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.     

(99m)Tc sestamibi breast imaging for the examination of patients with dense and fatty breasts: multicenter study.

PURPOSE: To evaluate the accuracy of scintimammography as an adjunct to physical examination and mammography in the detection of breast cancer in women with dense and fatty breasts. MATERIALS AND METHODS: A total of 558 women were prospectively enrolled from 42 centers in North America. Images were interpreted by readers blinded to the subjects' clinical history, mammographic findings, and other test results. The Breast Imaging Reporting and Data System classification was used to describe breast density. Parenchymal patterns of "heterogeneously dense" and "extremely dense" were used to classify breasts as dense, whereas "almost entirely fat" and "numerous vague densities" defined fatty breasts. Between-group differences were evaluated with the 2 test for categorical variables and Student t test for continuous variables. Accuracy of scintimammography was assessed against the core laboratory histopathologic evaluation, the standard. The 95% CIs around point estimates of sensitivity, specificity, and positive and negative predictive values were calculated with the normal approximation to the binomial distribution. RESULTS: The analyses were based on 580 breasts with an abnormality; 276 (48%) breasts were dense and 228 had a malignant lesion. Diagnostic properties for scintimammography of fatty versus dense breasts were, respectively, sensitivity, 72% versus 70%; specificity, 80% versus 78%; positive predictive value, 72% versus 67%; negative predictive value, 81% versus 81%; and accuracy, 77% versus 75% (all not significant). Scintimammography led to similar and significant changes in the posttest likelihood of cancer for both dense and fatty breasts. CONCLUSION: The diagnostic accuracy of scintimammography is not affected by breast density.     

Relationship between 18F-FDG uptake and breast density in women with normal breast tissue.

Breast density affects the mammographic detectability of breast cancer. The study aimed to evaluate the impact of breast density on the (18)F-FDG uptake of normal breast tissue. METHODS: The study population consisted of 45 women (median age, 54 y; age range, 42-77 y). All underwent whole-body (18)F-FDG PET for various indications other than breast cancer, and all underwent mammography within a mean of 6.6 +/- 4.9 mo of PET. On the basis of mammographic findings, breasts were categorized as extremely dense, heterogeneously dense, primarily fatty, or entirely fatty. Regions of interest were drawn on every PET image in which breast tissue was visualized. Average and peak standardized uptake values (SUVs) were calculated for the left and right breasts. RESULTS: Mammography showed that 20 of the 45 women had heterogeneously dense breasts, 1 had extremely dense breasts, 20 had primarily fatty breasts, and 4 had entirely fatty breasts. In dense breasts, the average SUV was 0.39 +/- 0.05 (right breast) and 0.36 +/- 0.07 (left breast) and the peak SUV was 0.93 +/- 0.16 and 0.89 +/- 0.18, respectively. The average and peak SUVs were significantly lower for primarily fatty breasts than for dense breasts (P < 0.01). Peak and average SUVs of entirely fatty breasts also differed significantly from peak and average SUVs of dense and primarily fatty breasts (P < 0.01). The impact of hormonal status on SUV was significant but less than the impact of breast density. No significant relationship between average SUV or peak SUV and age or serum glucose level was observed. CONCLUSION: Breast density and hormonal status affect the uptake of (18)F-FDG. Dense breasts exhibit, on average, significantly higher (18)F-FDG uptake than do nondense breasts. However, the highest peak SUV observed in dense breasts was 1.39, which is well below the SUV of 2.5 commonly used as a cutoff between benign and malignant tissue. Therefore, breast density is unlikely to affect the ability of (18)F-FDG PET to discriminate between benign and malignant breast lesions.     

The role of breast tomosynthesis in a predominantly dense breast population at a tertiary breast centre: breast density assessment and diagnostic performance in comparison with MRI

Objectives

To compare breast density measured on digital breast tomosynthesis (DBT) (BI-RADS-based breast composition and fully-automatic estimation) and magnetic resonance imaging (MRI) (BI-RADS amount of fibroglandular tissue), and to evaluate the diagnostic performance in terms of sensitivity and specificity of DBT and MRI in a predominantly dense breast population.

Methods

Between 2015 and 2016, 152 women with 103 breast malignancies, who underwent 3-T breast MRI and DBT within 2 months’ time, were enrolled in this study. Breast composition/fibroglandular tissue and findings on DBT (two readers) and MRI were reported using BI-RADS 5th edition. Digital mammography images were analysed for breast percent density (PD) using the Libra software tool.

Results

A majority of women had dense breasts as categorised by breast composition c (heterogeneously dense) (68%) and d (extremely dense) (15%). The mean PD was 44% (range, 18-89%) and the correlation between breast composition and PD was r = 0.6. The diagnostic performance of MRI was significantly higher compared to DBT for one reader as described by the area under the receiver operating characteristic (ROC) curve (p = 0.004) and of borderline significance for the other reader (p = 0.052).

Conclusions

MRI had higher diagnostic performance than DBT in a dense breast population in the tertiary setting.

Key Points

? MRI had higher diagnostic performance than DBT in a dense breast population ? Diagnostic performance of DBT was comparable to MRI in women with fatty breasts ? MRI was superior to DBT in preoperative breast cancer size assessment

     

Mammographic density measured with quantitative computer-aided method: comparison with radiologists' estimates and BI-RADS categories

PURPOSE: To retrospectively compare computer-aided mammographic density estimation (MDEST) with radiologist estimates of percentage density and Breast Imaging Reporting and Data System (BI-RADS) density classification. MATERIALS AND METHODS: Institutional Review Board approval was obtained for this HIPAA-compliant study; patient informed consent requirements were waived. A fully automated MDEST computer program was used to measure breast density on digitized mammograms in 65 women (mean age, 53 years; range, 24-89 years). Pixel gray levels in detected breast borders were analyzed, and dense areas were segmented. Percentage density was calculated by dividing the number of dense pixels by the total number of pixels within the borders. Seven breast radiologists (five trained with MDEST, two not trained) prospectively assigned qualitative BI-RADS density categories and visually estimated percentage density on 260 mammograms. Qualitative BI-RADS assessments were compared with new quantitative BI-RADS standards. The reference standard density for this study was established by allowing the five trained radiologists to manipulate the MDEST gray-level thresholds, which segmented mammograms into dense and nondense areas. Statistical tests performed include Pearson correlation coefficients, Bland-Altman agreement method, kappa statistics, and unpaired t tests. RESULTS: There was a close correlation between the reference standard and radiologist-estimated density (R = 0.90-0.95) and MDEST density (R = 0.89). Untrained radiologists overestimated percentage density by an average of 37%, versus 6% for trained radiologists (P < .001). MDEST showed better agreement with the reference standard (average overestimate, 1%; range, -15% to +18%). MDEST correlated better with percentage density than with qualitative BI-RADS categories. There were large overlaps and ranges of percentage density in qualitative BI-RADS categories 2-4. Qualitative BI-RADS categories correlated poorly with new quantitative BI-RADS categories, and 16 (6%) of 260 views were erroneously classified by MDEST. CONCLUSION: MDEST compared favorably with radiologist estimates of percentage density and is more reproducible than radiologist estimates when qualitative BI-RADS density categories are used. Qualitative and quantitative BI-RADS density assessments differed markedly.     

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.     

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.     

Lobular carcinoma in situ of the breast: clinical, pathologic, and mammographic features

Lobular carcinoma in situ (LCIS) was diagnosed in 165 surgical specimens (119 patients) at our institution between 1974 and 1987. LCIS was seen more often in younger women (mean age, 49 years) than other breast carcinomas were (mean age, 58 years). Sampling of a single breast revealed multifocal disease in 70% (96/138). When both breasts were sampled, bilateral foci were found in 50% (41/82). Of 165 breasts with foci of LCIS, 37% (61/165) had simultaneously occurring invasive cancers in the same breast. Direct mammographic-pathologic correlation of foci of LCIS was possible in 73 breasts (67 patients). Microcalcifications were an indication for biopsy in 49% (20/41) of breasts with a mammographic abnormality, but were a nonspecific finding often found in tissues adjacent to foci of LCIS. The mammogram was normal in 44% (32/73) of breasts with foci of LCIS. The mammograms of patients with LCIS and those from a group of age-matched control subjects were compared by using a modified form of Wolfe's criteria and the percentage of fibroglandular elements. LCIS was seldom found in an N1 breast (1% vs 29%) or in a breast with less than 25% of its parenchymal area occupied by fibroglandular density (3% vs 33%). Compared with the control group, breasts with LCIS had more than 50% fibroglandular density (85% vs 45%) and a much higher frequency of the DY pattern (56% vs 36%). More fibroglandular density was seen in the LCIS group at all ages. Postmenopausally, the frequencies of the DY pattern and fibroglandular density greater than 50% in LCIS patients were nearly double those in the control group. LCIS patients have disease of the entire breast parenchyma, characterized by multifocality and bilaterality of various forms of lobular disease. Their mammograms reveal a higher rate of the DY pattern and higher percentages of fibroglandular or parenchymal density than those of age-matched controls. In LCIS patients, persistence of the DY pattern, or large amounts of fibroglandular density postmenopausally supports the concept that mammographically dense breasts are a marker for increased cancer risk in women 50 years old and older.     

Breast Density Knowledge in a Screening Mammography Population Exposed to Density Notification

ObjectiveWomen are increasingly informed about their breast density due to state density reporting laws. However, accuracy of personal breast density knowledge remains unclear. We compared self-reported with clinically assessed breast density and assessed knowledge of density implications and feelings about future screening.MethodsFrom December 2017 to January 2020, we surveyed women aged 40 to 74 years without prior breast cancer, with a normal screening mammogram in the prior year, and ≥1 recorded breast density measures in four Breast Cancer Surveillance Consortium registries with density reporting laws. We measured agreement between self-reported and BI-RADS breast density categorized as “ever-dense” if heterogeneously or extremely dense within the past 5 years or “never-dense” otherwise, knowledge of dense breast implications, and feelings about future screening.ResultsSurvey participation was 28% (1,528 of 5,408), and 59% (896 of 1,528) of participants had ever-dense breasts. Concordance between self-report versus clinical density was 76% (677 of 896) among women with ever-dense breasts and 14% (89 of 632) among women with never-dense breasts, and 34% (217 of 632) with never-dense breasts reported being told they had dense breasts. Desire for supplemental screening was more frequent among those who reported having dense breasts 29% (256 of 893) or asked to imagine having dense breasts 30% (152 of 513) versus those reporting nondense breasts 15% (15 of 102) (P = .003, P = .002, respectively). Women with never-dense breasts had 6.3-fold higher odds (95% confidence interval:3.39-11.80) of accurate knowledge in states reporting density to all compared to states reporting only to women with dense breasts.DiscussionStandardized communications of breast density results to all women may increase density knowledge and are needed to support informed screening decisions.     

Optimal gradation processing parameter for soft-copy reading of digital mammogram: comparison between the parameter recommended for hard-copy and other parameters

PURPOSE: To investigate optimal gradation processing parameter for soft-copy reading comparing the parameter recommended for hard-copy with other parameters. MATERIALS AND METHODS: Digital mammograms using a Computed Radiography system were evaluated. The gradation processing parameter recommended by the manufacturer was GA (1.2). We prepared seven parameters that changed the degree of contrast: GA (0.6, 0.8, 1.0, 1.2, 1.4, 1.6, and 1.8). Images of an anthropomorphic breast phantom were displayed on a 5-megapixel liquid crystal display monitor using each parameter. Three readers independently assessed each image, and scored for the following items: intramammary contrast, extramammary contrast, sharpness, and graininess. Total score was calculated in each parameter. We also displayed normal mammograms of nine cases: three with a scattered fibroglandular density, three with a heterogeneously dense breast, and three with an extremely dense breast. These were displayed using GA (1.2) or using parameters with a higher total score than GA (1.2) in the phantom test. Three readers assessed each mammogram as in the phantom test. RESULTS: In phantom test, GA (1.4), GA (1.6), and GA (1.8) obtained higher scores than GA (1.2). In normal cases tested using these parameters, GA (1.4) obtained the highest score. This was significantly higher than that of GA (1.2) (P=0.004). The score obtained for GA (1.4) was the highest in cases with extremely dense and heterogeneously dense breast tissue, though there was no statistically significant difference. CONCLUSION: Soft-copy image quality was improved by gradient processing using higher contrast parameter than that routinely used in hard-copy, especially in dense breast cases.     

Breast-density assessment with hand-held ultrasound: A novel biomarker to assess breast cancer risk and to tailor screening?

Objectives

To assess feasibility and diagnostic accuracy of a novel hand-held ultrasound (US) method for breast density assessment that measures the speed of sound (SoS), in comparison to the ACR mammographic (MG) categories.

Methods

ACR-MG density (a=fatty to d=extremely dense) and SoS-US were assessed in the retromamillary, inner and outer segments of 106 women by two radiographers. A conventional US system was used for SoS-US. A reflector served as timing reference for US signals transmitted through the breasts. Four blinded readers assessed average SoS (m/s), ΔSoS (segment-variation SoS; m/s) and the ACR-MG density. The highest SoS and ΔSoS values of the three segments were used for MG-ACR whole breast comparison.

Results

SoS-US breasts were examined in <2 min. Mean SoS values of densities a-d were 1,421 m/s (SD 14), 1,432 m/s (SD 17), 1,448 m/s (SD 20) and 1,500 m/s (SD 31), with significant differences between all groups (p<0.001). The SoS-US comfort scores and inter-reader agreement were significantly better than those for MG (1.05 vs. 2.05 and 0.982 vs. 0.774; respectively). A strong segment correlation between SoS and ACR-MG breast density was evident (r_s=0.622, p=<0.001) and increased for full breast classification (r_s=0.746, p=<0.001). SoS-US allowed diagnosis of dense breasts (ACR c and d) with sensitivity 86.2 %, specificity 85.2 % and AUC 0.887.

Conclusions

Using hand-held SoS-US, radiographers measured breast density without discomfort, readers evaluated measurements with high inter-reader agreement, and SoS-US correlated significantly with ACR-MG breast-density categories.

Key Points

? The novel speed-of-sound ultrasound correlated significantly with mammographic ACR breast density categories. ? Radiographers measured breast density without women discomfort or radiation. ? SoS-US can be implemented on a standard US machine. ? SoS-US shows potential for a quantifiable, cost-effective assessment of breast density.

     

Can mammographic assessments lead to consider density as a risk factor for breast cancer?

Admitting that mammographic breast density is an important independent risk factor for breast cancer in the general population, has a crucial economical health care impact, since it might lead to increasing screening frequency or reinforcing additional modalities. Thus, the impact of density as a risk factor has to be carefully investigated and might be debated. Some authors suggested that high density would be either a weak factor or confused with a masking effect. Others concluded that most of the studies have methodological biases in basic physics to quantify percentage of breast density, as well as in mammographic acquisition parameters. The purpose of this review is to evaluate mammographic procedures and density assessments in published studies regarding density as a breast cancer risk. No standardization was found in breast density assessments and compared density categories. High density definitions varied widely from 25 to 75% of dense tissues on mammograms. Some studies showed an insufficient follow-up to reveal masking effect related to mammographic false negatives. Evaluating breast density impact needs thorough studies with consensual mammographic procedures, methods of density measurement, breast density classification as well as a standardized definition of high breast density. Digital mammography, more effective in dense breasts, should help to re-evaluate the issue of density as a risk factor for breast cancer.     

Assessment of breast lesions using BI-RADS US lexicon in mammographically dense breasts (ACR categories 3 and 4) with histopathological correlation

Purpose

To assess the role of ultrasonography in detection, and categorization of breast lesions in patients with mammographically dense breasts with the use of the BI-RADS US lexicon.

Patients and methods

This study included 60 female patients (age range from 20 to 80 years, mean 38.3 ± 11.9) complaining of mastalgia, breast lump or nipple discharge with mammographically dense breast tissue. Breast ultrasound was performed to all patients with a 12-MHz linear-array transducer. Sonographic findings of the breast lesions were described and categorized according to the BI-RADS US assessment categories. Biopsy procedures were performed for the sonographically detected breast lesions with histopathological examination of the biopsied tissue.

Results

The main complaint was palpable breast mass encountered in 25 patients, 12 of mastalgia, 4 of nipple discharge, 12 patients were on screening and 7 on follow up. 36 patients were categorized as ACR 3 and 24 ACR 4 regarding the density of their breasts in mammography. Mammography revealed no abnormalities in 31 patients and abnormal in 29 patients, the commonest mammographic finding was breast mass, detected in 19 patients. Ultrasound detected breast lesions in 56 (93.3%) out of 60 patients. BI-RADS US category 2 was the most common category representing 36.7%. Ultrasonography had a diagnostic reliability for differentiating between benign and malignant breast lesions (p = 0.869) in mammographically dense breasts while mammography was diagnostically unreliable (p = 0.045).

Conclusion

Ultrasound is a mandatory adjunct to mammography in detection and characterization of breast lesions in mammographically dense breasts.     

Impact of menopausal status on background parenchymal enhancement and fibroglandular tissue on breast MRI

Objective

To evaluate the effect of menopausal status on the background parenchymal enhancement (BPE) and amount of fibroglandular tissue (FGT) on breast MRI.

Methods

Retrospective review identified 1,130 women who underwent screening breast MRI between July and November 2010. In 28 of these women, breast MRI was performed both at one time point while pre- and one time point while post-menopausal (median interval 49?months). Two independent readers blinded to menopausal status used categorical scales to rate BPE (minimal/mild/moderate/marked) and FGT (fatty/scattered/heterogeneously dense/dense). Consensus was reached when there was disagreement. The sign test was used to assess changes in rating categories, and the Spearman rank and Fisher’s exact tests were used to measure correlations and associations between variables.

Results

Significant proportions of women demonstrated decreases in BPE and FGT on post-menopausal breast MRI (P?=?0.0001 and P?=?0.0009). BPE category was unchanged in 39?% (11/28) and decreased in 61?% (17/28) of women. FGT category was unchanged in 61?% (17/28) and decreased in 39?% (11/28) of women. Age, reason for menopause, or interval between MRIs had no significant impact on changes in BPE and FGT.

Conclusion

On MRI, BPE, and FGT decrease after menopause in significant proportions of women; BPE decreases more than FGT.

Key Points

? On MRI, background parenchymal enhancement and fibroglandular tissue both decrease after menopause. ? The reduced postmenopausal enhancement is more marked in parenchyma than fibroglandular tissue. ? Background enhancement and fibroglandular tissue seen on MRI are under hormonal influence.     

乳腺影像报告和数据系统在国人女性乳腺癌筛查中的应用价值

目的 探讨乳腺影像报告和数据系统(BI-RADS)评估分类在国人女性乳腺癌筛查中的应用价值.方法 搜集2009年8月至12月参加乳腺癌筛查项目中行乳腺X线摄影的3483名妇女资料,参照BI-RADS标准对乳腺评估分类,对于疾病的诊断最终以组织病理结果为金标准,计算BI-RADS评估分类的准确度、敏感度、特异度及BI-RADS各类的阳性预测值(PPV)和阴性预测值(NPV).结果 3483名受检妇女乳腺组成中脂肪型、散在腺体型、不均匀致密型和高度致密型分别有267、1245、1890和81名.进行BI-RADS评估分类,0～5类分别为273(7.8%)、1011(29.0%)、1741(50.0%)、383(11.0%)、59(1.7%)和16(0.5%)名.71例受检者的77个乳腺病变经病理证实,包括恶性病变29例,良性病变48例.BI-RADS评估分类的准确度为63.6%(49/77),敏感度为93.1%(27/29),特异度为45.8%(22/48),BI-RADS总体PPV为50.9%(27/53),0类、4类和5类的PPV分别为25.0%(1/4)、36.4%(12/33)和87.5%(14/16),2类、3类的NPV分别为90.9%(10/11)和100.0%(12/12).结论 乳腺X线摄影应用BI-RADS评估分类可以有效地预测乳腺恶性病变,在国人女性乳腺癌筛查应用中有一定价值.

Abstract：

Objective To study the value of breast imaging reporting and data system (BI-RADS)in Chinese breast cancer screening. Methods A total number of 3483 women participated in breast cancer screening with mammography in Hexi district in Tianjin from August to December 2009, which was organized by ministry of public health. BI-RADS assessment categories and recommendations were compared with histological findings. The precision, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. Results Among 3483 screening mammography cases, 267 were almost entirely fat breast, 1245 were scauered fibroglandular, 1890 were dense and 81 extremely dense.There were 1011 patients(29.0%) with category 1, 1741 (50.0%) with category 2, 383 (11.0%) with category 3, 59 patients(1. 7%) with category 4 and 16 (0. 5%) with category 5 according to BI-RADS assessment categories. Totally, 71 women with 77 lesions were confirmed by histological examinations. There were 29 malignant and 48 benign lesions. The diagnostic precision, sensitivity, specificity of BI-RADS were 63. 6% (49/77) , 93. 1% (27/29) and 45.8% (22/48) . The general PPV of BI-RADS was 50. 9%(27/53). The PPV of categories 0, 4, 5 were 25.0% (1/4), 36. 4% (12/33) and 87. 5% (14/16). The NPV of categories 2 and3 were90.9% (10/11), 100.0% (12/12). Conclusions B1-RADS is of much value in assessing the breast malignancy. It is applicable in Chinese breast cancer screening.     

乳腺影像报告和数据系统在国人女性乳腺癌筛查中的应用价值

目的 探讨乳腺影像报告和数据系统(BI-RADS)评估分类在国人女性乳腺癌筛查中的应用价值.方法 搜集2009年8月至12月参加乳腺癌筛查项目中行乳腺X线摄影的3483名妇女资料,参照BI-RADS标准对乳腺评估分类,对于疾病的诊断最终以组织病理结果为金标准,计算BI-RADS评估分类的准确度、敏感度、特异度及BI-RADS各类的阳性预测值(PPV)和阴性预测值(NPV).结果 3483名受检妇女乳腺组成中脂肪型、散在腺体型、不均匀致密型和高度致密型分别有267、1245、1890和81名.进行BI-RADS评估分类,0～5类分别为273(7.8%)、1011(29.0%)、1741(50.0%)、383(11.0%)、59(1.7%)和16(0.5%)名.71例受检者的77个乳腺病变经病理证实,包括恶性病变29例,良性病变48例.BI-RADS评估分类的准确度为63.6%(49/77),敏感度为93.1%(27/29),特异度为45.8%(22/48),BI-RADS总体PPV为50.9%(27/53),0类、4类和5类的PPV分别为25.0%(1/4)、36.4%(12/33)和87.5%(14/16),2类、3类的NPV分别为90.9%(10/11)和100.0%(12/12).结论 乳腺X线摄影应用BI-RADS评估分类可以有效地预测乳腺恶性病变,在国人女性乳腺癌筛查应用中有一定价值.     

乳腺影像报告和数据系统在国人女性乳腺癌筛查中的应用价值

目的 探讨乳腺影像报告和数据系统(BI-RADS)评估分类在国人女性乳腺癌筛查中的应用价值.方法 搜集2009年8月至12月参加乳腺癌筛查项目中行乳腺X线摄影的3483名妇女资料,参照BI-RADS标准对乳腺评估分类,对于疾病的诊断最终以组织病理结果为金标准,计算BI-RADS评估分类的准确度、敏感度、特异度及BI-RADS各类的阳性预测值(PPV)和阴性预测值(NPV).结果 3483名受检妇女乳腺组成中脂肪型、散在腺体型、不均匀致密型和高度致密型分别有267、1245、1890和81名.进行BI-RADS评估分类,0～5类分别为273(7.8%)、1011(29.0%)、1741(50.0%)、383(11.0%)、59(1.7%)和16(0.5%)名.71例受检者的77个乳腺病变经病理证实,包括恶性病变29例,良性病变48例.BI-RADS评估分类的准确度为63.6%(49/77),敏感度为93.1%(27/29),特异度为45.8%(22/48),BI-RADS总体PPV为50.9%(27/53),0类、4类和5类的PPV分别为25.0%(1/4)、36.4%(12/33)和87.5%(14/16),2类、3类的NPV分别为90.9%(10/11)和100.0%(12/12).结论 乳腺X线摄影应用BI-RADS评估分类可以有效地预测乳腺恶性病变,在国人女性乳腺癌筛查应用中有一定价值.     

The incremental contribution of clinical breast examination to invasive cancer detection in a mammography screening program

OBJECTIVE: The objective of this study was to determine the potential added contribution of clinical breast examination (CBE) to invasive breast cancer detection in a mammography screening program, by categories of age and breast density. SUBJECTS AND METHODS: We prospectively followed 61,688 women aged 40 years or older who had undergone at least one screening examination with mammography and CBE between January 1, 1996, and December 31, 2000, for 1 year after their mammogram for invasive cancer. We computed the incremental sensitivity, specificity, and positive predictive value of CBE over mammography alone for combinations of age and breast density (predominantly fatty or dense). RESULTS: Mammography sensitivity was 78% and combined mammography-CBE sensitivity was 82%, thus CBE detected an additional 4% of invasive cancers. CBE detected a minority of invasive cancers compared with mammography for all age groups and all breast densities. Sensitivity increased from adding CBE to screening mammography for all ages, from 6.8% in women ages 50-59 with dense breasts to 1.8% in women ages 60-69 years with fatty breasts. CBE generally added incrementally more to sensitivity among women with dense breasts. Specificity and positive predictive value declined when CBE was used in conjunction with mammography, and this decrement was more pronounced in women with dense breasts. CONCLUSION: CBE had modest incremental benefit to invasive cancer detection over mammography alone in a screening program, but also led to greater risk of false-positive results. These risks and benefits were greater in women with dense breasts. The balance of risks and benefits must be weighed carefully when evaluating the inclusion of CBE in a screening examination.     

Mammography and subsequent whole-breast sonography of nonpalpable breast cancers: the importance of radiologic breast density

OBJECTIVE: Our purpose was to determine the contribution of mammography followed by sonography for the detection of nonpalpable breast cancers in Breast Imaging Reporting and Data System (BI-RADS) density grades 1-4 breasts, in grades 1 and 2 breasts, and in grades 3 and 4 breasts. MATERIALS AND METHODS: The results of physical, mammographic, and sonographic examinations performed in 4236 patients were reviewed to determine the sensitivities of mammography and sonography for the detection of nonpalpable breast cancers and to calculate the relative risk for detecting nonpalpable breast cancers using sonography in comparison with mammography in density grades 1-4, grades 1 and 2, and grades 3 and 4 breasts. Sonography was performed after mammographic interpretation. RESULTS: Sensitivities of mammography and subsequent sonography for the detection of nonpalpable breast cancers were 69% and 88% in grades 1-4, 80% and 88% in grades 1 and 2, and 56% and 88% in grades 3 and 4 breasts, respectively. The relative risk for detecting nonpalpable breast cancers using sonography was statistically significantly greater than that for detecting nonpalpable breast cancers using mammography in grades 1-4 (relative risk, 1.29; p = 0.024) and in grades 3 and 4 (relative risk, 1.57; p = 0.013) but not in grades 1 and 2 (relative risk, 1.1; p = 0.445) breasts. CONCLUSION: Sonography is a useful adjunct after mammography for the detection of nonpalpable breast cancer, particularly in the dense breast.     

CTLM as an adjunct to mammography in the diagnosis of patients with dense breast

PurposeThe purpose was to evaluate the utility of computed tomographic laser mammography (CTLM) as an adjunct examination to mammography in women with dense breast tissue.MethodsWe retrospectively compared the findings of mammography, CTLM, and adjunct CTLM to mammography with pathology of 155 women scheduled for biopsy or surgery.ResultsPositive lesions were observed more significantly in malignant than benign lesions. The sensitivity of mammography vs. mammography+CTLM was 34.4% vs. 81.57% among extremely dense breasts and 68.29% vs. 95.34% among heterogeneously dense breasts.ConclusionCTLM could distinguish benign lesions from malignant lesions and is not affected by breast density.