一种用于扩大的椭圆锥束计算机断层扫描视场的新型离轴扫描方法。

A novel off-axis scanning method for an enlarged ellipse cone-beam computed tomography field of view.

机构信息

Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania 15232, USA.

出版信息

Med Phys. 2010 Dec;37(12):6233-9. doi: 10.1118/1.3514130.

DOI:10.1118/1.3514130

PMID:21302780

Abstract

PURPOSE

Current on-board imaging systems commonly used by modern linear accelerators (LINACs) have a limited field of view (FOV) for a cone-beam CT (CBCT) scan, which is typically less than 50 cm. Consequently, truncation artifacts often occur for large patients. The goal of this work is to investigate a novel method to increase the FOV for current on-board CBCT systems.

METHODS

When a large patient is scanned with CBCT, any region outside the FOV is only partially sampled within a short range of projection angles, and at other angles no x-ray beams may pass through that region. To increase the sampling rate for the region outside the FOV, we have designed a new source trajectory by shifting the center of rotation during a CBCT scan. This resulted in a reduced sampling rate at the central area and increased sampling rate at the edges. The tradeoff led to a more balanced sampling for an enlarged FOV. An iterative algorithm was also developed to reconstruct the CT image under the new sampling scheme using a compressed sensing technique.

RESULTS

The method was validated by numerical simulations mimicking a Varian Trilogy CBCT system, and it was found that artifact-free images could be obtained with the FOV as large as 80 cm.

CONCLUSIONS

The new CT scanning trajectory can be easily realized under current clinical setup with little modification of the control system, and this can be useful for treating obese patients.

摘要

目的

现代直线加速器（LINAC）中常用的当前机载成像系统，其锥形束 CT（CBCT）扫描的视场（FOV）有限，通常小于 50cm。因此，对于体型较大的患者，通常会出现截断伪影。本研究旨在探讨一种新的方法，以增加当前机载 CBCT 系统的 FOV。

方法

当对体型较大的患者进行 CBCT 扫描时，视野外的任何区域在短投影角度范围内仅被部分采样，而在其他角度，射线束可能无法穿过该区域。为了增加视野外区域的采样率，我们通过在 CBCT 扫描期间移动旋转中心，设计了一种新的源轨迹。这导致中心区域的采样率降低，边缘区域的采样率增加。这种权衡导致了更大 FOV 的更均衡采样。还开发了一种迭代算法，以便在新的采样方案下使用压缩感知技术重建 CT 图像。