A cluster of microcalcifications: women with high risk for breast cancer versus other women.
ABSTRACT Abnormal screening mammographic findings are the most common presentation of ductal carcinoma in situ, which usually appears as a cluster of microcalcifications. No report has documented the risk of malignancy between the finding of a cluster of microcalcifications and women with high risk of breast cancer.
We investigated the morphologic descriptors of a cluster of microcalcifications in women with a high risk for breast cancer and compared the results with the characteristics of a cluster of microcalcifications in other women. A retrospective review was performed for 81 non-palpable clusters of microcalcifications that had stereotactic vacuum-assisted breast biopsy.
The frequency of malignancy associated with a cluster of microcalcifications was 27%. The 50% frequency of malignancy with high risk for breast cancer was higher, but not significantly so, than the 24% frequency of 71 cases without high risk for breast cancer (P = 0.125). The frequency of malignancy and ADH of a cluster of microcalcifications with high risk of breast cancer was 70%, significantly higher than the 30% frequency of 71 cases without high risk of breast cancer (P = 0.028).
A cluster of microcalcifications in women with high risk for breast cancer should be considered suspicious and referred for biopsy.
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ABSTRACT: The frequency histogram of connected elements (FHCE) is a recently proposed algorithm that has successfully been applied in various medical image segmentation tasks. The FHCE is based on the idea that most pixels belong to the same class as their neighbouring pixels. However, the FHCE performance relies to a great extent on the optimal selection of a threshold parameter. Since evaluating segmentation results is a highly subjective process, a collection of threshold values must typically be examined. No algorithm has been proposed to automate the determination of the threshold parameter value of the FHCE. This study presents a method based on the fuzzy C-means clustering algorithm, designed to automatically generate optimal threshold values for the FHCE. This new approach was applied as a part of a structured sequence of image processing steps in order to facilitate segmentation of microcalcifications in digitized mammograms. A unique threshold value was generated for each mammogram, taking into account the different grey-level patterns based on different compositions of various breast tissues in it. The segmentation algorithm was tested on 100 mammograms (50 collected from the Mammographic Image Analysis Society and 50 normal mammograms onto which a number of simulated microcalcifications were generated). The algorithm was able to detect subtle microcalcifications with sensitivity ranging from 93 to 98%, False alarm ratio from 3 to 5% and false negatives variability from 2 to 3%.Imaging Science Journal The 05/2010; 58(3):146-154. DOI:10.1179/136821909X12581187860095 · 0.30 Impact Factor
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ABSTRACT: This study was undertaken to determine the prevalence of flat epithelial atypia at ultrasound-guided and stereotactically guided needle biopsies, to describe the mammographic and sonographic features of flat epithelial atypia, and to determine the significance of lesions diagnosed as flat epithelial atypia at imaging-guided needle biopsies. Retrospective review of a database of 1369 consecutive sonographically and stereotactically guided needle biopsies performed during a 12-month period yielded 33 lesions with flat epithelial atypia as the most severe pathologic entity (32 patients). Two radiologists retrospectively reviewed the imaging presentation, by combined consensus, according to the BI-RADS lexicon. Twenty-two of 33 flat epithelial atypia diagnoses (67%) were obtained under stereotactic guidance, and 11 (33%) were obtained under sonographic guidance. Six patients had synchronous breast cancer. Flat epithelial atypia lesions presented mammographically most often as microcalcifications (20/33 [61%]) distributed in a cluster (14/20 [70%]) with amorphous morphology (13/20 [65%]). Sonographically, flat epithelial atypia lesions appeared most often as masses (9/11 [82%]), with an irregular shape (6/9 [67%]), microlobulated margins (5/9 [56%]), and hypoechoic or complex echotexture (7/9 [78%]). Twenty-eight of 33 lesions (85%) were surgically excised, confirming the flat epithelial atypia diagnosis in 11 of the 28 lesions (39%), yielding carcinoma in four (14%) and atypical ductal hyperplasia in six (21%). Columnar cell changes without atypia were diagnosed in four lesions (14%), and lobular carcinoma in situ was diagnosed in three lesions (11%). Mammographic and sonographic presentation of flat epithelial atypia is not specific (clustered amorphous microcalcifications and irregular, hypoechoic or complex masses). Given the underestimation rate of malignancy, surgical excision should be considered when imaging-guided biopsy yields flat epithelial atypia.American Journal of Roentgenology 09/2011; 197(3):740-6. DOI:10.2214/AJR.10.5265 · 2.73 Impact Factor
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ABSTRACT: The aims of this study were to investigate improving work flow efficiency by shortening the reading time of digital mammograms using a computer-aided reading protocol (CARP) in the screening environment and to increase detection sensitivity using CARP, compared to the current protocol, commonly referred to as the quadrant view (QV). A total of 200 cases were selected for a receiver-operating characteristic (ROC) study to evaluate two image display work flows, CARP and QV, in the screening environment. A Web-based tool was developed for scoring, reporting, and statistical analysis. Cases were scored for and stratified by difficulty. A total of six radiologists of differing levels of training ranging from dedicated mammographers to senior radiology residents participated. Each was timed while interpreting the 200 cases in groups of 50, first using QV and then, after a washout period, using CARP. The data were analyzed using ROC and κ analysis. Interpretation times were also assessed. Using QV, readers' average area under the ROC curve was 0.68 (range, 0.54-0.73). Using CARP, readers' average area under the ROC curve was 0.71 (range, 0.66-0.75). There was no statistically significant difference in reader performance using either work flow. However, there was a statistically significant reduction in the average interpretation time of negative cases from 64.7 seconds using QV to 58.8 seconds using CARP. CARP determines the display order of regions of interest depending on computer-aided detection findings. This is a variation of traditional computer-aided detection for digital mammography that has the potential to reduce interpretation times of studies with negative findings without significantly affecting sensitivity, thus allowing improved work flow efficiency in the screening environment, in which, in most settings, the majority of cases are negative.Academic radiology 11/2011; 18(11):1420-9. DOI:10.1016/j.acra.2011.07.003 · 1.75 Impact Factor