Lin Yuan, Samei Ehsan
Carestream Health Inc. , Division of Research and Innovations, 1049 Ridge Road West, Rochester, New York 14615, United States.
Duke University , Carl E. Ravin Advanced Imaging Lab, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705, United States.
J Med Imaging (Bellingham). 2016 Jul;3(3):033503. doi: 10.1117/1.JMI.3.3.033503. Epub 2016 Aug 23.
Dynamic perfusion imaging can provide the morphologic details of the scanned organs as well as the dynamic information of blood perfusion. However, due to the polyenergetic property of the x-ray spectra, beam hardening effect results in undesirable artifacts and inaccurate CT values. To address this problem, this study proposes a segmentation-free polyenergetic dynamic perfusion imaging algorithm (pDP) to provide superior perfusion imaging. Dynamic perfusion usually is composed of two phases, i.e., a precontrast phase and a postcontrast phase. In the precontrast phase, the attenuation properties of diverse base materials (e.g., in a thorax perfusion exam, base materials can include lung, fat, breast, soft tissue, bone, and metal implants) can be incorporated to reconstruct artifact-free precontrast images. If patient motions are negligible or can be corrected by registration, the precontrast images can then be employed as a priori information to derive linearized iodine projections from the postcontrast images. With the linearized iodine projections, iodine perfusion maps can be reconstructed directly without the influence of various influential factors, such as iodine location, patient size, x-ray spectrum, and background tissue type. A series of simulations were conducted on a dynamic iodine calibration phantom and a dynamic anthropomorphic thorax phantom to validate the proposed algorithm. The simulations with the dynamic iodine calibration phantom showed that the proposed algorithm could effectively eliminate the beam hardening effect and enable quantitative iodine map reconstruction across various influential factors. The error range of the iodine concentration factors ([Formula: see text]) was reduced from [Formula: see text] for filtered back-projection (FBP) to [Formula: see text] for pDP. The quantitative results of the simulations with the dynamic anthropomorphic thorax phantom indicated that the maximum error of iodine concentrations can be reduced from [Formula: see text] for FBP to less than [Formula: see text] for pDP, which suggested that the proposed algorithm could not only effectively eliminate beam hardening artifacts but also significantly reduce the influence of the metal artifacts and accurately reconstruct the iodine map regardless of the influential factors. A segmentation-free polyenergetic dynamic perfusion imaging algorithm was proposed and validated via simulations. This method can accurately reconstruct artifact-free iodine maps for quantitative analyses.
动态灌注成像可以提供扫描器官的形态学细节以及血液灌注的动态信息。然而,由于X射线光谱的多能特性,束硬化效应会导致不良伪影和不准确的CT值。为了解决这个问题,本研究提出了一种无分割的多能动态灌注成像算法(pDP)以提供卓越的灌注成像。动态灌注通常由两个阶段组成,即对比剂前阶段和对比剂后阶段。在对比剂前阶段,可以纳入不同基础材料的衰减特性(例如,在胸部灌注检查中,基础材料可以包括肺、脂肪、乳腺、软组织、骨骼和金属植入物)来重建无伪影的对比剂前图像。如果患者运动可忽略不计或可通过配准校正,那么对比剂前图像可作为先验信息,从对比剂后图像中导出线性化碘投影。利用线性化碘投影,可以直接重建碘灌注图,而不受各种影响因素的影响,如碘的位置、患者体型、X射线光谱和背景组织类型。在动态碘校准体模和动态人体胸部体模上进行了一系列模拟,以验证所提出的算法。对动态碘校准体模的模拟表明,所提出的算法可以有效消除束硬化效应,并能够在各种影响因素下进行定量碘图重建。碘浓度因子([公式:见原文])的误差范围从滤波反投影(FBP)的[公式:见原文]降低到pDP的[公式:见原文]。对动态人体胸部体模的模拟定量结果表明,碘浓度的最大误差可以从FBP的[公式:见原文]降低到pDP的小于[公式:见原文],这表明所提出的算法不仅可以有效消除束硬化伪影,还可以显著降低金属伪影的影响,并且无论影响因素如何,都能准确重建碘图。提出了一种无分割的多能动态灌注成像算法,并通过模拟进行了验证。该方法可以准确重建无伪影的碘图用于定量分析。