Elsevier

Academic Radiology

Volume 10, Issue 12, December 2003, Pages 1349-1358
Academic Radiology

Medical image computing
Myocardial delineation via registration in a polar coordinate system1☆

https://doi.org/10.1016/S1076-6332(03)00537-3Get rights and content

Abstract

Rationale and Objectives. Cardiovascular disease is the number one cause of premature death in the western world. Analysis of cardiac function provides clinically useful diagnostic and prognostic information; however, manual analysis of function via delineation is prohibitively time consuming. This article describes a technique for analysis of dynamic magnetic resonance images of the left ventricle using a non-rigid registration algorithm. A manually delineated contour of a single phase was propagated through the dynamic sequence.

Materials and Methods. Short-axis cine magnetic resonance images were resampled into polar coordinates before all the time frames were aligned using a non-rigid registration algorithm. The technique was tested on 10 patient data sets, a total of 1,052 images were analyzed.

Results. Results of this approach were investigated and compared with manual delineation at all phases in the cardiac cycle, and with registration performed in a Cartesian coordinate system. The results correlated very well with manually delineated contours.

Conclusion. A novel approach to the registration and subsequent delineation of cardiac magnetic resonance images has been introduced. For the endocardium, the polar resampling technique correlated well with manual delineation, and better than for images registered without radial resampling in a Cartesian coordinate system. For the epicardium, the difference was not as apparent with both techniques correlating well.

Section snippets

Automated myocardial delineation

When designing an image analysis technique, it makes intuitive sense to use all of the available information to help perform the task. There are essentially three types of information that can be used in this process: anatomical information, acquisition information, and image information. Anatomical information could include, for example, the fact that the left ventricular myocardium is expected to be a closed ring of muscle encompassing the left ventricular blood pool, or that one would expect

Data

Short axis electrocardiogram retrospectively gated steady state free precession SENSE (33) images (Fig 1, top row) were obtained in 10 patients undergoing cardiac MRI for the investigation of ischemic heart disease. The images had eight to nine contiguous slices, taken in blocks of three slices over three breath holds, imaged with slice thickness 8 mm–10 mm, field of view 350 mm × 344 mm–390 mm × 390 mm, acquisition matrix 192 × 192 with 120% phase encode direction sampling, reconstructed to

Results

Figure 2 shows examples of contours produced via registration propagation of segmentations. Examples of the endo- and epicardial volumes (produced by summing the in-slice volumes) for an example patient, are shown in Figure 3, Figure 4. The traces produced via registration evolve in a smooth and physically plausible manner as opposed to the erratic evolution of the manually produced traces. This suggests that, subject to the initial delineation, segmentation propagation via registration

Discussion

We have described a new technique for analysis of left ventricular function from short axis cine cardiac MR images. The technique delineates the epicardial and endocardial boundaries by non-rigid registration of the images across the phases of the cardiac cycle, and propagation of manually delineated boundaries at one phase using the calculated deformation field. The proposed technique is affected by the following issues:

Conclusion

A novel approach to the analysis of cardiac magnetic resonance images has been introduced. Ten sets of patient images were resampled into a polar coordinate system and initial manual delineations were propagated following non-rigid registration of the resampled images. In total, contours were propagated to 1,052 images. Expert delineation time was reduced from around 3 hours for manual delineation to around 9 minutes for the described technique. The resulting propagated contours were then

Acknowledgements

We are grateful to Philips Medical Systems Nederland B.V. Medical Imaging Information Technology-Advanced Development for funding this work, to those at the Imaging Sciences Division for their assistance, and in particular to P. Batchelor for many invaluable discussions.

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    ☆

    Funding provided by EasyVision Advanced Development, Medical Information Technology, Philips Medical Systems, Best, The Netherlands.

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