Introduction

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s disease. The main pathological focus in parkinsonism is the substantia nigra pars compacta (SNc) of the midbrain, and the primary pathological issue is dopamine deficiency in the striatum, due to the loss of dopaminergic neurons within the SNc.
Neuromelanin (NM) imaging can assess degeneration of the SNc directly using a TSE sequence. Although NM imaging is a useful technique for diagnosing PD, it is difficult to quantitative evaluation for slight changes of SN because the contrast in the NM image is changed not only by the severity of PD but also by imaging parameters related to the scanner and the static magnetic field. There is, therefore, a need for an imaging technique that allows quantitative evaluation of the degeneration of the SN.
It is considered that the T₁ value of the SN may be altered with degeneration. If the T₁ value of the SN could be measured during routine MRI examination, it could provide a quantitative evaluation of the degeneration of the SN. A 3D phase-sensitive inversion recovery (PSIR) sequence can obtain high T₁ contrast and simultaneously measure the T₁ value of the tissue with high accuracy. Since PSIR can be easily implemented in a clinical setting, it may also be applicable for assessment of the SN.
The relationship between age and the T₁ value of the SN is not clear. Moreover, the correlation between the contrast of the SN obtained by NM imaging and the T₁ value of the SN has not been clarified. This needs to be clarified in healthy subjects first, before attempting to use T₁ values of the SN in PD patients. Thus, the purpose of this study was to estimate the T₁ value of the SN in healthy subjects, and to clarify its correlation with the characteristics of the SN obtained in NM images.

Materials and Methods

All examinations in this study were performed using a 3.0-T MRI (Ingenia, Philips Healthcare, Best, The Netherlands). Thirty-two healthy volunteers were enrolled (mean age, 52.4 years; age range, 36–63 years). NM and PSIR images of the midbrain were obtained from all volunteers.
NM imaging was performed using a 2D TSE sequence. The 3D PSIR sequence consisted of an inversion pulse and TFE readouts at two TIs. The magnitude and reference images were obtained at the first and second TIs, respectively. Real image (phase-sensitive images) at the first TI were produced using magnitude and reference images.
The signal intensity of cerebral peduncle (CP) and SN on the NM image was measured. The contrast between the SN and CP was calculated. As for PSIR imaging, we carefully traced the ROIs of both SNs on the magnitude image. The signal intensity of the SN, the area of the SN, and the contrast between the SN and CP on the PSIR image was measured. Moreover, the T1 value of the SN was calculated using PSIR and reference images in accordance with the iterative process reported by Warntjes et al.

Results

Figure 1 shows the representative images in a volunteer. There was a significant negative correlation between age and SN area obtained using PSIR imaging (r = -0.37, p = 0.037). No significant correlation was found between age and SN area measured on the TSE image (r = 0.126, p = 0.49) (Fig. 2).
The SN area on PSIR image was thus significantly larger than that on the NM image (p < 0.0001). No significant correlation was found between age and contrast with either imaging approach (r = 0.022, p = 0.905 for NM images, and r = 0.126, p = 0.49 for PSIR images) (Fig .3).
The contrast on PSIR images was thus significantly greater than that on NM images (p < 0.0001). There was a weak positive correlation between age and the T₁ value of the SN, which was a not significant (r = 0.31, p = 0.080) (Fig. 4). There was a significant negative correlation between the SN area and the T1 value (r = -0.59, p = 0.004) (Fig. 5).

Discussion

In this study, we measured the area and T₁ value of the SN in healthy volunteers using PSIR to assess its characteristics in non-pathological conditions. We demonstrated that the area and T₁ value of the SN changes with age. We also confirmed that the contrast of the SN on PSIR images was higher than that on NM images, which enables easy identification of the SN by PSIR imaging. Contrast of PSIR was significantly higher than that obtained with NM imaging. Thus, the PSIR is useful for identifying the SN region. The T₁ value of SN estimated by PSIR may correlate with NM accumulation in the SN. Although we have not validated this finding pathologically, measurement of T₁ value of the SN using PSIR may help evaluate degenerative changes of the SN on NM imaging.
In conclusion, the quantitative measurements of the T₁ value and area of the SN using PSIR imaging in healthy adults differ from those obtained by NM imaging. PSIR imaging may allow the evaluation of SN degeneration.

Acknowledgements

No acknowledgement found.