机构：[1]College of Polymer Science and Engineering, National Key Laboratory of Advanced Polymer Materials, Sichuan University, Chengdu 610065, China.[2]Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.四川大学华西医院[3]Nuclear Power Institute of China, Chengdu 610101, China.
Skin hemangioma is a tumor originating from skin blood vessels, which often occurs in infants and children. Brachytherapy with the 32P-based radionuclide applicator is an effective non-invasive therapeutic method. However, the inordinance of lesions is still the main challenge for precise local treatment and radiation protection of normal skins. A radionuclide applicator possessing advanced shape adaptability, favorable radionuclide biodistribution, optimized stress feature, and convenient preparation method is highly required for clinical practice. Herein, we present a customizable polyacrylamide (PAAm) hydrogel-based radionuclide applicator, integrating automatic lesion recognition via machine learning and 3D printing technology. The machine learning algorithm achieved a geometric accuracy of 98.78% in automated lesion contour recognition, providing guaranteed data support for 3D printing. The optimized hydrogel exhibited excellent mechanical properties (elastic modulus: 228 kPa, fracture toughness: 4.51 MJ m-3), rapid curing (<10 min), and promising 32P loading efficiency (>85%). Especially, this system greatly shortened the fabrication time while ensuring precise geometric matching for complex lesions. Through in vitro cell and in vivo tumor-bearing mouse models, the hydrogel loaded with 32P (P-HG) demonstrated favorable biocompatibility and effective therapeutic efficacy. It is believed that the synergy of intelligent recognition, 3D printing, and enhanced hydrogel performance can establish a promising treatment method with great practical potential for precise fitting brachytherapy of skin hemangioma.
基金：
This work was supported by the National Natural Science
Foundation of China (52003179), the joint innovation project
of Sichuan University and the Nuclear Power Institute of China
(HG2023131, HG2023156, and 22H1363), the State Key Laboratory
of Polymer Materials Engineering (no. sklpme2023-2-18),
the Natural Science Foundation of Sichuan Province
(2024NSFSC0240 and 2025NSFTD0011), and the Institutional
Research Fund from Sichuan University (2024SCUQJTX016).
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2025]版：
大类|3 区材料科学
小类|3 区材料科学：生物材料
最新[2025]版：
大类|3 区材料科学
小类|3 区材料科学：生物材料
第一作者：
第一作者机构：[1]College of Polymer Science and Engineering, National Key Laboratory of Advanced Polymer Materials, Sichuan University, Chengdu 610065, China.
共同第一作者：
通讯作者：
推荐引用方式(GB/T 7714)：
Wang Jingyu,Wang Rang,Chen Peng,et al.A customizable 32P hydrogel applicator for brachytherapy of skin hemangioma based on machine learning and 3D-printing[J].Journal Of Materials Chemistry. B.2025,doi:10.1039/d5tb00647c.
APA：
Wang Jingyu,Wang Rang,Chen Peng,Jiang Lisha,Luo Banggan...&Xu Yuanting.(2025).A customizable 32P hydrogel applicator for brachytherapy of skin hemangioma based on machine learning and 3D-printing.Journal Of Materials Chemistry. B,,
MLA：
Wang Jingyu,et al."A customizable 32P hydrogel applicator for brachytherapy of skin hemangioma based on machine learning and 3D-printing".Journal Of Materials Chemistry. B .(2025)
