From the Division of Biostatistics, Department of Public Health Sciences, University of California, Davis School of Medicine, One Shields Ave, Med Sci 1C, Room 144, Davis, CA 95616 (D.L.M.); Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Wash (D.L.M., L.A., D.S.M.B.); Department of Radiology, University of Washington School of Medicine; Department of Health Services, University of Washington School of Public Health; Hutchinson Institute for Cancer Outcomes Research, Seattle, Wash (C.I.L.); Department of Radiology (S.D.H.) and Department of Surgery, Office of Health Promotion Research (B.L.S.), Larner College of Medicine at the University of Vermont and University of Vermont Cancer Center, Burlington, Vt; Department of Radiology, University of North Carolina, Chapel Hill, NC (L.M.H.); The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth and Norris Cotton Cancer Center, Lebanon, NH (A.N.A.T.); and Departments of Medicine andEpidemiology and Biostatistics and the General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, Calif (K.K.).
Radiology. 2019 Apr;291(1):34-42. doi: 10.1148/radiol.2019182305. Epub 2019 Feb 26.
Background There is growing evidence that digital breast tomosynthesis (DBT) results in lower recall rates and higher cancer detection rates when compared with digital mammography. However, whether DBT interpretative performance changes with experience (learning curve effect) is unknown. Purpose To evaluate screening DBT performance by cumulative DBT volume within 2 years after adoption relative to digital mammography (DM) performance 1 year before DBT adoption. Materials and Methods This prospective study included 106 126 DBT and 221 248 DM examinations in 271 362 women (mean age, 57.5 years) from 2010 to 2017 that were interpreted by 104 radiologists from 53 facilities in the Breast Cancer Surveillance Consortium. Conditional logistic regression was used to estimate within-radiologist effects of increasing cumulative DBT volume on recall and cancer detection rates relative to DM and was adjusted for examination-level characteristics. Changes were also evaluated by subspecialty and breast density. Results Before DBT adoption, DM recall rate was 10.4% (95% confidence interval [CI]: 9.5%, 11.4%) and cancer detection rate was 4.0 per 1000 screenings (95% CI: 3.6 per 1000 screenings, 4.5 per 1000 screenings); after DBT adoption, DBT recall rate was lower (9.4%; 95% CI: 8.2%, 10.6%; P = .02) and cancer detection rate was similar (4.6 per 1000 screenings; 95% CI: 4.0 per 1000 screenings, 5.2 per 1000 screenings; P = .12). Relative to DM, DBT recall rate decreased for a cumulative DBT volume of fewer than 400 studies (odds ratio [OR] = 0.83; 95% CI: 0.78, 0.89) and remained lower as volume increased (400-799 studies, OR = 0.8 [95% CI: 0.75, 0.85]; 800-1199 studies, OR = 0.81 [95% CI: 0.76, 0.87]; 1200-1599 studies, OR = 0.78 [95% CI: 0.73, 0.84]; 1600-2000 studies, OR = 0.81 [95% CI: 0.75, 0.88]; P < .001). Improvements were sustained for breast imaging subspecialists (OR range, 0.67-0.85; P < .02) and readers who were not breast imaging specialists (OR range, 0.80-0.85; P < .001). Recall rates decreased more in women with nondense breasts (OR range, 0.68-0.76; P < .001) than in those with dense breasts (OR range, 0.86-0.90; P ≤ .05; P interaction < .001). Cancer detection rates for DM and DBT were similar, regardless of DBT volume (P ≥ .10). Conclusion Early performance improvements after digital breast tomosynthesis (DBT) adoption were sustained regardless of DBT volume, radiologist subspecialty, or breast density. © RSNA, 2019 See also the editorial by Hooley in this issue.
背景 与数字乳腺摄影术(digital mammography,DM)相比,数字乳腺断层合成术(digital breast tomosynthesis,DBT)在降低召回率和提高癌症检出率方面的效果日益明显。然而,DBT 的解读性能是否会随经验(学习曲线效应)的变化而改变尚不清楚。
目的 评估在采用 DBT 后 2 年内,DBT 累积体积与采用 DBT 前 1 年 DM 性能之间的筛查 DBT 性能。
材料与方法 本前瞻性研究纳入了 2010 年至 2017 年间,271362 名女性(平均年龄,57.5 岁)的 106126 次 DBT 和 221248 次 DM 检查,由来自 53 个机构的 104 名放射科医生进行解读。采用条件逻辑回归评估每位放射科医生累积 DBT 体积增加与 DM 相比对召回率和癌症检出率的影响,并对检查水平的特征进行了调整。还根据亚专科和乳腺密度评估了变化。
结果 在采用 DBT 之前,DM 的召回率为 10.4%(95%置信区间[CI]:9.5%,11.4%),癌症检出率为 4.0 例/1000 次筛查(95%CI:3.6 例/1000 次筛查,4.5 例/1000 次筛查);采用 DBT 后,DBT 的召回率降低(9.4%;95%CI:8.2%,10.6%;P =.02),癌症检出率相似(4.6 例/1000 次筛查;95%CI:4.0 例/1000 次筛查,5.2 例/1000 次筛查;P =.12)。与 DM 相比,DBT 累积体积小于 400 例时,召回率降低(比值比[OR] = 0.83;95%CI:0.78,0.89),随着体积的增加,召回率持续降低(400-799 例,OR = 0.8[95%CI:0.75,0.85];800-1199 例,OR = 0.81[95%CI:0.76,0.87];1200-1599 例,OR = 0.78[95%CI:0.73,0.84];1600-2000 例,OR = 0.81[95%CI:0.75,0.88];P <.001)。乳腺成像亚专科医生(OR 范围,0.67-0.85;P <.02)和非乳腺成像专家(OR 范围,0.80-0.85;P <.001)的结果得到持续改善。在无致密乳腺的女性中,召回率降低幅度更大(OR 范围,0.68-0.76;P <.001),而在致密乳腺的女性中,召回率降低幅度较小(OR 范围,0.86-0.90;P ≤.05;P 交互 <.001)。DM 和 DBT 的癌症检出率相似,与 DBT 体积无关(P ≥.10)。
结论 在采用 DBT 后,无论 DBT 体积、放射科医生的亚专科或乳腺密度如何,早期性能的提高都得到了持续。
(本文由周亦川译自 Hooley et al. Radiology. 2019;290:767-776.)