Open Access
CC BY 4.0 · World J Nucl Med 2024; 23(04): 242-249
DOI: 10.1055/s-0044-1787995
Original Article

Reviewing the Diagnostic Performance of 99mTc-TRODAT-1 Imaging in Distinguishing Idiopathic Parkinson's Disease from Parkinson-Plus Syndromes

Tejasvini Singhal
1   Department of Nuclear Medicine, All India Institute of Medical Sciences, Bhubaneswar, Bhubaneswar, Orissa, India
,
2   Department of Nuclear Medicine, All India Institute of Medical Sciences, Rishikesh, Rishikesh, Uttarakhand, India
,
Rajat Manchanda
3   Department of Neurology, Neuro Care Hospital, Karnal, Haryana, India
,
Parneet Singh
1   Department of Nuclear Medicine, All India Institute of Medical Sciences, Bhubaneswar, Bhubaneswar, Orissa, India
,
Minakshi Dhar
4   Department of Internal Medicine, All India Institute of Medical Sciences, Rishikesh, Rishikesh, Uttarakhand, India
,
Ashutosh Tiwari
5   Department of Neurology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, Uttarakhand, India
,
Niraj Kumar
5   Department of Neurology, All India Institute of Medical Sciences, Rishikesh, Rishikesh, Uttarakhand, India
› Institutsangaben
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Abstract

Aim Diagnosing movement disorders can be challenging owing to their similar clinical presentations with other neurodegenerative and basal ganglia disorders, like idiopathic Parkinson's disease (IPD), essential tremors (ET), vascular parkinsonism, multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). Technetium-99m labeled tropane derivative (99mTc-TRODAT-1) imaging can help in diagnosing Parkinson's disease at an early stage to help early initiation of the treatment. The current study aimed to evaluate the role of 99mTc-TRODAT-1 imaging in differentiating IPD and Parkinson-plus syndromes (PPS).

Material and Methods We have analyzed 38 patients, referred to our department for 99mTc-TRODAT imaging. These patients were thoroughly evaluated in the movement disorder clinic at our institute and had a possible/ probable diagnosis of IPD, Hoehn and Yahr (H&Y) stage I/II (n = 28) or PPS (PSP [n = 06] and MSA [n = 04]). Striatal uptake ratio (SUR) was calculated in all the patients and data was statistically analyzed.

Results The mean age of IPD, PSP, and MSA groups was 56.5 ± 12.15, 65.2 ± 11.1, and 51.2 ± 3.9 years, respectively. On qualitative evaluation, all patients had reduced striatal uptake on 99mTc-TRODAT imaging, with 31/38 patients showed a greater reduction in putaminal uptake compared with the caudate nucleus. On semiquantitative evaluation, mean total SUR was 0.58 ± 0.27, 0.53 ± 0.31, and 0.91 ± 0.20 in IPD, PSP, and MSA groups, respectively. The total SUR was lowest in the PSP group followed by IPD, but MSA had relatively higher SUR, although the difference was not statistically significant. Among the IPD patient group, 25/28 patients (89.3%) experienced a greater reduction in SUR values in the striatum contralateral to the side, where motor symptoms first manifested at disease onset.

Conclusion 99mTc-TRODAT is a potential imaging biomarker for the evaluation of presynaptic dopaminergic dysfunction in patients with movement disorders. In our study cohort, mean SUR values were lowest for the PSP group followed by IPD and MSA group, which was in concordance with previous studies. However, the difference between SUR values in these two groups was not statistically significant. The present study emphasizes that the capacity of 99mTc-TRODAT-1 imaging alone for diagnosing IPD from PPS is constrained, although it offers a precise approach for distinguishing patients with IPD from those with essential tremors, drug-induced, or psychogenic parkinsonism. Consequently, more specific imaging biomarkers are needed to effectively differentiate between patients with IPD and those with PPS.

Previous Presentation

This research was previously presented as an Oral Presentation in Society of Nuclear Medicine, Hyderabad, India on December 16–18, 2021.




Publikationsverlauf

Artikel online veröffentlicht:
04. Juli 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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