A novel, computer-aided, scanning platform agnostic solution for grading carcinomas in breast biopsy whole slide images.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12575-e12575
Author(s):  
Nicolas M Orsi ◽  
Tathagata Dasgupta ◽  
Satabhisa Mukhopadhyay ◽  
Michele Cummings ◽  
Angelene Berwick
Keyword(s):  
Breast Cancer ◽  
Gold Standard ◽  
Breast Biopsy ◽  
Digital Pathology ◽  
Observer Agreement ◽  
P Value ◽  
Tissue Sampling ◽  
Tertiary Referral Center ◽  
Resection Specimen ◽  
Whole Slide Images

e12575 Background: The determination of breast cancer grade remains a problematic diagnostic issue in biopsies due to limited tissue sampling and the inherent inter-observer variability associated with the Nottingham (histologic) score. Significantly, biopsy grading corresponds only moderately with that based on excision specimens, with discordance rates of 21-30.0%, which is a concern for cases managed neoadjuvantly or with minimally ablative therapy. Although the advent of digital pathology has encouraged endeavors to automate breast cancer detection and grading, no method has yet received regulatory approval for clinical use or proven to be a platform agnostic solution. Methods: This study was the blinded clinical validation a novel, FDA breakthrough designation approved automated device-based predictive solution which uses a surrogate scale to determine breast carcinoma grade in core biopsies using H&E slide whole slide images (WSIs) only. Non-preselected malignant breast core biopsy clinical cases (n=173 WSIs; 107 cases) covering a broad spectrum of breast cancer morphological subtypes were scanned at x20 magnification on both on Aperio high-throughput T2/T3 systems (.SVS files) and Roche-Ventana DP200 scanners (.BIF files). The diagnostic gold standard reference was the reports of tertiary referral center breast subspecialty consultant histopathologists. Diagnostic outputs were also compared to case-matched resection specimen grades. Comparison of diagnostic outcomes with pathologists as gold standard was done using inter observer agreement (cohen kappa) with 95% CI and statistically significant chi-squared test p-value for two different scanner platforms. Results: Although biopsy-based diagnostic concordance with pathologists was very good, the device actually delivered a much better concordance between case-matched biopsy and resection specimen (accuracy: 95%, cohen kappa: 0.91) relative to pathologists’ assessments (accuracy: 80%). Conclusions: This indicates that the use of a single continuous surrogate grading scale is much less affected by limited tissue sampling than conventional ordinal morphological scales. This level of performance was independent of file format analyzed, demonstrating the device’s platform agnosia.

scholarly journals Comparison of the Accuracy of Thermography and Mammography in the Detection of Breast Cancer

Breast Care ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. 260-264 ◽  
Author(s):  
Ramesh Omranipour ◽  
Ali Kazemian ◽  
Sadaf Alipour ◽  
Masoume Najafi ◽  
Mansour Alidoosti ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Diagnosis ◽  
Gold Standard ◽  
Breast Biopsy ◽  
Screening Mammography ◽  
Tissue Sampling ◽  
Predictive Values ◽  
Referral Center ◽  
Medical Centers ◽  
Sensitivity Specificity

Background: Benefits and harms of screening mammography have been disputed in recent years. This fact, along with the limitations of mammography as well as its unavailability in all our medical centers, tempted us to evaluate the accuracy of thermography in detecting breast abnormalities. Patients and Methods: All patients who were candidates for breast biopsy were examined by both mammography and thermography before tissue sampling in a referral center between January 2013 and January 2014. We defined sensitivities and specificities, and positive predictive values (PPVs) and negative predictive values (NPVs), of the 2 modalities in comparison with histologic results as the gold standard. Results: 132 patients were included. The median age of all patients was 49.5 ± 10.3 years (range 24-75 years). The sensitivity, specificity, PPV, NPV, and accuracy for mammography were 80.5%, 73.3%, 85.4%, 66.0%, and 76.9%, respectively, whereas for thermography the figures were 81.6%, 57.8%, 78.9%, 61.9%, and 69.7%, respectively. Conclusion: Our study confirms that, at the present time, thermography cannot substitute for mammography for the early diagnosis of breast cancer.

scholarly journals COMPARATIVE FEATURES OF OPEN SOURCE SOFTWARE PRODUCTS FOR THE DEVELOPMENT OF AN AUTOMATED BREAST CANCER DIAGNOSTIC PROGRAM

2019 ◽  
Vol 7 (4) ◽  
pp. 377-385
Author(s):  
V. Kovalev ◽  
Y. Diachenko ◽  
V. Malyshev ◽  
S. Rjabceva ◽  
O. Kolomiets ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Open Source ◽  
Cancer Diagnosis ◽  
Open Source Software ◽  
Imaging Techniques ◽  
Digital Pathology ◽  
Third Party ◽  
Histopathological Diagnosis ◽  
Histological Verification ◽  
Whole Slide Images

Breast cancer is one of the most common cancer diseases in the world among women. The reliability of histological verification of breast cancer depends on pathologist’s experience, knowledge, his willingness to self-improve and study specialized literature. Digital pathology is also widely used for educational purposes, in telepathology, teleconsultation and research projects. Recently developed Whole Slide Image (WSI) system opens great opportunities in the histopathological diagnosis quality improvement. Digital whole-slide images provide the effective use of morphometry and various imaging techniques to assist pathologists in quantitative and qualitative evaluation of histopathological preparations. The development of software for morphological diagnosis is important for improving the quality of histological verification of diagnosis in oncopathology. The purpose of this work is to find and benchmark existing open-source software for the whole-slide histological images processing. Choosing an open source program is an important step in developing an automated breast cancer diagnosis program. The result is a detailed study of open-source software: ASAP, Orbit, Cytomine and QuPath. Their features and methods of image processing were analyzed. QuPath software has the best characteristics for extending it with an automated module for the cancer diagnosis. QuPath combines a user-friendly, easy-to-use interface, customizable functionality, and moderate computing power requirements. Besides, QuPath works with whole-slide images with immunohistochemical markers; features implemented in this software allow making a morphometric analysis. QuPath saves time for a graphical user interface development and provides a scalable system to add new key features. QuPath supports third-party MATLAB and Python extensions.

scholarly journals Atypical Ductal Hyperplasia after Vacuum-Assisted Breast Biopsy: Can We Reduce the Upgrade to Breast Cancer to an Acceptable Rate?

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1120
Author(s):  
Luca Nicosia ◽  
Antuono Latronico ◽  
Francesca Addante ◽  
Rossella De Santis ◽  
Anna Carla Bozzini ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Invasive Carcinoma ◽  
Breast Biopsy ◽  
Ductal Carcinoma ◽  
Atypical Ductal Hyperplasia ◽  
Univariate Analysis ◽  
Surgical Excision ◽  
P Value ◽  
Ductal Hyperplasia

(1) Background: to evaluate which factors can reduce the upgrade rate of atypical ductal hyperplasia (ADH) to in situ or invasive carcinoma in patients who underwent vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. (2) Methods: 2955 VABBs were reviewed; 141 patients with a diagnosis of ADH were selected for subsequent surgical excision. The association between patients’ characteristics and the upgrade rate to breast cancer was evaluated in both univariate and multivariate analyses. (3) Results: the upgrade rates to ductal carcinoma in situ (DCIS) and invasive carcinoma (IC) were, respectively, 29.1% and 7.8%. The pooled upgrade rate to DCIS or IC was statistically lower at univariate analysis, considering the following parameters: complete removal of the lesion (p-value < 0.001); BIRADS ≤ 4a (p-value < 0.001); size of the lesion ≤15 mm (p-value: 0.002); age of the patients <50 years (p-value: 0.035). (4) Conclusions: the overall upgrade rate of ADH to DCIS or IC is high and, as already known, surgery should be recommended. However, ADH cases should always be discussed in multidisciplinary meetings: some parameters appear to be related to a lower upgrade rate. Patients presenting these parameters could be strictly followed up to avoid overtreatment.

scholarly journals Learning from crowds in digital pathology using scalable variational Gaussian processes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Miguel López-Pérez ◽  
Mohamed Amgad ◽  
Pablo Morales-Álvarez ◽  
Pablo Ruiz ◽  
Lee A. D. Cooper ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Gaussian Processes ◽  
Gold Standard ◽  
Digital Pathology ◽  
Machine Learning Algorithms ◽  
Medical Applications ◽  
Comparable Performance ◽  
Primary Determinant ◽  
Scale Data

AbstractThe volume of labeled data is often the primary determinant of success in developing machine learning algorithms. This has increased interest in methods for leveraging crowds to scale data labeling efforts, and methods to learn from noisy crowd-sourced labels. The need to scale labeling is acute but particularly challenging in medical applications like pathology, due to the expertise required to generate quality labels and the limited availability of qualified experts. In this paper we investigate the application of Scalable Variational Gaussian Processes for Crowdsourcing (SVGPCR) in digital pathology. We compare SVGPCR with other crowdsourcing methods using a large multi-rater dataset where pathologists, pathology residents, and medical students annotated tissue regions breast cancer. Our study shows that SVGPCR is competitive with equivalent methods trained using gold-standard pathologist generated labels, and that SVGPCR meets or exceeds the performance of other crowdsourcing methods based on deep learning. We also show how SVGPCR can effectively learn the class-conditional reliabilities of individual annotators and demonstrate that Gaussian-process classifiers have comparable performance to similar deep learning methods. These results suggest that SVGPCR can meaningfully engage non-experts in pathology labeling tasks, and that the class-conditional reliabilities estimated by SVGPCR may assist in matching annotators to tasks where they perform well.

scholarly journals Preoperative Staging in Women with Known Breast Cancer: Comparison between Digital Breast Tomosynthesis (DBT) and Magnetic Resonance Imaging (MRI)

2018 ◽  
Vol 7 (2) ◽  
pp. 33
Author(s):  
Francesca Galati ◽  
Flaminia Marzocca ◽  
Andrea Tancredi ◽  
Emmanuel Collalunga ◽  
Carlo Catalano ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Gold Standard ◽  
Preoperative Staging ◽  
Digital Breast Tomosynthesis ◽  
P Value ◽  
Resonance Imaging ◽  
Breast Tomosynthesis ◽  
Magnetic Resonance Imaging Mri

Objectives To prospectively evaluate the accuracy in tumor extent and size assessment of Digital Breast Tomosynthesis (DBT) and Magnetic Resonance Imaging (MRI) in women with known breast cancer, with pathological size as the gold standard. Methods From May 2014 to April 2016, 50 patients with known breast cancer were enrolled in our prospective study. All patients underwent MRI on a 3T magnet and DBT projections. Two radiologists, with 15 and 7 years of experience in breast imaging respectively, evaluated in consensus each imaging set unaware of the final histological examination. MR and DBT sensitivity, PPV and accuracy were calculated, using histology as the gold standard. McNemar test was used to compare MR and DBT sensitivity. Correlation and regression analyses were used to evaluate MRI vs Histology, DBT vs Histology and MRI vs DBT lesions tumor size agreement to histological results. Results On histological examination 70 lesions were detected. MRI showed 100% sensitivity, 96% PPV and 96% accuracy; DBT sensitivity was 81%, PPV 92% and accuracy 77%. McNemar test p-value was 0.0003. Lesions size Pearson correlation coefficient was 0.97 for MRI vs Histology, 0.92 for DBT vs Histology, (p-value&lt;0.0001). MRI vs DBT regression coefficient was 0.83. Conclusions MRI confirmed to be the most accurate imaging technique in preoperative staging of breast cancer. However, DBT showed very good accuracy, sensitivity and tumor size assessment and could be a valid tool for preoperative staging when MRI is contraindicated.

First experience with MRI-guided vacuum aspirated breast biopsy

2020 ◽  
pp. 25-31
Author(s):  
M. L. Mazo ◽  
O. E. Jacobs ◽  
O. S. Puchkova ◽  
M. V. Feldsherov ◽  
E. V. Kondratyev
Keyword(s):  
Breast Cancer ◽  
Breast Augmentation ◽  
Breast Biopsy ◽  
Breast Mri ◽  
Breast Tumors ◽  
High Tech ◽  
X Ray ◽  
Vacuum Aspiration ◽  
Mri Guided ◽  
Aesthetic Breast

The rate of detection of breast cancer by MRI, while other methods of radiological diagnosis are not sufficiently informative, ranges from 5.2 to 26.3 per cent. Suspicious breast tumors of category BI-RADS 4, 5 show morphological image-guided biopsy verification, in particular MRI with contrast. Purpose. To show the possibilities and features of carrying out MRI-guided vacuum breast biopsy, including after aesthetic breast augmentation. Material and methods. A comprehensive X-ray, ultrasound and MRI examination of 54 women aged between 28 and 70 years with different breast tumors was conducted. Of these, five were detected only by breast MRI with contrast, and were morphologically verified by MRI-guided vacuum aspiration biopsy. Results. 14 of the 54 patients with breast mass were diagnosed with breast cancer and 26 were diagnosed with benign diseases. The effectiveness of comprehensive examination and low-invasive high-tech MRI-guided procedures in early refined screening for breast cancer, including after aesthetic breast augmentation, has been demonstrated. MRI-guided vacuum-assisted breast biopsy is a fast, safe and accurate diagnostic method of morphological verification of suspicious breast tumors that do not have X-ray and ultrasound.

THE RELATION OF COPPING STRATEGY BY LOOKING SOCIAL SUPPORT WITH STRESS LEVEL OF BREAST CANCER PATIENT WHO GONE TROUGH CHEMOTHERAPY

2018 ◽  
Vol 1 (1) ◽  
pp. 51-54
Author(s):  
Sri Burhani Putri
Keyword(s):  
Breast Cancer ◽  
Social Support ◽  
Cancer Patient ◽  
Breast Cancer Patient ◽  
Cross Sectional Study ◽  
P Value ◽  
Spiritual Support ◽  
Cross Sectional ◽  
Breast Cancer Chemotherapy ◽  
Patient Stress

Breast cancer is one of the most common illness that killed woman. One of the therapy to cure breast cancer is chemotherapy. Chemotherapy has side effect either physical and psychology, that caused people who’s in chemo therapy, prone to stress. Stress effected by many factors, such as characteristic and chopping strategy that patient has been using. The aim of this research is to get a perspective about the relation of characteristic and chopping strategy with breast cancer patient stress, whose in chemo therapy. This research using cross sectional study and taking sample by using accidental sampling method. The data analyzed by using bavariat and multivariat with variable result shows that breast cancer patient stress who has chemo therapy realted to age characteristic (p value = 0.00) the time since they diagnosed with cancer (pvalue = 0.03), how long they have chemo therapy (pvalue = 0.00) and chopping strategyby looking social support (pvalue = 0.00) looking for spiritual (pvalue = 0.00) with dominan variable which related to stress is chopping strategy to looking spiritual support (coeffecients B = -1.139).   Key words : Breast cancer, chemotherapy, stress  

HUBUNGAN ANTARA UMUR DAN STATUS PERKAWINAN DENGAN KEJADIAN KANKER PAYUDARA DI INSTALASI BEDAH RUMAH SAKIT UMUM PUSAT DR. MOHAMMAD HOESIN PALEMBANG TAHUN 2012

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Rini Mayasari Rini Mayasari
Keyword(s):  
Breast Cancer ◽  
Marital Status ◽  
Cancer Incidence ◽  
Random Sampling ◽  
Breast Cancer Incidence ◽  
P Value ◽  
Chi Square ◽  
Cross Sectional ◽  
Systematic Random Sampling ◽  
Breast Cancer Event

ABSTRACT Breast cancer on the mark with the growth or uncontrolled growth of cells that are excessive. Factors affecting the incidence of breast cancer include maternal age, marital status, family history, hormone use, radiation, manarche, and obesity. The purpose of this study was to determine the relationship between Age and Marital Status of Mother with Breast Cancer incidence in the Installation Surgeon General Hospital Dr. Mohammad Hoesin Palembang in 2012. The study design was analytical descriptive with the approach in which the independent variables Cross Sectional Age Mother and Status Perkawianan and dependent variables in breast cancer incidence collected at the same time. The study population was all women who develop breast cancer in the Installation General Hospital Surgery Center Dr. Mohammad Hoesin Palembang in 2012 and samples taken by systematic random sampling with a sample of 130 respondents. The results of univariate analysis of data showed that respondents had breast cancer with a percentage of total 58 (44.61%) while respondents who had not had breast cancer totaled 72 by the percentage (63.39%). Respondents by Age Mothers who are at risk amounted to 34 by the percentage (26.15%) while respondents with Age Mothers who are not at risk amounted to 96 by the percentage (73.85%). Respondents by Marital Status is married and the mother who totaled 69 by the percentage (53.07%) and Marital Status with the status of unmarried women totaled 61 by the percentage (46.03%). Of Chi-Square test results found no significant relationship between Age Mothers with Breast Cancer event in which the p value = 0.007, no significant relationship between Marital Status in Breast Cancer event in which the p value = 0.030. Based on the results of the study, researchers suggest counseling efforts, medical knowledge and improve the quality of health services in order to reduce the incidence of breast cancer..   ABSTRAK Kanker payudara di tandai dengan pertumbuhan atau perkembangan tidak terkontrol dari sel-sel yang berlebihan. Faktor-faktor yang mempengaruhi kejadian kanker payudara antara lain umur ibu, status perkawinan, riwayat keluarga, penggunaan hormon, radiasi, manarche, dan obesitas. Tujuan penelitian ini adalah untuk mengetahui hubungan antara Umur Ibu dan Status Perkawinan dengan kejadian Kanker Payudara di Instalasi Bedah Rumah Sakit Umum Pusat Dr. Mohammad Hoesin Palembang Tahun 2012. Desain Penelitian ini adalah deskriptif analitik dengan pendekatan Cross Sectional dimana variabel independen Umur Ibu dan Status Perkawianan dan variabel dependen kejadian kanker payudara dikumpulkan dalam waktu yang bersamaan. Populasi penelitian ini adalah semua ibu yang menderita kanker payudara di Instalasi Bedah Rumah Sakit Umum Pusat Dr. Mohammad Hoesin Palembang Tahun 2012 dan sampel di ambil secara systematic random sampling dengan jumlah sampel 130 responden. Hasil analisis univariat data menunjukan responden yang mengalami Kanker Payudara berjumlah 58 dengan persentase sebesar (44,61%) sedangkan responden yang tidak mengalami Kanker Payudara berjumlah 72 dengan persentase (63,39%). Responden dengan Umur Ibu yang beresiko berjumlah 34 dengan persentase (26,15%) sedangkan responden dengan Umur Ibu yang tidak beresiko berjumlah 96 dengan persentase (73,85%). Responden dengan Status Perkawinan ibu yang berstatus kawin berjumlah 69 dengan persentase (53,07%) dan Status Perkawinan ibu yang berstatus tidak kawin berjumlah 61 dengan persentase (46,03%). Dari hasil uji Chi-Square didapatkan ada hubungan bermakna antara Umur Ibu dengan kejadian Kanker Payudara dimana p Value = 0,007, ada hubungan bermakna antara Status Perkawinan dengan kejadian Kanker Payudara dimana p Value = 0,030. Berdasarkan hasil penelitian, peneliti menyarankan upaya-upaya penyuluhan, pengetahuan tenaga medis dan meningkatkan mutu pelayanan kesehatan guna menurunkan angka kejadian kanker payudara.

scholarly journals A Digital Pathology Solution to Resolve the Tissue Floater Conundrum

2020 ◽  
Author(s):  
Liron Pantanowitz ◽  
Pamela Michelow ◽  
Scott Hazelhurst ◽  
Shivam Kalra ◽  
Charles Choi ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Primary Diagnosis ◽  
Image Search ◽  
Molecular Tests ◽  
Tissue Identification ◽  
Digital Database ◽  
Glass Slides ◽  
Search Tool ◽  
Hematoxylin And Eosin ◽  
Whole Slide Images

Context.— Pathologists may encounter extraneous pieces of tissue (tissue floaters) on glass slides because of specimen cross-contamination. Troubleshooting this problem, including performing molecular tests for tissue identification if available, is time consuming and often does not satisfactorily resolve the problem. Objective.— To demonstrate the feasibility of using an image search tool to resolve the tissue floater conundrum. Design.— A glass slide was produced containing 2 separate hematoxylin and eosin (H&E)-stained tissue floaters. This fabricated slide was digitized along with the 2 slides containing the original tumors used to create these floaters. These slides were then embedded into a dataset of 2325 whole slide images comprising a wide variety of H&E stained diagnostic entities. Digital slides were broken up into patches and the patch features converted into barcodes for indexing and easy retrieval. A deep learning-based image search tool was employed to extract features from patches via barcodes, hence enabling image matching to each tissue floater. Results.— There was a very high likelihood of finding a correct tumor match for the queried tissue floater when searching the digital database. Search results repeatedly yielded a correct match within the top 3 retrieved images. The retrieval accuracy improved when greater proportions of the floater were selected. The time to run a search was completed within several milliseconds. Conclusions.— Using an image search tool offers pathologists an additional method to rapidly resolve the tissue floater conundrum, especially for those laboratories that have transitioned to going fully digital for primary diagnosis.

Correlation of AGR2 expression with the incidence of metastasis in luminal breast cancer

2021 ◽  
pp. 1-5
Author(s):  
David Samuel Kereh ◽  
John Pieter ◽  
William Hamdani ◽  
Haryasena Haryasena ◽  
Daniel Sampepajung ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Mean Value ◽  
Rank Test ◽  
Luminal Breast Cancer ◽  
P Value ◽  
Strong Positive Correlation ◽  
Breast Cancer Patients ◽  
The Mean ◽  
Spearman Test

BACKGROUND: AGR2 expression is associated with luminal breast cancer. Overexpression of AGR2 is a predictor of poor prognosis. Several studies have found correlations between AGR2 in disseminated tumor cells (DTCs) in breast cancer patients. OBJECTIVE: This study aims to determine the correlation between anterior Gradient2 (AGR2) expression with the incidence of distant metastases in luminal breast cancer. METHODS: This study was an observational study using a cross-sectional method and was conducted at Wahidin Sudirohusodo Hospital and the network. ELISA methods examine AGR2 expression from blood serum of breast cancer patients. To compare the AGR2 expression in metastatic patients and the non-metastatic patient was tested with Mann Whitney test. The correlation of AGR2 expression and metastasis was tested with the Rank Spearman test. RESULTS: The mean value of AGR2 antibody expression on ELISA in this study was 2.90 ± 1.82 ng/dl, and its cut-off point was 2.1 ng/dl. Based on this cut-off point value, 14 subjects (66.7%) had overexpression of AGR2 serum ELISA, and 7 subjects (33.3%) had not. The mean value AGR2 was significantly higher in metastatic than not metastatic, 3.77 versus 1.76 (p < 0.01). The Spearman rank test obtained a p-value for the 2 tail test of 0.003 (p < 0.05), which showed a significant correlation of both, while the correlation coefficient of 0.612 showed a strong positive correlation of AGR2 overexpression and metastasis. CONCLUSIONS: AGR2 expression is correlated with metastasis in Luminal breast cancer.

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