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- W4200595057 abstract "The study preliminarily explored the sequence and difference of involvement in different neuroanatomical structures in idiopathic normal pressure hydrocephalus (INPH). We retrospectively analyzed the differences in diffusion tensor imaging (DTI) parameters in 15 ROIs [including the bilateral centrum semiovale (CS), corpus callosum (CC) (body, genu, and splenium), head of the caudate nucleus (CN), internal capsule (IC) (anterior and posterior limb), thalamus (TH), and the bilateral frontal horn white matter hyperintensity (FHWMH)] between 27 INPH patients and 11 healthy controls and the correlation between DTI indices and clinical symptoms, as evaluated by the INPH grading scale (INPHGS), the Mini-Mental State Examination (MMSE), and the timed up and go test (TUG-t), before and 1 month after shunt surgery. Significant differences were observed in DTI parameters from the CS (pFA1 = 0.004, pADC1 = 0.005) and the genu (pFA2 = 0.022; pADC2 = 0.001) and body (pFA3 = 0.003; pADC3 = 0.002) of the CC between the groups. The DTI parameters from the CS were strongly correlated with the MMSE score both pre-operatively and post-operatively. There was association between apparent diffusion coefficient (ADC) values of anterior and posterior limbs of the IC and MMSE. The DTI parameters of the head of the CN were correlated with motion, and the ADC value was significantly associated with the MMSE score. The FA value from TH correlated with an improvement in urination after shunt surgery. We considered that different neuroanatomical structures are affected differently by disease due to their positions in neural pathways and characteristics, which is further reflected in clinical symptoms and the prognosis of shunt surgery." @default.
- W4200595057 created "2021-12-31" @default.
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- W4200595057 date "2021-12-17" @default.
- W4200595057 modified "2023-09-24" @default.
- W4200595057 title "Preliminary Exploration of the Sequence of Nerve Fiber Bundles Involvement for Idiopathic Normal Pressure Hydrocephalus: A Correlation Analysis Using Diffusion Tensor Imaging" @default.
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- W4200595057 doi "https://doi.org/10.3389/fnins.2021.794046" @default.
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