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The International Journal of Cardiovascular Imaging
Published in: The International Journal of Cardiovascular Imaging 6/2017

Open Access 01-06-2017 | Editorial

Cardiovascular imaging 2016 in the International Journal of Cardiovascular Imaging

Authors: Johan H. C. Reiber, Johan De Sutter, Paul Schoenhagen, Arthur E. Stillman, Nico R. L. Vande Veire

Published in: The International Journal of Cardiovascular Imaging | Issue 6/2017

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Excerpt

An overview of the most relevant papers in the International Journal of Cardiovascular Imaging over the year 2016 for the different modalities. Relatively few manuscripts in the field of X-ray imaging were published in 2016. The far majorities were in MSCT, MRI and echocardiography, followed by nuclear cardiology and intravascular imaging, of which the last one is not included in this overview. …
Literature
1.
He B, Ding S, Qiao Z, Gao L, Wang W, Ge H, Shen X, Pu J (2016) Influence of microvascular dysfunction on regional myocardial deformation post-acute myocardial infraction: insights from a novel angiographic index for assessing myocardial tissue-level reperfusion. Int J Cardiovasc Imaging 32:711–719CrossRefPubMed
2.
Chen D, Wei H, Tang J, Liu L, Wu S, Lin C, Zhang Q, Liang Y (2016) Chen s a randomized comparison of fluoroscopic techniques for implanting pacemaker lead on the right ventricular outflow tract septum. Int J Cardiovasc Imaging 32:721–728CrossRefPubMedPubMedCentral
3.
Starek Z, Lehar F, Jez J, Wolf J, Kulik T, Zbankova A, Novak M (2016) Periprocedural 3D imaging of the left atrium and esophagus: comparison of different protocols of 3D rotational angiography of the left atrium and esophagus in group of 547 consecutive patients undergoing catheter ablation of the complex atrial arrhythmias. Int J Cardiovasc Imaging 32:1011–1019CrossRefPubMed
4.
Rodriguez-Olivares R, El Faquir N, Rahhab Z, Maugenest A-M, Mieghem NM van, Schultz C, Lauritsch G, Jaegere PPT de (2016) Determinants of image quality of rotational angiography for on-line assessment of frame geometry after transcatheter aortic valve implantation. Int J Cardiovasc Imaging 32:1021–1029CrossRefPubMedPubMedCentral
5.
Guler A, Guler Y, Acar E, Aung SM, Efe SC, Kilicgedik A, Karabay CY, Barutcu S, Tigen MK, Pala S, Izgi A, Esen AM, Kirma C (2016) Clinical, angiographic and procedural characteristics of longitudinal stent deformation. Int J Cardiovasc Imaging 32:1163–1170CrossRefPubMed
6.
Timmins LH, Suo J, Eshtehardi P, Molony DS, McDaniel MC, Oshinski JN, Giddens DP, Samady H (2016) Comparison of angiographic and IVUS derived coronary geometric reconstructions for evaluation of the association of hemodynamics with coronary artery disease progression. Int J Cardiovasc Imaging 32:1327–1336CrossRefPubMed
7.
Donmez E, Koc M, Seker T, Icen YK, Cayli M (2016) The assessment of non culprit coronary artery lesions in patients with ST segment elevated myocardial infraction and multivessel disease by control angiography with quantitative coronary angiography. Int J Cardiovasc Imaging 32:1471–1476CrossRefPubMed
8.
De Lorenzo A, Peclat T, Amaral AC, Lima RS (2016) Prognostic evaluation in obese patients using a dedicated multipinhole cadmium-zinc telluride SPECT camera. Int J Cardiovasc Imaging 32:355–361CrossRefPubMed
9.
Kincl V, Kaminek M, Vasina J, Panovsky R, Havel M (2016) Feasibility of ultra low-dose thallium stress-redistribution protocol including prone imaging in obese patients using CZT camera. Int J Cardiovasc Imaging 32:1463–1469CrossRefPubMed
10.
Liu J, Kerwin WS, Caldwell J, Ferguson MS, Hippe DS, Alessio AM, Martinez-Malo V, Pimentel K, Miyaoka R, Kohler TR, Hatsukami TS, Yuan C (2016) High resoluation FDG-micro PET of carotid atherosclerosis: plaque components underlying enhanced FDG uptake. Int J Cardiovasc Imaging 32:145–152CrossRefPubMed
11.
Tavares A, Peclat T, Lima RS (2016) Prevalance and predictors of left intraventricular dyssynchrony determined by phase analysis in patients undergoing gated SPECT myocardial perfusion imaging. Int J Cardiovasc Imaging 32:845–852CrossRefPubMed
12.
Fagman E, van Essen M, Lindqvist JF, Snygg-Martin U, Bech-Hanssen O, Svensson G (2016) (18)F-FDG PET/CT in the diagnosis of prosthetic valve endocarditis Int J Cardiovasc Imaging 32:679–686
13.
van Dalen et al (2016) A simple, fast and reproducible echocardiographic approach to grade left ventricular diastolic function. Int J Cardiovasc Imaging 32: 743.
14.
Hedberg P et al (2016) Left atrial minimum volume is more strongly associated with N-terminal pro-B-type natriuretic peptide than the left atrial maximum volume in a community-based sample. Int J Cardiovasc Imaging 32: 417.CrossRefPubMed
15.
de Groot- de Laat et al (2016) The role of experience in echocardiographic identification of location and extent of mitral valve prolapse with 2D and 3D echocardiography. Int J Cardiovasc Imaging 32:1171–1177CrossRef
16.
Abdelghani M et al (2016) A granular approach to improve reproducibility of the echocardiographic assessment of paravalvular regurgitation after TAVI. Int J Cardiovasc Imaging 32: 1519.CrossRefPubMedPubMedCentral
17.
Menting et al (2016) Quantitative assessment of systolic left ventricular function with speckle-tracking echocardiography in adult patients with repaired aortic coarctation. Int J Cardiovasc Imaging 32:777–787
18.
Oxborough D et al (2016) Left and right ventricular longitudinal strain-volume/area relationships in elite athletes. Int J Cardiovasc Imaging 32:1199–1211CrossRefPubMed
19.
Schinkel AF et al (2016) Contrast-enhanced ultrasound: clinical applications in patients with atherosclerosis. Int J Cardiovasc Imaging 32: 35CrossRefPubMed
20.
21.
22.
Corona-Villalobos CP, Sorensen LL, Pozios I et al (2016) Left ventricular wall thickness in patients with hypertrophic cardiomyopathy: a comparison between cardiac magnetic resonance imaging and echocardiography. Int J Cardiovasc Imaging 32:945–954. doi:10.​1007/​s10554-016-0858-4 CrossRefPubMed
23.
24.
Wu L-M, Chen B-H, Yao Q-Y et al (2016) Quantitative diffusion-weighted magnetic resonance imaging in the assessment of myocardial fibrosis in hypertrophic cardiomyopathy compared with T1 mapping. Int J Cardiovasc Imaging 32:1289–1297. doi:10.​1007/​s10554-016-0909-x CrossRefPubMed
25.
Yune S, Choi D-C, Lee B-J et al (2016) Detecting cardiac involvement with magnetic resonance in patients with active eosinophilic granulomatosis with polyangiitis. Int J Cardiovasc Imaging 32(Suppl 1):155–162. doi:10.​1007/​s10554-016-0843-y CrossRefPubMed
26.
Rutz T, Piccini D, Coppo S et al (2016) Improved border sharpness of post-infarct scar by a novel self-navigated free-breathing high-resolution 3D whole-heart inversion recovery magnetic resonance approach. Int J Cardiovasc Imaging 32:1735–1744. doi:10.​1007/​s10554-016-0963-4 CrossRefPubMed
27.
Nham E, Kim SM, Lee S-C et al (2016) Association of cardiovascular disease risk factors with left ventricular mass, biventricular function, and the presence of silent myocardial infarction on cardiac MRI in an asymptomatic population. Int J Cardiovasc Imaging 32(Suppl 1):173–181. doi:10.​1007/​s10554-016-0885-1 CrossRefPubMed
28.
van Slochteren FJ, van Es R, Gyöngyösi M et al (2016) Three dimensional fusion of electromechanical mapping and magnetic resonance imaging for real-time navigation of intramyocardial cell injections in a porcine model of chronic myocardial infarction. Int J Cardiovasc Imaging 32:833–843. doi:10.​1007/​s10554-016-0852-x CrossRefPubMedPubMedCentral
29.
van den Bosch H, Westenberg J, Setz-Pels W et al (2016) Prognostic value of cardiovascular MR imaging biomarkers on outcome in peripheral arterial disease: a 6-year follow-up pilot study. Int J Cardiovasc Imaging 32:1281–1288. doi:10.​1007/​s10554-016-0908-y CrossRefPubMed
30.
Gitsioudis G, Fortner P, Stuber M et al (2016) Off-resonance magnetic resonance angiography improves visualization of in-stent lumen in peripheral nitinol stents compared to conventional T1-weighted acquisitions: an in vitro comparison study. Int J Cardiovasc Imaging 32:1645–1655. doi:10.​1007/​s10554-016-0955-4 CrossRefPubMed
31.
32.
Karp G, Wolak A, Baumfeld Y et al (2016) Assessment of aortic stiffness among patients with systemic lupus erythematosus and rheumatoid arthritis by magnetic resonance imaging. Int J Cardiovasc Imaging 32:935–944. doi:10.​1007/​s10554-016-0851-y CrossRefPubMed
33.
Faletti R, Gatti M, Salizzoni S et al (2016) Cardiovascular magnetic resonance as a reliable alternative to cardiovascular computed tomography and transesophageal echocardiography for aortic annulus valve sizing. Int J Cardiovasc Imaging 32:1255–1263. doi:10.​1007/​s10554-016-0899-8 CrossRefPubMed
34.
Nadjiri J, Nieberler H, Hendrich E et al (2016) Prognostic value of T1-mapping in TAVR patients: extra-cellular volume as a possible predictor for peri- and post-TAVR adverse events. Int J Cardiovasc Imaging 32:1625–1633. doi:10.​1007/​s10554-016-0948-3 CrossRefPubMed
35.
36.
37.
38.
39.
40.
André F, Stock FT, Riffel J et al (2016) Incremental value of cardiac deformation analysis in acute myocarditis: a cardiovascular magnetic resonance imaging study. Int J Cardiovasc Imaging 32:1093–1101. doi:10.​1007/​s10554-016-0878-0 CrossRefPubMed
41.
42.
43.
Hwang SH, Oh Y-W, Kim M-N et al (2016) Relationship between left atrial appendage emptying and left atrial function using cardiac magnetic resonance in patients with atrial fibrillation: comparison with transesophageal echocardiography. Int J Cardiovasc Imaging 32(Suppl 1):163–171. doi:10.​1007/​s10554-016-0893-1 CrossRefPubMed
44.
45.
46.
47.
48.
Tandon A, Byrne N, Nieves Velasco Forte M de L, et al (2016) Use of a semi-automated cardiac segmentation tool improves reproducibility and speed of segmentation of contaminated right heart magnetic resonance angiography. Int J Cardiovasc Imaging 32:1273–1279. doi:10.1007/s10554-016-0906-0
49.
Nyns ECA, Dragulescu A, Yoo S-J, Grosse-Wortmann L (2016) Evaluation of knowledge-based reconstruction for magnetic resonance volumetry of the right ventricle after arterial switch operation for dextro-transposition of the great arteries. Int J Cardiovasc Imaging 32:1415–1423. doi:10.​1007/​s10554-016-0921-1 CrossRefPubMed
50.
Ghelani SJ (2016) Echocardiography and magnetic resonance imaging based strain analysis of functional single ventricles: a study of intra-and inter-modality reproducibility. Int J Cardiovasc Imaging. doi:10.​1007/​s10554-016-0882-4 PubMed
51.
Messenger B, Li D, Nasir K, Carr JJ, Blankstein R, Budoff MJ (2016) Coronary calcium scans and radiation exposure in the multi-ethnic study of atherosclerosis. Int J Cardiovasc Imaging 32(3):525–529CrossRefPubMed
52.
Szilveszter B, Elzomor H, Károlyi M, Kolossváry M, Raaijmakers R, Benke K, Celeng C, Bartykowszki A, Bagyura Z, Lux Á, Merkely B, Maurovich-Horvat P (2016) The effect of iterative model reconstruction on coronary artery calcium quantification. Int J Cardiovasc Imaging 32(1):153–160CrossRefPubMed
53.
Petisco AC, Assef JE, de Jesus CA, Saleh MH, Barbosa JE, Costa de Souza Le Bihan D, Pinto IM, Rolim Fernandes Fontes Pedra S, Barretto RB, Sousa AG (2016) High prevalence of subclinical atherosclerosis in Brazilian postmenopausal women with low and intermediate risk by Framingham score. Int J Cardiovasc Imaging
54.
Jang SY, Kim SM, Sung J, Cho SJ, Choe YH (2016) Coronary artery calcium scores and cardiovascular risk factors in 31,545 asymptomatic Korean adults. Int J Cardiovasc Imaging 32(Suppl 1):139–145CrossRefPubMed
55.
Liyanage L, Lee NJ, Cook T, Herrmann HC, Jagasia D, Litt H, Han Y (2016) The impact of gender on cardiovascular system calcification in very elderly patients with severe aortic stenosis. Int J Cardiovasc Imaging 32(1):173–179CrossRefPubMed
56.
Tavares CA, Rassi CH, Fahel MG, Wajchenberg BL, Rochitte CE, Lerario AC (2016) Relationship between glycemic control and coronary artery disease severity, prevalence and plaque characteristics by computed tomography coronary angiography in asymptomatic type 2 diabetic patients. Int J Cardiovasc Imaging 32(10):1577–1585CrossRefPubMed
57.
Tomizawa N, Inoh S, Nojo T, Nakamura S (2016) The association of hemoglobin A1c and high risk plaque and plaque extent assessed by coronary computed tomography angiography. Int J Cardiovasc Imaging 32(3):493–500CrossRefPubMed
58.
Nadjiri J, Hausleiter J, Deseive S, Will A, Hendrich E, Martinoff S, Hadamitzky M (2016) Prognostic value of coronary CT angiography in diabetic patients: a 5-year follow up study. Int J Cardiovasc Imaging 32(3):483–491CrossRefPubMed
59.
Kawaji T, Shiomi H, Morishita H, Morimoto T, Taylor CA, Kanao S, Koizumi K, Kozawa S, Morihiro K, Watanabe H, Tazaki J, Imai M, Saito N, Shizuta S, Ono K, Togashi K, Kimura T (2016) Feasibility and diagnostic performance of fractional flow reserve measurement derived from coronary computed tomography angiography in real clinical practice. Int J Cardiovasc Imaging
60.
Liu L, Yang W, Nagahara Y, Li Y, Lamooki SR, Muramatsu T, Kitslaar P, Sarai M, Ozaki Y, Barlis P, Yan F, Reiber JH, Tu S (2016) The impact of image resolution on computation of fractional flow reserve: coronary computed tomography angiography versus 3-dimensional quantitative coronary angiography. Int J Cardiovasc Imaging 32(3):513–523CrossRefPubMed
61.
Linde JJ, Sørgaard M, Kühl JT, Hove JD, Kelbæk H, Nielsen WB, Kofoed KF (2016) Prediction of clinical outcome by myocardial CT perfusion in patients with low-risk unstable angina pectoris. Int J Cardiovasc Imaging
62.
Feger S, Shaban A, Lukas S, Kendziorra C, Rief M, Zimmermann E, Dewey M (2016) Temporal averaging for analysis of four-dimensional whole-heart computed tomography perfusion of the myocardium: proof-of-concept study. Int J Cardiovasc Imaging
63.
Lee HJ, Im DJ, Youn JC, Chang S, Suh YJ, Hong YJ, Kim YJ, Hur J, Choi BW (2016) Assessment of myocardial delayed enhancement with cardiac computed tomography in cardiomyopathies: a prospective comparison with delayed enhancement cardiac magnetic resonance imaging. Int J Cardiovasc Imaging
64.
Tu S, Hu F, Cai W, Xiao L, Zhang L, Zheng H, Jiang Q, Chen L (2016) Visualizing polymeric bioresorbable scaffolds with three-dimensional image reconstruction using contrast-enhanced micro-computed tomography. Int J Cardiovasc Imaging. doi:10.​1007/​s10554-016-1049-z PubMedCentral
65.
Collet C, Sotomi Y, Cavalcante R, Asano T, Miyazaki Y, Tenekecioglu E, Kistlaar P, Zeng Y, Suwanasson P, de Winter RJ, Nieman K, Serruys PW, Onuma Y (2016) Accuracy of coronary computed tomography angiography for bioresorbable scaffold luminal investigation: a comparison with optical coherence tomography. Int J Cardiovasc Imaging
66.
Chung MS, Yang DH, Kim YH, Roh JH, Song J, Kang JW, Ahn JM, Park DW, Kang SJ, Lee SW, Lee CW, Park SW, Park SJ, Lim TH (2016) Stent fracture and longitudinal compression detected on coronary CT angiography in the first- and new-generation drug-eluting stents. Int J Cardiovasc Imaging 32(4):637–646CrossRefPubMed
67.
Min JK, Hasegawa JT, Machacz SF, O’Day K (2016) Costs and clinical outcomes for non-invasive versus invasive diagnostic approaches to patients with suspected in-stent restenosis. Int J Cardiovasc Imaging 32(2):309–315CrossRefPubMed
68.
Elattar M, Wiegerinck E, van Kesteren F, Dubois L, Planken N, Vanbavel E, Baan J, Marquering H (2016) Automatic aortic root landmark detection in CTA images for preprocedural planning of transcatheter aortic valve implantation. Int J Cardiovasc Imaging 32(3):501–511. doi:10.​1007/​s10554-015-0793-9 CrossRefPubMed
69.
Bai W, Chen Z, Tang H, Wang H, Cheng W, Rao L (2016) Assessment of the left atrial appendage structure and morphology: comparison of real-time three-dimensional transesophageal echocardiography and computed tomography. Int J Cardiovasc Imaging. doi:10.​1007/​s10554-016-1044-4 PubMed
70.
Molloi S, Johnson T, Ding H, Lipinski J (2016) Accurate quantification of vessel cross-sectional area using CT angiography: a simulation study. Int J Cardiovasc Imaging
71.
Gao X, Kitslaar PH, Budde RP, Tu S, de Graaf MA, Xu L, Xu B, Scholte AJ, Dijkstra J, Reiber JH (2016) Automatic detection of aorto-femoral vessel trajectory from whole-body computed tomography angiography data sets. Int J Cardiovasc Imaging 32(8):1311–1322CrossRefPubMed
72.
Dos Santos FL, Joutsen A, Paci M, Salenius J, Eskola H (2016) Automatic detection of carotid arteries in computed tomography angiography: a proof of concept protocol. Int J Cardiovasc Imaging 32(8):1299–1310CrossRefPubMed
73.
Amanuma M, Kondo T, Sano T, Takayanagi T, Matsutani H, Sekine T, Arai T, Morita H, Ishizaka K, Arakita K, Iwasa A, Takase S (2016) Assessment of coronary in-stent restenosis: value of subtraction coronary computed tomography angiography. Int J Cardiovasc Imaging 32(4):661–670CrossRefPubMed
74.
de Knegt MC, Fuchs A, Weeke P, Møgelvang R, Hassager C, Kofoed KF (2016) Optimisation of coronary vascular territorial 3D echocardiographic strain imaging using computed tomography: a feasibility study using image fusion. Int J Cardiovasc Imaging 32(12):1715–1723CrossRefPubMed
75.
Beeres M, Trommer J, Frellesen C, Nour-Eldin NE, Scholtz JE, Herrmann E, Vogl TJ, Wichmann JL (2016) Evaluation of different keV-settings in dual-energy CT angiography of the aorta using advanced image-based virtual monoenergetic imaging. Int J Cardiovasc Imaging 32(1):137–144CrossRefPubMed
76.
Huang D, Muramatsu T, Li Y, Yang W, Nagahara Y, Chu M, Kitslaar P, Sarai M, Ozaki Y, Chatzizisis YS, Yan F, Reiber JH, Wu R, Pu J, Tu S (2016) Assessment of endothelial shear stress in patients with mild or intermediate coronary stenoses using coronary computed tomography angiography: comparison with invasive coronary angiography. Int J Cardiovasc Imaging
77.
Isma’eel HA, Cremer PC, Khalaf S, Almedawar MM, Elhajj IH, Sakr GE, Jaber WA (2016) Artificial neural network modeling enhances risk stratification and can reduce downstream testing for patients with suspected acute coronary syndromes, negative cardiac biomarkers, and normal ECGs. Int J Cardiovasc Imaging 32(4):687–696CrossRefPubMed
78.
Han BK, Hlavacek AM, Kay WA, Pham TD, Grant K, Garberich RF, Lesser JR, Raman SV (2016) Multi-institutional evaluation of the indications and radiation dose of functional cardiovascular computed tomography (CCT) imaging in congenital heart disease. Int J Cardiovasc Imaging 32(2):339–346. doi:10.​1007/​s10554-016-0844-x CrossRefPubMed
79.
Maaniitty T, Stenström I, Uusitalo V, Ukkonen H, Kajander S, Bax JJ, Saraste A, Knuuti J (2016) Incidence of persistent renal dysfunction after contrast enhanced coronary CT angiography in patients with suspected coronary artery disease. Int J Cardiovasc Imaging 32(10):1567–1575CrossRefPubMed
Metadata
Title
Cardiovascular imaging 2016 in the International Journal of Cardiovascular Imaging
Authors
Johan H. C. Reiber
Johan De Sutter
Paul Schoenhagen
Arthur E. Stillman
Nico R. L. Vande Veire
Publication date
01-06-2017
Publisher
Springer Netherlands
Published in
The International Journal of Cardiovascular Imaging / Issue 6/2017
Print ISSN: 1569-5794
Electronic ISSN: 1875-8312
DOI
https://doi.org/10.1007/s10554-017-1111-5

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