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Automatic bone marrow segmentation for precise [177Lu]Lu-PSMA-617 dosimetry.

Zhonglin Lu1,2, Jiaxi Hu3, Gefei Chen1

  • 1Biomedical Imaging Laboratory (BIG), Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China.

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|February 12, 2025
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Summary

X-means clustering effectively segments bone marrow (BM) in [177Lu]Lu-PSMA-617 therapy, improving personalized dosimetry and showing better correlation with blood count changes than other methods.

Keywords:
SPECT/CT[177Lu]Lu‐PSMA‐617bone marrowdosimetrysegmentation

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Area of Science:

  • Nuclear Medicine
  • Medical Physics
  • Radiotherapy

Background:

  • Bone marrow (BM) is a critical dose-limiting organ in [177Lu]Lu-PSMA-617 therapy for metastatic castration-resistant prostate cancer.
  • Accurate BM dosimetry is challenging due to difficulties in image segmentation.

Purpose of the Study:

  • To develop an automated image-based segmentation method for personalized bone marrow dosimetry.
  • Utilize peri-therapeutic sequential [177Lu]Lu-PSMA-617 SPECT/CT images.

Main Methods:

  • Applied X-means clustering on deep learning-segmented lumbar spine CT images to classify BM regions.
  • Compared X-means clustering with single threshold, empirical sphere segmentation, and manual segmentation (gold standard).
  • Evaluated segmentation accuracy using Dice similarity coefficient and assessed BM mean absorbed dose (Dmean) errors and Bland-Altman analysis.

Main Results:

  • X-means clustering achieved a higher average Dice similarity coefficient (0.76 ± 0.18) compared to the single threshold method (0.61 ± 0.19).
  • X-means clustering demonstrated significantly lower mean absolute BM Dmean errors (25.34 ± 64.48%) and smaller Dmean differences (0.0330 Gy) versus the gold standard.
  • Stronger correlations (r ≤ -0.65) were observed between BM Dmean (from X-means clustering and gold standard) and changes in platelets/WBC.

Conclusions:

  • X-means clustering is a feasible and advantageous method for segmenting bone marrow from peri-therapy SPECT/CT images.
  • This approach offers improved accuracy for personalized bone marrow dosimetry in [177Lu]Lu-PSMA-617 therapy compared to existing methods.