Kowallick, Johannes Tammo

[["dc.bibliographiccitation.artnumber","e0193746"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","PLOS ONE"],["dc.bibliographiccitation.volume","13"],["dc.contributor.author","Gertz, Roman Johannes"],["dc.contributor.author","Lange, Torben"],["dc.contributor.author","Kowallick, Johannes Tammo"],["dc.contributor.author","Backhaus, Sören Jan"],["dc.contributor.author","Steinmetz, Michael"],["dc.contributor.author","Staab, Wieland"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2019-07-09T11:45:26Z"],["dc.date.available","2019-07-09T11:45:26Z"],["dc.date.issued","2018"],["dc.description.abstract","AIM: Since cardiovascular magnetic resonance feature-tracking (CMR-FT) has been demonstrated to be of incremental clinical merit we investigated the interchangeability of global left and right ventricular strain parameters between different CMR-FT software solutions. MATERIAL AND METHODS: CMR-cine images of 10 patients without significant reduction in LVEF and RVEF and 10 patients with a significantly impaired systolic function were analyzed using two different types of FT-software (TomTec, Germany; QStrain, Netherlands). Global longitudinal strains (LV GLS, RV GLS), global left ventricular circumferential (GCS) and radial strains (GRS) were assessed. Differences in intra- and inter-observer variability within and between software types based on single and up to three repeated and subsequently averaged measurements were evaluated. RESULTS: Inter-vendor agreement was highest for GCS followed by LV GLS. GRS and RV GLS showed lower inter-vendor agreement. Variability was consistently higher in healthy volunteers as compared to the patient group. Intra-vendor reproducibility was excellent for GCS, LV GLS and RV GLS, but lower for GRS. The impact of repeated measurements was most pronounced for GRS and RV GLS on an intra-vendor level. CONCLUSION: Cardiac pathology has no influence on CMR-FT reproducibility. LV GLS and GCS qualify as the most robust parameters within and between individual software types. Since both parameters can be interchangeably assessed with different software solutions they may enter the clinical arena for optimized diagnostic and prognostic evaluation of cardiovascular morbidity and mortality in various pathologies."],["dc.identifier.doi","10.1371/journal.pone.0193746"],["dc.identifier.pmid","29538467"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15206"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59229"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.haserratum","/handle/2/110092"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Inter-vendor reproducibility of left and right ventricular cardiovascular magnetic resonance myocardial feature-tracking"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0210127"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","PLOS ONE"],["dc.bibliographiccitation.volume","14"],["dc.contributor.author","Backhaus, Sören J."],["dc.contributor.author","Metschies, Georg"],["dc.contributor.author","Billing, Marcus"],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Gertz, Roman J."],["dc.contributor.author","Lapinskas, Tomas"],["dc.contributor.author","Pieske, Burkert"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Beerbaum, Philipp"],["dc.contributor.author","Kelle, Sebastian"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2019-07-09T11:50:08Z"],["dc.date.available","2019-07-09T11:50:08Z"],["dc.date.issued","2019"],["dc.description.abstract","BACKGROUND: Cardiovascular magnetic resonance feature tracking (CMR-FT) is increasingly used for myocardial deformation assessment including ventricular strain, showing prognostic value beyond established risk markers if used in experienced centres. Little is known about the impact of appropriate training on CMR-FT performance. Consequently, this study aimed to evaluate the impact of training on observer variance using different commercially available CMR-FT software. METHODS: Intra- and inter-observer reproducibility was assessed prior to and after dedicated one-hour observer training. Employed FT software included 3 different commercially available platforms (TomTec, Medis, Circle). Left (LV) and right (RV) ventricular global longitudinal as well as LV circumferential and radial strains (GLS, GCS and GRS) were studied in 12 heart failure patients and 12 healthy volunteers. RESULTS: Training improved intra- and inter-observer reproducibility. GCS and LV GLS showed the highest reproducibility before (ICC >0.86 and >0.81) and after training (ICC >0.91 and >0.92). RV GLS and GRS were more susceptible to tracking inaccuracies and reproducibility was lower. Inter-observer reproducibility was lower than intra-observer reproducibility prior to training with more pronounced improvements after training. Before training, LV strain reproducibility was lower in healthy volunteers as compared to patients with no differences after training. Whilst LV strain reproducibility was sufficient within individual software solutions inter-software comparisons revealed considerable software related variance. CONCLUSION: Observer experience is an important source of variance in CMR-FT derived strain assessment. Dedicated observer training significantly improves reproducibility with most profound benefits in states of high myocardial contractility and potential to facilitate widespread clinical implementation due to optimized robustness and diagnostic performance."],["dc.identifier.doi","10.1371/journal.pone.0210127"],["dc.identifier.pmid","30682045"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15866"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59708"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.subject.ddc","610"],["dc.title","Cardiovascular magnetic resonance imaging feature tracking: Impact of training on observer performance and reproducibility"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]