Radiologists' performance in reading digital breast tomosynthesis with and without synthesized views for cancer detection

被引:0
作者
Trieu, Phuong Dung [1 ]
Noakes, Jennie [1 ,2 ]
Li, Tong [1 ]
Borecky, Natacha [1 ,3 ]
Brennan, Patrick C. [1 ]
Barron, Melissa L. [1 ]
Lewis, Sarah J. [1 ]
机构
[1] Univ Sydney, Fac Med & Hlth, Discipline Med Imaging Sci, Camperdown, NSW, Australia
[2] BreastScreen New South Wales, Level 6,Community Serv Bldg,Herbert St, St Leonards, NSW, Australia
[3] BreastScreen New South Wales North Coast, POB 1098, Lismore, NSW, Australia
关键词
RECONSTRUCTED PROJECTION IMAGES; MAMMOGRAPHY; POPULATION; DBT;
D O I
10.1259/bjr.20220704
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objective: The study aims to evaluate the diagnostic efficacy of radiologists and radiology trainees in digital breast tomosynthesis (DBT) alone vs DBT plus synthe-sized view (SV) for an understanding of the adequacy of DBT images to identify cancer lesions.Methods: Fifty -five observers (30 radiologists and 25 radiology trainees) participated in reading a set of 35 cases (15 cancer) with 28 readers reading DBT and 27 readers reading DBT plus SV. Two groups of readers had similar experience in interpreting mammograms. The performances of participants in each reading mode were compared with the ground truth and calculated in term of specificity, sensitivity, and ROC AUC. The cancer detection rate in various levels of breast density, lesion types and lesion sizes between 'DBT' and 'DBT + SV' were also analyzed. The difference in diagnostic accuracy of readers between two reading modes was assessed using Man-Whitney U test. p < 0.05 indicated a significant result.Results: There was no significant difference in specificity (0.67-vs-0.65; p = 0.69), sensitivity (0.77-vs-0.71; p = 0.09), ROC AUC (0.77-vs-0.73; p = 0.19) of radiologists reading DBT plus SV compared with radiologists reading DBT. Similar result was found in radiology trainees with no significant difference in specificity (0.70-vs-0.63; p = 0.29), sensitivity (0.44-vs-0.55; p = 0.19), ROC AUC (0.59-vs-0.62; p = 0.60) between two reading modes. Radiologists and trainees obtained similar results in two reading modes for cancer detection rate with different levels of breast density, cancer types and sizes of lesions (p > 0.05).Conclusion: Findings show that the diagnostic perfor-mances of radiologists and radiology trainees in DBT alone and DBT plus SV were equivalent in identifying cancer and normal cases. Advances in knowledge: DBT alone had equivalent diag-nostic accuracy as DBT plus SV which could imply the consideration of using DBT as a sole modality without SV.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Digital breast tomosynthesis versus mammography and breast ultrasound: a multireader performance study
    Thibault, Fabienne
    Dromain, Clarisse
    Breucq, Catherine
    Balleyguier, Corinne S.
    Malhaire, Caroline
    Steyaert, Luc
    Tardivon, Anne
    Baldan, Enrica
    Drevon, Harir
    EUROPEAN RADIOLOGY, 2013, 23 (09) : 2441 - 2449
  • [32] Efficacy of digital breast tomosynthesis for breast cancer diagnosis
    Alakhras, M.
    Mello-Thoms, C.
    Rickard, M.
    Bourne, R.
    Brennan, P. C.
    MEDICAL IMAGING 2014: IMAGE PERCEPTION, OBSERVER PERFORMANCE, AND TECHNOLOGY ASSESSMENT, 2014, 9037
  • [33] Digital Breast Tomosynthesis Is Comparable to Mammographic Spot Views for Mass Characterization
    Noroozian, Mitra
    Hadjiiski, Lubomir
    Rahnama-Moghadam, Sahand
    Klein, Katherine A.
    Jeffries, Deborah O.
    Pinsky, Renee W.
    Chan, Heang-Ping
    Carson, Paul L.
    Helvie, Mark A.
    Roubidoux, Marilyn A.
    RADIOLOGY, 2012, 262 (01) : 61 - 68
  • [34] Digital tomosynthesis in breast cancer: A systematic review
    Garcia-Leon, F. J.
    Llanos-Mendez, A.
    Isabel-Gomez, R.
    RADIOLOGIA, 2015, 57 (04): : 333 - 343
  • [35] Development of digital breast tomosynthesis and diffuse optical tomography fusion imaging for breast cancer detection
    Chae, Eun Young
    Kim, Hak Hee
    Sabir, Sohail
    Kim, Yejin
    Kim, Hyeongseok
    Yoon, Sungho
    Ye, Jong Chul
    Cho, Seungryong
    Heo, Duchang
    Kim, Kee Hyun
    Bae, Young Min
    Choi, Young-Wook
    SCIENTIFIC REPORTS, 2020, 10 (01)
  • [36] Impact of prior mammograms on combined reading of digital mammography and digital breast tomosynthesis
    Kim, Won Hwa
    Chang, Jung Min
    Koo, Hye Ryoung
    Seo, Mirinae
    Bae, Min Sun
    Lee, Joongyub
    Moon, Woo Kyung
    ACTA RADIOLOGICA, 2017, 58 (02) : 148 - 155
  • [37] Digital Breast Tomosynthesis: Observer Performance of Clustered Microcalcification Detection on Breast Phantom Images Acquired with an Experimental System Using Variable Scan Angles, Angular Increments, and Number of Projection Views
    Chan, Heang-Ping
    Goodsitt, Mitchell M.
    Helvie, Mark A.
    Zelakiewicz, Scott
    Schmitz, Andrea
    Noroozian, Mitra
    Paramagul, Chintana
    Roubidoux, Marilyn A.
    Nees, Alexis V.
    Neal, Colleen H.
    Carson, Paul
    Lu, Yao
    Hadjiiski, Lubomir
    Wei, Jun
    RADIOLOGY, 2014, 273 (03) : 675 - 685
  • [38] Computer-Aided Detection of Microcalcifications in Digital Breast Tomosynthesis (DBT): A Multichannel Signal Detection Approach on Projection Views
    Wei, Jun
    Chan, Heang-Ping
    Hadjiiski, Lubomir
    Helvie, Mark A.
    Zhou, Chuan
    Lu, Yao
    MEDICAL IMAGING 2012: COMPUTER-AIDED DIAGNOSIS, 2012, 8315
  • [39] Breast cancer screening in women with and without implants: retrospective study comparing digital mammography to digital mammography combined with digital breast tomosynthesis
    Ethan O. Cohen
    Rachel E. Perry
    Hilda H. Tso
    Kanchan A. Phalak
    Michele D. Lesslie
    Karen E. Gerlach
    Jia Sun
    Ashmitha Srinivasan
    Jessica W. T. Leung
    European Radiology, 2021, 31 : 9499 - 9510
  • [40] Comparative Study of Digital Breast Tomosynthesis (DBT) with and without Ultrasound versus Breast Magnetic Resonance Imaging (MRI) in Detecting Breast Lesion
    Goh, Janice Hui Ling
    Tan, Toh Leong
    Aziz, Suraya
    Rizuana, Iqbal Hussain
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (02)