Neuro-Imaging in Parkinson’s Disease

A special issue of Tomography (ISSN 2379-139X). This special issue belongs to the section "Neuroimaging".

Deadline for manuscript submissions: closed (1 December 2021) | Viewed by 4480

Special Issue Editor


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Guest Editor
Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ 85013, USA
Interests: Parkinson’s Disease; parkinsonism; Huntington’s Disease; Lewy Body Disorders; movement disorders; neuroimaging across neurodegenerative diseases; MRI; clinical trials

Special Issue Information

Dear Colleagues,

Neuro-Imaging in Parkinson’s Disease (PD) is in a phase of rapid evolution. From molecular imaging to PET-based imaging, to multi-modal MRI, neuroimaging in PD has reached a critical mass of investigative capacity. The ability of neuroimaging to diagnose, monitor response to treatment, and predict symptom development in PD has made important strides. This has resulted not only in an improved understanding of PD itself, but also in imaging tools with utility in the clinic and in clinical research. Thus, this is a fertile and opportune time to review the past, present, and future of neuroimaging in PD, including consideration of the field through the lens of the NIH, industry, basic science, and clinical/translational science perspectives. Papers addressing these topics are invited for this Special Issue, especially those combining a high academic standard coupled with a focus on identifying the remaining challenges in the field and suggesting pathways forward.

Dr. Ryan R. Walsh
Guest Editor

Manuscript Submission Information

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Keywords

  • Parkinson’s Disease
  • SPECT
  • PET
  • MRI
  • Multi-modal
  • Dopamine
  • Dopamine transporter
  • Synuclein
  • Molecular imaging
  • Clinical trial

Published Papers (1 paper)

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Research

10 pages, 30940 KiB  
Article
Practical Application of DaTQUANT with Optimal Threshold for Diagnostic Accuracy of Dopamine Transporter SPECT
by Matthew Neill, Julia M. Fisher, Christine Brand, Hong Lei, Scott J. Sherman, Ying-Hui Chou and Phillip H. Kuo
Tomography 2021, 7(4), 980-989; https://doi.org/10.3390/tomography7040081 - 18 Dec 2021
Cited by 6 | Viewed by 3792
Abstract
Evaluation of Parkinsonian Syndromes (PS) with Ioflupane iodine-123 dopamine transporter single photon emission computed tomography (DaT-SPECT), in conjunction with history and clinical examination, aids in diagnosis. FDA-approved, semi-quantitative software, DaTQUANTTM (GE Healthcare, Chicago, IL, USA) is available to assist in interpretation. This [...] Read more.
Evaluation of Parkinsonian Syndromes (PS) with Ioflupane iodine-123 dopamine transporter single photon emission computed tomography (DaT-SPECT), in conjunction with history and clinical examination, aids in diagnosis. FDA-approved, semi-quantitative software, DaTQUANTTM (GE Healthcare, Chicago, IL, USA) is available to assist in interpretation. This study aims to evaluate the optimal variables and thresholds of DaTQUANT to yield the optimal diagnostic accuracy. It is a retrospective review with three different patient populations. DaT-SPECT images from all three study groups were evaluated using DaTQUANTTM software, and both single and multi-variable logistic regression were used to model PS status. The optimal models were chosen via accuracy, sensitivity, and specificity, then evaluated on the other study groups. Among single variable models, the posterior putamen yielded the highest accuracy (84% to 95%), while balancing sensitivity and specificity. Multi-variable models did not substantially improve the accuracy. When the optimal single variable models for each group were used to evaluate the remaining two groups, comparable results were achieved. In typical utilization of DaT-SPECT for differentiation between nigrostriatal degenerative disease (NSDD) and non-NSDD, the posterior putamen was the single variable that yielded the highest accuracy across three different patient populations. The posterior putamen’s recommended thresholds for DaTQUANT are SBR ≤ 1.0, z-score of ≤−1.8 and percent deviation ≤ −0.34. Full article
(This article belongs to the Special Issue Neuro-Imaging in Parkinson’s Disease)
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