|
1
|
Tang Y, Zhu H, Xiao L, Li R, Han H, Tang W, Liu D, Zhou C, Liu D, Yang Z, Zhou L, Xiao B, Rominger A, Shi K, Hu S, Feng L. Individual cerebellar metabolic connectome in patients with MTLE and NTLE associated with surgical prognosis. Eur J Nucl Med Mol Imaging 2024; 51:3600-3616. [PMID: 38805089 DOI: 10.1007/s00259-024-06762-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/12/2024] [Indexed: 05/29/2024]
Abstract
PURPOSE This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes. METHODS This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients. RESULTS Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis. CONCLUSION The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.
Collapse
Affiliation(s)
- Yongxiang Tang
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Haoyue Zhu
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, PR China
| | - Ling Xiao
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China
| | - Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Honghao Han
- The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China
| | - Weiting Tang
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, PR China
| | - Ding Liu
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Chunyao Zhou
- Department of Neurosurgery, Xiangya Hospital, Central Southern University, Changsha, China
| | - Dingyang Liu
- Department of Neurosurgery, Xiangya Hospital, Central Southern University, Changsha, China
| | - Zhiquan Yang
- Department of Neurosurgery, Xiangya Hospital, Central Southern University, Changsha, China
| | - Luo Zhou
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, PR China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, PR China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
- Department of Informatics, Technische Universität München, Munich, Germany
| | - Shuo Hu
- Department of Nuclear Medicine, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
- Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, Changsha, Hunan, China.
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, 87 Xiangya Rd, Changsha, 410008, PR China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
| |
Collapse
|
|
2
|
Zhang L, Qu J, Ma H, Chen T, Liu T, Zhu D. Exploring Alzheimer's disease: a comprehensive brain connectome-based survey. PSYCHORADIOLOGY 2024; 4:kkad033. [PMID: 38333558 PMCID: PMC10848159 DOI: 10.1093/psyrad/kkad033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/21/2023] [Accepted: 01/03/2024] [Indexed: 02/10/2024]
Abstract
Dementia is an escalating global health challenge, with Alzheimer's disease (AD) at its forefront. Substantial evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network, leading to disruptions in both individual brain regions and their interconnections. Although a comprehensive understanding of the neurodegeneration-brain network link is lacking, it is undeniable that brain networks play a pivotal role in the development and progression of AD. To thoroughly elucidate the intricate network of elements and connections constituting the human brain, the concept of the brain connectome was introduced. Research based on the connectome holds immense potential for revealing the mechanisms underlying disease development, and it has become a prominent topic that has attracted the attention of numerous researchers. In this review, we aim to systematically summarize studies on brain networks within the context of AD, critically analyze the strengths and weaknesses of existing methodologies, and offer novel perspectives and insights, intending to serve as inspiration for future research.
Collapse
Affiliation(s)
- Lu Zhang
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Junqi Qu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Haotian Ma
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Tong Chen
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Tianming Liu
- Department of Computer Science, The University of Georgia, Athens, GA 30602, USA
| | - Dajiang Zhu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| |
Collapse
|