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ECR 2019 / C-1412
Added advantage of automated breast ultrasound in the detection of breast lesions in mammographically dense breast
Congress: ECR 2019
Poster No.: C-1412
Type: Scientific Exhibit
Keywords: Breast, Ultrasound, Image compression, Staging, History, Cancer
Authors: N. A. E. H. ElDeib, E. A. Aly, A. M. A. Elmosselhy; Cairo/EG

Methods and materials



1-Methods and Materials


This prospective study was performed in the Female Imaging Unit of the National Cancer Institute (N.C.I), Cairo University; all the included cases gave informed consent.

The study was conducted on 59 patients with 64 lesions presented to the NCI with either palpable breast mass or as a part of early screening starting from January 2017 till July 2018. Their ages ranged from 24 to 81 years (mean age :41 ± 10 SD years). Three cases were represented with bilateral lesions and two cases had two lesions at the same breast.




Dense breast (ACR C or ACR D) on digital mammography.



Breasts with ACR A(predominantly fatty breast)or ACR B (scattered glandular tissue)on digital mammography were excluded.



All of the cases (n=59) were subjected to both digital mammography and Automated breast ultrasound ,as well as routine hand held ultrasound . They were asked to expose the upper part of the body. No other special preparations were needed.

a)  Digital mammography examination protocol design:


A craniocaudal (CC) and a medio-lateral oblique (MLO) view were obtained with the patient in a standing position. Breast compression was applied. 


b)  Automated breast examination protocol design:


AllparticipantsunderwentABUSexamination.Thetransducer lengthis15.3cm,with6-15MHzfrequency.The grayscalelevelsare256withframerate10frame/second.The  examination was performed in the supine position.



A cushion was placed under the shoulder that helped to spread out the breast tissue evenly, with the nipple pointing to the ceiling. A hypo allergenic lotion was placed evenly on the breast with an additional amount on the area of the nipple.

A disposal membrane was used to aid an acoustic coupling and one of the three levels of compression was applied to spread out the breast evenly with respect to image quality and patient comfort. The ABUS scan was continuous and automated. During the acquisition women were asked not to move and to breathe smoothly.

Volume acquisitions were obtained in the axial plane starting from the inferior part of the breast with coronal and sagittal reconstruction.

Image data automatically acquired a 15.4 cm x 17.0 cm volume from the skin to the chest wall up to 5 cm deep with 0.2mm thickness of each slice. For each breast, three volumes were obtained: the central (anteroposterior) volume with the nipple in the center of the footprint , the lateral volume that included the upper outer part of the breast tissue with the nipple located in the inferior-medial corner and the medial volume that included the inner and inferior part of the breast tissue. A nipple marker was placed in every examination for accurate coordinance. For optimal image quality a selection between three breast sizes was made. In women with larger breasts additional views were taken to avoid tissue exclusion.


c)Handheld ultrasound images:-


Gel is applied to breasts and ultrasound examination was done using radial and anteradial techniques with axilla US examination.

Using ultasound device with probe frequency 18-5MHz and footprint 3.89 cm




The digital mammography and automated ultrasound data were evaluated by two experienced radiologists in consensus; both observers were unaware of the pathological data of each patient.

Digital mammography  images:-


Assessment of breast composition, mass characterization (shape, margin density), asymmetry, calcification, mass number, location, axillary lymphadenopathy, extension, skin thickening, retraction and extension architectural distortion, BIRADS classification were done.


Automated ultrasound images(ABUS) and Handheld ultrasound(HHUS)images:-


Assessment of mass characterization (shape, margin orientation, echopattern, posterior feature, calcification), mass number, location, axillary lymphadenopathy,

skin thickening, retraction and BIRADS classification were done. Additionally for ABUS we assessed lesions' character in coronal view.

All breast masses included in this study were interpreted as above described and then the accuracy in reaching the final diagnosis was calculated for ; digital mammography and Automated Ultrasound as well as HHUS.

Pathological results were  used as the gold standard of reference for the 64lesions.Samples were obtained with fine needle aspiration cytology (FNAC),cytology from nipple discharge, core biopsy, surgical excision and radical surgery. Analysis of the samples was performed in the pathology department of the Egyptian National Cancer Institute by a group of well-trained expert pathologists.

Apart from 13 lesionswhichwere proven to benign byfollow upafter 6 months(BIRADSIII)





Data were coded and entered using the statistical package SPSS (Statistical Package for the Social Sciences) version 25. Data was summarized using mean, standard deviation, median, minimum and maximum in quantitative data and using frequency (count) and relative frequency (percentage) for categorical data.

Comparisons between quantitative variables were done using the non-parametric Mann-Whitney test . For comparing categorical data, Chi square (c2) test was performed. Exact test was used instead when the expected frequency is less than 5 . Correlations between quantitative variables were done using Spearman correlation coefficient . Standard diagnostic  indices including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic efficacy were calculated as described by . Testing for agreement between different methods in numerical data was done using the Intra Class Coefficient (ICC) with 95% confidence interval (95%CI) . P value less than 0.05 was considered as statistically significant.

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