Meningeal lymphatic dysfunction in sporadic cerebral small vessel diseases and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy by DCE-MRI

Abstract

Background: The distinction between cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), a prevalent hereditary cerebrovascular disease, and sporadic cerebrovascular disease has sparked significant interest among researchers. Meningeal lymphatic vessels (mLVs) have become a new research topic in recent years. This study aimed to investigate the function of meningeal lymphatics in cerebral small vessel disease (CSVD) and to develop a predictive model to assist in the diagnosis of CADASIL patients.

Methods: We systematically examined the functional changes in the meningeal lymphatic system in both sporadic CSVD patients and CADASIL patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and the correlations among blood biomarkers were subsequently calculated. Finally, a nomogram was generated for the identification of CADASIL using multiple significant risk factors.

Results: This study enrolled 41 sporadic CSVD (S-CSVD) patients, 15 CADASIL patients, and 18 normal controls (NC). Both CSVD and CADASIL groups demonstrated mLVs dysfunction compared to controls, characterized by decreased mLVs wash-in rates (P<0.05) and prolonged time-to-peak (TTP, P<0.01). Significant metabolic correlations emerged specifically in CSVD: In the S-CSVD group, the parameters of DCE-MRI [wash-in rate, TTP, incremental area under the curve (IAUC), transfer rate constant (Ktrans), extravascular extracellular volume fraction (Ve)] correlated with total cholesterol (TC, TTP, r=-0.38), low-density lipoprotein cholesterol (LDL-C, TTP, r=-0.41), serum creatinine (SCr, Ktrans, r=0.34), uric acid (UA, Ve, r=0.34), homocysteine (Hcy, wash-in, r=-0.31, both P<0.05), and hemoglobin A1c (HbA1c, wash-in; r=-0.32, P<0.01, IAUC; r=-0.47, P<0.01). In the CADASIL group, the parameter of DCE-MRI correlated with folic acid (FA, TTP, r=-0.57, P=0.03), SCr (IAUC; r=0.54, P=0.04, Ktrans; r=0.45, P=0.01, Ve; r=0.61, P<0.01), and UA (Ktrans; r=0.45, Ve; r=0.71, both P<0.05). Additionally, we identified several critical risk factors for diagnosing CADASIL and developed a nomogram to differentiate CADASIL from S-CSVD (area under the curve 0.870, 95% confidence interval: 0.767-0.973).

Conclusions: This study confirmed that mLVs were dysfunctional in both S-CSVD patients and CADASIL patients. IAUC was identified as a key risk factor, and a nomogram was generated. This research enhances our understanding of the role of mLVs in CSVD and contributes to distinguishing between these S-CSVD and CADASIL.

Keywords: Cerebral small vessel disease (CSVD); dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI); meningeal lymphatic system; nomogram.

Figure 1

Flowchart of patient selection. CADASIL, cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy; CSVD, cerebral small vessel disease; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; NC, normal control.

Figure 2

Quantitative assessment of mLVs-SSS flow by DCE-MRI. (A) Representative DCE-MRI images of mLVs after administration of gadopentetate dimeglumine. The upper red rectangle represents the left, right and lower mLVs-SSS (L, R, Lo-mLVs-SSS) and lower red rectangle represents mLVs-SS (L-, R-, Lo-mLVs-SS) in the NC, S-CSVD, and H-CSVD groups. (B-D) Representative TICs of mLVs-SSS and mLVs-SS in the NC, S-CSVD, and H-CSVD groups. (E-J) The quantification of average wash-in rate value (E,F), average TTP value (G,H), and average IAUC value (I,J) of mLVs (mLVs-SSS, mLVs-SS) among the NC (n=18), S-CSVD (n=41) and H-CSVD (n=15) groups (Kruskal-Wallis test with Dunn’s multiple comparison test); *, P<0.05; **, P<0.01. A.U., arbitrary units; CSVD, cerebral small vessel disease; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; H-CSVD, hereditary CSVD; IAUC, incremental area under the curve; mLVs, meningeal lymphatic vessels; NC, normal control; S-CSVD, sporadic CSVD; SS, sigmoid sinus; SSS, superior sagittal sinus; TICs, time-intensity curves; TTP, time-to-peak.

Figure 3

Correlation analysis was carried out to analyze the relationship between the levels of blood biomarkers and DCE-MRI parameters in patients with S-CSVD and CADASIL. *, P<0.05; **, P<0.01; ***, P<0.001. BUN, blood urea nitrogen; CADASIL, cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy; CRP, C-reactive protein; CSVD, cerebral small vessel disease; DCE-MRI, dynamic contrast-enhanced magnetic resonance imaging; FA, folic acid; FIB, fibrinogen; HbA1c, hemoglobin A1C; Hcy, homocysteine; IAUC, incremental area under the curve; Ktrans, transfer rate constant; Lpa, lipoprotein a; LDL-C, low-density lipoprotein cholesterol; SCr, serum creatinine; S-CSVD, sporadic CSVD; SF, ferritin; SS, sigmoid sinus; SSS, superior sagittal sinus; TC, total cholesterol; TG, triglyceride; TTP, time-to-peak; UA, uric acid; Ve, extravascular extracellular volume fraction.

Figure 4

Construction of the nomogram graph. (A) The graph shows the nomogram predicting CADASIL. The nomogram summed the points identified on the scale for each predictor. The total points projected on the bottom scales indicate the probabilities of CADASIL diagnosis. (B) The ROC curves of the nomogram model (blue) for CADASIL diagnosis prediction. AUC, area under the curve; CADASIL, cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy; FPR, false positive rate; mLVs-SSS, meningeal lymphatic vessels of the superior sagittal sinus; IAUC, incremental area under the curve; ROC, receiver operating characteristic; TPR, true positive rate.