Novel factors to improve prediction of nodal positivity in patients with clinical T1/T2 breast cancers.

BACKGROUND: Memorial Sloan Kettering Cancer Center (MSKCC) and MD Anderson Cancer Center (MDACC) have established nomograms to predict sentinel node positivity. We propose the addition of two novel variables-distance of tumor from the nipple and from the skin-can improve their performance. METHODS: Ultrasounds of clinical T1/T2 tumors were reviewed. Distances of the tumor from the skin and from the nipple were measured. MSKCC and MDACC nomogram predictions and the AUC-ROC for each model were calculated. The added utility of the two variables was then examined using multiple logistic regression. RESULTS: Of 401 cancers studied, 79 (19.7 %) were node positive. The mean distance of tumors from the nipple in node-positive patients was 4.9 cm compared with 6.0 cm in node-negative patients (p = 0.0007). The mean distance of tumors from the skin was closer in node-positive cases (0.8 cm) versus node-negative cases (1.0 cm, p = 0.0007). The MSKCC and MDACC nomograms AUC-ROC values were 0.71 (95 % CI 0.64-0.77) and 0.74 (95 % CI 0.68-0.81). When adjusted for the MSKCC predicted probability, addition of both distance from nipple (p = 0.008) and distance from skin (p = 0.02) contributed significantly to prediction of nodal positivity and improved the AUC-ROC to 0.75 (95 % CI 0.70-0.81). Similarly, distance from nipple (p = 0.002), but not distance from skin (p = 0.09), added modestly to the MDACC nomogram performance (AUC 0.77; 95 % CI 0.71-0.83). CONCLUSIONS: Distance of tumor from the nipple and from the skin are important variables associated with nodal positivity. Adding these to established nomograms improves prediction of nodal positivity.

The influence of mammogram acquisition on the mammographic density and breast cancer association in the Mayo Mammography Health Study cohort.

INTRODUCTION: Mammographic density is a strong risk factor for breast cancer. Image acquisition technique varies across mammograms to limit radiation and produce a clinically useful image. We examined whether acquisition technique parameters at the time of mammography were associated with mammographic density and whether the acquisition parameters confounded the density and breast cancer association. METHODS: We examined this question within the Mayo Mammography Health Study (MMHS) cohort, comprised of 19,924 women (51.2% of eligible) seen in the Mayo Clinic mammography screening practice from 2003 to 2006. A case-cohort design, comprising 318 incident breast cancers diagnosed through December 2009 and a random subcohort of 2,259, was used to examine potential confounding of mammogram acquisition technique parameters (x-ray tube voltage peak (kVp), milliampere-seconds (mAs), thickness and compression force) on the density and breast cancer association. The Breast Imaging Reporting and Data System four-category tissue composition measure (BI-RADS) and percent density (PD) (Cumulus program) were estimated from screen-film mammograms at time of enrollment. Spearman correlation coefficients (r) and means (standard deviations) were used to examine the relationship of density measures with acquisition parameters. Hazard ratios (HR) and C-statistics were estimated using Cox proportional hazards regression, adjusting for age, menopausal status, body mass index and postmenopausal hormones. A change in the HR of at least 15% indicated confounding. RESULTS: Adjusted PD and BI-RADS density were associated with breast cancer (p-trends < 0.001), with a 3 to 4-fold increased risk in the extremely dense vs. fatty BI-RADS categories (HR: 3.0, 95% CI, 1.7 - 5.1) and the ≥ 25% vs. ≤ 5% PD categories (HR: 3.8, 95% CI, 2.5 - 5.9). Of the acquisition parameters, kVp was not correlated with PD (r = 0.04, p = 0.07). Although thickness (r = -0.27, p < 0.001), compression force (r = -0.16, p < 0.001), and mAs (r = -0.06, p = 0.008) were inversely correlated with PD, they did not confound the PD or BI-RADS associations with breast cancer and their inclusion did not improve discriminatory accuracy. Results were similar for associations of dense and non-dense area with breast cancer. CONCLUSIONS: We confirmed a strong association between mammographic density and breast cancer risk that was not confounded by mammogram acquisition technique.

Is there a role for magnetic resonance imaging in diagnosing palpable breast masses when mammogram and ultrasound are negative?

BACKGROUND: The use of breast magnetic resonance imaging (MRI) for screening high-risk patients is well established. However, the role of MRI as a diagnostic problem-solving tool is less well studied. With the increasing availability of MRI, its use for problem solving has increased. This small retrospective study examines the use and utility of breast MRI in evaluating palpable breast masses with negative diagnostic mammogram and ultrasound studies. METHODS: We reviewed our breast MRI database, selecting breast MRI studies performed to assess palpable abnormalities with negative mammogram and ultrasound findings. Evidence of cancer was determined by biopsy. RESULTS: Seventy-seven studies were included, comprising 1.3% of all breast MRI studies performed at our institution during the study period (2005-2011). Twenty-two patients underwent biopsy, and 55 were followed clinically without biopsy. Approximately half (27 of 55) of the patients without biopsy were lost to follow-up after negative MRI, and the rest had no evidence of cancer on imaging or clinical examination at 1 year. Of the 22 patients who underwent biopsy, 2 were diagnosed with cancer, both with positive MRI studies. Sensitivity of MRI when compared to tissue diagnosis was 100%, and specificity was 70%. Positive and negative predictive values were 25% and 100%, respectively. CONCLUSIONS: When used for evaluation of a palpable breast mass with negative traditional imaging, breast MRI likely offers low yield of cancer diagnosis and low specificity. Negative MRI results may cause a low compliance rate for recommended follow-up. Because a biopsy is indicated for persistent palpable masses, the addition of diagnostic MRI only adds another step, with associated costs and burdens.

A novel automated mammographic density measure and breast cancer risk.

BACKGROUND: Mammographic breast density is a strong breast cancer risk factor but is not used in the clinical setting, partly because of a lack of standardization and automation. We developed an automated and objective measurement of the grayscale value variation within a mammogram, evaluated its association with breast cancer, and compared its performance with that of percent density (PD). METHODS: Three clinic-based studies were included: a case-cohort study of 217 breast cancer case subjects and 2094 non-case subjects and two case-control studies comprising 928 case subjects and 1039 control subjects and 246 case subjects and 516 control subjects, respectively. Percent density was estimated from digitized mammograms using the computer-assisted Cumulus thresholding program, and variation was estimated from an automated algorithm. We estimated hazards ratios (HRs), odds ratios (ORs), the area under the receiver operating characteristic curve (AUC), and 95% confidence intervals (CIs) using Cox proportional hazards models for the cohort and logistic regression for case-control studies, with adjustment for age and body mass index. We performed a meta-analysis using random study effects to obtain pooled estimates of the associations between the two mammographic measures and breast cancer. All statistical tests were two-sided. RESULTS: The variation measure was statistically significantly associated with the risk of breast cancer in all three studies (highest vs lowest quartile: HR = 2.0 [95% CI = 1.3 to 3.1]; OR = 2.7 [95% CI = 2.1 to 3.6]; OR = 2.4 [95% CI = 1.4 to 3.9]; [corrected] all P (trend) < .001). [corrected]. The risk estimates and AUCs for the variation measure were similar to [corrected] those for percent density (AUCs for variation = 0.60-0.62 and [corrected] AUCs for percent density = 0.61-0.65). [corrected]. A meta-analysis of the three studies demonstrated similar associations [corrected] between variation and breast cancer (highest vs lowest quartile: RR = 1.8, 95% CI = 1.4 to 2.3) and [corrected] percent density and breast cancer (highest vs lowest quartile: RR = 2.3, 95% CI = 1.9 to 2.9). CONCLUSION: The association between the automated variation measure and the risk of breast cancer is at least as strong as that for percent density. Efforts to further evaluate and translate the variation measure to the clinical setting are warranted.

Should axillary ultrasound be used in patients with a preoperative diagnosis of ductal carcinoma in situ?

BACKGROUND: We evaluated the usefulness of axillary ultrasound (US) in patients with core biopsy-proven ductal carcinoma in situ (DCIS). METHODS: Preoperative axillary US, fine-needle aspiration (FNA), and sentinel lymph node (SLN) data from women with DCIS were reviewed. RESULTS: Eighty-two women with DCIS underwent axillary US. In 16 women (19.5%) US was abnormal; however, FNA was negative in all cases. Sixty-one women (74%) underwent SLN surgery; 2 were positive for macrometastasis (3%) and 1 had isolated tumor cells. None of them had an abnormal US. Axillary US did not change the management in any of the cases. CONCLUSIONS: Axillary US and FNA did not change the management in any of the 82 cases. In women with a core biopsy diagnosis of DCIS, positive nodes are uncommon and unlikely to be detected by axillary US. Routine preoperative axillary US is not recommended for pure DCIS on core biopsy.

Detection of breast cancer with addition of annual screening ultrasound or a single screening MRI to mammography in women with elevated breast cancer risk.

CONTEXT: Annual ultrasound screening may detect small, node-negative breast cancers that are not seen on mammography. Magnetic resonance imaging (MRI) may reveal additional breast cancers missed by both mammography and ultrasound screening. OBJECTIVE: To determine supplemental cancer detection yield of ultrasound and MRI in women at elevated risk for breast cancer. DESIGN, SETTING, AND PARTICIPANTS: From April 2004-February 2006, 2809 women at 21 sites with elevated cancer risk and dense breasts consented to 3 annual independent screens with mammography and ultrasound in randomized order. After 3 rounds of both screenings, 612 of 703 women who chose to undergo an MRI had complete data. The reference standard was defined as a combination of pathology (biopsy results that showed in situ or infiltrating ductal carcinoma or infiltrating lobular carcinoma in the breast or axillary lymph nodes) and 12-month follow-up. MAIN OUTCOME MEASURES: Cancer detection rate (yield), sensitivity, specificity, positive predictive value (PPV3) of biopsies performed and interval cancer rate. RESULTS: A total of 2662 women underwent 7473 mammogram and ultrasound screenings, 110 of whom had 111 breast cancer events: 33 detected by mammography only, 32 by ultrasound only, 26 by both, and 9 by MRI after mammography plus ultrasound; 11 were not detected by any imaging screen. Among 4814 incidence screens in the second and third years combined, 75 women were diagnosed with cancer. Supplemental incidence-screening ultrasound identified 3.7 cancers per 1000 screens (95% CI, 2.1-5.8; P < .001). Sensitivity for mammography plus ultrasound was 0.76 (95% CI, 0.65-0.85); specificity, 0.84 (95% CI, 0.83-0.85); and PPV3, 0.16 (95% CI, 0.12-0.21). For mammography alone, sensitivity was 0.52 (95% CI, 0.40-0.64); specificity, 0.91 (95% CI, 0.90-0.92); and PPV3, 0.38 (95% CI, 0.28-0.49; P < .001 all comparisons). Of the MRI participants, 16 women (2.6%) had breast cancer diagnosed. The supplemental yield of MRI was 14.7 per 1000 (95% CI, 3.5-25.9; P = .004). Sensitivity for MRI and mammography plus ultrasound was 1.00 (95% CI, 0.79-1.00); specificity, 0.65 (95% CI, 0.61-0.69); and PPV3, 0.19 (95% CI, 0.11-0.29). For mammography and ultrasound, sensitivity was 0.44 (95% CI, 0.20-0.70, P = .004); specificity 0.84 (95% CI, 0.81-0.87; P < .001); and PPV3, 0.18 (95% CI, 0.08 to 0.34; P = .98). The number of screens needed to detect 1 cancer was 127 (95% CI, 99-167) for mammography; 234 (95% CI, 173-345) for supplemental ultrasound; and 68 (95% CI, 39-286) for MRI after negative mammography and ultrasound results. CONCLUSION: The addition of screening ultrasound or MRI to mammography in women at increased risk of breast cancer resulted in not only a higher cancer detection yield but also an increase in false-positive findings. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00072501.

Distance of breast cancer from the skin and nipple impacts axillary nodal metastases.

BACKGROUND: Lymphatic drainage of the breast is via subareolar and dermal lymphatics. The aim of this study was to determine whether distance of breast cancers from the skin and/or distance from the nipple impacts the likelihood of axillary nodal metastases. METHODS: A retrospective review was performed of sonographically visible T1 and T2 breast cancers with breast and axillary surgery performed at Mayo Clinic, Rochester, MN. Distance of tumor from the nipple was reviewed. Ultrasounds were reviewed to measure the distance of tumor from the skin. RESULTS: Data were collected on 233 eligible T1 or T2 breast cancers, of which 177 (76%) were node negative and 56 (24%) were node positive. On multivariable analysis, tumor stage and lymphovascular invasion, as well as decreasing distance of the tumor from the nipple and decreasing distance of the tumor from the skin, were significantly associated with axillary lymph node positivity. Each 1-cm decrease in the distance of the tumor from the nipple was associated with a 23% increased likelihood of positive lymph nodes (odds ratio 1.23; P = .003). Each 1-mm decrease in the distance of the tumor from the skin was associated with a 15% increased likelihood of positive lymph nodes (odds ratio 1.15; P = .003). CONCLUSION: T1 and T2 breast cancers located closer to the skin and those located closer to the nipple have a higher incidence of metastases to axillary lymph nodes. Distance from the skin and distance from the nipple should be considered when estimating a patient's likelihood of axillary nodal positivity.

Predictive value of sonographic features of extranodal extension in axillary lymph nodes.

OBJECTIVE: The purpose of this study was to assess the accuracy of 5 sonographic features in the prediction of extranodal extension (ENE) in axillary lymph nodes (ALNs) of patients with biopsy-proven breast cancer. METHODS: A review of our institution's surgical and pathologic database was performed for patients with pathologically proven axillary ENE from October 1, 2003, to October 1, 2007. An equivalent number of patients without ENE were included. All patients had sonograms of ALNs available. A radiologist to whom the study was masked reviewed ALN images with specific attention to unclear margins, node matting, perinodal edema, and hilar effacement or replacement. Univariate and multivariate logistic regression analyses were used to obtain the sensitivity, specificity, and odds ratio (OR) for each feature. RESULTS: Our review included a total of 131 patients (64 with ENE and 67 without ENE). The respective sensitivity and specificity estimates for each feature were as follows: node matting, 52% and 84%; perinodal edema, 34% and 87%; unclear margins, 64% and 75%; hilar replacement, 71% and 42%; and hilar effacement, 74% and 60%. Univariate analysis showed a statistically significant association between features and ENE with ORs as follows: matting, 5.4; perinodal edema, 3.4; unclear margins, 5.2; and hilar replacement, 4.3. Multivariate analysis showed that matting and unclear margins were independently associated with ENE. CONCLUSIONS: The sonographic features of unclear margins, node matting, perinodal edema, and hilar replacement have a statistically significant association with ENE. The sonographic features of unclear margins, node matting, and perinodal edema predict ENE with high specificity.

Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer.

CONTEXT: Screening ultrasound may depict small, node-negative breast cancers not seen on mammography. OBJECTIVE: To compare the diagnostic yield, defined as the proportion of women with positive screen test results and positive reference standard, and performance of screening with ultrasound plus mammography vs mammography alone in women at elevated risk of breast cancer. DESIGN, SETTING, AND PARTICIPANTS: From April 2004 to February 2006, 2809 women, with at least heterogeneously dense breast tissue in at least 1 quadrant, were recruited from 21 sites to undergo mammographic and physician-performed ultrasonographic examinations in randomized order by a radiologist masked to the other examination results. Reference standard was defined as a combination of pathology and 12-month follow-up and was available for 2637 (96.8%) of the 2725 eligible participants. MAIN OUTCOME MEASURES: Diagnostic yield, sensitivity, specificity, and diagnostic accuracy (assessed by the area under the receiver operating characteristic curve) of combined mammography plus ultrasound vs mammography alone and the positive predictive value of biopsy recommendations for mammography plus ultrasound vs mammography alone. RESULTS: Forty participants (41 breasts) were diagnosed with cancer: 8 suspicious on both ultrasound and mammography, 12 on ultrasound alone, 12 on mammography alone, and 8 participants (9 breasts) on neither. The diagnostic yield for mammography was 7.6 per 1000 women screened (20 of 2637) and increased to 11.8 per 1000 (31 of 2637) for combined mammography plus ultrasound; the supplemental yield was 4.2 per 1000 women screened (95% confidence interval [CI], 1.1-7.2 per 1000; P = .003 that supplemental yield is 0). The diagnostic accuracy for mammography was 0.78 (95% CI, 0.67-0.87) and increased to 0.91 (95% CI, 0.84-0.96) for mammography plus ultrasound (P = .003 that difference is 0). Of 12 supplemental cancers detected by ultrasound alone, 11 (92%) were invasive with a median size of 10 mm (range, 5-40 mm; mean [SE], 12.6 [3.0] mm) and 8 of the 9 lesions (89%) reported had negative nodes. The positive predictive value of biopsy recommendation after full diagnostic workup was 19 of 84 for mammography (22.6%; 95% CI, 14.2%-33%), 21 of 235 for ultrasound (8.9%, 95% CI, 5.6%-13.3%), and 31 of 276 for combined mammography plus ultrasound (11.2%; 95% CI. 7.8%-15.6%). CONCLUSIONS: Adding a single screening ultrasound to mammography will yield an additional 1.1 to 7.2 cancers per 1000 high-risk women, but it will also substantially increase the number of false positives. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00072501.

Carcinoma of the breast mimicking an areolar dermal lesion.

OBJECTIVE: This report describes the sonographic features of 2 patients with invasive carcinoma of the breast that sonographically mimicked benign epithelial cysts of the areola. METHODS: We retrospectively reviewed 2 cases of invasive ductal carcinoma that initially were diagnosed as dermal lesions in the areola after sonographic evaluation. RESULTS: Sonographically, the 2 lesions were centered between the echogenic lines of the deep dermis of the areola. Neither sonogram showed a deeper component arising from the underlying breast tissue that would suggest a breast origin. CONCLUSIONS: Lesions in the subcutaneous tissue superficial to the anterior pectoral fascia are extraparenchymal in origin and typically are benign. The areolar tissue, however, is not extraparenchymal because the dermis of the areola contains lactiferous ducts; these ducts extend from a more deeply placed mammary gland and are associated with modified sebaceous glands. All types of breast abnormalities, including malignancies, may affect deeper lactiferous glands and ducts and extend into the areola, independent of nipple involvement.

Screening mammograms: interpretation with computer-aided detection--prospective evaluation.

PURPOSE: To prospectively determine the effect of a commercially available computer-aided detection (CAD) system on interpretations of screening mammograms. MATERIALS AND METHODS: Institutional review board approval was granted; informed consent and HIPAA compliance were waived. A total of 21 349 screening mammograms obtained in 18 096 women were interpreted first without and then with review of CAD images to determine the effect of CAD analysis on the screening breast cancer detection rate, recall rate, and positive predictive value (PPV) for biopsy. The percentage of total cancers detected by the radiologists independent of CAD and the percentage correctly marked by the CAD system were determined. RESULTS: On the basis of pre-CAD interpretations, 2101 patients were recalled for diagnostic evaluation, 256 biopsies were performed, and 105 breast cancers were diagnosed. The breast cancer detection rate per 1000 screening mammograms was 4.92 (105 of 21 349 mammograms), the recall rate was 9.84% (2101 of 21 349 mammograms), and the PPV for biopsy was 41.0% (105 of 256 biopsies). After CAD image review, 199 additional patients were recalled, 21 additional biopsies were performed, and eight additional cancers were detected. The effect was a 7.62% (eight of 105) increase in the number of breast cancers detected, an increase in the recall rate to 10.77% (2300 of 21 349 mammograms), and a slight decrease in the PPV to 40.8% (113 of 277 biopsies). Radiologists detected 92.9% (105 of 113 cancers) of the total cancers, and CAD correctly marked 76.1% (86 of 113 cancers). CONCLUSION: The use of CAD improved the detection of breast cancer, with an acceptable increase in the recall rate and a minimal increase in the number of biopsies with benign results.

Breast lesions: evaluation with US strain imaging--clinical experience of multiple observers.

PURPOSE: To prospectively determine the accuracy of using an ultrasonographic (US) strain imaging technique known as lesion size comparison to differentiate benign from malignant breast lesions. MATERIALS AND METHODS: Institutional Review Board approval and patient informed consent were obtained for this HIPPA-compliant study. US strain imaging was performed prospectively for 89 breast lesions in 88 patients. Lesions were imaged by using freehand compression and a real-time strain imaging algorithm. Five observers obtained manual measurements of lesion height, width, and area from B-mode and strain images. By using these size measurements, individual observer and group performances were assessed by using the area under the receiver operating characteristic curve (A(z)). The performance of a single size parameter versus that of a combination of size parameters was evaluated by using univariate and multivariate logistic regression. RESULTS: Group A(z) values showed that width ratio and area ratio yielded the best results for differentiating benign and malignant breast lesions, and they were not statistically different from one another (P = .499). For the group, the performance of area and width, which was superior to that of height and aspect ratio, was statistically significant for all cases (P < .011) except for those that compared area with aspect ratio (P = .118). By using a group threshold of 1.04 for width ratio and 1.13 for area ratio, the sensitivity and specificity of the technique were 96% and 21%, respectively, for width and 96% and 24%, respectively, for area. The best observer achieved a sensitivity of 96% and a specificity of 61% by using the area ratio. For all but one observer, combined size parameters did not improve observer performance (P > .258). Significant interobserver performance variability was observed (P < .001). CONCLUSION: Results suggest that US strain imaging has the potential to aid diagnosis of breast lesions. However, manually tracing lesion boundaries for size ratio differentiation in a busy clinical setting did not match the diagnostic performance levels previously reported. Focusing on measurements of lesion width, along with additional observer training or automated processes, may yield a suitable method for routine clinical application.

Spontaneous unilateral nipple discharge: when screening tests are negative--a case report and review of current diagnostic management of a pathologic nipple discharge.

We describe a 45-year-old woman who presented with a spontaneous unilateral nipple discharge. With a negative breast examination and screening tests (mammography and ultrasonography) she underwent mammary ductography, which revealed a small 3-4 mm intraluminal filling defect. A core biopsy showed high-grade ductal carcinoma in situ (DCIS). An attempted wide local excision was unsuccessful, and the patient underwent a mastectomy. Pathologic assessment revealed high-grade DCIS and multiple foci of invasive mucinous ductal adenocarcinoma. Rare tumor cells were identified in the subcapsular sinuses in both sentinel lymph nodes. We report this case to point out the importance of the diagnostic examination for patients with a pathologic nipple discharge and review current and possible future diagnostic management.