DCRU-Net-based three-dimensional in vivo dose reconstruction method for limited-view radiation-induced acoustic imaging(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2026年第4期
- Page:
- 421-429
- Research Field:
- 医学放射物理
- Publishing date:
Info
- Title:
- DCRU-Net-based three-dimensional in vivo dose reconstruction method for limited-view radiation-induced acoustic imaging
- Author(s):
- ZHAO Xinxin1; WANG Xinyi1; DU Yinda1; CHEN Boyong1; ZHOU Linghong1; LI Yongbao2; SONG Ting1
- 1. School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China 2. Sun Yat-sen University Cancer Center/State Key Laboratory of Oncology in South China/Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China
- Keywords:
- Keywords: radiation-induced acoustic imaging three-dimensional in vivo dose monitoring back-projection reconstruction limited-view deep learning
- PACS:
- R318；R811.1
- DOI:
- DOI:10.3969/j.issn.1005-202X.2026.04.001
- Abstract:
- Abstract: Objective A novel three-dimensional (3D) in vivo dose reconstruction method based on a deep cascaded residual U-Net (DCRU-Net) is proposed to address the issues of image distortion and artifacts in limited-view radiation-induced acoustic (RA) imaging for online dose monitoring, thereby improving the accuracy of dose monitoring. Methods A DCRU-Net was constructed ?o achieve the complex mapping from limited-view acoustic signals to dose distribution through stepwise optimization. The first-stage sub-network took the initial pressure map reconstructed by back-projection (BP) as input, aiming to recover the missing acoustic information and reconstruct a full-view 3D pressure field. The second-stage sub-network further corrected errors and refined features based on physical conversion, generating a high-precision 3D dose map. Based on the clinical CT and planned dose data from 80 prostate cancer patients, the k-Wave toolbox was adopted to simulate limited-view RA signals acquired by a two-dimensional transducer array in the perineal region, with consideration of tissue heterogeneity, acoustic velocity variations, and noise. The relative root mean square error (rRMSE), structural similarity index (SSIM), and Gamma pass rate were taken as the primary evaluation metrics. Results Qualitative analysis demonstrated that the DCRU-Net effectively eliminated distortion and artifacts caused by limited-view acquisition, with reconstructed results showing high consistency with the ground truth maps. Quantitative evaluation revealed that the predicted pressure maps and dose maps achieved rRMSE of 3.40% and 2.50%, respectively, and the dose maps achieved an SSIM of 0.98. Under the 3%/5 mm criterion, the Gamma pass rates at 0% and 70% threshold conditions were 98.18% and 99.32%, respectively. Furthermore, the proposed method exhibited strong stability across different noise levels. Conclusion The proposed method realizes efficient and high-precision 3D dose reconstruction from limited-view data, and overcomes the practical clinical limitation of restricted transducer coverage, providing a significant technical approach for the application of RA imaging in real-time in vivo dose monitoring.
Last Update: 2026-04-28