Specificity Of Breast Cancer Detection Research Articles

Improvement of Breast Cancer Detection Using Dual-Layer Spectral CT.

This study aimed to investigate the diagnostic performance of breast mass detection on monoenergetic image data at 40 keV (MonoE40) and on iodine maps (IM) compared with conventional image data (CI). In this prospective single-center case-control study, 50 breast cancer patients were examined using contrast-enhanced dual-layer spectral CT. For qualitative and quantitative comparison of MonoE40 and IM with CI image data, four blinded, independent readers assessed 300 randomized single slices (two slices for each imaging type per case) with or without cancerous lesions for the presence of a breast mass. Detection sensitivity and specificity were calculated and readers rated their subjective diagnostic certainty. For statistical analysis of sensitivity and specificity, a paired t-test and ANOVA were used (significance level p = 0.05). A total of 50 female patients (median age 51 years, range 28-83 years) participated. IM had the highest overall scores in sensitivity and specificity for breast cancer detection, with 0.97 ± 0.06 and 0.95 ± 0.07, respectively, compared with 0.90 ± 0.04 and 0.92 ± 0.06 in CI. MonoE40 yielded a sensitivity of 0.96 ± 0.02 and specificity of 0.94 ± 0.08. All differences in sensitivity and specificity between MonoE or IM and CI were statistically significant (p < 0.001). The superiority of IM sensitivity and specificity was most pronounced in patients with dense breasts. Spectral CT improved the detection of breast cancer with higher sensitivity and specificity compared to conventional image data in our study.

Comparison of lesion detection and conspicuity between narrow-angle and wide-angle digital breast tomosynthesis for dense and non-dense breasts.

Digital breast tomosynthesis (DBT) has been shown to improve both sensitivity and specificity for breast cancer detection compared to full-field digital mammography. However, its performance could be limited for patients with dense breasts. Clinical DBT systems vary in their system designs, one of which is the acquisition angular range (AR), which leads to varied performance for different imaging tasks. In this study, we aim to compare DBT systems with different AR. We used a previously validated cascaded linear system model to investigate the dependence of in-plane breast structural noise (BSN) and detectability of masses on AR. We conducted a pilot clinical study to compare the lesion conspicuity between clinical DBT systems with the narrowest and the widest AR. Patients called back for diagnostic imaging on suspicious findings were imaged with both narrow-angle (NA) and wide-angle (WA) DBT. We analyzed the BSN for clinical images using noise power spectrum (NPS) analysis. A 5-point Likert scale was used in the reader study to compare the lesion conspicuity. Our theoretical calculation results show that increasing AR leads to reduced BSN and improved mass detectability. The NPS analysis on clinical images shows the lowest BSN for WA DBT. The WA DBT provides better lesion conspicuity for masses and asymmetries and shows a greater advantage for non-microcalcification lesions in dense breasts. The NA DBT provides better characterizations for microcalcifications. The WA DBT can downgrade false-positive findings seen on NA DBT. In conclusion, WA DBT could improve the detection of masses and asymmetries for patients with dense breasts.

Evaluation of Salivary KCNJ3 mRNA Levels in Breast Cancer: A Case–control Study and in silico Analysis

Background: Breast cancer (BC) is considered the most malignant and central cancer-related death among women worldwide. There is an essential need to discover new methods for developing noninvasive and low-cost diagnoses. The present study examines the expression of KCNJ3 which acts as a biomarker for detecting BC in the saliva of BC patients compared to controls. Methods: The mRNA expression level of KCNJ3 has been evaluated. Forty-three unstimulated whole saliva samples from BC patients and forty-three salivary samples from healthy controls were collected. The mRNA level was measured using quantitative real-time polymerase chain reaction (qRT-PCR). Furthermore, the protein-protein interaction network in which KCNJ3 is involved was obtained. In silico analysis was applied to predict the possible molecular mechanisms of KCNJ3 in BC development. Results: Differentially expressed KCNJ3 was statistically significant between BC patients and controls (p&lt;0.001). The sensitivity and specificity of KCNJ3 mRNA in BC detection were 76.74% and 94.95%, respectively. Receiver operating characteristic (ROC) curve analysis of KCNJ3 mRNA revealed that Area under the curve (AUC) was 0.923 (95% Confidence Interval (CI): 0.866-0.979). AUCs of ROC curve analysis were 0.743 (95% CI: 0.536-0.951), 0.685 (95% CI: 0.445-0.925), and 0.583(95% CI: 0.343-0.823) for differentiation stage I from stage III, stage I to stage II and finally stage II from stage III, respectively. Furthermore, the GABAergic synapse signaling pathway was suggested as a potential pathway involved in BC development. Conclusion: Salivary levels of KCNJ3 could be considered a potential diagnostic biomarker with high sensitivity and specificity for BC detection.

Characterization and imaging of surgical specimens of invasive breast cancer and normal breast tissues with the application of Raman spectral mapping: A feasibility study and comparison with randomized single-point detection method.

A mapping technique was used in the present study to explore the biological and imaging characteristics of invasive breast cancer and normal breast tissues in Raman examination data and construct a diagnostic model for breast cancer. Raman examination data reflect the biochemical or molecular characteristics of the target tissues. A total of 45 specimens from patients with breast cancer who underwent surgery and 25 adjacent normal breast tissue specimens were included in the present study. Using the specimens, a total of 53 sets of mapping data and 2,597 pieces of Raman spectral data were obtained. The collected spectra were corrected and fitted, the Raman spectra were analyzed by robust statistical methods, and a diagnostic model was constructed using the k-Nearest Neighbor (KNN) method. The KNN classification method was applied to analyze the characteristics of the mapping test application. The percentage of outliers in the mapping data for malignant and normal breast tissues was 12.7 and 6.6%, respectively. The percentage of outlier data in the conventional single-point detection data for malignant and normal breast tissues was 24.5 and 26.0%, respectively. Analysis using a t-test identified a significant difference in the number of outliers between mapping and single-point detection for malignant (t=−6.169; P<0.001) and normal breast tissues (t=−8.873; P<0.001). Based on the mapping data, the accuracy, sensitivity and specificity for breast cancer detection by the diagnostic model constructed using the KNN method was 99.56, 96.6 and 98.48%, respectively. The positive and negative predictive value of this model was 99.56 and 89.04%, respectively. The data obtained by mapping technology demonstrated improved stability and contained less outliers compared with single-point detection. The diagnostic model constructed using the mapping data demonstrated excellent diagnostic performance and good correspondence with pathological results. The findings of the present study demonstrated the feasibility of the application of the diagnostic model for intraoperative real-time imaging for patients with breast cancer. This study provided the foundation of Raman spectroscopy-based diagnostic imaging at the molecular level.

Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts.

ObjectiveTo evaluate the validity of two abbreviated protocols (AP) of MRI in breast cancer screening of dense breast tissue.Materials and MethodsThis was a retrospective study in 356 participants with dense breast tissue and negative mammography results. The study was approved by the Nanjing Medical University Ethics Committee. Patients were imaged with a full diagnostic protocol (FDP) of MRI. Two APs (AP-1 consisting of the first post-contrast subtracted [FAST] and maximum-intensity projection [MIP] images, and AP-2 consisting of AP-1 combined with diffusion-weighted imaging [DWI]) and FDP images were analyzed separately, and the sensitivities and specificities of breast cancer detection were calculated.ResultsOf the 356 women, 67 lesions were detected in 67 women (18.8%) by standard MR protocol, and histological examination revealed 14 malignant lesions and 53 benign lesions. The average interpretation time of AP-1 and AP-2 were 37 seconds and 54 seconds, respectively, while the average interpretation time of the FDP was 3 minutes and 25 seconds. The sensitivities of the AP-1, AP-2, and FDP were 92.9, 100, and 100%, respectively, and the specificities of the three MR protocols were 86.5, 95.0, and 96.8%, respectively. There was no significant difference among the three MR protocols in the diagnosis of breast cancer (p > 0.05). However, the specificity of AP-1 was significantly lower than that of AP-2 (p = 0.031) and FDP (p = 0.035), while there was no difference between AP-2 and FDP (p > 0.05).ConclusionThe AP may be efficient in the breast cancer screening of dense breast tissue. FAST and MIP images combined with DWI of MRI are helpful to improve the specificity of breast cancer detection.

Application of Abbreviated Protocol of Magnetic Resonance Imaging for Breast Cancer Screening in Dense Breast Tissue

The study aimed to evaluate the usefulness of an abbreviated protocol (AP) of magnetic resonance imaging (MRI) in comparison to a full diagnostic protocol (FDP) of MRI in the breast cancer screening with dense breast tissue. There are 478 female participants with dense breast tissue and negative mammography results, who were imaged with MRI using AP and FDP. The AP and FDP images were analyzed separately, and the sensitivity and specificity of breast cancer detection were calculated. The chi-square test and receiver operating characteristics curves were used to assess the breast cancer diagnostic capabilities of the two protocols. Sixteen cases of breast cancer from 478 patients with dense breasts were detected using the FDP method, with pathologic confirmation of nine cases of ductal carcinoma in situ, six cases of invasive ductal carcinoma, and one case of mucinous carcinoma. Fifteen cases of breast cancer were successfully screened using the AP method. The sensitivity showed no obvious significant difference between AP and FDP (χ2 = 0.592, P = 0.623), but the specificity showed a statistically significant difference (χ2 = 4.619, P = 0.036). The receiver operating characteristics curves showed high efficacy of both methods in the detection of breast cancer in dense breast tissue (the areas under the curve were 0.931 ± 0.025 and 0.947 ± 0.024, respectively), and the ability to diagnose breast cancer was not statistically significantly different between the two methods. The AP of MRI may improve the detection rate of breast cancer in dense breast tissue, and it may be useful in efficient breast cancer screening.

Integration of Serum Protein Biomarker and Tumor Associated Autoantibody Expression Data Increases the Ability of a Blood-Based Proteomic Assay to Identify Breast Cancer.

Despite significant advances in breast imaging, the ability to accurately detect Breast Cancer (BC) remains a challenge. With the discovery of key biomarkers and protein signatures for BC, proteomic technologies are currently poised to serve as an ideal diagnostic adjunct to imaging. Research studies have shown that breast tumors are associated with systemic changes in levels of both serum protein biomarkers (SPB) and tumor associated autoantibodies (TAAb). However, the independent contribution of SPB and TAAb expression data for identifying BC relative to a combinatorial SPB and TAAb approach has not been fully investigated. This study evaluates these contributions using a retrospective cohort of pre-biopsy serum samples with known clinical outcomes collected from a single site, thus minimizing potential site-to-site variation and enabling direct assessment of SPB and TAAb contributions to identify BC. All serum samples (n = 210) were collected prior to biopsy. These specimens were obtained from 18 participants with no evidence of breast disease (ND), 92 participants diagnosed with Benign Breast Disease (BBD) and 100 participants diagnosed with BC, including DCIS. All BBD and BC diagnoses were based on pathology results from biopsy. Statistical models were developed to differentiate BC from non-BC (i.e., BBD and ND) using expression data from SPB alone, TAAb alone, and a combination of SPB and TAAb. When SPB data was independently used for modeling, clinical sensitivity and specificity for detection of BC were 74.7% and 77.0%, respectively. When TAAb data was independently used, clinical sensitivity and specificity for detection of BC were 72.2% and 70.8%, respectively. When modeling integrated data from both SPB and TAAb, the clinical sensitivity and specificity for detection of BC improved to 81.0% and 78.8%, respectively. These data demonstrate the benefit of the integration of SPB and TAAb data and strongly support the further development of combinatorial proteomic approaches for detecting BC.

Diagnostic Performance and Additional Value of Elastosonography in Focal Breast Lesions: Statistical Correlation between Size-Dependant Strain Index Measurements, Multimodality-BI-RADS Score, and Histopathology in a Clinical Routine Setting

Objective. To evaluate the diagnostic benefit of real-time elastography (RTE) in clinical routine. Strain indices (SI) for benign and malignant tumors were assessed. Methods. 100 patients with 110 focal breast lesions were retrieved. Patients had mammography (MG), ultrasound (US), and, if necessary, MRI. RTE was conducted after ultrasound. Lesions were assessed with BI-RADS for mammography and ultrasound. Diagnosis was established with histology or follow-up. Results. SI for BI-RADS 2 was 1.71 ± 0.86. Higher SI (2.21 ± 1.96) was observed for BI-RADS 3 lesions. SI of BI-RADS 4 and 5 lesions were significantly higher (16.92 ± 20.89) and (19.54 ± 10.41). 31 malignant tumors exhibited an average SI of 16.13 ± 14.67; SI of benign lesions was 5.29 ± 11.87 (P value <0.0001). ROC analysis threshold was >3.8 for malignant disease. Sensitivity of sonography was 90.3% (specificity 78.5%). RTE showed a sensitivity of 87.1% (specificity 79.7%). Accuracy of all modalities combined was 96.8%. In BI-RADS 3 lesions RTE was able to detect all malignant lesions (sensitivity 100%, specificity 92.9%, and accuracy 93.9%). Conclusions. RTE increased sensitivity and specificity for breast cancer detection when used in combination with ultrasound.

Effectiveness of Breast-Specific Gamma Imaging (BSGI) for Breast Cancer in Korea: A Comparative Study

Despite the fact that mammography has been the golden standard in breast cancer detection for several decades, its sensitivity decreases for women with dense breast tissue, which happens to be common in Korea. As an alternative, breast ultrasonography can be effective diagnostic modalities that complement the defect of mammography. Recently, breast-specific gamma imaging (BSGI) has been introduced as a new diagnostic modality for breast cancer. This study was designed to analyze the effectiveness of BSGI in particular. In a retrospective study, 471 patients underwent BSGI, breast ultrasonography, and mammography simultaneously during the period between February 2009 and March 2010. The indications of BSGI were as follows: (a) patient who was diagnosed with malignancy prior to surgery, (b) patient who is under follow up after cancer surgery, (c) patient with lesions which cannot be evaluated by breast ultrasonography or mammography, (d) patient with multiple benign lesions, and (e) patient with suspicious lesion who refuses biopsy. Among these patients, 121 patients underwent biopsy, whereas others were followed up with imaging studies. We compared the BSGI results with those of mammography, breast ultrasonography, and pathology. The mean age of the patients was 49.63 ± 10.43 years. There were 107 patients with 110 malignant lesions and 364 patients with benign lesions. Total 474 lesions were evaluated. The sensitivities of BSGI, mammography, and breast ultrasonography were 94.45%, 93.64%, and 98.18%, respectively, whereas the specificities of BSGI, mammography, and breast ultrasonography were 90.93%, 90.66%, and 87.09%, respectively. The sensitivity and specificity of BSGI for axillary lymph node (LN) status were 44.7 4% and 87.88%, respectively. BSGI is a good complementary imaging modality with high sensitivity and high specificity for breast cancer detection. However, it has low efficacy for the evaluation for axillary LN status.

Near-infrared spectral tomography integrated with digital breast tomosynthesis: effects of tissue scattering on optical data acquisition design.

Design optimization and phantom validation of an integrated digital breast tomosynthesis (DBT) and near-infrared spectral tomography (NIRST) system targeting improvement in sensitivity and specificity of breast cancer detection is presented. Factors affecting instrumentation design include minimization of cost, complexity, and examination time while maintaining high fidelity NIRST measurements with sufficient information to recover accurate optical property maps. Reconstructed DBT slices from eight patients with abnormal mammograms provided anatomical information for the NIRST simulations. A limited frequency domain (FD) and extensive continuous wave (CW) NIRST system was modeled. The FD components provided tissue scattering estimations used in the reconstruction of the CW data. Scattering estimates were perturbed to study the effects on hemoglobin recovery. Breast mimicking agar phantoms with inclusions were imaged using the combined DBT∕NIRST system for comparison with simulation results. Patient simulations derived from DBT images show successful reconstruction of both normal and malignant lesions in the breast. They also demonstrate the importance of accurately quantifying tissue scattering. Specifically, 20% errors in optical scattering resulted in 22.6% or 35.1% error in quantification of total hemoglobin concentrations, depending on whether scattering was over- or underestimated, respectively. Limited frequency-domain optical signal sampling provided two regions scattering estimates (for fat and fibroglandular tissues) that led to hemoglobin concentrations that reduced the error in the tumor region by 31% relative to when a single estimate of optical scattering was used throughout the breast volume of interest. Acquiring frequency-domain data with six wavelengths instead of three did not significantly improve the hemoglobin concentration estimates. Simulation results were confirmed through experiments in two-region breast mimicking gelatin phantoms. Accurate characterization of scattering is necessary for quantification of hemoglobin. Based on this study, a system design is described to optimally combine breast tomosynthesis with NIRST.

Serum protein signature may improve detection of ductal carcinoma in situ of the breast

Ductal carcinoma in situ (DCIS) of the breast is part of a spectrum of preinvasive lesions that originate within normal breast tissue and progress to invasive breast cancer. The detection of DCIS is important for the reduction of mortality from breast cancer, but the diagnosis of preinvasive breast tumors is hampered by the lack of an adequate detection method. To identify the changes in protein expression during the initial stage of tumorigenesis and to identify the presence of new DCIS markers, we analysed serum from 60 patients with breast cancer and 60 normal controls using mass spectrometry. A 23-protein index was generated that correctly distinguishes the DCIS and control groups with sensitivities and specificities in excess of 80% in two independent cohorts. Two candidate peptides were purified and identified as platelet factor 4 (PF-4) and complement C3a(desArg) anaphylatoxin (C3a(desArg)) using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In an independent serum set of 165 patients, PF-4 and C3a(desArg) were significantly upregulated in DCIS compared with non-cancerous controls, as validated using western blot and enzyme-linked immunosorbent assay. We conclude that our serum protein-based test, used in conjunction with image-based screening practices, could improve the sensitivity and specificity of breast cancer detection.

Outcome of Men Presenting with Clinical Breast Problems: The Role of Mammography and Ultrasound

The purpose of this study was to determine the outcome of men presenting with clinical breast problems for breast imaging and to evaluate the role of mammography and ultrasound in the diagnosis of benign and malignant breast problems. We retrospectively reviewed clinical, radiographic, and pathologic records of 165 consecutive symptomatic men presenting to Breast Imaging over a 4 year period. We assessed the clinical indication for referral, mammographic findings, sonographic findings, histologic results, and clinical outcomes. Patients ranged in age from 22 to 96 years. Breast Imaging Reporting and Data System (BI-RADS) category 4 and 5 mammograms and solid sonographic masses were considered suspicious for malignancy. Six of 165 men (4%) had primary breast carcinoma, which were mammographically suspicious in all 6 (100%). Five were invasive ductal carcinoma and one was ductal carcinoma in situ (DCIS). Of 164 mammograms, 20 (12%) were suspicious. Six were cancer and 14 were benign. Clinical follow-up for 2 years or biopsy results were available for 138 of the 165 men (84%). Twelve with benign mammographic findings had benign biopsies. All men with benign mammography not undergoing biopsy were cancer free. Sensitivity for cancer detection (mammography) was 100% and specificity was 90%. Positive predictive value (mammography) was 32% (6 of 19) and the negative predictive value was 100%. Sonography was performed in 68 of the 165 men (41%). Three of three cancers (100%) were solid sonographic masses. There were 9 of 68 false-positive examinations (13%). Sensitivity and negative predictive value for cancer detection (ultrasound) was 100% and specificity was 74%. The most common clinical indication for referral was mass/thickening (56%). Mammography had excellent sensitivity and specificity for breast cancer detection and should be included as the initial imaging examination of men with clinical breast problems. The negative predictive value of 100% for mammography suggests that mammograms read as normal or negative need no further examination if the clinical findings are not suspicious. A normal ultrasound in these men confirms the negative predictive value of a normal mammogram.

Imaging in breast cancer – breast cancer imaging revisited

Imaging in breast cancer – breast cancer imaging revisited

Magnetic resonance imaging of breast cancer: Clinical indications and breast MRI reporting system

Magnetic resonance imaging (MRI) is well suited to the investigation of breast cancer by virtue of its noninvasive nature and its multiplanar imaging abilities. MRI investigations showed high sensitivity but modest specificity for breast cancer detection and diagnosis. Most early studies tested the ability of MRI to evaluate and diagnose findings in the breast discovered by other imaging tests or by breast physical examination (1-4). When it was discovered that MRI identified small breast cancers undetected by mammography or breast ultrasound, MRI was used to estimate breast cancer extent in known cancer cases for surgical planning (5,6). These investigations led to the use of MRI in a multitude of breast imaging applications, raising further questions about the use of MRI in everyday practice: What are the indications for breast MRI in general practice? What is its role in light of other imaging tests? What are its benefits and limitations in each setting? How do I report these studies? The purpose of this article is to review the clinical background regarding indications for the use of MRI and relevant cases in which MRI can impact patient management in breast disease, and to describe new developments in reporting breast MRI studies. J. Magn. Reson. Imaging 2000;12:975-983.

Mammography use and outcomes in a community. The Greater Lansing Area Mammography Study.

Mammography is widely known to reduce morbidity and mortality from breast cancer, but a population-based assessment of mammography use and follow-up of mammography findings has not been reported previously. An observational, population-based, follow-up study was conducted of all women having mammograms in the Greater Lansing, Michigan, metropolitan area, between June 1987 and June 1988. A total of 17,811 Greater Lansing women participated. The adherence of women to mammography screening guidelines was estimated, and mammography's utility to detect breast cancer was assessed through follow-up review of breast biopsy results. Thirty-seven percent of the expected number of women 35 years of age and older had mammograms. Adherence to screening guidelines declined with age, and less than 5% (302 of 6700) of women 55 years of age and older reporting having annual mammograms. Seventy-six percent of women reported that their physicians prompted the examination. The predictive value of a positive mammogram was 21.9% for women without symptoms and 32.4% for women with symptoms. Mammography's sensitivity and specificity for breast cancer detection were 71% and 98%, respectively. The study highlights the need to target mammography to women 50 years of age and older, underscores the importance of physicians in promoting mammography, and demonstrates the analytic value and limitation of mammography in clinical decision-making.