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Quantitative Transcranial Sonography Evaluation of Substantia Nigra Hyperechogenicity Is Useful for Predicting Levodopa-Induced Dyskinesia in Parkinson Disease
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Neurology, Suqian First People's Hospital, Suqian, Jiangsu, China
Address correspondence to: Chun-Feng Liu, Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, 1055, Sanxiang Road, Suzhou, Jiangsu 215004, China.
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaJiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, Jiangsu, ChinaDepartment of Neurology, Suqian First People's Hospital, Suqian, Jiangsu, ChinaDepartment of Neurology, Second Affiliated Hospital of Xinjiang Medical University, Urumqi, China
Levodopa-induced dyskinesia (LID) is a common motor complication in Parkinson disease (PD). Abnormal substantia nigra hyperechogenicity (SN+), detected by transcranial sonography (TCS), plays an important role in the differential diagnosis of PD. The purpose of this study was to investigate the predictive performance of quantitative SN+ evaluations for LID. Five hundred sixty-two individuals were included in our analysis, and 198 individuals were followed up. These individuals were divided into two groups at baseline: the PD with LID (PD+LID) group and the PD without LID (PD-LID) group. The association between total hyperechogenic area of the SN on both sides (SNT) and LID was analyzed by binary logistic analysis. A binary logistic regression model including SNT was applied to establish a model for discriminating LID. At baseline, 105 (18.7%) individuals were diagnosed with LID. The PD+LID group had a longer disease duration, shorter education duration, higher levodopa equivalent doses, greater disease severity and larger SNT. A model combining clinical features and SNT was further established with better efficiency (area under the receiver operating characteristic curve = 0.839). One hundred ninety-eight individuals were followed up; individuals with a larger SNT and a higher predicted probability were more likely to develop LID in our follow-up. Our study determined that quantitative TCS evaluation of SN echogenicity is useful in predicting LID in PD.
Parkinson disease (PD) is one of the most common neurodegenerative movement disorders, and is characterized by bradykinesia, resting tremor, rigidity and postural instability (
). The pathology of PD is widely considered to be the lack of levodopa, which can be caused by the degeneration of dopaminergic neurons originating in the substantia nigra pars compacta (
With long-term use of levodopa, some individuals with PD may develop levodopa-induced dyskinesia (LID), which is accompanied by various abnormal movements, including chorea, akathisia and dystonia (
), which may greatly affect the quality of life of individuals with PD and their families. Because of this additional problem, LID is gaining increasing attention among patients and clinicians. To date, the detailed mechanism underlying LID remains unclear; however, sex, body weight, age, age at onset, duration of disease and treatment have been shown to be associated with LID (
Transcranial sonography (TCS) is a non-invasive neuroimaging technique, and is regarded as a useful method (by detecting substantia nigra [SN] echogenicity) in providing evidence for PD diagnosis (
). In addition, abnormal SN hyperechogenicity (SN+) and a larger hyperechogenic area of the SN were indicated to be associated with the subtype of PD and disease severity (
Clinical features and dysfunctions of iron metabolism in Parkinson disease patients with hyper echogenicity in substantia nigra: A cross-sectional study.
), which revealed an important clinical application of TCS in PD. To date, studies focusing on the potential associations between SN+ and motor complications in PD are lacking. On the basis of the aforementioned evidence, we assumed that LID is associated with SN+. In this study, we attempted to determine the potential associations between SN+ and LID and to establish a prediction model for LID.
Methods
Individuals and study design
We recruited 601 individuals with PD from the Department of Neurology of the Second Affiliated Hospital of Soochow University (Suzhou, China) from April 2015 to 2021. All participants fulfilled either the 2015 Movement Disorder Society clinical diagnostic criteria (
) for PD. Exclusion criteria included (i) atypical and secondary parkinsonism (i.e., multiple system atrophy, progressive supranuclear palsy, brain injury, etc.); (ii) insufficient temporal bone window; and (iii) lack of full clinical assessments. We finally included 562 individuals, and 198 individuals without LID at baseline were successfully followed up every 3–6 mo (Fig. 1). The follow-up duration was determined from the baseline to the first occurrence of LID or, in the non-LID cases, from baseline to the last visit (the average follow-up duration was 37 mo). The investigation protocol was approved by the ethics committee of the Second Affiliated Hospital of Soochow University. Detailed clinical data including demographics were collected after written consent was obtained from all participants or their legally authorized representatives. All techniques were performed in accordance with the relevant guidelines and regulations.
) within 1 wk after the baseline clinical assessment. The brain was insonated through the right and left temporal bone windows in the axial plane by a sonographer using a 2.5-MHz sonographic device (Sequoia 512, Siemens Medical Solutions USA, Inc. 4V1C transducer) with a penetration depth of 14–16 cm and a dynamic range of 45–55 dB (
) (Fig. 2). The area of SN echogenicity was manually encircled with the cursor, and the planimetric area of SN and the mesencephalon was calculated automatically. TCS was performed in a darkened room by the same experienced clinician, who was blinded to the individuals’ clinical status to eliminate any bias in the examination results.
Fig. 2Transcranial sonography image of individual with Parkinson disease. The dotted area represents mesencephalon, and the white arrow, substantia nigra.
), where grade I = the same as brainstem; grade II = scattered points and thin lines slightly stronger than brainstem; grade III = patches of moderate echogenicity but weaker than brain pool; grade IV = patches of hyperechogenicity similar to brain pool; grade V= patches of hyperechogenicity stronger than brain pool. Grades I and II are defined as hypo-echogenicity (SN–), and grades III and V as SN+ (
). To quantitatively evaluate SN+, we measured the area of SN+ on the left and right sides and calculated the larger area of SN+ of two sides (SNL), the total hyperechogenic area of the SN on both sides (SNT) and the S/M ratio (defined as SNT divided by the area of mesencephalon).
Clinical assessments
All individuals included in our study underwent detailed clinical and neuropsychological tests at baseline and follow-up. Disease severity was evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS) (
) in the “off state.” PD with LID was diagnosed if the UPDRS-IV dyskinesia score (items 32–35) was >0. The participants were divided into two groups: the PD with LID (PD+LID) group and the PD without LID (PD-LID) group. Levodopa-equivalent doses (LEDs) of medications were calculated as previously described (
In univariate analyses, variables were tested for normality using the Kolmogorov–Smirnov test or Shapiro–Wilk test. Differences in metric variables between the groups were evaluated with Student's t-test or the Mann–Whitney U-test. Dichotomous variables were compared between groups with the χ2-test. Binary logistic regression of LID was used to assess the associations among the demographic profiles, clinical assessments and SNT. A binary logistic regression model with backward stepwise procedure was used to build a model for discriminating LID. The Hosmer–Lemeshow test was performed to assess the goodness of fit. Receiver-operating characteristic (ROC) curves and areas under the ROC curves (AUCs) were also determined. Kaplan–Meier (K–M) curves were constructed to illustrate the effect of SNT and the predicted probability on LID. K–M curves were compared using the log-rank (Mantel–Cox) test. All statistical tests were two sided with p < 0.05 as the threshold for statistical significance. All tests were performed using SPSS Statistics, version 26.0, 64-bit (IBM Corp., Armonk, NY, USA).
Results
Demographics and clinical assessments at baseline
This study recruited 601 individuals with PD; 39 individuals were then excluded (Fig. 1). Therefore, 562 individuals were included in the analysis. At baseline, 105 individuals (18.7%) had experienced LID. Table 1 outlines the demographic variables and clinical assessments in the PD-LID and PD+LID groups. Sex composition and age did not significantly differ between the two groups (p = 0.266 and 0.244, respectively). Compared with the PD-LID group, the PD+LID group had an earlier age at onset (p = 0.012), longer disease duration (p < 0.001), shorter education duration (p < 0.001) and higher LEDs (p < 0.001). With respect to disease severity, the PD+LID group had a more advanced H–Y scale (p < 0.001) and higher UPDRS scores (p = 0.004 for UPDRS-I, p < 0.001 for UPDRS-II and p < 0.001 for UPDRS-III, respectively). However, there were no significant differences in cognitive performance between the two groups (p = 0.078 for the MMSE and p = 0.082 for the MoCA, respectively) (Table 1).
Table 1Demographic variables and clinical assessments in the PD-LID and PD+LID groups at baseline
LID = levodopa-induced dyskinesia; LEDs = levodopa-equivalent doses; PD = Parkinson disease; PD+LID = PD with LID; PD-LID = PID without LID; MoCA = Montreal Cognitive Assessment; MMSE = Mini Mental State Examination; SNT = total hyperechogenic area of the substantia nigra on both sides; UPDRS = Unified Parkinson's Disease Rating Scale.
Values are expressed as the number (%) or mean ± standard deviation.
p Value estimated using the χ2-test.
† p Values estimated using the Mann–Whitney U-test.
Quantitative SN+ evaluations between the PD-LID and PD+LID groups
We detected 406 (72.2%) individuals with SN+, 316 in the PD-LID group and 90 in the PD+LID group. Compared with the PD-LID group, the D+LID group had a higher proportion of SN+ (p = 0.001), larger SNL, larger SNT and higher S/M ratio (p < 0.001, respectively) (Table 2).
Table 2SN+ evaluations in the PD-LID and PD+LID groups
PD+LID = PD with LID; PD-LID = PID without LID; SN+ = substantia nigra hyperechogenicity; SNL = the larger area of SN+ on both sides; SNT = total hyperechogenic area of the substantia nigra on both sides; S/M ratio = SNT divided by the area of midbrain.
Values are expressed as the number (%) or mean ± standard deviation.
p Value estimated using the χ2-test.
† p Values estimated using the Mann–Whitney U-test.
In Figure 3 are the ROC curves of the SN+ evaluations (SNT, SNL and S/M ratio) for discriminating LID in individuals with PD. The ideal diagnostic threshold should yield the highest sum of sensitivity and specificity, and the point situated at the top left corner of the curve would be the best diagnostic cutoff value. Among three ROC curves, the curve of SNT reached the highest AUC (0.657), and we marked the point in this curve for the cutoff value of 0.315 cm2. At this point, the sensitivity was 71.4% and the specificity was 53.8%. Thus, we included SNT in our further analysis.
Fig. 3(A) ROC curve of SNT for discriminating LID. Asterisk marks the point in the SNT curve for the cutoff of 0.315 cm2. At this point, the sensitivity value was 71.4%, and the specificity value was 53.8%. The AUC was 0.657 (95% CI: 0.599–0.715, p < 0.001). (B) ROC curve of SNL for discriminating LID. The asterisk marks the point in the SNL curve for the cutoff of 0.205 cm2. At this point, the sensitivity value was 83.8%, and the specificity value was 41.6%. The AUC was 0.650 (95% CI: 0.592–0.707, p < 0.001). (C) ROC curve of S/M ratio for discriminating LID. The asterisk marks the point in the SNT curve for the cutoff of 7.97%. At this point, the sensitivity value was 66.7%, and the specificity value was 58.9%. The AUC was 0.654 (95% CI: 0.596–0.712, p < 0.001). AUC = area under the ROC curve; CI = confidence interval; LID = levodopa-induced dyskinesia; ROC = receiver operating characteristic; S/M = SNT divided by the area of mesencephalon; SN = substantia nigra; SNL = larger area of SN of two sides; SNT = total hyperechogenic area of the SN on both sides.
Table 3 outlines the results of binary logistic regression analysis of the risk factors and SNT in the PD-LID and PD+LID groups. Following binary logistic regression analysis, we found that disease duration (odds ratio [OR] = 1.015, 95% confidence interval [CI]: 1.003–1.026, p = 0.014), education duration (OR = 0.923, 95% CI: 0.865–0.984, p = 0.015), LEDs (OR = 1.003, 95% CI: 1.002–1.004, p < 0.001) and UPDRS-III score (OR = 1.026, 95% CI: 1.003–1.049, p = 0.026) were independently associated with LID. After adjustments for sex, age, age at onset, disease duration, education duration, treatment, disease severity and cognitive performance, the SNT was found to be significantly larger in the PD+LID group (OR = 2.601, 95% CI: 1.267–5.337, p = 0.009) (Table 3).
Table 3Binary logistic regression of risk factors and SNT in the PD-LID and PD+LID groups
p Values were estimated from binary logistic regression models adjusted for sex, age, age at onset, disease duration, education duration, LEDs, UPDRS-III and MoCA.
Sex (male)
296 (64.8%)
74 (70.5%)
0.863 (0.474–1.571)
0.630
Age (y)
61.2 ± 9.9
62.4 ± 9.6
1.003 (0.884–1.138)
0.962
Age at onset (y)
58.0 ± 9.8
55.3 ± 9.9
0.975 (0.856–1.111)
0.706
Disease duration (mo)
38.8 ± 34.9
89.0 ± 56.0
1.015 (1.003–1.026)
0.014
Education duration (y)
7.8 ± 4.6
5.7 ± 4.3
0.923 (0.865–0.984)
0.015
LEDs (mg)
376.7 ± 203.9
619.5 ± 290.0
1.003 (1.002–1.004)
<0.001
UPDRS-III (“off” state)
21.5 ± 11.4
30.1 ± 15.8
1.026 (1.003–1.049)
0.026
MoCA
21.2 ± 5.0
20.2 ± 5.2
0.985 (0.930–1.043)
0.599
SNT (cm2)
0.35 ± 0.34
0.55 ± 0.37
2.601 (1.267–5.337)
0.009
CI = confidence interval; LID = levodopa-induced dyskinesia; LEDs = levodopa-equivalent doses; MoCA = Montreal Cognitive Assessment; PD = Parkinson disease; PD+LID = PD with LID; PD-LID = PID without LID; SNT = total hyperechogenic area of the substantia nigra on both sides; UPDRS = Unified Parkinson's Disease Rating Scale.
The UPDRS score and Hoehn and Yahr scale were synergistic, and the MoCA and Mini Mental State Examination were synergistic, so only the UPDRS-III score and MoCA were included for analysis.
Values are expressed as the number (%) or mean ± standard deviation unless otherwise noted.
p Values were estimated from binary logistic regression models adjusted for sex, age, age at onset, disease duration, education duration, LEDs, UPDRS-III and MoCA.
The above-mentioned associated risk factors, including disease duration, education duration, LEDs, UPDRS-III score and SNT, were included in the binary logistic regression analysis with the backward stepwise procedure. Figure 4 illustrates the ROC curve of the probability for discriminating LID, which indicates that the AUC was 0.839 (95% CI: 0.795–0.883, p < 0.001) with an acceptable goodness of fit (Hosmer–Lemeshow, p > 0.05). We also marked the point in the curve for the cutoff value of 0.2025. At this point, the sensitivity was 71.4%, and the specificity was 82.3% (Fig. 4).
Fig. 4Receiver operating characteristic curve of predicted probability for discriminating levodopa-induced dyskinesia in individuals with Parkinson disease. The predicted probability was used to plot the receiver operating characteristic curve. The predicted probability was calculated with the prediction model, established by binary logistic regression analysis with the backward stepwise procedure using disease duration, education duration, levodopa-equivalent doses, Unified Parkinson's Disease Rating Scale-III score and SNT. The asterisk marks the point in the model curve for the cutoff of 0.2025. At this point, the sensitivity value was 71.4%, and the specificity value was 82.3%. The area under the receiver operating characteristic curve was 0.839 (95% confidence interval: 0.795–0.883, p < 0.001). SNT = total hyperechogenic area of the SN on both sides.
Confirmation of SNT and the prediction model with follow-up
We successfully followed up 198 individuals from the PD-LID group at baseline; the average follow-up duration was 37 mo, and 29 individuals (14.6%) developed LID during the follow-up. We first divided 198 patients into two groups, according to the SNT cutoff value (0.315 cm2). Follow-up duration, change in LEDs and UPDRS-III score between follow-up and baseline did not significantly differ between the two groups (Table 4). From the K–M curves, individuals with a lager SNT were more likely to develop LID as compared with individuals with a smaller SNT (Fig. 5).
Table 4Clinical assessments at follow-up (grouped by SNT)
p Value estimated between two groups using the χ2-test.
LEDs = levodopa-equivalent doses; LID = levodopa-induced dyskinesia; SNT = total hyperechogenic area of the substantia nigra on both sides; UPDRS = Unified Parkinson's Disease Rating Scale.
Values are expressed as the number (%) or mean ± standard deviation.
p Values estimated between two groups using the Mann–Whitney U-test.
† p Value estimated between two groups using the χ2-test.
Fig. 5Kaplan–Meier curves of developing levodopa-induced dyskinesia during follow-up (grouped by SNT). p Values were estimated using the log-rank test: p1 = comparison between the SNT <0.315 and SNT ≥0.315 groups; p2 = comparison between the SNT ≥0.315 group and all individuals followed up. SNT = total hyperechogenic area of the SN on both sides.
We then divided 198 patients according to the baseline-predicted probability cutoff value (0.2025). Follow-up duration, change in LEDs and UPDRS-III score between the follow-up and baseline groups did not significantly differ between the two groups (Table 5). From the K–M curves, individuals with a higher predicted probability were more likely to develop LID as compared with individuals with a lower predicted probability (Fig. 6).
Table 5Clinical assessments at follow-up (grouped by predicted probability)
Fig. 6Kaplan–Meier curves of developing levodopa-induced dyskinesia during follow-up (grouped by predicted probability). p Values were estimated using the log-rank test: p1 = comparison between the predicted probability <0.2025 group and the predicted probability ≥0.2025 group; p2 = comparison between the predicted probability ≥0.2025 group and all individuals followed up.
). LID may greatly affect the quality of life of individuals with PD and their families; therefore, discriminating individuals at higher risk of LID may be of importance. In this study, using binary logistic regression analysis, we found that disease duration, education duration, LEDs and disease severity were independent risk factors for LID, which is consistent with previous studies (
Clinical features and dysfunctions of iron metabolism in Parkinson disease patients with hyper echogenicity in substantia nigra: A cross-sectional study.
); this difference may be due to different components, diagnostic criteria and the operator. Therefore, because of its convenience and high diagnostic value, TCS currently has a wide range of applications in various movement disorders, especially in individuals without obvious motor symptoms.
We quantitatively analyzed the association between SN+ (detected by TCS) and LID in individuals with PD. Sex, age, age at onset, disease duration, education duration, treatment, disease severity and cognitive performance were included as covariates. We found that individuals with PD+LID had significantly larger SNT compared with individuals with PD-LID. We then constructed an ROC curve of SNT and detected moderate sensitivity (71.4%) and specificity (53.8%); the AUC was 0.657. We further established a model including four independent risk factors (disease duration, education duration, LEDs and UPDRS-III score) and SNT. The sensitivity and specificity of our model were 71.4% and 82.3%, and the AUC reached 0.839, which indicated the credibility and validity of our established model. In addition, our findings were also validated by follow-up observations, where individuals with a lager SNT or a higher predicted probability were more likely to develop LID during follow-up. These findings indicated that the quantitative characteristics of SN+ had good values in discriminating LID to a certain extent, which had not been reported before and may also increase the scope of the application of TCS in PD.
To date, the detailed mechanism causing SN+ and the causal relationship between SN+ and LID remain unknown. However, abnormal iron deposition has been reported to be associated with SN+ (
), which may provide some clues to understanding the detailed mechanism underlying SN+. Interestingly, excessive iron deposition may lead to abnormal oxidative stress in the brain, which could result in dopaminergic neuron degeneration and death (
). Nigrostriatal pathology may then further increase the risk of LID. Functional analyses are warranted in the future for further clarification.
To our knowledge, this is the first study to investigate the association between the hyperechogenic area of the SN and LID in individuals with PD. In addition, we provided an effective tool that is helpful in discriminating LID. However, our study has some limitations. First, our sample size was relatively small. Second, our patients were from one center. Further studies with a larger sample size and in different populations are warranted.
Conclusions
This study found that quantitative TCS evaluations of SN+ are associated with LID and are useful in predicting LID in individuals with PD.
Acknowledgments—We express our gratitude to all the individuals who participated in the study. This work was supported by the National Key R&D Program of China (2017YFC 0909100), Jiangsu Provincial Key R&D Program (BE2018658), Jiangsu Provincial Medical Key Discipline Project (ZDXKB2016022), Discipline Construction Program of the Second Affiliated Hospital Soochow University (XKTJ-XK202001), Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), National Natural Science Foundation of China (81801120), Pre-research Project for Doctors of the Second Affiliated Hospital of Soochow University (SDFEYBS1702) and Pre-Research Project for Doctors of the Second Affiliated Hospital of Soochow University (SDFEYBS2014).
Conflict of interest disclosure—The authors declare no competing interests.
Data availability statement—The data that support the findings of this study are available from the corresponding author on reasonable request.
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Clinical features and dysfunctions of iron metabolism in Parkinson disease patients with hyper echogenicity in substantia nigra: A cross-sectional study.
p Value estimated using the χ2-test.
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