MRI of nigrosome-1: A potential triage tool for patients with suspected parkinsonism.
J Neuroimaging
; 32(2): 273-278, 2022 03.
Article
en En
| MEDLINE
| ID: mdl-34724281
BACKGROUND AND PURPOSE: Susceptibility-weighted imaging (SWI) of nigrosome-1 is an emerging and clinically applicable imaging marker for parkinsonism, which can be derived from routinely performed brain MRI. The purpose of the study was to assess whether SWI can be used as a triage tool for more efficient selection of subsequent Dopamine Transporter Scan (DaTSCAN) single-photon emission computed tomography (SPECT). METHODS: We examined 72 consecutive patients with suspected parkinsonism with both DaTSCAN SPECT and SWI (48 in Philips Ingenia, 24 in GE Signa). Additionally, we examined 24 healthy controls with SWI (14 in Philips Ingenia, 10 in GE Signa). Diagnostic performance of SWI and DaTSCAN SPECT was assessed on the basis of clinical diagnosis, in terms of sensitivity, specificity, and diagnostic accuracy. RESULTS: A total of 54 parkinsonism patients (69 years ± 9, 32 men), 18 nonparkinsonism patients (69.4 years ± 9, 10 men), and 24 healthy controls (62 years ± 8, 10 men) were recruited. SWI had a specificity of 92% and a sensitivity of 74%, whereas DaTSCAN SPECT had 83% and 94%, respectively. By preselecting patients with abnormal or inconclusive SWI, the diagnostic performance of DaTSCAN SPECT improved (specificity 100%, sensitivity 95%). Scans from Philips were associated with significantly lower image quality compared to GE (p < .001). The experienced rater outperformed the less experienced one in diagnostic accuracy (82% vs. 68%). CONCLUSIONS: SWI can be used as triage tool because normal SWI can in most cases rule out parkinsonism. However, the performance of SWI depends on acquisition parameters and rater's experience.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Triaje
/
Trastornos Parkinsonianos
Límite:
Humans
/
Male
Idioma:
En
Revista:
J Neuroimaging
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
/
NEUROLOGIA
Año:
2022
Tipo del documento:
Article
País de afiliación:
Suiza
Pais de publicación:
Estados Unidos