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Pasquini J, Firbank MJ, Ceravolo R, Silani V, Pavese N. Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review. Mov Disord 2022; 37:1963-1984. [PMID: 36036378 DOI: 10.1002/mds.29195] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/22/2022] [Accepted: 08/01/2022] [Indexed: 01/07/2023] Open
Abstract
Multiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty-four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Jacopo Pasquini
- Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michael J Firbank
- Positron Emission Tomography Centre, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Roberto Ceravolo
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.,Neurodegenerative Diseases Center, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milan, Italy.,Department of Pathophysiology and Transplantation, Dino Ferrari Center, Università degli Studi di Milano, Milan, Italy
| | - Nicola Pavese
- Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
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Zhang Y, Burock MA. Diffusion Tensor Imaging in Parkinson's Disease and Parkinsonian Syndrome: A Systematic Review. Front Neurol 2020; 11:531993. [PMID: 33101169 PMCID: PMC7546271 DOI: 10.3389/fneur.2020.531993] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Accepted: 08/18/2020] [Indexed: 12/21/2022] Open
Abstract
Diffusion tensor imaging (DTI) allows measuring fractional anisotropy and similar microstructural indices of the brain white matter. Lower than normal fractional anisotropy as well as higher than normal diffusivity is associated with loss of microstructural integrity and neurodegeneration. Previous DTI studies in Parkinson's disease (PD) have demonstrated abnormal fractional anisotropy in multiple white matter regions, particularly in the dopaminergic nuclei and dopaminergic pathways. However, DTI is not considered a diagnostic marker for the earliest Parkinson's disease since anisotropic alterations present a temporally divergent pattern during the earliest Parkinson's course. This article reviews a majority of clinically employed DTI studies in PD, and it aims to prove the utilities of DTI as a marker of diagnosing PD, correlating clinical symptomatology, tracking disease progression, and treatment effects. To address the challenge of DTI being a diagnostic marker for early PD, this article also provides a comparison of the results from a longitudinal, early stage, multicenter clinical cohort of Parkinson's research with previous publications. This review provides evidences of DTI as a promising marker for monitoring PD progression and classifying atypical PD types, and it also interprets the possible pathophysiologic processes under the complex pattern of fractional anisotropic changes in the first few years of PD. Recent technical advantages, limitations, and further research strategies of clinical DTI in PD are additionally discussed.
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Affiliation(s)
- Yu Zhang
- Department of Psychiatry, War Related Illness and Injury Study Center, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, United States
| | - Marc A Burock
- Department of Psychiatry, Mainline Health, Bryn Mawr Hospital, Bryn Mawr, PA, United States
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Differential Diagnostic Reasoning Method for Benign Paroxysmal Positional Vertigo Based on Dynamic Uncertain Causality Graph. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2020; 2020:1541989. [PMID: 32411277 PMCID: PMC7204354 DOI: 10.1155/2020/1541989] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 09/08/2019] [Accepted: 11/11/2019] [Indexed: 11/17/2022]
Abstract
The accurate differentiation of the subtypes of benign paroxysmal positional vertigo (BPPV) can significantly improve the efficacy of repositioning maneuver in its treatment and thus reduce unnecessary clinical tests and inappropriate medications. In this study, attempts have been made towards developing approaches of causality modeling and diagnostic reasoning about the uncertainties that can arise from medical information. A dynamic uncertain causality graph-based differential diagnosis model for BPPV including 354 variables and 885 causality arcs is constructed. New algorithms are also proposed for differential diagnosis through logical and probabilistic inference, with an emphasis on solving the problems of intricate and confounding disease factors, incomplete clinical observations, and insufficient sample data. This study further uses vertigo cases to test the performance of the proposed method in clinical practice. The results point to high accuracy, a satisfactory discriminatory ability for BPPV, and favorable robustness regarding incomplete medical information. The underlying pathological mechanisms and causality semantics are verified using compact graphical representation and reasoning process, which enhance the interpretability of the diagnosis conclusions.
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Pandya S, Zeighami Y, Freeze B, Dadar M, Collins DL, Dagher A, Raj A. Predictive model of spread of Parkinson's pathology using network diffusion. Neuroimage 2019; 192:178-194. [PMID: 30851444 PMCID: PMC7180066 DOI: 10.1016/j.neuroimage.2019.03.001] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 01/20/2019] [Accepted: 03/01/2019] [Indexed: 02/03/2023] Open
Abstract
Growing evidence suggests that a "prion-like" mechanism underlies the pathogenesis of many neurodegenerative disorders, including Parkinson's disease (PD). We extend and tailor previously developed quantitative and predictive network diffusion model (NDM) to PD, by specifically modeling the trans-neuronal spread of alpha-synuclein outward from the substantia nigra (SN). The model demonstrated the spatial and temporal patterns of PD from neuropathological and neuroimaging studies and was statistically validated using MRI deformation of 232 Parkinson's patients. After repeated seeding simulations, the SN was found to be the most likely seed region, supporting its unique lynchpin role in Parkinson's pathology spread. Other alternative spread models were also evaluated for comparison, specifically, random spread and distance-based spread; the latter tests for Braak's original caudorostral transmission theory. We showed that the distance-based spread model is not as well supported as the connectivity-based model. Intriguingly, the temporal sequencing of affected regions predicted by the model was in close agreement with Braak stages III-VI, providing what we consider a "computational Braak" staging system. Finally, we investigated whether the regional expression patterns of implicated genes contribute to regional atrophy. Despite robust evidence for genetic factors in PD pathogenesis, NDM outperformed regional genetic expression predictors, suggesting that network processes are far stronger mediators of regional vulnerability than innate or cell-autonomous factors. This is the first finding yet of the ramification of prion-like pathology propagation in Parkinson's, as gleaned from in vivo human imaging data. The NDM is potentially a promising robust and clinically useful tool for diagnosis, prognosis and staging of PD.
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Affiliation(s)
- S Pandya
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
| | - Y Zeighami
- Montreal Neurological Institute, Brain Imaging Centre, McGill University, Canada
| | - B Freeze
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - M Dadar
- Montreal Neurological Institute, Brain Imaging Centre, McGill University, Canada
| | - D L Collins
- Montreal Neurological Institute, Brain Imaging Centre, McGill University, Canada
| | - A Dagher
- Montreal Neurological Institute, Brain Imaging Centre, McGill University, Canada
| | - A Raj
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA; Department of Radiology, UCSF School of Medicine, San Francisco, CA, USA.
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Geibl FF, Henrich MT, Oertel WH. Mesencephalic and extramesencephalic dopaminergic systems in Parkinson's disease. J Neural Transm (Vienna) 2019; 126:377-396. [PMID: 30643975 DOI: 10.1007/s00702-019-01970-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 01/08/2019] [Indexed: 12/13/2022]
Abstract
Neurodegeneration of the nigrostriatal dopaminergic system and concurrent dopamine (DA) deficiency in the basal ganglia represent core features of Parkinson's disease (PD). Despite the central role of DA in the pathogenesis of PD, dopaminergic systems outside of the midbrain have not been systematically investigated for Lewy body pathology or neurodegeneration. Dopaminergic neurons show a surprisingly rich neurobiological diversity, suggesting that there is not one general type of dopaminergic neuron, but rather a spectrum of different dopaminergic phenotypes. This heterogeneity on the cellular level could account for the observed differences in susceptibility of the dopaminergic systems to the PD disease process. In this review, we will summarize the long history from the first description of PD to the rationally derived DA replacement therapy, describe the basal neuroanatomical and neuropathological features of the different dopaminergic systems in health and PD, explore how neuroimaging techniques broadened our view of the dysfunctional dopaminergic systems in PD and discuss how dopaminergic replacement therapy ameliorates the classical motor symptoms but simultaneously induces a new set of hyperdopaminergic symptoms.
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Affiliation(s)
- Fanni F Geibl
- Department of Neurology, Philipps University Marburg, Baldingerstraße 1, 35043, Marburg, Germany.
| | - Martin T Henrich
- Department of Neurology, Philipps University Marburg, Baldingerstraße 1, 35043, Marburg, Germany
| | - Wolfgang H Oertel
- Department of Neurology, Philipps University Marburg, Baldingerstraße 1, 35043, Marburg, Germany
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Talai AS, Ismail Z, Sedlacik J, Boelmans K, Forkert ND. Improved Automatic Morphology-Based Classification of Parkinson's Disease and Progressive Supranuclear Palsy. Clin Neuroradiol 2018; 29:605-614. [PMID: 30218110 DOI: 10.1007/s00062-018-0727-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 08/25/2018] [Indexed: 12/12/2022]
Abstract
OBJECTIVES The overlapping symptoms of Parkinson's disease (PD) and progressive supranuclear palsy-Richardson's syndrome (PSP-RS) often make a correct clinical diagnosis difficult. The volume of subcortical brain structures derived from high-resolution T1-weighted magnetic resonance imaging (MRI) datasets is frequently used for individual level classification of PD and PSP-RS patients. The aim of this study was to evaluate the benefit of including additional morphological features beyond the simple regional volume, as well as clinical features, and morphological features of cortical structures for an automatic classification of PD and PSP-RS patients. MATERIAL AND METHODS A total of 98 high-resolution T1-weighted MRI datasets from 76 PD patients, and 22 PSP-RS patients were available for this study. Using an atlas-based approach, the volume, surface area, and surface-area-to-volume ratio (SA:V) of 21 subcortical and 48 cortical brain regions were calculated and used as features for a support vector machine classification after application of a RELIEF feature selection method. RESULTS The comparison of the classification results suggests that including all three morphological parameters (volume, surface area and SA:V) can considerably improve classification accuracy compared to using volume or surface area alone. Likewise, including clinical patient features in addition to morphological parameters also considerably increases the classification accuracy. In contrast to this, integrating morphological features of other cortical structures did not lead to improved classification accuracy. Using this optimal set-up, an accuracy of 98% was achieved with only one falsely classified PD and one falsely classified PSP-RS patient. CONCLUSION The results of this study suggest that clinical features as well as more advanced morphological features should be used for future computer-aided diagnosis systems to differentiate PD and PSP-RS patients based on morphological parameters.
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Affiliation(s)
- Aron S Talai
- Department of Radiology and Hotchkiss Brain Institute, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, AB T2N 4N1, Calgary, Canada
| | - Zahinoor Ismail
- Departments of Psychiatry, Clinical Neurosciences, and Community Health Sciences, and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Jan Sedlacik
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kai Boelmans
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Nils D Forkert
- Department of Radiology and Hotchkiss Brain Institute, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, AB T2N 4N1, Calgary, Canada.
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Atkinson-Clement C, Pinto S, Eusebio A, Coulon O. Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis. Neuroimage Clin 2017; 16:98-110. [PMID: 28765809 PMCID: PMC5527156 DOI: 10.1016/j.nicl.2017.07.011] [Citation(s) in RCA: 169] [Impact Index Per Article: 24.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Revised: 07/13/2017] [Accepted: 07/14/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing. METHODS We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (DES) as the main variable; the heterogeneity index (I2) and Pearson's correlations between the DES and co-variables (demographic, clinical and MRI parameters) were also calculated. RESULTS Our results showed that FA-DES and MD-DES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-DES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter. CONCLUSIONS Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.
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Affiliation(s)
| | - Serge Pinto
- Aix Marseille Univ, CNRS, LPL, Aix-en-Provence, France
- Brain and Language Research Institute, Aix Marseille Univ, Aix-en-Provence, France
| | - Alexandre Eusebio
- Aix Marseille Univ, APHM, Hôpital de la Timone, Service de Neurologie et Pathologie du Mouvement, Marseille, France
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille France
| | - Olivier Coulon
- Brain and Language Research Institute, Aix Marseille Univ, Aix-en-Provence, France
- Aix Marseille Univ, CNRS, INT, Inst Neurosci Timone, Marseille France
- Aix Marseille Univ, CNRS, LSIS lab, UMR 7296, Marseille, France
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Diffusion tensor imaging parameters' changes of cerebellar hemispheres in Parkinson's disease. Neuroradiology 2014; 57:327-34. [PMID: 25479963 DOI: 10.1007/s00234-014-1473-5] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2014] [Accepted: 11/24/2014] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Studies with diffusion tensor imaging (DTI) analysis have produced conflicting information about the involvement of the cerebellar hemispheres in Parkinson's disease (PD). We, thus, used a new approach for the analysis of DTI parameters in order to ascertain the involvement of the cerebellum in PD. METHODS We performed a fiber tract-based analysis of cerebellar peduncles and cerebellar hemispheres in 16 healthy subjects and in 16 PD patients with more than 5 years duration of disease, using a 3T MRI scanner and a constrained spherical deconvolution (CSD) approach for tractographic reconstructions. In addition, we performed statistical analysis of DTI parameters and fractional anisotropy (FA) XYZ direction samplings. RESULTS We found a statistically significant decrement of FA values in PD patients compared to controls (p < 0.05). In addition, extrapolating and analyzing FA XYZ direction samplings for each patient and each control, we found that this result was due to a stronger decrement of FA values along the Y axis (antero-posterior direction) (p < 0.01); FA changes along X and Z axes were not statistically significant (p > 0.05). We confirmed also no statistically significant differences of FA and apparent diffusion coefficient (ADC) for cerebellar peduncles in PD patients compared to healthy controls. CONCLUSIONS The DTI-based cerebellar abnormalities in PD could constitute an advance in the knowledge of this disease. We demonstrated a statistically significant reduction of FA in cerebellar hemispheres of PD patients compared to healthy controls. Our work also demonstrated that the use of more sophisticated approaches in the DTI parameter analysis could potentially have a clinical relevance.
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Politis M. Neuroimaging in Parkinson disease: from research setting to clinical practice. Nat Rev Neurol 2014; 10:708-22. [PMID: 25385334 DOI: 10.1038/nrneurol.2014.205] [Citation(s) in RCA: 165] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Over the past three decades, neuroimaging studies-including structural, functional and molecular modalities-have provided invaluable insights into the mechanisms underlying Parkinson disease (PD). Observations from multimodal neuroimaging techniques have indicated changes in brain structure and metabolic activity, and an array of neurochemical changes that affect receptor sites and neurotransmitter systems. Characterization of the neurobiological alterations that lead to phenotypic heterogeneity in patients with PD has considerably aided the in vivo investigation of aetiology and pathophysiology, and the identification of novel targets for pharmacological or surgical treatments, including cell therapy. Although PD is now considered to be very complex, no neuroimaging modalities are specifically recommended for routine use in clinical practice. However, conventional MRI and dopamine transporter imaging are commonly used as adjuvant tools in the differential diagnosis between PD and nondegenerative causes of parkinsonism. First-line neuroimaging tools that could have an impact on patient prognosis and treatment strategies remain elusive. This Review discusses the lessons learnt from decades of neuroimaging research in PD, and the promising new approaches with potential applicability to clinical practice.
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Affiliation(s)
- Marios Politis
- Neurodegeneration Imaging Group, Department of Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, UK
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Bova J, Sergent A. Chiropractic management of an 81-year-old man with Parkinson disease signs and symptoms. J Chiropr Med 2014; 13:116-20. [PMID: 25685120 PMCID: PMC4322011 DOI: 10.1016/j.jcm.2014.06.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Revised: 01/13/2014] [Accepted: 01/14/2014] [Indexed: 12/26/2022] Open
Abstract
OBJECTIVE The purpose of this case report is to describe the chiropractic management of a patient with Parkinson disease. CLINICAL FEATURES An 81-year-old male with a 12-year history of Parkinson disease sought chiropractic care. He had a stooped posture and a shuffling gait. He was not able to ambulate comfortably without the guidance of his walker. The patient had a resting tremor, most notably in his right hand. Outcome measures were documented using the Parkinson's Disease Questionaire-39 (PDQ-39) and patient subjective reports. INTERVENTION AND OUTCOME The patient was treated with blue-lensed glasses, vibration stimulation therapy, spinal manipulation, and eye-movement exercises. Within the first week of treatment, there was a reduction in symptoms, improvement in ambulation, and tremor. CONCLUSION For this particular patient, the use of alternative treatment procedures appeared to help his Parkinson disease signs and symptoms.
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Affiliation(s)
- Joesph Bova
- Private Practice, Private Practice, Latham NY
| | - Adam Sergent
- Assistant Professor, Faculty Clinician, Palmer College of Chiropractic Florida, Port Orange, FL
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