Evidence Of Dopaminergic Deficit Research Articles

Long-term follow-up study of SWEDD patients with mild parkinsonian signs

BackgroundWhether scan without evidence of dopaminergic deficit (SWEDD) can be a reliable indication of a clinical entity of Parkinson’s disease (PD) is controversial.ObjectiveTo evaluate the proportion of SWEDD patients with...

Distinctive clinical and imaging trajectories in SWEDD and Parkinson’s disease patients

A proportion of patients clinically diagnosed with Parkinson’s disease (PD) can have a 123I-FP-CIT-SPECT scan without evidence of dopaminergic deficit (SWEDD), generating a debate about the underlying biological mechanisms. This study investigated differences in clinical features, 123I-FP-CIT binding, molecular connectivity, as well as clinical and imaging progression between SWEDD and PD patients.We included 36 SWEDD, 49 de novo idiopathic PD, and 49 healthy controls with 123I-FP-CIT-SPECT from the Parkinson’s Progression Markers Initiative. Clinical and imaging 2-year follow-ups were available for 27 SWEDD and 40 PD. Regional-based and voxel-wise analysis assessed dopaminergic integrity in dorsal and ventral striatal, as well as extrastriatal regions, at baseline and follow-up. Molecular connectivity analyses evaluated dopaminergic pathways. Spatial correlation analyses tested whether 123I-FP-CIT-binding alterations would also pertain to the serotoninergic system.SWEDD and PD patients showed comparable symptoms at baseline, except for hyposmia, which was more severe for PD. PD showed significantly lower striatal and extrastriatal 123I-FP-CIT-binding compared to SWEDD and controls. SWEDD exhibited lower binding than controls in striatal regions, insula, and olfactory cortex. Both PD and SWEDD showed extensive altered connectivity of dopaminergic pathways, however, with major impairment in the mesocorticolimbic system for SWEDD. Motor symptoms and dopaminergic deficits worsened after 2 years for PD only.The limited dopaminergic impairment and its stability over time observed for SWEDD, as well as the presence of extrastriatal 123I-FP-CIT binding alterations and prevalent mesocorticolimbic connectivity impairment, suggest other mechanisms contributing to SWEDD pathophysiology.

Association between body mass index (BMI) and [123I]Ioflupane (DaTSCAN) availabilities in patients with parkinsonism using single-photon emission computed tomography–computed tomography (SPECT-CT)

Aim[123I]Ioflupane (DaTSCAN) has a high binding affinity to the dopamine (DA) transporter (DaT) and tenfold less affinity to serotonin (5-HT) transporter (SERT). Both neurotransmitters are considered to contribute to body weight regulation. This study assesses the association between body mass index (BMI) and DaTSCAN availability in brain.MethodScans from 74 consecutive patients who had undergone DaTSCAN single-photon emission computed tomography–computed tomography (SPECT-CT) were used to obtain semi- and absolute quantitative data in several volumes of interest (VOIs). Relative semi-quantitative specific binding ratios (SBRs) from Chang attenuated SPECT were obtained from GE DaTQUANT. Absolute normalised concentration (NC) was calculated from attenuation/scatter corrected SPECT-CT images, using an adapted version of the EARL Ltd (European Association of Nuclear Medicine (EANM) Research 4 Life) template. Scans were subdivided into either degenerative parkinsonism (abnormal = 49), borderline (n = 14) or scan without evidence of dopaminergic deficit (SWEDD = 11) using visual assessment and SBR values by two nuclear medicine consultants.ResultsSBRs did not correlate with BMI. However, NC values correlated negatively in the entire cohort, with the strongest correlation in the frontal (r = − 0.649. p = 0.000), occipital (r = − 0.555, p = 0.000) regions and pons (r = − 0.555, p = 0.000). In the abnormal (n = 49) and SWEDD group (n = 11), NC of the frontal region was the most correlated with BMI (r = − 0.570, p = 0.000; r = − 0.813, p = 0.002, respectively). In the borderline group (n = 14), the left posterior putamen displayed the strongest correlation (r = − 0.765, p = 0.001).ConclusionAbsolute NC values demonstrate a strong inverse correlation with BMI, strongest in the extrastriatal regions. Due to the predominately non-overlapping distribution of DaT and SERT, this study suggests greater involvement of SERT in obesity with possible interplay with DA transmission.

Cerebrospinal fluid biomarkers profile in scans without evidence of dopaminergic deficits (SWEDD)

BackgroundA small proportion of patients with clinical parkinsonism have normal transporter-single photon emission computed tomography (DaTSPECT) which is commonly defined as scans without evidence of dopaminergic deficits (SWEDD). A better understanding of SWEDD can improve the current therapeutic options and appropriate disease monitoring. AimWe aimed to assess CSF biomarkers levels including α-synuclein (α-syn), amyloid βeta (Aβ1–42), total tau (t-tau), and phosphorylated tau (p-tau) in SWEDD and investigate the longitudinal alteration in the CSF profile. MethodsIn total, 406 early-stage PD, 58 SWEDD, and 187 healthy controls (HCs) were entered into our study from PPMI. We compared the level of CSF biomarkers at baseline, six months, one year, and two years. Furthermore, the longitudinal alteration of CSF biomarkers was explored in each group using linear mixed models. ResultsThere was no significant difference in the level of CSF α-syn Aβ1–42, t-tau, and p-tau between HCs and SWEDD at different time points. Investigating the level of CSF α-syn in PD and SWEDD showed a significant difference at one (p = 0.016) and two years (p = 0.006). Also, we observed a significant difference in the level of CSF Aβ1–42 between SWEDD and PD at one year (p = 0.012). Moreover, there was a significant difference in the level of CSF t-tau between SWEDD and PD subjects at one (p = 0.013) and two years (p = 0.017). Furthermore, there was a significant difference in the level of CSF p-tau between SWEDD and PD groups at two years visits (p = 0.030). Longitudinal analysis showed a significant decrease after one (p = 0.029) and two years (p = 0.002) from baseline in the level of CSF α-syn only in the PD group. Also, we observed that the level of CSF Aβ1–42 significantly increased after one year in SWEDD (p = 0.031) and decreased after two years from baseline in PD subjects (p = 0.005). Moreover, there was a significant increase in the level of CSF t-tau after two years (p = 0.036) and CSF p-tau after six months from baseline in SWEDD subjects (p = 0.011). ConclusionThis finding suggests a faster neurodegeneration process in PD patients compared to SWEDD at least based on these biomarkers. Future studies with longer follow-up duration and more sample sizes are necessary to validate our results.

Quantitative [123]I-Ioflupane DaTSCAN single-photon computed tomography-computed tomography in Parkinsonism.

[123]I-Ioflupane (DaTSCAN) binds to the presynaptic dopamine transporter (DAT) and with a lower affinity to the serotonin transporter (SERT). We aimed to develop a novel method to quantify absolute uptake in the striatal (predominantly DAT binding) and extra-striatal regions (mainly SERT binding) using single-photon computed tomography-computed tomography (SPECT-CT) DaTSCAN and to improve DaTSCAN image quality. Twenty-six patients with Parkinsonism underwent DaTSCAN SPECT-CT prospectively. The scans were visually analyzed independently by two experienced reporters. Specific binding ratios (SBRs) from Chang attenuation corrected SPECT were obtained using GE DaTQuant. Normalized concentrations and specific uptakes (NSU) from measured attenuation and modelled scatter-corrected SPECT-CT were obtained using HERMES Hybrid Recon and Affinity and modified EARL volumes of interest. Striatal NSU and SBR positively correlate ( R = 0.65-0.88, P = 0.00). SBR, normalized concentrations, and NSU box plots differentiated between scans without evidence of dopaminergic deficit and abnormal scans. Interestingly, body weight inversely correlated with normalized concentrations values in extra-striatal regions [frontal ( R = 0.81, P = 0.00); thalamus ( R = 0.58, P = 0.00); occipital ( R = 0.69, P = 0.00)] and both caudate nuclei [ R = 0.42, P = 0.03 (Right), R = 0.52, P = 0.01 (Left)]. Both reporters noted improved visual quality of SPECT-CT versus SPECT images for all scans. DaTSCAN SPECT-CT resulted in more accurate quantification, improved image quality, and enabled absolute quantification of extra-striatal regions. More extensive studies are required to establish the full value of absolute quantification for diagnosis and monitoring the progression of neurodegenerative disease, to assess an interplay between DAT and SERT, and to verify whether serotonin and DATs are potentially dysfunctional in obesity.

Comparison of resting tremor at the upper limb joints between patients with Parkinson's disease and scans without evidence of dopaminergic deficit.

A representative symptom of Parkinson's disease (PD) is resting tremor. The clinical manifestation of scans without evidence of dopaminergic deficit (SWEDD) is similar to it of PD, though the phenomenology of SWEDD is not well known. In the present study, the resting tremor of 9 SWEDD patients was quantitatively compared with that of 11 PD patients. Four 3-axis gyro sensors were attached on the index finger, thumb, dorsum of the hand, and arm of the more tremulous side. Root mean square (RMS) angular speed and angular displacement as well as irregularity of angular speed and displacement were derived from the sensor data. Although disease duration and Hoehn and Yahr stages were comparable, SWEDD patients exhibited different tremor features from PD patients. Significantly faster RMS angular speed and greater RMS angular displacement (p< 0.05) were observed in PD patients than in SWEDD patients. The irregularity of angular displacement of pitch direction at the dorsum of the hand was greater in SWEDD patients than in PD patients (p< 0.05). These results indicate that quantitative indices obtained from resting tremor task could be important biomarkers for identifying potential patients with SWEDD among patients diagnosed with PD.

Assessment of heterogeneity among participants in the Parkinson's Progression Markers Initiative cohort using α-synuclein seed amplification: a cross-sectional study

Emerging evidence shows that α-synuclein seed amplification assays (SAAs) have the potential to differentiate people with Parkinson's disease from healthy controls. We used the well characterised, multicentre Parkinson's Progression Markers Initiative (PPMI) cohort to further assess the diagnostic performance of the α-synuclein SAA and to examine whether the assay identifies heterogeneity among patients and enables the early identification of at-risk groups. This cross-sectional analysis is based on assessments done at enrolment for PPMI participants (including people with sporadic Parkinson's disease from LRRK2 and GBA variants, healthy controls, prodromal individuals with either rapid eye movement sleep behaviour disorder (RBD) or hyposmia, and non-manifesting carriers of LRRK2 and GBA variants) from 33 participating academic neurology outpatient practices worldwide (in Austria, Canada, France, Germany, Greece, Israel, Italy, the Netherlands, Norway, Spain, the UK, and the USA). α-synuclein SAA analysis of CSF was performed using previously described methods. We assessed the sensitivity and specificity of the α-synuclein SAA in participants with Parkinson's disease and healthy controls, including subgroups based on genetic and clinical features. We established the frequency of positive α-synuclein SAA results in prodromal participants (RBD and hyposmia) and non-manifesting carriers of genetic variants associated with Parkinson's disease, and compared α-synuclein SAA to clinical measures and other biomarkers. We used odds ratio estimates with 95% CIs to measure the association between α-synuclein SAA status and categorical measures, and two-sample 95% CIs from the resampling method to assess differences in medians between α-synuclein SAA positive and negative participants for continuous measures. A linear regression model was used to control for potential confounders such as age and sex. This analysis included 1123 participants who were enrolled between July 7, 2010, and July 4, 2019. Of these, 545 had Parkinson's disease, 163 were healthy controls, 54 were participants with scans without evidence of dopaminergic deficit, 51 were prodromal participants, and 310 were non-manifesting carriers. Sensitivity for Parkinson's disease was 87·7% (95% CI 84·9-90·5), and specificity for healthy controls was 96·3% (93·4-99·2). The sensitivity of the α-synuclein SAA in sporadic Parkinson's disease with the typical olfactory deficit was 98·6% (96·4-99·4). The proportion of positive α-synuclein SAA was lower than this figure in subgroups including LRRK2 Parkinson's disease (67·5% [59·2-75·8]) and participants with sporadic Parkinson's disease without olfactory deficit (78·3% [69·8-86·7]). Participants with LRRK2 variant and normal olfaction had an even lower α-synuclein SAA positivity rate (34·7% [21·4-48·0]). Among prodromal and at-risk groups, 44 (86%) of 51 of participants with RBD or hyposmia had positive α-synuclein SAA (16 of 18 with hyposmia, and 28 of 33 with RBD). 25 (8%) of 310 non-manifesting carriers (14 of 159 [9%] LRRK2 and 11 of 151 [7%] GBA) were positive. This study represents the largest analysis so far of the α-synuclein SAA for the biochemical diagnosis of Parkinson's disease. Our results show that the assay classifies people with Parkinson's disease with high sensitivity and specificity, provides information about molecular heterogeneity, and detects prodromal individuals before diagnosis. These findings suggest a crucial role for the α-synuclein SAA in therapeutic development, both to identify pathologically defined subgroups of people with Parkinson's disease and to establish biomarker-defined at-risk cohorts. PPMI is funded by the Michael J Fox Foundation for Parkinson's Research and funding partners, including: Abbvie, AcureX, Aligning Science Across Parkinson's, Amathus Therapeutics, Avid Radiopharmaceuticals, Bial Biotech, Biohaven, Biogen, BioLegend, Bristol-Myers Squibb, Calico Labs, Celgene, Cerevel, Coave, DaCapo Brainscience, 4D Pharma, Denali, Edmond J Safra Foundation, Eli Lilly, GE Healthcare, Genentech, GlaxoSmithKline, Golub Capital, Insitro, Janssen Neuroscience, Lundbeck, Merck, Meso Scale Discovery, Neurocrine Biosciences, Prevail Therapeutics, Roche, Sanofi Genzyme, Servier, Takeda, Teva, UCB, VanquaBio, Verily, Voyager Therapeutics, and Yumanity.

Nigral volumetric and microstructural measures in individuals with scans without evidence of dopaminergic deficit.

Striatal dopamine transporter (DAT) imaging using 123I-ioflupane single photon positron emitted computed tomography (SPECT) (DaTScan, GE) identifies 5-20% of newly diagnosed Parkinson's disease (PD) subjects enrolling in clinical studies to have scans without evidence of dopaminergic deficit (SWEDD). These individuals meet diagnostic criteria for PD, but do not clinically progress as expected, and they are not believed to have neurodegenerative Parkinsonism. Inclusion of SWEDD participants in PD biomarker studies or therapeutic trials may therefore cause them to fail. DaTScan can identify SWEDD individuals, but it is expensive and not widely available; an alternative imaging approach is needed. Here, we evaluate the use of neuromelanin-sensitive, iron-sensitive, and diffusion contrasts in substantia nigra pars compacta (SNpc) to differentiate SWEDD from PD individuals. Neuromelanin-sensitive, iron-sensitive, and diffusion imaging data for SWEDD, PD, and control subjects were downloaded from the Parkinson's progression markers initiative (PPMI) database. SNpc volume, SNpc iron (R 2), and SNpc free water (FW) were measured for each participant. Significantly smaller SNpc volume was seen in PD as compared to SWEDD (P < 10-3) and control (P < 10-3) subjects. SNpc FW was elevated in the PD group relative to controls (P = 0.017). No group difference was observed in SNpc R 2. In conclusion, nigral volume and FW in the SWEDD group were similar to that of controls, while a reduction in nigral volume and increased FW were observed in the PD group relative to SWEDD and control participants. These results suggest that these MRI measures should be explored as a cost-effective alternative to DaTScan for evaluation of the nigrostriatal system.

Advancement of biomolecular engineering in Parkinson disease

Parkinson's Condition (PD) is the second most common degenerative neurological disease, affecting 10 million people globally. Nigrostriatal degeneration is linked to decreased motor and non-motor functioning in this chronic illness. Resting tremor, stiffness, akinesia (or bradykinesia), and postural instability are the four cardinal symptoms of Parkinson's disease. Because the symptoms of Parkinson's disease are similar to those of other age-related disorders like SWEDD (scans without evidence of dopaminergic deficit), essential tremors, and Parkinson's disease, early diagnosis is difficult. A synucleinopathy is Parkinson's disease (PD) with Lewy Bodies (DLB).Although both genetic and environmental variables are assumed to play a role in Parkinson's disease (PD), there was no direct evidence to support either as a causal component until recently. Six distinct genes have been discovered as producing familial PD in the last eight years. They back up the idea that similar pathogenetic pathways exist across the spectrum of Parkinson's disease etiologies. Mutations in α-synuclein, parkin, UCHL1, DJ1, PINK1, and LRRK2 cause.Parkinson's disease, which is inherited in a Mendelian form. Overexpression of α- synuclein and parkin causes mitochondrial issues, but DJ1 and PINK1 are mitochondrial proteins. These same proteins regulate proteasomal function and play a role in the oxidative stress response.Doped carbon nanotubes, especially phosphorus-doped carbon nanotubes, can efficiently prevent the formation of α- synuclein amyloid, suggesting that they could be utilized to treat Parkinson's disease. More in vitro and clinical research is, however, necessary. As previously stated, αsynuclein could be a therapeutic target for Parkinson's disease and other synucleinopathies. The most promising option would be small chemicals that may modify the structure of protofibrillar forms of α-synuclein and render them nonpathogenic. Given the pathogenic consequences of αsynuclein's feed-forward amplification loops, a range of therapeutic options will almost certainly be required.

Studying cognitive function in patients with a long-standing diagnosis of SWEDD

IntroductionThe cognitive profile of patients with longstanding clinical Parkinsonism possessing scans without evidence of dopaminergic deficit (SWEDD) remains unclear from previous studies. MethodsWe studied 47 patients recruited in the Parkinson's Progression Markers Initiative with SWEDD as baseline diagnosis. They were subdivided by final clinical diagnoses after a 2-year follow-up period into 25 patients with either clinical evidence of Parkinson's Disease (PD) or unclassified parkinsonism and normal SPECT imaging (“true SWEDDs”), 6 patients with a psychogenic illness exhibiting Parkinsonism, 6 patients who had phenoconverted to PD based on reduced striatal dopaminergic activity on imaging, and 10 patients with another tremulous condition. Cognitive symptoms were compared between these subgroups, as well as with 62 PD patients and 195 healthy controls (HCs), at baseline and follow-ups. ResultsA significant difference in working memory was found between true SWEDDs and HCs (P = 0.009), but not true SWEDDs and PD patients (P = 0.432), nor PD patients and HCs (P = 0.154). The prevalence of attentional impairment was also significantly different between the three groups (P < 0.001). SWEDD subgroups possessed similar cognitive symptoms irrespective of their final clinical diagnosis. Psychogenic, phenoconverted and tremulous SWEDDs also possessed stable cognitive symptoms over the 2-year period whilst true SWEDDs, PD patients and HCs experienced significant changes in working memory. ConclusionsOur results, particularly relating to working memory and attention, add to the knowledge of other true SWEDD non-motor symptoms to facilitate earlier diagnosis and improved management strategies for these patients.

Convolutional Neural Network-Based Parkinson Disease Classification Using SPECT Imaging Data

In this paper, we used the single-photon emission computerized tomography (SPECT) imaging technique to visualize the deficiency of dopamine-generated patterns inside the brain. These patterns are used to establish a patient’s disease progression, which helps distinguish the patients into different categories. Furthermore, we used a convolutional neural network (CNN) model to classify the patients based on the dopamine level inside the brain. The dataset used throughout this paper is the Parkinson’s progressive markers initiative (PPMI) dataset. The collected dataset was pre-processed and data amplification was performed to balance the imbalanced dataset. A CNN-based neural network was defined to classify input SPECT images into four categories. The motivation behind the proposed model is to reduce the number of resources consumed while maintaining the performance of the classification model. This will help the healthcare ecosystem run the classification model on mobile devices. The proposed model contains 14 layers with input layers, convolutional layers, max-pool layers, flatten layers, and dense layers with different dimensions. The dense layer classifies the patients into four different categories, including PSD, healthy control, scans without evidence of dopaminergic deficit (SWEDD), and GenReg PSD from the entire SPECT imaging dataset, which is used to establish the disease progression of different patients using SPECT images. The proposed model is trained with a large dataset with 58,692 images for training and 11,738 images for validation, and 7826 for testing. The proposed model outperforms the classification models from the surveyed papers. The proposed model’s accuracy is 0.889, recall is 0.9012, the precision is 0.9104, and the F1-score is 0.9057.

Structural connectivity alterations in the motor network of patients with scans without evidence of dopaminergic deficit (SWEDD).

Approximatively, 10% of patients initially diagnosed with Parkinson's disease (PD) show preserved presynaptic dopaminergic function in the nigrostriatal pathway on DAT-SPECT imaging. This syndrome is not compatible with PD diagnosis, and is known as scans without evidence of dopaminergic deficit (SWEDD). To investigate structural connectivity of cerebello-subcortico-cortical networks, including the nigrostriatal pathway, in an international cohort of subjects with SWEDD compared to normal controls using probabilistic tractography. Twenty-eight patients with SWEDD and 21 age- and sex-matched healthy controls (HC) were selected from the Parkinson's Progression Markers Initiative (PPMI) database. All participants underwent whole-brain 3D T1-weighted and diffusion-weighted MRI, as well as DAT-SPECT. Probabilistic tractography was performed in network-mode between regions of the cerebello-thalamo-basal ganglia-cortical circuits, to extract the connectivity strength between pairs of nodes of the circuit, as well as volumetric and diffusion measures of each reconstructed tract. Analysis of covariance with age and sex as covariates of non-interest was performed to assess group differences. Statistical significance was set at p < 0.05 after false-discovery-rate correction for multiple comparisons. Compared to HC, patients with SWEDD showed increased fractional anisotropy in bilateral thalamo-putamen-precentral, left nigro-putaminal and left thalamo-pallidal pathways. Furthermore, we found decreased mean streamline length in bilateral thalamo-nigro-cerebellar pathways and in the left nigro-caudate connection. Clinical heterogeneity of SWEDD syndrome may account for involvement of different brain circuits, such as the cerebello-thalamo-cortical and the nigrostriatal pathways, characteristic of different tremulous disorders.

245 Cognitive function in patients with a long-standing diagnosis of SWEDD

IntroductionPatients with clinical features of Parkinson’s Disease (PD), but scans without evidence of dopaminergic deficit are termed SWEDDs. Only a portion of these patients retain their SWEDDs diagnosis later in life and are here regarded as ‘true SWEDDs’. Cognitive symptoms of ‘true SWEDDs’ remain unclear yet important to optimise their management. We used data from the Parkinson’s Progression Markers Initiative to investigate these further.MethodologyBaseline cognitive data of 25 SWEDDs, who retained diagnoses after 2 years of follow up (confirmed by normal 123I-FP-CIT SPECT scans), were compared with that of 62 de novo PD and 195 healthy control (HC) subjects. Data was analysed using SPSS Statistics.ResultsNo significant difference was found when comparing ‘true SWEDDs’ to de novo PD patients and HCs in tests of global cognition, visuospatial function, executive function and attention. However, Hopkins Verbal Learning Test-Revised (HVLT-R) showed a significant difference between the three groups (P=0.004), maintained when specifically analysing ‘true SWEDDs’ versus HCs (P=0.009).ConclusionOur data suggest a significant difference in memory function between ‘true SWEDDs’ and HCs, as demonstrated by the HVLT-R test. This suggests memory-stimulating therapies are important for managing ‘true SWEDDs’, however further work is required to validate these findings.aaronjesuthasan@gmail.com

Explainable machine learning with pairwise interactions for the classification of Parkinson's disease and SWEDD from clinical and imaging features.

Scans without evidence of dopaminergic deficit (SWEDD) refers to patients who mimics motor and non-motor symptoms of Parkinson’s disease (PD) but showing integrity of dopaminergic system. For this reason, the differential diagnosis between SWEDD and PD patients is often not possible in absence of dopamine imaging. Machine Learning (ML) showed optimal performance in automatically distinguishing these two diseases from clinical and imaging data. However, the most common applied ML algorithms provide high accuracy at expense of findings intelligibility. In this work, a novel ML glass-box model, the Explainable Boosting Machine (EBM), based on Generalized Additive Models plus interactions (GA2Ms), was employed to obtain interpretability in classifying PD and SWEDD while still providing optimal performance. Dataset (168 healthy controls, HC; 396 PD; 58 SWEDD) was obtained from PPMI database and consisted of 178 among clinical and imaging features. Six binary EBM classifiers were trained on feature space with (SBR) and without (noSBR) dopaminergic striatal specific binding ratio: HC-PDSBR, HC-SWEDDSBR, PD-SWEDDSBR and HC-PDnoSBR, HC-SWEDDnoSBR, PD-SWEDDnoSBR. Excellent AUC-ROC (1) was reached in classifying HC from PD and SWEDD, both with and without SBR, and by PD-SWEDDSBR (0.986), while PD-SWEDDnoSBR showed lower AUC-ROC (0.882). Apart from optimal accuracies, EBM algorithm was able to provide global and local explanations, revealing that the presence of pairwise interactions between UPSIT Booklet #1 and Epworth Sleepiness Scale item 3 (ESS3), MDS-UPDRS-III pronation-supination movements right hand (NP3PRSPR) and MDS-UPDRS-III rigidity left upper limb (NP3RIGLU) could provide good performance in predicting PD and SWEDD also without imaging features.

Machine Learning for Early Parkinson's Disease Identification within SWEDD Group Using Clinical and DaTSCAN SPECT Imaging Features.

Early Parkinson’s Disease (PD) diagnosis is a critical challenge in the treatment process. Meeting this challenge allows appropriate planning for patients. However, Scan Without Evidence of Dopaminergic Deficit (SWEDD) is a heterogeneous group of PD patients and Healthy Controls (HC) in clinical and imaging features. The application of diagnostic tools based on Machine Learning (ML) comes into play here as they are capable of distinguishing between HC subjects and PD patients within an SWEDD group. In the present study, three ML algorithms were used to separate PD patients from HC within an SWEDD group. Data of 548 subjects were firstly analyzed by Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques. Using the best reduction technique result, we built the following clustering models: Density-Based Spatial (DBSCAN), K-means and Hierarchical Clustering. According to our findings, LDA performs better than PCA; therefore, LDA was used as input for the clustering models. The different models’ performances were assessed by comparing the clustering algorithms outcomes with the ground truth after a follow-up. Hierarchical Clustering surpassed DBSCAN and K-means algorithms by 64%, 78.13% and 38.89% in terms of accuracy, sensitivity and specificity. The proposed method demonstrated the suitability of ML models to distinguish PD patients from HC subjects within an SWEDD group.

Anxiety predicts impulsive-compulsive behaviours in Parkinson's disease: Clinical relevance and theoretical implications

Patients with Parkinson's disease (PD) often present symptoms of anxiety, depression and apathy. These negative affect manifestations have been recently associated with the presence of impulsive compulsive behaviours (ICBs). However, their relation with the use of dopamine replacement therapy (DRT), a renewed risk factor for ICBs, is still not fully understood. Elucidating the role of these different ICBs predictors in PD could inform both prevention/intervention recommendations as well as theoretical models. In the present study, we have analysed data collected in 417 PD patients, 50 patients with Parkinsonian symptoms but with scan without evidence of dopaminergic deficit (SWEDD), and 185 healthy controls (HC). We examined each patient's clinical profile over a two-year time window, investigating the role of both negative affect and DRT on ICBs. Results confirmed the presence of higher levels of anxiety in both the clinical groups, and of higher level of ICBs in SWEDD patients, respect to both PD and HC. Mixed model analyses revealed a statistically significant association between anxiety and ICBs in the SWEDD patients who did not take any DRT. Findings suggest the independence between anxiety and DRT in ICBs development, and provide new evidence for the motivational opponency theoretical framework.

Evaluating dopamine transporter imaging as an enrichment biomarker in a phase 2 Parkinson\u2019s disease trial

BackgroundDopamine transporter single-photon emission computed tomography (DaT-SPECT) can quantify the functional integrity of the dopaminergic nerve terminals and has been suggested as an imaging modality to verify the clinical diagnosis of Parkinson’s disease (PD). Depending on the stage of progression, approximately 5–15% of participants clinically diagnosed with idiopathic PD have been observed in previous studies to have normal DaT-SPECT patterns. However, the utility of DaT-SPECT in enhancing early PD participant selection in a global, multicenter clinical trial of a potentially disease-modifying therapy is not well understood.MethodsThe SPARK clinical trial was a phase 2 trial of cinpanemab, a monoclonal antibody against alpha-synuclein, in participants with early PD. DaT-SPECT was performed at screening to select participants with DaT-SPECT patterns consistent with degenerative parkinsonism. Acquisition was harmonised across 82 sites. Images were reconstructed and qualitatively read at a central laboratory by blinded neuroradiologists for inclusion prior to automated quantitative analysis.ResultsIn total, 482 unique participants were screened between January 2018 and May 2019; 3.8% (15/398) of imaged participants were excluded owing to negative DaT-SPECT findings (i.e., scans without evidence of dopaminergic deficit [SWEDD]).ConclusionA smaller proportion of SPARK participants were excluded owing to SWEDD status upon DaT-SPECT screening than has been reported in prior studies. Further research is needed to understand the reasons for the low SWEDD rate in this study and whether these results are generalisable to future studies. If supported, the radiation risks, imaging costs, and operational burden of DaT-SPECT for enrichment may be mitigated by clinical assessment and other study design aspects.Trial registrationClinicalTrials.gov identifier: NCT03318523.Date submitted: October 19, 2017.First Posted: October 24, 2017.

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.

Improved Classification Accuracy for Diagnosing the Early Stage of Parkinson’s Disease Using Alpha Stable Distribution

Early diagnosis of the neurodegenerative disorder Parkinson’s disease (PD) and Scan without Evidence of Dopaminergic Deficit (SWEDD) is essential for effective patient management in neurodisorders, as both have the same clinical characteristics. The present work intends to propose an efficient method for analyzing volume rendering Single-Photon Emission Computed Tomography (SPECT) image slices, using Alpha stable distribution-based intensity normalization techniques for discriminating early PD from Healthy Control (HC) and SWEDD. The Volume rendering image (VRI) slices of early PD, HC and SWEDD are chosen from the database called Parkinson’s Progression Markers Initiative (PPMI). The alpha stable distribution technique is adapted to normalize the intensity values outside the striatum of the VRI in order to keep up the uniform intensity values throughout the database images. The shape features and image surface-related features are taken out from the VRI slices of the three different groups. The most optimized feature set is computed based on its consistency by Genetic Algorithm (GA). The computed optimized features of VRI slices show a remarkable performance in detecting the early stage of PD. The Extreme learning machine (ELM) classifier with Radial Basis Function (RBF) kernel shows a better performance accuracy of 99.12% than Support vector machine (SVM). Performance measures of the classifiers have ensured the validity of the experiments. Thus, the proposed method is advantageous to the neurologist in the early diagnosis of PD.

Association of autonomic symptoms with cerebrospinal fluid biomarkers in Parkinson disease and scans without evidence of dopaminergic deficit.

Dysautonomia is common in patients with Parkinson disease (PD) since disease early phase. Scales for Outcomes in Parkinson's disease – Autonomic (SCOPA-AUT) is a well-designed scale assessing the autonomic dysfunctions of PD patients. Our objectives were to examine the autonomic dysfunction in PD and scan without evidence of dopaminergic deficit (SWEDD) patients and to assess the correlation of autonomic dysfunctions with cerebrospinal fluid (CSF) biomarkers.An analysis of the Parkinson's Progression Markers Initiative (PPMI) data including 414 PD patients, 60 SWEDD patients, and 170 healthy controls (HCs) with baseline CSF biomarker measurements and SCOPA-AUT assessments was presented. Autonomic symptoms including gastrointestinal, urinary, cardiovascular, pupillomotor, thermoregulatory and sexual dysfunctions were assessed by SCOPA-AUT scales. Spearman correlation test was used to examine the correlations between CSF measurements and each section of SCOPA-AUT scales in HCs and subjects with PD or SWEDD.More severe autonomic dysfunctions were observed in patients with SWEDD than those with PD (P < .001). Specifically, patients with PD have lower scores on the urinary scale [4 (0–17) vs 5 (1–18)], pupillomotor scale [0 (0–3) vs 0 (0–3)], thermoregulatory scale [0 (0–4) vs 1.5 (0–10)] and sexual scale [1 (0–6) vs 2 (0–6)] compared with SWEDD patients. Thermoregulatory dysfunction scores were found correlated with CSF α-syn levels in SWEDD group, and gastrointestinal dysfunction scores were correlated with CSF Abeta1–42 in PD group. Additionally, urinary dysfunction scores were correlated with CSF total tau and tau phosphorylated at threonine 181(p-tau181) levels in both HCs and PD patients.