Voxel-wise quantification of myocardial blood flow with cardiovascular magnetic resonance: effect of variations in methodology and validation with positron emission tomography

被引:38
作者
Miller, Christopher A. [1 ,2 ,3 ,4 ]
Naish, Josephine H. [2 ,3 ]
Ainslie, Mark P. [1 ]
Tonge, Christine [5 ]
Tout, Deborah [5 ]
Arumugam, Parthiban [5 ]
Banerji, Anita [2 ,3 ]
Egdell, Robin M. [6 ]
Clark, David [7 ]
Weale, Peter [8 ]
Steadman, Christopher D. [9 ,10 ]
McCann, Gerry P. [9 ,10 ]
Ray, Simon G. [1 ,4 ]
Parker, Geoffrey J. M. [2 ,3 ]
Schmitt, Matthias [1 ,2 ,3 ]
机构
[1] Univ S Manchester Hosp, Wythenshawe Hosp, North West Heart Ctr, Manchester M20 8LR, Lancs, England
[2] Univ Manchester, Ctr Imaging Sci, Manchester, Lancs, England
[3] Univ Manchester, Biomed Imaging Inst, Manchester, Lancs, England
[4] Univ Manchester, Inst Cardiovasc Sci, Manchester, Lancs, England
[5] Cent Manchester Univ Hosp, Nucl Med Ctr, Manchester, Lancs, England
[6] East Cheshire NHS Trust, Macclesfield, Cheshire, England
[7] Wythenshawe Hosp, Alliance Med Cardiac MRI Unit, Manchester M23 9LT, Lancs, England
[8] Siemens Healthcare, Camberlely, Surrey, England
[9] Univ Leicester, NIHR Leicester Cardiovasc Biomed Res Unit, Leicester, Leics, England
[10] Univ Leicester, Dept Cardiovasc Sci, Leicester, Leics, England
基金
美国国家卫生研究院;
关键词
Cardiovascular magnetic resonance; Coronary artery disease; Myocardial blood flow; Positron emission tomography; Quantification; CALCULATING CORRELATION-COEFFICIENTS; PERFUSION RESERVE; MICROVASCULAR DYSFUNCTION; COMPUTED-TOMOGRAPHY; MRI; FEASIBILITY; MODEL;
D O I
10.1186/1532-429X-16-11
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: Quantitative assessment of myocardial blood flow (MBF) from cardiovascular magnetic resonance (CMR) perfusion images appears to offer advantages over qualitative assessment. Currently however, clinical translation is lacking, at least in part due to considerable disparity in quantification methodology. The aim of this study was to evaluate the effect of common methodological differences in CMR voxel-wise measurement of MBF, using position emission tomography (PET) as external validation. Methods: Eighteen subjects, including 9 with significant coronary artery disease (CAD) and 9 healthy volunteers prospectively underwent perfusion CMR. Comparison was made between MBF quantified using: 1. Calculated contrast agent concentration curves (to correct for signal saturation) versus raw signal intensity curves; 2. Midventricular versus basal-ventricular short-axis arterial input function (AIF) extraction; 3. Three different deconvolution approaches; Fermi function parameterization, truncated singular value decomposition (TSVD) and first-order Tikhonov regularization with b-splines. CAD patients also prospectively underwent rubidium-82 PET (median interval 7 days). Results: MBF was significantly higher when calculated using signal intensity compared to contrast agent concentration curves, and when the AIF was extracted from mid-compared to basal-ventricular images. MBF did not differ significantly between Fermi and Tikhonov, or between Fermi and TVSD deconvolution methods although there was a small difference between TSVD and Tikhonov (0.06 mL/min/g). Agreement between all deconvolution methods was high. MBF derived using each CMR deconvolution method showed a significant linear relationship (p < 0.001) with PET-derived MBF however each method underestimated MBF compared to PET (by 0.19 to 0.35 mL/min/g). Conclusions: Variations in more complex methodological factors such as deconvolution method have no greater effect on estimated MBF than simple factors such as AIF location and observer variability. Standardization of the quantification process will aid comparison between studies and may help CMR MBF quantification enter clinical use.
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页数:15
相关论文
共 32 条
  • [1] TISSUE MEAN TRANSIT-TIME FROM DYNAMIC COMPUTED-TOMOGRAPHY BY A SIMPLE DECONVOLUTION TECHNIQUE
    AXEL, L
    [J]. INVESTIGATIVE RADIOLOGY, 1983, 18 (01) : 94 - 99
  • [2] Evaluation of the effect of myocardial segmentation errors on myocardial blood flow estimates from DCE-MRI
    Biglands, J.
    Magee, D.
    Boyle, R.
    Larghat, A.
    Plein, S.
    Radjenovic, A.
    [J]. PHYSICS IN MEDICINE AND BIOLOGY, 2011, 56 (08) : 2423 - 2443
  • [3] STATISTICS NOTES .12. CALCULATING CORRELATION-COEFFICIENTS WITH REPEATED OBSERVATIONS .1. CORRELATION WITHIN-SUBJECTS
    BLAND, JM
    ALTMAN, DG
    [J]. BRITISH MEDICAL JOURNAL, 1995, 310 (6977) : 446 - 446
  • [4] CALCULATING CORRELATION-COEFFICIENTS WITH REPEATED OBSERVATIONS .2. CORRELATION BETWEEN SUBJECTS
    BLAND, JM
    ALTMAN, DG
    [J]. BRITISH MEDICAL JOURNAL, 1995, 310 (6980) : 633 - 633
  • [5] Quantification of perfusion using bolus tracking magnetic resonance imaging in stroke - Assumptions, limitations, and potential implications for clinical use
    Calamante, F
    Gadian, DG
    Connelly, A
    [J]. STROKE, 2002, 33 (04) : 1146 - 1151
  • [6] Coronary microvascular dysfunction and prognosis in hypertrophic cardiomyopathy
    Cecchi, F
    Olivotto, I
    Gistri, R
    Lorenzoni, R
    Chiriatti, G
    Camici, PG
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2003, 349 (11) : 1027 - 1035
  • [7] Absolute myocardial perfusion in canines measured by using dual-bolus first-pass MR imaging
    Christian, TF
    Rettmann, DW
    Aletras, AH
    Liao, SL
    Taylor, JL
    Balaban, RS
    Arai, AE
    [J]. RADIOLOGY, 2004, 232 (03) : 677 - 684
  • [8] Estimation of absolute myocardial blood flow during first-pass MR perfusion imaging using a dual-bolus injection technique: Comparison to single-bolus injection method
    Christian, Timothy F.
    Aletras, Anthony H.
    Arai, Andrew E.
    [J]. JOURNAL OF MAGNETIC RESONANCE IMAGING, 2008, 27 (06) : 1271 - 1277
  • [9] Dekemp RA, 2013, J NUCL MED
  • [10] Fihn SD, 2012, CIRCULATION, V126, P3097, DOI 10.1161/CIR.0b013e3182776f83