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Transcranial sonography images of the substantia nigra at the midbrain level. Zoomed images of the butterfly-shaped midbrain are shown in the bottom left corner. (a) Normal substantia nigra echogenicity. (b) Substantia nigra hyperechogenicity (white arrow).
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Background
Numerous studies have demonstrated that patients with Parkinson's disease (PD) have a higher prevalence of substantia nigra (SN) hyperechogenicity compared with controls. Our aim was to explore the neuroimaging characteristics of transcranial sonography (TCS) of patients with PD and those with PD with dementia (PDD). The correlation betw...
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Context 1
... hyperechoic sizes of ≥0.20 cm 2 were classified as SN hyperechogenicity (SN+) and the maximum SN+ size was defined as the greater value across bilateral SN regions. [10,15,16] SN echogenicity is shown in Figure 1. The width of the TV [ Figure 2] was calculated by measuring the distance between the inner boundaries of both hyperechoic lines of ependyma at the thalamus level. ...
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Objective:
In multiple sclerosis (MS), deep grey matter (DGM) atrophy has been recognised as a crucial component of the disease that presents early and it has been associated with disability. Although the precise mechanism underlying grey matter atrophy is unknown, several hypotheses have been postulated. Our previous research pointed to correlati...
Citations
... Four studies focused on the link between midbrain ultrasound changes and cognitive impairment or dementia in PD patients. They included a total of 375 PD subjects with and without dementia, 54 patients with other Parkinsonism, 14 patients with dementia with Lewy bodies (DLB), and 40 healthy controls [13,[23][24][25]. Frontal horn dilatation and third ventricle dilatation were associated with dementia and the width of both ventricles corre lated with age but not with PD duration. ...
... Frontal horn dilatation and third ventricle dilatation were associated with dementia and the width of both ventricles corre lated with age but not with PD duration. No differences were identified between PD patients without dementia and controls [13,[23][24][25]. Walter et al. [13] found that PD subjects with dementia had larger third ventricle width (8.7 ± 2.1 vs. 6.9 ± 2.5 mm; p = 0.002) and frontal horn width (17.3 ± 3.1 vs. 14.9 ± 3.1 mm; p = 0.003) compared to PD patients without dementia. ...
... In addition, based on the ROC curve, Dong et al. [25] suggested that a third ventricle width cut-off of 6.8 mm had a 69.6% sensitivity and a 61.5% specificity for discriminating between PD patients with and without dementia. ...
Non-motor symptoms (NMS) in Parkinson’s disease (PD), including neuropsychiatric or dysautonomic complaints, fatigue, or pain, are frequent and have a high impact on the patient’s quality of life. They are often poorly recognized and inadequately treated. In the recent years, the growing awareness of NMS has favored the development of techniques that complement the clinician’s diagnosis. This review provides an overview of the most important ultrasonographic findings related to the presence of various NMS. Literature research was conducted in PubMed, Scopus, and Web of Science from inception until January 2021, retrieving 23 prospective observational studies evaluating transcranial and cervical ultrasound in depression, dementia, dysautonomic symptoms, psychosis, and restless leg syndrome. Overall, the eligible articles showed good or fair quality according to the QUADAS-2 assessment. Brainstem raphe hypoechogenicity was related to the presence of depression in PD and also in depressed patients without PD, as well as to overactive bladder. Substantia nigra hyperechogenicity was frequent in patients with visual hallucinations, and larger intracranial ventricles correlated with dementia. Evaluation of the vagus nerve showed contradictory findings. The results of this systematic review demonstrated that transcranial ultrasound can be a useful complementary tool in the evaluation of NMS in PD.
... However, TCS examination is not feasible in all patients because approximately 4-15% of European populations [32,33] and 15-60% of Asian populations [34] have an insufficient temporal window; thus, MRI of the SN can be used as an adjunct to TCS when necessary. e principal pathological changes occur in the SN in patients with PD, but TCS can also detect enlargement of the third ventricle in patients of Parkinson's disease dementia (PDD) [35]. In contrast, this phenomenon is seldom found in patients with PD without dementia, indicating that TCS can be used as a potential method for the diagnosis of PDD. ...
This meta-analysis aimed to evaluate the accuracy of hyperechogenicity of the substantia nigra (SN) for the differential diagnosis of Parkinson’s disease (PD) and other movement disorders. We systematically searched the PubMed, EMBASE, Cochrane Library, and China National Knowledge Infrastructure databases for relevant studies published between January 2015 and May 2020. Eligible articles comparing the echogenicity of the SN between patients with PD and those with other movement disorders were screened, and two independent reviewers extracted data according to the inclusion and exclusion criteria. Statistical analyses were conducted using STATA (version 15.0) (Stata Corporation, College Station, TX, USA), Review Manager 5.3 (Cochrane Collaboration), and Meta-DiSc1.4 to assess the pooled diagnostic value of transcranial sonography (TCS) for PD. Nine studies with a total of 1046 participants, including 669 patients with PD, were included in the final meta-analysis. Our meta-analysis demonstrated that hyperechogenicity of the SN had a pooled sensitivity and specificity of 0.85 (0.82, 0.87) and 0.71 (0.66, 0.75), respectively, for distinguishing idiopathic Parkinson’s disease from other movement disorders. Furthermore, the area under the curve of the summary receiver operating characteristic was 0.94. Transcranial sonography of the SN is a valuable tool for the differential diagnosis of PD and other movement disorders.
... In our department, hyperechogenicity was defined as SN + ≥ 0.20 cm 2 , while normoechogenicity was defined as SN + < 0.20 cm 2 . [20] Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of PD on the basis of SN + measurements were calculated. Subgroup analysis were undergone according to sex (male or female) and age (≥60 or <60). ...
... These findings are consistent with those from our former meta-analysis, which included 3123 patients with PD from 39 studies and indicated that TCS can be an appropriate method for differentiation of patients with PD from both HCs and patients with other parkinsonism symptoms. [21] The TCS through the preaurical bone window allows the depiction of characteristic abnormalities in the echogenicity of SN. [20] In this study, increased SN + was detected in up to 91% (reader 1) and 90% (reader 2) of patients with PD and could be found unilaterally or asymmetrically bilaterally. In addition, 9 (8.5%, reader 1) and 11 (10.4%, ...
Substantia nigra (SN) hyperechogenicity measured by transcranial sonography (TCS) is a promising biomarker for Parkinson disease (PD). The aim of this study was to explore the diagnostic accuracy of SN hyperechogenicity (SN) for differentiating PD from essential tremor (ET). A total of 119 patients with PD, 106 ET patients and 112 healthy controls that underwent TCS from November 2016 to February 2019 were included in this single-center retrospective case-control study. Two reviewers who were blinded to clinical information independently measured the SN by TCS imaging. The diagnostic sensitivity, specificity, and accuracy of TCS imaging were evaluated between the PD and healthy controls and between patients with PD and ET. Interrater agreement was assessed with the Cohen κ statistic. TCS imaging of the SN allowed to differentiate between patients with PD and ET with a sensitivity (91.6% and 90.8%) and specificity (91.5% and 89.6%) for readers 1 and 2, respectively. Interobserver agreement was excellent (к = 0.87). In addition, measurement of the SN allowed to differentiate between patients with PD and healthy subjects with a sensitivity (91.6% and 90.8%) and specificity (88.4% and 89.3%) for readers 1 and 2, respectively. Interobserver agreement was excellent (к = 0.91). Measurement of SN on TCS images could be a useful tool to distinguishing patients with PD from those with ET.
... We have evaluated the feasibility and diagnostic accuracy of TCS for diagnosing PD in the Chinese population. Although various studies have evaluated the efficacy of TCS in the diagnosis of PD, most of them were conducted in European populations (van de Loo et al. 2010;Bor-Seng-Shu et al. 2014), and there have been only a few studies in Asian populations (Dong et al. 2017;Oh et al. 2018). Notably, we found that visual analysis of TCS images had a sensitivity of 90.3% and 89.6% (251 and 249 of 278 participants) and a specificity of 89.3% and 88.3% (268 and 265 of 300 participants) in assessments by readers 1 and 2, respectively. ...
... In addition, according to ROC analysis, the optimal cutoff value for PD diagnosis is 0.20 and 0.21 cm 2 for readers 1 and 2, respectively. We finally chose 0.20 cm 2 as the cutoff value because it has higher accuracy, which is consistent with some previous trials in the Chinese population (Huang et al. 2007;Luo et al. 2012;Dong et al. 2017). Almost 12% of the HCs exhibited SN+ in this study, which is consistent with previous studies reporting that SN+ can be observed in 8%À14% of the general population Krogias et al. 2010). ...
... In addition, this study found that the SN area in PD patients did not correlate with age, sex, midbrain area, third ventricle area, tremor type or disease severity (Hoehn and Yahr stage or UPDRS III score). These data suggest that SN+ can be a stable marker for PD diagnosis, which is consistent with the findings of previous studies (van de Loo et al. 2010;Dong et al. 2017;Tao et al. 2019). ...
To determine the diagnostic performance of transcranial sonography (TCS) in assessing increased echogenic area of the substantia nigra (SN) in patients with Parkinson's disease (PD). Institutional review board approval was obtained for this retrospective study. A total of 278 PD patients (mean age: 64.7 ± 9.8 y, 100 women) and 300 healthy control patients (mean age: 63.6 ± 9.3 y, 97 women) were referred for TCS assessment of SN hyper-echogenicity (SN+) from June 2016 to December 2018. Two sonographers independently measured the sizes of the echogenic areas of the SN by TCS imaging in both PD patients and healthy controls. The diagnostic sensitivity, specificity and accuracy of TCS imaging were compared between PD patients and healthy controls. Inter-rater agreement was assessed with the Cohen's κ statistic. The sensitivity, specificity and accuracy of readers 1 and 2, respectively, for the identification of SN+ in TCS were 90.3% and 89.6% (251 and 249 of 278), 89.3% and 88.3% (268 and 265 of 300) and 89.8% and 88.9% (519 and 514 of 578). Inter-observer agreement was excellent (к = 0.84). The area under the receiver operating characteristic curve (AUC) for differentiation of PD patients from healthy controls was 0.92 for reader 1 and 0.91 for reader 2. Cutoff values of 0.20 and 0.21 cm2 were derived from the assessments performed by readers 1 and 2, respectively. We defined 0.20 cm2 as the optimal cutoff value because it had a higher AUC. TCS is a promising diagnostic technique and can be very helpful in differentiating PD patients from healthy individuals.
... Thirty-nine articles (Alonso-Canovas et al. 2014; Ambrosius et al. 2014;Bartova et al. 2014;Bor-Seng-Shu et al. 2014;Bouwmans et al. 2013;Busse et al. 2012;Chitsaz et al. 2013;Doepp et al. 2008;Dong et al. 2017;Fathinia et al. 2013;Gaenslen et al. 2008;Huang et al. 2007;Iranzo et al. 2014;Izawa et al. 2012;Kim et al. 2007;Kresojevic et al. 2013;Kwon et al. 2010;Lauckaite et al. 2012Lauckaite et al. , 2014Mahlknecht et al. 2013;Mehnert et al. 2010;Oh et al. 2018;Prati et al. 2017;Prestel et al. 2006;Ressner et al. 2007;Ryu et al. 2011;Schmidauer et al. 2005;Shin et al. 2013;Sierra et al. 2013;Skoloudik et al. 2014;Stockner et al. 2007;Toomsoo et al. 2016;Tunc et al. 2015;Vlaar et al. 2008;Walter et al. 2007a;Zhuang et al. 2015) that involved 49 comparisons and 6641 patients were enrolled in the metaanalysis. Characteristics of the trials are listed in Table 1. ...
... In terms of applicability concerns, all studies were applicable to clinical practice in terms of index test and reference standard. In the participant selection domain, 2 studies Dong et al. 2017) were considered of high concern because they included participants with greater severity of the target condition. In terms of risk of bias, the most common risk of bias was in the patient selection category, with the most common underlying reason related to the non-consecutive enrollment of patients and caseÀcontrol design. ...
... Walter et al. 2007a;Zhuang et al. 2015) were regarded as high quality, and the remaining 12 studies (Alonso-Ambrosius et al. 2014;Bor-Seng-Shu et al. 2014;Busse et al. 2012;Dong et al. 2017;Huang et al. 2007;Mehnert et al. 2010;Prati et al. 2017;Schmidauer et al. 2005;Skoloudik et al. 2014;Toomsoo et al. 2016; were regarded as low quality. Fifteen studiesBusse et al. 2012;Dong et al. 2017;Gaenslen et al. 2008;Iranzo et al. 2014;Lauckaite et al. 2012;Mahlknecht et al. 2013;Oh et al. 2018;Stockner et al. 2007;Toomsoo et al. 2016;Tunc et al. 2015;Vlaar et al. 2008;Walter et al. 2007a) were conducted among adults >65 y, and 24 studies (Ambrosius et al. 2014;Bartova et al. 2014;Bor-Seng-Shu et al. 2014;Chitsaz et al. 2013;Doepp et al. 2008;de C assia Leite Fernandes et al. 2011;Izawa et al. 2012;Kim et al. 2007;Kwon et al. 2010;Lauckaite et al. 2014;Mehnert et al. 2010;Prati et al. 2017;Prestel et al. 2006;Ressner et al. 2007;Ryu et al. 2011;Schmidauer et al. 2005;Shin et al. 2013;Sierra et al. 2013;Skoloudik et al. 2014;Zhuang et al. 2015) were conducted in adults <65 y. ...
A systematic review and meta-analysis were conducted to evaluate the diagnostic accuracy of substantia nigra hyper-echogenicity by transcranial sonography (TCS) for the diagnosis of Parkinson's disease (PD). PubMed, Embase and the Cochrane Library were electronically searched from inception to June 2018 for all relevant studies. The methodological quality of each study was evaluated by two independent reviewers, who used the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Articles reporting information sufficient to calculate the sensitivity and specificity of TCS to diagnose PD were included. Statistical analysis included data pooling, heterogeneity testing, sensitivity analyses and forest meta-regression. Thirty-nine studies (3123 participants with PD) were analyzed. The pooled sensitivity and specificity of TCS were 0.84 (95% confidence interval: 0.81–0.87) and 0.85 (0.80–0.88), respectively, for differentiating PD from normal controls or participants with other parkinsonian syndromes. In the secondary outcome, PD participants exhibited a significant increase in substantia nigra areas than either normal controls (0.14 [0.12–0.16], p < 0.0001) or participants with other parkinsonian syndromes (0.11 [0.08–0.13], p < 0.0001). This meta-analysis revealed the high diagnostic performance of TCS in differentiating patients with PD from both normal controls and participants with other parkinsonian syndromes.
... Parkinson's disease (PD) is featured with motor disorder and nonmotor manifestations Zhang et al. 2016) under the pathological change of Substantia Nigra (Dong et al., 2017) and non substantia nigra including medial prefrontal cortex . Its primary motor symptoms include tremor (oscillatory movement), bradykinesia (slowness of motion), rigidity (increment of muscle tone), and postural instability, which seriously affect patients' quality of life (Du and Chen, 2017). ...
Transcranial sonography has been used as a valid neuroimaging tool to diagnose Parkinson’s disease (PD). This study aimed to develop a modified transcranial sonography (TCS) technique based on a deep convolutional neural network (DCNN) model to predict Parkinson’s disease.
This retrospective diagnostic study was conducted using 1529 transcranial sonography images collected from 854 patients with PD and 775 normal controls admitted to the Second Affiliated Hospital of Soochow University (Suzhou, Jiangsu, China) between September 2019 and May 2022. The data set was divided into training cohorts (570 PD patients and 541 normal controls), and the validation set (184 PD patients and 234 normal controls). Using these datasets, we developed four different DCNN models (ResNet18, ResNet50, ResNet152, and DenseNet121). We then assessed their diagnostic performance, including the area under the receiver operating characteristic (AUROC) curve, specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), and F1 score and compared with traditional diagnostic criteria.
Among the 1529 TCS images, 570 PD patients and 541 normal controls from 4 of 6 sonographers of the TCS team were selected as the training cohort, and 184 PD patients and 234 normal controls from the other 2 sonographers were chosen as the validation cohort. There were no sex and age differences between PD patients and normal control subjects in the training and validation cohorts (P values > 0.05). All DCNN models achieved good performance in distinguishing PD patients from normal control subjects on the validation datasets, with diagnostic AUROCs and accuracy of 0.949 (95% CI 0.925, 0.965) and 86.60 for the RestNet18 model, 0.949 (95% CI 0.929, 0.971) and 87.56 for ResNet50, 0.945 (95% CI 0.931, 0.969) and 88.04 for ResNet152, 0.953 (95% CI 0.935, 0.971) and 87.80 for DenseNet121, respectively. On the other hand, the diagnostic accuracy of the traditional diagnostic method was 82.30. The accuracy of all DCNN models was higher than that of traditional diagnostic method. Moreover, the 5k-fold cross-validation results in train datasets showed that these DCNN models are robust.
The developed transcranial sonography-based DCNN models performed better than traditional diagnostic criteria, thus improving the sonographer’s accuracy in diagnosing PD.
Background
Persons with Parkinson’s disease (PD) differentially progress to cognitive impairment and dementia. With a 3-year longitudinal sample of initially non-demented PD patients measured on multiple dementia risk factors, we demonstrate that machine learning classifier algorithms can be combined with explainable artificial intelligence methods to identify and interpret leading predictors that discriminate those who later converted to dementia from those who did not.
Method
Participants were 48 well-characterized PD patients ( M baseline age = 71.6; SD = 4.8; 44% female). We tested 38 multi-modal predictors from 10 domains (e.g., motor, cognitive) in a computationally competitive context to identify those that best discriminated two unobserved baseline groups, PD No Dementia (PDND), and PD Incipient Dementia (PDID). We used Random Forest (RF) classifier models for the discrimination goal and Tree SHapley Additive exPlanation (Tree SHAP) values for deep interpretation.
Results
An excellent RF model discriminated baseline PDID from PDND ( AUC = 0.84; normalized Matthews Correlation Coefficient = 0.76). Tree SHAP showed that ten leading predictors of PDID accounted for 62.5% of the model, as well as their relative importance, direction, and magnitude (risk threshold). These predictors represented the motor (e.g., poorer gait), cognitive (e.g., slower Trail A), molecular (up-regulated metabolite panel), demographic (age), imaging (ventricular volume), and lifestyle (activities of daily living) domains.
Conclusion
Our data-driven protocol integrated RF classifier models and Tree SHAP applications to selectively identify and interpret early dementia risk factors in a well-characterized sample of initially non-demented persons with PD. Results indicate that leading dementia predictors derive from multiple complementary risk domains.
Objectives
This study aimed to explore the association of homocysteine (Hcy) with third ventricle (V3) dilatation and mesencephalic area (MA) atrophy as determined by transcranial sonography (TCS) in Parkinson’s disease (PD) with cognitive impairment.
Methods
The final statistical analysis included 101 PD patients and 20 age- and sex-matched controls. Using the Movement Disorder Society (MDS) level II criteria for PD with cognitive impairment, we categorized the PD patients into PD with normal cognition group (PD) and PD with cognitive impairment group (PDC). All subjects underwent TCS and laboratory analysis.
Results
The V3 width (r = 0.349, P = 0.005) and the MA (r = −0.484, P < 0.001) were significantly correlated with the Hcy concentration in the PDC patients. Binary logistic regression analysis revealed that age (OR [95% CI] = 1.114 [0.991–1.251], P = 0.002), and Hcy level (OR [95% CI] = 0.931 [0.752–1.153], P = 0.411) were independent risk factors for V3 dilatation. Hcy level (OR [95% CI] = 0.557 [0.323–0.967], P = 0.035) were independent risk factors for MA atrophy. After adjustment for confounding factors, the odds ratio of V3 dilatation was 3.50 (95% CI 1.054–11.399, P = 0.031) and the odds ratio of MA atrophy was 4.67 (95% CI 1.395–15.602, P = 0.012) in the patients with higher Hcy level compared with the lower level.
Conclusions
The results revealed a close association between the V3 width, MA and Hcy concentration in PD patients with cognitive impairment. We hypothesized that increased Hcy concentration played a significant role in the development of brain atrophy in PD with cognitive impairment.
Background
Rigidity is one of the major manifestations of Parkinson’s disease (PD), but no quantitative and objective imaging method has been developed to measure rigidity. Ultrasound shear wave elastography (SWE) can reflect the stiffness of tissue by providing a quantitative index. Thus, we conducted this study to evaluate the potential clinical value of SWE in assessing rigidity in PD.MethodsA total of 63 subjects (44 patients with rigidity-dominant PD and 19 right-dominant-hand normal controls with matched age) were enrolled, and each underwent ultrasound SWE testing. The tests were conducted on the brachioradialis (BR) and biceps brachii (BB) on the more affected side in patients with PD and on the right side in normal controls. Differences in quantitative shear wave velocity (SWV) between patients with PD and normal controls were determined. The relationship of muscle SWV with joint rigidity, UPDRSIII, disease duration, sex, and age in patients with PD was analyzed. The intraclass correlation coefficient (ICC) was used to evaluate the reliability of SWE in assessing muscle stiffness in patients with PD.ResultsThe mean SWVs of the BB and BR were higher in the PD group (3.65±0.46 and 4.62±0.89 m/s, respectively) than in normal controls (2.79±0.37 and 3.26±0.40 m/s, respectively). Stiffness in BR and BB was correlated with the upper-limb joint rigidity, UPDRSIII, and disease duration but not with sex or age in the PD group. The intraobserver correlation coefficients (ICCs) for interobserver and intraobserver variations in measuring SWV were 0.85 (95% confidence interval 0.56–0.95) and 0.85 (95% confidence interval 0.58–0.95), respectively, for BR and 0.90 (95% confidence interval 0.73–0.97) and 0.86 (95% confidence interval 0.61–0.95), respectively, for BB.ConclusionsSWV is associated with joint rigidity and disease duration, indicating that SWE can be potentially used as an objective and quantitative tool for evaluating rigidity.
