scholarly journals Evaluation of Quantra Hologic Volumetric Computerized Breast Density Software in Comparison With Manual Interpretation in a Diverse Population

2018 ◽  
Vol 12 ◽  
pp. 117822341875929
Author(s):  
Gloria Richard-Davis ◽  
Brianna Whittemore ◽  
Anthony Disher ◽  
Valerie Montgomery Rice ◽  
Rathinasamy B Lenin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Stratification ◽  
Breast Density ◽  
Gold Standard ◽  
Assessment Tool ◽  
Low Risk ◽  
Mammographic Breast Density ◽  
Cutoff Value ◽  
Density Assessment

Objective: Increased mammographic breast density is a well-established risk factor for breast cancer development, regardless of age or ethnic background. The current gold standard for categorizing breast density consists of a radiologist estimation of percent density according to the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) criteria. This study compares paired qualitative interpretations of breast density on digital mammograms with quantitative measurement of density using Hologic’s Food and Drug Administration–approved R2 Quantra volumetric breast density assessment tool. Our goal was to find the best cutoff value of Quantra-calculated breast density for stratifying patients accurately into high-risk and low-risk breast density categories. Methods: Screening digital mammograms from 385 subjects, aged 18 to 64 years, were evaluated. These mammograms were interpreted by a radiologist using the ACR’s BI-RADS density method, and had quantitative density measured using the R2 Quantra breast density assessment tool. The appropriate cutoff for breast density–based risk stratification using Quantra software was calculated using manually determined BI-RADS scores as a gold standard, in which scores of D3/D4 denoted high-risk densities and D1/D2 denoted low-risk densities. Results: The best cutoff value for risk stratification using Quantra-calculated breast density was found to be 14.0%, yielding a sensitivity of 65%, specificity of 77%, and positive and negative predictive values of 75% and 69%, respectively. Under bootstrap analysis, the best cutoff value had a mean ± SD of 13.70% ± 0.89%. Conclusions: Our study is the first to publish on a North American population that assesses the accuracy of the R2 Quantra system at breast density stratification. Quantitative breast density measures will improve accuracy and reliability of density determination, assisting future researchers to accurately calculate breast cancer risks associated with density increase.

Correlation of mammographic breast density with Ki-67 expression in benign breast epithelial cells obtained by random periareolar fine needle aspiration of high risk women

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 1011-1011
Author(s):  
Q. J. Khan ◽  
B. F. Kimler ◽  
E. J. Smith ◽  
A. P. O’Dea ◽  
P. Sharma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Mammographic Density ◽  
Breast Density ◽  
Fine Needle Aspiration ◽  
Needle Aspiration ◽  
Mammographic Breast Density ◽  
Ki 67 ◽  
Fine Needle ◽  
Cytologic Atypia

1011 
 >Background: Known risk factors for breast cancer development include elements incorporated into the Gail risk model, mammographic breast density and cytologic atypia detected by Random Periareolar Fine Needle Aspiration (RPFNA). Ki-67 expression is a possible risk biomarker and is currently being used as a response biomarker in chemoprevention trials. We have previously shown that Ki-67 expression is higher in RPFNA specimens of benign breast cells exhibiting cytologic atypia. It is not known whether there is a correlation between mammographic density and Ki-67 expression in benign breast ductal cells obtained by RPFNA. Methods: 344 women at high risk of developing breast cancer (based on personal or family history) seen at The University of Kansas Medical Center high risk breast clinic, who underwent RPFNA with cytomorphology and Ki-67 assessment, plus a mammogram were included in the study. Mammographic breast density was assessed using the Cumulus program. Categorical variables were analyzed by Chi-square test and continuous variables were analyzed by non-parametric test and linear regression. Results: 40% of women were premenopausal, 7% perimenopausal and 53% were postmenopausal. Median age was 49 years, median 5 year Gail Risk was 2.2%, and median Ki-67 was 1.9%. Median mammographic breast density was 37%. Ki-67 expression increased with cytologic abnormality and number of cells collected, but was unrelated to Gail risk (as observed previously). Breast density was higher in pre-menopausal women (p=0.001), those with lower BMI (p< 0.001), and lower 5-year Gail risk (p=0.012); Breast density showed no correlation with Ki-67 expression or cytomorphology. Conclusion: Given the lack of correlation of mammographic breast density with either cytomorphology or Ki-67 expression in RPFNA specimens, mammographic density and Ki-67 expression should be considered as potentially complementary response biomarkers for breast cancer chemoprevention trials. No significant financial relationships to disclose.

scholarly journals Identification and Validation of m6A-Related lncRNA Signature as Potential Predictive Biomarkers in Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Wenchang Lv ◽  
Yichen Wang ◽  
Chongru Zhao ◽  
Yufang Tan ◽  
Mingchen Xiong ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Score ◽  
Assessment Tool ◽  
Cox Regression ◽  
Screening Method ◽  
Predictive Biomarkers ◽  
Risk Groups ◽  
Low Risk ◽  
Main Challenge

The metastasis and poor prognosis are still regarded as the main challenge in the clinical treatment of breast cancer (BC). Both N6-methyladenosine (m6A) modification and lncRNAs play vital roles in the carcinogenesis and evolvement of BC. Considering the unknown association of m6A and lncRNAs in BC, this study therefore aims to discern m6A-related lncRNAs and explore their prognostic value in BC patients. Firstly, a total of 6 m6A-related lncRNAs were screened from TCGA database and accordingly constructed a prognostic-predicting model. The BC patients were then divided into high-risk and low-risk groups dependent on the median cutoff of risk score based on this model. Then, the predictive value of this model was validated by the analyses of cox regression, Kaplan-Meier curve, ROC curve, and the biological differences in the two groups were validated by PCA, KEGG, GSEA, immune status as well as in vitro assay. Finally, we accordingly constructed a risk prognostic model based on the 6 identified m6A-related lncRNAs, including Z68871.1, AL122010.1, OTUD6B-AS1, AC090948.3, AL138724.1, EGOT. Interestingly, the BC patients were divided into the low-risk and high-risk groups with different prognoses according to the risk score. Notably, the risk score of the model was an excellent independent prognostic factor. In the clinical sample validation, m6A regulatory proteins were differentially expressed in patients with different risks, and the markers of tumor-associated macrophages and m6A regulators were co-localized in high-risk BC tissues. This well-validated risk assessment tool based on the repertoire of these m6A-related genes and m6A-related lncRNAs, is of highly prognosis-predicting ability, and might provide a supplemental screening method for precisely judging BC prognosis.

BRCA1 and BRCA2 germline mutation carriers have a lower breast density compared to high risk women without such mutations

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 1517-1517
Author(s):  
P. Sharma ◽  
J. R. Klemp ◽  
B. F. Kimler ◽  
Q. J. Khan ◽  
E. J. Smith ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Family History ◽  
High Risk ◽  
Breast Density ◽  
Genetic Factors ◽  
Mammographic Breast Density ◽  
Mutation Status ◽  
High Risk Women ◽  
Mutation Carriers ◽  
Chi Square Analysis

1517 Background: High mammographic breast density, a known risk factor for breast cancer is influenced by both genetic and non genetic factors. It is not clear if there are differences in breast densities between BRCA1/2 mutation carriers and high-risk non carriers. The aim of this study was to compare breast density in high-risk women with and without BRCA1/2 mutation. Methods: Women at high risk for development of breast cancer (based on family history, prior precancerous disease or prior breast cancer) who underwent genetic testing at the University of Kansas Breast Cancer Prevention Center between 1998 and 2005 were identified under an IRB approved protocol. BRCA1/2 full sequencing was performed at Myriad Genetic Laboratories. The earliest digitized mammogram of these subjects was identified from a preexisting mammogram database. All mammograms had to be prior to/at least one year from any chemoprevention intervention. For subjects with prior breast cancer, mammogram of the uninvolved breast was used. Breast density was assessed on the left craniocaudal mammographic view by computer assisted method, Cumulus. Frequencies of categorical variables were assessed using chi-square analysis. Continuous variables were assessed using Mann-Whitney non parametric test. Multiple regression analysis was used to investigate whether differences are due to variables other than mutation status. Results: The study population consisted of 284 high-risk women who underwent BRCA1/2 testing and for whom a mammogram was available. 30 (11%) had BRCA1 and/or 2 deleterious mutation. There was no difference between mutation carriers and non-carriers for BMI, 5 year Gail risk, parity, menopausal status and HRT use. Mutation carriers were younger (median age 42 vs. 46, p=0.020) and more likely to have a positive family history (100% vs. 85%, p=0.020). Older age (p<0.001), higher BMI (p<0.001) and having a BRCA1/2 mutation (p=0.025) were significantly associated with a lower breast density. Conclusion: Among high risk women, possession of a deleterious BRCA1/2 mutation is associated with lower breast density after adjusting for factors known to affect breast density. This suggests that breast density may be governed by genetic factors other than BRCA1/2 mutation status. No significant financial relationships to disclose.

scholarly journals Predicting complication risk in spine surgery: a prospective analysis of a novel risk assessment tool

2017 ◽  
Vol 27 (1) ◽  
pp. 81-91 ◽  
Author(s):  
Anand Veeravagu ◽  
Amy Li ◽  
Christian Swinney ◽  
Lu Tian ◽  
Adrienne Moraff ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Risk Stratification ◽  
Spine Surgery ◽  
Assessment Tool ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Acs Nsqip ◽  
Medium Risk

OBJECTIVEThe ability to assess the risk of adverse events based on known patient factors and comorbidities would provide more effective preoperative risk stratification. Present risk assessment in spine surgery is limited. An adverse event prediction tool was developed to predict the risk of complications after spine surgery and tested on a prospective patient cohort.METHODSThe spinal Risk Assessment Tool (RAT), a novel instrument for the assessment of risk for patients undergoing spine surgery that was developed based on an administrative claims database, was prospectively applied to 246 patients undergoing 257 spinal procedures over a 3-month period. Prospectively collected data were used to compare the RAT to the Charlson Comorbidity Index (CCI) and the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator. Study end point was occurrence and type of complication after spine surgery.RESULTSThe authors identified 69 patients (73 procedures) who experienced a complication over the prospective study period. Cardiac complications were most common (10.2%). Receiver operating characteristic (ROC) curves were calculated to compare complication outcomes using the different assessment tools. Area under the curve (AUC) analysis showed comparable predictive accuracy between the RAT and the ACS NSQIP calculator (0.670 [95% CI 0.60–0.74] in RAT, 0.669 [95% CI 0.60–0.74] in NSQIP). The CCI was not accurate in predicting complication occurrence (0.55 [95% CI 0.48–0.62]). The RAT produced mean probabilities of 34.6% for patients who had a complication and 24% for patients who did not (p = 0.0003). The generated predicted values were stratified into low, medium, and high rates. For the RAT, the predicted complication rate was 10.1% in the low-risk group (observed rate 12.8%), 21.9% in the medium-risk group (observed 31.8%), and 49.7% in the high-risk group (observed 41.2%). The ACS NSQIP calculator consistently produced complication predictions that underestimated complication occurrence: 3.4% in the low-risk group (observed 12.6%), 5.9% in the medium-risk group (observed 34.5%), and 12.5% in the high-risk group (observed 38.8%). The RAT was more accurate than the ACS NSQIP calculator (p = 0.0018).CONCLUSIONSWhile the RAT and ACS NSQIP calculator were both able to identify patients more likely to experience complications following spine surgery, both have substantial room for improvement. Risk stratification is feasible in spine surgery procedures; currently used measures have low accuracy.

Risk stratification in breast cancer screening: Cost‐effectiveness and harm‐benefit ratios for low‐risk and high‐risk women

2020 ◽  
Vol 147 (11) ◽  
pp. 3059-3067
Author(s):  
Valérie D. V. Sankatsing ◽  
Nicolien T. Ravesteyn ◽  
Eveline A. M. Heijnsdijk ◽  
Mireille J. M. Broeders ◽  
Harry J. Koning
Keyword(s):  
Breast Cancer ◽  
Cost Effectiveness ◽  
Cancer Screening ◽  
High Risk ◽  
Risk Stratification ◽  
Breast Cancer Screening ◽  
Low Risk ◽  
High Risk Women ◽  
Screening Cost

Reduction in Ki-67 in benign breast tissue of high-risk premenopausal women with the SERM acolbifene.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 520-520
Author(s):  
Carol J. Fabian ◽  
Bruce F. Kimler ◽  
Carola M. Zalles ◽  
Brian K. Petroff ◽  
Trina Metheny ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Adverse Events ◽  
Breast Density ◽  
Premenopausal Women ◽  
Wilcoxon Test ◽  
Mammographic Breast Density ◽  
Relative Reduction ◽  
Marginal Effect ◽  
Ki 67

520 Background: Selective Estrogen Receptor Modulators (SERMs) are approved for reduction of risk for breast cancer; however, uptake and use is limited. We conducted a pilot study of a 4th generation SERM to determine tolerability and effect on tissue biomarkers in healthy women at high risk for development of breast cancer. Methods: Premenopausal women at elevated risk for breast cancer were screened by random periareolar fine needle aspiration (RPFNA) performed during the follicular phase of the menstrual cycle. Women were eligible if breast epithelial cells exhibited evidence of cytologic hyperplasia with or without atypia, as well as Ki-67 ≥2% by immunocytochemistry. Following 6-8 months of open-label acolbifene (20 mg/d), the RPFNA was repeated. The primary endpoint was modulation of the proportion of cells that expressed Ki-67. Body composition (DEXA), pelvic sonography, mammographic breast density, and serum levels of IGF-1/IGFBP3 and several bioavailable hormones were assessed pre and post intervention. Results: 76 women were screened by RPFNA, with 25 eligible and enrolled in the intervention over a 9 month period. All 25 (7 on oral contraceptives) subjects completed the study, had a second RPFNA, and were evaluable. Median Ki-67 at baseline was 4.6% (range 2.4 – 21.9%) and off study 1.4% (range 0 – 6.6%); median change was a reduction of 3.0% (range -20.2% to +2.8%; decreased in 23, increased in 2) or a relative reduction of 77%. The end-of-study Ki-67 was significantly less than baseline (p<0.001, 2-tailed Wilcoxon test). There were no statistically significant changes in cytomorphology over this short intervention period. There was a marginal effect on breast density (16 decreased; 8 increased; p=0.067). Adverse events were minimal with greatest grade of 3 reported by 2 subjects, grade 2 by 7 subjects, and grade 1 by 11 subjects. No serious adverse event was reported and no subject discontinued the study due to an AE. Conclusions: Based on preliminary evaluation showing favorable modulation of proliferation and minimal adverse events, further investigation of acolbifene, a fourth generation SERM, as a breast cancer chemoprevention agent for premenopausal women appears warranted. Supported by NO1-CN-35135.

Mammographic Breast Density Assessment

2013 ◽  
Vol 311 ◽  
pp. 518-523
Author(s):  
Chien Shun Lo ◽  
Si Wa Chan ◽  
San Kan Lee
Keyword(s):  
Breast Cancer ◽  
Breast Density ◽  
Early Stage ◽  
Characteristic Curve ◽  
Entropy Method ◽  
Mammographic Breast Density ◽  
Dense Area ◽  
Incidence And Mortality ◽  
High Mammographic Density ◽  
Density Assessment

In Taiwan, breast cancer has become the second leading type of cancerous diseases among women. The incidence and mortality rates keep rising, and mammography remains to be the only effective screening technique which is capable of detecting breast cancer at an early stage. High mammographic density is a strong risk factor for breast cancer. Based on BI-RADS categories, mammograms are classified into four categories (D1-D4) based on the percentage of dense area (PDA). However, reporting of breast density suffers from high inter and intra observer variability. Because the risk of breast cancer is at least three times greater in women with density (D3&D4) than in women with density D1, this paper proposes a local entropy method to identify the higher density (D3&D4) from (D1&D2) by two features. There are 406 mammograms with four categories collected for the test. The higher density (D3&D4) can be identified from lower density (D1&D2) in the correction of 100%. The Az of receiver operating characteristic curve of 0.9996 can be achieved.

Effect of the third generation selective estrogen receptor modulator arzoxifene on mammographic breast density

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 562-562
Author(s):  
B. F. Kimler ◽  
G. Ursin ◽  
C. J. Fabian ◽  
J. R. Anderson ◽  
C. Chamberlain ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Estrogen Receptor ◽  
High Risk ◽  
Phase Ii ◽  
Breast Density ◽  
Receptor Expression ◽  
Mammographic Breast Density ◽  
Computer Assisted ◽  
Breast Cancer Patients ◽  
Dense Area

562 Background: Arzoxifene (ARZ) is currently being studied for treatment of breast cancer patients in a Phase II trial because of tamoxifen-like efficacy but lack of uterine agonist effect. We conducted a Phase II chemoprevention trial in women at high risk for development of breast cancer on the basis of personal or family history. Methods: Potential subjects had multiple biomarkers assessed, including random periareolar fine needle aspiration (RPFNA) with breast epithelial cells processed for cytomorphology and immunocytochemistry. Women who exhibited cytologic hyperplasia ± atypia were eligible for enrollment. Subjects were stratified on the basis of atypia, estrogen receptor expression, menopause status, germline BrCa1/2 mutation status, and accrual site. Subjects were randomized (double-blind) between placebo and ARZ (LY353381.HCI, 20 mg daily) for 6 mo, with an option to continue on study for another 6 mo while receiving open-label ARZ. Assessments conducted at baseline, 6 mo, and 12 mo included mammographic breast density. Mammograms were digitized to image files which were cropped to remove labels and dates, and then identified by a study subject ID number and a random coding for baseline, 6 or 12 mo. This allowed the reader (GU) to view the three files for a subject, but to remain blinded as to the sequence of the films or the study agent. The files were assessed for mammographic density using the Madena computer-assisted system. Results: Of 199 subjects enrolled on the study, 52% were pre-menopausal; with 101 women randomized to placebo and 98 to ARZ. At baseline, mean values were comparable for placebo and ARZ groups for breast area (∼244 cm2), total dense area (∼100 cm2), and the percent of the breast at increased density (41.3% vs 46.2%). After 6 mo, there were minimal changes in total breast area (P=0.13); but statistically significant decreases (P<0.001) for the comparison of placebo vs ARZ (2-sided T-test) for change in both dense area (+3.8 vs −12.9 cm2) and percent breast density (+0.8% vs −4.6%). Conclusions: The 3rd generation SERM arzoxifene administered for 6 mo produces statistically significant decreases in mammographic breast density relative to placebo in women at high risk for development of breast cancer. No significant financial relationships to disclose.

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