Method for Quantitative Evaluation of the Substantia Nigra Using Phase-sensitive Inversion Recovery in 1.5 T Magnetic Resonance Imaging
Purpose: Parkinson's disease is a neurodegenerative disease with movement disorders caused by degeneration of the substantia nigra (SN) in the midbrain. Magnetic resonance imaging (MRI) is used to exclude similar diseases. Recently, neuro-melanin imaging (NMI) has been proposed as an imaging me...
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Veröffentlicht in: | Japanese Journal of Radiological Technology 2020, Vol.76(6), pp.563-571 |
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Sprache: | jpn |
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Zusammenfassung: | Purpose: Parkinson's disease is a neurodegenerative disease with movement disorders caused by degeneration of the substantia nigra (SN) in the midbrain. Magnetic resonance imaging (MRI) is used to exclude similar diseases. Recently, neuro-melanin imaging (NMI) has been proposed as an imaging method for evaluating the SN. However, the evaluation of the image using this is qualitative, and normal SN cannot be visualized at 1.5 T. This study aimed to investigate whether the SN can be quantitatively evaluated by using phase-sensitive inversion recovery (PSIR) at 1.5 T. Method: The phantom was imaged by PSIR and the accuracy of T1 value was verified. Next, the healthy volunteers were imaged by PSIR, and the T1 value and area of the SN were measured. Result: As a result of the phantom study, the difference of the T1value between PSIR and inversion recovery spin-echo in the range of the T1 value the SN and the cerebral peduncle (500 to 1000 ms) was lesser than ±10%. The difference between the average of T1 values of the SN measured by PSIR and the previously reported T1 values of the SN was about 1.1%. Furthermore, the average of the area of the SN measured by PSIR was measured independently of imaging parameters by using the T1 value as a reference. Conclusion: These results indicate the possibility of a quantitative evaluation of the SN by measuring its area and T1 value by using PSIR at 1.5 T. |
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ISSN: | 0369-4305 1881-4883 |
DOI: | 10.6009/jjrt.2020_JSRT_76.6.563 |