Correlation between mean gland dose and breast lesions in contrast-enhanced spectral mammography
-
摘要:
目的探讨乳腺病变类型、病变良恶性及病变大小对对比增强乳腺X线摄影(CESM)低能图、高能图及减影后图像的乳腺平均腺体剂量(AGD)的影响。 方法收集2018年2~10月于本院行CESM检查且经过组织学病理学证实的123例女性患者作为研究对象。根据病变良恶性、主要病变类型(非肿块型与肿块型)及肿块型病变大小进行分组,比较不同组患者的低能图AGD、高能图AGD及减影后图像的AGD(减影后图像的AGD为低能图加高能图像AGD的总和)。 结果恶性病变65例,良性病变58例; 肿块型病变86例,非肿块型病变37例。肿块≥2 cm 44例, < 2 cm 42例; 恶性肿块≥2 cm 32例, < 2 cm 25例。恶性病变组无论低能、高能以及减影后的AGD均高于良性病变组,差异具有统计学意义(P < 0.05); 无论良恶性病变,乳腺患侧高能AGD均高于健侧,差异均具有统计学意义(P < 0.05)。肿块型病变组低能、高能及减影后的AGD差异均无统计学意义(P>0.05)。肿块长径≥2 cm组高能、低能及减影后的AGD均高于肿块长径 < 2 cm组,差异有统计学意义(P < 0.05); 其中,恶性肿块长径≥2 cm组的高能图AGD较肿块长径 < 2 cm组高,差异具有统计学意义(P < 0.05)。 结论恶性病变、≥2 cm肿块AGD高于良性病变及 < 2 cm肿块; 无论病变良恶性,患侧高能AGD均高于健侧。 -
关键词:
- 对比增强乳腺X线摄影 /
- 良恶性 /
- 肿块大小 /
- 平均腺体剂量
Abstract:ObjectiveTo investigate the effect of breast lesion type, benign or malignant lesion and lesion size on the average glandular dose (AGD) in low-energy, high-energy and subtraction images of contrast-enhanced mammography. MethodsA total of 123 female patients who underwent CESM examination in our hospital from February 2018 to October 2018 and confirmed by histopathology were enrolled as subjects. According to benign and malignant lesions, major lesion types, and mass lesion size, patients were divided and the total AGD of low energy imaging, high energy imaging and subtracted imaging (the subtraction imaging AGD is the sum of low energy imaging and high energy imaging) were compared in different groups. ResultsThere were 65 cases of malignant lesions and 58 cases of benign lesions. There were 86 cases of mass lesions and 37 cases of non-mass lesions. The tumor size was ≥2 cm in 44 cases, < 2 cm in 42 cases, including malignant mass ≥ 2 cm in 32 cases and < 2 cm in 25 cases. The AGD of the malignant lesion group was higher than the benign lesion group regardless of low energy, high energy and subtraction, and the results were statistically significant (P < 0.05). Both benign and malignant lesions were higher on the affected side than on the healthy side, and the results were statistically significant (P < 0.05). The AGD of the low energy, high energy and subtraction in the mass lesion group were higher than those in the nontumor lesion group, but the results were not statistically significant (P>0.05). The AGD of high energy, low energy and subtraction in the group with a long diameter ≥2 cm was higher than that in a group with a long diameter < 2 cm, and the results were statistically significant (P < 0.05). The AGD was higher than the group with a diameter < 2 cm, and the results were statistically significant (P < 0.05). ConclusionThe AGD of malignant lesions and ≥2 cm masses were higher than that of benign lesions and < 2 cm masses. The high energy AGD of the affected side was higher than that of the healthy side, no matter whether the lesions were benign or malignant. -
表 1 良恶性病变低能图、高能图及减影后图像的AGD
Table 1. AGD of low energy, high energy and subtraction images of benign and malignant lesions (mGy)
AGD/病变性质 平均值 方差 范围 F P 低能图AGD 11.25 0.001 恶性病变 6.10 1.62 3.46~10.88 良性病变 5.20 1.20 3.27~10.03 高能图AGD 5.73 0.018 恶性病变 2.06 0.79 0.96~3.83 良性病变 1.74 0.67 0.99~3.59 减影后AGD 9.73 0.002 恶性病变 8.17 2.35 4.46~14.71 良性病变 7.45 1.81 4.27~13.26 AGD: 乳腺平均腺体质量. 表 2 乳腺良、恶性病变健侧与患侧低能图、高能图及减影后图像的AGD
Table 2. AGD of low energy, high energy and subtraction image of healthy and affected sides of benign and malignant breast lesions (mGy)
病变性质/病变部位 平均值 方差 95%CI t P 恶性病变 低能图AGD患侧-健侧 -0.006 0.54 -0.14~0.12 -0.08 0.929 高能图AGD患侧-健侧 0.11 0.28 0.04~0.18 3.17 0.002 减影后AGD患侧-健侧 0.10 0.77 -0.08~0.29 1.12 0.266 良性病变 低能图AGD患侧-健侧 0.02 0.43 -0.08~0.13 0.42 0.670 高能图AGD患侧-健侧 0.06 0.21 0.01~0.12 2.38 0.020 减影后AGD患侧-健侧 0.09 0.60 -0.06~0.25 1.15 0.251 表 3 乳腺肿块型病变与非肿块型病变的AGD对比
Table 3. Comparison ofAGD between breast mass lesions and non-mass lesions (mGy)
AGD/病变类型 平均值 方差 范围 F P 低能图AGD 1.55 0.215 肿块型病变 5.75 1.57 3.27~10.88 非肿块型病变 5.40 1.03 3.39~7.96 高能图AGD 1.57 0.212 肿块型病变 1.95 0.80 0.96~3.83 非肿块型病变 1.77 0.56 1.00~3.10 减影后AGD 1.66 0.200 肿块型病变 7.71 2.32 4.27~14.71 非肿块型病变 7.18 1.48 4.41~10.52 表 4 乳腺肿块型病变长径≥2 cm组与长径 < 2 cm组的AGD对比
Table 4. Comparison of AGD between long diameter ≥2 cm group and long diameter < 2 cm group of breast mass lesions (mGy)
AGD/病变长径 平均值 方差 范围 F P 低能图AGD ≥2 cm组 6.20 1.76 3.31~10.88 7.53 0.007 < 2 cm组 5.30 1.21 3.27~8.63 高能图AGD ≥2 cm组 2.20 0.88 0.96~3.83 11.08 0.001 < 2 cm组 1.66 0.59 0.99~3.25 减影后AGD ≥2 cm组 8.41 2.58 4.31~14.71 9.05 0.003 < 2 cm组 6.96 1.77 4.27~11.88 表 5 乳腺恶性肿块型病变长径≥2 cm组与长径 < 2 cm组的AGD对比
Table 5. Comparison of AGD between long diameter ≥2 cm group and long diameter < 2 cm group of breast malignant mass lesions (mGy)
AGD/病变长径 平均值 方差 范围 F P 低能图AGD ≥2 cm组 6.39 1.84 3.63~10.88 1.89 0.174 < 2 cm组 5.78 1.29 3.46~8.63 高能图AGD ≥2 cm组 2.28 0.86 0.96~3.83 4.34 0.042 < 2 cm组 1.84 0.65 1.00~3.25 减影后AGD ≥2 cm组 8.67 2.64 4.63~14.71 2.70 0.106 < 2 cm组 7.63 1.90 4.46~11.88 -
[1] Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017[J]. CA Cancer J Clin, 2017, 67(1): 7-30. doi: 10.3322/caac.21387 [2] 杨行, 张雪琴, 袁元, 等. 对比增强能谱乳腺X线摄影在致密型乳腺疾病中的诊断价值[J]. 影像科学与光化学, 2020, 38(2): 296-300. https://www.cnki.com.cn/Article/CJFDTOTAL-GKGH202002022.htm [3] Mori M, Akashi-Tanaka S, Suzuki S, et al. Diagnostic accuracy of contrast-enhanced spectral mammography in comparison to conventional full-field digital mammography in a population of women with dense breasts[J]. Breast Cancer, 2017, 24(1): 104-10. doi: 10.1007/s12282-016-0681-8 [4] Jong RA, Yaffe MJ, Skarpathiotakis M, et al. Contrast-enhanced digital mammography: initial clinical experience[J]. Radiology, 2003, 228(3): 842-50. doi: 10.1148/radiol.2283020961 [5] 张征委, 金彪. 对比增强乳腺X线成像技术与应用[J]. 国际医学放射学杂志, 2018, 41(6): 705-8. https://www.cnki.com.cn/Article/CJFDTOTAL-GWLC201806022.htm [6] 沈茜刚, 周良平, 郑晓静, 等. 对比增强能谱乳腺X线摄影的辐射剂量分析[J]. 中国癌症杂志, 2017, 27(12): 940-5. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGAZ201712005.htm [7] Zanardo M, Cozzi A, Trimboli RM, et al. Technique, protocols and adverse reactions for contrast-enhanced spectral mammography (CESM): a systematic review[J]. Insights Imaging, 2019, 10(1): 76. doi: 10.1186/s13244-019-0756-0 [8] Patel BK, Lobbes MBI, Lewin J. Contrast enhanced spectral mammography: a review[J]. Semin Ultrasound CT MR, 2018, 39 (1): 70-9. doi: 10.1053/j.sult.2017.08.005 [9] Bhimani C, Matta D, Roth RG, et al. Contrast-enhanced spectral mammography: technique, indications, and clinical applications[J]. Acad Radiol, 2017, 24(1): 84-8. doi: 10.1016/j.acra.2016.08.019 [10] Sorin V, Yagil Y, Shalmon A, et al. Background parenchymal enhancement at contrast-enhanced spectral mammography (CESM) as a breast cancer risk factor[J]. Acad Radiol, 2020, 27(9): 1234-40. doi: 10.1016/j.acra.2019.10.034 [11] Lalji UC, Houben IP, Prevos R, et al. Contrast-enhanced spectral mammography in recalls from the Dutch breast cancer screening program: validation of results in a large multireader, multicase study [J]. Eur Radiol, 2016, 26(12): 4371-9. doi: 10.1007/s00330-016-4336-0 [12] Sogani J, Mango VL, Keating D, et al. Contrast-enhanced mammography: past, present, and future[J]. Clin Imaging, 2021, 69: 269-79. doi: 10.1016/j.clinimag.2020.09.003 [13] Polat DS, Evans WP, Dogan BE. Contrast-enhanced digital mammography: technique, clinical applications, and pitfalls[J]. AJR Am J Roentgenol, 2020, 215(5): 1267-78. doi: 10.2214/AJR.19.22412 [14] 文婵娟, 徐维敏, 曾辉, 等. 对比增强X线摄影对乳腺可疑病变的诊断价值[J]. 中华放射学杂志, 2019, 53(9): 737-41. https://cdmd.cnki.com.cn/Article/CDMD-10285-1020418725.htm [15] 姜婷婷, 张盛箭, 李瑞敏, 等. 对比增强能谱X线摄影对乳腺疾病的诊断价值[J]. 中华放射学杂志, 2017, 51(4): 273-8. https://www.cnki.com.cn/Article/CJFDTOTAL-SCYX202010019.htm [16] Jeukens CR, Lalji UC, Meijer E, et al. Radiation exposure of contrastenhanced spectral mammography compared with full- field digital mammography[J]. Invest Radiol, 2014, 49(10): 659-65. doi: 10.1097/RLI.0000000000000068 [17] Fredenberg E, Willsher P, Moa, et al. Measurement of breast-tissue Xray attenuation by spectral imaging: fresh and fixed normal and malignant tissue[J]. Phys Med Biol, 2018, 63(23): 235003. doi: 10.1088/1361-6560/aaea83 [18] Fredenberg E. Spectral and dual-energy X-ray imaging for medical applications[J]. Nucl Inst Methods Phys ResA, 2018, 878: 74-87. doi: 10.1016/j.nima.2017.07.044 [19] Ma L, Lin XJ, Lai BJ, et al. Additive value of exposure parameters for breast cancer diagnosis in digital mammography[J]. Eur Radiol, 2020. DOI: 10.1007/s00330-020-07311-9. [20] Gail MH, Brinton LA, Byar DP, et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually[J]. J Natl Cancer Inst, 1989, 81(24): 1879-86. doi: 10.1093/jnci/81.24.1879 [21] Tyrer J, Duffy SW, Cuzick J. A breast cancer prediction model incorporating familial and personal risk factors[J]. Stat Med, 2004, 23(7): 1111-30. doi: 10.1002/sim.1668 [22] Li H, Mendel KR, Lan L, et al. Digital mammography in breast cancer: additive value of radiomics of breast parenchyma[J]. Radiology, 2019, 291(1): 15-20. doi: 10.1148/radiol.2019181113 [23] Li X, Qin G, He Q, et al. Digital breast tomosynthesis versus digital mammography: integration of image modalities enhances deep learning-based breast mass classification[J]. Eur Radiol, 2020, 30 (2): 778-88. doi: 10.1007/s00330-019-06457-5 [24] Zheng B, Sumkin JH, Zuley ML, et al. Bilateral mammographic density asymmetry and breast cancer risk: a preliminary assessment [J]. Eur J Radiol, 2012, 81(11): 3222-8. doi: 10.1016/j.ejrad.2012.04.018
计量
- 文章访问数: 481
- HTML全文浏览量: 280
- PDF下载量: 7
- 被引次数: 0