Hasenfuß, Gerd P.

[["dc.bibliographiccitation.journal","International Journal of Cardiology"],["dc.contributor.author","Backhaus, Sören J."],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Stiermaier, Thomas"],["dc.contributor.author","Lange, Torben"],["dc.contributor.author","Koschalka, Alexander"],["dc.contributor.author","Navarra, Jenny-Lou"],["dc.contributor.author","Uhlig, Johannes"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Eitel, Ingo"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2019-08-06T12:07:43Z"],["dc.date.available","2019-08-06T12:07:43Z"],["dc.date.issued","2019"],["dc.description.abstract","Sex-specific outcome data following myocardial infarction (MI) are inconclusive with some evidence suggesting association of female sex and increased major adverse cardiac events (MACE). Since mechanistic principles remain elusive, we aimed to quantify the underlying phenotype using cardiovascular magnetic resonance (CMR) quantitative deformation imaging and tissue characterisation."],["dc.identifier.doi","10.1016/j.ijcard.2019.06.036"],["dc.identifier.pmid","31300172"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/62311"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.relation.eissn","1874-1754"],["dc.relation.issn","0167-5273"],["dc.title","Atrioventricular mechanical coupling and major adverse cardiac events in female patients following acute ST elevation myocardial infarction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["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.firstpage","1262"],["dc.bibliographiccitation.issue","11"],["dc.bibliographiccitation.journal","European Heart Journal - Cardiovascular Imaging"],["dc.bibliographiccitation.lastpage","1270"],["dc.bibliographiccitation.volume","20"],["dc.contributor.author","Schuster, Andreas"],["dc.contributor.author","Backhaus, Sören J"],["dc.contributor.author","Stiermaier, Thomas"],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Stulle, Alina"],["dc.contributor.author","Koschalka, Alexander"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Eitel, Ingo"],["dc.date.accessioned","2020-04-03T13:12:22Z"],["dc.date.available","2020-04-03T13:12:22Z"],["dc.date.issued","2019-11-01"],["dc.description.abstract","Cardiovascular magnetic resonance feature tracking (CMR-FT) global longitudinal strain (GLS) provides incremental prognostic value following acute myocardial infarction (AMI) but requires substantial post-processing. Alternatively, manual global long-axis strain (LAS) can be easily assessed from standard steady state free precession images. We aimed to define the prognostic value of LAS in a large multicentre study in patients following AMI."],["dc.identifier.doi","10.1093/ehjci/jez077"],["dc.identifier.pmid","31329854"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/63616"],["dc.language.iso","en"],["dc.relation.eissn","2047-2412"],["dc.relation.issn","2047-2404"],["dc.relation.issn","2047-2412"],["dc.title","Fast manual long-axis strain assessment provides optimized cardiovascular event prediction following myocardial infarction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["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.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Backhaus, Sören J."],["dc.contributor.author","Aldehayat, Haneen"],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","Evertz, Ruben"],["dc.contributor.author","Lange, Torben"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2022-09-01T09:50:07Z"],["dc.date.available","2022-09-01T09:50:07Z"],["dc.date.issued","2022"],["dc.description.abstract","Abstract\n \n Feasibility of automated volume-derived cardiac functional evaluation has successfully been demonstrated using cardiovascular magnetic resonance (CMR) imaging. Notwithstanding, strain assessment has proven incremental value for cardiovascular risk stratification. Since introduction of deformation imaging to clinical practice has been complicated by time-consuming post-processing, we sought to investigate automation respectively. CMR data (n = 1095 patients) from two prospectively recruited acute myocardial infarction (AMI) populations with ST-elevation (STEMI) (AIDA STEMI n = 759) and non-STEMI (TATORT-NSTEMI n = 336) were analysed fully automated and manually on conventional cine sequences. LV function assessment included global longitudinal, circumferential, and radial strains (GLS/GCS/GRS). Agreements were assessed between automated and manual strain assessments. The former were assessed for major adverse cardiac event (MACE) prediction within 12 months following AMI. Manually and automated derived GLS showed the best and excellent agreement with an intraclass correlation coefficient (ICC) of 0.81. Agreement was good for GCS and poor for GRS. Amongst automated analyses, GLS (HR 1.12, 95% CI 1.08–1.16,\n p\n  < 0.001) and GCS (HR 1.07, 95% CI 1.05–1.10,\n p\n  < 0.001) best predicted MACE with similar diagnostic accuracy compared to manual analyses; area under the curve (AUC) for GLS (auto 0.691 vs. manual 0.693,\n p\n  = 0.801) and GCS (auto 0.668 vs. manual 0.686,\n p\n  = 0.425). Amongst automated functional analyses, GLS was the only independent predictor of MACE in multivariate analyses (HR 1.10, 95% CI 1.04–1.15,\n p\n  < 0.001). Considering high agreement of automated GLS and equally high accuracy for risk prediction compared to the reference standard of manual analyses, automation may improve efficiency and aid in clinical routine implementation.\n \n Trial registration: ClinicalTrials.gov, NCT00712101 and NCT01612312."],["dc.description.sponsorship"," Deutsches Zentrum für Herz-Kreislaufforschung http://dx.doi.org/10.13039/100010447"],["dc.description.sponsorship"," Georg-August-Universität Göttingen 501100003385"],["dc.identifier.doi","10.1038/s41598-022-16228-w"],["dc.identifier.pii","16228"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113627"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-597"],["dc.relation.eissn","2045-2322"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Artificial intelligence fully automated myocardial strain quantification for risk stratification following acute myocardial infarction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1059"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","European Heart Journal - Cardiovascular Imaging"],["dc.bibliographiccitation.lastpage","1069"],["dc.bibliographiccitation.volume","20"],["dc.contributor.author","Backhaus, Sören J"],["dc.contributor.author","Stiermaier, Thomas"],["dc.contributor.author","Lange, Torben"],["dc.contributor.author","Chiribiri, Amedeo"],["dc.contributor.author","Uhlig, Johannes"],["dc.contributor.author","Freund, Anne"],["dc.contributor.author","Kowallick, Johannes T"],["dc.contributor.author","Gertz, Roman J"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Villa, Adriana"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Eitel, Ingo"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2020-12-10T18:18:53Z"],["dc.date.available","2020-12-10T18:18:53Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1093/ehjci/jey219"],["dc.identifier.eissn","2047-2412"],["dc.identifier.issn","2047-2404"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/75107"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Atrial mechanics and their prognostic impact in Takotsubo syndrome: a cardiovascular magnetic resonance imaging study"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","292"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Radiology"],["dc.bibliographiccitation.lastpage","302"],["dc.bibliographiccitation.volume","293"],["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","Lotz, Joachim"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Hasenfuss, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Eitel, Ingo"],["dc.date.accessioned","2020-12-10T18:37:38Z"],["dc.date.available","2020-12-10T18:37:38Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1148/radiol.2019190559"],["dc.identifier.eissn","1527-1315"],["dc.identifier.issn","0033-8419"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/77047"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.title","Left Atrial Function with MRI Enables Prediction of Cardiovascular Events after Myocardial Infarction: Insights from the AIDA STEMI and TATORT NSTEMI Trials"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","989"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Clinical Radiology"],["dc.bibliographiccitation.lastpage","998"],["dc.bibliographiccitation.volume","70"],["dc.contributor.author","Schuster, Andreas"],["dc.contributor.author","Stahnke, V. -C."],["dc.contributor.author","Unterberg-Buchwald, Christina"],["dc.contributor.author","Kowallick, Johannes Tammo"],["dc.contributor.author","Lamata, Pablo"],["dc.contributor.author","Steinmetz, Michael"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Faßhauer, M."],["dc.contributor.author","Staab, Wieland"],["dc.contributor.author","Sohns, Jan Martin"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Ritter, Caroline"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Beerbaum, P."],["dc.contributor.author","Lotz, Joachim"],["dc.date.accessioned","2017-09-07T11:43:34Z"],["dc.date.available","2017-09-07T11:43:34Z"],["dc.date.issued","2015"],["dc.description.abstract","AIM: To assess intervendor agreement of cardiovascular magnetic resonance feature tracking (CMR-FT) and to study the impact of repeated measures on reproducibility. MATERIALS AND METHODS: Ten healthy volunteers underwent cine imaging in short-axis orientation at rest and with dobutamine stimulation (10 and 20 mu g/kg/min). All images were analysed three times using two types of software (TomTec, Unterschleissheim, Germany and Circle, cvi(42), Calgary, Canada) to assess global left ventricular circumferential (Ecc) and radial (Err) strains and torsion. Differences in intra-and interobserver variability within and between software types were assessed based on single and averaged measurements (two and three repetitions with subsequent averaging of results, respectively) as determined by Bland-Altman analysis, intraclass correlation coefficients (ICC), and coefficient of variation (CoV). RESULTS: Myocardial strains and torsion significantly increased on dobutamine stimulation with both types of software (p<0.05). Resting Ecc and torsion as well as Ecc values during dobutamine stimulation were lower measured with Circle (p<0.05). Intra-and interobserver variability between software types was lowest for Ecc (ICC 0.81 [0.63-0.91], 0.87 [0.72-0.94] and CoV 12.47% and 14.3%, respectively) irrespective of the number of analysis repetitions. Err and torsion showed higher variability that markedly improved for torsion with repeated analyses and to a lesser extent for Err. On an intravendor level TomTec showed better reproducibility for Ecc and torsion and Circle for Err. CONCLUSIONS: CMR-FT strain and torsion measurements are subject to considerable intervendor variability, which can be reduced using three analysis repetitions. For both vendors, Ecc qualifies as the most robust parameter with the best agreement, albeit lower Ecc values obtained using Circle, and warrants further investigation of incremental clinical merit. (C) 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved."],["dc.identifier.doi","10.1016/j.crad.2015.05.006"],["dc.identifier.gro","3141835"],["dc.identifier.isi","000361899600012"],["dc.identifier.pmid","26139384"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/1601"],["dc.notes.intern","WoS Import 2017-03-10"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.relation.eissn","1365-229X"],["dc.relation.issn","0009-9260"],["dc.title","Cardiovascular magnetic resonance feature-tracking assessment of myocardial mechanics: Intervendor agreement and considerations regarding reproducibility"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","270"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Clinical Research in Cardiology"],["dc.bibliographiccitation.lastpage","280"],["dc.bibliographiccitation.volume","110"],["dc.contributor.author","Lange, Torben"],["dc.contributor.author","Stiermaier, Thomas"],["dc.contributor.author","Backhaus, Sören J."],["dc.contributor.author","Boom, Patricia C."],["dc.contributor.author","Kowallick, Johannes T."],["dc.contributor.author","de Waha-Thiele, Suzanne"],["dc.contributor.author","Lotz, Joachim"],["dc.contributor.author","Kutty, Shelby"],["dc.contributor.author","Bigalke, Boris"],["dc.contributor.author","Gutberlet, Matthias"],["dc.contributor.author","Feistritzer, Hans-Josef"],["dc.contributor.author","Desch, Steffen"],["dc.contributor.author","Hasenfuß, Gerd"],["dc.contributor.author","Thiele, Holger"],["dc.contributor.author","Eitel, Ingo"],["dc.contributor.author","Schuster, Andreas"],["dc.date.accessioned","2021-04-14T08:32:12Z"],["dc.date.available","2021-04-14T08:32:12Z"],["dc.date.issued","2020"],["dc.identifier.doi","10.1007/s00392-020-01747-1"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/83841"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-399"],["dc.relation.eissn","1861-0692"],["dc.relation.issn","1861-0684"],["dc.title","Functional and prognostic implications of cardiac magnetic resonance feature tracking-derived remote myocardial strain analyses in patients following acute myocardial infarction"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["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"]]