Interobserver agreement and performance score comparison in quality control using a breast phantom: screen-film mammography vs computed radiography

Our objective was to evaluate interobserver agreement and to compare the performance score in quality control of screen-film mammography and computed radiography (CR) using a breast phantom. Eleven radiologists interpreted a breast phantom image (CIRS model X) by four viewing methods: (a) original screen-film; (b) soft-copy reading of the digitized film image; (c) hard-copy reading of CR using an imaging plate; and (d) soft-copy reading of CR. For the soft-copy reading, a 17-in. CRT monitor (1024x1536x8 bits) was used. The phantom image was evaluated using a scoring system outlined in the instruction manual, and observers judged each object using a three-point rating scale: (a) clearly seen; (b) barely seen; and (c) not seen. For statistical analysis, the kappa statistic was employed. For "mass" depiction, interobserver agreement using CR was significantly lower than when using screen-film ( p<0.05). There was no significant difference in the kappa value for detecting "microcalcification"; however, the performance score of "microcalcification" on CR hard-copy was significantly lower than on the other three viewing methods ( p<0.05). Viewing methods (film or CR, soft-copy or hard-copy) could affect how the phantom image is judged. Paying special attention to viewing conditions is recommended for quality control of CR mammograms.     

Accuracy of assigned BI-RADS breast density category definitions

RATIONALE AND OBJECTIVES: Quantitative criteria for the Breast Imaging Reporting and Data System (BI-RADS) mammographic density categories have recently been defined as <25% dense for almost entirely fatty, 25%-50% dense for scattered fibroglandular densities, 51%-75% for heterogeneously dense, and >75% dense for the extremely dense category. The purpose of this study is to compare the range of percent mammographic densities with radiologist-assigned BI-RADS mammographic density categories and compare with the recently issued definitions. MATERIALS AND METHODS: In this study, 200 consecutive negative analog screening mammograms were assigned BI-RADS mammographic density categories independently by three radiologists blinded to the other readers' density assignment. Quantitative assessment of percent mammographic density was performed using previously validated software. RESULTS: All three readers agreed on BI-RADS mammographic density categories in 98 cases (49%), and two of three readers agreed in all 200 cases. Using two reader's consensus, median mammographic density (range) was 6.0% (0.5%-19.2%) for fatty, 14.8% (1.2%-52.7%) for scattered densities, 51.2% (15.9%-82.2%) for heterogeneously dense, and 78.4% (60.1%-87.9%) for extremely dense breasts. The percent mammographic density ranges for fatty and extremely dense breasts correlated well with BI-RADS definitions, whereas the ranges of densities in the scattered and heterogeneously dense categories were considerably broader. CONCLUSION: Fatty and extremely dense BI-RADS categories compare relatively well to defined criteria, and therefore may be helpful in breast cancer risk models. Scattered fibroglandular densities and heterogeneously dense categories have broad percent mammographic density ranges and may not function well in breast cancer risk models.     

Accuracy of segmentation of a commercial computer-aided detection system for mammography

PURPOSE: To assess the accuracy of segmentation in a commercially available computer-aided detection (CAD) system. MATERIALS AND METHODS: Approval for this study was obtained from the authors' institutional review board. Informed consent was not required by the board for this review, as data were stripped of patient identifiers. Two thousand twenty mammograms from 507 women were analyzed with the hardware and software of a commercial CAD system. The accuracy of the segmentation process was determined semiquantitatively and categorized as near perfect if the skin line of the breast was accurately detected, acceptable if only subcutaneous fat was excluded, or unacceptable if any breast parenchyma was excluded from consideration. The accuracy of segmentation was compared for different breast densities and film sizes by using logistic regression (P < .05). RESULTS: Overall, segmentation was near perfect or acceptable in almost 96.8% of images. However, segmentation defects were significantly more common in mammograms with heterogeneously dense breast tissue (8% unacceptable) than in those with fatty replaced (0% unacceptable), scattered (1.2% unacceptable), or extremely dense (1.8% unacceptable) breast parenchyma (P < .05). For images with unacceptable segmentation, the average percentage of breast parenchyma excluded was almost 25% (range, 5%-100%), with no significant differences among breast densities. CONCLUSION: For one commercial CAD system, segmentation was usually near perfect or acceptable but was unacceptable more than five times more frequently for mammograms of breasts with heterogeneously dense parenchyma than for those with all other breast densities. On average, one-quarter of the breast parenchyma was excluded from CAD analysis for images with unacceptable segmentation.     

Detection of masses and microcalcifications of breast cancer on digital mammograms: comparison among hard-copy film, 3-megapixel liquid crystal display (LCD) monitors and 5-megapixel LCD monitors: an observer performance study

The purpose of the study was to compare observer performance in the detection of masses and microcalcifications of breast cancer among hard-copy reading and soft-copy readings using 3-megapixel (3M) and 5-megapixel (5M) liquid crystal display (LCD) monitors. For the microcalcification detection test, we prepared 100 mammograms: 40 surgically verified cancer cases and 60 normal cases. For the mass detection test, we prepared 100 mammograms: 50 cancer cases and 50 normal cases. After six readers assessed both microcalcifications and masses set for each modality, receiver operating characteristic (ROC) analysis was performed. The average A_zs for mass detection using a hard copy and 3M and 5M LCD monitors were 0.923, 0.927 and 0.920, respectively; there were no significant differences. The average A_z for microcalcification detection using hard copy, 3M and 5M LCD monitors was 0.977, 0.954 and 0.972, respectively. There were no significant differences, but the P-values between the hard copy and 3M LCD monitor and that between the 3M and 5M LCD monitor were 0.08 and 0.09, respectively. In conclusion, the observer performances for detecting masses of breast cancers were comparable among the hard copy and two LCD monitors; however, soft-copy reading with a 3M LCD monitor showed slightly lower observer performance for detecting microcalcifications of breast cancers than hard-copy or 5M LCD monitor reading.     

Improving the Detection of Simulated Masses in Mammograms through Two Different Image-Processing Techniques

RATIONALE AND OBJECTIVES: The purpose of this study was to determine whether contrast-limited adaptive histogram equalization (CLAHE) or histogram-based intensity windowing (HIW) improves the detection of simulated masses in dense mammograms. MATERIALS AND METHODS: Simulated masses were embedded in portions of mammograms of patients with dense breasts; the mammograms were digitized at 50 microm per pixel, 12 bits deep. In two different experiments, images were printed both with no processing applied and with related parameter settings of two image-processing methods. A simulated mass was embedded in a realistic background of dense breast tissue, with its position varied. The key variables in each trial included the position of the mass, the contrast levels of the mass relative to the background, and the selected parameter settings for the image-processing method. RESULTS: The success in detecting simulated masses on mammograms with dense backgrounds depended on the parameter settings of the algorithms used. The best HIW setting performed better than the best fixed-intensity window setting and better than no processing. Performance with the best CLAHE settings was no different from that with no processing. In the HIW experiment, there were no significant differences in observer performance between processing conditions for radiologists and nonradiologists. CONCLUSION: HIW should be tested in clinical images to determine whether the detection of masses by radiologists can be improved. CLAHE processing will probably not improve the detection of masses on clinical mammograms.     

Selection of parameters for multi-objective frequency processing in CR mammography: visual evaluation of mammographic phantom images

The multi-objective frequency processing installed in the FCR5000R (Fuji Film Medical) is superior to the conventional processing used in the FCR9000 (Fuji Film Medical) in evaluating frequency processing. A suitable combination of parameters for multi-frequency-processing in computed radiography (CR) mammography was evaluated. The paired-comparison method using phantom images was performed for the visual evaluation. Results showed that the evaluation score of mass and fiber lesions depended on the multi-frequency balance type (MRB) parameter, and the low-frequency-cycle emphasizing parameter had the highest score. In contrast, the score of microcalcifications depended on the degree of multi-frequency enhancement (MRE). The most suitable parameters for the multi-frequency processing of every size and type of breast lesion were not obtained. However, MRB=A, MRT=p, and MRE=1.0 can be recommend for CR mammography.     

Film-screen magnification versus electronic magnification and enhancement of digitized contact mammograms in the assessment of subtle microcalcifications.

RATIONALE AND OBJECTIVES: To compare information drawn from magnification mammography with that extracted from electronic magnification, processing, and display of the digitized contact images. METHODS: Contact and magnification images of a mammographic statistical phantom were obtained. The magnification films versus the computer-enhanced, digitized images of the corresponding contact mammograms were separately presented to three observers. Receiver operating characteristic analysis was used to compare lesion detectability. The contact and magnification mammograms of 86 patients with subtle microcalcifications were also studied. The breast imaging reporting and data system (BI-RADS) scheme was used to compare the magnification patient films versus the corresponding digitized contact images. Differences in mammographic assessment were evaluated by using the kappa statistic. The dose to breast tissue from contact and magnification mammography was measured to evaluate dose reduction in instances where magnification mammography was to be avoided. RESULTS: Lesion detectability was found to be similar when either the digitized film image or the magnification hard-copy film was inspected. Interpretation of patient images by inspection of the contact and magnification screen-film mammograms on a view-box was in excellent agreement with that yielded by inspection of the contact image on a view-box and the computer-enhanced, digitized contact image on a display monitor. CONCLUSIONS: Electronic magnification and processing of the digitized contact image may provide valuable information concerning subtle microcalcifications, rendering magnification mammography unnecessary for many patients with such lesions.     

Analysis of optical density and contrast in mammograms

The objective of this project is the development of tools for the UK NHSBSP to assess image quality quantitatively in clinical films, for the purposes of optimizing imaging procedures and audit. As an initial step, 120 mammograms of 46 women on a single day of screening were digitized and analysed to produce indices of optical density (OD) and contrast. Analysis was performed on three regions of interest (ROI): pectoral muscle, main breast and skin edge. Two radiologists independently graded the quality of information in the different parts of each mammogram, and categorized breast type as either "dense", "mixed density" or "fatty". Measurements of contrast and OD generally correlated well with the opinions of the radiologists. For the oblique mammograms, the mean OD in the main breast ranged between films from 1.25 to 2.24 with a mean of 1.69 +/- 0.02. In the craniocaudal mammograms, the mean OD in the main breast ROI ranged from 1.14 to 1.94 with a mean of 1.61 +/- 0.05. The OD for a quality control film of a 40 mm block of PMMA exposed on the same day with this system was 1.53. A contrast index (CI) was calculated for each mammogram as the difference between the points of maximum and minimum OD in the main breast. Mean CI was 1.02 +/- 0.09 for fatty breasts, 1.50 +/- 0.10 for mixed density breasts and 2.05 +/- 0.23 for dense breasts. A review of the radiologist assessments indicated that the main breast was satisfactorily displayed when glandular and fatty tissues were displayed within the OD range 0.8-2.9. An analysis of the dynamic range requirements showed that 17% of films had a dynamic range that lay above that calculated using the suggested OD limits.     

Mammographic microcalcifications: detection with xerography, screen- film, and digitized film display

Pulverized bone specks and aluminum oxide specks were measured by hand into sizes ranging from 0.2 mm to 1.0 mm and then arranged in clusters. These clusters were superimposed on a human breast tissue phantom, and xeromammograms and screen-film mammograms of the clusters were made. The screen-film mammograms were digitized using a high-resolution laser scanner and then displayed on cathode ray tube (CRT) monitors. Six radiologists independently counted the microcalcifications on the xeromammograms, the screen-film mammograms, and the digitized-film mammograms. The xeromammograms were examined with a magnifying glass; the screen-film images were examined with a magnifying glass and by hot light; and the digitized-film images were examined by electronic magnification and image processing. The bone speck size that corresponded to a mean 50% detectability level for each technique was as follows: xeromammography, 0.550 mm; digitized film, 0.573 mm; and screen-film, 0.661 mm. We postulate that electronic magnification and image processing with edge enhancement can improve the capability of screen-film mammography to enhance the detection of microcalcifications.     

Clinical performance of computer-assisted detection (CAD system in detecting carcinoma in breasts of different densities

OBJECTIVES: To determine the clinical performance of a computer-assisted detection (CAD) system in detecting carcinoma in breasts of different densities. MATERIALS AND METHODS: A total of 264 sets of bilateral screening mammograms taken in craniocaudal and medial-lateral oblique projections during the year 1997 were divided into four groups according to the BI-RADS density classification: fatty (pattern 1), scattered fibroglandular (pattern 2), heterogeneously dense (pattern 3) and extremely dense (pattern 4). Each group contained about 60% normal and 40% biopsy-proven cancer cases. Of the malignant cases, there were a mixture of mammographic findings including focal masses (<2.5 cm), asymmetrical density, architectural distortion or microcalcifications. Films with artefacts and obvious masses>2.5 cm were not included. The chosen cases were then digitized and analysed by the CAD system. Sensitivity was calculated as detection of cancer by at least one marker in at least one view. Specificity was calculated as the number of false-positive marks per image on normal cases. Statistical tests of significance were performed by using contingency tables and Chi square test. RESULTS: The CAD system detected 14 out of the total 15 cancer cases in totally fatty breasts with a sensitivity of 93.3% at a specificity of 1.3 false-positive marks per image. In breasts with scattered fibroglandular pattern, the sensitivity was 93.9% (31/33) and the specificity was 1.6 false-positive marks per image while in heterogeneously dense breasts, the sensitivity of the CAD system fell to 84.8% at a specificity of 1.6 false-positive marks per image. The sensitivity of the CAD system further dropped to 64.3% in markedly dense breasts while maintaining a specificity of 1.2 false-positive marks per image. The decrease in sensitivity in dense breast was found to be significant (p=0.046). CONCLUSION: The sensitivity of the CAD system deteriorated significantly as the density of the breast increased while the specificity of the system remained relatively constant.     

Image quality of a wet laser printer versus a paper printer for full-field digital mammograms

OBJECTIVE: The purpose of our study was to compare the image quality of a wet laser printer with that of a paper printer for full-field digital mammography (FFDM). MATERIALS AND METHODS: For both a wet laser printer and a paper printer connected to an FFDM system, image quality parameters were evaluated using a standardized printer test image (luminance density, dynamic range). The detectability of standardized objects on a phantom was also evaluated. Furthermore, 640 mammograms of 80 patients with different breast tissue composition patterns were imaged with both printers. Subjective image quality parameters (brightness, contrast, and detection of details of anatomic structures-that is, skin, subcutis, musculature, glandular tissue, and fat), the detectability of breast lesions (mass, calcifications), and the diagnostic performance according to the BI-RADS classification were evaluated. RESULTS: Both the luminance density and the dynamic range were superior for the wet laser printer. More standardized objects were visible on the phantom imaged with the wet laser printer than with the paper printer (13/16 vs 11/16). Each subjective image quality parameter of the mammograms from the wet laser printer was rated superior to those of the paper printer. Significantly more breast lesions were detected on the wet laser printer images than on the paper printer images (masses, 13 vs 10; calcifications, 65 vs 48; p < 0.05). With the paper printer images, BI-RADS 4 and 5 categories were underestimated for 10 (43.5%) of 23 patients. CONCLUSION: For FFDM, images obtained from a wet laser printer show superior objective and subjective image quality compared with a paper printer. As a consequence, the paper printer should not be used for FFDM.     

Observer variability in screen-film mammography versus full-field digital mammography with soft-copy reading

Full-field digital mammography (FFDM) with soft-copy reading is more complex than screen-film mammography (SFM) with hard-copy reading. The aim of this study was to compare inter- and intraobserver variability in SFM versus FFDM of paired mammograms from a breast cancer screening program. Six radiologists interpreted mammograms of 232 cases obtained with both techniques, including 46 cancers, 88 benign lesions, and 98 normals. Image interpretation included BI-RADS categories. A case consisted of standard two-view mammograms of one breast. Images were scored in two sessions separated by 5 weeks. Observer variability was substantial for SFM as well as for FFDM, but overall there was no significant difference between the observer variability at SFM and FFDM. Mean kappa values were lower, indicating less agreement, for microcalcifications compared with masses. The lower observer agreement for microcalcifications, and especially the low intraobserver concordance between the two imaging techniques for three readers, was noticeable. The level of observer agreement might be an indicator of radiologist performance and could confound studies designed to separate diagnostic differences between the two imaging techniques. The results of our study confirm the need for proper training for radiologists starting FFDM with soft-copy reading in breast cancer screening. Presented at ECR, Wien 2006.     

Use of prior mammograms in the transition to digital mammography: a performance and cost analysis

Breast screening in Europe is gradually changing from film to digital imaging and reporting of cases. In the transition period prior mammograms (from the preceding screening round) are films thereby potentially causing difficulties in comparison to current digital mammograms. To examine this breast screening performance was measured at a digital mammography workstation with prior mammograms displayed in different formats, and the associated costs calculated. 160 selected difficult cases (41% malignant) were read by eight UK qualified mammography readers in three conditions: with film prior mammograms; with digitised prior mammograms; or without prior mammograms. Lesion location and probability of malignancy were recorded, alongside a decision of whether to recall each case for further tests. JAFROC analysis showed a difference between conditions (p=.006); performance with prior mammograms in either film or digitised formats was superior to that without prior mammograms (p<.05). There was no difference in the performance when the prior mammograms were presented in film or digitised form. The number of benign or normal cases recalled was 26% higher without prior mammograms than with digitised or film prior mammograms (p<.05). This would correspond to an increase in recall rate at the study hospital from 4.3% to 5.5% with no associated increase in cancer detection rate. The cost of this increase was estimated to be ￡11,581 (€13,666) per 10,000 women screened, which is higher than the cost of digitised (￡11,114/€13,115), or film display (￡6451/€7612) of the prior mammograms. It is recommended that, where available, prior mammograms are used in the transition to digital breast screening.     

Diagnostic performance of detecting breast cancer on computed radiographic (CR) mammograms: comparison of hard copy film, 3-megapixel liquid-crystal-display (LCD) monitor and 5-megapixel LCD monitor

The purpose was to compare observer performance in the detection of breast cancer using hard-copy film, and 3-megapixel (3-MP) and 5-megapixel (5-MP) liquid crystal display (LCD) monitors in a simulated screening setting. We amassed 100 sample sets, including 32 patients with surgically proven breast cancer (masses present, N = 12; microcalcifications, N = 10; other types, N = 10) and 68 normal controls. All the mammograms were obtained using computed radiography (CR; sampling pitch of 50 μm). Twelve mammographers independently assessed CR mammograms presented in random order for hard-copy and soft-copy reading at minimal 4-week intervals. Observers rated the images on seven-point (1 to 7) and continuous (0 to 100) malignancy scales. Receiver-operating-characteristics analysis was performed, and the average area under the curve (AUC) was calculated for each modality. The jackknife method with the Bonferroni correction was applied to multireader/multicase analysis. The average AUC values for the 3-MP LCD, 5-MP LCD, and hard-copy film were 0.954, 0.947, and 0.956 on the seven-point scale and 0.943, 0.923, and 0.944 on the continuous scale, respectively. There were no significant differences among the three modalities on either scale. Soft-copy reading using 3-MP and 5-MP LCDs is comparable to hard-copy reading for detecting breast cancer.     

Radiologists' preferences for digital mammographic display. The International Digital Mammography Development Group

PURPOSE: To determine the preferences of radiologists among eight different image processing algorithms applied to digital mammograms obtained for screening and diagnostic imaging tasks. MATERIALS AND METHODS: Twenty-eight images representing histologically proved masses or calcifications were obtained by using three clinically available digital mammographic units. Images were processed and printed on film by using manual intensity windowing, histogram-based intensity windowing, mixture model intensity windowing, peripheral equalization, multiscale image contrast amplification (MUSICA), contrast-limited adaptive histogram equalization, Trex processing, and unsharp masking. Twelve radiologists compared the processed digital images with screen-film mammograms obtained in the same patient for breast cancer screening and breast lesion diagnosis. RESULTS: For the screening task, screen-film mammograms were preferred to all digital presentations, but the acceptability of images processed with Trex and MUSICA algorithms were not significantly different. All printed digital images were preferred to screen-film radiographs in the diagnosis of masses; mammograms processed with unsharp masking were significantly preferred. For the diagnosis of calcifications, no processed digital mammogram was preferred to screen-film mammograms. CONCLUSION: When digital mammograms were preferred to screen-film mammograms, radiologists selected different digital processing algorithms for each of three mammographic reading tasks and for different lesion types. Soft-copy display will eventually allow radiologists to select among these options more easily.     

Computer-aided detection (CAD) in screening mammography: sensitivity of commercial CAD systems for detecting architectural distortion

OBJECTIVE: Computer-aided detection (CAD) algorithms have successfully revealed breast masses and microcalcifications on screening mammography. The purpose of our study was to evaluate the sensitivity of commercially available CAD systems for revealing architectural distortion, the third most common appearance of breast cancer. MATERIALS AND METHODS: Two commercially available CAD systems were used to evaluate screening mammograms obtained in 43 patients with 45 mammographically detected regions of architectural distortion. For each CAD system, we determined the sensitivity for revealing architectural distortion on at least one image of the two-view mammographic examination (case sensitivity) and for each individual mammogram (image sensitivity). Surgical biopsy results were available for each case of architectural distortion. RESULTS: Architectural distortion was deemed present and actionable by a panel of expert breast imagers in 80 views of the 45 cases. One CAD system detected distortion in 22 of 45 cases of distortion (case sensitivity, 49%) and in 30 of 80 mammograms (image sensitivity, 38%); it displayed 0.7 false-positive marks per image. Another CAD system identified distortion in 15 of 45 cases (case sensitivity, 33%) and 17 of 80 mammograms (image sensitivity, 21%); it displayed 1.27 false-positive marks per image. Sensitivity for malignancy-caused distortion was similar to or lower than sensitivity for all causes of distortion. CONCLUSION: Fewer than one half of the cases of architectural distortion were detected by the two most widely available CAD systems used for interpretations of screening mammograms. Considerable improvement in the sensitivity of CAD systems is needed for detecting this type of lesion. Practicing breast imagers who use CAD systems should remain vigilant for architectural distortion.     

Impact of breast density on computer-aided detection for breast cancer

OBJECTIVE: Our aim was to determine whether breast density affects the performance of a computer-aided detection (CAD) system for the detection of breast cancer. MATERIALS AND METHODS: Nine hundred six sequential mammographically detected breast cancers and 147 normal screening mammograms from 18 facilities were classified by mammographic density. BI-RADS 1 and 2 density cases were classified as nondense breasts; BI-RADS 3 and 4 density cases were classified as dense breasts. Cancers were classified as either masses or microcalcifications. All mammograms from the cancer and normal cases were evaluated by the CAD system. The sensitivity and false-positive rates from CAD in dense and nondense breasts were evaluated and compared. RESULTS: Overall, 809 (89%) of 906 cancer cases were detected by CAD; 455/505 (90%) cancers in nondense breasts and 354/401 (88%) cancers in dense breasts were detected. CAD sensitivity was not affected by breast density (p=0.38). Across both breast density categories, 280/296 (95%) microcalcification cases and 529/610 (87%) mass cases were detected. One hundred fourteen (93%) of the 122 microcalcifications in nondense breasts and 166 (95%) of 174 microcalcifications in dense breasts were detected, showing that CAD sensitivity to microcalcifications is not dependent on breast density (p=0.46). Three hundred forty-one (89%) of 383 masses in nondense breasts, and 188 (83%) of 227 masses in dense breasts were detected-that is, CAD sensitivity to masses is affected by breast density (p=0.03). There were more false-positive marks on dense versus nondense mammograms (p=0.04). CONCLUSION: Breast density does not impact overall CAD detection of breast cancer. There is no statistically significant difference in breast cancer detection in dense and nondense breasts. However, the detection of breast cancer manifesting as masses is impacted by breast density. The false-positive rate is lower in nondense versus dense breasts. CAD may be particularly advantageous in patients with dense breasts, in which mammography is most challenging.     

Sclerosing lobular hyperplasia: sonographic pathologic correlation

The objective was to evaluate the sonographic findings of sclerosing lobular hyperplasia (SLH) of the breast and to correlate the sonographic findings and the pathologic features. This study consisted of 9 patients with pathologically proven sclerosing lobular hyperplasia who had undergone a preoperative imaging study. We retrospectively reviewed 9 ultrasonograms and 6 mammograms. In each patient mammographic findings including, shape and margin, and ultrasonographic findings including the size, length-to-anteroposterior ratio, shape, margin, internal echo pattern, and the presence and location of internal echogenic septum, were evaluated. Histopathologic correlations focused on characteristic imaging findings. Of the 6 mammograms, 4 cases showed a lobular (3 of 6) or an oval shaped mass (1 of 6) with a partly obscured margin (4 of 6). The remaining 2 cases showed heterogeneously dense breast without visible mass. Ultrasonograms showed a lobular (5 of 9) or an oval (4 of 9) shaped mass with a circumscribed margin (9 of 9). The mean length/anteroposterior ratio was 1.98. Intratumoral echogenic septum was present in 8 cases. Six cases had a peripherally arising septum. Histopathologic review revealed that this septum was correlated to interlobular sclerosis. A peripherally arising intratumoral echogenic septum on ultrasonography seen in SLH might be explained by the interlobular sclerosis.     

Quantitative analysis of breast parenchymal density: correlation with women's age

RATIONALE AND OBJECTIVES: The authors evaluated the relationship between a woman's breast parenchymal density and her age by means of a quantitative method for measuring density from digitized mammograms. MATERIALS AND METHODS: The percentage of the breast considered to be dense was evaluated from mammograms of 50 women stratified by age. Quantitative analysis based on the computer segmentation of tissue in digitized mammograms was performed by three expert mammographers. The results of this analysis were compared with results from a review of the film mammograms by three expert mammographers. RESULTS: A slight decrease in the percentage of breast considered to be dense with increased age was observed. The average difference in the percentage of dense breast tissue between the youngest and the oldest age groups was 6.4% based on the digital review and 14.6% based on the film review. Within each age group, the total variability was on the order of 75%. CONCLUSION: The difference in mean magnitude between the youngest and oldest age groups was small and may not be clinically important. The variability within an age group was large, which suggests that age is not a reliable indicator of percentage of dense breast tissue.     

Computerized analysis of tissue density effect on missed cancer detection in digital mammography.

This paper presents a study of the analysis of breast density in missed cancer cases and the effect of tissue density on cancer detection. A total of 100 missed cancer cases were collected. The breast density tissue was segmented with a statistical-based method. A set of tests was then applied to examine: (1) the differences in density between the mammograms at the detected stage and that at missed stage; (2) the density difference between the cancerous mammograms and their contra-lateral normal mammograms in the missed cancer cases; (3) the effect of breast density on CAD cancer detection. The results demonstrate that breast density is an important factor affecting not only radiologist's reading but also CAD performance. In order to improve early detection of breast cancer, a special effort should be directed to the high dense breast cases in CAD system design.