Neurodegenerative Parkinsonian Syndromes Research Articles

Predictive biomarkers for cognitive decline in patients with idiopathic REM sleep behavior disorder

AbstractBackgroundIdiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is regarded as an early stage of the synucleinopathy, which may precede the onset of cognitive impairment or parkinsonism. Biomarkers for cognitive decline in patients with iRBD would be helpful to early intervention. Our aim was to identify biomarkers for predicting the cognitive deterioration risk in patients with iRBD.MethodWe involved patients with polysomnographically confirmed iRBD who has at least 2 visits from the Parkinson’s Progression Markers Initiative (PPMI) database. Progression of cognitive state to MCI or dementia during follow‐up was defined as the endpoint. Baseline clinical features, biofluid and genetic biomarkers were compared between iRBD with or without progression of cognitive decline. Predictive biomarkers were identified with Kaplan‐Meier and Cox proportional hazards analysis, adjusting for age, sex, and years of education.ResultA total of 38 patients with iRBD were enrolled (average age: 69.53 ± 5.54, male: 84.21%) . During follow‐up (median 5.45, IQR 4.08‐7.1 years), Progression of cognitive decline occurred in 57.89% (22/38) patients with iRBD. Baseline clinical features including hallucinations and psychosis (HR = 13.783, p = 0.022) and higher confidence abnormalities consistent with a neurodegenerative parkinsonian syndrome (HR = 2.258, p = 0.017) increased the risk. Patients with a lower loge‐transformed the ratio of Aβ 1‐42 in cerebrospinal fluid (CSF) to ΝfL in serum (Aβ/NfL, HR = 0.375, p = 0.044) and t‐tau in CSF to ΝfL in serum (t‐tau/NfL, HR = 0.277, p = 0.044) had a higher risk of cognitive decline. Genetic biomarkers consisting of GBA rs75548401(HR = 13.783, p = 0.022), STK39 rs1955337 (HR = 11.882, p<0.001), and COMT rs4680 (HR = 2.376, p = 0.021) variants increased the risk, while MCCC1 rs12637471 (HR = 0.408, p = 0.024), COMT rs165656 (HR = 0.451, p = 0.033), COMT rs4633 (HR = 0.421, p = 0.021), and COMT rs165599 (HR = 0.427, p = 0.023) variants decreased the risk. A model combining age and variables with p<0.05 exhibited above presented the best predictive performance, with an AUC of 0.963 (95% CI 0.896–1.000, p<0.001).ConclusionOur findings provide potential biomarkers to evaluate the risk of progression to MCI or dementia in patients with iRBD. Combination of clinical features, biofluid and genetic biomarkers performs optimal predicting accuracy.

Clinical Utility of Skin Biopsy Compared to DaTscan in Diagnosing Synucleinopathies (P3-11.001)

<h3>Objective:</h3> To compare the utility of skin biopsy versus DaTscan in supporting a diagnosis of a synucleinopathy. <h3>Background:</h3> Though the diagnosis of synucleinopathies (Lewy Body Dementia, Parkinson’s disease, Multiple System Atrophy, Pure Autonomic Failure) is clinical, there are supportive tests that can aid in the diagnosis. SPECT imaging with DaTscan (Ioflupane 123-I SPECT) identifies pre-synaptic dopaminergic deficits, which helps distinguish neurodegenerative parkinsonian syndromes from non-dopamine deficiency disorders. Skin biopsy in identifies the presence of phosphorylated synuclein (p-syn) within cutaneous nerves, and can help distinguish synucleinopathies from other atypical parkinsonian syndromes and non-parkinsonian disorders. <h3>Design/Methods:</h3> 24 patients were identified that were seen in the movement disorders clinic for possible parkinsonism. All patients underwent a DaTscan and a skin biopsy (3 small punch biopsies in the cervical area, thigh and leg). DaTscan and skin biopsy results were compared to clinician’s suspected diagnosis (prior to testing, synucleinopathy vs other disorder) to assess diagnostic efficacy. <h3>Results:</h3> DaTscan results were congruent with clinician’s suspected diagnosis in 15/24 cases (62.5%). Skin biopsy results were congruent with clinician’s suspected diagnosis in 20/24 cases (83.3%). In two cases, the skin biopsy was positive for p-syn deposition where a synucleinopathy was not suspected. In 8 patients where the DaTscan was negative but clinician suspicion for a synucleinopathy was high, skin biopsies were positive. <h3>Conclusions:</h3> Skin biopsy had greater diagnostic accuracy than the DaTscan when compared to the clinician’s suspected pre-testing diagnosis. This suggests that performing skin biopsies (minimally invasive, lower cost, can be done in the office) may be of higher diagnostic utility than a DaTscan. <b>Disclosure:</b> Dr. Urval has nothing to disclose. Dr. Meytin has nothing to disclose. Dr. Dorfman has nothing to disclose. Dr. Lahrmann has nothing to disclose. Dr. Bortan has nothing to disclose. Dr. Dagostine has received personal compensation for serving as an employee of Adamas. Dr. Dagostine has received personal compensation for serving as an employee of Neurocrine. Dr. Dagostine has received personal compensation for serving as an employee of Boston Scientific. Dr. Dagostine has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Adamas. Dr. Dagostine has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Neurocrine. Dr. Dagostine has received personal compensation in the range of $10,000-$49,999 for serving on a Speakers Bureau for Adamas. Dr. Dagostine has received personal compensation in the range of $10,000-$49,999 for serving on a Speakers Bureau for Neurocrine. Dr. Duffy has stock in Meru Health. An immediate family member of Dr. Moro-de-Casillas has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Medtronic. An immediate family member of Dr. Moro-de-Casillas has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Intuitive. The institution of Dr. Moro-de-Casillas has received research support from Davis Phinney Foundation. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Supernus. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Neurocrine. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Abbvie. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Adamas. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Ipsen. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Kyowa Kirin. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Merz. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Neurocrine. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Sunovion. Dr. Machado has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Teva. Dr. Kanchana has nothing to disclose. Dr. DeMarcaida has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Abbvie. Dr. DeMarcaida has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Teva. Dr. DeMarcaida has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Acorda. Dr. DeMarcaida has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Kyowa Kirin. The institution of Dr. DeMarcaida has received research support from Pharma2B. The institution of Dr. DeMarcaida has received research support from Neuroderm. The institution of Dr. DeMarcaida has received research support from Addex.

Same same but different: dopamine transporter SPECT on scanners with CZT vs. NaI detectors

BackgroundThe aims of this study were to establish a normal database (NDB) for semiquantification of dopamine transporter (DAT) single-photon emission computed tomography (SPECT) with [123I]FP-CIT on a cadmium zinc telluride (CZT) camera, test the preexisting NaI-derived NDB for use in CZT scans, and compare the diagnostic findings in subjects imaged with a CZT scanner with either the preexisting NaI-based NDB or our newly defined CZT NDB.MethodsThe sample comprised 73 subjects with clinically uncertain parkinsonian syndrome (PS) who prospectively underwent [123I]FP-CIT SPECT on a CZT camera according to standard guidelines with identical acquisition and reconstruction protocols (DaTQUANT). Two experienced readers visually assessed the images and binarized the subjects into “non-neurodegenerative PS” and “neurodegenerative PS”. Twenty-five subjects from the “non-neurodegenerative PS” subgroup were randomly selected to establish a CZT NDB. The remaining 48 subjects were defined as “test group”. DaTQUANT was used to determine the specific binding ratio (SBR). For the test group, SBR values were transformed to z-scores for the putamen utilizing both the CZT NDB and the manufacturer-provided NaI-based NDB (GE NDB). A predefined fixed cut-off of -2 was used for dichotomization of z-scores to classify neurodegenerative and non-neurodegenerative PS. Performance of semiquantification using the two NDB to identify subjects with neurodegenerative PS was assessed in comparison with the visual rating. Furthermore, a randomized head-to-head comparison of both detector systems was performed semiquantitatively in a subset of 32 out of all 73 subjects.ResultsCompared to the visual rating as reference, semiquantification based on the dedicated CZT NDB led to fewer discordant ratings than the GE NDB in CZT scans (3 vs. 8 out of 48 subjects). This can be attributed to the putaminal z-scores being consistently higher with the GE NDB on a CZT camera (median absolute difference of 1.68), suggesting an optimal cut-off of -0.5 for the GE NDB instead of -2.0. Average binding ratios and z-scores were significantly lower in CZT compared to NaI data.ConclusionsUse of a dedicated, CZT-derived NDB is recommended in [123I]FP-CIT SPECT with a CZT camera since it improves agreement between semiquantification and visual assessment.

Diagnosis of vascular parkinsonism: A new tool for gait hypokinesia occurring in older persons

IntroductionReliable diagnosis of vascular parkinsonism (VaP) in the presence of a gait hypokinesia is an issue that is encountered in geriatrics. The EVAMAR-AGEX study was focusing on the phenomenon of recurrent falls in older persons (OP) with this parkinsonian gait. The present study is focusing on the diagnosis of VaP-related parkinsonian gait by developing a diagnostic guidance model adapted to OP. MethodsData from baseline and the 2-year follow-up visit were used to carry out univariate analysis and calculation of odds ratios, allowing to identify relevant variables to include in the diagnostic guidance model. To evaluate the model, confusion matrices were created, evaluating true positive, false negative, false positive and true negative incidences, sensitivity and specificity, and negative and positive predictive values. Results79 patients included 58% male; average age 81.24 years. VaP diagnosis according to Zijlmans criteria occurred in 28%; neurodegenerative parkinsonian syndromes in 72%. A 4-criteria model was established to facilitate diagnostic: lack of prior hallucinations, lack of movement disorders tremor excluded, no cognitive fluctuations, and ≥75 years of age at diagnosis. In combination of 4/4 criteria, all of them were required to disclose a specificity of 91% in the diagnosis of VaP. In combination of 3/4, in case of negative test, a negative predictive value for VaP diagnosis of 0.97 was obtained. ConclusionThe challenge of our tool is both to be able to rule out what is probably not a VaP and to argue what makes a VaP diagnosis probable in OP.

Nigral glucose metabolism as a diagnostic marker of neurodegenerative parkinsonian syndromes

Parkinson’s disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP) are characterized by nigrostriatal degeneration. We used [18F]FDG PET to assess glucose metabolism of the substantia nigra (SN) in patients with these diseases and evaluated its ability to discriminate neurodegenerative parkinsonian syndromes (NP) from controls. We retrospectively evaluated [18F]FDG PET scans of 171 patients with NP (n = 115 PD, n = 35 MSA, n = 21 PSP) and 48 controls (13 healthy controls [HC] and 35 control patients). Mean normalized bilateral [18F]FDG uptake in the SN was calculated and compared between groups with covariance and receiver operating characteristic (ROC) analyses (selection of the optimal cut-off required a minimum specificity of 90% to meet the clinical need of a confirmatory test). PD patients were additionally stratified by the expression of the well-established PD-related metabolic pattern (PDRP; elevated expression defined as 2 standard deviations above the mean value of HC). [18F]FDG uptake was significantly lower in NP (Cohen’s d = 1.09, p < 0.001) and its subgroups (PD, d = 1.10, p < 0.001; MSA, d = 0.97, p < 0.001; PSP, d = 1.79, p < 0.001) than in controls. ROC analysis for discriminating NP vs. controls revealed an area under the curve of 0.81 and a sensitivity and specificity of 56 and 92%. Moreover, nigral metabolism was below the cut-off in 60% of PD patients without elevated PDRP expression. Glucose metabolism of the SN can distinguish patients with NP from controls with good diagnostic accuracy and can be used as a marker of nigral degeneration. Its evaluation is particularly valuable in PD patients without elevated PDRP expression and may thus help to narrow the diagnostic gap of [18F]FDG PET in neurodegenerative parkinsonism (i.e., identification of patients with PD without cortical involvement).

18F]FE-PE2I PET is a feasible alternative to [123I]FP-CIT SPECT for dopamine transporter imaging in clinically uncertain parkinsonism

BackgroundDopamine transporter (DAT) imaging of striatum is clinically used in Parkinson’s disease (PD) and neurodegenerative parkinsonian syndromes (PS) especially in the early disease stages. The aim of the present study was to evaluate the diagnostic performance of the recently developed tracer for DAT imaging [18F]FE-PE2I PET/CT to the reference standard [123I]FP-CIT SPECT.MethodsNinety-eight unselected patients referred for DAT imaging were included prospectively and consecutively and evaluated with [18F]FE-PE2I PET/CT and [123I]FP-CIT SPECT on two separate days. PET and SPECT scans were categorized independently by two blinded expert readers as either normal, vascular changes, or mixed. Semiquantitative values were obtained for each modality and compared regarding effect size using Glass’ delta.ResultsFifty-six of the [123I]FP-CIT SPECT scans were considered abnormal (52 caused by PS, 4 by infarctions). Using [18F]FE-PE2I PET/CT, 95 of the 98 patients were categorized identically to SPECT as PS or non-PS with a sensitivity of 0.94 [0.84–0.99] and a specificity of 1.00 [0.92–1.00]. Inter-reader agreement for [18F]FE-PE2I PET with a kappa of 0.97 [0.89–1.00] was comparable to the agreement for [123I]FP-CIT SPECT of 0.96 [0.76–1.00]. Semiquantitative values for short 10-min reconstructions of [18F]FE-PE2I PET/CT were comparable to longer reconstructions. The effect size for putamen/caudate nucleus ratio was significantly increased using PET compared to SPECT.ConclusionsThe high correspondence of [18F]FE-PE2I PET compared to reference standard [123I]FP-CIT SPECT establishes [18F]FE-PE2I PET as a feasible PET tracer for clinical use with favourable scan logistics.

Development and validation of a radiomic model for the diagnosis of dopaminergic denervation on [18F]FDOPA PET/CT

PurposeFDOPA PET shows good performance for the diagnosis of striatal dopaminergic denervation, making it a valuable tool for the differential diagnosis of Parkinsonism. Textural features are image biomarkers that could potentially improve the early diagnosis and monitoring of neurodegenerative parkinsonian syndromes. We explored the performances of textural features for binary classification of FDOPA scans.MethodsWe used two FDOPA PET datasets: 443 scans for feature selection, and 100 scans from a different PET/CT system for model testing. Scans were labelled according to expert interpretation (dopaminergic denervation versus no dopaminergic denervation). We built LASSO logistic regression models using 43 biomarkers including 32 textural features. Clinical data were also collected using a shortened UPDRS scale.ResultsThe model built from the clinical data alone had a mean area under the receiver operating characteristics (AUROC) of 63.91. Conventional imaging features reached a maximum score of 93.47 but the addition of textural features significantly improved the AUROC to 95.73 (p < 0.001), and 96.10 (p < 0.001) when limiting the model to the top three features: GLCM_Correlation, Skewness and Compacity. Testing the model on the external dataset yielded an AUROC of 96.00, with 95% sensitivity and 97% specificity. GLCM_Correlation was one of the most independent features on correlation analysis, and systematically had the heaviest weight in the classification model.ConclusionA simple model with three radiomic features can identify pathologic FDOPA PET scans with excellent sensitivity and specificity. Textural features show promise for the diagnosis of parkinsonian syndromes.

Neuroimaging in Parkinson’s Disease: necessity or exaggeration?

Neuroimaging plays an increasingly important role in the diagnosis of parkinsonian syndromes. In this paper, the authors elaborate on the necessity of using magnetic resonance imaging (MRI) in Parkinson's Disease (PD) and its potential role in differential diagnosis versus other neurodegenerative parkinsonian syndromes such as dementia with Lewy bodies, multiple system atrophy, progressive supranuclear palsy and corticobasal syndrome. The currently known characteristic abnormalities are listed and tabulated, current recommendations are summarised and sample images are provided. As routine MRI scanning in PD remains controversial, the authors' aim is to show the pros and cons in clinical practice. Additionally, the rationale for functional imaging examination, including [123I]-FP-CIT SPECT (DaTSCAN) and [99mTc]- HMPAO-SPECT, [18F]-FDG-PET, [123I]-mIBG-SPECT is discussed. This paper is accompanied by two illustrative clinical cases in which neuroimaging studies played a key role in diagnosis and further management. Neuroimaging can be helpful in differentiating PD from both atypical and symptomatic parkinsonism. Nevertheless, extensive neurological assessment in a majority of PD cases is sufficient to make a diagnosis. A network of specialists in movement disorders should be established in order to enable better, faster and more precise diagnosis of parkinsonism.

Data-driven identification of diagnostically useful extrastriatal signal in dopamine transporter SPECT using explainable AI

This study used explainable artificial intelligence for data-driven identification of extrastriatal brain regions that can contribute to the interpretation of dopamine transporter SPECT with 123I-FP-CIT in parkinsonian syndromes. A total of 1306 123I-FP-CIT-SPECT were included retrospectively. Binary classification as ‘reduced’ or ‘normal’ striatal 123I-FP-CIT uptake by an experienced reader served as standard-of-truth. A custom-made 3-dimensional convolutional neural network (CNN) was trained for classification of the SPECT images with 1006 randomly selected images in three different settings: “full image”, “striatum only” (3-dimensional region covering the striata cropped from the full image), “without striatum” (full image with striatal region removed). The remaining 300 SPECT images were used to test the CNN classification performance. Layer-wise relevance propagation (LRP) was used for voxelwise quantification of the relevance for the CNN-based classification in this test set. Overall accuracy of CNN-based classification was 97.0%, 95.7%, and 69.3% in the “full image”, “striatum only”, and “without striatum” setting. Prominent contributions in the LRP-based relevance maps beyond the striatal signal were detected in insula, amygdala, ventromedial prefrontal cortex, thalamus, anterior temporal cortex, superior frontal lobe, and pons, suggesting that 123I-FP-CIT uptake in these brain regions provides clinically useful information for the differentiation of neurodegenerative and non-neurodegenerative parkinsonian syndromes.

Unexpected (123I)FP-CIT SPECT findings: SWIDD, SWEDD and all DAT.

Although the diagnosis of Parkinson's disease (PD) is essentially clinical, the implementation of imaging techniques can improve diagnostic accuracy. While some techniques (e.g. magnetic resonance imaging-MRI, computerized tomography-CT) are used to exclude secondary syndromes, presynaptic dopaminergic imaging including imaging of dopamine transporter (DAT)-can help the Neurologist in the differential diagnosis between neurodegenerative parkinsonian syndromes and parkinsonism without dopamine deficiency. DAT imaging can be useful in cases in which the clinical picture is not univocal, as in case of overlapping clinical features in patients with early disease, atypical syndromes or unsatisfying response to therapy. Currently, (123I)FP-CIT ([123I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane) (trade name DaTSCAN) is the only agent approved by international regulatory agencies for this purpose. With the increasing use of this technique, some unexpected findings have been reported, including patients clinically diagnosed with PD with a normal SPECT scan [e.g. Scans Without Evidence of Dopaminergic Deficit (SWEDD)]; PD patients with a greater dopaminergic deficit in the striatum ipsilateral to the clinicallymore affected side [e.g. Scans With Ipsilateral Dopaminergic Deficit (SWIDD)]; as well as some artifacts. Moreover, the neurologist must remember that structural lesions and administration of some drugs might alter the result of DAT imaging. Unexpected findings, artifacts, and misinterpretation of imaging findings can lead to an erroneous diagnosis and inappropriate therapy, neglect of other medical conditions that might explain the clinical picture, and undermine the selection phase in clinical trials. The aim of the present review is to bring clarity on these controversial (and sometimes erroneous) results, in order to informof these possibilities the clinicians requesting a DaTSCAN in clinical practice.

Differentiating neurodegenerative parkinsonian syndromes using vestibular evoked myogenic potentials and balance assessment

ObjectiveVestibular evoked myogenic potentials (VEMP) were investigated to differentiate between parkinsonian syndromes. We correlated balance and VEMP parameters to investigate the VEMP brainstem circuits as possible origin for postural instability. MethodsWe assessed clinical status, ocular and cervical VEMP (oVEMP, cVEMP) and conducted a balance assessment (posturography, Activities-specific Balance Confidence Scale, Berg Balance Scale, modified Barthel Index) in 76 subjects: 30 with Parkinson’s disease (PD), 16 with atypical parkinsonism (AP) and 30 healthy controls. VEMP were elicited by using a mini-shaker on the forehead. ResultsPatients with PD had a prolonged oVEMP n10 in comparison to controls and prolonged p15 compared to controls and AP. Patients with AP showed reduced oVEMP amplitudes compared to PD and controls. CVEMP did not differ between groups. Postural impairment was higher in AP compared to controls and PD, particularly in the rating scales. No correlations between VEMP and posturography were found. A support vector machine classifier was able to automatically classify controls and patient subgroups with moderate to good accuracy based on oVEMP latencies and balance questionnaires. ConclusionsBoth oVEMP and posturography, but not cVEMP, may be differentially affected in PD and AP. We did not find evidence that impairment of the cVEMP or oVEMP pathways is directly related to postural impairment. SignificanceOVEMP and balance assessment could be implemented in the differential diagnostic work-up of parkinsonian syndromes.

Distinct Vestibular Evoked Myogenic Potentials in Patients With Parkinson Disease and Progressive Supranuclear Palsy.

Background: Early brainstem neurodegeneration is common in Parkinson's disease (PD) and progressive supranuclear palsy (PSP). While previous work showed abnormalities in vestibular evoked myogenic potentials (VEMPs) in patients with either disorder as compared to healthy humans, it remains unclear whether ocular and cervical VEMPs differ between PD and PSP patients.Methods: We prospectively included 12 PD and 11 PSP patients, performed ocular and cervical VEMPs, and calculated specific VEMP scores (0 = normal, 12 = most pathological) based on latencies, amplitude, and absent responses. In addition, we assessed disease duration, presence of imbalance, motor asymmetry, and motor disability using the Movement Disorder Society Unified Parkinson's Disease Rating Scale, part III (MDS-UPDRS III). Moreover, we ascertained various sleep parameters by video-polysomnography.Results: PSP and PD patients had similar oVEMP scores (6 [3–6] vs. 3 [1.3–6], p = 0.06), but PSP patients had higher cVEMP scores (3 [0–6] vs. 0 [0–2.8], p = 0.03) and total VEMP scores (9 [5–12] vs. 4 [2–7.5], p = 0.01). Moreover, total VEMP scores >10 were only observed in PSP patients (45%, p = 0.01). MDS-UPDRS III correlated with cVEMP scores (rho = 0.77, p = 0.01) in PSP, but not in PD. In PD, but not in PSP, polysomnographic markers of disturbed sleep, including decreased rapid eye movement sleep, showed significant correlations with VEMP scores.Conclusions: Our findings suggest that central vestibular pathways are more severely damaged in PSP than in PD, as indicated by higher cervical and total VEMP scores in PSP than PD in a between-groups analysis. Meaningful correlations between VEMPs and motor and non-motor symptoms further encourage its use in neurodegenerative Parkinsonian syndromes.

Impact of age and sex correction on the diagnostic performance of dopamine transporter SPECT

PurposeThe specific binding ratio (SBR) of 123I-FP-CIT (FP-CIT) in the putamen decreases with age by about 5% per decade and most likely is about 10% higher in females. However, the clinical utility of age and sex correction of the SBR is still a matter of debate. This study tested the impact of age and sex correction on the diagnostic performance of the putamen SBR in three independent patient samples.MethodsResearch sample: 207 healthy controls (HC) and 438 Parkinson’s disease (PD) patients. Clinical sample A: 183 patients with neurodegenerative parkinsonian syndrome (PS) and 183 patients with non-neurodegenerative PS from one site. Clinical sample B: 84 patients with neurodegenerative PS and 38 patients with non-neurodegenerative PS from another site. Correction for age and sex of the putamen SBR was based on linear regression in the HC or non-neurodegenerative PS, separately in each sample. The area under the ROC curve (AUC) was used as performance measure.ResultsThe putamen SBR was higher in females compared to males (PPMI: 14%, p < 0.0005; clinical sample A: 7%, p < 0.0005; clinical sample B: 6%, p = 0.361). Age-related decline of the putamen SBR ranged between 3.3 and 10.4% (p ≤ 0.019). In subjects ≥ 50 years, age and sex explained < 10% of SBR between-subjects variance. Correction of the putamen SBR for age and sex resulted in slightly decreased AUC in the PPMI sample (0.9955 versus 0.9969, p = 0.025) and in clinical sample A (0.9448 versus 0.9519, p = 0.057). There was a small, non-significant AUC increase in clinical sample B (0.9828 versus 0.9743, p = 0.232).ConclusionThese findings do not support age and sex correction of the putaminal FP-CIT SBR in the diagnostic workup of parkinsonian syndromes. This most likely is explained by the fact that the proportion of between-subjects variance caused by age and sex is considerably below the symptom threshold of about 50% reduction in neurodegenerative PS.

Parkinsonian gait in elderly people: Significance of the threshold value of two and more falls per year.

Parkinsonism in the elderly presents a major risk factor for recurrent falls (2 and more falls per year), which is associated with increased morbidity. The main objective was to investigate explanatory variables relating to the risk of being recurrent fallers (RF) in persons with parkinsonian gait. Seventy-nine among 172 eligible persons were enrolled in this prospective study, the findings of which were analyzed at 12 months. Motor and non-motor features, as well as follow-up interviews to identify falls, loss of ability to walk, fluctuating cognition, traumatic falls, all-cause hospitalizations and deaths were collated and results compared between non RF (zero and one fall per year) and RF. Bayesian model averaging was used to predict the probability of patients being RF from their medical history as well as from cognitive assessment, gait velocity, vision and posture. N=79, 0.58 men, 50% had Parkinson's disease, 14% other neurodegenerative parkinsonian syndrome, 23% vascular parkinsonism and 13% Lewy body disease, 58% were RF. Median age 81.2 years and median MMSE 25/30. A history of falls and of hallucinations, median odds ratio respectively 9.06 (CI 2.34-38.22), 4.21 (CI 1.04-18.67) were associated with the highest odds ratios along with fluctuating cognition and abnormal posture. Two or more falls a year was a relevant threshold to distinguish a population with a high risk of comorbidity. The whole history of falls, hallucinations and fluctuating cognition can be considered predictive of recurrent falls in elderly people with parkinsonian gait and provide a tracking tool for patient management.

Recommendation for the differentiated use of nuclear medical diagnostic for parkinsonian syndromes

The present work provides an overview of the various nuclear medicine methods in the diagnosis of neurodegenerative parkinsonian syndromes and their respective evidence and is intended to enable practical decision-making aids in the application and interpretation of the methods and findings. The value of the procedures differs considerably in relation to the two relevant diagnostic questions. On the one hand, it is the question of whether there is a neurodegenerative parkinsonian syndrome at all, and on the other hand the question of which one. While the DAT-SPECT is undisputedly the method of choice for answering the first question (taking certain parameters into account), this method is not suitable for answering the second question. To categorise parkinsonian syndromes into idiopathic (i. e. Parkinson´s disease) or atypical, various procedures are used in everyday clinical practice including MIBG scintigraphy, and FDG-PET. We explain why FDG-PET currently is not only the most suitable of these methods to differentiate an idiopathic parkinsonian syndrome, from an atypical Parkinson's syndrome, but also enables sufficiently valid to distinguish the various atypical neurodegenerative Parkinson's syndromes (i. e. MSA, PSP and CBD) from each other and therefore should be reimbursed by health insurances.

Impact of the size of the normal database on the performance of the specific binding ratio in dopamine transporter SPECT

BackgroundThis study investigated the impact of the size of the normal database on the classification performance of the specific binding ratio (SBR) in dopamine transporter (DAT) SPECT with [123I]FP-CIT in different settings.MethodsThe first subject sample comprised 645 subjects from the Parkinson’s Progression Marker Initiative (PPMI), 207 healthy controls (HC), and 438 Parkinson’s disease (PD) patients. The second sample comprised 372 patients from clinical routine patient care, 186 with non-neurodegenerative parkinsonian syndrome (PS) and 186 with neurodegenerative PS. Single-photon emission computed tomography (SPECT) images of the clinical sample were reconstructed with two different reconstruction algorithms (filtered backprojection, iterative ordered subsets expectation maximization (OSEM) reconstruction with resolution recovery). The putaminal specific binding ratio (SBR) was computed using an anatomical region of interest (ROI) predefined in standard (MNI) space in the Automated Anatomic Labeling (AAL) atlas or using hottest voxels (HV) analysis in large predefined ROIs. SBR values were transformed to z-scores using mean and standard deviation of the SBR in a normal database of varying sizes (n = 5, 10, 15,…, 50) randomly selected from the HC subjects (PPMI sample) or the patients with non-neurodegenerative PS (clinical sample). Accuracy, sensitivity, and specificity for identifying patients with PD or neurodegenerative PS were determined as performance measures using a predefined fixed cutoff on the z-score. This was repeated for 10,000 randomly selected normal databases, separately for each size of the normal database. Mean and 5th percentile of the performance measures over the 10,000 realizations were computed. Accuracy, sensitivity, and specificity when using the whole set of HC or non-neurodegenerative PS subjects as normal database were used as benchmark.ResultsMean loss of accuracy of the putamen SBR z-score was below 1% when the normal database included at least 15 subjects, independent of subject sample (PPMI or clinical), reconstruction method (filtered backprojection or OSEM), and ROI method (AAL or HV). However, the variability of the accuracy of the putamen SBR z-score decreased monotonically with increasing size of normal database and was still considerable at size 15. In order to achieve less than 5% “maximum” loss of accuracy (defined by the 5th percentile) in all settings required at least 25 to 30 subjects in the normal database. Reduction of mean and “maximum” loss of accuracy of the putamen SBR z-score by further increasing the size of the normal database was very small beyond size 40.ConclusionsThe results of this study suggest that 25 to 30 is the minimum size of the normal database to reliably achieve good performance of semi-quantitative analysis in dopamine transporter (DAT) SPECT, independent of the algorithm used for image reconstruction and the ROI method used to estimate the putaminal SBR.

Nuclear Imaging in the Diagnosis of Clinically Uncertain Parkinsonian Syndromes.

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. 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. 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. 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.

PET Imaging of Astrogliosis and Tau Facilitates Diagnosis of Parkinsonian Syndromes.

Neurodegenerative parkinsonian syndromes comprise a number of disorders that are characterized by similar clinical features but are separated on the basis of different pathologies, i.e., aggregates of α-synuclein or tau protein. Due to the overlap of signs and symptoms a precise differentiation is often difficult, especially early in the disease course. Enormous efforts have been taken to develop tau-selective PET imaging agents, but strong off-target binding to monoamine oxidase B (MAO-B) has been observed across first generation ligands. Nonetheless, astrogliosis-related MAO-B elevation is a common histopathological known feature of all parkinsonian syndromes and might be itself an interesting imaging target. Therefore, this study aimed to investigate the performance of [18F]-THK5351, a combined MAO-B and tau tracer for differential diagnosis of parkinsonian syndromes. [18F]-THK5351 PET was performed in 34 patients: six with Parkinson’s disease (PD), nine with multiple system atrophy with predominant parkinsonism (MSA-P), six with MSA with predominant cerebellar ataxia (MSA-C), and 13 with progressive supranuclear palsy (PSP) Richardson’s syndrome. Volume-of-interest-based quantification of standardized-uptake-values was conducted in different parkinsonian syndrome-related target regions. PET results were subjected to multinomial logistic regression to create a prediction model discriminating among groups. Furthermore, we correlated tracer uptake with clinical findings. Elevated [18F]-THK5351 uptake in midbrain and diencephalon differentiated PSP patients from PD and MSA-C. MSA-C patients were distinguishable by high tracer uptake in the pons and cerebellar deep white matter when compared to PSP and PD patients, whereas MSA-P patients tended to show higher tracer uptake in the lentiform nucleus. A multinomial logistic regression classified 33/34 patients into the correct clinical diagnosis group. Tracer uptake in the pons, cerebellar deep white matter, and striatum was closely associated with the presence of cerebellar and parkinsonian symptoms of MSA patients. The current study demonstrates that combined MAO-B and tau binding of THK5351 facilitates differential diagnosis of parkinsonian syndromes. Furthermore, our data indicate a correlation of MSA phenotype with [18F]-THK5351 uptake in certain brain regions, illustrating their relevance for the emergence of clinical symptoms and underlining the potential of THK5351 PET as a biomarker that correlates with pathological changes as well as with disease stage.

Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics.

This study investigated the potential of deep convolutional neural networks (CNN) for automatic classification of FP-CIT SPECT in multi-site or multi-camera settings with variable image characteristics. The study included FP-CIT SPECT of 645 subjects from the Parkinson's Progression Marker Initiative (PPMI), 207 healthy controls, and 438 Parkinson's disease patients. SPECT images were smoothed with an isotropic 18-mm Gaussian kernel resulting in 3 different PPMI settings: (i) original (unsmoothed), (ii) smoothed, and (iii) mixed setting comprising all original and all smoothed images. A deep CNN with 2,872,642 parameters was trained, validated, and tested separately for each setting using 10 random splits with 60/20/20% allocation to training/validation/test sample. The putaminal specific binding ratio (SBR) was computed using a standard anatomical ROI predefined in MNI space (AAL atlas) or using the hottest voxels (HV) analysis. Both SBR measures were trained (ROC analysis, Youden criterion) using the same random splits as for the CNN. CNN and SBR trained in the mixed PPMI setting were also tested in an independent sample from clinical routine patient care (149 with non-neurodegenerative and 149 with neurodegenerative parkinsonian syndrome). Both SBR measures performed worse in the mixed PPMI setting compared to the pure PPMI settings (e.g., AAL-SBR accuracy = 0.900 ± 0.029 in the mixed setting versus 0.957 ± 0.017 and 0.952 ± 0.015 in original and smoothed setting, both p < 0.01). In contrast, the CNN showed similar accuracy in all PPMI settings (0.967 ± 0.018, 0.972 ± 0.014, and 0.955 ± 0.009 in mixed, original, and smoothed setting). Similar results were obtained in the clinical sample. After training in the mixed PPMI setting, only the CNN provided acceptable performance in the clinical sample. These findings provide proof of concept that a deep CNN can be trained to be robust with respect to variable site-, camera-, or scan-specific image characteristics without a large loss of diagnostic accuracy compared with mono-site/mono-camera settings. We hypothesize that a single CNN can be used to support the interpretation of FP-CIT SPECT at many different sites using different acquisition hardware and/or reconstruction software with only minor harmonization of acquisition and reconstruction protocols.

Differential diagnosis of parkinsonian syndromes using dopamine transporter and perfusion SPECT

ObjectiveWe aimed to assess whether a combined analysis of dopamine transporter (DAT)- and perfusion-SPECT images (or either) could: (1) distinguish atypical parkinsonian syndromes (APS) from Lewy body diseases (LBD; majority Parkinson disease [PD]), and (2) differentiate among APS subgroups (progressive supranuclear palsy [PSP], corticobasal syndrome [CBS], and multiple system atrophy [MSA]). MethodsWe recruited consecutive patients with neurodegenerative parkinsonian syndromes (LBD, n = 46; APS, n = 33). Individual [123I]FP-CIT- and [123I]iodoamphetamine-SPECT images were coregistered onto anatomical MRI segmented into brain regions. Striatal DAT activity and regional perfusion were extracted from each brain region for each patient and submitted to logistic regression analyses. Stepwise procedures were used to select predictors that should be included in the models to distinguish APS from LBD, and differentiate among the APS subgroups. Receiver-operating characteristic (ROC) analyses were performed to measure diagnostic power. Leave-one-out cross-validation (LOOCV) was performed to evaluate the diagnostic accuracy. ResultsThe model to discriminate APS from LBD showed that the area under the ROC curve (AUC) was 0.923, while the total diagnostic accuracy (TDA) was 86.1% in LOOCV. In the model to distinguish PSP, CBS, and MSA from LBD, the AUC/TDA values were 0.978/94.6%, 0.978/87.0%, and 0.880/80.3%, respectively. In the model to differentiate between CBS and MSA, MSA and PSP, and PSP and CBS, the AUC/TDA values were 0.967/91.3%, 0.920/88.0%, 0.875/77.8%, respectively. ConclusionAn image-based automated classification using striatal DAT activity and regional perfusion patterns provided a good performance in the differential diagnosis of neurodegenerative parkinsonian syndromes without clinical information.