BACKGROUND AND PURPOSE: The degree to which MR imaging is useful in the diagnosis of MS is predicated on standardized and reliable evaluation of MR imaging parameters. We aimed to devise items for an MR imaging scoring tool that would have high inter-rater agreement and would be straightforward to apply. MATERIALS AND METHODS: On the basis of a literature search and consensus of an expert panel, we identified 48 parameters that describe acute CNS demyelination, predict MS diagnosis, or characterize demyelinating disorder mimics. MR images of children with clinically confirmed MS, monophasic ADEM, and angiography-negative biopsy-positive small-vessel primary angiitis of the CNS were scored by 2 neuroradiologists independently, using the preliminary 48-parameter tool. Parameters with Cohen κ ≥ 0.6 and deemed important in predicting diagnosis were retained. Parameters not visualized on routine clinical imaging or not important in differentiating MS, ADEM, and SV-cPACNS were discarded. RESULTS: Of 65 eligible patients, 55 children were enrolled (16 with monophasic ADEM, 27 with MS, 12 with SV-cPACNS); 10 were excluded (6 had hard-copy films, 4 did not meet MR imaging quality requirements). Of the 48 parameters, 16 were retained in the final scoring tool. The remaining 28 parameters were discarded: 4 had κ < 0.6 and were not deemed useful in predicting diagnosis; 9 were not visible on routinely acquired clinical images; and 15 had inter-rater agreement ≥0.6 but were not useful in differentiating monophasic ADEM, MS, and SV-cPACNS. CONCLUSIONS: We propose a 16-parameter MR imaging scoring tool that is straightforward to apply in the clinical setting and demonstrates high inter-rater agreement.
BACKGROUND AND PURPOSE: The degree to which MR imaging is useful in the diagnosis of MS is predicated on standardized and reliable evaluation of MR imaging parameters. We aimed to devise items for an MR imaging scoring tool that would have high inter-rater agreement and would be straightforward to apply. MATERIALS AND METHODS: On the basis of a literature search and consensus of an expert panel, we identified 48 parameters that describe acute CNS demyelination, predict MS diagnosis, or characterize demyelinating disorder mimics. MR images of children with clinically confirmed MS, monophasic ADEM, and angiography-negative biopsy-positive small-vessel primary angiitis of the CNS were scored by 2 neuroradiologists independently, using the preliminary 48-parameter tool. Parameters with Cohen κ ≥ 0.6 and deemed important in predicting diagnosis were retained. Parameters not visualized on routine clinical imaging or not important in differentiating MS, ADEM, and SV-cPACNS were discarded. RESULTS: Of 65 eligible patients, 55 children were enrolled (16 with monophasic ADEM, 27 with MS, 12 with SV-cPACNS); 10 were excluded (6 had hard-copy films, 4 did not meet MR imaging quality requirements). Of the 48 parameters, 16 were retained in the final scoring tool. The remaining 28 parameters were discarded: 4 had κ < 0.6 and were not deemed useful in predicting diagnosis; 9 were not visible on routinely acquired clinical images; and 15 had inter-rater agreement ≥0.6 but were not useful in differentiating monophasic ADEM, MS, and SV-cPACNS. CONCLUSIONS: We propose a 16-parameter MR imaging scoring tool that is straightforward to apply in the clinical setting and demonstrates high inter-rater agreement.
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Authors: Matthias Baumann; Astrid Grams; Tanja Djurdjevic; Eva-Maria Wendel; Christian Lechner; Bettina Behring; Astrid Blaschek; Katharina Diepold; Astrid Eisenkölbl; Joel Fluss; Michael Karenfort; Johannes Koch; Bahadir Konuşkan; Steffen Leiz; Andreas Merkenschlager; Daniela Pohl; Mareike Schimmel; Charlotte Thiels; Barbara Kornek; Kathrin Schanda; Markus Reindl; Kevin Rostásy Journal: J Neurol Date: 2018-02-08 Impact factor: 4.849
Authors: Andreas Wegener-Panzer; Robert Cleaveland; Eva-Maria Wendel; Matthias Baumann; Annikki Bertolini; Martin Häusler; Ellen Knierim; Edith Reiter-Fink; Markus Breu; Özcan Sönmez; Adela Della Marina; Renate Peters; Christian Lechner; Martin Piepkorn; Claudia Roll; Romana Höftberger; Frank Leypoldt; Markus Reindl; Kevin Rostásy Journal: Neurol Neuroimmunol Neuroinflamm Date: 2020-05-01