|Year : 2019 | Volume
| Issue : 2 | Page : 58-64
Gray matter correlates of progression of motor symptoms in patients with Parkinson’s disease
Rajini M Naduthota1, Abhishek Lenka1, Lija George1, Ketan R Jhunjhunwala1, Jitender Saini2, Rose D Bharath2, Rita Christopher3, Ravi Yadav1, Arun K Gupta2, Pramod K Pal1
1 Department of Neurology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
2 Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
3 Department of Neurochemistry, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
|Date of Web Publication||13-Aug-2019|
Dr. Pramod K Pal
Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Hosur Road, Bengaluru 560029, Karnataka
Source of Support: None, Conflict of Interest: None
OBJECTIVE: The objective of this study was to evaluate the gray matter (GM) volume alterations in different clinical stages of Parkinson’s disease (PD) through voxel-based morphometry (VBM). BACKGROUND: Assessment of the clinical stages of PD is usually carried out using the Hoehn and Yahr (H–Y) scale. However, there is paucity of literature on the association of GM atrophy with the progression of motor symptoms in PD. METHODS: Forty-five patients with a diagnosis of PD (H–Y I: 15, H–Y II: 15, H–Y III: 15) and 45 healthy controls (HC) were recruited. T1-weighted images were obtained through a 3-Tesla magnetic resonance imaging machine. VBM was used to compare the regional changes in the GM volume of the three groups. RESULTS: No significant differences were observed in the demographic and clinical characteristics of the groups except in the duration of symptoms (H–Y I vs. H–Y III, 2.7 ± 1.9 vs. 7.4 ± 5.2 years, P < 0.01), and Unified Parkinson’s Disease Rating Scale III ON-state score (H–Y I vs. H–Y III, 16.2 ± 8.4 vs. 24.5 ± 8.3, P < 0.02). Volume of the left parahippocampal gyrus (Brodmann area 34) was significantly different among the four groups. Post hoc analysis revealed gradual reduction in the volume of the parahippocampal gyrus from H–Y stage I (highest) to H–Y stage III (lowest). CONCLUSION: There is progressive decrease in GM volume of the parahippocampal gyrus with the advancement of stage of PD. This result suggests that the volume of parahippocampal gyrus may represent one of the neuroimaging correlates of the H–Y staging of PD.
Keywords: Hoehn and Yahr staging, magnetic resonance imaging, parahippocampal gyrus, Parkinson’s disease, voxel-based morphometry
|How to cite this article:|
Naduthota RM, Lenka A, George L, Jhunjhunwala KR, Saini J, Bharath RD, Christopher R, Yadav R, Gupta AK, Pal PK. Gray matter correlates of progression of motor symptoms in patients with Parkinson’s disease. Ann Mov Disord 2019;2:58-64
|How to cite this URL:|
Naduthota RM, Lenka A, George L, Jhunjhunwala KR, Saini J, Bharath RD, Christopher R, Yadav R, Gupta AK, Pal PK. Gray matter correlates of progression of motor symptoms in patients with Parkinson’s disease. Ann Mov Disord [serial online] 2019 [cited 2019 Oct 23];2:58-64. Available from: http://www.aomd.in/text.asp?2019/2/2/58/264363
| Introduction|| |
Parkinson’s disease (PD) is a progressive neurodegenerative disorder. In addition to the cardinal motor symptoms, such as tremor at rest, bradykinesia, rigidity, and postural instability, several non-motor symptoms (NMS) may emerge during the clinical course of PD. Neuronal loss in the substantia nigra pars compacta and the presence of Lewy bodies (LB) filled with misfolded α-synuclein aggregates in the neuronal cell bodies are the pathological hallmarks of PD. The pathological process in PD may begin 5–20 years before the clinical manifestations. As per the Braak staging system, progressive accumulation of LB in different regions of the brain foretells the clinical spectrum of PD. Clinically, PD is categorized into different stages as per the Hoehn and Yahr (H–Y) scale, which is the most widely used categorical motor disability rating scale for PD.
Voxel-based morphometry (VBM) is an automated, quantitative magnetic resonance imaging (MRI) technique that is used to assess the in vivo gray matter (GM) changes in several neurodegenerative conditions. VBM studies in PD have revealed alterations in the GM volume in different regions of the brain. However, there is paucity of data on the neuroanatomical correlation of PD progression according to H–Y staging. In a longitudinal study, Ramírez-Ruiz et al. observed progressive GM loss in limbic, paralimbic, and temporo-occipital regions during a mean follow-up of 25 months in patients with PD using VBM. On the contrary, a recent study has reported increased thalamic volume in the patients of PD with progression of the disease when compared to that in the healthy controls (HC). Given the significant influence of GM atrophy on PD pathology, it is essential to study the pattern of alterations in the volume of GM in different clinical stages of PD. Therefore, to evaluate the neural correlates of the progressive nature of PD, we assessed the changes in the GM using VBM in different clinical stages of PD and compared it with HC.
| Methodology|| |
We recruited 45 patients with PD and an equal number of age- and gender-matched HC. All the patients were prospectively recruited from the neurology outpatient clinics and the movement disorder clinics. Diagnosis of PD was carried out as per the UK Parkinson’s Disease Society Brain Bank criteria. This study was approved by the Institutional Ethics Committee, and written informed consent was obtained from all the subjects.
Severity of the motor symptoms was evaluated using the motor component of the Unified Parkinson’s Disease Rating Scale (UPDRS-III). Clinical stages of PD were determined using the H–Y scale. Mini-Mental State Examination (MMSE) was used to assess the global cognitive function. Hamilton Anxiety Rating Scale (HAM-A) and Hamilton Depression Rating Scale (HAM-D) were also applied as a part of neurobehavioral assessment. In the 17-item HAM-D scale, a higher score suggests increased depression. The scale scores were classified as (1) no depression (0–7), (2) mild depression (8–16), (3) moderate depression (17–23), and (4) severe depression (≥24). Similarly, the 14-item HAM-A scale was scored on a scale of 0 (not present) to 4 (severe), with a total score range of 0–56, where <17 score indicates mild anxiety; 18–24, mild to moderate anxiety; and 25–30, moderate to severe anxiety.
Magnetic resonance imaging acquisition
MR images were obtained through a 3-Tesla scanner (Philips Achieva 3T, Philips Medical Systems, Amsterdam, the Netherlands) using a 32-channel head coil. The images were acquired during the best ON-state of the patients to minimize the movement artefacts. The same imaging protocol was used for all the patients and HC. The T1-weighted images were acquired using a magnetization prepared rapid acquisition gradient echo sequence (repetition time = 8.2ms, echo time = 3.8ms, flip angle = 8°, field of view = 256 × 256 × 165mm, 256 sagittal slices, and voxel size = 1 × 1 ×1mm). All the images were checked by an experienced neuroradiologist (author, JS) for structural abnormalities before analysis.
Processing of the MR images was carried out using the Statistical Parametric Mapping 8 (Wellcome Department of Cognitive Neurology, www.fil.ion.ucl.ac.uk/spm/software/spm8/) in MATLAB (Math Works, R2013a) setup using VBM8 toolbox. Before processing the data, each subject’s data were oriented into standard anterior commissure-posterior commissure plane. The processing steps included an initial segmentation into GM, white matter, and cerebrospinal fluid, followed by a spatial normalization of the GM images into the Montreal Neurological Institute (MNI) template. Subsequently, the GM images were smoothened with an isotropic Gaussian kernel of 8mm full width at half maximum.
The clinical results were expressed as mean ± standard deviation. All clinical parameters were assessed for normal distribution. Two-sample t-test was applied to assess the intergroup differences, and one-way analysis of variance (ANOVA) was applied to test intergroup differences for more than two groups. Statistical significance was determined with P < 0.05.
For VBM, a general linear model was applied on the smoothened GM images. ANOVA analysis (family-wise error [FWE] corrected P < 0.05) of all the three patient groups and HC was carried out to determine and evaluate the differences in the GM volume among the groups. Age, gender, and total intracranial volume (TIV) were considered as covariates for group comparison. The results were corrected for multiple comparisons with a threshold of P < 0.05 (FWE). Multiple regression analysis was reported with uncorrected P < 0.001 with an extend threshold of 100 voxels.
The graph showing the contrast estimates corresponding to all the four groups included in ANOVA analysis was generated at a confidence interval of 90%. MarsBaR (MARSeille Boîte À Région d’Intérêt) toolbox implemented in SPM8 was used to extract the mean raw signal value of the left parahippocampal gyrus cluster, which was identified to be significantly different among groups in one-way ANOVA analysis. Anatomical localization of the brain regions having significant alterations of GM density was carried out using the Talairach client (www.talairach.org) after converting the MNI coordinates into Talairach coordinates using GingerALE (http://www.brainmap.org/ale/).
| Results|| |
No statistically significant differences were observed in the age, gender, and age at the onset of PD between PD subgroups. The duration of symptoms was 5.1 ± 4.1 years in overall PD cohort, 2.7 ± 1.9 years in H–Y I, 5.9 ± 3.9 years in H–Y II, and 7.4 ± 5.2 years in H–Y III. ANOVA analysis revealed significant difference in the duration of illness between PD subgroups, F (2,42) = 5.2, P = 0.01. UPDRS-III scores between PD subgroups were also significantly different as ascertained by one-way ANOVA, F (2,42) = 4.03, P = 0.02. Post hoc analysis with Bonferroni correction revealed that UPDRS-III score was significantly less in H–Y I when compared to that in H–Y III (16.2 ± 8.4 vs. 24.5 ± 8.3, P = 0.02). No statistically significant differences were observed in H–Y II (22.4 ± 6.1) either with H–Y I (P = 0.08) or with H–Y III (P = 0.8).
Of the 45 patients with PD, eight had history of psychosis (four in H–Y II and four in H–Y III). Among those eight patients, six had history of formed visual hallucinations (VH) and two had history of both visual and minor hallucinations.
HAM-D score was significantly different between the PD subgroups, F (2,42) = 9.8, P > 0.001. Further analysis showed that HAM-D was significantly higher in H–Y III (11.5 ± 4.3) when compared with that in H–Y I (5.7 ± 2.2, P = 0.001) and with that in H–Y II group (8.3 ± 3.2, P = 0.047). In the overall PD group, 17 (37%) patients had mild depression (four in H–Y I, eight in H–Y II, and five in H–Y III), four (8.9%) patients had moderate depression (none in H–Y I, one in H–Y II, and three in H–Y III), and one (2.2%) patient in H–Y III had severe depression. A total of 53% patients with PD complained about loss of taste and smell in the overall PD group (40% in H–Y I, 47% in H–Y II, and 67% in H–Y III) as recorded by item 12 of HAM-D.
Severity of anxiety, measured by HAM-A scale, was found to be significantly different between PD subgroups, F (2,42) = 8.1, P = 0.001. HAM-A was significantly different between H–Y III and H–Y I (P = 0.001), but not between H–Y I and H–Y II (P = 0.23) and between H–Y II and H–Y III (P = 0.08). In the overall patient cohort, seven (15.6%) patients had mild anxiety (two in H–Y I, three in H–Y II, and two in H–Y III), five (11.1%) patients had moderate anxiety (none in H–Y I, two in H–Y II, and three in H–Y III) and two (4.4%) patients had severe anxiety (none in H–Y I and H–Y II and two in H–Y III) as assessed by HAM-A. However, these findings were not significantly different among PD groups. Clinical and demographical details are presented in [Table 1].
|Table 1: Demographics and clinical profile of different H–Y stages of patients with PD and healthy controls|
Click here to view
Voxel-based morphometry results
The patients and the controls had a comparable TIV (1314 ± 109 vs. 1287 ± 95mm3). ANOVA performed between four groups (three PD groups and HC group) showed significant GM loss in left parahippocampal gyrus (Brodmann area, 34) (P < 0.05, FWE corrected) [Figure 1]. Further, two-sample t-test between each stage of H–Y with HC revealed gradual reduction in the volume of GM in parahippocampal gyrus, which was evident by increased voxel size and peak t-value (voxel size, 76 < 695 < 887; peak t-value, 5.3 < 5.97 < 6.33) [Figure 2]. However, within PD groups (H–Y I vs. H–Y II, H–Y I vs. H–Y III, and H–Y II vs. H–Y III), there was a trend toward increased GM atrophy, but it failed to attain any statistical significance with disease stage progression. Apart from parahippocampal gyrus, GM atrophy was found in medial frontal gyrus and superior frontal gyrus in H–Y III when compared to HC. [Table 2] summarizes the MNI coordinates of GM atrophy in the affected brain regions.
|Figure 1: (A) Analysis of variance (ANOVA) analysis depicting gray matter atrophy in left parahippocampal gyrus (PHG) (P < 0.05, FWE corrected). Results superimposed on an SPM8 canonical single subject template in selected planes. Color bar represents the t score. (B) “Glass brain” image representing maximum intensity at left parahippocampal gyrus (PHG). (C) Description of contrast estimates in parahippocampal gyrus (PHG) using MarsBaR toolbox implemented in SPM8. (D) The SPM 8 design matrix for ANOVA analysis|
Click here to view
|Figure 2: Gradual increase in gray matter atrophy as Hoehn and Yahr (H–Y) stage advances, (P < 0.05, FWE corrected). (A) H–Y I vs. controls. (B) H–Y II vs. controls. (C) H–Y III vs. controls. The set of images shows results superimposed on an SPM8 canonical single-subject template in selected planes. The color bar on the right side represents the t score|
Click here to view
|Table 2: Voxel-based morphometry results showing anatomical regions with grey matter volume loss in different H–Y stages of patients with Parkinson’s disease compared to the controls (FWE corrected, P < 0.05)|
Click here to view
HAM-A, HAM-D, MMSE, and UPDRS scores were correlated with GM volume in the patient group. Age, gender, and TIV were considered as covariates for multiple regression analysis. HAM-A, HAM-D, and MMSE scores did not correlate with any of the brain areas in PD and HC groups. UPDRS-III score had significant negative correlation with left parahippocampal GM volume (voxel size, 607; peak t value, 5.52) (P < 0.001 uncorrected). We further estimated the parahippocampal volume using the MarsBaR toolbox. Although parahippocampal volume was significantly decreased in patients with PD (0.667 ± 0.07 vs. 0.778 ± 0.05), it did not correlate with UPDRS-III, HAM-A, and HAM-D score, age at onset, or with duration of symptoms.
| Discussion|| |
The pathological hallmark of PD is progressive degeneration of the nigrostriatal dopaminergic neurons. However, PD is a network disorder and is also known to alter non-dopamine systems such as serotonergic and noradrenergic systems. This multisystem effect is perhaps related to atrophy in several areas of the brain, which perhaps leads to a series of motor and NMS. Several NMS are observed in PD, onset of which may, in fact, predate the onset of the motor symptoms. A number of studies on PD have revealed an association between cognitive impairment, depression, VH, and hyposmia with a reduced volume of the parahippocampal gyrus.,, This study, using VBM, evaluated the changes in the GM volume associated with different clinical stages of PD and compared with HC. The most important finding of our study is the gradual decline in GM volume in left parahippocampal gyrus with disease progression.
Parahippocampal gyrus is a part of medial temporal lobe, which is situated between hippocampus and fusiform cortex. It is a part of larger complex network, which connects regions of frontal, parietal, and temporal lobes and is believed to be implied in many higher order functions. A functional MRI (fMRI) study has shown that functional activation in the parahippocampal gyrus has positive correlation with the recollection-based memory and it works in concert with the hippocampus and the perirhinal cortex to execute episodic memory functions. There is evidence to suggest that the parahippocampal gyrus also plays a critical role in emotional interpretation. In addition, the parahippocampal place area, a subunit of the parahippocampal gyrus, has been found to be associated with visual scene analysis.
Results of this study are in agreement with the previous studies, which confirmed the involvement of left parahippocampal gyrus atrophy in nondemented patients with PD in the advanced stages of the disease. We observed a gradual decrease in the GM volume with disease progression according to H–Y staging. There are various published studies, which have found association between parahippocampal gyrus atrophy and cognitive functions such as visuospatial and executive memory.,, Some of the NMS such as cognitive dysfunction, depression, disturbances in the sleep, and autonomic function are known to be increased in PD with the duration of illness. Hence, gradual increase in GM atrophy may be associated with increased severity of these NMS with the duration of illness. In our study, the MMSE scores were comparable between the subgroups of PD. This could be because MMSE is not sensitive enough to detect mild cognitive dysfunction. As most of the patients with PD develop cognitive impairment and depression in later stages of the illness, GM atrophy in parahippocampal gyrus may be an indicator of the extent of disability in the future course of the disease. Neuropsychological assessment and its correlation with GM atrophy would give a better picture of the pathobiology of PD, which we consider as a limitation in our study.
Parahippocampal gyrus atrophy was found in patients of PD with depression when compared to those without depression. In our study, depression and anxiety scores were found to be significantly higher with the progression of disease stage. However, multiple regression analysis did not reveal significant correlation between depression and anxiety scores and GM volume. These results could be due to GM loss in areas other than parahippocampal gyrus, such as bilateral orbitofrontal, right temporal, and limbic regions, which are also responsible for depression in PD. In addition, UPDRS-III motor score was negatively correlated with parahippocampal volume. The complex interplay of parahippocampal gyrus may be one of the reasons for the non-motor manifestations in PD. Impaired reality monitoring and afflicted visual inputs are speculated to be one of the main reasons for VH in patients with PD. A VBM-based study, performed between the patients of PD with and without VH, revealed GM atrophy in right parahippocampal gyrus in those with VH. A study by Summerfield et al. also found similar observation in their case–control study using VBM analysis. Presence of VH in higher stages of H–Y staging, in our study, substantiates the aforementioned finding. However, our study failed to find any association between parahippocampal volume and the presence of VH in patient group. In view of less number of patients with PD having VH in our study, future studies need to be carried out with a larger sample size.
Changes in olfaction are common premotor symptoms in PD. Wu et al., in a study on 26 patients with PD, attributed the changes in olfactory function in early PD to the GM atrophy in parahippocampal gyrus. They used the “five odors of olfactory detection arrays” method developed by the Chinese Academy of Sciences to assess olfaction, and correlated the findings with VBM to demonstrate that structural changes in the parahippocampal gyrus may appear even before the obvious olfactory dysfunction. This finding is directly supported by a combined olfactory event-related potential and fMRI study. Patients with hyposmia showed reduced neuronal activity in parahippocampal cortex following olfactory stimulation as analyzed by fMRI. Almost 80% of flavor identification depends on olfactory inputs. Most often patients with loss of smell interpret it as loss of taste, so dysgeusia can be used as an indicator of hyposmia. Consistent with this view, patients with PD who had complained about loss of taste were more in H–Y III in our study group when compared to H–Y I as interpreted by HAM-D subscore. Therefore, our study indirectly confirms the association between parahippocampal gyrus and the presence of hyposmia. Apart from parahippocampal gyrus, GM atrophy was also found in medial frontal gyrus and superior frontal gyrus between H–Y III and HC. These structures are known to be associated with PD pathology.
Our study highlights the volume loss in parahippocampal gyrus in PD and its correlation with neurological findings. FWE corrected thresholds used in VBM analysis, fully protect the results owing to chance findings and false positives. Patients with PD have several NMS that may be associated with GM atrophy in specific brain areas. In accordance with the current neuropathological staging system, GM atrophy may be highlighting the pathological alterations in the cortical and subcortical structures, thus predicting severity of illness.
The major limitation of our study is the small sample size of each PD subgroup, which could be one of the possible explanation for failure to find statistical difference between PD subgroups. Another demerit is the absence of neuropsychological testing and non-motor scale application to study the correlation of these measures with the GM volume loss. However, the primary aim of this study was to look for gradual change in GM structures with H–Y staging, which was significantly established.
| Conclusion|| |
To conclude, our study reveals progressive GM loss in non-nigrostriatal system, mainly the parahippocampal gyrus with the advancement of H–Y stage. Future longitudinal studies in larger cohort of patients with more detailed motor and NMS evaluations are required to study the neuroanatomical correlates of the clinical H–Y staging.
Financial support and sponsorship
This work was financially supported by the Department of Biotechnology (DBT), Government of India (Grant Number: NO. BT/PR14315/MED/30/474/2010).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Jellinger KA A critical reappraisal of current staging of Lewy-related pathology in human brain. Acta Neuropathol 2008;116:1-16.
van de Berg WDJ, Hepp DH, Dijkstra AA, Rozemuller JAM, Berendse HW, Foncke E Patterns of alpha-synuclein pathology in incidental cases and clinical subtypes of Parkinson’s disease. Parkinsonism Relat Disord 2011;18:s28-30.
Braak H, Del Tredici K, Bratzke H, Hamm-Clement J, Sandmann-Keil D, Rüb U Staging of the intracerebral inclusion body pathology associated with idiopathic Parkinson’s disease (preclinical and clinical stages). J Neurol 2003;249:1-5.
Hoehn MM, Yahr MD Parkinsonism: Onset, progression and mortality. Neurology 1998;17:427-42.
Ashburner J, Friston KJ Voxel-based morphometry—The methods. Neuroimage 2000;11:8-5-21.
Pavese N, Brooks DJ Imaging neurodegeneration in Parkinson’s disease. Biochim Biophys Acta Mol Basis Dis 2009;1792:722-9.
Ramírez-Ruiz B, Martí MJ, Tolosa E, Bartrés-Faz D, Summerfield C, Salgado-Pineda P, et al
. Longitudinal evaluation of cerebral morphological changes in Parkinson’s disease with and without dementia. J Neurol 2005;252:1345-52.
Jia X, Liang P, Li Y, Shi L, Wang D, Li K Longitudinal study of gray matter changes in Parkinson disease. Am J Neuroradiol 2015;36:2219-26.
Hughes AJ, Daniel SE, Kilford L, Lees AJ Accuracy of clinical diagnosis of idiopathic Parkinson’s disease: A clinico-pathological study of 100 cases. J Neurol Neurosurg Psychiatry 1992;55:181-4.
Folstein MF, Folstein SE, McHugh PR “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-98.
Hamilton M The assessment of anxiety states by rating. Br J Med Psychol 1959;32:50-5.
Hamilton M A rating scale for depression. J Neurol Neurosurg Psychiatry 1960;23:56-62.
Xia JG, Wang J, Tian WZ, Ding H, Wei QL, Huang HX, et al
. Magnetic resonance morphometry of the loss of gray matter volume in Parkinson’s disease patients. Neural Regen Res 2013;8:2557-65. [Full text]
Pont-Sunyer C, Hotter A, Gaig C, Seppi K, Compta Y, Katzenschlager R, et al
. The onset of nonmotor symptoms in Parkinson’s disease (the ONSET PD study). Mov Disord 2015;30:229-37.
Watanabe H, Senda J, Kato S, Ito M, Atsuta N, Hara K, et al
. Cortical and subcortical brain atrophy in Parkinson’s disease with visual hallucination. Mov Disord 2013;28:1732-6.
Wu X, Yu C, Fan F, Zhang K, Zhu C, Wu T, et al
. Correlation between progressive changes in piriform cortex and olfactory performance in early Parkinson’s disease. Eur Neurol 2011;66:98-105.
Gerrits NJHM, van der Werf YD, Hofman M, Foncke EMJ, Klein M, Berendse HW, et al
. Gray matter differences contribute to variation in cognitive performance in Parkinson’s disease. Eur J Neurol 2014;21:245-52.
Aminoff EM, Kveraga K, Bar M The role of the parahippocampal cortex in cognition. Trends Cogn Sci 2013;17:379-90.
Diana RA, Yonelinas AP, Ranganath C Medial temporal lobe activity during source retrieval reflects information type, not memory strength. J Cogn Neurosci 2010;22:1808-18.
Gosselin N, Samson S, Adolphs R, Noulhiane M, Roy M, Hasboun D, et al
. Emotional responses to unpleasant music correlates with damage to the parahippocampal cortex. Brain 2006;129:2585-92.
Stevens WD, Kahn I, Wig GS, Schacter DL Hemispheric asymmetry of visual scene processing in the human brain: Evidence from repetition priming and intrinsic activity. Cereb Cortex 2012;22:1935-49.
Nagano-Saito A, Washimi Y, Arahata Y, Kachi T, Lerch JP, Evans AC, et al
. Cerebral atrophy and its relation to cognitive impairment in Parkinson disease. Neurology 2005;64:224-9.
van Rooden SM, Verbaan D, Stijnen T, Marinus J, van Hilten JJ The influence of age and approaching death on the course of nondopaminergic symptoms in Parkinson’s disease. Parkinsonism Relat Disord 2016;24:113-8.
Feldmann A, Illes Z, Kosztolanyi P, Illes E, Mike A, Kover F, et al
. Morphometric changes of gray matter in Parkinson’s disease with depression: A voxel-based morphometry study. Mov Disord 2008;23:42-6.
Summerfield C, Junqué C, Tolosa E, Salgado-Pineda P, Gómez-Ansón B, Martí MJ, et al
. Structural brain changes in Parkinson disease with dementia: A voxel-based morphometry study. Arch Neurol 2005;62:281-5.
Welge-Lüssen A, Wattendorf E, Schwerdtfeger U, Fuhr P, Bilecen D, Hummel T, et al
. Olfactory-induced brain activity in Parkinson’s disease relates to the expression of event-related potentials: A functional magnetic resonance imaging study. Neuroscience 2009;162:537-43.
Wrobel BB, Leopold DA Clinical assessment of patients with smell and taste disorders. Otolaryngol Clin North Am 2004;37:1127-42.
[Figure 1], [Figure 2]
[Table 1], [Table 2]