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Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
Evaluation of cerebrovascular hemodynamics in vascular dementia patients with a new individual computational fluid
Jian Xie1, Zaiheng Cheng2, Lihua Gu1
1Department of Neurology, Key Laboratory of Developmental Genes and Human Disease, Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, Jiangsu 210009, China.
Insights
Computational fluid dynamics (CFD) offers a non-invasive method to quantitatively assess cerebrovascular hemodynamics. Reduced arterial outlets and increased cerebrovascular resistance are key indicators differentiating subcortical vascular dementia patients from controls.
Area of Science:
- Neuroscience
- Medical Imaging
- Biomedical Engineering
Background:
- Cerebral hemodynamic disorders are implicated in vascular dementia (VaD) progression.
- Current methods for detecting hemodynamics are often uncertain.
- A quantitative computational fluid dynamics (CFD) approach is proposed for individual cerebrovascular hemodynamics.
Purpose of the Study:
- To develop and validate a patient-specific CFD model for quantitative hemodynamic assessment.
- To identify hemodynamic differences between subcortical vascular dementia (SVaD) patients and cognitive normal controls (CNCs).
- To explore the association of hemodynamic parameters with SVaD.
Main Methods:
- Constructed patient-specific CFD models using MRA and ultrasound Doppler data.
- Calculated hemodynamic indexes: cerebral arterial volume (CAV), arterial outlets, total cerebral blood flow (tCBF), and total cerebrovascular resistance (tCVR).
- Compared hemodynamic parameters between 38 SVaD patients and 40 CNCs.
Main Results:
- SVaD patients exhibited fewer outlets, reduced CAV and tCBF, and increased white matter hyperintensity (WMH) volume and tCVR compared to CNCs.
- Fewer outlets, higher Hachinski ischemic score (HIS), increased tCVR, and WMH volume were independently associated with SVaD.
- A composite index of outlets, tCVR, and HIS effectively differentiated SVaD patients (AUC=0.943).
Conclusions:
- Reduced outlets, elevated HIS, and increased tCVR are potential independent risk factors for SVaD.
- A combination of these indexes reliably differentiates SVaD patients from CNCs.
- The tCBF index may mediate the relationship between hemodynamic alterations and SVaD, with the CFD model offering non-invasive, patient-specific insights.
Background:
Cerebral hemodynamic disorders are involved in the occurrence and progression of vascular dementia (VaD), but the methods to detect hemodynamics remainmultifarious and uncertain nowadays. We aim to exploit a computational fluid dynamics (CFD) approach by static and dynamic parameters, which can be used to detect individual cerebrovascular hemodynamics quantitatively.
Methods:
A patient-specific CFD model was constructed with geometrical arteries on the magnetic resonance angiography (MRA) and hemodynamic parameters on ultrasound Doppler, by which, the structural and simulated hemodynamic indexes could be obtained, mainly including the cerebral arterial volume (CAV), the number of visible arterial outlets, the total cerebral blood flow (tCBF) index and the total cerebrovascular resistance (tCVR) index. The hemodynamics were detected in subcortical vascular dementia (SVaD) patients (n = 38) and cognitive normal controls (CNCs; n = 40).
Results:
Compared with CNCs, the SVaD patients had reduced outlets, CAV and tCBF index (all P ≤ 0.001), increased volume of white matter hyperintensity (WMH) and tCVR index (both P ≤ 0.01). The fewer outlets (OR = 0.77), higher Hachinski ischemic score (HIS) (OR = 3.65), increased tCVR index (OR = 1.98) and volume of WMH (OR = 1.12) were independently associated with SVaD. All hemodynamic parameters could differentiate the SVaD patinets and CNCs, especially the composite index calculated by outlets, tCVR index and HIS (AUC = 0.943). Fewer outlets and more WMH increased the odds of SVaD, which were partly mediated by the tCBF index (14.4% and 13.0%, respectively).
Conclusion:
The reduced outlets, higher HIS and tCVR index may be independent risk factors for the SVaD, and a combination of these indexes can differentiate SVaD patients and CNCs reliably. The tCBF index potentially mediates the relationships between hemodynamic indexes and SVaD. Although all simulated indexes only represented the true hemodynamics indirectly, this CFD model can provide patient-specific hemodynamic alterations non-invasively and conveniently.
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