Value of digital mammography in predicting lymphovascular invasion of breast cancer.
Ontology highlight
ABSTRACT:
SUBMITTER: Liu Z
PROVIDER: S-EPMC7119272 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
Publications
Value of digital mammography in predicting lymphovascular invasion of breast cancer.
Liu Zhuangsheng Z Li Ruqiong R Liang Keming K Chen Junhao J Chen Xiangmeng X Li Xiaoping X Li Ronggang R Zhang Xin X Yi Lilei L Long Wansheng W
BMC cancer 20200403 1
<h4>Background</h4>Lymphovascular invasion (LVI) has never been revealed by preoperative scans. It is necessary to use digital mammography in predicting LVI in patients with breast cancer preoperatively.<h4>Methods</h4>Overall 122 cases of invasive ductal carcinoma diagnosed between May 2017 and September 2018 were enrolled and assigned into the LVI positive group (n = 42) and the LVI negative group (n = 80). Independent t-test and χ2 test were performed.<h4>Results</h4>Difference in Ki-67 betwe ...[more]
Similar Datasets
Project description:Background Previous studies have suggested that breast parenchymal texture features may reflect the biologic risk factors associated with breast cancer development. Therefore, combining the characteristics of normal parenchyma from the contralateral breast with radiomic features of breast tumors may improve the accuracy of digital mammography in the diagnosis of breast cancer. Purpose To determine whether the addition of radiomic analysis of contralateral breast parenchyma to the characterization of breast lesions with digital mammography improves lesion classification over that with radiomic tumor features alone. Materials and Methods This HIPAA-compliant, retrospective study included 182 patients (age range, 25-90 years; mean age, 55.9 years ± 14.9) who underwent mammography between June 2002 and July 2009. There were 106 malignant and 76 benign lesions. Automatic lesion segmentation and radiomic analysis were performed for each breast lesion. Radiomic texture analysis was applied in the normal regions of interest in the contralateral breast parenchyma to assess the mammographic parenchymal patterns. The classification performance of both individual features and the output from a Bayesian artificial neural network classifier was evaluated with the leave-one-patient-out method by using the area under the receiver operating characteristic curve (AUC) as the figure of merit in the task of differentiating between malignant and benign lesions. Results The performance of the combined lesion and parenchyma classifier in the differentiation between malignant and benign mammographic lesions was better than that with the lesion features alone (AUC = 0.84 ± 0.03 vs 0.79 ± 0.03, respectively; P = .047). Overall, six radiomic features-spiculation, margin sharpness, size, circularity from the tumor feature set, and skewness and power law beta from the parenchymal feature set-were selected more than 50% of the time during the feature selection process on the combined feature set. Conclusion Combining quantitative radiomic data from tumors with contralateral parenchyma characterizations may improve diagnostic accuracy for breast cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Shaffer in this issue.
| S-EPMC6445042 | biostudies-literature
Project description:BackgroundOur objective was to perform a systematic review and meta-analysis comparing the breast cancer detection rate (CDR), invasive CDR, recall rate, and positive predictive value 1 (PPV1) of digital mammography (DM) alone, combined digital breast tomosynthesis (DBT) and DM, combined DBT and synthetic 2-dimensional mammography (S2D), and DBT alone.MethodsMEDLINE and Embase were searched until April 2020 to identify comparative design studies reporting on patients undergoing routine breast cancer screening. Random effects model proportional meta-analyses estimated CDR, invasive CDR, recall rate, and PPV1. Meta-regression modeling was used to compare imaging modalities. All statistical tests were 2-sided.ResultsForty-two studies reporting on 2 606 296 patients (13 003 breast cancer cases) were included. CDR was highest in combined DBT and DM (6.36 per 1000 screened, 95% confidence interval [CI] = 5.62 to 7.14, P < .001), and combined DBT and S2D (7.40 per 1000 screened, 95% CI = 6.49 to 8.37, P < .001) compared with DM alone (4.68 per 1000 screened, 95% CI = 4.28 to 5.11). Invasive CDR was highest in combined DBT and DM (4.53 per 1000 screened, 95% CI = 3.97 to 5.12, P = .003) and combined DBT and S2D (5.68 per 1000 screened, 95% CI = 4.43 to 7.09, P < .001) compared with DM alone (3.42 per 1000 screened, 95% CI = 3.02 to 3.83). Recall rate was lowest in combined DBT and S2D (42.3 per 1000 screened, 95% CI = 37.4 to 60.4, P<.001). PPV1 was highest in combined DBT and DM (10.0%, 95% CI = 8.0% to 12.0%, P = .004), and combined DBT and S2D (16.0%, 95% CI = 10.0% to 23.0%, P < .001), whereas no difference was detected for DBT alone (7.0%, 95% CI = 6.0% to 8.0%, P = .75) compared with DM alone (7.0%, 95.0% CI = 5.0% to 8.0%).ConclusionsOur findings provide evidence on key performance metrics for DM, DBT alone, combined DBT and DM, and combined DBT and S2D, which may inform optimal application of these modalities for breast cancer screening.
| S-EPMC8168096 | biostudies-literature
Project description:ImportanceMany US radiologists have screening mammography recall rates above the expert-recommended threshold of 12%. The influence of digital breast tomosynthesis (DBT) on the distribution of radiologist recall rates is uncertain.ObjectiveTo evaluate radiologists' recall and cancer detection rates before and after beginning interpretation of DBT examinations.Design, setting, and participantsThis cohort study included 198 radiologists from 104 radiology facilities in the Breast Cancer Surveillance Consortium who interpreted 251?384 DBT and 2?000?681 digital mammography (DM) screening examinations from 2009 to 2017, including 126 radiologists (63.6%) who interpreted DBT examinations during the study period and 72 (36.4%) who exclusively interpreted DM examinations (to adjust for secular trends). Data were analyzed from April 2018 to July 2019.ExposuresDigital breast tomosynthesis and DM screening examinations.Main outcomes and measuresRecall rate and cancer detection rate.ResultsA total of 198 radiologists interpreted 2?252?065 DM and DBT examinations (2?000?681 [88.8%] DM examinations; 251?384 [11.2%] DBT examinations; 710?934 patients [31.6%] aged 50-59 years; 1?448?981 [64.3%] non-Hispanic white). Among the 126 radiologists (63.6%) who interpreted DBT examinations, 83 (65.9%) had unadjusted DM recall rates of no more than 12% before using DBT, with a median (interquartile range) recall rate of 10.0% (7.5%-13.0%). On DBT examinations, 96 (76.2%) had an unadjusted recall rate of no more than 12%, with a median (interquartile range) recall rate of 8.8% (6.3%-11.3%). A secular trend in recall rate was observed, with the multivariable-adjusted risk of recall on screening examinations declining by 1.2% (95% CI, 0.9%-1.5%) per year. After adjusting for examination characteristics and secular trends, recall rates were 15% lower on DBT examinations compared with DM examinations interpreted before DBT use (relative risk, 0.85; 95% CI, 0.83-0.87). Adjusted recall rates were significantly lower on DBT examinations compared with DM examinations interpreted before DBT use for 45 radiologists (35.7%) and significantly higher for 18 (14.3%); 63 (50.0%) had no statistically significant change. The unadjusted cancer detection rate on DBT was 5.3 per 1000 examinations (95% CI, 5.0-5.7 per 1000 examinations) compared with 4.7 per 1000 examinations (95% CI, 4.6-4.8 per 1000 examinations) on DM examinations interpreted before DM use (multivariable-adjusted risk ratio, 1.21; 95% CI, 1.11-1.33).Conclusions and relevanceIn this study, DBT was associated with an overall decrease in recall rate and an increase in cancer detection rate. However, our results indicated that there is wide variability among radiologists, including a subset of radiologists who experienced increased recall rates on DBT examinations. Radiology practices should audit radiologist DBT screening performance and consider additional DBT training for radiologists whose performance does not improve as expected.
| S-EPMC7292996 | biostudies-literature
Project description:BackgroundLymphovascular invasion (LVI) is associated with the development of metastasis in invasive breast cancer (BC). However, the complex molecular mechanisms of LVI, which overlap with other oncogenic pathways, remain unclear. This study, using available large transcriptomic datasets, aims to identify genes associated with LVI in early-stage BC patients.MethodsGene expression data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (n = 1565) was used as a discovery dataset, and The Cancer Genome Atlas (TCGA; n = 854) cohort was used as a validation dataset. Key genes were identified on the basis of differential mRNA expression with respect to LVI status as characterised by histological review. The relationships among LVI-associated genomic subtype, clinicopathological features and patient outcomes were explored.ResultsA 99-gene set was identified that demonstrated significantly different expression between LVI-positive and LVI-negative cases. Clustering analysis with this gene set further divided cases into two molecular subtypes (subtypes 1 and 2), which were significantly associated with pathology-determined LVI status in both cohorts. The 10-year overall survival of subtype 2 was significantly worse than that of subtype 1.ConclusionThis study demonstrates that LVI in BC is associated with a specific transcriptomic profile with potential prognostic value.
| S-EPMC6738092 | biostudies-literature
Project description:BackgroundDigital breast tomosynthesis (DBT) combined with digital mammography (DM) is increasingly used in the United States instead of DM alone for breast cancer screening. Early screening outcomes incorporating synthetic mammography (SM) with DBT have suggested that SM is an acceptable non-radiation dose alternative to DM.PurposeTo compare multicenter outcomes from breast cancer screening with SM/DBT versus DM/DBT.Materials and MethodsThis was a retrospective study of consecutive screening mammograms obtained at two institutions. Eligible studies consisted of 34 106 DM/DBT examinations between October 3, 2011, and October 31, 2014, and 34 180 SM/DBT examinations between January 7, 2015, and February 2, 2018, at the University of Pennsylvania and 51 148 DM/DBT examinations between January 1, 2012, and May 31, 2016, and 31 929 SM/DBT examinations between June 1, 2016, and March 30, 2018, at the University of Vermont. Demographics of women who attended screening and results from screening were recorded. Recall rate, biopsy rate, false-negative rate, cancer detection rate, positive predictive value, sensitivity, and specificity were calculated according to modality and institution. Descriptive statistics, χ2 tests, and logistic regression were used in analysis.ResultsThe study included 151 363 screening examinations among 151 363 women (mean age, 58.1 years ± 10.9 [standard deviation]). The unadjusted recall rate was lower with SM/DBT than with DM/DBT (7.0% [4630 of 66 109 examinations] for SM/DBT vs 7.9% [6742 of 85 254 examinations] for DM/DBT; P < .01). However, after multivariable adjustment, SM/DBT was associated with a slightly higher recall rate compared with DM/DBT (adjusted odds ratio [OR], 1.06; adjusted 95% CI: 1.01, 1.11; P = .02). Similarly, after multivariable adjustment, SM/DBT was associated with slightly lower specificity compared with DM/DBT (adjusted OR, 0.95; adjusted 95% CI: 0.90, 0.99; P = .02). There was no statistically significant difference in biopsy rate (P = .54), false-negative rate (P = .38), cancer detection rate (P = .55), invasive or in situ cancer detection rate (P = .52 and P = .98, respectively), positive predictive value (P = .78), or sensitivity (P = .33) for SM/DBT versus DM/DBT overall or within either institution (P > .05 for all).ConclusionBreast cancer screening performance is maintained within benchmarks when synthetic mammography replaces digital mammography in digital breast tomosynthesis imaging.© RSNA, 2020Online supplemental material is available for this article.See also the editorial by Lång in this issue.
| S-EPMC7706877 | biostudies-literature
Project description:Lymphovascular invasion (LVI) is the primary and essential step in the systemic dissemination of cancer cells. The aim of our study was to assess the independent prognostic role of LVI for pT1 urothelial carcinoma with squamous differentiation in bladder cancer. We retrospectively analyzed the clinical and pathological information of 206 patients diagnosed pT1 urothelial carcinoma with squamous differentiation. Of the 206 patients, LVI was detected in 57 (27.6%) patients. The 5 year cancer specific survival (CSS) rates were 87.2% in LVI (-) and 52.4% in LVI (+) (p < 0.001). According to univariate analysis, tumor multiplicity, tumor size, recurrence and LVI were the prognostic factors associated with CSS. Additionally, tumor size and LVI significantly influenced the CSS in multivariate analysis. TURBT had shorter median CSS than RC in recurred patients with LVI (+). Our study suggested that LVI is an important predictor for survival of pT1 urothelial carcinoma with squamous differentiation. LVI positive status and tumor size ≥3 cm led to a higher risk of death. RC should be routinely performed in recurred LVI (+) bladder cancer patients of pT1 urothelial carcinoma with squamous differentiation.
| S-EPMC4899777 | biostudies-other
Project description:ImportanceBreast cancer screening examinations using digital breast tomosynthesis (DBT) has been shown to be associated with decreased false-positive test results and increased breast cancer detection compared with digital mammography (DM). Little is known regarding the size and stage of breast cancer types detected and their association with age and breast density.ObjectiveTo determine whether screening examinations using DBT detect breast cancers that are associated with an improved prognosis and to compare the detection rates by patient age and breast density.Design, setting, and participantsThis retrospective analysis of prospective cohort data from 3 research centers in the Population-based Research Optimizing Screening Through Personalized Regimens (PROSPR) consortium included data of women aged 40 to 74 years who underwent screening examinations using DM and DBT from January 1, 2011, through September 30, 2014. Statistical analysis was performed from November 8, 2017, to August 14, 2018.ExposuresUse of DBT as a supplement to DM at breast cancer screening examination.Main outcomes and measuresRecall rate, cancer detection rate, positive predictive value, biopsy rate, and distribution of invasive cancer subtypes.ResultsAmong 96 269 women (mean [SD] patient age for all examinations, 55.9 [9.0] years), patient age was 56.4 (9.0) years for DM and 54.6 (8.9) years for DBT. Of 180 340 breast cancer screening examinations, 129 369 examinations (71.7%) used DM and 50 971 examinations (28.3%) used DBT. Screening examination with DBT (73 of 99 women [73.7%]) was associated with the detection of smaller, more often node-negative, HER2-negative, invasive cancers compared with DM (276 of 422 women [65.4%]). Screening examination with DBT was also associated with lower recall (odds ratio, 0.64; 95% CI, 0.57-0.72; P < .001) and higher cancer detection (odds ratio, 1.41; 95% CI, 1.05-1.89; P = .02) compared with DM for all age groups even when stratified by breast density. The largest increase in cancer detection rate and the greatest shift toward smaller, node-negative invasive cancers detected with DBT was for women aged 40 to 49 years. For women aged 40 to 49 years with nondense breasts, the cancer detection rate for examinations using DBT was 1.70 per 1000 women higher compared with the rate using DM; for women with dense breasts, the cancer detection rate was 2.27 per 1000 women higher for DBT. For these younger women, screening with DBT was associated with only 7 of 28 breast cancers (25.0%) categorized as poor prognosis compared with 19 of 47 breast cancers (40.4%) when screening with DM.Conclusions and relevanceThe findings suggest that screening with DBT is associated with increased specificity and an increased proportion of breast cancers detected with better prognosis compared with DM. In the subgroup of women aged 40 to 49 years, routine DBT screening may have a favorable risk-benefit ratio.
| S-EPMC6512257 | biostudies-literature
Project description:The lymphovascular invasion (LVI) status facilitates the determination of the optimal therapeutic strategy for superficial esophageal squamous cell carcinoma (SESCC), but in clinical practice, LVI must be confirmed by postoperative pathology. However, studies of the risk factors for LVI in SESCC are limited. Consequently, this study aimed to identify the risk factors for LVI and use these factors to establish a prediction model. The data of 516 patients who underwent radical esophagectomy between January 2007 and September 2019 were retrospectively collected (training set, n=361, January 2007 to May 2015; validation set, n=155, June 2015 to September 2019). In the training set, least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were utilized to identify predictive factors for LVI in patients with SESCC. A nomogram was then developed using these predictors. The area under the curve (AUC), calibration curve, and decision curve were used to evaluate the efficiency, accuracy, and clinical utility of the model. LASSO regression indicated that the tumor size, depth of invasion, tumor differentiation, lymph node metastasis (LNM), sex, circumferential extension, the presence of multiple lesions, and the resection margin were correlated with LVI. However, multivariate analysis revealed that only the tumor size, depth of invasion, tumor differentiation, and LNM were independent risk factors for LVI. Incorporating these four variables, model 1 achieved an AUC of 0.817 in predicting LVI. Adding circumferential extension to model 1 did not appreciably change the AUC and integrated discrimination improvement, but led to a significant increase in the net reclassification improvement (p=0.011). A final nomogram was constructed by incorporating tumor size, depth of invasion, tumor differentiation, LNM, and circumferential extension and showed good discrimination (training set, AUC=0.833; validation set, AUC=0.819) and good calibration in the training and validation sets. Decision curve analysis demonstrated that the nomogram was clinically useful in both sets. Thus, it is possible to predict the status of LVI using this nomogram scoring system, which can aid the selection of an appropriate treatment plan.
| S-EPMC8141657 | biostudies-literature
Project description:Background Breast Imaging Reporting and Data System (BI-RADS) breast density categories assigned by interpreting radiologists often influence decisions surrounding supplemental breast cancer screening and risk assessment. The landscape of mammographic screening continuously evolves, and different mammographic screening modalities may result in different perception of density, reflected in different assignment of BI-RADS density categories. Purpose To investigate the effect of screening mammography modality on BI-RADS breast density assessments. Materials and Methods Data were retrospectively analyzed from 24 736 individual women (42.3% [10 455 of 24 736] white women, 57.7% [14 281 of 24 736] black women; mean age, 56.3 years; age range, 40.0-74.9 years) who underwent from one to seven mammographic screening examinations from September 2010 through February 2017 (60 766 examinations). Three screening modalities were used: digital mammography alone (8935 examinations); digital mammography with digital breast tomosynthesis (DBT; 30 779 examinations); and synthetic mammography with DBT (21 052 examinations). Random-effects logistic regression analysis was performed to estimate the likelihood of assignment to high versus low BI-RADS density category according to each modality, adjusted for ethnicity, age, body mass index (BMI), and radiologist. The interactions of modality with ethnicity and BMI on density categorization were also tested with the model. Results Women screened with DBT versus digital mammography alone had lower likelihood regarding categorization of high density breasts (digital mammography and DBT vs digital mammography: odds ratio, 0.69 [95% confidence interval: 0.61, 0.80], P < .001; synthetic mammography and DBT vs digital mammography: odds ratio, 0.43 [95% confidence interval: 0.37, 0.50], P < .001). Lower likelihood of high density was also observed at synthetic mammography and DBT compared with digital mammography and DBT (odds ratio, 0.62; 95% confidence interval: 0.56, 0.69; P < .001). There were interactions of modality with ethnicity (P = .007) and BMI (P = .003) on breast density assessment, with greater differences in density categorization according to modality observed for black women than for white women and groups with higher BMI. Conclusion Breast density categorization may vary by screening mammographic modality, and this effect appears to vary by ethnicity and body mass index. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.
| S-EPMC6493215 | biostudies-literature
Project description:We aimed to predict molecular subtypes of breast cancer using radiomics signatures extracted from synthetic mammography reconstructed from digital breast tomosynthesis (DBT). A total of 365 patients with invasive breast cancer with three different molecular subtypes (luminal A + B, luminal; HER2-positive, HER2; triple-negative, TN) were assigned to the training set and temporally independent validation cohort. A total of 129 radiomics features were extracted from synthetic mammograms. The radiomics signature was built using the elastic-net approach. Clinical features included patient age, lesion size and image features assessed by radiologists. In the validation cohort, the radiomics signature yielded an AUC of 0.838, 0.556, and 0.645 for the TN, HER2 and luminal subtypes, respectively. In a multivariate analysis, the radiomics signature was the only independent predictor of the molecular subtype. The combination of the radiomics signature and clinical features showed significantly higher AUC values than clinical features only for distinguishing the TN subtype. In conclusion, the radiomics signature showed high performance for distinguishing TN breast cancer. Radiomics signatures may serve as biomarkers for TN breast cancer and may help to determine the direction of treatment for these patients.
| S-EPMC7726048 | biostudies-literature