Blumenfeld Janet, Carballido-Gamio Julio, Krug Roland, Blezek Daniel J, Hancu Ileana, Majumdar Sharmila
Department of Radiology, University of California, 1700 4th St., Suite 203, Box 2520, San Francisco, CA 94107, USA.
Ann Biomed Eng. 2007 Nov;35(11):1924-31. doi: 10.1007/s10439-007-9365-z. Epub 2007 Aug 17.
Magnetic Resonance Imaging (MRI) longitudinal studies conducted to assess changes in tibia bone quality impose strict requirements on the reproducibility of the prescribed region acquired. Registration, the process of aligning two images, is commonly performed on the images after acquisition. However, techniques to improve image registration precision by adjusting scanning parameters prospectively, prior to image acquisition, would be preferred. We have adapted an automatic prospective mutual information based registration algorithm to a MRI longitudinal study of trabecular bone of the tibia and compared it to a post-scan manual registration. Qualitatively, image alignment due to the prospective registration is shown in 2D subtraction images and 3D surface renderings. Quantitatively, the registration performance is demonstrated by calculating the sum of the squares of the subtraction images. Results show that the sum of the squares is lower for the follow up images with prospective registration by an average of 19.37% +/- 0.07 compared to follow up images with post-scan manual registration. Our study found no significant difference between the trabecular bone structure parameters calculated from the post-scan manual registration and the prospective registration images (p > 0.05). All coefficient of variation values for all trabecular bone structure parameters were within a 2-4.5% range which are within values previously reported in the literature. Results suggest that this algorithm is robust enough to be used in different musculoskeletal imaging applications including the hip as well as the tibia.
为评估胫骨骨质变化而进行的磁共振成像(MRI)纵向研究对所获取规定区域的可重复性提出了严格要求。配准,即对齐两幅图像的过程,通常在采集后对图像进行。然而,在图像采集之前通过前瞻性调整扫描参数来提高图像配准精度的技术会更受青睐。我们已将基于自动前瞻性互信息的配准算法应用于胫骨小梁骨的MRI纵向研究,并将其与扫描后手动配准进行比较。定性地,在二维减法图像和三维表面渲染图中展示了前瞻性配准导致的图像对齐情况。定量地,通过计算减法图像的平方和来证明配准性能。结果表明,与扫描后手动配准的后续图像相比,前瞻性配准的后续图像的平方和平均低19.37% +/- 0.07。我们的研究发现,从扫描后手动配准图像和前瞻性配准图像计算出的小梁骨结构参数之间没有显著差异(p > 0.05)。所有小梁骨结构参数的变异系数值均在2 - 4.5%的范围内,这在先前文献报道的值之内。结果表明,该算法足够稳健,可用于包括髋部和胫骨在内的不同肌肉骨骼成像应用。