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双能计算机断层扫描在乳腺癌随访评估中的应用:虚拟单能图像与碘图的比较

Dual-Energy Computed Tomography for Evaluation of Breast Cancer Follow-Ups: Comparison of Virtual Monoenergetic Images and Iodine-Map.

作者信息

Li Jun-Xian, Xie Feng-Ji, Chen Chia-Hui, Chen Kuan-Ming, Tsai Chia-Jung

机构信息

Department of Radiology, Yuan's General Hospital, No. 162, Chenggong 1st Rd, Lingya District, Kaohsiung City 802, Taiwan.

Department of Medical Imaging and Radiological Sciences, I-Shou University, No. 1, Section 1, Xuecheng Rd, Dashu District, Kaohsiung City 84001, Taiwan.

出版信息

Diagnostics (Basel). 2022 Apr 10;12(4):946. doi: 10.3390/diagnostics12040946.

Abstract

Differentiating tumor tissue from dense breast tissue can be difficult. Dual-energy CT (DECT) could be suitable for making diagnoses at breast cancer follow-ups. This study investigated the contrast in DECT images and iodine maps for patients with breast cancer being followed-up. Chest CT images captured in 2019 were collected. Five cases of metastatic breast cancer in the lungs were analyzed; the contrast-to-noise ratio (for breast tissue and muscle: CNRb and CNRm, respectively), tumor-to-breast mammary gland ratio (T/B), and tumor-to-muscle ratio (T/M) were calculated. For 84 cases of no metastasis, monochromatic spectral and iodine maps were obtained to compare differences under various breast densities using the K-means algorithm. The optimal T/B, T/M, and CNRb (related to mammary glands) were achieved for the 40-keV image. Conversely, CNRm (related to lungs) was better for higher energy. The optimal balance was achieved at 80 keV. T/B, T/M, and CNR were excellent for iodine maps, particularly for density > 25%. In conclusion, energy of 80 keV is the parameter most suitable for observing the breast and lungs simultaneously by using monochromatic spectral images. Adding iodine mapping can be appropriate when a patient’s breast density is greater than 25%.

摘要

区分肿瘤组织与致密乳腺组织可能具有挑战性。双能CT(DECT)可能适用于乳腺癌随访中的诊断。本研究调查了乳腺癌随访患者DECT图像和碘图中的对比度。收集了2019年采集的胸部CT图像。分析了5例肺转移乳腺癌病例;计算了对比噪声比(分别针对乳腺组织和肌肉:CNRb和CNRm)、肿瘤与乳腺腺体比值(T/B)以及肿瘤与肌肉比值(T/M)。对于84例无转移病例,使用K均值算法获得单色光谱图和碘图,以比较不同乳腺密度下的差异。40 keV图像实现了最佳的T/B、T/M和CNRb(与乳腺腺体相关)。相反,较高能量下的CNRm(与肺相关)更佳。80 keV时实现了最佳平衡。碘图的T/B、T/M和CNR均表现出色,尤其是对于密度>25%的情况。总之,80 keV能量是通过使用单色光谱图像同时观察乳腺和肺的最合适参数。当患者乳腺密度大于25%时,添加碘图可能是合适的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abea/9028705/ea3d6aea37e4/diagnostics-12-00946-g001.jpg

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