Malignant Breast Masses Research Articles

Utilizing of gray scale &unenhanced power Doppler ultrasound in differentiation of malignant & begin palpable breast lesions :Does vascularity in power Doppler correlate with lymph node status?

US (ultrasound) is currently one of the main diagnosing breast disease .In gay scale US there are typical characteristic features of benign & malignant mass. Used of power Doppler has also been exploited in aiding the benign & malignant differentiation of solid masses.
 1.The purpose of this study was to investigate sensitivity of gray scale US features in differentiating benign from malignant solid breast masses .2.To evaluate the role of power Doppler imaging to differentiate benign & malignant solid breast masse & how power Doppler findings correlate with lymph node involvement .
 The study involved 55 female present with breast lesion , in Department of Diagnostic radiology in AL Dewanyia teaching hospital refered from breast centre in period July 2008 – January 2010 , the inclusion criteria was the presence of breast lesion, undergo surgery , exclusion criteria female with breast lesion & refused surgery. Tempt was made to categories lesions as benign , malignant by using US criteria & power Doppler correlate this findings with pathological results .A total of 55 female patients with solid breast mass. Mean age was (44year ) . Size of breast lesion range from 1-6cm , most common sit of the tumor was upper lateral quadrant in both malignant & benign breast mass. Comparison of US & histological findings was made , this enable to calculate sensitivity (90%) of gray scale ultrasound , sensitivity of power Doppler was 70% & majority of malignant tumors (78%) that demonstrate vascularity in power Doppler showed axillary lymph node invasion . Power Doppler sonography should be considered together with the established criteria in gray scale ultrasound. Further study is indicated by using more advanced procedures like enhanced power Doppler US(using levovist) to increase sensitivity of US.

Descriptive Analysis of the Cytological and Histopathological Diagnosis in Malignant Breast Masses : Experience at King Hussien Medical Center

Descriptive Analysis of the Cytological and Histopathological Diagnosis in Malignant Breast Masses : Experience at King Hussien Medical Center

The Role of Dynamic Contrast Enhanced and Diffusion Weighted MRI in Characterization of Suspicious Breast Masses

Background: Early detection and diagnosis of breast cancer are mandatory for accurate management. Traditionally, mammography and ultrasound are the basic imaging techniques for the detection and localization of breast masses. The low sensitivity and specificity of these imaging tools resulted in a demand for new imaging modalities. Aim of study: to evaluate the role of either diffusion weighted images-MRI or dynamic contrast enhanced MRI in differentiating malignant from benign breast lesions comparing with histopathology results. Patients and Methods: from November 2016 to July 2017, a total of 20 patients presented with suspicious breast lesions BIRADS (4&5) were included in the study. All participants underwent breast DWI and DCE-MRI. Results were compared with histopathological results as a standard final diagnostic method. Results: the study included 20 female patients with suspicious breast lesions, there was 15 (75%) malignant lesions while benign lesions, while benign lesions were 5 (25%) cases. DCE-MRI was found to have a sensitivity of 86.7% and specificity of 80%. ADC cutoff value was found to have a value of 1.143*10-3, which was the best to differentiate between benign and malignant breast masses. DWI MRI was found to have sensitivity of 93.3% and a specificity of 80%. Conclusion: DW-MRI alone gave the same performance as in combination with DCE-MRI. The comparison of DWI and DCE-MRI provides a dramatic superiority in the sensitivity, specificity and accuracy of breast DWI-MRI over other modality.

Huge lactating adenoma of the breast: Case report

Lactating adenoma is the commonest benign breast lesion seen during pregnancy and puerperium. It is commonly seen in young primigravideous women in the second or third decade during the third trimester of their pregnancy. Occasionally, lactating adenoma is large and rapidly growing and must be differentiated from malignant breast masses that could be seen during pregnancy and lactation. The diagnosis is usually established by cytological and histopathological examination. Here we have presented a rare case with huge lactating adenoma arising in the left breast of 38 years old Egyptian multiparous lady during lactation. Enucleation of the mass was done with good aesthetic outcome. The case we have presented was unique in its huge size and in being diagnosed in a multiparous lady and furthermore it was successfully treated by enucleation without any need for reconstruction.

Comparison of 3D and 2D shear-wave elastography for differentiating benign and malignant breast masses: focus on the diagnostic performance

To evaluate the diagnostic performance of three-dimensional (3D) image shear-wave elastography (SWE) for differentiating benign from malignant breast masses compared to two-dimensional (2D) SWE and B-mode ultrasound (US). This study consisted of 205 breast lesions from 199 patients who underwent B-mode US and SWE before biopsy from January 2014 to March 2016. Quantitative elasticity values (maximum and mean elasticity, Emax and Emean) obtained from 2D and 3D SWE (axial, sagittal, and coronal images) were reviewed retrospectively, in addition to the histopathological findings including immunohistochemistry profiles (luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple-negative breast cancer) in cases of malignancy. Histopathological findings were regarded as the reference standard. The diagnostic performance of each data set was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC) analysis to compare sensitivity and specificity. Among 205 lesions, 105 (51.22%) were malignant and 100 (48.78%) were benign. Compared to benign masses, malignant masses had higher values of Emax and Emean on both 2D and 3D SWE, the differences of which were statistically significant (p<0.001). The AUCs of 2D, 3D axial, and sagittal SWE were significantly higher than that of 3D coronal SWE (p<0.05). In addition, the sensitivities of axial, sagittal, and coronal 3D SWE were all higher than that of 2D SWE for Emean (81.9%, 87.6%, and 89.5% versus 70.5%, respectively, p<0.05). Conversely, the specificity of 2D and 3D axial SWE was higher than that of 3D sagittal and coronal SWE (Emax, 84%, 83% versus 76%, 73%; Emean, 85%, 81% versus 68%, 50%, respectively, p<0.05). We also assessed changes in Breast Imaging-Reporting and Data System (BI-RADS) category 3 and category 4a lesions by adding each of the parameters for 2D and 3D SWE in B-mode US. The specificity, PPV, and accuracy of combined 2D or combined 3D SWE with B-mode US was statistically higher than that of B-mode US alone for differentiating benign and malignant lesions (p<0.05). Among SWE images, 2D SWE, and 3D SWE axial and sagittal images exhibited superior diagnostic performance compared to 3D coronal images. Addition of 3D SWE images to B-mode US improved the diagnostic performance for distinguishing benign from malignant masses.

Time–frequency based photoacoustic spectral response technique for differentiating human breast masses

Breast cancer is the most prevalent form of cancer among women. Non-invasive and early stage diagnosis of breast cancer would be pragmatic to reduce unnecessary biopsy and mortality rate. We propose Wigner–Ville distribution (WVD) based photoacoustic spectral response (WVD-PASR), a tissue elasticity dependent technique for human breast cancer diagnosis. Since tissue elasticity acts as a finger print of many diseases including cancer, the proposed technique would differentiate normal from malignant breast masses. In addition, WVD is an advanced signal processing tool for time–frequency analysis which provides frequency domain parameters along with time information. This feature of WVD would elicit critical information about frequency component of the PA time domain signal. Since frequency content of PA signal is related to tissue elasticity, WVD-PASR would differentiate human breast masses. Applying the proposed technique on normal and malignant human breast tissues reveals that frequency analysis of malignant tissues contain two dominant peaks as compared to one dominant peak for a normal tissue. Besides having two dominant frequencies, the energy density of malignant breast is significantly more than that of normal tissue. Hence the proposed tool, in addition to detection of malignant breast tumours, could also provide tissue elasticity and other mechano-biological properties.

Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation.

BackgroundLesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses.MethodsWith written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19–85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young’s modulus. In correlation to pathology results, statistical analyses were performed.ResultsPathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21).ConclusionCUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness.

Staging of breast cancer and the advanced applications of digital mammogram: what the physician needs to know?

To study the role of advanced applications of digital mammogram, whether contrast-enhanced spectral mammography (CESM) or digital breast tomosynthesis (DBT), in the "T" staging of histologically proven breast cancer before planning for treatment management. In this prospective analysis, we evaluated 98 proved malignant breast masses regarding their size, multiplicity and the presence of associated clusters of microcalcifications. Evaluation methods included digital mammography (DM), 3D tomosynthesis and CESM. Traditional DM was first performed then in a period of 10-14-day interval; breast tomosynthesis and contrast-based mammography were performed for the involved breast only. Views at tomosynthesis were acquired in a "step-and-shoot" tube motion mode to produce multiple (11-15), low-dose images and in contrast-enhanced study, low-energy (22-33 kVp) and high-energy (44-49 kVp) exposures were taken after the i.v. injection of the contrast agent. Operative data were the gold standard reference. Breast tomosynthesis showed the highest accuracy in size assessment (n = 69, 70.4%) than contrast-enhanced (n = 49, 50%) and regular mammography (n = 59, 60.2%). Contrast-enhanced mammography presented the least performance in assessing calcifications, yet it was most sensitive in the detection of multiplicity (92.3%), followed by tomosynthesis (77%) and regular mammography (53.8%). The combined analysis of the three modalities provided an accuracy of 74% in the "T" staging of breast cancer. The combined application of tomosynthesis and contrast-enhanced digital mammogram enhanced the performance of the traditional DM and presented an informative method in the staging of breast cancer. Advances in knowledge: Staging and management planning of breast cancer can divert according to tumour size, multiplicity and the presence of microcalcifications. DBT shows sharp outlines of the tumour with no overlap tissue and spots microcalcifications. Contrast-enhanced spectral mammogram shows the extent of abnormal contrast uptake and detects multiplicity. Integrated analysis provides optimal findings for proper "T" staging of breast cancer.

Computer-aided classification of mammographic masses using visually sensitive image features.

To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a "visual aid" interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features.

Application of 3D and 2D quantitative shear wave elastography (SWE) to differentiate between benign and malignant breast masses

As breast cancer tissues are stiffer than normal tissues, shear wave elastography (SWE) can locally quantify tissue stiffness and provide histological information. Moreover, tissue stiffness can be observed on three-dimensional (3D) colour-coded elasticity maps. Our objective was to evaluate the diagnostic performances of quantitative features in differentiating breast masses by two-dimensional (2D) and 3D SWE. Two hundred ten consecutive women with 210 breast masses were examined with B-mode ultrasound (US) and SWE. Quantitative features of 3D and 2D SWE were assessed, including elastic modulus standard deviation (ESDE) measured on SWE mode images and ESDU measured on B-mode images, as well as maximum elasticity (Emax). Adding quantitative features to B-mode US improved the diagnostic performance (p < 0.05) and reduced false-positive biopsies (p < 0.0001). The area under the receiver operating characteristic curve (AUC) of 3D SWE was similar to that of 2D SWE for ESDE (p = 0.026) and ESDU (p = 0.159) but inferior to that of 2D SWE for Emax (p = 0.002). Compared with ESDU, ESDE showed a higher AUC on 2D (p = 0.0038) and 3D SWE (p = 0.0057). Our study indicates that quantitative features of 3D and 2D SWE can significantly improve the diagnostic performance of B-mode US, especially 3D SWE ESDE, which shows considerable clinical value.

Color Doppler Findings Differentiating between Benign and Malignant Breast Masses -Jabts Bc-04 Study Part 1-

Color Doppler Findings Differentiating between Benign and Malignant Breast Masses -Jabts Bc-04 Study Part 1-

Diagnostic Value of Fine-Needle Aspiration Biopsies and Pathologic Methods for Benign and Malignant Breast Masses and Axillary Node Assessment

Bacground:The goal of this study was to evaluate the fine needle aspiration (FNA) preoperatively together with Touch Print, Crush Print, frozen section and pathologic methods to reach a diagnosis for patients with breast and axillary masses.Methods:This study was conducted on 107 patients, and included 111 samples of breast and 43 of axillary masses taken at surgery. Data on epidemiological and clinical features of the patients were collected using a questionnaire. The results of the methods of FNA, Touch Print, and Crush Print were compared with the results of pathology after operations.Results:Comparison between the diagnosis values of FNA with pathology for breast cancer showed sensitivity, sensitivity, positive predictive values, negative predictive values, positive mendacious percentages, and negative mendacious percentages of 80.4%, 98%, 97.3%, 87.6%, 2%, and 19.6%, respectively, and for metastatic axillary lymph nodes, 80%, 95.6%, 94.1%, 84.6%, 4.4%, and 20%. Comparison of diagnosis values of FNA with Touch Print and Crush Print for breast cancer gave values of 82.2%, 89%, 97.3%, 89%, 1.6%, and 17.8%, respectively, and for metastatic axillary lymph nodes 84.2%, 95.8%, 94.1%, 88.4%, 14.2%, and 15.8%.Conclusion:Use of these methods, compared with pathology, can decrease cost, time, and a need for a second surgery and related complications.

Contribution of Sonoelastography in the Differentiation of Benign and Malignant Breast Masses: A Comparative Analysis on Sonographic BIRADS Classification

Contribution of Sonoelastography in the Differentiation of Benign and Malignant Breast Masses: A Comparative Analysis on Sonographic BIRADS Classification

Real-Time Elastography for Differentiation of Breast Lesions.

SummaryBackroungTo investigate the diagnostic performance of the elastography-based strain index ratio in the differential diagnosis of malignant and benign breast lesions.Material/MethodsSeventy-nine breast masses that were classified as BI-RADS category 3, 4, and 5 on B-mode ultrasonography (US) were further prospectively evaluated by real-time sonoelastography (RTE). To obtain an optimal cut-off value of the strain ratio for differentiating between malignant and benign breast lesions, RTE findings were compared with histopathology of core needle biopsy samples or with ultrasound follow-up data of the analyzed masses.ResultsSeventy-nine breast lesions [BI-RADS category 3 (n=15), BI-RADS category 4 (n=34), and BI-RADS category 5 (n=30)] were classified as malignant (n=36) or benign (n=43). The mean strain index value was 6.59±3.44 (range 0.6–14) for malignant lesions and 2.79±2.16 (range 0.6–8.7) for benign lesions, respectively (p<0.05). As regards the detection of malignant lesions, US was characterized by sensitivity and specificity of 100% (CI 95%; 88–100) and 90% (CI 95%; 76–97), respectively. When an optimal value of the strain ratio (4.25) was obtained by ROC curve analysis, the sensitivity and specificity for diagnosing malignant lesions were 86% (CI 95%; 70–95) and 76% (CI 95%; 60–87), respectively.ConclusionsRTE can play an important role in the differentiation between malignant and benign breast masses, but it should be used in conjunction with ultrasonography.

Color Doppler Findings of Malignant Breast Masses -Jabts Bc-04 Study Part 2-

Color Doppler Findings of Malignant Breast Masses -Jabts Bc-04 Study Part 2-

Value of virtual touch tissue quantification combined with BI-RADS for differential diagnosis of benign and malignant breast masses

Objective To investigate the value of virtual touch tissue quantification combined with BI-RADS for differential diagnosis of benign and malignant breast lesions. Methods A total of 142 breast masses in 138 patients were detected by normal ultrasound and VTQ, and classified in grade 3 and grade 4 by BI-RADS. Share wave velocities(SWV) of lesions were measured, and the results were correlated with the pathologic results, the ROC curve were produced to find the cutoff value point of SWV to predict breast cancer. The difference between benign and malignant of masses was analyzed. Results VTQ in diagnosis of malignant breast masses of ROC area was 0.91(95%CI: 0.86~0.96). The cut-off point of SWV was determined as 3.4 m/s, the sensitivity, specificity, consistent rate and positive predictive value were 82.7%, 78.1%, 82.4%, 85.9%, respectively. The sensitivity, specificity, consistent rate and positive predictive value of BI-RADS were 85.2%, 78.7%, 82.4%, 84.1%, respectively. The sensitivity, specificity, consistent rate and positive predictive value of VTQ(3.4 m/s as the cut-off point) combined with BI-RADS in diagnosis malignant breast masses were 96.3%, 63.9%, 82.4% and 78.0%, respectively. Conclusions VTQ can help to differentiate benign from malignant breast diseases.The diagnostic value is improved when VTQ combined with BI-RADS. Key words: Ultrasonography; Breast diseases; Virtual touch tissue quantification; BI-RADS

Contribution of IVIM to Conventional Dynamic Contrast-Enhanced and Diffusion-Weighted MRI in Differentiating Benign from Malignant Breast Masses

Background: The aim of this study was to determine whether the indicators obtained from intravoxel incoherent motion (IVIM) imaging can improve the characterization of benign and malignant breast masses compared with conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI). Patients and Methods: This study included 23 benign and 31 malignant breast masses of 48 patients. Main indicators were initial enhancement ratio (IER), time-signal intensity curve (TIC), apparent diffusion coefficient (ADC), tissue diffusivity (D), pseudodiffusivity (D*), and perfusion fraction (f). The discriminative abilities of the different models were compared by means of receiver operating characteristic (ROC) curve and area under the ROC curve (AUC) analysis. Results: D had the highest AUC (0.980), sensitivity (93.55%), specificity (100%), and diagnostic accuracy (96.36%). Both D and TIC could provide the independent predicted features for malignant breast masses. The combination of D and TIC had an AUC of up to 0.990. Conclusion: D of IVIM can effectively complement existing conventional DCE-MRI and DW-MRI in differentiating malignant from benign breast masses. IVIM combined with DCE-MRI is a robust means of evaluating breast masses.

A randomised pilot study comparing 13 G vacuum-assisted biopsy and conventional 14 G core needle biopsy of axillary lymph nodes in women with breast cancer

To compare the acceptability, safety, and feasibility of vacuum-assisted biopsy (VAB) and core needle biopsy (CNB) of axillary lymph nodes in women with breast cancer. This parallel, non-blinded, randomised study was approved by the National Research Ethics Service. Following written informed consent, women with abnormal appearing axillary lymph nodes and radiologically malignant breast masses were randomised 1:1 to lymph node sampling under local anaesthetic with either 14 G CNB or 13 G VAB in a single UK centre. Primary outcomes were study uptake rate and patient willingness to undergo a repeat procedure if necessary. Procedure duration, immediate and post-procedure pain scores, diagnostic yield, complications, and surgical histopathology were recorded. Ninety-five women were approached; 81 (85.3%) consented and were randomised. Forty underwent CNB; 40 underwent VAB; one was excluded. Median age was 57 years. The median procedure time was 2 minutes for both techniques. The median number of samples obtained was three for CNB and four for VAB. Median pain scores for the procedure and first 3 days were 1/10 and 1/10 for CNB and 1/10 and 2/10 for VAB (p=0.11 and 0.04). More women were prepared to undergo repeat CNB compared to VAB, but the difference was not significant (38/39 versus 33/39; p=0.11). Two patients developed a haematoma after VAB. One CNB and six VABs failed to yield adequate tissue (p=0.11), but the sensitivity was similar at 79% and 78%. Study uptake was high. Acceptability of the two procedures was similar, but VAB was associated with more post-procedure pain. The sensitivity appears to be similar.

Efficacy of Sonoelastography in Distinguishing Benign from Malignant Breast Masses.

The study aimed to evaluate the influence of sonoelastographic strain ratio in distinguishing benign from malignant breast masses. Patients who were referred for diagnostic biopsy of a breast mass were examined by ultrasound and sonoelastography prior to percutaneous biopsy. Sonoelastography was performed twice by the same observer in the same session. The strain ratios (SR) were calculated for both measurements as well as the mean strain ratio. Results were compared with histopathologic findings. For each strain ratio, a threshold value was determined using a ROC analysis for the differentiation of benign and malignant masses. After histopathological examination of 135 mass lesions in 132 female patients (mean age 48±12 years), 65 masses were diagnosed as benign and 70 as malignant. According to the Tsukuba classification with 5 scores; 44 of 65 benign masses had scores of either 1 or 2 while 56 of 70 malignant lesions had scores of either 4 or 5. No benign lesion was classified as score 5, and no malignant lesion as score 1. The mean cut-off in the two ROC measurements in distinguishing benign from malignant lesions was calculated as 4.52. When a threshold value of 4.52 was used for the mean strain ratio: the sensitivity, specificity, PPV, NPV, and accuracy rates were determined as 85.5%, 84.8%, 85.5%, 84.8% and 85.2%, respectively. The threshold value for strain ratio in the differentiation of benign and malignant masses was detected as 4.52, and a significant intra-observer difference was not observed in this study. The diagnostic value of sonoelastograghy in distinguishing benign from malignant breast masses was higher in comparison to conventional ultrasound.

Automated Detection Algorithm of Breast Masses in Three-Dimensional Ultrasound Images.

ObjectivesWe propose an automatic breast mass detection algorithm in three-dimensional (3D) ultrasound (US) images using the Hough transform technique.MethodsOne hundred twenty-five cropped images containing 68 benign and 60 malignant masses are acquired with clinical diagnosis by an experienced radiologist. The 3D US images are masked, subsampled, contrast-adjusted, and median-filtered as preprocessing steps before the Hough transform is used. Thereafter, we perform 3D Hough transform to detect spherical hyperplanes in 3D US breast image volumes, generate Hough spheres, and sort them in the order of votes. In order to reduce the number of the false positives in the breast mass detection algorithm, the Hough sphere with a mean or grey level value of the centroid higher than the mean of the 3D US image is excluded, and the remaining Hough sphere is converted into a circumscribing parallelepiped cube as breast mass lesion candidates. Finally, we examine whether or not the generated Hough cubes were overlapping each other geometrically, and the resulting Hough cubes are suggested as detected breast mass candidates.ResultsAn automatic breast mass detection algorithm is applied with mass detection sensitivity of 96.1% at 0.84 false positives per case, quite comparable to the results in previous research, and we note that in the case of malignant breast mass detection, every malignant mass is detected with false positives per case at a rate of 0.62.ConclusionsThe breast mass detection efficiency of our algorithm is assessed by performing a ROC analysis.