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• Clinical Article •
Construction of a nomogram for predicting cerebral small-vessel disease-related cognitive impairment by combining MRI imaging biomarkers and serum biochemical biomarkers
YANG Li  CHEN Ran  LU Wenli  ZHU Shengnan  ZHANG Jinshuo  JI Liya  LI Cheng  ZHOU Dan 

Cite this article as: YANG L, CHEN R, LU W L, et al. Construction of a nomogram for predicting cerebral small-vessel disease-related cognitive impairment by combining MRI imaging biomarkers and serum biochemical biomarkers[J]. Chin J Magn Reson Imaging, 2026, 17(10): 55-62, 133. DOI:10.12015/issn.1674-8034.2026.10.007.


[Abstract] Objective To explore the independent risk factors for cerebral small vessel disease (CSVD)-related cognitive impairment, develop a nomogram prediction model for risk stratification of cognitive impairment in CSVD patients, and evaluate its discriminative ability, calibration performance and clinical decision-making value.Materials and Methods A total of 108 right-handed patients with CSVD (total imaging burden score ≥ 1) were enrolled in accordance with the 2021 Chinese Expert Consensus on the Diagnosis and Treatment of Cerebral Small Vessel Disease. Brain imaging data were acquired using a 3.0 T MRI scanner, and multidimensional variables including the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index and total imaging burden score were collected. Combined with demographic, clinical, and laboratory parameters, univariate logistic regression was performed to screen potential risk factors, followed by multivariate logistic regression to identify independent risk factors. A nomogram prediction model was established using R software. The model was comprehensively validated in terms of discriminative ability, calibration, and clinical utility via the concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA).Results Univariate logistic regression analysis demonstrated that homocysteine level, DTI-ALPS index, total imaging burden score, age, sex,systolic blood pressure, low-density lipoprotein cholesterol, triglyceride, serum creatinine, and drinking history were significantly associated with the development of CSVD-related cognitive impairment (all P < 0.05). Multivariate logistic regression further confirmed that homocysteine (OR = 1.507, 95% CI: 1.117 to 2.033, P = 0.007), DTI-ALPS index (OR = 0.008, 95% CI: 0.000 to 0.272, P = 0.007), and total imaging burden score (OR = 19.126, 95% CI: 2.700 to 135.467, P = 0.003) were independent risk factors. The newly constructed nomogram model yielded an AUC of 0.955 (95% CI: 0.920 to 0.990), which was superior to the predictive efficacy of each individual indicator. The calibration curves showed excellent consistency with the ideal curve, and the C-index of the model was 0.955 (95% CI: 0.920 to 0.990), indicating favorable stability and reliability. DCA analysis confirmed that the nomogram has favorable clinical decision-making application value.Conclusions Elevated serum homocysteine, decreased DTI-ALPS index, and increased total imaging burden score are core independent risk factors for CSVD-related cognitive impairment. The established nomogram model integrates laboratory and neuroimaging indicators, exhibiting excellent discrimination, favorable predictive accuracy, and robust clinical effectiveness. This model can rapidly quantify the individual risk of cognitive impairment in CSVD patients, thereby providing a reliable reference for early clinical screening, risk stratification, and individualized intervention.
[Keywords] cerebral small vessel disease；cognitive dysfunction；risk factor；predictive model；nomogram；magnetic resonance imaging

YANG Li   CHEN Ran   LU Wenli   ZHU Shengnan   ZHANG Jinshuo   JI Liya   LI Cheng   ZHOU Dan*  

Department of Radiology, Nanjing BenQ Medical Center, the Affiliated BenQ Hospital of Nanjing Medical University, Nanjing 210019, China

Corresponding author: ZHOU D, E-mail: daniezhou@126.com

Conflicts of interest   None.

Received  2026-05-28
Accepted  2026-09-22
DOI: 10.12015/issn.1674-8034.2026.10.007
Cite this article as: YANG L, CHEN R, LU W L, et al. Construction of a nomogram for predicting cerebral small-vessel disease-related cognitive impairment by combining MRI imaging biomarkers and serum biochemical biomarkers[J]. Chin J Magn Reson Imaging, 2026, 17(10): 55-62, 133. DOI:10.12015/issn.1674-8034.2026.10.007.

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