation.

Purpose of the Study:

  • To evaluate the performance of a semiautomated algorithm, Background Layer Statistics (BLAST), for segmenting brain metastases.
  • To assess the accuracy, reproducibility, and clinical acceptance of BLAST-generated segmentations.

Main Methods:

  • A semiautomated segmentation algorithm (BLAST) was applied to 48 brain metastases in 19 patients.
  • K-means clustering identified normal brain tissue, which was then subtracted.
  • Operator-defined thresholds segmented metastases; Dice-Sørensen coefficient and Hausdorff distance measured accuracy.
  • Clinical acceptance was assessed using a 5-point Likert scale.

Main Results:

  • The median Dice-Sørensen coefficient was 0.82 (0.9 for metastases ≥10 mm), indicating high accuracy.
  • Median Hausdorff distance was 1.4 mm, demonstrating precise boundary delineation.
  • Excellent interreader agreement (ICC=0.9978) and high clinical acceptance (94% Likert score 4 or 5) were observed.
  • Median segmentation time was 2.8 minutes per metastasis.

Conclusions:

  • Background Layer Statistics (BLAST) provides accurate and reproducible segmentation of brain metastases.
  • The algorithm demonstrates significant potential as a valuable tool for radiation oncology planning.
  • BLAST facilitates precise evaluation of treatment response in patients with brain metastases.