Hasenfuß, Gerd P.

[["dc.bibliographiccitation.artnumber","e109164"],["dc.bibliographiccitation.issue","10"],["dc.bibliographiccitation.journal","PLoS ONE"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Kowallick, Johannes Tammo"],["dc.contributor.author","Lamata, Pablo"],["dc.contributor.author","Hussain, Shazia T."],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Steinmetz, Michael"],["dc.contributor.author","Sohns, Jan Martin"],["dc.contributor.author","Fasshauer, Martin"],["dc.contributor.author","Staab, Wieland"],["dc.contributor.author","Unterberg-Buchwald, Christina"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2017-09-07T11:45:27Z"],["dc.date.available","2017-09-07T11:45:27Z"],["dc.date.issued","2014"],["dc.description.abstract","Objectives: Cardiovascular magnetic resonance feature tracking (CMR-FT) offers quantification of myocardial deformation from routine cine images. However, data using CMR-FT to quantify left ventricular (LV) torsion and diastolic recoil are not yet available. We therefore sought to evaluate the feasibility and reproducibility of CMR-FT to quantify LV torsion and peak recoil rate using an optimal anatomical approach. Methods: Short-axis cine stacks were acquired at rest and during dobutamine stimulation (10 and 20 mu g.kg(-1).min(-1)) in 10 healthy volunteers. Rotational displacement was analysed for all slices. A complete 3D-LV rotational model was developed using linear interpolation between adjacent slices. Torsion was defined as the difference between apical and basal rotation, divided by slice distance. Depending on the distance between the most apical (defined as 0% LV distance) and basal (defined as 100% LV distance) slices, four different models for the calculation of torsion were examined: Model-1 (25-75%), Model-2 (0-100%), Model-3 (25-100%) and Model-4 (0-75%). Analysis included subendocardial, subepicardial and global torsion and recoil rate (mean of subendocardial and subepicardial values). Results: Quantification of torsion and recoil rate was feasible in all subjects. There was no significant difference between the different models at rest. However, only Model-1 (25-75%) discriminated between rest and stress (Global Torsion: 2.7 +/- 1.5 degrees cm(-1), 3.6 +/- 2.0 degrees cm(-1), 5.1 +/- 2.2 degrees cm(-1), p<0.01; Global Recoil Rate: -30.1 +/- 11.1 degrees cm(-1) s (-1), -469 +/- 15.0 degrees cm (-1) s (-1), -68.9 +/- 32.3 degrees cm(-1) s(-1), p<0.01; for rest, 10 and 20 mu g.kg(-1).min(-1) of dobutamine, respectively). Reproducibility was sufficient for all parameters as determined by Bland-Altman analysis, intraclass correlation coefficients and coefficient of variation. Conclusions: CMR-FT based derivation of myocardial torsion and recoil rate is feasible and reproducible at rest and with dobutamine stress. Using an optimal anatomical approach measuring rotation at 25% and 75% apical and basal LV locations allows effective quantification of torsion and recoil dynamics. Application of these new measures of deformation by CMR-FT should next be explored in disease states."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2014"],["dc.identifier.doi","10.1371/journal.pone.0109164"],["dc.identifier.gro","3142035"],["dc.identifier.isi","000345743700050"],["dc.identifier.pmid","25285656"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/10994"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/3823"],["dc.notes.intern","WoS Import 2017-03-10"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","final"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Public Library Science"],["dc.relation.issn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Quantification of Left Ventricular Torsion and Diastolic Recoil Using Cardiovascular Magnetic Resonance Myocardial Feature Tracking"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","60"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Cardiovascular Magnetic Resonance"],["dc.bibliographiccitation.volume","23"],["dc.contributor.author","Metschies, Georg"],["dc.contributor.author","Billing, Marcus"],["dc.contributor.author","Schmidt-Rimpler, Jonas"],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Gertz, Roman J."],["dc.contributor.author","Lapinskas, Tomas"],["dc.contributor.author","Pieske-Kraigher, Elisabeth"],["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","Kelle, Sebastian"],["dc.contributor.author","Schuster, Andreas"],["dc.contributor.author","Backhaus, Sören J."],["dc.date.accessioned","2021-11-25T11:12:48Z"],["dc.date.available","2021-11-25T11:12:48Z"],["dc.date.issued","2021-05-17"],["dc.date.updated","2021-11-19T12:47:36Z"],["dc.description.abstract","Abstract Background Myocardial deformation analyses using cardiovascular magnetic resonance (CMR) feature tracking (CMR-FT) have incremental value in the assessment of cardiac function beyond volumetric analyses. Since guidelines do not recommend specific imaging parameters, we aimed to define optimal spatial and temporal resolutions for CMR cine images to enable reliable post-processing. Methods Intra- and inter-observer reproducibility was assessed in 12 healthy subjects and 9 heart failure (HF) patients. Cine images were acquired with different temporal (20, 30, 40 and 50 frames/cardiac cycle) and spatial resolutions (high in-plane 1.5 × 1.5 mm through-plane 5 mm, standard 1.8 × 1.8 x 8mm and low 3.0 × 3.0 x 10mm). CMR-FT comprised left ventricular (LV) global and segmental longitudinal/circumferential strain (GLS/GCS) and associated systolic strain rates (SR), and right ventricular (RV) GLS. Results Temporal but not spatial resolution did impact absolute strain and SR. Maximum absolute changes between lowest and highest temporal resolution were as follows: 1.8% and 0.3%/s for LV GLS and SR, 2.5% and 0.6%/s for GCS and SR as well as 1.4% for RV GLS. Changes of strain values occurred comparing 20 and 30 frames/cardiac cycle including LV and RV GLS and GCS (p < 0.001–0.046). In contrast, SR values (LV GLS/GCS SR) changed significantly comparing all successive temporal resolutions (p < 0.001–0.013). LV strain and SR reproducibility was not affected by either temporal or spatial resolution, whilst RV strain variability decreased with augmentation of temporal resolution. Conclusion Temporal but not spatial resolution significantly affects strain and SR in CMR-FT deformation analyses. Strain analyses require lower temporal resolution and 30 frames/cardiac cycle offer consistent strain assessments, whilst SR measurements gain from further increases in temporal resolution."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.citation","Journal of Cardiovascular Magnetic Resonance. 2021 May 17;23(1):60"],["dc.identifier.doi","10.1186/s12968-021-00740-5"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/93537"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-425"],["dc.publisher","BioMed Central"],["dc.relation.eissn","1532-429X"],["dc.relation.orgunit","Klinik für Kardiologie und Pneumologie"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)"],["dc.subject","Myocardial deformation"],["dc.subject","Strain"],["dc.subject","Cardiovascular magnetic resonance"],["dc.subject","Temporal resolution"],["dc.subject","Spatial resolution"],["dc.subject","Reproducibility"],["dc.title","Defining the optimal temporal and spatial resolution for cardiovascular magnetic resonance imaging feature tracking"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["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"]]

[["dc.bibliographiccitation.firstpage","210"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Journal of Clinical Medicine"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Schuster, Andreas"],["dc.contributor.author","Backhaus, Sören J."],["dc.contributor.author","Stiermaier, Thomas"],["dc.contributor.author","Navarra, Jenny-Lou"],["dc.contributor.author","Uhlig, Johannes"],["dc.contributor.author","Rommel, Karl-Philipp"],["dc.contributor.author","Koschalka, Alexander"],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Eitel, Ingo"],["dc.date.accessioned","2020-12-10T18:47:12Z"],["dc.date.available","2020-12-10T18:47:12Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.3390/jcm9010210"],["dc.identifier.eissn","2077-0383"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78679"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.publisher","MDPI"],["dc.relation.eissn","2077-0383"],["dc.rights","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Impact of Right Atrial Physiology on Heart Failure and Adverse Events after Myocardial Infarction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","18"],["dc.bibliographiccitation.journal","Journal of the American Heart Association"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Schuster, Andreas"],["dc.contributor.author","Lange, Torben"],["dc.contributor.author","Backhaus, Sören J."],["dc.contributor.author","Strohmeyer, Carolin"],["dc.contributor.author","Boom, Patricia C."],["dc.contributor.author","Matz, Jonas"],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Steinmetz, Michael"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","de Waha‐Thiele, Suzanne"],["dc.contributor.author","Desch, Steffen"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Stiermaier, Thomas"],["dc.contributor.author","Eitel, Ingo"],["dc.date.accessioned","2021-04-14T08:32:49Z"],["dc.date.available","2021-04-14T08:32:49Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1161/JAHA.120.016612"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/17697"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/84028"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.notes.intern","Merged from goescholar"],["dc.relation.eissn","2047-9980"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Fully Automated Cardiac Assessment for Diagnostic and Prognostic Stratification Following Myocardial Infarction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]