The utility of the combined use of 123I-FP-CIT SPECT and neuromelanin MRI in differentiating Parkinson's disease from other parkinsonian syndromes

Utility of combining multiple parameters of 123I-IMP SPECT and voxel-based morphometry MRI using a multiparametric scoring system for differentiating dementia with Lewy bodies from Alzheimer's disease

BACKGROUND

Brain magnetic resonance imaging voxel-based morphometry (VBM) and perfusion single-photon emission computed tomography (SPECT) are useful for differentiating dementia with Lewy bodies (DLB) from Alzheimer's disease (AD).

PURPOSE

To determine whether combining multiple parameters of VBM and SPECT using a multiparametric scoring system (MSS) improves diagnostic accuracy in differentiating DLB from AD.

MATERIAL AND METHODS

In total, 23 patients with DLB and 57 patients with AD underwent imaging using a voxel-based specific regional analysis system for AD (VSRAD), an easy Z-score imaging system, and a Z-Graph using three-dimensional stereotactic surface projection. The cutoff values were determined using the receiver operating characteristic curve to differentiate DLB from AD for all parameters. Patients were scored 1 (DLB) or 0 (AD) for each statistically significant parameter, according to a threshold. The total score was determined for each case to obtain a cutoff value for the MSS.

RESULTS

The mean Z-scores in the medial temporal lobes using the VSRAD were significantly lower in patients with DLB than in those with AD. Each Z-score of the summed Z-scores in all four segmented regions of the occipital lobes using the Z-Graph was significantly higher in patients with DLB than in those with AD. Among the five parameters, the highest accuracy was 80% for the Z-score of the summed Z-scores in the left medial occipital lobe. For the MSS, a cutoff value of four improved the diagnostic accuracy to 82%.

CONCLUSION

MSS was more accurate than any single parameter of VBM or SPECT in differentiating DLB from AD.

Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.

Diagnostic performance of a high-spatial-resolution voxelwise analysis of neuromelanin-sensitive imaging in early-stage idiopathic Parkinson's disease

BACKGROUND

Quantitative assessments of neuromelanin (NM) of the substantia nigra pars compacta (SNpc) in neuromelanin-sensitive MRI (NM-MRI) to determine its abnormality have been conducted by measuring either the volume or contrast ratio (CR) of the SNpc. A recent study determined the regions in the SNpc that are significantly different between early-stage idiopathic Parkinson's disease (IPD) patients and healthy controls (HCs) using a high spatial-resolution NM-MRI template, which enables a template-based voxelwise analysis to overcome the susceptibility of CR measurement to inter-rater discrepancy. We aimed to assess the diagnostic performance, which has not been reported, of the CRs between early-stage IPD patients and HCs using a NM-MRI template.

METHODS

We retrospectively enrolled early-stage IPD patients (n = 50) and HCs (n = 50) who underwent 0.8-mm isovoxel NM-MRI and dopamine-transporter PET as the standard of reference. A template-based voxelwise analysis revealed two regions in nigrosomes 1 and 2 (N1 and N2, respectively), with significant differences in each substantia nigra (SNpc) between IPD and HCs. The mean CR values of N1, N2, volume-weighted mean of N1 and N2 (N1 + N2), and whole SNpc on each side were compared between IPD and HC using the independent t-test or the Mann-Whitney U test. The diagnostic performance was compared in each region using receiver operating characteristic curves.

RESULTS

The mean CR values in the right N1 (0.149459 vs. 0.194505), left N1 (0.133328 vs. 0.169160), right N2 (0.230245 vs. 0.278181), left N2 (0.235784 vs. 0.314169), right N1 + N2 (0.155322 vs. 0.278143), left N1 + N2 (0.140991 vs. 0.276755), right whole SNpc (0.131397 vs. 0.141422), and left whole SNpc (0.127099 vs. 0.137873) significantly differed between IPD patients and HCs (all p < 0.001). The areas under the curve of the left N1 + N2, right N1 + N2, left N1, right N1, left N2, right N2, left whole SNpc, and right whole SNpc were 0.994 (sensitivity, 98.0%; specificity, 94.0%), 0.985, 0.804, 0.802, 0.777, 0.766, 0.632, and 0.606, respectively.

CONCLUSION

Our NM-MRI template-based CR measurements revealed significant differences between early-stage IPD patients and HCs. The CR values of the left N1 + N2 demonstrated the highest diagnostic performance.

MRI multiparametric scoring system for pial blood supply of intracranial meningiomas

Background

Meningiomas are occasionally fed by pial blood supply (PBS). It is postulated that peritumoral flow void (PTFV), peritumoral brain edema (PTBE), and absence of an arachnoid plane (AP) are useful parameters for evaluating PBS.

Purpose

To determine whether conventional magnetic resonance imaging (MRI) using a multiparametric scoring system (MSS) is a useful way to predict PBS.

Material and Methods

Forty-six patients were included and divided: PBS and non-PBS groups. Differences between the groups in six parameters of MR imaging were analyzed: tumor size, tumor location, PTBE grade, AP grade, PTFV, and MIB1 labeling index (MIB1-LI) grade. Cutoff values were determined using receiver operating characteristic (ROC) curve analysis for the differentiation of both groups based on statistically significant parameters. All cases were scored as 1 (PBS) or 0 (non-PBS) for each parameter according to set thresholds. Individual scores were totaled for each case, yielding a combined score for each case to obtain a cutoff value using ROC curve analysis for the MSS.

Results

Peritumoral brain edema grade, AP grade, PTFV, and MIB-LI grade were statistically associated with PBS. Receiver operating characteristic curve analyses showed that PTBE grade 3 or 4, AP grade 3 or 4, and PTFV positivity had the highest accuracy of 69%, 64%, and 68%, respectively. Regarding the MSS, a cutoff value of 2 had the highest accuracy of 71%; PBS diagnosis was indicated by at least two of the three parameters, namely, PTBE grade, AP grade, and PTFV.

Conclusion

The MSS is a useful way to predict PBS in intracranial meningiomas on MRI.

Dopamine Transporter Imaging, Current Status of a Potential Biomarker: A Comprehensive Review

A major goal of current clinical research in Parkinson's disease (PD) is the validation and standardization of biomarkers enabling early diagnosis, predicting outcomes, understanding PD pathophysiology, and demonstrating target engagement in clinical trials. Molecular imaging with specific dopamine-related tracers offers a practical indirect imaging biomarker of PD, serving as a powerful tool to assess the status of presynaptic nigrostriatal terminals. In this review we provide an update on the dopamine transporter (DAT) imaging in PD and translate recent findings to potentially valuable clinical practice applications. The role of DAT imaging as diagnostic, preclinical and predictive biomarker is discussed, especially in view of recent evidence questioning the incontrovertible correlation between striatal DAT binding and nigral cell or axon counts.

Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review recent developments in nigral imaging for Parkinson disease and other parkinsonian syndromes, including nigrosome imaging, neuromelanin imaging, quantitative iron mapping, and diffusion-tensor imaging. In particular, this article examines nigrosome imaging using 7-T MRI and 3-T susceptibility-weighted imaging. Finally, this article discusses volumetry and its clinical importance related to symptom manifestation. This review will improve understanding of recent advancements in nigral imaging of Parkinson disease. Published under a CC BY 4.0 license.

Early-stage Parkinson's disease: Abnormal nigrosome 1 and 2 revealed by a voxelwise analysis of neuromelanin-sensitive MRI

Previous pathologic studies evaluated the substantia nigra pars compacta (SNpc) of a limited number of idiopathic Parkinson's disease (IPD) patients with relatively longer disease durations. Therefore, it remains unknown which region of the SNpc is most significantly affected in early‐stage IPD. We hypothesized that a voxelwise analysis of thin‐section neuromelanin‐sensitive MRI (NM‐MRI) may help determine the significantly affected regions of the SNpc in early‐stage IPD and localize these areas in each nigrosome on high‐spatial‐resolution susceptibility map‐weighted imaging (SMwI). Ninety‐six healthy subjects and 50 early‐stage IPD patients underwent both a 0.8 × 0.8 × 0.8 mm³ NM‐MRI and a 0.5 × 0.5 × 1.0 mm³ multi‐echo gradient‐recalled echo imaging for SMwI. Both NM‐MRI and SMwI templates were created by using image data from the 96 healthy subjects. Permutation‐based nonparametric tests were conducted to investigate spatial differences between the two groups in NM‐MRI, and the results were displayed on both NM‐MRI and SMwI templates. The posterolateral and anteromedial regions of the SNpc in NM‐MRI were significantly different between the two groups, corresponding to the nigrosome 1 and nigrosome 2 regions, respectively, on the SMwI template. There were the areas of significant spatial difference in the hypointense SN on SMwI between early‐stage IPD patients and healthy subjects. These areas on SMwI were slightly greater than those on NM‐MRI, including the areas showing group difference on NM‐MRI. Our voxelwise analysis of NM‐MRI suggests that two regions (nigrosome 1 and nigrosome 2) of the SNpc are separately affected in early‐stage IPD.

Diagnostic performance of neuromelanin-sensitive magnetic resonance imaging for patients with Parkinson's disease and factor analysis for its heterogeneity: a systematic review and meta-analysis

OBJECTIVE

To determine the diagnostic performance of neuromelanin-sensitive magnetic resonance imaging discriminating between patients with Parkinson's disease and normal healthy controls and to identify factors causing heterogeneity influencing the diagnostic performance.

METHODS

A systematic literature search in the Ovid-MEDLINE and EMBASE databases was performed for studies reporting the relevant topic before February 17, 2020. The pooled sensitivity and specificity values with their 95% confidence intervals were calculated using bivariate random-effects modeling. Subgroup and meta-regression analyses were also performed to determine factors influencing heterogeneity.

RESULTS

Twelve articles including 403 patients with Parkinson's disease and 298 control participants were included in this systematic review and meta-analysis. Neuromelanin-sensitive magnetic resonance imaging showed a pooled sensitivity of 89% (95% confidence interval, 86-92%) and a pooled specificity of 83% (95% confidence interval, 76-88%). In the subgroup and meta-regression analysis, a disease duration longer than 5 and 10 years, comparisons using measured volumes instead of signal intensities, a slice thickness in terms of magnetic resonance imaging parameters of more than 2 mm, and semi-/automated segmentation methods instead of manual segmentation improved the diagnostic performance.

CONCLUSION

Neuromelanin-sensitive magnetic resonance imaging had a favorable diagnostic performance in discriminating patients with Parkinson's disease from healthy controls. To improve diagnostic accuracy, further investigations directly comparing these heterogeneity-affecting factors and optimizing these parameters are necessary.

KEY POINTS

• Neuromelanin-sensitive MRI favorably discriminates patients with Parkinson's disease from healthy controls. • Disease duration, parameters used for comparison, magnetic resonance imaging slice thickness, and segmentation methods affected heterogeneity across the studies.

Spatiotemporal changes in substantia nigra neuromelanin content in Parkinson’s disease

This study aimed to investigate the spatiotemporal changes in neuromelanin-sensitive MRI signal in the substantia nigra and their relation to clinical scores of disease severity in patients with early or progressing Parkinson’s disease and patients with idiopathic rapid eye movement sleep behaviour disorder (iRBD) exempt of Parkinsonian signs compared to healthy control subjects. Longitudinal T1-weighted anatomical and neuromelanin-sensitive MRI was performed in two cohorts, including patients with iRBD, patients with early or progressing Parkinson’s disease, and control subjects. Based on the aligned substantia nigra segmentations using a study-specific brain anatomical template, parametric maps of the probability of a voxel belonging to the substantia nigra were calculated for patients with various degrees of disease severity and controls. For each voxel in the substantia nigra, probability map of controls, correlations between signal-to-noise ratios on neuromelanin-sensitive MRI in patients with iRBD and Parkinson’s disease and clinical scores of motor disability, cognition and mood/behaviour were calculated. Our results showed that in patients, compared to the healthy control subjects, the volume of the substantia nigra was progressively reduced for increasing disease severity. The neuromelanin signal changes appeared to start in the posterolateral motor areas of the substantia nigra and then progressed to more medial areas of this region. The ratio between the volume of the substantia nigra in patients with Parkinson’s disease relative to the controls was best fitted by a mono-exponential decay. Based on this model, the pre-symptomatic phase of the disease started at 5.3 years before disease diagnosis, and 23.1% of the substantia nigra volume was lost at the time of diagnosis, which was in line with previous findings using post-mortem histology of the human substantia nigra and radiotracer studies of the human striatum. Voxel-wise patterns of correlation between neuromelanin-sensitive MRI signal-to-noise ratio and motor, cognitive and mood/behavioural clinical scores were localized in distinct regions of the substantia nigra. This localization reflected the functional organization of the nigrostriatal system observed in histological and electrophysiological studies in non-human primates (motor, cognitive and mood/behavioural domains). In conclusion, neuromelanin-sensitive MRI enabled us to assess voxel-wise modifications of substantia nigra’s morphology in vivo in humans, including healthy controls, patients with iRBD and patients with Parkinson’s disease, and identify their correlation with nigral function across all motor, cognitive and behavioural domains. This insight could help assess disease progression in drug trials of disease modification.

Semi-Automatic Signature-Based Segmentation Method for Quantification of Neuromelanin in Substantia Nigra

In Parkinson's disease (PD), there is a reduction of neuromelanin (NM) in the substantia nigra (SN). Manual quantification of the NM volume in the SN is unpractical and time-consuming; therefore, we aimed to quantify NM in the SN with a novel semi-automatic segmentation method. Twenty patients with PD and twelve healthy subjects (HC) were included in this study. T1-weighted spectral pre-saturation with inversion recovery (SPIR) images were acquired on a 3T scanner. Manual and semi-automatic atlas-free local statistics signature-based segmentations measured the surface and volume of SN, respectively. Midbrain volume (MV) was calculated to normalize the data. Receiver operating characteristic (ROC) analysis was performed to determine the sensitivity and specificity of both methods. PD patients had significantly lower SN mean surface (37.7 ± 8.0 vs. 56.9 ± 6.6 mm²) and volume (235.1 ± 45.4 vs. 382.9 ± 100.5 mm³) than HC. After normalization with MV, the difference remained significant. For surface, sensitivity and specificity were 91.7 and 95 percent, respectively. For volume, sensitivity and specificity were 91.7 and 90 percent, respectively. Manual and semi-automatic segmentation methods of the SN reliably distinguished between PD patients and HC. ROC analysis shows the high sensitivity and specificity of both methods.

Biomarkers for Parkinson's Disease: How Good Are They?

Parkinson's disease (PD) is a complex neurodegenerative disorder with no cure in sight. Clinical challenges of the disease include the inability to make a definitive diagnosis at the early stages and difficulties in predicting the disease progression. The unmet demand to identify reliable biomarkers for early diagnosis and management of the disease course of PD has attracted a lot of attention. However, only a few reported candidate biomarkers have been tried in clinical practice at the present time. Studies on PD biomarkers have often overemphasized the discovery of novel identity, whereas efforts to further evaluate such candidates are rare. Therefore, we update the new development of biomarker discovery in PD and discuss the standard process in the evaluation and assessment of the diagnostic or prognostic value of the identified potential PD biomarkers in this review article. Recent developments in combined biomarkers and the current status of clinical trials of biomarkers as outcome measures are also discussed. We believe that the combination of different biomarkers might enhance the specificity and sensitivity over a single measure that might not be sufficient for such a multiplex disease.

Advances in the Research of Risk Factors and Prodromal Biomarkers of Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. With the advent of an aging population and improving life expectancy worldwide, the number of PD patients is expected to increase, which may lead to an urgent need for effective preventive and diagnostic strategies for PD. Although there is increasing research regarding the pathogenesis of PD, there is limited knowledge regarding the prevention of PD. Moreover, the diagnosis of PD depends on clinical criteria, which require the occurrence of bradykinesia and at least one symptom of rest tremor or rigidity. However, converging evidence from clinical, genetic, neuropathological, and imaging studies suggests the initiation of PD-specific pathology prior to the initial presentation of these classical motor clinical features by years or decades. This latent stage of neurodegeneration in PD is a particularly important stage for effective neuroprotective therapies, which might retard the progression or prevent the onset of PD. Therefore, the exploration of risk factors and premotor biomarkers is not only crucial to the early diagnosis of PD but is also helpful in the development of effective neuroprotection and health care strategies for appropriate populations at risk for PD. In this review, we searched and summarized ∼249 researches and 31 reviews focusing on the risk factors and prodromal biomarkers of PD and published in MEDLINE.

Cerebrospinal Fluid Levels of Autophagy-related Proteins Represent Potentially Novel Biomarkers of Early-Stage Parkinson's Disease

The roles of autophagy-related proteins as diagnostic or monitoring biomarkers in Parkinson's disease (PD) have not been clearly elucidated. We recruited 32 patients with early-stage PD and 28 control subjects, and evaluated parkinsonian motor symptoms and dopamine transporter imaging data. Cerebrospinal fluid (CSF) levels of LC3B, Beclin1, and LAMP-2 were estimated using ELISAs, and CSF levels of ATG5, ATG7, and p62 were examined by immunoblotting. Additionally, we also assessed the levels of α-synuclein, total tau, and phosphorylated tau in CSF using ELISAs. Significant differences in the levels of LC3B, LAMP-2, and Beclin1 were observed between the PD and control groups. Using 29.8 pg/mL as the cut-off value for a diagnostic biomarker of PD, CSF LC3B levels exhibited high sensitivity (96.9%) and specificity (89.3%) with an area under the curve of 0.982. Furthermore, LC3B was significantly correlated with the asymmetry index in the caudate and putamen, as estimated by a semi-quantitative analysis of [¹⁸F] N-(3-fluoropropyl)-2β-carbon ethoxy-3β-(4-iodophenyl) nortropane (FP-CIT) positron emission tomography (PET). CSF levels of LC3B represented a potential diagnostic and prognostic biomarker of early-stage PD in patients. Based on our findings, molecular biological changes in PD are associated with dysregulation of the lysosomal autophagy pathway.