Affiliation:
1. Yantai Affiliated Hospital of Binzhou Medical University
2. The Second Hospital of Jiaxing
3. Henan Province Hospital of Traditional Chinese Medicine, The Second Afiliated Hospital of Henan University of Chinese Medicine
4. Yuhuangding Hospital
Abstract
Abstract
Background: Coronavirus disease 2019 (COVID-19) is a respiratory disease, but it also affects brain function. The use of resting-state functional MRI (rs_fMRI) technology to study COVID-19 patients has not been thoroughly explored. To investigate the effects of COVID-19 on brain functional activity and pave the way for a deeper understanding and future research.
Methods: fMRI scans were conducted on a cohort of 42 confirmed COVID-19-positive patients and 46 healthy controls (HCs) to assess brain functional activity. A combination of dynamic and static amplitude of low-frequency fluctuations (dALFF/sALFF) and functional connectivity (dFC/sFC) was used for evaluation. Abnormal brain regions identified were then used as feature inputs in the model to evaluate support vector machine (SVM) capability in recognizing COVID-19 patients. Moreover, the random forest (RF) model was employed to verify the stability of SVM diagnoses for COVID-19 patients.
Results: Compared to HCs, COVID-19 patients exhibited a decrease in sALFF in the right lingual gyrus and the left medial occipital gyrus, and an increase in dALFF in the right straight gyrus. Moreover, there was a decline in sFC between both lingual gyri and the right superior occipital gyrus and a reduction in dFC with the precentral gyrus. The dynamic and static combined ALFF and FC could distinguish between COVID-19 patients and the HCs with an accuracy of 0.885, a specificity of 0.818, a sensitivity of 0.933, and an AUC of 0.909.
Conclusion: The combination of dynamic and static ALFF and FC can provide information for detecting brain functional abnormalities in COVID-19 patients.
Publisher
Research Square Platform LLC