Quantifying individualized deviations of brain structure in patients with multiple neurological diseases from normative references

Quantifying individualized deviations in the brain structure of patients with brain disorders from those of normal individuals is crucial for understanding disease pathology and guiding personalized management. In this study, we aimed to establish Chinese-specific normative references using 3D T1-weighted magnetic resonance images of 12,060 healthy controls (HCs) and to quantify the deviations in brain structure of 3,245 patients with multiple neurological diseases, including neurodegenerative diseases (mild cognitive impairment [n = 212], Alzheimer's disease [n = 467], and Parkinson's disease [PD, n = 1,263]), cerebrovascular disease (cerebral small vessel disease [n = 498]), and neuroinflammatory diseases (multiple sclerosis [MS, n = 497] and aquaporin-4 antibody-seropositive neuromyelitis optica spectrum disorder [NMOSD, n = 308]). The Chinese normative references exhibited a later peak age than those of previously reported references, which were mainly from European and North American populations, differing by 2.3 to 9.9 years. Distinct deviations in brain structural measures were observed among individuals with neurogenerative, cerebrovascular, and neuroinflammatory diseases. We subsequently performed three clinical tasks to assess the utility of individualized deviation scores. Task 1: We estimated the individual disease propensity score relative to that of HCs, with median scores ranging from 0.84 to 0.95. Task 2: We predicted the cognitive and physical scores of individuals with neurological diseases using cross-sectional data. The correlations between the predicted and actual scores ranged from 0.13 to 0.70. Task 3: In a longitudinal cohort, we analyzed the effects of different treatments on individuals with PD. Predictions of motor outcomes in PD patients receiving medication and deep brain stimulation showed correlations between predicted and actual variables ranging from 0.16 to 0.31. In addition, we stratified individuals with MS and NMOSD according to the predicted risks of disability progression. Comparative analyses demonstrated that deviation scores outperformed raw brain structural measures in disease propensity score estimation and risk stratification of neuroinflammatory patients. Longitudinal and sensitivity analyses confirmed the stability and robustness of deviation scores in individualized brain structure quantification. Finally, using these deviation scores, we created a clinically applicable individualized brain health report. In conclusion, the quantified individualized deviation scores derived from population-specific normative references can serve as a novel approach to understanding disease pathology and contribute to accurately personalized diagnosis and prognosis for various neurological diseases.