TY - JOUR
T1 - Spatial–Texture Hybrid MRI Model for Orbital Lymphoma Typing
AU - Li, Lunhao
AU - Wei, Lai
AU - Shi, Jiahao
AU - Zhai, Guangtao
AU - Hu, Menghan
AU - Zhou, Yixiong
N1 - Publisher Copyright:
© 2025 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH.
PY - 2025/5
Y1 - 2025/5
N2 - The ability to distinguish between mucosa-associated lymphoid tissue (MALT) and non-MALT orbital lymphomas aids ophthalmologists in opting for either conservative or aggressive treatment strategies. Radiographic assessment is a noninvasive approach to diagnose orbital lesions. This study aims to develop a hybrid model leveraging magnetic resonance imaging scans to discern between MALT and non-MALT orbital lymphomas. The occupation of the tumor alters the relative positions of structures in the orbit. Hence, for the first time, the relative spatial positional features are extracted between different orbital structures and the tumor, complemented by the texture characteristics of the tumor area, to perform hybrid modeling. To validate this idea, 114 orbital lymphoma patients were are included. Statistical analysis reveals significant differences between the two groups in terms of four spatial features (lymphoma lesion, eyeball, inferior rectus, and optic nerve) and two texture features (angular second moment and contrast). The accuracy of the classifier based on spatial, texture, and hybrid features is 84.7, 83.1, and 88.3%, respectively. The innovative hybrid model offers a supportive approach for the differentiation of MALT and non-MALT orbital lymphomas, enhancing the clinical decision-making process. To facilitate the use of this hybrid model, a web-based diagnostic tool has been launched at https://ads.testop.top.
AB - The ability to distinguish between mucosa-associated lymphoid tissue (MALT) and non-MALT orbital lymphomas aids ophthalmologists in opting for either conservative or aggressive treatment strategies. Radiographic assessment is a noninvasive approach to diagnose orbital lesions. This study aims to develop a hybrid model leveraging magnetic resonance imaging scans to discern between MALT and non-MALT orbital lymphomas. The occupation of the tumor alters the relative positions of structures in the orbit. Hence, for the first time, the relative spatial positional features are extracted between different orbital structures and the tumor, complemented by the texture characteristics of the tumor area, to perform hybrid modeling. To validate this idea, 114 orbital lymphoma patients were are included. Statistical analysis reveals significant differences between the two groups in terms of four spatial features (lymphoma lesion, eyeball, inferior rectus, and optic nerve) and two texture features (angular second moment and contrast). The accuracy of the classifier based on spatial, texture, and hybrid features is 84.7, 83.1, and 88.3%, respectively. The innovative hybrid model offers a supportive approach for the differentiation of MALT and non-MALT orbital lymphomas, enhancing the clinical decision-making process. To facilitate the use of this hybrid model, a web-based diagnostic tool has been launched at https://ads.testop.top.
KW - hybrid models
KW - magnetic resonance imaging
KW - mucosa-associated lymphoid tissues
KW - orbital lymphomas
KW - radiomics
UR - https://www.scopus.com/pages/publications/85219021691
U2 - 10.1002/aisy.202400595
DO - 10.1002/aisy.202400595
M3 - 文章
AN - SCOPUS:85219021691
SN - 2640-4567
VL - 7
JO - Advanced Intelligent Systems
JF - Advanced Intelligent Systems
IS - 5
M1 - 2400595
ER -