1 research outputs found
NM-MRI for treatment evaluation of Parkinson’s Disease patients
T1-weighted fast spin echo magnetic resonance imaging (MRI) sequences are able to
depict neuromelanin (NM)-containing structures, such as the Substantia nigra (SN), as
hyper-intense signal areas. NM-MRI can accurately discriminate Parkinson’s Disease (PD)
patients from controls and could potentially be used to evaluate the effects of PD treatment
- either surgery or medication. PD patients that are treated with Deep Brain Stimulation
(DBS) can only undergo 1.5T MRI sequences with specific conditions that prevent the
tissues surrounding the neurostimulators from overheating. However, NM-MRI sequences
are usually not applied at 1.5T due to worse image quality. Nevertheless, it would be
interesting to study how DBS and medication influence the NM signal as a path for a
better understanding of the disease and to potentially evaluate the progression of PD after
the surgical intervention.
Firstly in this work, a NM-MRI sequence was adapted for scanning patients with
implanted DBS systems at 1.5T. To evaluate the performance of the sequence, images
were taken on the same day with 1.5T and 3T MRI systems. The contrast ratio of
both sequences was evaluated and SN areas were measured resorting to a semi-automatic
segmentation algorithm. The assessment of these measurements revealed a good agreement
between the developed sequence and the original 3T sequence.
A second study was carried out, in which SN areas of PD de novo patients were evaluated
before and after two months of initiating pharmacological treatment. The median SN area
tended to be increased after treatment, suggesting a potential increase of NM related to
dopamine therapy.
In conclusion, this work presented the first 1.5T NM-MRI sequence that enables SN
area measurement of patients with implanted neurostimulators, for further investigation
of this method as a diagnostic tool for assessment of disease progression and to better
understand clinical effects on NM-MRI and PD itself