Table · dataset · 2026
Table 1_The clinical value of combined assessment of substantia nigra morphology and intracranial hemodynamics via transcranial ultrasound in the diagnosis and differentiation of Parkinson’s disease.docx
Listed in figshare and Loughborough Research Repository — shown once because both records carry DOI 10.3389/fneur.2026.1913166.s001
Background<p>Parkinson’s disease (PD) is a common neurodegenerative disease, and its clinical differentiation from Parkinson-plus syndromes (PPS) remains challenging due to the lack of highly specific biomarkers.
Description
Although dopamine transporter single-photon emission computed tomography (DAT-SPECT) provides objective evidence of dopaminergic denervation, its limited value in distinguishing PD from PPS and restricted availability underscore the need for accessible and reliable diagnostic tools.
This study aimed to evaluate a novel, non-invasive, and convenient auxiliary diagnostic approach for the diagnosis and differentiation of PD by integrating the assessment of substantia nigra hyperechogenicity (SN+) and intracranial hemodynamics using transcranial ultrasound.</p>Methods<p>A total of 68 PD patients (PD group), 30 PPS patients (PPS group), and 80 healthy controls (NC group) were enrolled between June 2023 and December 2025.
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All subjects underwent Transcranial Sonography (TCS) to measure the area of SN+ and Transcranial Color Doppler (TCCD) to measure intracranial vascular hemodynamic parameters. Intergroup differences were analyzed, and receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of individual parameters and their combination.</p>Results<p>Ultrasound parameters of the substantia nigra, including unilateral and bilateral hyperechogenicity, were markedly elevated in PD patients compared to PPS and control groups (p < 0.05).
Additionally, the PD group exhibited altered hemodynamic profiles, with significant differences in resistance index and diastolic flow velocity of the middle cerebral artery (MCA Vd) relative to controls. ROC curve analyses indicated that the diagnostic accuracy for PD using the SN+ area was high (AUC = 0.918), while a combined model incorporating TCS and TCCD parameters achieved a superior AUC of 0.945, with a sensitivity of 91.2% and specificity of 95.0%.</p>Conclusion<p>TCS-detected SN+ is an effective imaging biomarker for PD.
Combining SN+ with MCA Vd demonstrated superior diagnostic efficacy (AUC = 0.945) compared with either parameter alone, providing a non-invasive multimodality tool for distinguishing PD from non-PD individuals (including PPS and healthy controls).</p>
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Where it is published
- DOI doi.org/10.3389/fneur.2026.1913166.s001 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
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- Computed tomography 75% · Disease 75% · Imaging 75% · Tabular 65%
Provenance · 2 source records, 34 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| figshare | oai:figshare.com:article/33979489 | 12 d ago | JSON v1 |
| Loughborough Research Repository | oai:figshare.com:article/33979489 | 11 d ago | JSON v1 |
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| concepts[field].anzsrc:field:320905 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Neurology and Neuromuscular Diseases'] |
| concepts[field].anzsrc:field:320905 | mapping · repository lboro ac uk | vocabulary-mapper@1.0.0 | keywords['Neurology and Neuromuscular Diseases'] |
| concepts[field].local:field:astronomy | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| concepts[field].local:field:computer-science-ai | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| concepts[field].local:field:humanities | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| concepts[field].local:field:materials-science | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:mathematics-statistics | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| concepts[field].local:field:ocean-atmospheric | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:psychology-behavioral | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| concepts[field].local:field:social-science | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[modality].local:modality:ct | enrichment · figshare com | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:imaging | enrichment · figshare com | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:tabular | enrichment · figshare com | keyword-concept-rules@1.0.0 | title+description (65%) |
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| publication_date | source · figshare com | connector:figshare_com@1.0.0 | |
| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |