Affiliation:
1. School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China
2. Department of Radiology, The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University, Changzhou 213003, China
Abstract
Patients with end-stage renal disease (ESRD) experience changes in both the structure and function of their brain networks. In the past, cognitive impairment was often classified based on connectivity features, which only reflected the characteristics of the binary brain network or weighted brain network. It exhibited limited interpretability and stability. This study aims to quantitatively characterize the topological properties of brain functional networks (BFNs) using multi-threshold derivative (MTD), and to establish a new classification framework for end-stage renal disease with mild cognitive impairment (ESRDaMCI). The dynamic BFNs (DBFNs) were constructed and binarized with multiple thresholds, and then their topological properties were extracted from each binary brain network. These properties were then quantified by calculating their derivative curves and expressing them as multi-threshold derivative (MTD) features. The classification results of MTD features were compared with several commonly used DBFN features, and the effectiveness of MTD features in the classification of ESRDaMCI was evaluated based on the classification performance test. The results indicated that the linear fusion of MTD features improved classification performance and outperformed individual MTD features. Its accuracy, sensitivity, and specificity were 85.98 ± 2.92%, 86.10 ± 4.11%, and 81.54 ± 4.27%, respectively. Finally, the feature weights of MTD were analyzed, and MTD-cc had the highest weight percentage of 28.32% in the fused features. The MTD features effectively supplemented traditional feature quantification by addressing the issue of indistinct classification differentiation. It improved the quantification of topological properties and provided more detailed features for diagnosing cognitive disorders.
Funder
National Natural Science Foundation of China
Jiangsu Provincial Key Research and Development Program
Qing Lan Project of Jiangsu Province
Reference47 articles.
1. Abnormal degree centrality in neurologically asymptomatic patients with end-stage renal disease: A resting-state fMRI study;Li;Clin. Neurophysiol. Off. J. Int. Fed. Clin. Neurophysiol.,2016
2. Clinical and pathophysiological aspects of neurological complications in renal failure;Saxena;Acta Neurol. Belg.,1992
3. Ma, X.F., Jiang, G.H., Li, S.M., Wang, J.H., Zhan, W.F., Zeng, S.Q., Tian, J.Z., and Xu, Y.K. (2015). Aberrant functional connectome in neurologically asymptomatic patients with end-stage renal disease. PLoS ONE, 10.
4. Dementia and cognitive impairment in ESRD: Diagnostic and therapeutic strategies;Tamura;Kidney Int.,2011
5. Depression on dialysis;Chilcot;Nephron Clin. Pract.,2008