Imaging the Autonomic Nervous System in Parkinson's Disease

Manual and semi-automated approaches to MIBG myocardial scintigraphy in patients with Parkinson's disease

Objective

This study investigates the effects of manual and semi-automatic methods for assessing MIBG semi-quantitative indices in a clinical setting.

Materials and methods

We included ¹²³I-MIBG scans obtained in 35 patients with idiopathic Parkinson's Disease. Early and late heart-to-mediastinum (H/M) ratios were calculated from ¹²³I-MIBG images using regions of interest (ROIs) placed over the heart and the mediastinum. The ROIs were derived using two approaches: (i) manually drawn and (ii) semi-automatic fixed-size ROIs using anatomical landmarks. Expert, moderate-expert, and not expert raters applied the ROIs procedures and interpreted the ¹²³I-MIBG images. We evaluated the inter and intra-rater agreements in assessing ¹²³I-MIBG H/M ratios.

Results

A moderate agreement in the raters' classification of pathological and non-pathological scores emerged regarding early and late H/M ratio values (κ = 0.45 and 0.69 respectively), applying the manual method, while the early and late H/M ratios obtained with the semi-automatic method reached a good agreement among observers (κ = 0.78). Cohen-Kappa values revealed that the semi-automatic method improved the agreement between expert and inexpert raters: the agreement improved from a minimum of 0.29 (fair, for early H/M) and 0.69 (substantial, in late H/M) with the manual method, to 0.90 (perfect, in early H/M) and 0.87 (perfect, in late H/M) with the semi-automatic method.

Conclusion

The use of the semi-automatic method improves the agreement among raters in classifying' H/M ratios as pathological or non-pathological, namely for inexpert readers. These results have important implications for semi-quantitative assessment of ¹²³I-MIBG images in clinical routine.

The gut-brain axis and Parkinson disease: clinical and pathogenetic relevance

Gastrointestinal disorders are one of the most significant non-motor problems affecting people with Parkinson disease (PD). Pathogenetically, the gastrointestinal tract has been proposed to be the initial site of pathological changes in PD. Intestinal inflammation and alterations in the gut microbiota may contribute to initiation and progression of pathology in PD. However, the mechanisms underlying this "gut-brain" axis in PD remain unclear. PD patients can display a large variety of gastrointestinal symptoms, leading to reduced quality of life and psychological distress. Gastrointestinal disorders can also limit patients' response to medications, and consequently negatively impact on neurological outcomes. Despite an increasing research focus, gastrointestinal disorders in PD remain poorly understood and their clinical management often suboptimal. This review summarises our understanding of the relevance of the "gut-brain" axis to the pathogenesis of PD, discusses the impact of gastrointestinal disorders in patients with PD, and provides clinicians with practical guidance to their management.

Parkinson's disease outside the brain: targeting the autonomic nervous system

Patients with Parkinson's disease present with signs and symptoms of dysregulation of the peripheral autonomic nervous system that can even precede motor deficits. This dysregulation might reflect early pathology and therefore could be targeted for the development of prodromal or diagnostic biomarkers. Only a few objective clinical tests assess disease progression and are used to evaluate the entire spectrum of autonomic dysregulation in patients with Parkinson's disease. However, results from epidemiological studies and findings from new animal models suggest that the dysfunctional autonomic nervous system is a probable route by which Parkinson's disease pathology can spread both to and from the CNS. The autonomic innervation of the gut, heart, and skin is affected by α-synuclein pathology in the early stages of the disease and might initiate α-synuclein spread via the autonomic connectome to the CNS. The development of easy-to-use and reliable clinical tests of autonomic nervous system function seems crucial for early diagnosis, and for developing strategies to stop or prevent neurodegeneration in Parkinson's disease.

[123I]Metaiodobenzylguanidine (MIBG) Cardiac Scintigraphy and Automated Classification Techniques in Parkinsonian Disorders

PURPOSE

To provide reliable and reproducible heart/mediastinum (H/M) ratio cut-off values for parkinsonian disorders using two machine learning techniques, Support Vector Machines (SVM) and Random Forest (RF) classifier, applied to [¹²³I]MIBG cardiac scintigraphy.

PROCEDURES

We studied 85 subjects, 50 with idiopathic Parkinson's disease, 26 with atypical Parkinsonian syndromes (P), and 9 with essential tremor (ET). All patients underwent planar early and delayed cardiac scintigraphy after [¹²³I]MIBG (111 MBq) intravenous injection. Images were evaluated both qualitatively and quantitatively; the latter by the early and delayed H/M ratio obtained from regions of interest (ROIt₁ and ROIt₂) drawn on planar images. SVM and RF classifiers were finally used to obtain the correct cut-off value.

RESULTS

SVM and RF produced excellent classification performances: SVM classifier achieved perfect classification and RF also attained very good accuracy. The better cut-off for H/M value was 1.55 since it remains the same for both ROIt₁ and ROIt_2. This value allowed to correctly classify PD from P and ET: patients with H/M ratio less than 1.55 were classified as PD while those with values higher than 1.55 were considered as affected by parkinsonism and/or ET. No difference was found when early or late H/M ratio were considered separately thus suggesting that a single early evaluation could be sufficient to obtain the final diagnosis.

CONCLUSIONS

Our results evidenced that the use of SVM and CT permitted to define the better cut-off value for H/M ratios both in early and in delayed phase thus underlining the role of [¹²³I]MIBG cardiac scintigraphy and the effectiveness of H/M ratio in differentiating PD from other parkinsonism or ET. Moreover, early scans alone could be used for a reliable diagnosis since no difference was found between early and late. Definitely, a larger series of cases is needed to confirm this data.

Assessment of Gastrointestinal Autonomic Dysfunction: Present and Future Perspectives

The autonomic nervous system delicately regulates the function of several target organs, including the gastrointestinal tract. Thus, nerve lesions or other nerve pathologies may cause autonomic dysfunction (AD). Some of the most common causes of AD are diabetes mellitus and α-synucleinopathies such as Parkinson’s disease. Widespread dysmotility throughout the gastrointestinal tract is a common finding in AD, but no commercially available method exists for direct verification of enteric dysfunction. Thus, assessing segmental enteric physiological function is recommended to aid diagnostics and guide treatment. Several established assessment methods exist, but disadvantages such as lack of standardization, exposure to radiation, advanced data interpretation, or high cost, limit their utility. Emerging methods, including high-resolution colonic manometry, 3D-transit, advanced imaging methods, analysis of gut biopsies, and microbiota, may all assist in the evaluation of gastroenteropathy related to AD. This review provides an overview of established and emerging assessment methods of physiological function within the gut and assessment methods of autonomic neuropathy outside the gut, especially in regards to clinical performance, strengths, and limitations for each method.

Premotor Parkinson's disease: Overview of clinical symptoms and current diagnostic methods

Parkinson's disease (PD) is characterized by typical motor symptoms. However, recent studies show several non-motor features that may precede the development of the motor symptoms of PD. The best known premotor symptoms include hyposmia, REM sleep behavior disorder (RBD), constipation, and depression; other symptoms are excessive daytime somnolence, orthostatic hypotension and symptomatic hypotension, erectile or urinary dysfunction, musculoskeletal symptoms, pain, and global cognitive deficit. In this review, we summarize currently available diagnostic methods for these symptoms. We also briefly summarize neuroimaging, polyneuropathy, peripheral markers, and cerebrospinal fluid biomarkers that may be used in the early diagnosis of PD.

Predictive Value of Midsagittal Tissue Bridges on Functional Recovery After Spinal Cord Injury

Background

The majority of patients with spinal cord injury (SCI) have anatomically incomplete lesions and present with preserved tissue bridges, yet their outcomes vary.

Objective

To assess the predictive value of the anatomical location (ventral/dorsal) and width of preserved midsagittal tissue bridges for American Spinal Injury Association (ASIA) Impairment Scale (AIS) grade conversion and SCI patient stratification into recovery-specific subgroups.

Methods

This retrospective longitudinal study includes 70 patients (56 men, age: 52.36 ± 18.58 years) with subacute (ie, 1 month) SCI (45 tetraplegics, 25 paraplegics), 1-month neuroimaging data, and 1-month and 12-month clinical data. One-month midsagittal T2-weighted scans were used to determine the location and width of tissue bridges. Their associations with functional outcomes were assessed using partial correlation and unbiased recursive partitioning conditional inference tree (URP-CTREE).

Results

Fifty-seven (81.4%) of 70 patients had tissue bridges (2.53 ± 2.04 mm) at 1-month post-SCI. Larger ventral (P = .001, r = 0.511) and dorsal (P < .001, r = 0.546) tissue bridges were associated with higher AIS conversion rates 12 months post-SCI (n = 39). URP-CTREE analysis identified 1-month ventral tissue bridges as predictors of 12-month total motor scores (0.4 mm cutoff, P = .008), recovery of upper extremity motor scores at 12 months (1.82 mm cutoff, P = .002), 12-month pin-prick scores (1.4 mm cutoff, P = .018), and dorsal tissue bridges at 1 month as predictors of 12-month Spinal Cord Independence Measure scores (0.5 mm cutoff, P = .003).

Conclusions

Midsagittal tissue bridges add predictive value to baseline clinical measures for post-SCI recovery. Based on tissue bridges’ width, patients can be classified into subgroups of clinical recovery profiles. Midsagittal tissue bridges provide means to optimize patient stratification in clinical trials.

Nuclear Imaging in the Diagnosis of Clinically Uncertain Parkinsonian Syndromes

BACKGROUND

Parkinsonian syndromes are classified by etiology mainly on clinical grounds, that is, on the basis of the clinical manifestations and with the aid of conventional ancillary studies. In most cases, the clinical diagnosis is clear. In up to 30% of cases, however, the etiological classification remains uncertain after completion of the basic clinical diagnostic evaluation, and additional investigation with nuclear imaging may be indicated. In particular, cerebral single-photon emission computed tomography (SPECT) with dopamine transporter (DAT) ligands may be helpful. DAT-SPECT can be used to demonstrate or rule out nigrostriatal degeneration and thereby differentiate neurodegenerative parkinsonian syndromes from symptomatic parkinsonian syndromes and other differential diagnoses. Positron emission tomography (PET) with the glucose analogue [18F]fluorodeoxyglucose (FDG) can be used to identify disease-specific patterns of neuronal dysfunction/degeneration in order to differentiate the various neurodegenerative parkinsonian syndromes from one another.

METHODS

In this review, we summarize the current state of the evidence on DAT-SPECT and FDG-PET for the indications mentioned above on the basis of a selective review of the literature.

RESULTS

DAT-SPECT has been adequately validated as an in vivo marker for nigrostriatal degeneration. Studies using the clinical diagnosis of a movement disorders specialist over the course of the disease as a reference have shown that DAT- SPECT is 78-100% sensitive (median, 93%) and 70-100% specific (median, 89%) for the differentiation of neurodegenerative parkinsonian syndromes from symptomatic parkinsonism and other differential diagnoses in clinically unclear cases. DAT- SPECT scanning led to a change of diagnosis in 27-56% of patients (median, 43%) and to a change of treatment in 33-72% (median, 43%). FDG-PET enables the differentiation of atypical neurodegenerative parkinsonian syndromes from the idiopathic parkinsonian syndrome (i.e., Parkinson's disease proper) with high sensitivity and specificity (both approximately 90%), when the clinical diagnosis by a movement disorders specialist over the course of the disease is used as a reference.

CONCLUSION

DAT-SPECT has been well documented to be highly diagnostically accurate and to have a relevant influence on the diagnosis and treatment of patients with clinically uncertain parkinsonian or tremor syndrome. It has not yet been shown to improve patient-relevant endpoints such as mortality, morbidity, and health-related quality of life; proof of this will probably have to await the introduction of neuroprotective treatments. The current evidence for the high differential diagnostic accuracy of FDG-PET in neurodegenerative parkinsonian syndromes needs to be reinforced by prospective studies with neuropathological verification of the diagnosis.

α-Synuclein oligomers in skin biopsy of idiopathic and monozygotic twin patients with Parkinson's disease

A variety of cellular processes, including vesicle clustering in the presynaptic compartment, are impaired in Parkinson’s disease and have been closely associated with α-synuclein oligomerization. Emerging evidence proves the existence of α-synuclein-related pathology in the peripheral nervous system, even though the presence of α-synuclein oligomers in situ in living patients remains poorly investigated. In this case-control study, we show previously undetected α-synuclein oligomers within synaptic terminals of autonomic fibres in skin biopsies by means of the proximity ligation assay and propose a procedure for their quantification (proximity ligation assay score). Our study revealed a significant increase in α-synuclein oligomers in consecutive patients with Parkinson’s disease compared to consecutive healthy controls (P < 0.001). Proximity ligation assay score (threshold value > 96 using receiver operating characteristic) was found to have good sensitivity, specificity and positive predictive value (82%, 86% and 89%, respectively). Furthermore, to disclose the role of putative genetic predisposition in Parkinson’s disease aetiology, we evaluated the differential accumulation of oligomers in a unique cohort of 19 monozygotic twins discordant for Parkinson’s disease. The significant difference between patients and healthy subjects was confirmed in twins. Intriguingly, although no difference in median values was detected between consecutive healthy controls and healthy twins, the prevalence of healthy subjects positive for proximity ligation assay score was significantly greater in twins than in the consecutive cohort (47% versus 14%, P = 0.019). This suggests that genetic predisposition is important, but not sufficient, in the aetiology of the disease and strengthens the contribution of environmental factors. In conclusion, our data provide evidence that α-synuclein oligomers accumulate within synaptic terminals of autonomic fibres of the skin in Parkinson’s disease for the first time. This finding endorses the hypothesis that α-synuclein oligomers could be used as a reliable diagnostic biomarker for Parkinson’s disease. It also offers novel insights into the physiological and pathological roles of α-synuclein in the peripheral nervous system.

Translation Imaging in Parkinson's Disease: Focus on Neuroinflammation

Parkinson's disease (PD) is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the appearance of α-synuclein insoluble aggregates known as Lewy bodies. Neurodegeneration is accompanied by neuroinflammation mediated by cytokines and chemokines produced by the activated microglia. Several studies demonstrated that such an inflammatory process is an early event, and contributes to oxidative stress and mitochondrial dysfunctions. α-synuclein fibrillization and aggregation activate microglia and contribute to disease onset and progression. Mutations in different genes exacerbate the inflammatory phenotype in the monogenic compared to sporadic forms of PD. Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) with selected radiopharmaceuticals allow in vivo imaging of molecular modifications in the brain of living subjects. Several publications showed a reduction of dopaminergic terminals and dopamine (DA) content in the basal ganglia, starting from the early stages of the disease. Moreover, non-dopaminergic neuronal pathways are also affected, as shown by in vivo studies with serotonergic and glutamatergic radiotracers. The role played by the immune system during illness progression could be investigated with PET ligands that target the microglia/macrophage Translocator protein (TSPO) receptor. These agents have been used in PD patients and rodent models, although often without attempting correlations with other molecular or functional parameters. For example, neurodegeneration and brain plasticity can be monitored using the metabolic marker 2-Deoxy-2-[¹⁸F]fluoroglucose ([¹⁸F]-FDG), while oxidative stress can be probed using the copper-labeled diacetyl-bis(N-methyl-thiosemicarbazone) ([Cu]-ATSM) radioligand, whose striatal-specific binding ratio in PD patients seems to correlate with a disease rating scale and motor scores. Also, structural and functional modifications during disease progression may be evaluated by Magnetic Resonance Imaging (MRI), using different parameters as iron content or cerebral volume. In this review article, we propose an overview of in vivo clinical and non-clinical imaging research on neuroinflammation as an emerging marker of early PD. We also discuss how multimodal-imaging approaches could provide more insights into the role of the inflammatory process and related events in PD development.

Relationship between the washout rate of I-123 MIBG scans and autonomic function in Parkinson's disease

Purpose

We have evaluated the clinical significance of the washout rate (WR) on I-123 MIBG scans through the analysis of the relationship between the I-123 MIBG scans and autonomic status in patients with Parkinson’s disease (PD).

Materials and methods

Sixty patients with clinical PD who had decreased HMR were enrolled. An autonomic symptom was evaluated using a head-up tilt test and the Composite Autonomic Severity Score (CASS). An I-123 MIBG scan and F-18 FP-CIT positron emission tomography (PET) were performed. All of the patients were classified into three groups according to the WR. The differences in patient characteristics and the imaging parameters among the three groups were evaluated, and a correlation analysis was also performed.

Results

The frequency of orthostatic hypotension was significantly different among the three groups. The difference in systolic pressure (dSysPr) and the difference in diastolic pressure (dDiaPr) of group 3 was significantly larger than those of groups 1 and 2. From the correlation analysis, it can be seen that age, Hoehn and Yahr (H&Y) stage, dSysPr, and dDiaPr had a weak positive correlation with the WR. The total CASS score was significantly higher in group 3 compared with groups 1 and 2. The WR had a moderate positive correlation with the cardiosympathetic score and the total CASS score.

Conclusion

The WR is related to autonomic dysfunction. An I-123 MIBG cardiac scan is considered to be a good method to evaluate not only the differential diagnosis of Parkinson's disease but also the degree of autonomic dysfunction.

Biomarkers of Parkinson's disease: 20 years later

Despite intensive effort, biomarker research for the detection of prodromal stage, diagnosis and progression of Parkinson's disease (PD) falls short of expectations. This article reviews the attempts in the last 20 years to find a biomarker, addresses challenges along the biomarker search and suggests the steps that should be taken to overcome these challenges. Although several biomarkers are currently available, none of them is specific enough for diagnosis, prediction of future PD or disease progression. The main reason for the failure finding a strong biomarker seems to be drastic heterogeneity of PD, which exhibits itself in all domains; from the clinic to pathophysiology or genetics. The diversity in patient selection, assessment methods or outcomes in biomarker studies also limit the interpretation and generalizability of the data. In search of a reliable biomarker, consideration of novel approaches encompassing individual demographic, clinical, genetic, epigenetic and environmental differences, employment of strategies enabling marker combinations, designing multicenter studies with compatible assessment methods, integration of data from preclinical domains and utilization of novel technology-based assessments are necessary.