Synopsis

Keywords: Parkinson's Disease, Brain, essential tremor; neuromelanin MRI; locus coeruleus;substantia nigra

In this study, we used neuromelanin MRI to investigate locus coeruleus (LC) and substantia nigra changes between essential tremor (ET) and Parkinson’s disease (PD). We found the neuromelanin of LC was significantly lower in tremor-dominant PD patients than in ET patients or healthy controls, and the area under the curve of the model constructed by NM measures reached 0.92 in differentiating tremor-dominant PD from ET. These results provided new perspectives in the differential diagnosis of patients with tremor and in the investigation of the underlying pathophysiology.

Introduction

Differential diagnosis of essential tremor (ET) and Parkinson’s disease (PD) (the two most common movement disorders with tremor) can still be a challenge in clinical practice. These two tremor disorders may have different pathogenesis related to the substantia nigra (SN) and locus coeruleus (LC). Characterizing neuromelanin (NM) in these structures may help improve the differential diagnosis. This study aimed to explore the combined value of NM measures in the LC and SN in the differentiation of tremor-dominant PD (PD_TD) from ET patients as extracted from NM magnetic resonance imaging (NM-MRI) data.

Methods

Forty-three patients with PD_TD, 31 patients with ET, and 30 age- and sex-matched healthy controls were included. All subjects were scanned with a 3D multi-echo gradient recalled echo sequence with an activated magnetization transfer contrast pulse on a 3.0 T Philips Ingenia scanner. The imaging parameters were as follows: voxel size = 0.67×1×1.34 mm3 interpolated to 0.67×0.67×1.34 mm3, first echo time (TE) = 7.5ms, (with 4 more echoes each with a separation of 7.5ms), repeat time (TR) = 62ms, flip angle =30° and 12°, pixel bandwidth =174 Hz/pixel, slice thickness =2 mm, number of slices = 48, a sense factor of 2, and a total acquisition time of 9 minutes 20 seconds inclusive of both flip angles. The NM regions of interest (ROIs) associated with the SN were automatically drawn on the 12° flip angle original transverse images using SPIN software (SpinTech, Inc., Bingham Farms, Ml, USA). The NM ROIs for LC were manually segmented on each subject from the 30° MTC magnitude coronally reformatted images. The background ROIs for the SN and LC were set in nearby structures. The NM volume and contrast-to-noise ratio (CNR) of the SN, and NM area and CNR of LC derived from the NM-MRI data were evaluated (Figure 1). Logistic regression was used to calculate predicted probabilities by using a combination of SN and LC NM parameters. The discriminative power of the NM measures in detecting patients with PD_TD from ET was assessed with a receiver operative characteristic curve.

Results

The NM CNR of the LC, the NM volume, and the CNR of the SN on the right and left sides were significantly lower in PD_TD patients than in ET patients or healthy controls (all P<0.05) (Figure2). Furthermore, when combining the best model constructed from the NM measures, the AUC reached 0.92 in differentiating PD_TD from ET (Figure3).

Discussion

The reduced NM parameters in PD_TD compared to ET is similar to what has been found in a previous study¹. In our analysis, the NM CNR calculation of SN focused on the central part of the SN, because it was difficult to find the lateral part of the SN in all slices, especially in PD_TD patients. In addition, a previous study suggested that noradrenergic neurons in ET were not diminished in the LC when compared with healthy controls². Our study is similar to the pathological study, we found no significant difference for LC NM CNR between healthy controls and patients with ET.

Conclusion

The NM volume and contrast in both the LC and SN derived from NM-MRI could be a potential diagnostic biomarker to differentiate PD_TD from ET.

Acknowledgements

None