OSA's Digital Library

Biomedical Optics Express

Biomedical Optics Express

  • Editor: Joseph A. Izatt
  • Vol. 4, Iss. 11 — Nov. 1, 2013
  • pp: 2540–2545
« Show journal navigation

Optical tractography of the mouse heart using polarization-sensitive optical coherence tomography

Yuanbo Wang and Gang Yao  »View Author Affiliations


Biomedical Optics Express, Vol. 4, Issue 11, pp. 2540-2545 (2013)
http://dx.doi.org/10.1364/BOE.4.002540


View Full Text Article

Acrobat PDF (3063 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

We developed a method to image myocardial fiber architecture in the mouse heart using a Jones matrix-based polarization-sensitive optical coherence tomography (PSOCT) system. The “cross-helical” laminar structure of myocardial fibers can be clearly visualized using this technology. The obtained myocardial fiber organization agrees well with existing knowledge acquired using conventional histology and diffusion tensor magnetic resonance imaging.

© 2013 Optical Society of America

1. Introduction

Histological studies [1

1. D. D. Streeter Jr, H. M. Spotnitz, D. P. Patel, J. Ross Jr, and E. H. Sonnenblick, “Fiber orientation in the canine left ventricle during diastole and systole,” Circ. Res. 24(3), 339–347 (1969). [CrossRef] [PubMed]

, 2

2. D. D. Streeter and D. L. Bassett, “An engineering analysis of myocardial fiber orientation in pig’s left ventricle in systole,” Anat. Rec. 155(4), 503–511 (1966). [CrossRef]

] have revealed the “cross-helical” structure of myocardial fibers formed laminarly at different transmural thicknesses in the ventricular myocardium of the heart [3

3. I. J. LeGrice, B. H. Smaill, L. Z. Chai, S. G. Edgar, J. B. Gavin, and P. J. Hunter, “Laminar structure of the heart: ventricular myocyte arrangement and connective tissue architecture in the dog,” Am. J. Physiol.-Heart. C. 269(2 38–2), H571–H582 (1995).

]. This unique fiber architecture has a great influence on mechanical and electrical heart functions [4

4. B. Taccardi, E. Macchi, R. L. Lux, P. R. Ershler, S. Spaggiari, S. Baruffi, and Y. Vyhmeister, “Effect of myocardial fiber direction on epicardial potentials,” Circulation 90(6), 3076–3090 (1994). [CrossRef] [PubMed]

, 5

5. I. J. LeGrice, Y. Takayama, and J. W. Covell, “Transverse shear along myocardial cleavage planes provides a mechanism for normal systolic wall thickening,” Circ. Res. 77(1), 182–193 (1995). [CrossRef] [PubMed]

]. Abnormal fiber organization is linked to cardiac dysfunction and alterations in cardiac muscle structure have been found as a result of myocardial infarction [6

6. G. J. Strijkers, A. Bouts, W. M. Blankesteijn, T. H. J. M. Peeters, A. Vilanova, M. C. van Prooijen, H. M. H. F. Sanders, E. Heijman, and K. Nicolay, “Diffusion tensor imaging of left ventricular remodeling in response to myocardial infarction in the mouse,” NMR Biomed. 22(2), 182–190 (2009). [CrossRef] [PubMed]

]. Therefore “tractography”, an imaging tool that can acquire microstructural details of tissue fiber organization, is valuable for both basic research and clinical diagnosis. Despite its superior spatial resolution, histological assessment is time consuming and limited to imaging of small areas. Alternatively, diffusion-tensor magnetic resonance imaging (DTI) [7

7. D. E. Sosnovik, R. Wang, G. Dai, T. G. Reese, and V. J. Wedeen, “Diffusion MR tractography of the heart,” J. Cardiovasc. Magn. Reson. 11(1), 47–61 (2009). [CrossRef] [PubMed]

] has been established as a state-of-art method for imaging the 3D fiber organization in whole hearts; however, the image resolution in DTI is usually limited to submillimeters.

Optical coherence tomography (OCT) is a non-destructive optical imaging technique that can provide depth-resolved high resolution tissue images at high speed. It has been shown that ultrahigh resolution OCT can be used to acquire fiber orientation in heart tissue using intensity contrast [8

8. C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008). [CrossRef] [PubMed]

10

10. C. J. Goergen, H. Radhakrishnan, S. Sakadžić, E. T. Mandeville, E. H. Lo, D. E. Sosnovik, and V. J. Srinivasan, “Optical coherence tractography using intrinsic contrast,” Opt. Lett. 37(18), 3882–3884 (2012). [CrossRef] [PubMed]

]. Because fibrous tissues such as myocardium show intrinsic optical birefringence, fiber orientation can be estimated using the optical axis’ information. Recently, a set of algorithms [11

11. C. Fan and G. Yao, “Mapping local retardance in birefringent samples using polarization sensitive optical coherence tomography,” Opt. Lett. 37(9), 1415–1417 (2012). [CrossRef] [PubMed]

13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

] have been developed to extract the depth-resolved local optical polarization properties from polarization-sensitive optical coherence tomography (PSOCT) images. Fan and Yao [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

] demonstrated that these algorithms can be applied in a Jones matrix PSOCT system [14

14. C. Fan and G. Yao, “Full-range spectral domain Jones matrix optical coherence tomography using a single spectral camera,” Opt. Express 20(20), 22360–22371 (2012). [CrossRef] [PubMed]

] to visualize myocardial fiber orientation in a piece of bovine heart tissue.

2. Method

The Jones matrix PSOCT system used in this study is a single camera-based full-range spectral domain system as described in detail in [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

]. This system was carefully calibrated for imaging conventional ‘cumulative’ polarization properties including retardance (or ‘phase retardation’), optical axis and diattenuation [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

]. A Superluminescent Light Emitting Diode (SLD) was used as the light source (SLD-351-HP, Superlum, Ireland) at a central wavelength of 847.8 nm. The system had a depth resolution of 8.2 μm in the air within 1.5 mm of the zero delay line as characterized using the interference signal from a mirror at the sample arm. The lateral resolution of the system was 12.4 µm when measured using a 1951 USAF test target. All size/distance values presented in this report were measured in air.

The excised mouse heart was fixed in 4% paraformaldehyde and imaged ex vivo. A 20 gauge needle was used to hold the heart by passing through the heart apex and center of the base. The needle was mounted on a rotational stage (PRM1Z8, Thorlabs, Inc., Newton, New Jersey, USA) and was aligned with the rotational axis. The stage was rotated continuously over 270° at a speed of 1.25°/sec. This rotation range was chosen to ensure that the entire left ventricle and part of the right ventricle can be imaged within the effective image depth of 2.6 mm of the PSOCT system [14

14. C. Fan and G. Yao, “Full-range spectral domain Jones matrix optical coherence tomography using a single spectral camera,” Opt. Express 20(20), 22360–22371 (2012). [CrossRef] [PubMed]

]. A total of 2700 B-scans (2000 pixels in each B-scan covering 7.0 mm) were acquired at a speed of 12.5 B-scans per second (18μs camera exposure) to match the rotation speed. The entire scanning took 216 seconds to complete.

A coordinate system was set up to illustrate the measurement geometry as shown in Fig. 1
Fig. 1 An illustration of the imaging geometry. The incident light (A-scan) was aligned with the z-axis; the B-scan was along the axis of rotation (y-axis); and the heart sample was rotated for C-scan.
. The incident light was aligned with the Z-axis (A-scan) and the B-scan was aligned with the Y-axis (parallel to the axis of rotation). The XY plane, i.e. the imaging plane for axis measurement, was perpendicular to the Z-axis and was set up as an analog to a histology slice. The projection angle of myocardial fibers passing through a pixel within the XY plane was measured by extracting the local (slow) optical axis in relation to the x-axis from the PSOCT images. The measured orientation θ had a range of [-90°, 90°] with positive angles inclined toward the positive x-axis (Fig. 1).

The procedure for extracting local optical axis, retardance and diattenuation from PSOCT was detailed in [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

]. The term “optical axis” used here refers to the “slow” optical axis which is aligned with the fiber orientation. Briefly, the two orthogonal (horizontally and vertically polarized) components of the backscattered OCT signal were measured for both right- and left-handed circularly polarized incident light. The measured signals were stored in a “planar” 3D matrix of 650 × 2000 × 2700 pixels with pixel sizes of 5.4µm × 4µm × 7.9µm in A-, B-, and C-scans, respectively. A birefringent Jones matrix was constructed at each image pixel in the data set with tissue diattenuation removed by using only the real component of the measured complex retardance [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

]. To improve signal-to-noise, the amplitudes of the two orthogonal polarization components and their phase difference were averaged over 3 consecutive B-scans during the calculation. In addition, a size three median filter (3 × 3 × 3) was applied to the 3D data set to further reduce speckle noise. Then, an iterative algorithm [12

12. C. Fan and G. Yao, “Mapping local optical axis in birefringent samples using polarization-sensitive optical coherence tomography,” J. Biomed. Opt. 17(11), 110501 (2012). [CrossRef] [PubMed]

, 13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

] was used to calculate the local depth-resolved optical axis.

Figure 2
Fig. 2 An illustration of the procedure for reconstructing the tractography in a mouse heart. (a) Extracting an en face image at a given transmural depth. The planar presentation of the extracted en face images of (b) intensity, (c) local retardance, and (d) local fiber orientation; (e) the streamline presentation of fiber tract overlaying on the intensity image; (f) the reconstructed 3D tractographic representation of the fiber tracts in (e).
illustrates the procedure for constructing the 3D fiber tract from the local optical axis data set. The sample surface boundary was first obtained from the intensity data for each A-scan using a threshold-based segmentation algorithm [14

14. C. Fan and G. Yao, “Full-range spectral domain Jones matrix optical coherence tomography using a single spectral camera,” Opt. Express 20(20), 22360–22371 (2012). [CrossRef] [PubMed]

]. Then, depth-resolved en face images were constructed from all pixels at a given transmural depth from the surface boundary (Fig. 2(a)). Examples of the extracted “planar” en face PSOCT images (intensity, local retardance, and optical axis) are shown in Fig. 2(b)-2(d). As shown in Fig. 2(c), the artery tissues (enclosed by the dashed line) had low retardance values which led to unreliable optical axis calculation. To focus on quantifying myocardial fibers in ventricles, the artery and atrium tissues were removed from further processing using a retardance threshold of 0.012 rad at the boundary of the ventricle as shown in Fig. 2(c)-2(e).

Within each en face image of the local optical axis (Fig. 2(d)), the stream2 function in Matlab was used to obtain the “streamline” representation of fiber tracts (Fig. 2(e)) [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

]. A uniform 25 × 34 mesh grid was used as the starting points in streamline calculation of the whole mouse heart. To improve the tractographic visualization, a cubic-spline interpolation algorithm was applied to each obtained fiber tract to fill the empty space between the tracking seeds so that each fiber tract contained 2700 points. The obtained fiber tract was further smoothed using an averaging filter with 1% of the given fiber length as the window size. To help eliminate incorrect fiber tracts produced by noisy data, short fiber tracts whose lengths were less than 5% of C-scan length were removed from visualization.

Once the “planar” orientation map (Fig. 2(e)) was obtained, it was then transformed into 3D coordinates using a polar transformation. The polar angle αi at C-scan index i was computed as: αi=(i/Nc)×Φ,where NC denotes the total number of C-scan and Φ is the full rotation range angle (270° in this study). The radius r in the polar transformation was computed as r=R0Surf(Ci,Bj,Ak), where R0 denotes the maximum radius of the sample heart within the XZ plane (Fig. 1) and was 4.5 mm for the same presented here. Surf(Ci,Bj,Ak)represents the depth of the image pixel at ith C-scan, jth B-scan, and kth A-scan in relation to R0. An example of the obtained 3D tractographic representation is shown in Fig. 2(f). To better visualize the change in fiber orientation, fiber tracts were also displayed using a color map based on the orientation as shown in the color bar in Fig. 2(f).

All image processing was implemented using the Matlab software. The open source 3DSlicer (http://www.slicer.org/) was used for 3D data visualization.

3. Results and discussion

The 3D structure image of the whole mouse heart is shown in Fig. 3(a)
Fig. 3 (a) The 3D structure image of the mouse heart; (b) the corresponding 3D tractographic visualization. The B-scan images of structure, local retardance and optical axis acquired along the dashed line in (a) are shown in (c)-(e). Also shown are the en face images of the (f) structure, (g) local retardance, (h) local optical axis, and (i) cardiac fiber tract of a small region of interest (ROI) extracted at transmural depths from 0.11 mm to 0.91 mm. As shown in (a), the ROI was extracted from the lateral side of the left ventricle wall and had a size of 1.57 mm × 20° rotation (B × C-scan). The size bars in (c) and (f) are 1 mm.
. Figure 3(c) to 3(e) show example B-scan images of the intensity, local retardance and axis extracted along the dashed line in Fig. 3(a). Clear optical axis information can be observed at a depth of 1.1 mm beneath the surface for most parts of the heart tissue, and up to 1.4 mm at some locations. As an assessment of the overall polarization properties, the average retardance and diattenuation were 2.8 ± 1.5 rad/mm and 1.2 ± 1.1 mm−1 in the left ventricle tissue over an area of 4.0 × 7.8 mm2 (B × C) from 0.1 to 0.9 mm beneath the epicardium. The large variation suggested inhomogeneous polarization properties throughout the sample. We also noticed that the retardance value in mouse heart was smaller than that obtained in a piece of bovine heart [13

13. C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

].

Four additional small pieces of ROIs extracted at various left ventricle locations (Fig. 4
Fig. 4 (a) Four ROIs were extracted from different locations of the mouse heart. ROI-A, ROI-B, and ROI-C were located around the mid-heart of the left ventricle; while ROI-D was close to the apex of the heart. These ROIs had a size of 0.95 mm × 12° (B-scan by C-scan). (b) 3D color-coded tractography of the four ROIs. (c) The average fiber orientation as a function of transmural distance from the heart surface. Error bars shown represent standard deviations.
) were quantified to examine the organization of myocardial fibers in the mouse heart. Each ROI had a size of 0.95 mm × 12° rotation (B-scan by C-scan). As shown in Fig. 4(a), the ROI-A, B, and C were located at the anterior, lateral, and posterior side of the left ventricle, respectively; whereas the ROI-D was located at the apical lateral wall of the left ventricle. Figure 4(b) shows the color-coded 3D tractography in the aforementioned four ROIs. A consistent transition in fiber orientation from negative angles (red color) at epicardium to positive angles (blue to pink color) toward endocardium can be seen.

4. Conclusion

In summary, we developed a new scanning and image reconstruction procedure for acquiring tractography in whole mouse hearts. The “cross-helical” laminar structure of myocardial fibers was clearly visualized using this technology. The obtained myocardial fiber organization was in accordance with existing knowledge acquired using diffusion tensor magnetic resonance imaging. Although the imaging depth of our current PSOCT system was not able to penetrate the entire heart wall (1.5 – 1.8 mm) [15

15. Y. Jiang, K. Pandya, O. Smithies, and E. W. Hsu, “Three-dimensional diffusion tensor microscopy of fixed mouse hearts,” Magn. Reson. Med. 52(3), 453–460 (2004). [CrossRef] [PubMed]

] in mice, it was sufficient to cover the majority of the heart wall from the surface. The imaging depth may be improved by using an incident light at longer wavelengths such as 1060 nm or 1300 nm. Nevertheless, the micrometer scale resolution achieved by OCT is superior to that obtained in DTI and approaches the capability of histological imaging. Moreover, the fast imaging speed of current OCT technologies far exceeds the speed of DTI and histology analysis. Therefore PSOCT may become a valuable tool for studying myocardial microstructures in small animals.

Acknowledgments

We thank Dr. Shinghua Ding for providing mouse heart samples.

References and links

1.

D. D. Streeter Jr, H. M. Spotnitz, D. P. Patel, J. Ross Jr, and E. H. Sonnenblick, “Fiber orientation in the canine left ventricle during diastole and systole,” Circ. Res. 24(3), 339–347 (1969). [CrossRef] [PubMed]

2.

D. D. Streeter and D. L. Bassett, “An engineering analysis of myocardial fiber orientation in pig’s left ventricle in systole,” Anat. Rec. 155(4), 503–511 (1966). [CrossRef]

3.

I. J. LeGrice, B. H. Smaill, L. Z. Chai, S. G. Edgar, J. B. Gavin, and P. J. Hunter, “Laminar structure of the heart: ventricular myocyte arrangement and connective tissue architecture in the dog,” Am. J. Physiol.-Heart. C. 269(2 38–2), H571–H582 (1995).

4.

B. Taccardi, E. Macchi, R. L. Lux, P. R. Ershler, S. Spaggiari, S. Baruffi, and Y. Vyhmeister, “Effect of myocardial fiber direction on epicardial potentials,” Circulation 90(6), 3076–3090 (1994). [CrossRef] [PubMed]

5.

I. J. LeGrice, Y. Takayama, and J. W. Covell, “Transverse shear along myocardial cleavage planes provides a mechanism for normal systolic wall thickening,” Circ. Res. 77(1), 182–193 (1995). [CrossRef] [PubMed]

6.

G. J. Strijkers, A. Bouts, W. M. Blankesteijn, T. H. J. M. Peeters, A. Vilanova, M. C. van Prooijen, H. M. H. F. Sanders, E. Heijman, and K. Nicolay, “Diffusion tensor imaging of left ventricular remodeling in response to myocardial infarction in the mouse,” NMR Biomed. 22(2), 182–190 (2009). [CrossRef] [PubMed]

7.

D. E. Sosnovik, R. Wang, G. Dai, T. G. Reese, and V. J. Wedeen, “Diffusion MR tractography of the heart,” J. Cardiovasc. Magn. Reson. 11(1), 47–61 (2009). [CrossRef] [PubMed]

8.

C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, and A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008). [CrossRef] [PubMed]

9.

C. M. Ambrosi, V. V. Fedorov, R. B. Schuessler, A. M. Rollins, and I. R. Efimov, “Quantification of fiber orientation in the canine atrial pacemaker complex using optical coherence tomography,” J. Biomed. Opt. 17(7), 071309 (2012). [CrossRef] [PubMed]

10.

C. J. Goergen, H. Radhakrishnan, S. Sakadžić, E. T. Mandeville, E. H. Lo, D. E. Sosnovik, and V. J. Srinivasan, “Optical coherence tractography using intrinsic contrast,” Opt. Lett. 37(18), 3882–3884 (2012). [CrossRef] [PubMed]

11.

C. Fan and G. Yao, “Mapping local retardance in birefringent samples using polarization sensitive optical coherence tomography,” Opt. Lett. 37(9), 1415–1417 (2012). [CrossRef] [PubMed]

12.

C. Fan and G. Yao, “Mapping local optical axis in birefringent samples using polarization-sensitive optical coherence tomography,” J. Biomed. Opt. 17(11), 110501 (2012). [CrossRef] [PubMed]

13.

C. Fan and G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]

14.

C. Fan and G. Yao, “Full-range spectral domain Jones matrix optical coherence tomography using a single spectral camera,” Opt. Express 20(20), 22360–22371 (2012). [CrossRef] [PubMed]

15.

Y. Jiang, K. Pandya, O. Smithies, and E. W. Hsu, “Three-dimensional diffusion tensor microscopy of fixed mouse hearts,” Magn. Reson. Med. 52(3), 453–460 (2004). [CrossRef] [PubMed]

16.

L. J. Healy, Y. Jiang, and E. W. Hsu, “Quantitative comparison of myocardial fiber structure between mice, rabbit, and sheep using diffusion tensor cardiovascular magnetic resonance,” J. Cardiovasc. Magn. Reson. 13(1), 74 (2011). [CrossRef] [PubMed]

17.

C. Mekkaoui, S. Huang, H. H. Chen, G. Dai, T. G. Reese, W. J. Kostis, A. Thiagalingam, P. Maurovich-Horvat, J. N. Ruskin, U. Hoffmann, M. P. Jackowski, and D. E. Sosnovik, “Fiber architecture in remodeled myocardium revealed with a quantitative diffusion CMR tractography framework and histological validation,” J. Cardiovasc. Magn. Reson. 14(1), 70 (2012). [CrossRef] [PubMed]

18.

R. H. Clayton, S. Abdalhamid, R. Bloor, G. Kyprianou, K. Kotagiri, J. Lee, A. Mane, and R. White, “Transmural changes in fibre helix angle in normal and failing canine ventricles,” Comput. Cardiol. 37, art. 5738123, 915–918 (2010).

19.

W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, and J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998). [CrossRef] [PubMed]

OCIS Codes
(110.4500) Imaging systems : Optical coherence tomography
(230.5440) Optical devices : Polarization-selective devices

ToC Category:
Optical Coherence Tomography

History
Original Manuscript: August 12, 2013
Revised Manuscript: October 13, 2013
Manuscript Accepted: October 15, 2013
Published: October 21, 2013

Citation
Yuanbo Wang and Gang Yao, "Optical tractography of the mouse heart using polarization-sensitive optical coherence tomography," Biomed. Opt. Express 4, 2540-2545 (2013)
http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-4-11-2540


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. D. D. Streeter, H. M. Spotnitz, D. P. Patel, J. Ross, E. H. Sonnenblick, “Fiber orientation in the canine left ventricle during diastole and systole,” Circ. Res. 24(3), 339–347 (1969). [CrossRef] [PubMed]
  2. D. D. Streeter, D. L. Bassett, “An engineering analysis of myocardial fiber orientation in pig’s left ventricle in systole,” Anat. Rec. 155(4), 503–511 (1966). [CrossRef]
  3. I. J. LeGrice, B. H. Smaill, L. Z. Chai, S. G. Edgar, J. B. Gavin, P. J. Hunter, “Laminar structure of the heart: ventricular myocyte arrangement and connective tissue architecture in the dog,” Am. J. Physiol.-Heart. C. 269(2 38–2), H571–H582 (1995).
  4. B. Taccardi, E. Macchi, R. L. Lux, P. R. Ershler, S. Spaggiari, S. Baruffi, Y. Vyhmeister, “Effect of myocardial fiber direction on epicardial potentials,” Circulation 90(6), 3076–3090 (1994). [CrossRef] [PubMed]
  5. I. J. LeGrice, Y. Takayama, J. W. Covell, “Transverse shear along myocardial cleavage planes provides a mechanism for normal systolic wall thickening,” Circ. Res. 77(1), 182–193 (1995). [CrossRef] [PubMed]
  6. G. J. Strijkers, A. Bouts, W. M. Blankesteijn, T. H. J. M. Peeters, A. Vilanova, M. C. van Prooijen, H. M. H. F. Sanders, E. Heijman, K. Nicolay, “Diffusion tensor imaging of left ventricular remodeling in response to myocardial infarction in the mouse,” NMR Biomed. 22(2), 182–190 (2009). [CrossRef] [PubMed]
  7. D. E. Sosnovik, R. Wang, G. Dai, T. G. Reese, V. J. Wedeen, “Diffusion MR tractography of the heart,” J. Cardiovasc. Magn. Reson. 11(1), 47–61 (2009). [CrossRef] [PubMed]
  8. C. P. Fleming, C. M. Ripplinger, B. Webb, I. R. Efimov, A. M. Rollins, “Quantification of cardiac fiber orientation using optical coherence tomography,” J. Biomed. Opt. 13(3), 030505 (2008). [CrossRef] [PubMed]
  9. C. M. Ambrosi, V. V. Fedorov, R. B. Schuessler, A. M. Rollins, I. R. Efimov, “Quantification of fiber orientation in the canine atrial pacemaker complex using optical coherence tomography,” J. Biomed. Opt. 17(7), 071309 (2012). [CrossRef] [PubMed]
  10. C. J. Goergen, H. Radhakrishnan, S. Sakadžić, E. T. Mandeville, E. H. Lo, D. E. Sosnovik, V. J. Srinivasan, “Optical coherence tractography using intrinsic contrast,” Opt. Lett. 37(18), 3882–3884 (2012). [CrossRef] [PubMed]
  11. C. Fan, G. Yao, “Mapping local retardance in birefringent samples using polarization sensitive optical coherence tomography,” Opt. Lett. 37(9), 1415–1417 (2012). [CrossRef] [PubMed]
  12. C. Fan, G. Yao, “Mapping local optical axis in birefringent samples using polarization-sensitive optical coherence tomography,” J. Biomed. Opt. 17(11), 110501 (2012). [CrossRef] [PubMed]
  13. C. Fan, G. Yao, “Imaging myocardial fiber orientation using polarization sensitive optical coherence tomography,” Biomed. Opt. Express 4(3), 460–465 (2013). [CrossRef] [PubMed]
  14. C. Fan, G. Yao, “Full-range spectral domain Jones matrix optical coherence tomography using a single spectral camera,” Opt. Express 20(20), 22360–22371 (2012). [CrossRef] [PubMed]
  15. Y. Jiang, K. Pandya, O. Smithies, E. W. Hsu, “Three-dimensional diffusion tensor microscopy of fixed mouse hearts,” Magn. Reson. Med. 52(3), 453–460 (2004). [CrossRef] [PubMed]
  16. L. J. Healy, Y. Jiang, E. W. Hsu, “Quantitative comparison of myocardial fiber structure between mice, rabbit, and sheep using diffusion tensor cardiovascular magnetic resonance,” J. Cardiovasc. Magn. Reson. 13(1), 74 (2011). [CrossRef] [PubMed]
  17. C. Mekkaoui, S. Huang, H. H. Chen, G. Dai, T. G. Reese, W. J. Kostis, A. Thiagalingam, P. Maurovich-Horvat, J. N. Ruskin, U. Hoffmann, M. P. Jackowski, D. E. Sosnovik, “Fiber architecture in remodeled myocardium revealed with a quantitative diffusion CMR tractography framework and histological validation,” J. Cardiovasc. Magn. Reson. 14(1), 70 (2012). [CrossRef] [PubMed]
  18. R. H. Clayton, S. Abdalhamid, R. Bloor, G. Kyprianou, K. Kotagiri, J. Lee, A. Mane, R. White, “Transmural changes in fibre helix angle in normal and failing canine ventricles,” Comput. Cardiol. 37, art. 5738123, 915–918 (2010).
  19. W. J. Karlon, J. W. Covell, A. D. McCulloch, J. J. Hunter, J. H. Omens, “Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras,” Anat. Rec. 252(4), 612–625 (1998). [CrossRef] [PubMed]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.

Figures

Fig. 1 Fig. 2 Fig. 3
 
Fig. 4
 

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited