Work

Hypo-segmentation of 18F-BPA PET-based boron distribution: a pragmatic approach for efficient BNCT treatment planning

Year: 2025

Type: article

Abstract: Precise modeling of boron distribution is essential for boron neutron capture therapy (BNCT) dose calculation. While full-three-dimensional (f3D) voxel modeling of ¹⁸F-BPA PET data offers high spatial resolution, its clinical value is limited by intrinsic image resolution—especially PET—and by registration errors in multi-modality image fusion. These factors constrain the reliability of voxel-level dose interpretation and increase computational burden. We propose a hypo-segmentation (hS) method that groups target tissue-to-blood ratio (TBR) values into 0.5-unit intervals to approximate boron distribution. This study retrospectively evaluated four malignant brain tumor cases, comparing dosimetric metrics derived from hS and f3D approaches. Key dose-volume parameters (D mean , D 80 , V 14 Gy−Eq ), spatial agreement (gamma pass rate), and dose–volume curve similarity (dynamic time warping, DTW) were assessed. Dose consistency in normal brain tissue was also evaluated using D 0.1 cc , D mean , and V 13 Gy−Eq . The hS method showed strong agreement with f3D results: within 2% for tumor D mean , 3% for D 80 , and 5% for V 14 Gy−Eq . Gamma pass rates exceeded 90% in three of four cases. In brain tissue, dose deviations between hS and f3D remained within 2%, demonstrating reliability even in low-uptake, spatially uniform regions. A single small, heterogeneous tumor showed larger discrepancy (D 95 deviation = 14.3%, gamma pass rate = 82%), which was mitigated by refining segmentation (h = 0.25). The hS method offers a clinically practical and computationally efficient alternative to full voxel-wise modeling. It preserves dosimetric fidelity in both tumor and normal brain regions, while aligning with the intrinsic resolution of PET and multimodal imaging. This approach supports accurate yet streamlined BNCT dose planning, particularly in clinical settings where ultra-high spatial granularity provides limited added value. ChiCTR2200066473, registered on December 16, 2022.

Source: EJNMMI Research

DOI: 10.1186/s13550-025-01341-4

Authors: Yi-Chiao Teng, Jiang Chen, Wan-Bing Zhong, Qin Lin, Yuan-Hao Liu

Institutions: First Affiliated Hospital of Xiamen University, Nanjing University of Industry Technology, Neuboron (China), Nanjing University of Aeronautics and Astronautics

Language: English

Topic: Boron Compounds in Chemistry

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,190