A five year audit of mammography in a tertiary hospital, North Central Nigeria

Akande, Halimat; Olafimihan, B.B.; Oyinloye, Olalekan Ibukun

doi:10.4103/0300-1652.160401

Cited by 15 publications

(21 citation statements)

References 24 publications

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“…Of these benign lesions, the most frequently diagnosed were fibroadenoma, followed by breast cysts. Most breast lesions had been reported to be benign in previous studies (1,2,3,14,15), this is in tandem with our finding which also reported that fibroadenoma of the breast was more prevalent than other breast lesions, though some studies had postulated other breast lesions such as fibrocystic diseases to be commoner (2). The characteristics malignant breast features we encountered in this study were dense breast mass with irregular, multilobular and spiculated margins which may be poorly defined.…”

Section: Discussionsupporting

confidence: 91%

Mammographic profiles of women with symptomatic breast diseases in Port Harcourt, Rivers State, Nigeria

Onwuchekwa¹,

Alazigha²

2018

Research Journal of Health Sciences

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Objectives: Most patients with breast lesions are usually anxious especially with the knowledge that breast cancer is associated with high rate of mortality and morbidity. The aim of this study is to evaluate the characteristics of breast lesion as depicted by mammography in women with symptomatic breast diseases.Methods: This was a prospective descriptive analytical study of women with symptomatic breast diseases who had mammography between January 2012 and December 2016 at our health facilities. Data sheet was developed to record the patients' biodata, indication for referral, and mammographic findings.Results: During the period of study, 166 females with symptomatic breast lesions had diagnostic mammography. The mean age was 49.29years ± 11.12. Sixty-five (39.2%) patients presented with breast lump, 54(32.5%) had breast pain, while 15 (9.0%) had nipple discharge. Seventy-five (45.2%) of the patients had no obvious lesion on mammogram, while 91(54.8%) had identifiable lesions. The masses were multiple in 9 (12.7%), diffused in 4 (5.6%) and solitary in 58 (81.7%). Six (3.6%) cases were found to have only calcifications. BI-RADS category 1 was the most prevalent constituting 75(45.2%). This was followed by BI-RADS categories 3 & 4, each constituted 30 (18.1%) cases. Conclusion:Breast diseases are common in our environment and this review had shown that most of these lesions were benign. Breast lumps and breast pains were the commonest indication for the mammograms and significant number of the patients had no demonstrable lesions on mammogram. BI-RADS category 3 and 4 were more common. Conclusion:Les maladies du sein sont courantes dans notre environnement et cette revue a montré que la plupart de ces lésions étaient bénignes. Les grosseurs de poitrine et les douleurs mammaires étaient les indications les plus courantes pour les mammographies et un nombre significatif de patientes n'avaient pas de lésions démontrables à la mammographie. BI-RADS catégories 3 et 4 étaient plus fréquents.

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Section: Discussionsupporting

confidence: 91%

Mammographic profiles of women with symptomatic breast diseases in Port Harcourt, Rivers State, Nigeria

Onwuchekwa¹,

Alazigha²

2018

Research Journal of Health Sciences

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“…Similarly, few males were reported to have undergone diagnostic mammography in some parts of Nigeria [2,14] in contrast to most other studies that had only female participants [1,13,16,17,19]. This underscores the fact that breast diseases are not exclusive to females, though the incidence of breast cancer in males is very low.…”

Section: Discussioncontrasting

confidence: 47%

“…Some studies have reported on the mammographic findings in different parts of the country [1,2,[13][14][15][16][17][18][19]. About half of the participants in this study were within the age group 40-49 years.…”

Section: Discussionmentioning

confidence: 96%

“…About half of the participants in this study were within the age group 40-49 years. Some studies within [2,18] and outside Nigeria [20,21] also revealed that a greater percentage of women presenting for mammography fall within this age group. This is may be due to the fact that baseline routine mammographic evaluation commences by the fifth decade of life [2].…”

Section: Discussionmentioning

confidence: 99%

“…Magnetic resonance imaging (MRI), Digital mammography, breast tomosynthesis, automated breast ultrasound scan, and shear wave elastography play key roles in breast imaging in the developed nations. [2][3][4][5] On the contrary, in the developing nations such sophisticated imaging equipment is not readily available due to resource constraints. Studies have reported that benign breast diseases are commoner than their malignant counterpart worldwide.…”

Section: Introductionmentioning

confidence: 99%

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Introducing Digital Mammography in a Resource Constrained Setting: Spectrum of Imaging Findings and Diagnostic Value in Ado-Ekiti, South Western Nigeria

Aduayi¹,

Akanbi²,

Aduayi³

2016

IJMI

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Early diagnosis and treatment achieved through Mammographic screening plays a key role in the reduction of breast related morbidities and mortalities in middle and low income countries. This study highlights the spectrum of digital mammography findings in a tertiary health institution in Ado-Ekiti, South western Nigeria. A cross-sectional descriptive study of clients who presented for digital mammography at a newly equipped hospital was conducted within a year. The mammograms were reviewed by two radiologists and overall imaging findings were classified using the American College of Radiology Breast Imaging Reporting and Data System (ACR-BIRADS). Data analysis was done using SPSS version 20.0. A total of 154 clients with age range of 37 to 85 years (mean age of 51± 9.6years) underwent mammography during the study period. There was one male and 153 females out of which 69(45.1%) were postmenopausal while 84(54.9%) were premenopausal. Major clinical indications for mammography included routine breast cancer screening (N= 59, 38.3%), breast lump (N= 43, 27.9%) and breast pain (N=34, 22.1%). Mammograms were normal in 37(24.0%), inconclusive in 51(33.1%) and abnormal in 66(42.9%) clients. Abnormal mammographic findings included various forms of calcifications (N=56, 36.4%), breast opacities/masses (N=42, 27.3%), axillary lymphadenopathy (N=14, 9.0%), focal glandular asymmetry (N=10, 6.5%) and architectural distortion (N=6, 3.9%). About 55(35.7%) patients underwent additional imaging with ultrasonography, out of which 32(58.2%) had positive sonographic findings. The use of ultrasonography for additional imaging in cases of inconclusive mammograms improves the diagnostic yield. A greater proportion of the clients had mammography done for diagnostic reasons rather than screening purposes. Hence there is the need for increased awareness of screening mammography among the women in resource constrained settings.

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Automated annotation and classification of BI-RADS assessment from radiology reports

Castro

Tseytlin

Medvedeva

et al. 2017

Journal of Biomedical Informatics

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The Breast Imaging Reporting and Data System (BI-RADS) was developed to reduce variation in the descriptions of findings. Manual analysis of breast radiology report data is challenging but is necessary for clinical and healthcare quality assurance activities. The objective of this study is to develop a natural language processing (NLP) system for automated BI-RADS categories extraction from breast radiology reports. We evaluated an existing rule-based NLP algorithm, and then we developed and evaluated our own method using a supervised machine learning approach. We divided the BI-RADS category extraction task into two specific tasks: (1) annotation of all BI-RADS category values within a report, (2) classification of the laterality of each BI-RADS category value. We used one algorithm for task 1 and evaluated three algorithms for task 2. Across all evaluations and model training, we used a total of 2159 radiology reports from 18 hospitals, from 2003 to 2015. Performance with the existing rule-based algorithm was not satisfactory. Conditional random fields showed a high performance for task 1 with an F-1 measure of 0.95. Rules from partial decision trees (PART) algorithm showed the best performance across classes for task 2 with a weighted F-1 measure of 0.91 for BIRADS 0–6, and 0.93 for BIRADS 3–5. Classification performance by class showed that performance improved for all classes from Naïve Bayes to Support Vector Machine (SVM), and also from SVM to PART. Our system is able to annotate and classify all BI-RADS mentions present in a single radiology report and can serve as the foundation for future studies that will leverage automated BI-RADS annotation, to provide feedback to radiologists as part of a learning health system loop.

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A five year audit of mammography in a tertiary hospital, North Central Nigeria

Cited by 15 publications

References 24 publications

Mammographic profiles of women with symptomatic breast diseases in Port Harcourt, Rivers State, Nigeria

Mammographic profiles of women with symptomatic breast diseases in Port Harcourt, Rivers State, Nigeria

Introducing Digital Mammography in a Resource Constrained Setting: Spectrum of Imaging Findings and Diagnostic Value in Ado-Ekiti, South Western Nigeria

Automated annotation and classification of BI-RADS assessment from radiology reports

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