2019
DOI: 10.3174/ajnr.a6107
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Improving Detection of Multiple Sclerosis Lesions in the Posterior Fossa Using an Optimized 3D-FLAIR Sequence at 3T

Abstract: BACKGROUND AND PURPOSE: There is no consensus regarding the best MR imaging sequence for detecting MS lesions. The aim of our study was to assess the diagnostic value of optimized 3D-FLAIR in the detection of infratentorial MS lesions compared with an axial T2-weighted imaging, a 3D-FLAIR with factory settings, and a 3D double inversion recovery sequence. MATERIALS AND METHODS: In this prospective study, 27 patients with confirmed MS were included. Two radiologists blinded to clinical data independently read t… Show more

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Cited by 9 publications
(6 citation statements)
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“…Automated lesion segmentation tools that require no or minimal training data are publicly available, including the LST, 3 LesionTOADS (https://github.com/sergivalverde/lesiontoads), 16,21 SALEM Lesion Segmentation, 22 and Automated Statistical Interference for Segmentation. 23 We chose to use LST with the lesion probability algorithm (LST-lesion prediction algorithm) 2 because it has high accuracy in automatically segmenting MS lesions compared with manual segmentation 7 and requires only FLAIR images as input. 2,7 Here, we found comparable volumes and numbers of white matter lesions as segmented by LST on ultrafast Wave-FLAIR images compared with standard FLAIR, despite the slightly greater image noise observed in the Wave-FLAIR images.…”
Section: Discussionmentioning
confidence: 99%
“…Automated lesion segmentation tools that require no or minimal training data are publicly available, including the LST, 3 LesionTOADS (https://github.com/sergivalverde/lesiontoads), 16,21 SALEM Lesion Segmentation, 22 and Automated Statistical Interference for Segmentation. 23 We chose to use LST with the lesion probability algorithm (LST-lesion prediction algorithm) 2 because it has high accuracy in automatically segmenting MS lesions compared with manual segmentation 7 and requires only FLAIR images as input. 2,7 Here, we found comparable volumes and numbers of white matter lesions as segmented by LST on ultrafast Wave-FLAIR images compared with standard FLAIR, despite the slightly greater image noise observed in the Wave-FLAIR images.…”
Section: Discussionmentioning
confidence: 99%
“…Als typisches klinisches Anwendungsfeld für 3 D FLAIR ist die Multiple Sklerose (MS) aufgrund von Vorteilen in der Detektion und Kontrolle von Läsionen [38][39][40] hervorzuheben. Neben guter Vergleichbarkeit im Verlauf erübrigen sich durch eine 3 D FLAIR im Regelfall zusätzliche Sequenzen zur Detektion infratentorieller Läsionen [38,39,[41][42][43]. Auch die Einordnung juxtakortikaler Läsionen gelingt eindeutiger als mit 2D-Techniken [39], da die durch die größere Schichtdicke und Schichtlücken bei 2D-Bildgebung auftretenden Partialvolumeneffekte reduziert werden.…”
Section: Gehirnunclassified
“…Multiple sclerosis (MS) stands out as a typical clinical application field for 3D-FLAIR due to advantages in lesion detection and monitoring [38][39][40]. In addition to good comparability over time, a 3 D FLAIR usually eliminates the need for additional sequences to detect infratentorial lesions [38,39,[41][42][43]. The classification of juxtacortical lesions likewise succeeds more clearly than with 2 D techniques [39], since the partial volume effects that occur due to the greater slice thickness and slice gaps in 2 D imaging are reduced.…”
Section: Brainmentioning
confidence: 99%
“…Ursprünglich war vielfach das Signal-Rausch-Verhältnis (SNR) bestimmend für die Voreinstellungen. Während beispielsweise eine Sequenz mit längerer Repetitionszeit (TR) aufgrund der dabei erforderlichen weiteren Einstellungsanpassungen typischerweise zu einer Verminderung des SNR führt, nimmt dagegen in einem bestimmten Rahmen zunächst das CNR für Läsionen zu [14,15]. Daher fordern beispielsweise Protokollempfehlungen für Gliome [4] eine TR von 6000 bis 10 000 ms. Diese ist bei älteren Implementationen zum Teil nicht mit akzeptabler Messzeit vereinbar.…”
Section: Praktische Hinweise Zur Anwendungunclassified