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Development of 3D patient-based super-resolution digital breast phantoms using machine learning.利用机器学习开发基于 3D 患者的超高分辨率数字乳腺体模。
Phys Med Biol. 2018 Nov 12;63(22):225017. doi: 10.1088/1361-6560/aae78d.
2
Patient-based 4D digital breast phantom for perfusion contrast-enhanced breast CT imaging.基于患者的 4D 数字乳腺体模用于灌注对比增强乳腺 CT 成像。
Med Phys. 2018 Oct;45(10):4448-4460. doi: 10.1002/mp.13156. Epub 2018 Sep 19.
3
Internal breast dosimetry in mammography: Monte Carlo validation in homogeneous and anthropomorphic breast phantoms with a clinical mammography system.乳腺钼靶摄影中乳腺内剂量测定:使用临床乳腺钼靶摄影系统在均匀和拟人化乳腺模型中的蒙特卡罗验证
Med Phys. 2018 Jun 29;45(8):3950-61. doi: 10.1002/mp.13069.
4
Contrast-enhanced cone-beam breast-CT (CBBCT): clinical performance compared to mammography and MRI.对比增强锥形束乳腺 CT(CBBCT):与乳腺 X 线摄影和 MRI 的临床性能比较。
Eur Radiol. 2018 Sep;28(9):3731-3741. doi: 10.1007/s00330-018-5376-4. Epub 2018 Mar 28.
5
Internal breast dosimetry in mammography: Experimental methods and Monte Carlo validation with a monoenergetic x-ray beam.乳腺内剂量测定在乳腺 X 线摄影中的应用:使用单能 X 射线束的实验方法和蒙特卡罗验证。
Med Phys. 2018 Apr;45(4):1724-1737. doi: 10.1002/mp.12792. Epub 2018 Feb 23.
6
Contrast Enhancement on Cone-Beam Breast-CT for Discrimination of Breast Cancer Immunohistochemical Subtypes.锥束乳腺CT上的对比增强用于鉴别乳腺癌免疫组织化学亚型
Transl Oncol. 2017 Dec;10(6):904-910. doi: 10.1016/j.tranon.2017.08.010. Epub 2017 Sep 22.
7
Generation and analysis of clinically relevant breast imaging x-ray spectra.生成和分析临床相关的乳腺 X 射线光谱。
Med Phys. 2017 Jun;44(6):2148-2160. doi: 10.1002/mp.12222. Epub 2017 May 4.
8
Incidence and Mortality and Epidemiology of Breast Cancer in the World.全球乳腺癌的发病率、死亡率及流行病学
Asian Pac J Cancer Prev. 2016;17(S3):43-6. doi: 10.7314/apjcp.2016.17.s3.43.
9
X-ray scatter correction method for dedicated breast computed tomography: improvements and initial patient testing.专用乳腺计算机断层扫描的X射线散射校正方法:改进与初步患者测试
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Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195.用于成像研究的蒙特卡罗参考数据集:美国医学物理学家协会研究委员会任务组195报告执行摘要
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面向癌症的 4D 专用乳腺 CT 灌注成像:计算机模拟图像的开发和验证。

Towards 4D dedicated breast CT perfusion imaging of cancer: development and validation of computer simulated images.

机构信息

Department of Radiology and Nuclear Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB Nijmegen, The Netherlands.

出版信息

Phys Med Biol. 2019 Dec 13;64(24):245004. doi: 10.1088/1361-6560/ab55ac.

DOI:10.1088/1361-6560/ab55ac
PMID:31703216
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10424558/
Abstract

Dedicated breast CT is a fully tomographic breast imaging modality with potential for various applications throughout breast cancer care. If implemented to perform dynamic contrast-enhanced (CE) imaging (4D breast CT), it could be useful to obtain functional information at high combined spatio-temporal resolution. Before developing a 4D dedicated breast CT system, a computer simulation method for breast CT perfusion imaging is proposed. The simulation uses previously developed patient-based 4D digital breast phantoms, and generates realistic images with the selected acquisition parameters, allowing to investigate the effect of different acquisition settings on image quality. The simulation pipeline includes all steps of the image generation process, from ray tracing and scatter map generation, to the addition of realistic resolution losses and noise models. The pipeline was validated against experimental measurements performed on physical phantoms with a dedicated breast CT system, in terms of average error compared to ground truth projections (6.0%  ±  1.65%), Hounsfield unit (HU) values in a homogeneous phantom (acquired: -149 HU  ±  2 HU; simulated:  -140 HU  ±  2 HU), signal-to-noise ratio (SNR) (average error 6.7%  ±  4.2%), noise power spectra (NPS) (average error 4.3%  ±  2.5%), modulation transfer function (MTF) (average error 8.4%  ±  7.2%), and attenuation of different adipose/glandular equivalent mixtures (average error 6.9%  ±  4.0%) and glandular plus iodinated contrast medium concentrations equivalent mixtures (average error of 9.1%  ±  9.0%). 4D patient images were then simulated for different 4D digital breast phantoms at different air kerma levels to determine the effect of noise on the extracted tumor perfusion curves. In conclusion, the proposed pipeline could simulate images with a good level of realism, resulting in a tool that can be used for the design, development, and optimization of a 4D dedicated breast CT system.

摘要

专用乳腺 CT 是一种完全层析的乳腺成像方式,在乳腺癌治疗的各个方面都具有潜在的应用。如果将其用于进行动态对比增强(CE)成像(4D 乳腺 CT),则可以在高的空间和时间分辨率下获得功能信息。在开发 4D 专用乳腺 CT 系统之前,提出了一种用于乳腺 CT 灌注成像的计算机模拟方法。该模拟使用以前开发的基于患者的 4D 数字乳腺体模,并使用所选采集参数生成真实图像,从而可以研究不同采集设置对图像质量的影响。模拟流水线包括从射线追踪和散射图生成到添加真实分辨率损失和噪声模型的所有图像生成过程步骤。该流水线针对具有专用乳腺 CT 系统的物理体模进行了实验测量,通过与真实投影的平均误差(6.0%±1.65%)、均匀体模中的 Hounsfield 单位(HU)值(获得:-149 HU±2 HU;模拟:-140 HU±2 HU)、信噪比(SNR)(平均误差 6.7%±4.2%)、噪声功率谱(NPS)(平均误差 4.3%±2.5%)、调制传递函数(MTF)(平均误差 8.4%±7.2%)和不同脂肪/腺体等效混合物的衰减(平均误差 6.9%±4.0%)以及腺体加碘化对比剂浓度等效混合物(平均误差 9.1%±9.0%)进行了验证。然后为不同的 4D 数字乳腺体模模拟了 4D 患者图像,以在不同的空气比释动能水平下确定噪声对提取的肿瘤灌注曲线的影响。总之,所提出的流水线可以模拟具有良好逼真度的图像,从而成为用于设计、开发和优化 4D 专用乳腺 CT 系统的工具。