Toward quantifying the composition of soft tissues by spectral CT with Medipix3
Toward quantifying the composition of soft tissues by spectral CT with Medipix3
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DOI：
10.1118/1.4760773
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发表时间：
2012-11-01
期刊：
影响因子：
3.8
通讯作者：
Anderson, Nigel G.
中科院分区：
文献类型：
--
作者：
Ronaldson, J. Paul;Zainon, Rafidah;Anderson, Nigel G.
目的：确定使用 Medipix3 进行光谱计算机断层扫描 (CT) 对小动物模型和脂肪肝（代谢综合征）和不稳定动脉粥样硬化等疾病的手术标本中软组织中的脂肪、钙和铁进行定量的潜力。方法：将光谱方法应用于使用微型 CT 系统采集的断层扫描数据，该系统结合了带有硅传感器层的 Medipix3 探测器阵列和在 50 kVp 下运行的微焦点 X 射线管。使用多个能量箱对直径 10 毫米的有机玻璃模型进行成像，其中含有脂肪替代品（葵花籽油）以及硝酸铁、氯化钙和碘的水溶液。作者利用 CT 数的光谱特征为软组织成分的分解奠定了基础。在使用和不使用体积守恒约束的情况下，根据信息熵和自由度评估了约束最小二乘法用于量化不同材料组的潜力。使用粥样斑块和小鼠等效模型对测量性能进行定量评估。最后，使用安乐死的小鼠和切除的人动脉粥样硬化斑块对分解方法进行定性评估。结果：对含有组织替代物的体模进行光谱 CT 测量，证实了通过 CT 数的光谱特征区分这些材料的能力。根据信息熵和自由度对性能潜力的评估表明，最多三种材料的某些集合可以通过约束最小二乘法进行分解。然而，数据集中没有足够的信息来区分软组织中的钙和铁。通过能谱 CT 对动脉粥样硬化斑块和小鼠等效体模内的钙浓度和脂肪质量分数进行量化，与标称值密切相关（分别为 R-2 = 0.990 和 R-2 = 0.985）。在安乐死的小鼠和切除的人动脉粥样硬化斑块中，钙和脂肪的区域根据其光谱特征进行了适当的分解。结论：光谱 CT 使用 Medipix3 探测器和硅传感器层，可以使用所提出的约束最小二乘方法对最多三种材料的某些组进行量化。该系统具有一定的独立区分钙、脂肪和水的能力，并且这些已经在脂肪肝和动脉粥样硬化的幻象中进行了量化。在这种配置中，能谱 CT 无法区分软组织内的铁和钙。 (C) 2012 年美国医学物理学家协会。 [http://dx.doi.org/10.1118/1.4760773]
Purpose: To determine the potential of spectral computed tomography (CT) with Medipix3 for quantifying fat, calcium, and iron in soft tissues within small animal models and surgical specimens of diseases such as fatty liver (metabolic syndrome) and unstable atherosclerosis.Methods: The spectroscopic method was applied to tomographic data acquired using a micro-CT system incorporating a Medipix3 detector array with silicon sensor layer and microfocus x-ray tube operating at 50 kVp. A 10 mm diameter perspex phantom containing a fat surrogate (sunflower oil) and aqueous solutions of ferric nitrate, calcium chloride, and iodine was imaged with multiple energy bins. The authors used the spectroscopic characteristics of the CT number to establish a basis for the decomposition of soft tissue components. The potential of the method of constrained least squares for quantifying different sets of materials was evaluated in terms of information entropy and degrees of freedom, with and without the use of a volume conservation constraint. The measurement performance was evaluated quantitatively using atheroma and mouse equivalent phantoms. Finally the decomposition method was assessed qualitatively using a euthanized mouse and an excised human atherosclerotic plaque.Results: Spectral CT measurements of a phantom containing tissue surrogates confirmed the ability to distinguish these materials by the spectroscopic characteristics of their CT number. The assessment of performance potential in terms of information entropy and degrees of freedom indicated that certain sets of up to three materials could be decomposed by the method of constrained least squares. However, there was insufficient information within the data set to distinguish calcium from iron within soft tissues. The quantification of calcium concentration and fat mass fraction within atheroma and mouse equivalent phantoms by spectral CT correlated well with the nominal values (R-2 = 0.990 and R-2 = 0.985, respectively). In the euthanized mouse and excised human atherosclerotic plaque, regions of calcium and fat were appropriately decomposed according to their spectroscopic characteristics.Conclusions: Spectral CT, using the Medipix3 detector and silicon sensor layer, can quantify certain sets of up to three materials using the proposed method of constrained least squares. The system has some ability to independently distinguish calcium, fat, and water, and these have been quantified within phantom equivalents of fatty liver and atheroma. In this configuration, spectral CT cannot distinguish iron from calcium within soft tissues. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4760773]