• Users Online: 674
  • Print this page
  • Email this page


 
 
Table of Contents
ORIGINAL ARTICLE
Year : 2022  |  Volume : 5  |  Issue : 1  |  Page : 52-58

Diagnostic accuracy of mammography in characterizing breast masses using the 5th edition of BI-RADS: A retrospective study


1 Department of Radiodiagnosis, AHPGIC, Mangalabag, Cuttack, Odisha, India
2 Department of Surgical Oncology, AHPGIC, Mangalabag, Cuttack, India
3 Department of Paediatrics, SCB Medical College, Cuttack, Odisha, India
4 Department of Community Medicine & Family Medicine, AIIMS, Bhubaneswar, Odisha, India
5 Department of Gynaecological Oncology, AHPGIC, Mangalabag, Cuttack, Odisha, India

Date of Submission16-Sep-2021
Date of Decision06-Mar-2022
Date of Acceptance06-Mar-2022
Date of Web Publication31-Mar-2022

Correspondence Address:
Suvendu Kumar Mohapatra
Ramakrishna Bhawan, Jagannathvihar, Gopalpur, Cuttack - 753 011, Odisha
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/crst.crst_224_21

Rights and Permissions
  Abstract 


Background: Breast imaging-reporting and data system (BI-RADS) is intended for standardizing mammography reporting.
Objectives: We aimed to evaluate the diagnostic precision of the BI-RADS assessment scoring system using histopathological findings as the reference standard. We also aimed to assess the positive predictive value (PPV) of different morphological descriptors for malignancy.
Materials and Methods: This retrospective record-based analytical study was conducted in the Department of Radiodiagnosis of Acharya Harihar Post Graduate Institute of Cancer, Cuttack, Odisha, a tertiary cancer center in eastern India. We included patients attending the breast cancer unit with various breast complaints who were subjected to mammographic imaging and histopathological examination. The primary outcomes were the sensitivity, PPV, negative predictive value (NPV), and diagnostic accuracy (DA) of the BI-RADS scores for the pathological reports; secondary objective was the evaluation of the mammographic morphological characteristics. Mammography was interpreted using the BI-RADS 5th edition guidelines, without prior knowledge of the biopsy report. A BI-RADS final assessment score between 1 and 5 was assigned, where 1 indicated a normal study, 2 benign, 3 possibly benign requiring follow up, 4 suspicious requiring biopsy, and 5 indicating likely malignant requiring biopsy and further actions.
Results: Between February 2020 and December 2020, we included 247 patients. All the category 5 lesions were malignant, while 76.5% of category 4 lesions were malignant. PPVs of BI-RADS categories 4a, 4b, and 4c were 38%, 90%, and 94%, respectively. Mammography had a sensitivity, specificity, PPV, NPV, and DA of 98.7%, 47.6%, 87.5%, 90.9%, and 87.9%, respectively. Morphological features that were significantly associated with malignancy were spiculated margins (P = 0.003, PPV = 100%), microlobulated margins (P = 0.005, PPV = 96.5%), irregular shape (P = 0.002, PPV = 89.6%), microcalcification (P = 0.005, PPV = 92.8%), skin thickening (P < 0.0001, PPV = 100%), and architectural distortion (P = 0.003, PPV = 96.7%).
Conclusion: Digital mammography is a sensitive tool for the evaluation of breast lumps, but BI-RADS final assessment score is subjective as it depends on the interpreter's expertise.

Keywords: BI-RADS, breast malignancy, mammography, sensitivity, spiculation


How to cite this article:
Mohapatra SK, Das PK, Nayak RB, Mishra A, Nayak B. Diagnostic accuracy of mammography in characterizing breast masses using the 5th edition of BI-RADS: A retrospective study. Cancer Res Stat Treat 2022;5:52-8

How to cite this URL:
Mohapatra SK, Das PK, Nayak RB, Mishra A, Nayak B. Diagnostic accuracy of mammography in characterizing breast masses using the 5th edition of BI-RADS: A retrospective study. Cancer Res Stat Treat [serial online] 2022 [cited 2022 May 28];5:52-8. Available from: https://www.crstonline.com/text.asp?2022/5/1/52/341240




  Introduction Top


According to GLOBOCAN 2020, breast cancer is one of the most common cancers among women and is responsible for more than 0.5 million deaths around the globe every year.[1] The incidence of breast cancer has increased steadily over the last decade even in India, with an age-adjusted incidence rate of 258 per one million population.[2],[3]

Great progress has been made in the field of medicine in the past few decades towards the detection of breast malignancies in early stages with the help of different imaging techniques like mammography, ultrasound, and breast magnetic resonance imaging (MRI). Self-breast assessment and routine clinical check-ups are clinical methods for diagnosing breast disease. However, most of the early breast cancers are occult and are not suitably assessed by clinical means. Mammography is the primary imaging modality for breast cancer, both in screening and diagnosis, due to its wide availability, acceptability, and cost-effectiveness. Breast imaging-reporting and database system (BI-RADS) score is a classification system proposed by the collaborative effort of many health groups in United States of America, and was published and trademarked by the American College of Radiology (ACR) in the late 1980s to address the problem of non-uniformity in mammography reporting. Its latest 5th edition released in 2013 has 7 categories , ranging from 0 to 6.[4] Details of BI-RADS categories and the likelihood of malignancy are described in [Table 1]. Representative images of each BI-RADS category are given in [Figure 1]a, [Figure 1]b, [Figure 1]c, [Figure 1]d, [Figure 1]e.
Table 1: Breast imaging-reporting and database system (BI-RADS) score and management guidelines (derived from BI-RADS atlas, 5th edition)

Click here to view
Figure 1: (a–e) Imaging appearances of BI-RADS subcategories. 1a) Rounded mass with well-circumscribed margin categorized as BI-RADS 3; 1b) Irregular mass with obscured margins categorized as BI-RADS 4a; 1c) Oval mass with microlobulation categorized as BI-RADS 4b; 1d) Irregular mass with spiculation categorized as BI-RADS 4c; 1e) Irregular spiculated mass with architectural distortion categorized as BI-RADS 5.

Click here to view




Data from an earlier study on Asian population suggest reduced sensitivity and positive predictive value (PPV) of mammograms due to smaller breast volume and relatively denser breasts in Asian women compared to the western population. Hence, the applicability of BI-RADS predictive scores and the management recommendations based on the BI-RADS score must be evaluated in the Indian context.[5] We therefore aimed to evaluate the diagnostic accuracy and PPV of the BI-RADS score using histopathological findings as the reference gold standard. We also estimated the PPV of mammographic morphological lexicons for the presence of malignancy.


  Materials and Methods Top


General study details

This retrospective, record-based, analytical study was conducted in the Department of Radiodiagnosis of Acharya Harihar Post Graduate Institute of Cancer (AHPGIC), Cuttack, Odisha, a tertiary cancer center in eastern India, from February 2020 to December 2020. The study was approved by the Institutional Ethics Committee, Number 124-IEC-AHRCC, on Feb 7, 2020 (Supplementary Appendix 1). The need for informed consent was waived off because of the retrospective nature of the study. The study was conducted in compliance with the ethical guidelines established by the Declaration of Helsinki and the Indian Council of Medical Research. The study was neither registered in a publicly accessible clinical trial registry nor did we utilize any funding for this study.

Participants

Patients attending our breast cancer unit during the study period with various breast complaints, and those who were subjected to mammographic imaging and histopathological examination were included in the study. Patients with dense breasts and inconclusive observations (BI-RADS 0) requiring further examination by imaging were excluded from the present study because of its retrospective design (as we were unable to call the subjects back for repeat imaging). Patients with poor mammographic image quality and missing clinical and histopathological data were also excluded from the present study.

Variables

The correlation between the BI-RADS scores and pathological reports, whether benign or malignant, was the primary endpoint of the study. Mammographic morphological characteristics like shape, margin, microcalcifications, architectural distortion, lymph nodal enlargement, and breast density were the secondary endpoints. Representative images of morphological descriptors, density pattern, and microcalcifications are given in Supplementary [Figure 1], [Figure 2], [Figure 3], [Figure 4]. Breast density, age, menopausal status, and clinical parameters like palpability were considered as confounders.
Figure 2: Patient recruitment and data analysis flowchart

Click here to view
{Figure 3}{Figure 4}

Study methodology

Stored images from the Senographae Pristina (GE Medical) mammography systems were used for analysis. Mammography was interpreted using BI-RADS 5th edition guidelines, without prior knowledge of the biopsy report. A BI-RADS final assessment score of 1–5 was assigned. BI-RADS assessment scores of 1, 2, and 3 were considered negative, while assessment scores of 4 and 5 were considered positive. Patients who were noted to have BI-RADS 3 category (although negative) underwent biopsy, despite their radiological findings suggesting likely benign disease, because of the surgeons' preference and patient anxiety.

Definitions

PPV was calculated by dividing the number of true positives (malignant) in each group by the total number of observations (true positives + false positives) for each group (BI-RADS 3 to 5). Similarly, the PPV for individual BI-RADS morphological lexicons was evaluated by dividing the number of malignant observations by the total number of such morphological observations in each group. The diagnostic accuracy was measured by the formula {(true positives + true negatives)/(true negatives + false positives + false negatives + true negatives)}

Statistics

The sample size was calculated using the online free calculator, Calculator.net. The following assumptions were taken for the sample size calculation: Presence of malignancy in those who had undergone mammography was 20%, confidence interval was 95%, margin of error was 5%, and unavailability of records was 5%.[6] The sample size was estimated to be 270. The histopathology report was categorized as positive or negative for malignancy, and was treated as the reference standard for this predictive analysis. Demographic and morphological characteristics were described using frequency and proportions. Proportions were compared by using the Chi-squared test. The receiver operating characteristic (ROC) curve was generated with sensitivity on the X-axis and 1-specificity on the Y-axis. The area under the curve (AUC) was measured in order to denote the comparability of the BI-RADS score with histopathology findings. Statistical analysis was performed using the Statistical Package for the Social Sciences (IBM Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp.).


  Results Top


Imaging and histopathological findings of 247 patients were retrieved, verified, and analyzed for the present study [Figure 2].

The demographic characteristics and clinical features of all patients included in the study are described in [Table 2]. For assessing the sensitivity of the BI-RADS score, we did not consider patients with BI-RADS scores of 1 and 2 in the test-negative group because a biopsy was neither indicated nor performed for these patients. Moreover, for the sake of uniformity of data, only cases with known biopsy outcomes were considered for the sensitivity analysis.
Table 2: Clinical features of the participants in the study to evaluate the diagnostic accuracy of mammography in characterizing breast masses using BI-RADS 5th edition

Click here to view


Out of the total 99 biopsies (88 positive and 11 negative cases with BI-RADS score of 3), 78.8% were found to be malignant and 21.2% were benign based on histopathological examination. Mean age of patients with a malignant pathology report was 49 years (standard deviation [SD] ± 9.7). Out of 78 patients with malignant disease, 7 (8.9%) had a family history of breast malignancy. The left upper outer quadrant was the commonest location of the malignant mass observed in 22% of the cases. Median size of malignant mass was 4.1 cm (range, 1.2–9.5 cm).

The association of breast carcinoma as compared with BI-RADS morphological descriptors and category are shown in [Table 3] and [Table 4]. The median size of the mass was found to increase with an increase in the BI-RADS score. The P value for the size of the lesion (per log increase and malignancy) using univariate logistic regression was 0.0003.
Table 3: Association of various morphological descriptors with malignancy as per Chi-squared test

Click here to view
Table 4: BI-RADS assessment category and biopsy result

Click here to view


Eleven cases from the test-positive set were negative for carcinoma on histopathological examination, thus showing false-positive outcomes on mammography. A total of 10 cases were true negatives, and 1 was false negative. The sensitivity, specificity, PPV, and NPV for mammography were 98.7%, 47.6%, 87.5%, and 90.9%, respectively. The overall diagnostic accuracy was 87.9%. The ROC curve for BI-RADS using histopathological examination as the reference is shown in [Supplementary Figure 5].



In our study, 44% of the participants aged below 50 years had dense breasts compared to 14% of those aged over 50 years. The median age in the false-positive group was 44 years, in which mammography showed reduced diagnostic accuracy (84.3% in those aged <50 years versus 94.3% in those aged >50 years).


  Discussion Top


The BI-RADS 4 assessment classification has been split into three subcategories based on the level of suspicion of cancer. However, this subcategorization is essentially subjective and based on the clinical understanding and prediction of radiologists; no objective standards have been specified for this. In 2014, a study by Leblebici et al.[7] demonstrated that the malignancy rates for BI-RADS subcategories 4a, 4b, and 4c were 5.5%, 50%, and 33%, respectively. In our study, the malignancy rates were 38%, 90%, and 94%, respectively. This could be due to the subjective nature of the subgroup assignment and biases secondary to a smaller sample size. Considering the inter-observer variations, we advocate objective definitions for every morphological parameter, similar to the Thyroid Imaging-Reporting and Data System (TI-RADS), for subcategory assignment in order to obtain consistent results and reduce inter-observer variations and errors in reporting.

According to a recently published study by Lehman et al.,[8] the benchmark sensitivity of mammography for non-palpable lesions is 92.2% and for palpable lesion is 93.2%. In our study, the sensitivity for palpable breast lesions was 98.7%. Factors contributing to higher sensitivity in our study included small selective sampling of patients in a tertiary cancer center and categorical exclusion of ill-defined breast lesions in extremely dense breasts requiring additional imaging or investigations (BI-RADS 0).

Mammographic appearances have a substantial influence on radiographic characterization and BI-RADS category assignments as per size, shape, density, and margins.[9] Radiologically isodense masses along with lobulated, obscured, or indistinct margins are categorized as doubtful. Extremely suspicious mammographic observations are mostly very dense, irregularly shaped, spiculated, and have indistinct margins. However, nearly 10% of cancerous lesions may show benign characteristics such as round, oval shape and well-defined margins.[10] In some cases, spiculations and adjoining parenchymal differences may be very faint and difficult to establish. Under these circumstances, especially in the screening setting, the low disease prevalence may lead to possibly cancerous lesions being ignored or misdiagnosed, resulting in inaccuracies in the interpretation of mammography results. In the current study, irregular shape (P = 0.002) and spiculated margin (P = 0.003) were significantly associated with the presence of malignancy, as reported in an earlier study.[10] Margin descriptors like microlobulation were also significantly associated (P = 0.005) with malignancy and were found to be more frequent than spiculation in our study. Although a final post-surgical immunohistochemical analysis was not performed in our study, Kojima et al.[11] reported that microlobulation of the mass margin was associated with triple-negative breast cancers.

Mammographic identification of microcalcifications with their distinctive appearance and distribution is critical to the early detection of breast carcinoma. However, mammography can only establish microcalcifications in 30%–50% of breast cancers.[12] Pleomorphic microcalcifications were seen in 28% of the total cases in our study, out of which 93% had malignant pathology, thus suggesting a significant association between microcalcifications and malignancy (P = 0.005).

Breast density is a major factor that influences breast cancer screening and diagnosis. Reduced sensitivity and failures in diagnosis are observed in patients with dense breasts, as fibro glandular density obscures subtle imaging finding, leading to diagnostic failures and increased interval cancer detection. In our study, mammographic identification of suspicious malignancies did not correlate with the results of the histopathological examination (false positive) in 12.5% of the participants. the diagnostic accuracy was lower in women aged less than 50 years due to dense breasts in this age group. Our findings are in agreement with those reported by Weigel et al.[13] which showed overall reduced diagnostic accuracy in dense breasts in population-based screening programs. One patient in our study was diagnosed as BI-RADS category 3 on mammography, while on biopsy, the diagnosis was malignant phyllodes (false negative). This patient had undergone surgery for a breast fibroid two years ago, with an oval-shaped mammographic morphology that could have led to the misdiagnosis.

Presurgical tumor size is important for clinical staging in breast cancer. Suitable staging helps in determining proper treatment, particularly with the increasing use of adjuvant and minimally invasive therapeutic alternatives. Clinical examination for tumor size determination often overestimates the tumor size while sonography and mammography underestimate it.[14] In the present study, the median size of the malignant lesion was 4.15 cm (range, 1.2–9.5 cm). Contrarily, Luparia et al.[15] reported an average tumor size of 2.23 cm. This could be suggestive of late detection of malignancy owing to the lack of breast cancer screening programs and low health awareness in our region.

In our study, the average age of patients with malignant histopathology was 49 years, which is similar to that reported in an earlier study.[16] The probability of developing breast cancer increases as women age because of longer duration of estrogen exposure. Women who have menopause after 55 years are more likely to develop malignancy than women with early menopause.[17] In an earlier study conducted in India by Surakasula et al.,[18] postmenopausal status was significantly associated with malignancy, which is similar to our study findings (P = 0.001).

Family history is another significant risk factor for the development of breast malignancy in young women in the presence of predisposing mutations. Thus, having a first-degree female family member with breast cancer increases a woman's risk of developing breast cancer. In our study, 8.9% of patients had a family history of breast cancer: this is similar to the findings reported by Chauhan et al.[19] However, another study reported that prior information of family history of breast malignancy decreased the diagnostic precision of mammograms as the radiologist tends to examine and overinterpret more breast lesions with no improvement in diagnostic accuracy.[20]

A lump was the commonest presenting feature in our study and was present in all cases of breast malignancy, as has also been reported in earlier studies.[21] The location of the lesion and its impression on adjacent breast tissues are also significant factors affecting cancer detection on mammography. The left upper outer quadrant was the commonest location (22%) for malignant lesions in our study; these findings are in agreement with those of an earlier study.[22]

The major limitations of our study were its sampling technique which might have resulted in a selection bias. We used hospital data from a cancer center that may not have been truly representative of the target population, thus hampering our ability to draw significant meaningful conclusions. A smaller sample size might also have not helped to overcome errors in data collection and interpretation, if any. We tried to overcome the case selection and information bias by blinding the interpreting radiologists to previous mammography and histopathology report during mammography reporting.

Our results show that digital mammography is a highly sensitive tool for the evaluation of palpable breast masses. Breast lump being the commonest presentation, information education and communication strategy of public awareness should be promoted for self-breast examination, which may increase the chances of early detection of breast carcinoma, thus improving survival. A nationwide digital database of mammograms may be maintained to strengthen our education and institutional image review on a large scale, which will also encourage radiologists to seek performance feedback, resulting in better clinical outcomes.


  Conclusion Top


Although mammography offers a highly accurate diagnostic solution for breast lesion characterization, it is subjective in the morphological description as well as final assessment categorization.

Data sharing statement

We are willing to share individual de-identified participant data or additional, related documents like the study protocol. These data can be accessed by individual investigators whose proposal has been approved by an independent review committee for the purpose of a meta-analysis. These data will be made available from the time of publication up to three years after the date of publication. Requests for data sharing should be sent to the principal investigator, Dr Suvendu Mohapatra, email address <[email protected]>.

Acknowledgements

We are indebted to Dr Dillip Kumar Agarwal for his critical comments and review of this article.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.


  Supplementary Appendix 1: Study Protocol Top


Protocol Title: MAMMOGRAPHIC CHARACTERIZATION OF MALIGNANT BREAST MASSES USING BIRADS LEXICON AND ASSESSMENT CATEGORY: KNOWING ITS ACCURACY IN A TERTIARY CANCER CARE CENTRE

Protocol Version: 1.0

Principal Investigator:

Dr Suvendu Kumar Mohapatra, MD Radiodiagnosis

Assistant Professor Dept Of Radiodiagnosis, AHPGIC, Mangalabag, Cuttack, Odisha, India. [email protected]

Research Personnel:

  1. Dr Suvendu Kumar Mohapatra, MD Radiodiagnosis, Assistant Professor Dept Of Radiodiagnosis, AHPGIC, Mangalabag, Cuttack, Odisha, India. [email protected]
  2. Dr Prafulla Kumar Das, MS surgery, Professor and Head Department Of Surgical Oncology AHPGIC, Mangalabag, Cuttack, Odisha, India. Email: [email protected]
  3. Dr Rashmita Binod Nayak, MD Pediatrics, Department Of Paediatrics SCB Medical College, Cuttack, Odisha, India. Email: [email protected]
  4. Dr Abhisek Mishra, MD PSM, Assistant Professor AIIMS Bhubaneswar, Odisha, India. Email: [email protected]
  5. Dr Bhagyalaxmi Nayak, MD O&G, Asso. Professor Department Of Gynaecological Oncology, AHPGIC, Mangalabag, Cuttack, Odisha, India. Email: [email protected]


Study Site: AHPGIC CUTTACK, ODISHA, INDIA

Protocol Date: 02.01.2020

  1. Abstract: Breast imaging-reporting and data system (BI-RADS) is a classification system proposed by the American College of Radiology (ACR) in 1986 with the original report released in 1993. BI-RADS was implemented to standardize risk assessment and quality control for mammography and provide uniformity in the reports for non-radiologist.[1]


  2. This present study is a retrospective analytical study aimed for studying the validity of diagnostic mammography and BI-RADS score in benign and malignant lesions compared with histopathological study as gold standard.

  3. Background and Significance/Preliminary Studies


  4. Data from an earlier study on the Asian population suggest reduced sensitivity and positive predictive values of mammograms due to smaller breast volume and relatively denser breasts compared to their western counterparts. Thus the applicability of BI-RADS predictability and its management recommendation must be evaluated in the Indian contexts[2]

  5. Study Aims


  6. The present study intended to evaluate the diagnostic accuracy and positive predictive value of the BI-RADS assessment score with that of the histopathological finding taken as gold standard. We also estimate the positive predictability value of the mammographic morphological lexicons in terms of the malignant outcome.

  7. Administrative Organization


  8. Patients attending our breast cancer unit during the study period with various breast complaints and those who were subjected to mammographic imaging and histopathological examination will be included in the study. Department of radiodiagnosis and surgical oncology are primarily involved in this study.

  9. Study Design-retrospective analytical


    1. Study population general description: Patients attending our breast cancer unit during the study period with various breast complaints.
    2. Sample size determination and power analyses: Considering existing disease prevalence using sample size calculator came to be approximately 250.
    3. Study outcomes/endpoints: NA


  10. Study Procedures


    1. Subject selection procedures: This study was a retrospective cross-sectional study which was conducted in the department of radiodiagnosis, AH Regional Cancer Center, Cuttack. Mammography, detailed clinical and histopathological data over 12 months will be retrospectively analyzed with reference to mammography report in BI-RADS and biopsy report to know the validity of BI-RADS scoring in suspicious and malignant category.


      1. Sampling plan including inclusion/exclusion criteria


      2. Inclusion criteria: 1. Female patients of all ages presenting with breast complaints may it be lump, pain, or discharge.

        Exclusion criteria: 1. Male patients; 2. Patients with non-retrievable clinical record and histopathology report; 3. BI-RADS 0

      3. Recruitment procedures


        1. Where will recruitment occur? Department of RADIODIAGNOSIS
        2. Where and when will consent be obtained? NAWhat is the advertising plan, if applicable? NA
        3. What recruitment materials will be provided to the potential participant (brochures/information sheets/video presentation)? NA


        4. Screening procedures: NA


      4. Randomization procedures: NA
      5. Study Intervention: NA
      6. Study assessments and activities: DONE, Internal data validation and cross checks.


    2. Safety Monitoring Plan: NA
    3. Analysis Plan


    4. The outcome of histopathology will be categorized as positive and negative for malignancy, which will be treated as the outcome of the study for predictive analysis. Demographic and morphological characteristics will be described in terms of frequency and proportions. The proportions will be compared by using the Chi-squared test. The receiver operating characteristics (ROC) curve will be constructed taking sensitivity and 1-specificity in X- and Y-axes. The area under the curve (AUC) will be measured, which will denote the measure of the comparability of BI-RADS with that of histopathology findings. Statistical analysis will be performed using SPSS v. 20.

    5. Literature Cited


    1. Sickles EA, d'Orsi CJ, Bassett LW, Appleton CM, Berg WA, Burnside ES. Acr bi-rads® mammography. ACR BI-RADS® atlas, breast imaging reporting and data system. 2013 Feb; 5:2013.
    2. Heller SL, Hudson S, Wilkinson LS. Breast density across a regional screening population: effects of age, ethnicity and deprivation. The Brit j of radiology. 2015 Nov; 88 (1055):20150242.




 
  References Top

1.
Heer E, Harper A, Escandor N, Sung H, McCormack V, Fidler-Benaoudia MM. Global burden and trends in premenopausal and postmenopausal breast cancer: A population-based study. Lancet Glob Health 2020;8:e1027-37.  Back to cited text no. 1
    
2.
Shetty R, Mathew RT, Vijayakumar M. Incidence and pattern of distribution of cancer in India: A secondary data analysis from six population-. Based cancer registries. Cancer Res Stat Treat 2020;3:678-82.  Back to cited text no. 2
  [Full text]  
3.
Malvia S, Bagadi SA, Dubey US, Saxena S. Epidemiology of breast cancer in Indian women. Asia Pac J Clin Oncol 2017;13:289-95.  Back to cited text no. 3
    
4.
Sickles EA, d'Orsi CJ, Bassett LW, Appleton CM, Berg WA, Burnside ES. ACR BI-RADS Mammography. Atlas, Breast Imaging Reporting and Data System, Vol. 5, American College of Radiology, Reston. 2013.  Back to cited text no. 4
    
5.
Heller SL, Hudson S, Wilkinson LS. Breast density across a regional screening population: Effects of age, ethnicity and deprivation. Br J Radiol 2015;88:20150242.  Back to cited text no. 5
    
6.
Wiratkapun C, Bunyapaiboonsri W, Wibulpolprasert B, Lertsithichai P. Biopsy rate and positive predictive value for breast cancer in BI-RADS category 4 breast lesions. J Med Assoc Thai 2010;93:830-7.  Back to cited text no. 6
    
7.
Leblebici IM, Bozkurt S, Eren TT, Ozemir IA, Sagiroglu J, Alimoglu O. Comparison of clinicopathological findings among patients whose mammography results were classified as category 4 subgroups of the BI-RADS. North Clin Istanb 2014;1:1-5.  Back to cited text no. 7
    
8.
Lehman CD, Arao RF, Sprague BL, Lee JM, Buist DS, Kerlikowske K, et al. National performance benchmarks for modern screening digital mammography: Update from the Breast Cancer Surveillance Consortium. Radiology 2017;283:49-58.  Back to cited text no. 8
    
9.
Burrell HC, Evans AJ, Wilson AR, Pinder SE. False-negative breast screening assessment. What lessons can we learn? Clin Radiol 2001;56:385-8.  Back to cited text no. 9
    
10.
Evans KK, Birdwell RL, Wolfe JM. If you don't find it often, you often don't find it: Why some cancers are missed in breast cancer screening. PLoS One 2013;8:e64366.  Back to cited text no. 10
    
11.
Kojima Y, Tsunoda H. Mammography and ultrasound features of triple-negative breast cancer. Breast Cancer 2011;18:146-51.  Back to cited text no. 11
    
12.
Scimeca M, Giannini E, Antonacci C, Pistolese CA, Spagnoli LG, Bonanno E. Microcalcifications in breast cancer: An active phenomenon mediated by epithelial cells with mesenchymal characteristics. BMC Cancer 2014;14:286.  Back to cited text no. 12
    
13.
Weigel S, Heindel W, Heidrich J, Hense HW, Heidinger O. Digital mammography screening: Sensitivity of the programme dependent on breast density. Eur Radiol 2017;27:2744-51.  Back to cited text no. 13
    
14.
Cuesta Cuesta AB, Martín Ríos MD, Noguero Meseguer MR, García Velasco JA, de Matías Martínez M, Sotillos SB, et al. Accuracy of tumor size measurements performed by magnetic resonance, ultrasound and mammography, and their correlation with pathological size in primary breast cancer. Cir Esp (Engl Ed) 2019;97:391-6.  Back to cited text no. 14
    
15.
Luparia A, Mariscotti G, Durando M, Ciatto S, Bosco D, Campanino PP, et al. Accuracy of tumour size assessment in the preoperative staging of breast cancer: Comparison of digital mammography, tomosynthesis, ultrasound and MRI. Radiol Med 2013;118:1119-36.  Back to cited text no. 15
    
16.
Harirchi I, Karbakhsh M, Kashefi A, Momtahen AJ. Breast cancer in Iran: Results of a multi-center study. Asian Pac J Cancer Prev 2004;5:24-7.  Back to cited text no. 16
    
17.
Cooper K. Springhouse: Springhouse Corp. Pathophysiology Made Incredibly Easy. 1998.  Back to cited text no. 17
    
18.
Surakasula A, Nagarjunapu GC, Raghavaiah KV. A comparative study of pre-and post-menopausal breast cancer: Risk factors, presentation, characteristics and management. J Res Pharm Pract 2014;3:12-8.  Back to cited text no. 18
[PUBMED]  [Full text]  
19.
Chauhan A, Subba SH, Menezes RG, Shetty BS, Thakur V, Chabra S, et al. Younger women are affected by breast cancer in South India-a hospital-based descriptive study. Asian Pac J Cancer Prev 2011;12:709-11.  Back to cited text no. 19
    
20.
Elmore JG, Wells CK, Howard DH, Feinstein AR. The impact of clinical history on mammographic interpretations. JAMA 1997;277:49-52.  Back to cited text no. 20
    
21.
Arsalan FA, Subhan A, Rasul SH, Jalali UZ, Yousuf M, Mehmood Z. Sensitivity and specificity of BI-RADS scoring system in carcinoma of breast. J Surg Pak 2010;15:38-43.  Back to cited text no. 21
    
22.
Naeem M, Khan N, Aman Z, Nasir A, Samad A, Khattak A. Pattern of breast cancer: Experience at Lady Reading Hospital, Peshawar. J Ayub Med Coll Abbottabad 2008;20:22-5.  Back to cited text no. 22
    


    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
  Search
 
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  Materials and Me...Supplementary Ap...
  In this article
Abstract
Introduction
Results
Discussion
Conclusion
References
Article Figures
Article Tables

 Article Access Statistics
    Viewed334    
    Printed4    
    Emailed0    
    PDF Downloaded43    
    Comments [Add]    

Recommend this journal