Manual MRI morphometry in Parkinsonian syndromes

Möller, Leona; Kassubek, Jan; Südmeyer, Martin; Hilker, Rüdiger; Hattingen, Elke; Egger, Karl; Amtage, Florian; Pinkhardt, Elmar H.; Respondek, Gesine; Stamelou, María; Möller, Franz; Schnitzler, Alfons; Oertel, Wolfgang H.; Knake, Susanne; Huppertz, Hans‐Jürgen; Höglinger, Günter U.

doi:10.1002/mds.26921

Cited by 75 publications

(113 citation statements)

References 22 publications

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“…Voxel-based morphometry (VBM), an operator-independent automated method, can detect focal volume differences between 2 or more groups based on study-specific templates (Ashburner et al, 2000). Studies using this approach confirmed previous ROI-based volumetric studies suggesting basal ganglia, infratentorial as well as cortical volume loss in MSA patients (Minnerop et al, 2007; Moller et al, 2017; Specht et al, 2003; Tzarouchi et al, 2010). Moreover, specific longitudinal changes in MSA (early atrophy of basal ganglia followed by late cortical atrophy) have been identified with this technique (Brenneis et al, 2007).…”

Section: Brain and Cardiac Neuroimagingsupporting

confidence: 83%

Diagnosis of multiple system atrophy

Palma

Norcliffe‐Kaufmann

Kaufmann

2018

Autonomic Neuroscience

126

114

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Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs.

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Section: Brain and Cardiac Neuroimagingsupporting

confidence: 83%

Diagnosis of multiple system atrophy

Palma

Norcliffe‐Kaufmann

Kaufmann

2018

Autonomic Neuroscience

126

114

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“…Measurements of these regions, and ratios thereof (e.g. midbrain-pons ratio, MR-Parkinson-index) proofed therefore very helpful as markers for the cross-sectional differential diagnosis of Parkinson syndromes, 24,25 however, only limited data addressed the utility of these ratios as progression measurement. 8 …”

Section: Discussionmentioning

confidence: 99%

“…In the midsagittal planes, several previous studies suggested the midbrain area and midbrain tegmentum area as reliable markers of atrophy in PSP. 24,25 For comparison, the midsagittal areas of other structures (corpus callosum, pons and pars basilaris of pons, medulla oblongata, cerebellar vermis) have also been determined. All cross-sectional results of ABV were ICV-corrected and normalized to the mean ICV of the whole study population.…”

Section: Methodsmentioning

confidence: 99%

Longitudinal magnetic resonance imaging in progressive supranuclear palsy: A new combined score for clinical trials

et al. 2017

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Background Two recent randomized, placebo-controlled phase II/III trials (clinicaltrials.gov: NCT01110720, NCT01049399) of davunetide and tideglusib in progressive supranuclear palsy (PSP) generated prospective, 1-year longitudinal datasets of high-resolution T1-weighted 3D MRI. Objectives Develop a quantitative MRI disease progression measurement for clinical trials. Methods We performed a fully automated quantitative MRI analysis employing atlas-based volumetry and provide sample size calculations based on data collected in N=99 PSP patients, assigned to placebo in these trials. Based on individual volumes of N=44 brain compartments and structures at baseline and 52 weeks follow-up, means and standard deviations of annualized percentage volume changes were used to estimate standardized effect sizes and the required sample sizes per group for future two-armed, placebo-controlled therapeutic trials. Results The highest standardized effect sizes were found for midbrain, frontal lobes, and third ventricle. Using the annualized percentage volume change of these structures to detect a 50% change in the 1-year progression (80% power, significance level 5%) required lower numbers of patients per group [third ventricle, N=32; midbrain, N=37; frontal lobe, N= 43] than the best clinical scale (PSP rating scale total score, N=58). A combination of volume changes in these three structures reduced the number of required patients to only N=20 and correlated best with the progression in the clinical scales. Conclusions We propose the 1-year change in the volumes of third ventricle, midbrain, and frontal lobe as combined imaging read-out for clinical trials in PSP, requiring the least number of patients for detecting efficacy to reduce brain atrophy.

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“…HC)m d /p d -ratioSe 86 (PSP)Sp 100 (vs. PD, MSA. HC)Kim et al (2015)PD 82/PSP 293.0 Tm d d and m a /p a ratio discriminated PSP from PD with similar discriminatory powerMRPI showed lower discriminatory powerm d Se 86 (PSP)Sp 54AUC = 0.76m a /p a ratio (Cosottini method) (Cosottini et al 2007)Se 62 (PSP)Sp 76AUC = 0.75m a /p a ratio (Oba method) (Oba et al 2005)Se 72 (PSP)Sp 64AUC = 0.75MRPISe 93 (PSP-RS)Sp 43AUC = 0.69Moller et al (2017)PD 204/PSP 106/MSA-C 21/MSA-P 60/HC 731.5 and 3.0 T↓ m a in PSP vs. all other groups↓ p a in MSA-C, MSA-P, and PSP vs. PD and HC.↓ m a /p a in PSP vs. all other groups↑ m a /p a in MSA-C and MSA-P vs. PD and PSPm a AUC = 0.90 (PSP vs. PD)Se 75, Sp 82, AUC = 0.85 (PSP vs. MSA-P)m a /p a Se 76, Sp 80, AUC = 0.84 (PSP vs. PD)Se 76, Sp 80, AUC = 0.89 (PSP vs. MSA-P)MRPISe 64, Sp 64, AUC = 0.75 (PSP vs. PD)Se 73, Sp 60, AUC = 0.80 (PSP vs. MSA-P)Automated methods for quantitative MRI analysis Huppertz et al (2016)PD 204, PSP 106, MSA-C 21, MSA-P 601.5 and 3.0 TFully automated brain volumetry combined with SVM classification allowed for automated differentiation on single-patient levelVolume changes of midbrain, basal ganglia, and cerebellar peduncles had the largest relevance for classificationAtlas-based voxel-based volumetry combined with SVM classificationClassifications between the groups resulted in balanced diagnostic accuracies ≥80% Scherfler et al (2016)PSP 30/MSA 40/PD 40 of whom 40 presented with a clinically uncertain parkinsonism Data were split into a training ( n = 72) and a test set ( n = 38)1.5 TVolume segmentation of subcortical brain regions followed by a machine-learning method-derived classification algorithm (i.e. C4.5 decision tree algorithm)Most discriminative regions include the volume of the midbrain, followed by cerebellar GM and putamenDiagnostic accuracy of the fully automated method for quantitative MRI analysis was 97% for the separation of PD vs. MSA or PSP, by contrast to the clinical diagnostic accuracy of 63% based on validated clinical consensus criteria at the time of MRI…”

Section: Exclusion Of Alternative Diagnosesmentioning

confidence: 99%

Magnetic resonance imaging for the diagnosis of Parkinson’s disease

et al. 2017

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The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson’s disease. This includes not only the exclusion of alternative diagnoses for Parkinson’s disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson’s disease.

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Manual MRI morphometry in Parkinsonian syndromes

Abstract: The midsagittal midbrain area most reliably identified PSP, the midsagittal pons area MSA-cerebellar. The midbrain/pons area ratio differentiated MSA-cerebellar and PSP better than the magnetic resonance-Parkinson index. © 2017 International Parkinson and Movement Disorder Society.

Cited by 75 publications

References 22 publications

Diagnosis of multiple system atrophy

Diagnosis of multiple system atrophy

Longitudinal magnetic resonance imaging in progressive supranuclear palsy: A new combined score for clinical trials

Magnetic resonance imaging for the diagnosis of Parkinson’s disease

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