Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, China.
Med Phys. 2018 Oct;45(10):4461-4470. doi: 10.1002/mp.13169. Epub 2018 Sep 22.
Cone beam CT (CBCT) has been widely used in radiation therapy. However, its main application is still to acquire anatomical information for patient positioning. This study proposes a multienergy element-resolved (MEER) CBCT framework that employs energy-resolved data acquisition on a conventional CBCT platform and then simultaneously reconstructs images of x-ray attenuation coefficients, electron density relative to water (rED), and elemental composition (EC) to support advanced applications.
The MEER-CBCT framework is realized on a Varian TrueBeam CBCT platform using a kVp-switching scanning scheme. A simultaneous image reconstruction and elemental decomposition model is formulated as an optimization problem. The objective function uses a least square term to enforce fidelity between x-ray attenuation coefficients and projection measurements. Spatial regularization is introduced via sparsity under a tight wavelet-frame transform. Consistency is imposed among rED, EC, and attenuation coefficients and inherently serves as a regularization term along the energy direction. The EC is further constrained by a sparse combination of ECs in a dictionary containing tissues commonly existing in humans. The optimization problem is solved by a novel alternating-direction minimization scheme. The MEER-CBCT framework was tested in a simulation study using an NCAT phantom and an experimental study using a Gammex phantom.
MEER-CBCT framework was successfully realized on a clinical Varian TrueBeam onboard CBCT platform with three energy channels of 80, 100, and 120 kVp. In the simulation study, the attenuation coefficient image achieved a structural similarity index of 0.98, compared to 0.61 for the image reconstructed by the conventional conjugate gradient least square (CGLS) algorithm, primarily because of reduction in artifacts. In the experimental study, the attenuation image obtained a contrast-to-noise ratio ≥60, much higher than that of CGLS results (~16) because of noise reduction. The median errors in rED and EC were 0.5% and 1.4% in the simulation study and 1.4% and 2.3% in the experimental study.
We proposed a novel MEER-CBCT framework realized on a clinical CBCT platform. Simulation and experimental studies demonstrated its capability to simultaneously reconstruct x-ray attenuation coefficient, rED, and EC images accurately.
锥形束 CT（CBCT）已广泛应用于放射治疗。然而，其主要应用仍然是获取患者定位的解剖学信息。本研究提出了一种多能元素分辨（MEER）CBCT 框架，该框架在常规 CBCT 平台上采用能量分辨数据采集，然后同时重建 X 射线衰减系数、相对水的电子密度（rED）和元素组成（EC）图像，以支持先进的应用。
MEER-CBCT 框架是在瓦里安 TrueBeam CBCT 平台上使用 kVp 切换扫描方案实现的。同时的图像重建和元素分解模型被表述为一个优化问题。目标函数使用最小二乘项来强制 X 射线衰减系数和投影测量之间的一致性。空间正则化是通过紧小波框架变换下的稀疏性引入的。rED、EC 和衰减系数之间的一致性被内在地作为沿能量方向的正则化项。EC 进一步受到包含人体中常见组织的字典中 EC 稀疏组合的约束。优化问题通过一种新颖的交替方向最小化方案求解。MEER-CBCT 框架在 NCAT 体模的仿真研究和 Gammex 体模的实验研究中进行了测试。
MEER-CBCT 框架成功地在临床瓦里安 TrueBeam 车载 CBCT 平台上实现，具有 80、100 和 120 kVp 三个能量通道。在仿真研究中，与传统共轭梯度最小二乘法（CGLS）算法重建的图像（0.61）相比，衰减系数图像的结构相似性指数达到 0.98，主要是因为伪影减少。在实验研究中，衰减图像获得的对比度噪声比≥60，远高于 CGLS 结果（~16），因为噪声降低。在仿真研究中，rED 和 EC 的中位数误差分别为 0.5%和 1.4%，在实验研究中，rED 和 EC 的中位数误差分别为 1.4%和 2.3%。
我们提出了一种在临床 CBCT 平台上实现的新型 MEER-CBCT 框架。仿真和实验研究表明，该框架能够准确地同时重建 X 射线衰减系数、rED 和 EC 图像。
