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Estimation of myocardial deformation using correlation image velocimetry

View Article: PubMed Central - PubMed

ABSTRACT

Background: Tagged Magnetic Resonance (tMR) imaging is a powerful technique for determining cardiovascular abnormalities. One of the reasons for tMR not being used in routine clinical practice is the lack of easy-to-use tools for image analysis and strain mapping. In this paper, we introduce a novel interdisciplinary method based on correlation image velocimetry (CIV) to estimate cardiac deformation and strain maps from tMR images.

Methods: CIV, a cross-correlation based pattern matching algorithm, analyses a pair of images to obtain the displacement field at sub-pixel accuracy with any desired spatial resolution. This first time application of CIV to tMR image analysis is implemented using an existing open source Matlab-based software called UVMAT. The method, which requires two main input parameters namely correlation box size (CB) and search box size (SB), is first validated using a synthetic grid image with grid sizes representative of typical tMR images. Phantom and patient images obtained from a Medical Imaging grand challenge dataset (http://stacom.cardiacatlas.org/motion-tracking-challenge/) were then analysed to obtain cardiac displacement fields and strain maps. The results were then compared with estimates from Harmonic Phase analysis (HARP) technique.

Results: For a known displacement field imposed on both the synthetic grid image and the phantom image, CIV is accurate for 3-pixel and larger displacements on a 512 × 512 image with (CB,SB)=(25,55) pixels. Further validation of our method is achieved by showing that our estimated landmark positions on patient images fall within the inter-observer variability in the ground truth. The effectiveness of our approach to analyse patient images is then established by calculating dense displacement fields throughout a cardiac cycle, and were found to be physiologically consistent. Circumferential strains were estimated at the apical, mid and basal slices of the heart, and were shown to compare favorably with those of HARP over the entire cardiac cycle, except in a few (∼4) of the segments in the 17-segment AHA model. The radial strains, however, are underestimated by our method in most segments when compared with HARP.

Conclusions: In summary, we have demonstrated the capability of CIV to accurately and efficiently quantify cardiac deformation from tMR images. Furthermore, physiologically consistent displacement fields and circumferential strain curves in most regions of the heart indicate that our approach, upon automating some pre-processing steps and testing in clinical trials, can potentially be implemented in a clinical setting.

Electronic supplementary material: The online version of this article (doi:10.1186/s12880-017-0195-7) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus

Comparison between CIV (shown in red) and HARP (shown in blue) for estimated mean (across 15 healthy individuals) circumferential strain in various segments of the heart. The x-axis of every plot signifies one cardiac cycle, with x=0 corresponding to end diastole. The error bars are based on the standard deviation across the 15 individuals
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Fig8: Comparison between CIV (shown in red) and HARP (shown in blue) for estimated mean (across 15 healthy individuals) circumferential strain in various segments of the heart. The x-axis of every plot signifies one cardiac cycle, with x=0 corresponding to end diastole. The error bars are based on the standard deviation across the 15 individuals

Mentions: Radial and circumferential strain curves, as described in the “Methods” section, were derived from the calculated dense displacement fields for every patient. To obtain the strain curves at the basal, mid and apical slices, the myocardium is divided into segments according to the American Heart Association (AHA) 17-segment model [27]. Strain values are averaged over each anatomical segment, and then plotted as a function of time in Figs. 8 and 9. A similar analysis was performed using an evaluation version of the commercial implementation of the HARP algorithm, and the results are compared with those of CIV in Figs. 8 and 9. Our estimated circumferential strain curves (red) in Fig. 8 are in excellent quantitative agreement with HARP (blue); the standard deviation, calculated over all the patients, from the two methods are also of a similar magnitude. The mean absolute deviation of our circumferential strain curves from those of HARP across all times, segments and patients is 0.034, with the corresponding standard deviation being 0.024. The circumferential strain curves are predominantly negative, characteristic of contraction of the myocardium during systole. Radial strain curves (Fig. 9) are also observed to be physiologically consistent in the antherior, infero-lateral and antheri-lateral segments, i.e. increasing positive values during the first half of the cardiac cycle and then a subsequent decrease in the second half. CIV, however, underestimates the magnitudes of the radial strain in certain segments, which we discuss further in the next section. For the radial strain, the mean and the standard deviation of the absolute difference between CIV and HARP are 0.0625 and 0.038, respectively.Fig. 8


Estimation of myocardial deformation using correlation image velocimetry
Comparison between CIV (shown in red) and HARP (shown in blue) for estimated mean (across 15 healthy individuals) circumferential strain in various segments of the heart. The x-axis of every plot signifies one cardiac cycle, with x=0 corresponding to end diastole. The error bars are based on the standard deviation across the 15 individuals
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5382518&req=5

Fig8: Comparison between CIV (shown in red) and HARP (shown in blue) for estimated mean (across 15 healthy individuals) circumferential strain in various segments of the heart. The x-axis of every plot signifies one cardiac cycle, with x=0 corresponding to end diastole. The error bars are based on the standard deviation across the 15 individuals
Mentions: Radial and circumferential strain curves, as described in the “Methods” section, were derived from the calculated dense displacement fields for every patient. To obtain the strain curves at the basal, mid and apical slices, the myocardium is divided into segments according to the American Heart Association (AHA) 17-segment model [27]. Strain values are averaged over each anatomical segment, and then plotted as a function of time in Figs. 8 and 9. A similar analysis was performed using an evaluation version of the commercial implementation of the HARP algorithm, and the results are compared with those of CIV in Figs. 8 and 9. Our estimated circumferential strain curves (red) in Fig. 8 are in excellent quantitative agreement with HARP (blue); the standard deviation, calculated over all the patients, from the two methods are also of a similar magnitude. The mean absolute deviation of our circumferential strain curves from those of HARP across all times, segments and patients is 0.034, with the corresponding standard deviation being 0.024. The circumferential strain curves are predominantly negative, characteristic of contraction of the myocardium during systole. Radial strain curves (Fig. 9) are also observed to be physiologically consistent in the antherior, infero-lateral and antheri-lateral segments, i.e. increasing positive values during the first half of the cardiac cycle and then a subsequent decrease in the second half. CIV, however, underestimates the magnitudes of the radial strain in certain segments, which we discuss further in the next section. For the radial strain, the mean and the standard deviation of the absolute difference between CIV and HARP are 0.0625 and 0.038, respectively.Fig. 8

View Article: PubMed Central - PubMed

ABSTRACT

Background: Tagged Magnetic Resonance (tMR) imaging is a powerful technique for determining cardiovascular abnormalities. One of the reasons for tMR not being used in routine clinical practice is the lack of easy-to-use tools for image analysis and strain mapping. In this paper, we introduce a novel interdisciplinary method based on correlation image velocimetry (CIV) to estimate cardiac deformation and strain maps from tMR images.

Methods: CIV, a cross-correlation based pattern matching algorithm, analyses a pair of images to obtain the displacement field at sub-pixel accuracy with any desired spatial resolution. This first time application of CIV to tMR image analysis is implemented using an existing open source Matlab-based software called UVMAT. The method, which requires two main input parameters namely correlation box size (CB) and search box size (SB), is first validated using a synthetic grid image with grid sizes representative of typical tMR images. Phantom and patient images obtained from a Medical Imaging grand challenge dataset (http://stacom.cardiacatlas.org/motion-tracking-challenge/) were then analysed to obtain cardiac displacement fields and strain maps. The results were then compared with estimates from Harmonic Phase analysis (HARP) technique.

Results: For a known displacement field imposed on both the synthetic grid image and the phantom image, CIV is accurate for 3-pixel and larger displacements on a 512 × 512 image with (CB,SB)=(25,55) pixels. Further validation of our method is achieved by showing that our estimated landmark positions on patient images fall within the inter-observer variability in the ground truth. The effectiveness of our approach to analyse patient images is then established by calculating dense displacement fields throughout a cardiac cycle, and were found to be physiologically consistent. Circumferential strains were estimated at the apical, mid and basal slices of the heart, and were shown to compare favorably with those of HARP over the entire cardiac cycle, except in a few (∼4) of the segments in the 17-segment AHA model. The radial strains, however, are underestimated by our method in most segments when compared with HARP.

Conclusions: In summary, we have demonstrated the capability of CIV to accurately and efficiently quantify cardiac deformation from tMR images. Furthermore, physiologically consistent displacement fields and circumferential strain curves in most regions of the heart indicate that our approach, upon automating some pre-processing steps and testing in clinical trials, can potentially be implemented in a clinical setting.

Electronic supplementary material: The online version of this article (doi:10.1186/s12880-017-0195-7) contains supplementary material, which is available to authorized users.

No MeSH data available.


Related in: MedlinePlus