scholarly journals Evaluation of diagnostic ultrasound use in a breast cancer detection strategy in Northern Peru

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252902
Author(s):  
Segen Aklilu ◽  
Carolyn Bain ◽  
Pooja Bansil ◽  
Silvia de Sanjose ◽  
Jorge A. Dunstan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Medical Records ◽  
Point Of Care ◽  
Breast Ultrasound ◽  
Breast Cancer Detection ◽  
Clinical Breast Exam ◽  
Diagnostic Impact ◽  
Clinical Breast

To evaluate the diagnostic impact of point-of-care breast ultrasound by trained primary care physicians (PCPs) as part of a breast cancer detection program using clinical breast exam in an underserved region of Peru. Medical records and breast ultrasound images of symptomatic women presenting to the Breast Cancer Detection Model (BCDM) in Trujillo, Peru were collected from 2017–2018. Performance was measured against final outcomes derived from regional cancer center medical records, fine needle aspiration results, patient follow-up (sensitivity, specificity, positive, and negative predictive values), and by percent agreement with the retrospective, blinded interpretation of images by a fellowship-trained breast radiologist, and a Peruvian breast surgeon. The diagnostic impact of ultrasound, compared to clinical breast exam (CBE), was calculated for actual practice and for potential impact of two alternative reporting systems. Of the 171 women presenting for breast ultrasound, 23 had breast cancer (13.5%). Breast ultrasound used as a triage test (current practice) detected all cancer cases (including four cancers missed on confirmatory CBE). PCPs showed strong agreement with radiologist and surgeon readings regarding the final management of masses (85.4% and 80.4%, respectively). While the triage system yielded a similar number of biopsies as CBE alone, using the condensed and full BI-RADS systems would have reduced biopsies by 60% while identifying 87% of cancers immediately and deferring 13% to six-month follow-up. Point-of-care ultrasound performed by trained PCPs improves diagnostic accuracy for managing symptomatic women over CBE alone and enhances access. Greater use of BI-RADS to guide management would reduce the diagnostic burden substantially.

A Robust Deep Neural Network Based Breast Cancer Detection and Classification

2020 ◽  
Vol 19 (01) ◽  
pp. 2050007
Author(s):  
Romany F. Mansour
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Adaptive Learning ◽  
Medical Records ◽  
Breast Cancer Detection ◽  
Aggregate Model ◽  
Element Analysis ◽  
Linear Discriminant ◽  
Characteristic Extraction ◽  
Assessment Measures

The exponential upward push in breast cancer cases across the globe has alarmed academia-industries to obtain certain more effect and strong Breast cancer laptop Aided prognosis (BC-CAD) device for breast most cancers detection. Some of techniques have been evolved with focus on case centric segmentation, feature extraction and class of breast cancer Histopathological photos. However, rising complexity and accuracy regularly demands more sturdy answer. Recently, Convolutional Neural community (CNN) has emerged as one of the maximum efferent techniques for medical records evaluation and diverse picture classification issues. On this paper, a notably strong and green BC-CAD solution has been proposed. Our proposed gadget consists of pre-processing, more suitable adaptive learning based totally Gaussian aggregate model (GMM), connected element analysis based vicinity of interest localization, and AlexNet-DNN primarily based characteristic extraction. The precept factor analysis (PCA) and Linear Discriminant analysis (LDA) primarily based on characteristic selection that's used as dimensional discount. One of the blessings of the proposed method is that not one of the current dimensional reduction algorithms hired with SVM to perform breast most cancers detection and class. The overall results acquired signify that the AlexNet-DNN based capabilities at completely connected layer; FC6 together with LDA dimensional discount and SVM-based totally classification outperforms other country-of-artwork techniques for breast cancer detection. The proposed method completed 96.20 for AlexNet-FC6 and 96.70 for AlexNet-FC7 in term of assessment measures.

scholarly journals Breast cancer detection: radiologists’ performance using mammography with and without automated whole-breast ultrasound

2010 ◽  
Vol 20 (11) ◽  
pp. 2557-2564 ◽  
Author(s):  
Kevin M. Kelly ◽  
Judy Dean ◽  
Sung-Jae Lee ◽  
W. Scott Comulada
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Breast Ultrasound ◽  
Breast Cancer Detection

scholarly journals Dietary fibre and risk of colorectal cancer in the Breast Cancer Detection Demonstration Project (BCDDP) follow-up cohort

2003 ◽  
Vol 32 (2) ◽  
pp. 234-239 ◽  
Author(s):  
Volker Mai ◽  
Andrew Flood ◽  
Ulrike Peters ◽  
James V Lacey ◽  
Catherine Schairer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Colorectal Cancer ◽  
Cancer Detection ◽  
Dietary Fibre ◽  
Breast Cancer Detection ◽  
Demonstration Project

scholarly journals Early Clinical Impact of Diagnostic Breast Ultrasound Performed by General Practitioners and Nurses in Rwanda

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 38s-38s
Author(s):  
L.E. Pace ◽  
J.M.V. Dusengimana ◽  
V. Rugema ◽  
V. Hategekimana ◽  
J.B. Bigirimana ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Clinical Care ◽  
Breast Ultrasound ◽  
Clinical Role ◽  
Detection Rates ◽  
Breast Masses ◽  
Management Plans ◽  
The Impact

Background: Diagnostic breast ultrasound (US) could be an important tool for early detection of breast cancer in low-resource settings, where efficient strategies to refine the likelihood of malignancy among palpable breast masses are needed. However, the feasibility and clinical role of diagnostic ultrasound in such settings has not been described. We trained 4 general practitioner doctors (GPs) and 5 nurses in diagnostic breast US at a rural district hospital in Rwanda that serves as a cancer referral facility. Aim: Assess management plans, biopsy rates and patient diagnoses after nurse- and GP-performed breast ultrasounds to determine the impact of diagnostic US on clinical care. Methods: We reviewed outcomes from trainees' ultrasounds during 21 months of in-person and electronic training and mentorship by Boston-based radiologists. Trainees' US assessments and management plans were recorded on structured clinical forms. Patient diagnoses and follow-up were extracted from medical records using a standardized data collection form. Among patients who received breast US, we examined a) clinicians' management plans; b) biopsy rate; c) cancer detection rate; c) rate of benign diagnoses; d) cancers diagnosed among patients who were sent home after initial evaluation. Results: Between January 1, 2016 and September 30, 2017, 307 patients with breast concerns had a diagnostic breast US and a documented trainee US assessment. Of these, following their initial US, 158 (51%) were recommended to receive a biopsy, 30 (10%) were recommended to have aspiration/drainage, 49 (16%) were recommended for clinical or US surveillance, 1 (0.3%) was referred to another facility, 65 (21%) were discharged, and 4 (all with no abnormalities on US) had missing recommendations. Of those recommended for biopsy at initial presentation, 151 (96%) had a biopsy at that time. 56 (37%) were diagnosed with breast cancer, 37 (25%) with fibroadenoma, 7 (5%) with lactating adenoma, and 50 (33%) with other benign diagnoses. Among those with breast masses on US (n=255), 149 (58%) received a biopsy and 55 (22%) were diagnosed with cancer. As of November 23, 2017, all patients ultimately diagnosed with cancer had had a biopsy at their initial visit, and no patients who had been discharged or recommended for clinical or radiographic surveillance had been subsequently diagnosed with cancer. Conclusion: Diagnostic breast US by GPs and nurses has been a useful tool in the evaluation of breast lesions, including palpable masses, at a rural cancer facility in Rwanda. Early findings suggest that it has allowed avoidance of biopsy for 42% of patients with breast masses noted on US. Clinical follow-up and evaluation are ongoing to assess longer-term patient outcomes, cancer detection rates among patients who are not initially biopsied, and rates of follow-up among patients recommended to have clinical or radiographic surveillance.

Comparison of various breast cancer detection methods with survival rates

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 17033-17033
Author(s):  
S. Misra ◽  
S. Tarr ◽  
D. Pratt
Keyword(s):  
Breast Cancer ◽  
Survival Time ◽  
Cancer Detection ◽  
Survival Rates ◽  
Staging System ◽  
Breast Cancer Detection ◽  
Detection Methods ◽  
Breast Cancer Patients ◽  
Estrogen Receptor Positivity

17033 Background: The role of mammography (MG) but not of breast self-exam (BSE) and clinical breast exam (CBE) in breast cancer detection and survival is well documented. This study compares the different methods of breast cancer detection and subsequent survival rates, analyzing the differences even within the same stage of the disease. Methods: Retrospective review of 1,259 patients was done using the hospital Tumor Registry data. Only patients with stage I, IIA and IIB are included and were diagnosed between April 1992 to December 2005 with follow up ranging from June 1993 to August 2006. The detection methods studied include BSE, CBE, MG and ultrasonography (USG). Parametric tests were conducted. Results: Mean age of the sample was 62 years (range 24–96). There were 293 BSE, 64 CBE, 885 MG, 17 USG detected breast cancer patients. Mean size of mass at presentation was 19 mm (range 1–110). Mean survival time for patients detected with breast cancer till August 2001 was 76 months (range 1–163). 67% patients survived 5 years or more and 12% survived more than 10 years. Mean survival for BSE/CBE and MG/USG group was 43 and 57 months respectively. This difference in survival is significant p< .05; The average survival time by stages I, IIA, IIB for BSE was 47, 45, 38 months, for CBE it was 43, 39, 51 months, for MG it was 57, 59, 50 months and for USG group it was 52, 47, 95 months respectively. Even within the same stage, the method of detection affected survival with the BSE and CBE group having less survival rates (Tukey Test mean difference 0.54, 95% C.I 42–66 and 0.38, 95% C.I 15–61) respectively than the MG group. Survival time also positively correlated with cancer recurrence (r =.7), family history (r = .06) and negatively correlated with age (r = -.09), size of tumor (r = -.09), estrogen receptor positivity status (r = -.06) all with (p < 0.05). We believe this study underestimates overall survival rate as the last follow up date was taken as an end point and also the survival rates are not disease specific survival. Conclusions: MG/USG group show higher survival rates compared to BSE/CBE across the early stages of breast cancer. Even within the same stage, the method of detection affects survival with MG/USG detected cases having more favorable outcomes. May be our current staging system for breast cancer is inadequate and needs revision. No significant financial relationships to disclose.

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