Journal of Cardiovascular Magnetic Resonance | |
Population-based studies of myocardial hypertrophy: high resolution cardiovascular magnetic resonance atlases improve statistical power | |
Declan P O’Regan1  Stuart A Cook5  Daniel Rueckert4  Giovanni Montana2  Giuliana Durighel1  Tamara Diamond1  Niall G Keenan3  Christopher Minas2  Wenzhe Shi4  Timothy JW Dawes1  Antonio de Marvao1  | |
[1] From the Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, London W12 0NN, UK;Department of Mathematics, Imperial College London, South Kensington Campus, Exhibition Road, London SW7 2AZ, UK;Department of Cardiology, Imperial College NHS Healthcare Trust, Du Cane Road, London W12 0HS, UK;Department of Computing, Imperial College London, Kensington Campus, Exhibition Road, London SW7 2AZ, UK;Duke-NUS, 8 College Road, Singapore 169857, Singapore | |
关键词: Image analysis; Cardiovascular magnetic resonance; Biobank; GWAS; Cardiomyopathy; LVH; Imaging-genetics; | |
Others : 801751 DOI : 10.1186/1532-429X-16-16 |
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received in 2013-10-28, accepted in 2014-01-29, 发布年份 2014 | |
【 摘 要 】
Background
Cardiac phenotypes, such as left ventricular (LV) mass, demonstrate high heritability although most genes associated with these complex traits remain unidentified. Genome-wide association studies (GWAS) have relied on conventional 2D cardiovascular magnetic resonance (CMR) as the gold-standard for phenotyping. However this technique is insensitive to the regional variations in wall thickness which are often associated with left ventricular hypertrophy and require large cohorts to reach significance. Here we test whether automated cardiac phenotyping using high spatial resolution CMR atlases can achieve improved precision for mapping wall thickness in healthy populations and whether smaller sample sizes are required compared to conventional methods.
Methods
LV short-axis cine images were acquired in 138 healthy volunteers using standard 2D imaging and 3D high spatial resolution CMR. A multi-atlas technique was used to segment and co-register each image. The agreement between methods for end-diastolic volume and mass was made using Bland-Altman analysis in 20 subjects. The 3D and 2D segmentations of the LV were compared to manual labeling by the proportion of concordant voxels (Dice coefficient) and the distances separating corresponding points. Parametric and nonparametric data were analysed with paired t-tests and Wilcoxon signed-rank test respectively. Voxelwise power calculations used the interstudy variances of wall thickness.
Results
The 3D volumetric measurements showed no bias compared to 2D imaging. The segmented 3D images were more accurate than 2D images for defining the epicardium (Dice: 0.95 vs 0.93, P < 0.001; mean error 1.3 mm vs 2.2 mm, P < 0.001) and endocardium (Dice 0.95 vs 0.93, P < 0.001; mean error 1.1 mm vs 2.0 mm, P < 0.001). The 3D technique resulted in significant differences in wall thickness assessment at the base, septum and apex of the LV compared to 2D (P < 0.001). Fewer subjects were required for 3D imaging to detect a 1 mm difference in wall thickness (72 vs 56, P < 0.001).
Conclusions
High spatial resolution CMR with automated phenotyping provides greater power for mapping wall thickness than conventional 2D imaging and enables a reduction in the sample size required for studies of environmental and genetic determinants of LV wall thickness.
【 授权许可】
2014 de Marvao et al.; licensee BioMed Central Ltd.
【 预 览 】
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【 参考文献 】
- [1]Post WS, Larson MG, Myers RH, Galderisi M, Levy D: Heritability of left ventricular mass: the Framingham Heart Study. Hypertension 1997, 30:1025-1028.
- [2]Marian AJ: Genetic determinants of cardiac hypertrophy. Curr Opin Cardiol 2008, 23:199-205.
- [3]Lorell BH, Carabello BA: Left ventricular hypertrophy: pathogenesis, detection, and prognosis. Circulation 2000, 102:470-479.
- [4]Vasan RS, Glazer NL, Felix JF, Lieb W, Wild PS, Felix SB, Watzinger N, Larson MG, Smith NL, Dehghan A, et al.: Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data. JAMA 2009, 302:168-178.
- [5]Stein JL, Hua X, Lee S, Ho AJ, Leow AD, Toga AW, Saykin AJ, Shen L, Foroud T, Pankratz N, et al.: Voxelwise genome-wide association study (vGWAS). Neuroimage 2010, 53:1160-1174.
- [6]Hua X, Lee S, Yanovsky I, Leow AD, Chou YY, Ho AJ, Gutman B, Toga AW, Jack CR Jr, Bernstein MA, et al.: Optimizing power to track brain degeneration in Alzheimer’s disease and mild cognitive impairment with tensor-based morphometry: an ADNI study of 515 subjects. Neuroimage 2009, 48:668-681.
- [7]Vounou M, Nichols TE, Montana G: Discovering genetic associations with high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach. Neuroimage 2010, 53:1147-1159.
- [8]Vounou M, Janousova E, Wolz R, Stein JL, Thompson PM, Rueckert D, Montana G: Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer’s disease. Neuroimage 2012, 60:700-716.
- [9]Shen L, Kim S, Risacher SL, Nho K, Swaminathan S, West JD, Foroud T, Pankratz N, Moore JH, Sloan CD, et al.: Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort. Neuroimage 2010, 53:1051-1063.
- [10]Young AA, Frangi AF: Computational cardiac atlases: from patient to population and back. Exp Physiol 2009, 94:578-596.
- [11]Fonseca CG, Backhaus M, Bluemke DA, Britten RD, Chung JD, Cowan BR, Dinov ID, Finn JP, Hunter PJ, Kadish AH, et al.: The Cardiac Atlas Project-an imaging database for computational modeling and statistical atlases of the heart. Bioinformatics 2011, 27:2288-2295.
- [12]Petitjean C, Dacher J-N: A review of segmentation methods in short axis cardiac MR images. Med Image Anal 2011, 15:169-184.
- [13]Kramer CM, Barkhausen J, Flamm SD, Kim RJ, Nagel E: Standardized cardiovascular magnetic resonance imaging (CMR) protocols, society for cardiovascular magnetic resonance: board of trustees task force on standardized protocols. J Cardiovasc Magn Reson 2008, 10:35. BioMed Central Full Text
- [14]Mascarenhas NB, Muthupillai R, Cheong B, Pereyra M, Flamm SD: Fast 3D cine steady-state free precession imaging with sensitivity encoding for assessment of left ventricular function in a single breath-hold. AJR Am J Roentgenol 2006, 187:1235-1239.
- [15]Rochitte CE, Azevedo CF, Rosario MA, Siqueira MH, Monsao V, Saranathan M, Foo TK, Filho RK, Cerri GG, Ramires JA: Single-Breathhold Four-Dimensional Assessment of Left Ventricular Morphological and Functional Parameters by Magnetic Resonance Imaging Using the VAST Technique. Open Cardiovasc Med J 2011, 5:90-98.
- [16]Hamdan A, Kelle S, Schnackenburg B, Wellnhofer E, Fleck E, Nagel E: Single-breathhold four-dimensional assessment of left ventricular volumes and function using k-t BLAST after application of extracellular contrast agent at 3 Tesla. J Magn Reson Imaging 2008, 27:1028-1036.
- [17]Sievers B, Schrader S, Rehwald W, Hunold P, Barkhausen J, Erbel R: Left ventricular function assessment using a fast 3D gradient echo pulse sequence: comparison to standard multi-breath hold 2D steady state free precession imaging and accounting for papillary muscles and trabeculations. Acta Cardiol 2011, 66:349-357.
- [18]Parish V, Hussain T, Beerbaum P, Greil G, Nagel E, Razavi R, Schaeffter T, Uribe S: Single breath-hold assessment of ventricular volumes using 32-channel coil technology and an extracellular contrast agent. J Magn Reson Imaging 2010, 31:838-844.
- [19]Davarpanah AH, Chen YP, Kino A, Farrelly CT, Keeling AN, Sheehan JJ, Ragin AB, Weale PJ, Zuehlsdorff S, Carr JC: Accelerated two- and three-dimensional cine MR imaging of the heart by using a 32-channel coil. Radiology 2010, 254:98-108.
- [20]Kozerke S, Tsao J, Razavi R, Boesiger P: Accelerating cardiac cine 3D imaging using k-t BLAST. Magn Reson Med 2004, 52:19-26.
- [21]Peters DC, Ennis DB, Rohatgi P, Syed MA, McVeigh ER, Arai AE: 3D breath-held cardiac function with projection reconstruction in steady state free precession validated using 2D cine MRI. J Magn Reson Imaging 2004, 20:411-416.
- [22]Jahnke C, Nagel E, Gebker R, Bornstedt A, Schnackenburg B, Kozerke S, Fleck E, Paetsch I: Four-dimensional single breathhold magnetic resonance imaging using kt-BLAST enables reliable assessment of left- and right-ventricular volumes and mass. J Magn Reson Imaging 2007, 25:737-742.
- [23]Greil GF, Boettger T, Germann S, Klumpp B, Baltes C, Kozerke S, Bialkowski A, Urschitz MS, Miller S, Wolf I, et al.: Quantitative assessment of ventricular function using three-dimensional SSFP magnetic resonance angiography. J Magn Reson Imaging 2007, 26:288-295.
- [24]Shellock FG: Reference manual for magnetic resonance safety. 2003 edition. Salt Lake City, Utah: Amirsys; 2003.
- [25]Bai W, Shi W, O’Regan DP, Tong T, Wang H, Jamil-Copley S, Peters NS, Rueckert D: A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images. IEEE Trans Med Imaging 2013, 32:1302-1315.
- [26]Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig G: User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage 2006, 31:1116-1128.
- [27]Shi W, Caballero J, Ledig C, Zhuang X, Bai W, Bhatia K, Marvao A, Dawes T, O’Regan D, Rueckert D: Cardiac Image Super-Resolution with Global Correspondence Using Multi-Atlas PatchMatch. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013.Volume 8151. Edited by Mori K, Sakuma I, Sato Y, Barillot C, Navab N. Berlin Heidelberg: Springer; 2013:9-16. Lecture Notes in Computer Science]
- [28]Grevera GJ, Udupa JK: Shape-based interpolation of multidimensional grey-level images. IEEE Trans Med Imaging 1996, 15:881-892.
- [29]Lorensen WE, Cline HE: Marching cubes: A high resolution 3D surface construction algorithm. [Abstract]. Computer graphics 1987, 21:163-169.
- [30]Salton CJ, Chuang ML, O’Donnell CJ, Kupka MJ, Larson MG, Kissinger KV, Edelman RR, Levy D, Manning WJ: Gender differences and normal left ventricular anatomy in an adult population free of hypertension. A cardiovascular magnetic resonance study of the Framingham Heart Study Offspring cohort. J Am Coll Cardiol 2002, 39:1055-1060.
- [31]Dice LR: Measures of the Amount of Ecologic Association Between Species. Ecology 1945, 26:297-302.
- [32]Alfakih K, Plein S, Thiele H, Jones T, Ridgway JP, Sivananthan MU: Normal human left and right ventricular dimensions for MRI as assessed by turbo gradient echo and steady-state free precession imaging sequences. J Magn Reson Imaging 2003, 17:323-329.
- [33]Malamateniou C, McGuinness AK, Allsop JM, O’Regan DP, Rutherford MA, Hajnal JV: Snapshot Inversion Recovery: An Optimized Single-Shot T1-weighted Inversion-Recovery Sequence for Improved Fetal Brain Anatomic Delineation. Radiology 2011, 258:229-235.
- [34]R: A language and environment for statistical computing. R Foundation for Statistical Computing http://www.R-project.org webcite
- [35]Bland JM, Altman DG: Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986, 1:307-310.
- [36]Bland JM, Altman DG: Measurement error and correlation coefficients. BMJ 1996, 313:41-42.
- [37]Grothues F, Smith GC, Moon JC, Bellenger NG, Collins P, Klein HU, Pennell DJ: Comparison of interstudy reproducibility of cardiovascular magnetic resonance with two-dimensional echocardiography in normal subjects and in patients with heart failure or left ventricular hypertrophy. Am J Cardiol 2002, 90:29-34.
- [38]Rodriguez CJ, Diez-Roux AV, Moran A, Jin Z, Kronmal RA, Lima J, Homma S, Bluemke DA, Barr RG: Left ventricular mass and ventricular remodeling among Hispanic subgroups compared with non-Hispanic blacks and whites: MESA (Multi-ethnic Study of Atherosclerosis). J Am Coll Cardiol 2010, 55:234-242.
- [39]Gupta S, Berry JD, Ayers CR, Peshock RM, Khera A, de Lemos JA, Patel PC, Markham DW, Drazner MH: Left ventricular hypertrophy, aortic wall thickness, and lifetime predicted risk of cardiovascular disease:the Dallas Heart Study. JACC Cardiovascular imaging 2010, 3:605-613.
- [40]Fox ER, Musani SK, Barbalic M, Lin H, Yu B, Ogunyankin KO, Smith NL, Kutlar A, Glazer NL, Post WS, et al.: Genome-wide association study of cardiac structure and systolic function in African Americans: the Candidate Gene Association Resource (CARe) study. Circulation Cardiovascular genetics 2013, 6:37-46.
- [41]Chun EJ, Choi SI, Jin KN, Kwag HJ, Kim YJ, Choi BW, Lee W, Park JH: Hypertrophic Cardiomyopathy: Assessment with MR Imaging and Multidetector CT1. Radiographics 2010, 30:1309-1328.
- [42]Ganau A, Devereux RB, Roman MJ, de Simone G, Pickering TG, Saba PS, Vargiu P, Simongini I, Laragh JH: Patterns of left ventricular hypertrophy and geometric remodeling in essential hypertension. J Am Coll Cardiol 1992, 19:1550-1558.
- [43]Pattynama PM, Doornbos J, Hermans J, van der Wall EE, de Roos A: Magnetic resonance evaluation of regional left ventricular function. Effect of through-plane motion. Investigative radiology 1992, 27:681-685.
- [44]Bloomer TN, Plein S, Radjenovic A, Higgins DM, Jones TR, Ridgway JP, Sivananthan MU: Cine MRI using steady state free precession in the radial long axis orientation is a fast accurate method for obtaining volumetric data of the left ventricle. J Magn Reson Imaging 2001, 14:685-692.
- [45]Weiger M, Pruessmann KP, Boesiger P: 2D SENSE for faster 3D MRI. MAGMA 2002, 14:10-19.
- [46]Makowski MR, Wiethoff AJ, Jansen CH, Uribe S, Parish V, Schuster A, Botnar RM, Bell A, Kiesewetter C, Razavi R, et al.: Single breath-hold assessment of cardiac function using an accelerated 3D single breath-hold acquisition technique–comparison of an intravascular and extravascular contrast agent. J Cardiovasc Magn Reson 2012, 14:53. BioMed Central Full Text
- [47]Mumford JA: A power calculation guide for fMRI studies. Soc Cogn Affect Neurosci 2012, 7:738-742.
- [48]Petersen SE, Matthews PM, Bamberg F, Bluemke DA, Francis JM, Friedrich MG, Leeson P, Nagel E, Plein S, Rademakers FE, et al.: Imaging in population science: cardiovascular magnetic resonance in 100,000 participants of UK Biobank - rationale, challenges and approaches. J Cardiovasc Magn Reson 2013, 15:46. BioMed Central Full Text
- [49]Mirnezami R, Nicholson J, Darzi A: Preparing for precision medicine. N Engl J Med 2012, 366:489-491.
- [50]Bland M: An introduction to medical statistics. 3rd edition. Oxford; New York: Oxford University Press; 2000.