Jadick Giavanna, Schlafly Geneva, La Rivière Patrick J
University of Chicago, Department of Radiology, Chicago, Illinois, United States.
J Med Imaging (Bellingham). 2024 Mar;11(2):023501. doi: 10.1117/1.JMI.11.2.023501. Epub 2024 Mar 4.
Single-energy computed tomography (CT) often suffers from poor contrast yet remains critical for effective radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) X-ray sources and thus already possess hardware for dual-energy (DE) CT. There is unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts.
A single-line integral toy model was designed for computing basis material signal-to-noise ratio (SNR) using estimation theory. Five dose-matched spectra (3 kV, 2 MV) and three variables were considered: spectral combination, spectral dose allocation, and object material composition. The single-line model was extended to a simulated CT acquisition of an anthropomorphic phantom with and without a metal implant. Basis material sinograms were computed and synthesized into virtual monoenergetic images (VMIs). MV-kV and kV-kV VMIs were compared with single-energy images.
The 80 kV-140 kV pair typically yielded the best SNRs, but for bone thicknesses , the detunedMV-80 kV pair surpassed it. Peak MV-kV SNR was achieved with dose allocated to the MV spectrum. In CT simulations of the pelvis with a steel implant, MV-kV VMIs yielded a higher contrast-to-noise ratio (CNR) than single-energy CT and kV-kV DE-CT. Without steel, the MV-kV VMIs produced higher contrast but lower CNR than single-energy CT.
This work analyzes MV-kV DE-CT imaging and assesses its potential advantages. The technique may be used for metal artifact correction and generation of VMIs with higher native contrast than single-energy CT. Improved denoising is generally necessary for greater CNR without metal.
单能计算机断层扫描(CT)常常存在对比度不佳的问题,但对于有效的放射治疗而言仍至关重要。现代治疗系统通常配备有兆伏(MV)和千伏(kV)X射线源,因此已经具备了双能(DE)CT的硬件设备。在放射治疗环境中,利用MV-kV双能CT提高图像对比度存在尚未被探索的潜力。
设计了一个单线积分简化模型,用于运用估计理论计算基础物质的信噪比(SNR)。考虑了五个剂量匹配的能谱(3 kV、2 MV)以及三个变量:能谱组合、能谱剂量分配和物体材料成分。将单线模型扩展到对有和没有金属植入物的人体模型进行模拟CT采集。计算基础物质的正弦图并合成虚拟单能图像(VMI)。将MV-kV和kV-kV的VMI与单能图像进行比较。
80 kV-140 kV的组合通常产生最佳的SNR,但对于骨骼厚度而言,失谐的MV-80 kV组合超过了它。当将 剂量分配给MV能谱时,可实现MV-kV的峰值SNR。在带有钢植入物的骨盆CT模拟中,MV-kV的VMI产生的对比度噪声比(CNR)高于单能CT和kV-kV双能CT。没有钢植入物时,MV-kV的VMI产生的对比度高于单能CT,但CNR较低。
本研究分析了MV-kV双能CT成像并评估了其潜在优势。该技术可用于金属伪影校正,并生成比单能CT具有更高固有对比度的VMI。对于在没有金属的情况下获得更高的CNR,通常需要改进去噪处理。