NDLI: The applied value in brain gray matter nuclei of patients with early-stage Parkinson’s disease : a study based on multiple magnetic resonance imaging techniques

Content Provider	Springer Nature : BioMed Central
Author	Meng, Heng Zhang, Duo Sun, Qiyuan
Abstract	Purpose This study compares the observation efficiency of brain gray matter nuclei of patients with early-stage Parkinson’s disease among various Magnetic Resonance Imaging techniques, which include susceptibility weighted imaging (SWI), quantitative susceptibility imaging (QSM), diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Based on the findings, this study suggests an efficient combination of scanning techniques for brain gray matter nuclei observation, aiming to provide an opportunity to advance the understanding of clinical diagnosis of early-stage Parkinson’s disease. Methods Forty examinees, including twenty patients who were clinically diagnosed with early Parkinson’s disease with a course of 0.5-6 years (PD group) and twenty healthy controls (HC group), underwent head MRI examination. Philips 3.0T (tesla) MR machine was used to measure the imaging indexes of gray matter nuclei in patients with early Parkinson’s disease. SWI, QSM, DTI and DKI were used for diagnosis. SPSS (Statistical Product and Service Solutions) 21.0 was used for data analysis. Results When SWI was used, fifteen PD patients and six healthy volunteers were diagnosed correctly. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic coincidence rate about the diagnosis of nigrosome-1 on imaging were 75.0%, 30.0%, 51.7%, 54.5% and 52.5% respectively. By contrast, when QSM was used, 19 PD patients and 11 healthy volunteers were diagnosed correctly. The sensitivity, specificity, positive predictive value, negative predictive value and diagnostic coincidence rate about the diagnosis of Nigrosome-one on imaging were 95.0%, 55.0%, 67.9%, 91.7% and 75.0% respectively. The mean kurtosis (MK) value within both the substantia nigra and thalamus, together with the mean diffusivity (MD) within both the substantia nigra and the head of caudate nucleus in PD group was greater than that of HC group. The susceptibility values within the substantia nigra, red nucleus, head of caudate nucleus and putamen of PD group was greater than that of HC group. The MD value in substantia nigra reveals the optimal diagnostic efficiency to distinguish the HC group and the PD group, followed by the MK value in substantia nigra. Specifically, the maximum area under ROC curve (AUC) of the MD value was 0.823, the sensitivity 70.0%, the specificity 85.0%, and the diagnostic threshold 0.414. The area under ROC curve (AUC) of the MK value was 0.695, the sensitivity 95.0%, the specificity 50.0%, and the diagnostic threshold was 0.667. Both of them were statistically significant. Conclusions In the early diagnosis of Parkinson’s disease, QSM is more efficient than SWI in observing nigrosome-1 in substantia nigra. In the early diagnosis of Parkinson’s disease, MD and MK values of substantia nigra in DKI parameters have higher diagnostic efficiency. The combined scanning of DKI and QSM has the highest diagnostic efficiency and provides imaging basis for clinical diagnosis of early Parkinson’s disease.
Related Links	https://head-face-med.biomedcentral.com/counter/pdf/10.1186/s13005-023-00371-4.pdf
Ending Page	15
Page Count	15
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s13005-023-00371-4
Journal	Head & Face Medicine
Issue Number	1
Volume Number	19
Language	English
Publisher	BioMed Central
Publisher Date	2023-06-29
Access Restriction	Open
Subject Keyword	Otorhinolaryngology Oral and Maxillofacial Surgery Dentistry Head and Neck Surgery Parkinson’s disease Magnetic resonance imaging Diffusion tensor imaging Diffusion kurtosis imaging Quantitative susceptibility mapping Susceptibility weighted imaging
Content Type	Text
Resource Type	Article
Subject	Otorhinolaryngology Neurology (clinical) Dentistry
Journal Impact Factor	2.4/2023
5-Year Journal Impact Factor	2.9/2023

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