AI Article Synopsis

  • Numerous biomarkers have been proposed to distinguish Parkinson's disease (PD) from similar conditions, but many require expensive technology and are not practical for regular clinical use.
  • Current research has primarily relied on small patient groups and manual MRI measurement techniques, leading to inconsistencies in results.
  • The review emphasizes the need for larger, international studies and simpler biomarkers that can differentiate diseases, identify disease subtypes, track progression, and potentially predict PD in its early stages.

Article Abstract

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11446779PMC
http://dx.doi.org/10.3389/fneur.2024.1460576DOI Listing

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