ArticleQuantitative imaging in medicine and surgery2024
A nomogram based on neuron-specific enolase and substantia nigra hyperechogenicity for identifying cognitive impairment in Parkinson's disease.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Potential protein blood-based biomarkers for cognitive dysfunction in Parkinson's disease: a systematic review and network meta-analysis.Frontiers in aging neuroscience · 2026Pooled it
- Machine learning methods for the detection and prediction of cognitive impairment in Parkinson's disease: a systematic review and meta-analysis.Frontiers in aging neuroscience · 2025Pooled it
- A stacked multi-classifier for multi-modal data fusion in transcranial sonography-based Parkinson's disease assessment.NPJ Parkinson's disease · 2026Article
- A nomogram combined substantia nigra hyperechogenicity with third ventricular width assessed by transcranial sonography in prediction Parkinson's disease-related cognitive impairment.BMC medical imaging · 2026Article
- Super-resolution ultrasound imaging indirectly reveals neurovascular uncoupling in substantia nigra of a Parkinson's disease model.NPJ Parkinson's disease · 2026Article
- Spatial variations and precise location of substantia nigra hyperechogenicity in Parkinson's disease using TCS-MR fusion imaging.NPJ Parkinson's disease · 2025Article
- Association between third ventricular width assessed by transcranial sonography and plasma homocysteine in Parkinson's disease with cognitive impairment and their potential to predict conversion to dementia.Quantitative imaging in medicine and surgery · 2025Article
- Predictive value of the combined DTI-ALPS index and serum creatinine levels in mild cognitive impairment in Parkinson's disease.Frontiers in neurology · 2025Article
- Diagnostic accuracy of transcranial sonography-magnetic resonance fusion imaging for Parkinson's disease versus multiple system atrophy-Parkinsonian type.Frontiers in neurologyArticle
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7 authors.
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Abstract
Background: One in four individuals with Parkinson's disease (PD) experience cognitive impairment (CI). However, few practical models integrating clinical and neuroimaging biomarkers have been developed to address CI in PD. This study aimed to evaluate the correlation between circulating neuron-specific enolase (NSE) levels, substantia nigra hyperechogenicity (SNH), and cognitive function in PD and to develop a nomogram based on clinical and neuroimaging biomarkers for predicting CI in patients with PD. Methods: A total of 385 patients with PD who underwent transcranial sonography (TCS) from January 2021 to December 2022 at Beijing Tiantan Hospital, Capital Medical University, were recruited as the training cohort. For validation, 165 patients with PD treated from January 2023 to December 2023 were enrolled. Data for SNH, plasma NSE, and other clinical measures were collected, and cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). Logistic regression analysis was employed to select potential risk factors and establish a nomogram. The receiver operating characteristic curve and calibration curve were generated to evaluate the performance of the nomogram. Results: Patients with PD exhibiting CI displayed advanced age, elevated Unified PD Rating Scale-III (UPDRS-III) score, an increased percentage of SNH, higher levels of plasma NSE and homocysteine (Hcy), a larger SNH area, and lower education levels compared to PD patients without CI. Gender [odds ratio (OR) =0.561, 95% confidence interval (CI): 0.330-0.954, P=0.03], age (OR =1.039; 95% CI: 1.011-1.066; P=0.005), education level (OR =0.892; 95% CI: 0.842-0.954; P<0.001), UPDRS-III scores (OR =1.026; 95% CI: 1.009-1.043; P=0.003), plasma NSE concentration (OR =1.562; 95% CI: 1.374-1.776; P<0.001), and SNH (OR =0.545; 95% CI: 0.330-0.902; P=0.02) were independent predictors of CI in patients with PD. A nomogram developed using these six factors yielded a moderate discrimination performance with an area under the curve (AUC) of 0.823 (95% CI 0.781-0.864; P<0.001). The calibration curve demonstrated acceptable agreement between predicted outcomes and actual values. Validation further confirmed the reliability of the nomogram, with an AUC of 0.864 (95% CI: 0.805-0.922; P<0.001). Conclusions: The level of NSE in plasma and the SNH assessed by TCS are associated with CI in patients with PD. The proposed nomogram has the potential to facilitate the detection of cognitive decline in individuals with PD.
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