The Positive Predictive Values of the Breast Imaging Reporting and Data System (BI-RADS) 4 Lesions and its Mammographic Morphological Features

被引:8
|
作者
Mohapatra, Suvendu Kumar [1 ]
Mishra, Abhisek [2 ]
Sahoo, Tapan Kumar [3 ]
Nayak, Rashmita Binod [4 ]
Das, Prafulla Kumar [5 ]
Nayak, Bhagyalaxmi [6 ]
机构
[1] AHPGIC, Dept Radiodiag, Cuttack, Odisha, India
[2] AIIMS Patna, Patna, Bihar, India
[3] AHPGIC, Radiat Oncol, Cuttack, Odisha, India
[4] SCB Med Coll, Dept Paediat, Cuttack, Odisha, India
[5] AHPGIC, Dept Surg Oncol, Cuttack, Odisha, India
[6] AHPGIC, Dept Gynaecol Oncol, Cuttack, Odisha, India
关键词
BI-RADS; 4; Malignancy; Mammography; Morphology; Positive predictive value; SCREENING MAMMOGRAPHY; CANCER; OVERDIAGNOSIS; US;
D O I
10.1007/s13193-020-01274-5
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The Breast Imaging Reporting and Data System (BI-RADS) is a comprehensive guideline to systematize breast imaging reporting, and as per its recommendations, any lesion with likelihoods of malignancy greater than 2% is deemed as suspicious and tissue diagnosis is recommended. The aim of the study is to determine the positive predictive value (PPV) of BI-RADS categories 4a, 4b, and 4c for malignancy and association of mammographic morphological features of BI-RADS 4 subgroups with malignant outcomes. We retrospectively reviewed all the patients undergoing mammography with BI-RADS score of 4 followed by biopsy from May 2019 to April 2020. The predictive values of BI-RADS 4 subcategories and morphological features with malignancy are performed taking histopathology report as the gold standard. The PPV of BI-RADS subcategories 4a, 4b, and 4c for malignancies were 34, 89, and 97%, respectively. BI-RADS 4c patients tend to be older (50.2 +/- 12.2 vs. 44.6 +/- 10.3 years) with larger mass (44 +/- 16 vs. 32.9 +/- 16.8 mm) at presentation than 4a. Postmenopausal state (P = 0.03) and older age (P = 0.019) were significantly associated with malignancy. There is no meaningful difference observed in the predictability of BI-RADS category 4c lesions among different breast density patterns. The overall higher PPV for BI-RADS 4a and 4b reflects subjectivity in subcategory assignments of BI-RADS 4. In patients, less than 40 years with the BI-RADS 4a category on mammograms may undergo supplementary imaging with MRI which may downscale the lesion classification in turn reducing unnecessary biopsy and surgery.
引用
收藏
页码:182 / 189
页数:8
相关论文
共 50 条
  • [21] Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI
    Honda, Maya
    Kataoka, Masako
    Kawaguchi, Kosuke
    Iima, Mami
    Miyake, Kanae Kawai
    Kishimoto, Ayami Ohno
    Ota, Rie
    Ohashi, Akane
    Toi, Masakazu
    Nakamoto, Yuji
    JAPANESE JOURNAL OF RADIOLOGY, 2021, 39 (01) : 56 - 65
  • [22] Subcategory classifications of Breast Imaging and Data System (BI-RADS) category 4 lesions on MRI
    Maya Honda
    Masako Kataoka
    Kosuke Kawaguchi
    Mami Iima
    Kanae Kawai Miyake
    Ayami Ohno Kishimoto
    Rie Ota
    Akane Ohashi
    Masakazu Toi
    Yuji Nakamoto
    Japanese Journal of Radiology, 2021, 39 : 56 - 65
  • [23] Breast Imaging Reporting and Data System (BI-RADS®): a success history and particularities of its use in Brazil
    Merjane, Vanessa
    Perin, Douglas Marcel Puricelli
    El Bacha, Patricia Martins Comes
    Miranda, Beatriz Medicis Maranhao
    Bitencourt, Almir Calvao Vieira
    Iared, Wagner
    REVISTA BRASILEIRA DE GINECOLOGIA E OBSTETRICIA, 2024, 46
  • [24] Observer Variability of the Breast Imaging Reporting and Data System (BI-RADS) Lexicon for Mammography
    Adibelli, Zehra H.
    Ergenc, Ruken
    Oztekin, Ozgur
    Ecevit, Suheyla
    Unal, Gokhan
    Abali, Yusuf
    BREAST CARE, 2010, 5 (01) : 11 - 16
  • [25] The Breast Imaging Reporting and Data System: Positive predictive value of mammographic features and final assessment categories
    Liberman, L
    Abramson, AF
    Squires, FB
    Glassman, JR
    Morris, EA
    Dershaw, DD
    AMERICAN JOURNAL OF ROENTGENOLOGY, 1998, 171 (01) : 35 - 40
  • [26] Value of breast MRI omics features and clinical characteristics in Breast Imaging Reporting and Data System (BI-RADS) category 4 breast lesions: an analysis of radiomics-based diagnosis
    Cui, Qian
    Sun, Liang
    Zhang, Yu
    Zhao, Zimu
    Li, Shuo
    Liu, Yajie
    Ge, Hongwei
    Qin, Dongxue
    Zhao, Yiping
    ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (22)
  • [27] Positive Predictive Value of BI-RADS MR Imaging
    Mahoney, Mary C.
    Gatsonis, Constantine
    Hanna, Lucy
    DeMartini, Wendy B.
    Lehman, Constance
    RADIOLOGY, 2012, 264 (01) : 51 - 58
  • [28] Computer aided classification system for breast ultrasound based on breast imaging reporting and data system (BI-RADS)
    Shen, Wei-Chih
    Chang, Ruey-Feng
    Moon, Woo Kyung
    ULTRASOUND IN MEDICINE AND BIOLOGY, 2007, 33 (11): : 1688 - 1698
  • [29] Validity of the breast imaging reporting and data system BI-RADS™ for clinical mammography in men.
    Bock, K
    Iwinska-Zelder, J
    Duda, VF
    Bonwetsch, C
    Rode, G
    Hadji, P
    Klose, KJ
    Schulz, KD
    ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2001, 173 (11): : 1019 - 1024
  • [30] Sonographic features of dense breast imaging reporting and data system 4 (BI-RADS-US4) for non-palpable breast lesions
    Li, Feng-Sheng
    Bai, Bao-Yan
    Wang, Yun-Mei
    Xiao, Yang
    Song, Can-Xu
    Song, Zhang-Jun
    Wang, Sheng-Li
    Yang, Xiao-Min
    INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE, 2017, 10 (07): : 10806 - 10812