Imaging of nigrosome 1 in substantia nigra at 3T using multiecho susceptibility map‐weighted imaging (SMWI)

Nam, Yoonho; Gho, Sung Min; Kim, Dong Hyun; Kim, Eung Yeop; Lee, Jong-Ho

doi:10.1002/jmri.25553

Cited by 65 publications

(79 citation statements)

References 39 publications

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“…The most consistently reported abnormalities in PD include loss of DNH (Schwarz et al 2014; Reiter et al 2015; Bae et al 2016) and nigral neuromelanin signal changes (Kashihara et al 2011; Matsuura et al 2013; Ohtsuka et al 2014; Castellanos et al 2015; Reimao et al 2015a, b; Langley et al 2016) establishing these qualitative MR markers in routine clinical practice for the diagnosis of early PD (Lehericy et al 2017). There are also promising quantitative markers including QSM, multiecho susceptibility map-weighted imaging, adiabatic techniques T1rho, T2rho, relaxations along a fictitious field (RAFF), NM-MRI, as well as post-processing diffusion imaging techniques including FW or NODDI (Barbosa et al 2015; Ofori et al 2015a, b; Du et al 2016; Kamagata et al 2016; Langkammer et al 2016; Nam et al 2016; Planetta et al 2016). Limitations of these techniques, however, include their unavailability on most conventional scanners and the lack of normative databases (Lehericy et al 2017).…”

Section: Conclusion and Future Developmentmentioning

confidence: 99%

Magnetic resonance imaging for the diagnosis of Parkinson’s disease

et al. 2017

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The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson’s disease. This includes not only the exclusion of alternative diagnoses for Parkinson’s disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson’s disease.

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Section: Conclusion and Future Developmentmentioning

confidence: 99%

Magnetic resonance imaging for the diagnosis of Parkinson’s disease

et al. 2017

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“…The exponent of the Susceptibility mask (m) was chosen to be 4, also as optimized in the previous study . The SWMI results from QSMnet and conventional iLSQR were compared.…”

Section: Methodsmentioning

confidence: 99%

“…This feature helps the susceptibility mask enhance the magnetic‐susceptibility induced tissue contrast. In the previous study, by using SMWI technique, contrast‐to‐noise ratio (CNR) between the nigrosome 1 and surrounding SN regions was 39% higher than magnitude images from GRE, QSM maps and SWIs . As a result, one can clearly identify nigrosome 1 and SN regions at clinical field strength …”

Section: Introductionmentioning

confidence: 93%

“…There exists a magnetic susceptibility contrast between nigrosome 1 and the other areas in the SN due to the difference in the iron concentration. Magnetic susceptibility based imaging, such as T 2 *‐weighted imaging and susceptibility weighted imaging (SWI) are well‐known MR imaging techniques that allow visualization of the changes in dopaminergic neurons in SNPC . In healthy volunteers, those imaging techniques generate higher magnetic‐susceptibility induced tissue contrast between nigrosome 1 and the surrounding SN.…”

Section: Introductionmentioning

confidence: 99%

“…In the clinical field strength (

\leq 3 T

), however, because of the lower magnetic‐susceptibility induced tissue contrast and signal‐to‐noise ratio (SNR), visualization of the SNPC using conventional T 2 * weighted imaging technique has been limited . Susceptibility map‐weighted imaging (SMWI) has been proposed to visualize SNPC at clinical field strength . To improve the magnetic‐susceptibility induced tissue contrast, the SMWI technique takes advantage of both T 2 * weighted imaging and quantitative susceptibility mapping (QSM) without the cost of additional scan time.…”

Section: Introductionmentioning

confidence: 99%

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A preliminary attempt to visualize nigrosome 1 in the substantia nigra for Parkinson’s disease at 3T: An efficient susceptibility map‐weighted imaging (SMWI) with quantitative susceptibility mapping using deep neural network (QSMnet)

2020

Medical Physics

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Purpose Visibility of nigrosome 1 in the substantia nigra (SN) is used as an MR imaging biomarker for Parkinson's disease. Because of lower susceptibility induced tissue contrast and SNR visualization of the SN pars compacta (SNPC) using conventional imaging technique in the clinical field strength (≤3T) has been limited. Susceptibility map‐weighted imaging (SMWI) has been proposed to visualize SNPC at 3T. To better visualize nigrosome 1 and SN areas using SMWI, accurate estimation of the quantitative susceptibility mapping (QSM) map is essential. In SMWI processing, however, QSM processing time using conventional algorithms is the most time‐consuming step and may limit clinical use. In this study, we introduce an efficient SMWI processing approach using the deep neural network (QSMnet). To improve the processing speed of SMWI while maintaining similar image quality to that obtained with the conventional method, QSMnet was applied to generate a susceptibility mask for SMWI processing. Methods To conduct a deep learning‐based image to image operation modified QSMnet was utilized. The network was trained with in vivo MR data from 57 healthy controls. To validate SMWI results from QSMnet, four datasets from healthy controls were used as the test datasets. As a preliminary attempt to explore the clinical applicability, Parkinson’s disease patient data were additionally tested. The SWMI images generated by QSMnet and conventional model‐based QSM outputs were compared. To validate SMWI results, region of interest (ROI) analysis was performed. The mean signal values at the nigrosome 1 and the surrounding regions were measured to calculate contrast‐to‐noise ratio (CNR). Results The experimental results confirmed that the proposed approach using QSMnet provided similar QSM and SMWI compared to that obtained with conventional iLSQR while the processing speed was much improved (5.4 times faster). The QSM results from QSMnet show similar tissue contrast with results from iLSQR. When compared, the absolute mean intensity difference between two methods near the nigrosome 1 was 0.015 ppm. SMWI results using susceptibility masks from QSMnet demonstrated signal distribution and tissue contrast that was comparable with those results from the conventional iLSQR method. The absolute difference maps of SMWI were calculated to show the similarity between the two methods. The overall mean absolute difference value in the presented ROIs obtained from healthy controls (n = 4) and a PD patient (n = 1) were 2.31 and 1.81, respectively. Mean CNR values (10 ROIs; n = 5; including both sides; 1.42 for QSMnet; 1.43 for iLSQR) between SN and nigrosome 1 in SMWI results obtained by ROI analysis were similar (P = 0.724). Conclusions In this study, we assessed an efficient approach for SMWI visualizing SN and nigrosome 1 on 3T. QSMnet provides a similar SMWI image to that obtained with the conventional iterative QSM algorithm and improves QSM processing speed by avoiding iterative computation. Since QSM is the most time‐consuming step of SMWI proc...

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Differential involvement of nigral subregions in idiopathic parkinson's disease

Sung

Lee

Nam

et al. 2017

Human Brain Mapping

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In this study, the prevalence of abnormality in putative nigrosome 1 and nigrosome 4 (N1 and N4, respectively) was investigated in early versus late-stage idiopathic Parkinson's disease (IPD) patients. A total of 128 IPD patients (early stage[n 5 89]; late stage[n 5 39]) and 15 healthy subjects were scanned for high-resolution (0.5 3 0.5 3 1.0 mm 3 ) multiecho gradient-recalled echo MRI and dopamine transporter PET imaging. The MRI data were processed for susceptibility map-weighted imaging (SMWI) to improve a contrast-to-noise ratio, and the images were resliced at 0.5 mm to define N1 and N4. When each side of N1 and N4 was assessed separately for the loss of hyperintensity by two independent reviewers, the consensus review results showed that in early-stage IPD (178 substantia nigras [SNs]), the loss of hyperintensity was observed more often in only the N1 region (65.2%) when compared to in both N1 and N4 regions (34.8%). In late-stage IPD (78 SNs), on the other hand, the loss in only the N1 region (25.6%) was less prevalent than in both N1 and N4 (74.4%) (P < 0.0001). Additionally, intact SNs (both in N1 and N4) were observed 17 SNs (9.6%) of the early-stage IPD patients, whereas it was not found in any SNs of the late-stage IPD patients (P 5 0.005). Moreover, involvement of both N1 and N4 on both sides was found in 19.1% of the early-stage IPD patients, whereas its incidence was higher (61.5%) in the late-stage IPD patients (P < 0.0001), suggesting that the loss of hyperintensity in IPD progresses from N1 to N4 as the disease advances. Hum Brain Mapp 39:542-553, 2018.V C 2017 Wiley Periodicals, Inc.

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Imaging of nigrosome 1 in substantia nigra at 3T using multiecho susceptibility map‐weighted imaging (SMWI)

Abstract: 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:528-536.

Cited by 65 publications

References 39 publications

Magnetic resonance imaging for the diagnosis of Parkinson’s disease

Magnetic resonance imaging for the diagnosis of Parkinson’s disease

A preliminary attempt to visualize nigrosome 1 in the substantia nigra for Parkinson’s disease at 3T: An efficient susceptibility map‐weighted imaging (SMWI) with quantitative susceptibility mapping using deep neural network (QSMnet)

Differential involvement of nigral subregions in idiopathic parkinson's disease

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