F J A Meijer1, A van Rumund2, B A C M Fasen3, I Titulaer2, M Aerts2, R Esselink2, B R Bloem2, M M Verbeek4, B Goraj5. 1. From the Departments of Radiology and Nuclear Medicine (F.J.A.M., B.A.C.M.F., B.G.) Anton.Meijer@radboudumc.nl. 2. Department of Neurology (A.v.R., I.T., M.A., R.E., B.R.B., M.M.V.), Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands. 3. From the Departments of Radiology and Nuclear Medicine (F.J.A.M., B.A.C.M.F., B.G.). 4. Laboratory Medicine (M.M.V.) Department of Neurology (A.v.R., I.T., M.A., R.E., B.R.B., M.M.V.), Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen Medical Center, Nijmegen, the Netherlands. 5. From the Departments of Radiology and Nuclear Medicine (F.J.A.M., B.A.C.M.F., B.G.) Department of Diagnostic Imaging (B.G.), Medical Center of Postgraduate Education, Warsaw, Poland.
Abstract
BACKGROUND AND PURPOSE: The differentiation between Parkinson disease and atypical parkinsonian syndromes can be challenging in clinical practice, especially in early disease stages. Brain MR imaging can help to increase certainty about the diagnosis. Our goal was to evaluate the added value of SWI in relation to conventional 3T brain MR imaging for the diagnostic work-up of early-stage parkinsonism. MATERIALS AND METHODS: This was a prospective observational cohort study of 65 patients presenting with parkinsonism but with an uncertain initial clinical diagnosis. At baseline, 3T brain MR imaging with conventional and SWI sequences was performed. After clinical follow-up, probable diagnoses could be made in 56 patients, 38 patients diagnosed with Parkinson disease and 18 patients diagnosed with atypical parkinsonian syndromes, including 12 patients diagnosed with multiple system atrophy-parkinsonian form. In addition, 13 healthy controls were evaluated with SWI. Abnormal findings on conventional brain MR imaging were grouped into disease-specific scores. SWI was analyzed by a region-of-interest method of different brain structures. One-way ANOVA was performed to analyze group differences. Receiver operating characteristic analyses were performed to evaluate the diagnostic accuracy of conventional brain MR imaging separately and combined with SWI. RESULTS: Disease-specific scores of conventional brain MR imaging had a high specificity for atypical parkinsonian syndromes (80%-90%), but sensitivity was limited (50%-80%). The mean SWI signal intensity of the putamen was significantly lower for multiple system atrophy-parkinsonian form than for Parkinson disease and controls (P < .001). The presence of severe dorsal putaminal hypointensity improved the accuracy of brain MR imaging: The area under the curve was increased from 0.75 to 0.83 for identifying multiple system atrophy-parkinsonian form, and it was increased from 0.76 to 0.82 for identifying atypical parkinsonian syndromes as a group. CONCLUSIONS: SWI improves the diagnostic accuracy of 3T brain MR imaging in the work-up of parkinsonism by identifying severe putaminal hypointensity as a sign indicative of multiple system atrophy-parkinsonian form.
BACKGROUND AND PURPOSE: The differentiation between Parkinson disease and atypical parkinsonian syndromes can be challenging in clinical practice, especially in early disease stages. Brain MR imaging can help to increase certainty about the diagnosis. Our goal was to evaluate the added value of SWI in relation to conventional 3T brain MR imaging for the diagnostic work-up of early-stage parkinsonism. MATERIALS AND METHODS: This was a prospective observational cohort study of 65 patients presenting with parkinsonism but with an uncertain initial clinical diagnosis. At baseline, 3T brain MR imaging with conventional and SWI sequences was performed. After clinical follow-up, probable diagnoses could be made in 56 patients, 38 patients diagnosed with Parkinson disease and 18 patients diagnosed with atypical parkinsonian syndromes, including 12 patients diagnosed with multiple system atrophy-parkinsonian form. In addition, 13 healthy controls were evaluated with SWI. Abnormal findings on conventional brain MR imaging were grouped into disease-specific scores. SWI was analyzed by a region-of-interest method of different brain structures. One-way ANOVA was performed to analyze group differences. Receiver operating characteristic analyses were performed to evaluate the diagnostic accuracy of conventional brain MR imaging separately and combined with SWI. RESULTS: Disease-specific scores of conventional brain MR imaging had a high specificity for atypical parkinsonian syndromes (80%-90%), but sensitivity was limited (50%-80%). The mean SWI signal intensity of the putamen was significantly lower for multiple system atrophy-parkinsonian form than for Parkinson disease and controls (P < .001). The presence of severe dorsal putaminal hypointensity improved the accuracy of brain MR imaging: The area under the curve was increased from 0.75 to 0.83 for identifying multiple system atrophy-parkinsonian form, and it was increased from 0.76 to 0.82 for identifying atypical parkinsonian syndromes as a group. CONCLUSIONS: SWI improves the diagnostic accuracy of 3T brain MR imaging in the work-up of parkinsonism by identifying severe putaminal hypointensity as a sign indicative of multiple system atrophy-parkinsonian form.
Authors: Joanna M Wardlaw; Will Brindle; Ana M Casado; Kirsten Shuler; Moira Henderson; Brenda Thomas; Jennifer Macfarlane; Susana Muñoz Maniega; Katherine Lymer; Zoe Morris; Cyril Pernet; William Nailon; Trevor Ahearn; Abdul Nashirudeen Mumuni; Carlos Mugruza; John McLean; Goultchira Chakirova; Yuehui Terry Tao; Johanna Simpson; Andrew C Stanfield; Harriet Johnston; Jehill Parikh; Natalie A Royle; Janet De Wilde; Mark E Bastin; Nick Weir; Andrew Farrall; Maria C Valdes Hernandez Journal: Eur Radiol Date: 2012-06-09 Impact factor: 5.315
Authors: A Berardelli; G K Wenning; A Antonini; D Berg; B R Bloem; V Bonifati; D Brooks; D J Burn; C Colosimo; A Fanciulli; J Ferreira; T Gasser; F Grandas; P Kanovsky; V Kostic; J Kulisevsky; W Oertel; W Poewe; J-P Reese; M Relja; E Ruzicka; A Schrag; K Seppi; P Taba; M Vidailhet Journal: Eur J Neurol Date: 2013-01 Impact factor: 6.089
Authors: I Litvan; Y Agid; D Calne; G Campbell; B Dubois; R C Duvoisin; C G Goetz; L I Golbe; J Grafman; J H Growdon; M Hallett; J Jankovic; N P Quinn; E Tolosa; D S Zee Journal: Neurology Date: 1996-07 Impact factor: 9.910
Authors: J Ding; Y Duan; M Wang; Y Yuan; Z Zhuo; L Gan; Q Song; B Gao; L Yang; H Liu; Y Hou; F Zheng; R Chen; J Wang; L Lin; B Zhang; G Zhang; Y Liu Journal: AJNR Am J Neuroradiol Date: 2022-03-03 Impact factor: 3.825
Authors: Trina Mitchell; Stéphane Lehéricy; Shannon Y Chiu; Antonio P Strafella; A Jon Stoessl; David E Vaillancourt Journal: JAMA Neurol Date: 2021-10-01 Impact factor: 29.907
Authors: I Hwang; C-H Sohn; K M Kang; B S Jeon; H-J Kim; S H Choi; T J Yun; J-H Kim Journal: AJNR Am J Neuroradiol Date: 2015-09-03 Impact factor: 3.825