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中华乳腺病杂志(电子版)

中华乳腺病杂志(电子版) ›› 2021, Vol. 15 ›› Issue (05) : 275 -282. doi: 10.3877/cma.j.issn.1674-0807.2021.05.002

论著

全视野数字化乳腺X线联合断层摄影对不可触及乳腺病灶的诊断价值
张云锁1, 池华茂1,†(), 孟砺实2, 丁玉兰2, 范丽莉1, 彭金娟1, 陶凯1, 杨卉1, 王水3, 肇毅3   
  1. 1. 212000　江苏省镇江市妇幼保健院乳腺外科
    2. 212000　江苏省镇江市妇幼保健院影像科
    3. 210029　南京，江苏省人民医院乳腺中心
  • 收稿日期:2020-07-09 出版日期:2021-10-01
  • 通信作者: 池华茂
  • 基金资助:
    江苏省妇幼健康科研项目(F201681)

Full-field digital mammography combined with digital breast tomosynthesis in the diagnosis of nonpalpable breast lesions

Yunsuo Zhang1, Huamao Chi1,†(), Lishi Meng2, Yulan Ding2, Lili Fan1, Jinjuan Peng1, Kai Tao1, Hui Yang1, Shui Wang3, Yi Zhao3   

  1. 1. Department of Breast Surgery, Zhenjiang Women and Children’s Hospital, Zhenjiang 212000, Jiangsu Province, China
    2. Department of Radiology, Zhenjiang Women and Children’s Hospital, Zhenjiang 212000, Jiangsu Province, China
    3. Breast Disease Center, Jiangsu Provincial Hospital, Nanjing 210029, China
  • Received:2020-07-09 Published:2021-10-01
  • Corresponding author: Huamao Chi
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引用本文：

张云锁, 池华茂, 孟砺实, 丁玉兰, 范丽莉, 彭金娟, 陶凯, 杨卉, 王水, 肇毅. 全视野数字化乳腺X线联合断层摄影对不可触及乳腺病灶的诊断价值[J/OL]. 中华乳腺病杂志(电子版), 2021, 15(05): 275-282.

Yunsuo Zhang, Huamao Chi, Lishi Meng, Yulan Ding, Lili Fan, Jinjuan Peng, Kai Tao, Hui Yang, Shui Wang, Yi Zhao. Full-field digital mammography combined with digital breast tomosynthesis in the diagnosis of nonpalpable breast lesions[J/OL]. Chinese Journal of Breast Disease(Electronic Edition), 2021, 15(05): 275-282.

目的

探讨全视野数字乳腺X线(FFDM)联合数字断层(DBT)摄影对乳腺不可触及病灶的诊断价值。

方法

本前瞻性研究纳入2017年6月至2019年12月镇江市妇幼保健院临床查体阴性而影像学检查发现乳腺病灶的患者126例，共计137处病灶。术前分别采用FFDM和FFDM+DBT检查进行独立诊断，入组后行导丝定位切除活组织检查、穿刺活组织检查或真空辅助旋切，标本送病理学检查。以病理结果为金标准，绘制受试者工作特征(ROC)曲线，计算曲线下面积(AUC),用McNemar检验、Fisher精确概率法或χ2检验比较2种方法的诊断效能。采用Bowker检验比较2种方法对肿块型病灶的边缘特征检查结果差异。

结果

FFDM和FFDM+DBT对137处不可触及乳腺病灶的总检出率分别为86.9%(119/137)、94.2%(129/137)，差异有统计学意义(χ2＝4.249，P＝0.039)；在致密性乳腺中的病灶检出率分别为79.8%(71/89)、91.0%(81/89)，FFDM+DBT优于FFDM(χ2＝4.504，P＝0.034);对非致密性腺体，2种检查均可检出所有病灶。以病理结果为金标准，FFDM+DBT对全部病灶的诊断准确率高于FFDM[92.0%(126/137)比78.8%(108/137)，χ2＝9.485, P＝0.002]；FFDM+DBT的AUC为0.976±0.010 (95%CI：0.934~0.994), FFDM的AUC为0.821±0.037 (95%CI：0.747~0.882)，差异具有统计学意义(Z＝4.131，P<0.001)。对于致密性腺体，FFDM+DBT的敏感度、准确率和阴性预测值均优于FFDM(P＝0.008、0.012、0.037)；对于非致密性腺体的检查，两种方法的各指标比较，差异均无统计学意义(P均>0.050)。对于112个肿块型病灶，FFDM+DBT的特异度、准确率及阳性预测值均高于FFDM (P＝0.011；χ2＝9.333、5.829；P＝0.002、0.016)；其中，对62个良性病灶，FFDM及FFDM+DBT的清晰边缘检出率分别为54.8%(34/62)、80.6% (50/62)，差异有统计学意义( Bowker T ＝18.000，P<0.001)；对50个恶性病灶，FFDM及FFDM+DBT的毛刺征检出率分别为50%(25/50)、72%(36/50)，差异有统计学意义(Bowker T ＝12.000，P＝0.017)。对于45个可疑钙化病灶，FFDM+DBT的特异度与准确率优于FFDM[83.9%(26/31)比61.3%(19/31), P＝0.046; 88.9%(40/45)比71.1%(32/45)，χ2＝4.444, P＝0.035]。对于结构纠结性病灶，FFDM及FFDM+DBT的检出率分别为3/9、9/9，FFDM+DBT优于FFDM(P＝0.003)。

结论

FFDM+DBT对于不可触及病灶的诊断效能优于FFDM，尤其对于致密性乳腺腺体。

关键词: 乳腺肿瘤, 诊断, 乳房X线摄影术, 数字乳腺断层摄影
Objective

To explore the diagnostic value of full-field digital mammography (FFDM) combined with digital breast tomosynthesis (DBT) for nonpalpable breast lesions.

Methods

This prospective study included 126 patients with a total of 137 breast lesions which was nonpalpable in clinic but confirmed by imaging examinations in Zhenjiang Women and Children’s Hospital from June 2017 to December 2019. All patients underwent FFDM and FFDM+ DBT before operation. After enrollment, the guide wire positioning excision biopsy, puncture biopsy or vacuum-assisted resection was performed, and the specimens were sent for pathological examination. With pathological results as the gold standard, the receiver operating characteristic (ROC) curve was drawn and the area under the curve (AUC) was calculated. The McNemar test, Fisher’s exact test or χ2 test was used to compare diagnostic power of the two methods. The Bowker test was used to analyze the differences in the edge characteristics between the two methods.

Results

The detection rate of 137 untouchable breast lesions by FFDM and FFDM+ DBT was 86.9% (119/137) and 94.2% (129/137), indicating a significant difference (χ2=4.249, P=0.039) The detection rates of lesions in dense breasts was 91.0% (81/89) by FFDM+ DBT, significantly higher than79.8% (71/89) by FFDM (χ2=4.504, P=0.034); all lesions in less dense breasts were detected in both examinations. Taking pathological result as the gold standard, the diagnostic accuracy of FFDM+ DBT for all lesions was significantly higher than that of FFDM [92.0% (126/137) vs. 78.8% (108/137), χ2=9.485, P=0.002]. For the diagnosis of all nonpalpable lesions, the AUC of FFDM+ DBT was 0.976±0.010 (95%CI: 0.934-0.994), and the AUC of FFDM was 0.821±0.037 (95%CI: 0.747-0.882), indicating a significant difference (Z=4.131, P<0.001). For diagnosis of lesions in dense breasts, the sensitivity, accuracy and negative predictive value of FFDM+ DBT were significantly higher than those of FFDM (P=0.008, 0.012, 0.037); for diagnosis of lesions in less dense breasts, the two methods showed no significant difference (all P>0.050). For 112 mass-type lesions, the specificity, accuracy and positive predictive value of FFDM+ DBT were significantly higher than those of FFDM (P=0.011; χ2= 9.333, 5.829; P=0.002, 0.016); among them, for 62 benign lesions, the detection rate of lesions with clear edges was 54.8% (34/62) by FFDM and 80.6% (50/62) by FFDM+ DBT, indicating a significant difference (Bowker T=18.000, P<0.001); for 50 malignant lesions, the detection rate of lesions with clear edges was 50% (25/50)by FFDM and 72% (36/50) by FFDM+ DBT, indicating a significant difference (Bowker T=12.000, P= 0.017). For 45 suspicious calcification lesions, the specificity and accuracy of FFDM+ DBT were significantly higher than those of FFDM [83.9%(26/31) vs 61.3%(19/31), P=0.046; 88.9%(40/45) vs 71.1%(32/45), χ2=4.444, P=0.035]. For structurally tangled lesions, the detection rate was 3/9 by FFDM and 9/9 by FFDM+ DBT, indicating a significant difference (P=0.003).

Conclusion

The combination of DBT and FFDM is superior to FFDM in the diagnosis of nonpalpable breast lesions, especially in the dense breasts.

Key words: Breast neoplasms, Diagnosis, Mammography, Digital breast tomosynthesis
表1 2种检查方法对137个不可触及乳腺病灶检出能力的对比
检查方法 非致密性腺体(n＝48) 致密性腺体(n＝89) 合计(n＝137)
检出 未检出 检出 未检出 检出 未检出
FFDM 48 0 71 18 119 18
FFDM+DBT 48 0 81 8 129 8
χ2值 0.000 4.504 4.249
P值 1.000 0.034 0.039
图1 FFDM和FFDM+DBT对137个不可触及乳腺病灶诊断的受试者操作特征曲线
表2 2种检查方法对对137个不可触及乳腺病灶的总体诊断效能的比较
检查方法 病灶数 病理结果(个) 敏感度(%) 特异度(%) 准确率(%) 阳性预测值(%) 阴性预测值(%)
阴性 阳性
FFDM                
                   
  阴性 90 68 22 64.5 90.7 78.8 85.1 75.6
  阳性 47 7 40
FFDM+DBT                
  阴性 76 70 6 90.3 93.3 92.0 91.8 92.1
  阳性 61 5 56
χ2值           9.485 1.205 8.048
P值       0.001a 0.765 a 0.002 0.358 0.006
表3 2种检查方法对不同密度腺体病灶诊断效能的比较
检查方法 非致密性腺体 致密性腺体
病理结果(个) 敏感度(%) 特异度(%) 准确率(%) 阳性预测值(%) 阴性预测值(%) 病理结果(个) 敏感度(%) 特异度(%) 准确率(%) 阳性预测值(%) 阴性预测值(%)
阳性 阴性 阳性 阴性
FFDM                            
  阳性 26 0 83.9 100.0 89.6 100.0 77.3 14 7 45.2 87.9 73.0 66.7 75.0
  阴性 5 17 17 51
FFDM+DBT                            
  阳性 31 1 100.0 94.1 97.9 96.9 100.0 25 4 80.6 93.1 88.8 86.2 90.0
  阴性 0 16 6 54
P值a     0.053 1.000 0.204 1.000 0.061     0.008 0.528 0.012 0.166 0.037
表4 2种检查方法对112个肿块型病灶诊断效能的比较
检查方法 病灶数 病理结果(个) 敏感度(%) 特异度(%) 准确率(%) 阳性预测值(%) 阴性预测值(%)
阴性(n＝62) 阳性(n＝50)
FFDM                
  阴性 90 48 10 80 7.4 78.6 74.1 82.8
  阳性 47 14 40
FFDM+DBT                
  阴性 76 58 4 92.0 93.5 92.9 92.0 93.5
  阳性 61 4 46
χ2值           9.333 5.829 3.385
P值       0.084a 0.011a 0.002 0.016 0.066
图2 1例肿块型乳腺病灶患者的术前影像图　a图为全视野数字乳腺X线摄影头尾位，箭头所示为伴有毛刺的模糊肿块影；b图为内外侧斜位，箭头所示为不清晰的局部结构紊乱和边界不清的肿块；c、d图为数字乳腺断层摄影头尾位，箭头所示分别为伴有明显毛刺征的肿块和边界清晰的肿块；e、f图为数字乳腺断层摄影内外侧斜位，箭头所示分别为伴有明显毛刺征的肿块和边界清晰的肿块
图3 1例不可触及乳腺病灶患者的术前影像图　a图为全视野数字乳腺X线摄影头尾位，b图为内外侧斜位，均未见明显异常征象；c~d图为数字乳腺断层摄影连续图像，箭头所示为被致密腺体掩盖的簇状钙化
表5 FFDM及FFDM+DBT对112个肿块型病灶边缘特征的比较(个)
FFDM FFDM+DBT
病理阴性(n＝62) 病理阳性(n＝50)
清楚 模糊 遮蔽 小分叶 毛刺 清楚 模糊 遮蔽 小分叶 毛刺
清楚 34 0 0 0 0 1 1 0 0 0
模糊 6 6 0 0 0 0 12 0 0 9
遮蔽 10 0 4 2 0 0 0 0 0 1
小分叶 0 0 0 0 0 0 0 0 0 1
毛刺 0 0 0 0 0 0 0 0 0 25
Bowker T 18.000 12.000
P值 <0.001 0.017
表6 2种检查方法对45个可疑钙化病灶的诊断效能比较
检查方法 病灶数 病理结果(个) 敏感度(%) 特异度(%) 准确率(%) 阳性预测值(%) 阴性预测值(%)
阴性(n＝31) 阳性(n＝14)
FFDM                
  阴性 20 19 1 92.9 61.3 71.1 52.0 95.0
  阳性 25 12 13
FFDM+DBT                
  阴性 26 26 0 100 83.9 88.9 73.7 100.0
  阳性 19 5 14
χ2值         3.971 4.444 2.141 0.018
P值       1.000a 0.046 0.035 0.143 0.894
[1]
徐兵河，王树森，江泽飞，等．中国晚期乳腺癌维持治疗专家共识[J]．中华医学杂志，2018，98(2)：87-90.
[2]
Park C, Yoon K, Kim J, et al. Integrative molecular profiling identifies a novel cluster of estrogen receptor-positive breast cancer in very young women [J]. Cancer Science, 2019, 110(5)：1760-1770.
[3]
Kang HJ, Chang JM, Lee J, et al. Replacing single-view mediolateral oblique (MLO) digital mammography (DM) with synthesized mammography (SM) with digital breast tomosynthesis (DBT) images: Comparison of the diagnostic performance and radiation dose with two-view DM with or without MLO-DBT [J]. Eur J Radiol, 2016, 85(11)：2042-2048.
[4]
Shieh Y, Scott CG, Jensen MR, et al. Body mass index, mammographic density, and breast cancer risk by estrogen receptor subtype [J]. Breast Cancer Res, 2019, 21(1)：48.
[5]
Cai SQ, Yao MM, Cai LD, et al. Association between digital breast tomosynthesis and molecular subtypes of breast cancer [J]. Oncol Lett, 2019, 17(3)：2669-2676.
[6]
American College of Radiology. Breast imaging reporting and data system [S/OL]. 5th ed. Reston: VA, 2013：12-34.
[7]
Marina M, Dragan J, Aleksandar M, et al. Early diagnosis and detection of breast cancer [J]. Technol Health Care, 2018，26(4)：729-759.
[8]
Prez MAF, Rodriguez IV, Royloa AT, et al. Metaplastic breast carcinoma with unusual presentation: review of three cases [J]. Breast Care (Basel), 2015，10(6)：404-407.
[9]
曲玉虹，李艳玲，曹崑，等．提高乳腺X线摄影对致密型腺体乳腺癌检出率的方法探讨[J]. 中国医学影像技术，2017, 33 (2)：303-306.
[10]
Marinovich ML, Bernardi D, Macaskill P, et al. Agreement between digital breast tomosynthesis and pathologic tumour size for staging breast cancer, and comparison with standard mammography [J]. Breast, 2019，43：59-66.
[11]
Gao Y, Babb JS, Toth HK, et al. Digital breast tomosynthesis practice patterns following 2011 FDA approval: a survey of breast imaging radiologists[J]. Acad Radiol，2017，24(8)：947-953.
[12]
Rafferty EA, Park JM, Philpotts LE, et al. Assessing radiologist performance using combined digital mammography and breast tomosynthesis compared with digital mammography alone: results of a multicenter, multireader trial. [J]．Radiology, 2013, 266(1)：104-113.
[13]
Svahn TM, Chakraborty DP, Ikeda D, et al. Breast tomosynthesis and digital mammography: a comparison of diagnostic accuracy [J]．Br J Radiol, 2012, 85(1019)：e1074-e1082.
[14]
Rafferty EA. Digital mammography: novel applications [J]．Radiol Clin North Am, 2007，45(5)：831-843.
[15]
Michell MJ, Iqbal A, Wasan RK, et al. A comparison of the accuracy of film-screen mammography, full-field digital mammography, and digital breast tomosynthesis [J]．Clin Radiol, 2012，67(10)：976-981.
[16]
Gilbert FJ, Tucker L, Gillan MG, et al. The TOMMY trial: a comparison of TOMosynthesis with digital MammographY in the UK NHS breast screening programme--a multicentre retrospective reading study comparing the diagnostic performance of digital breast tomosynthesis and digital mammography with digital mammography alone [J]．Health Technol Assess, 2015，19(4)：i-xxv, 1-136.
[17]
Whelehan P, Heywang-Köbrunner SH, Vinnicombe SJ, et al. Clinical performance of Siemens digital breast tomosynthesis versus standard supplementary mammography for the assessment of screen-detected soft-tissue abnormalities: a multi-reader study [J]．Clin Radiol，2017，72(1)：95.e9-95.e15.
[18]
Weigel S, Heindel W, Heidrich J, et al. Digital mammography screening: sensitivity of the programme dependent on breast density [J]. Eur Radiol, 2017，27(7)：2744-2751.
[19]
Horvat JV, Keating DM, Rodrigues-Duarte H, et al. Calcifications at digital breast tomosynthesis: imaging features and biopsy techniques [J]．Radiographics, 2019，39(2)：307-318.
[20]
Munck L, Fracheboud J, Bock GH, et al. Is the incidence of advanced-stage breast cancer affected by whether women attend a steady-state screening program? [J]. Int J Cancer, 2018，143(4)：842-850.
[21]
Rafferty EA, Durand MA, Conant EF, et al. Breast cancer screening using tomosynthesis and digital mammography in dense and nondense breasts [J]. JAMA, 2016，315(16)：1784-1786.
[22]
Nakashima K, Uematsu T, Itoh T, et al. Comparison of visibility of circumscribed masses on digital breast tomosynthesis (DBT) and 2D mammography: are circumscribed masses better visualized and assured of being benign on DBT? [J]. Eur Radiol, 2017，27(2)：570-577.
[23]
吕晓虹，刘宁，李琦，李满，等．数字乳腺断层摄影对致密型乳腺肿块的诊断价值[J]．中华医学杂志，2019，99(39)：3110-3113.
[24]
Kopans D, Gavenonis S, Halpern E, et al. Calcifications in the breast and digital breast tomosynthesis [J]．Breast J, 2011，17(6)：638-644.
[25]
Alberto , Tagliafico , Giovanna , et al. Characterisation of microcalcification clusters on 2D digital mammography (FFDM) and digital breast tomosynthesis (DBT): does DBT underestimate microcalcification clusters? Results of a multicentre study [J]．Eur Radiol，2015，25(1)：9-14.
[26]
Partyka L, Lourenco AP, Mainiero MB, et al. Detection of mammographically occult architectural distortion on digital breast tomosynthesis screening: initial clinical experience. [J]．AJR Am J Roentgenol, 2014，203(1)：216-22.
[27]
徐姝，于韬，罗娅红．数字乳腺断层摄影对致密型乳腺内结构扭曲病变的诊断价值[J]．中国医学影像学杂志，2019，27(4)：263-266.
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