Detection of breast cancer at a smaller size can reduce the likelihood of metastatic spread: a quantitative analysis

Spatiotemporal spread of oncolytic virus in a heterogeneous cell population

Oncolytic (cancer-killing) virus treatment is a promising new therapy for cancer, with many viruses currently being tested for their ability to eradicate tumors. One of the major stumbling blocks to the development of this treatment modality has been preventing spread of the virus to non-cancerous cells. Our recent ability to manipulate RNA and DNA now allows for the possibility of creating designer viruses specifically targeted to cancer cells, thereby significantly reducing unwanted side effects in patients. In this study, we use a partial differential equation model to determine the characteristics of a virus needed to contain spread of an oncolytic virus within a spherical tumor and prevent it from spreading to non-cancerous cells outside the tumor. We find that oncolytic viruses that have different infection rates or different cell death rates in cancer and non-cancerous cells can be made to stay within the tumor. We find that there is a minimum difference in infection rates or cell death rates that will contain the virus and that this threshold value depends on the growth rate of the cancer. Identification of these types of thresholds can help researchers develop safer strains of oncolytic viruses allowing further development of this promising treatment.

Aspirin Use and Survival Among Patients With Breast Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Previous meta-analyses have indicated that aspirin could affect breast cancer outcomes, particularly when taken post-diagnostically. However, several recent studies appear to show little to no association between aspirin use and breast cancer mortality, all-cause mortality, or recurrence.

AIMS

This study aims to conduct an updated systematic review and meta-analysis on the associations of pre-diagnostic and post-diagnostic aspirin use with the aforementioned breast cancer outcomes. It also looks, through subgroup analyses and meta-regressions, at a range of variables that could explain the associations between aspirin use and breast cancer outcomes.

RESULTS

In total, 24 papers and 149 860 patients with breast cancer were included. Pre-diagnostic aspirin use was not associated with breast-cancer-specific mortality (HR 0.98, 95% CI, 0.80-1.20, P = .84) or recurrence (HR 0.94, 95% CI, 0.88-1.02, P = .13). Pre-diagnostic aspirin was associated with non-significantly higher all-cause mortality (HR 1.27, 95% CI, 0.95-1.72, P = .11). Post-diagnostic aspirin was not significantly associated with all-cause mortality (HR 0.87, 95% CI, 0.71-1.07, P = .18) or recurrence (HR 0.89, 95% CI, 0.67-1.16, P = .38). Post-diagnostic aspirin use was significantly associated with lower breast-cancer-specific mortality (HR 0.79, 95% CI, 0.64-0.98, P = .032).

CONCLUSIONS

The only significant association of aspirin with breast cancer outcomes is lower breast-cancer-specific mortality in patients who used aspirin post-diagnostically. However, factors such as selection bias and high inter-study heterogeneity mean that this result should not be treated as conclusive, and more substantial evidence such as that provided by RCTs is needed before any decisions on new clinical uses for aspirin should be made.

Bioelectric Dysregulation in Cancer Initiation, Promotion, and Progression

Cancer is primarily a disease of dysregulation – both at the genetic level and at the tissue organization level. One way that tissue organization is dysregulated is by changes in the bioelectric regulation of cell signaling pathways. At the basis of bioelectricity lies the cellular membrane potential or V_mem, an intrinsic property associated with any cell. The bioelectric state of cancer cells is different from that of healthy cells, causing a disruption in the cellular signaling pathways. This disruption or dysregulation affects all three processes of carcinogenesis – initiation, promotion, and progression. Another mechanism that facilitates the homeostasis of cell signaling pathways is the production of extracellular vesicles (EVs) by cells. EVs also play a role in carcinogenesis by mediating cellular communication within the tumor microenvironment (TME). Furthermore, the production and release of EVs is altered in cancer. To this end, the change in cell electrical state and in EV production are responsible for the bioelectric dysregulation which occurs during cancer. This paper reviews the bioelectric dysregulation associated with carcinogenesis, including the TME and metastasis. We also look at the major ion channels associated with cancer and current technologies and tools used to detect and manipulate bioelectric properties of cells.

Selective in vitro anticancer effect of blueberry extract (Vaccinium virgatum) against C6 rat glioma: exploring their redox status

The aim of this study was to investigate the anticancer potential of blueberry extract (Vaccinium virgatum) against a C6 rat glioma lineage. Cultures of the C6 cells were exposed to blueberry extract at concentrations of 50 to 600 µg/mL for 12, 24, 48, or 72 h and then evaluated for cell viability, proliferation, migration, colony formation and oxidative stress. We also evaluated the effects of blueberry extract on primary rat cortical astrocytes. Our results show that treatment with blueberry extract did not alter the viability or proliferation of normal primary astrocytes but it did significantly reduce the viability in 21.54 % after 48 h and proliferation in 8.59 % after 24 h of C6 cells at 200 µg/mL. We also observed a reduction in the size of the colonies of 29.99 % at 100 µg/mL when compared to the control cells and cell migration was also reduced at 50 µg/mL. After 72 h, there was a reduction in the reactive oxygen species levels ranging from 46.26 to 34.73 %, in addition to a 380.2 % increase in total thiol content. Superoxide dismutase, catalase, and glutathione S-transferase activities were also enhanced when compared to the control. Taken together this data suggests that blueberry extract exerts some selective anticancer activity in C6 glioma cells.

Electric Fields at Breast Cancer and Cancer Cell Collective Galvanotaxis

Cancer growth interferes with local ionic environments, membrane potentials, and transepithelial potentials, resulting in small electrical changes in the tumor microenvironment. Electrical fields (EFs) have significant effects on cancer cell migration (galvanotaxis/electrotaxis), however, their role as a regulator of cancer progression and metastasis is poorly understood. Here, we employed unique probe systems to characterize the electrical properties of cancer cells and their migratory ability under an EF. Subcutaneous tumors were established from a triple-negative murine breast cancer cell line (4T1), electric currents and potentials of tumors were measured using vibrating probe and glass microelectrodes, respectively. Steady outward and inward currents could be detected at different positions on the tumor surface and magnitudes of the electric currents on the tumor surface strongly correlated with tumor weights. Potential measurements also showed the non-homogeneous intratumor electric potentials. Cancer cell migration was then surveyed in the presence of EFs in vitro. Parental 4T1 cells and metastatic sublines in isolation showed random migration in EFs of physiological strength, whereas cells in monolayer migrated collectively to the anode. Our data contribute to an improved understanding of breast cancer metastasis, providing new evidence in support of an electrical mechanism that promotes this phenomenon.

Neoadjuvant exemestane or exemestane plus docetaxel and cyclophosphamide tailored by clinicopathological response to 12 weeks' exemestane exposure in patients with estrogen receptor-positive breast cancer: A multicenter, open-label, phase II study

Our aim was to investigate the efficacy and safety of initial neoadjuvant endocrine therapy with exemestane alone followed by tailored treatment, either continued exemestane monotherapy or exemestane plus docetaxel–cyclophosphamide (TC) combination therapy, in postmenopausal patients with primary invasive estrogen receptor–positive, human epidermal growth factor receptor 2–negative, stage I‐IIIA breast cancer and Ki67 labeling index ≤30%. In this open‐label phase II study, patients initially received exemestane 25 mg/d for 12 weeks. Responders were defined as patients who achieved complete response (CR), partial response (PR) with Ki67 labeling index ≤5% after treatment, or stable disease with Ki67 labeling index ≤5% both before and after treatment. For the subsequent 12 weeks, exemestane monotherapy was continued for responders (group A), whereas nonresponders received exemestane plus four cycles of TC (docetaxel 75 mg/m² and cyclophosphamide 600 mg/m² every 3 weeks) (group B). Clinical response rate (ie the proportion of patients with CR or PR) at 24 weeks was the primary endpoint. Of 64 patients provisionally enrolled between December 2010 and May 2016, 58 (median age 60 years) started the study treatment. Five patients discontinued treatment in the initial exemestane monotherapy period, and 39 completed the study treatment. Clinical response rates at 8‐12 and 24 weeks were 71% (10/14, 95% confidence interval [CI] 41.9%‐91.6%) and 57% (8/14, 95% CI 28.9%‐82.3%), respectively, in group A, and 16% (4/25, 95% CI 4.5%‐36.1%) and 56% (14/25, 95% CI 34.9%‐75.6%), respectively, in group B. Grade ≥3 adverse events were reported in 8% (1/15) and 53% (20/38) in group A and group B, respectively. The tailored treatment maintained the favorable clinical response to exemestane alone in responders and improved clinical response in nonresponders.

Trial number

UMIN000004752 (UMIN Clinical Trials Registry).

The relationship between tumour size, nodal status and distant metastases: on the origins of breast cancer

Background

In patients with breast cancer, increasing tumour size at diagnosis is associated with an increased likelihood of axillary lymph node involvement and increased breast cancer-specific mortality. However, this relation is based on studies which combine all tumours smaller than 1.0 cm in a single category and all tumours larger than 5.0 cm in another category. This coarse classification may obscure a nuanced description of the effects of tumour size across the full range of possible sizes.

Methods

We examined the relationship between primary tumour size, lymph node status and distant metastases in a cohort of 819,647 women diagnosed with first primary invasive breast cancer from 1990 to 2014 in the Surveillance, Epidemiology and End Results (SEER) registries database. All patients in the cohort had a known primary tumour size between 1 and 150 mm in greatest dimension. Primary tumour size was examined as a continuous (1–150 mm) and categorical variable (15 size groups; 10-mm intervals). For each 1- or 10-mm size group, we determined the proportion of patients with positive lymph nodes at diagnosis, the proportion of patients with distant metastases at diagnosis and the actuarial cumulative risk of breast cancer-specific mortality at 15 years from diagnosis.

Results

Among 819,647 patients with invasive breast tumours between 1 and 150 mm in size, there was a non-linear correlation between increasing tumour size and the prevalence of lymph node metastases at diagnosis (% node-positive), the prevalence of distant metastases at diagnosis (% stage IV) and the 15-year rate of breast cancer-specific mortality across the entire size spectrum. For very small tumours (under 10 mm) and for very large tumours (larger than 60–90 mm) there was little correlation between tumour size and metastasis risk.

Conclusions

The relationship between tumour size, lymph node status and distant metastases in patients with invasive breast cancer is not linear. This calls into question the conventional model that the capacity for a primary breast tumour to metastasize increases as the tumour enlarges.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-4796-9) contains supplementary material, which is available to authorized users.

3D Breast Image Registration — A Review

Image registration is an important problem in breast imaging. It is used in a wide variety of applications that include better visualization of lesions on pre- and post-contrast breast MRI images, speckle tracking and image compounding in breast ultrasound images, alignment of positron emission, and standard mammography images on hybrid machines et cetera. It is a prerequisite to align images taken at different times to isolate small interval lesions. Image registration also has useful applications in monitoring cancer therapy. The field of breast image registration has gained considerable interest in recent years. While the primary focus of interest continues to be the registration of pre- and post-contrast breast MRI images, other areas like breast ultrasound registration have gained more attention in recent years. The focus of registration algorithms has also shifted from control point based semiautomated techniques, to more sophisticated voxel based automated techniques that use mutual information as a similarity measure. This paper visits the problem of breast image registration and provides an overview of the current state-of-the-art in this area.

An Artificial Immune System-Based Support Vector Machine Approach for Classifying Ultrasound Breast Tumor Images

A rapid and highly accurate diagnostic tool for distinguishing benign tumors from malignant ones is required owing to the high incidence of breast cancer. Although various computer-aided diagnosis (CAD) systems have been developed to interpret ultrasound images of breast tumors, feature selection and the setting of parameters are still essential to classification accuracy and the minimization of computational complexity. This work develops a highly accurate CAD system that is based on a support vector machine (SVM) and the artificial immune system (AIS) algorithm for evaluating breast tumors. Experiments demonstrate that the accuracy of the proposed CAD system for classifying breast tumors is 96.67%. The sensitivity, specificity, PPV, and NPV of the proposed CAD system are 96.67, 96.67, 95.60, and 97.48%, respectively. The receiver operator characteristic (ROC) area index A z is 0.9827. Hence, the proposed CAD system can reduce the number of biopsies and yield useful results that assist physicians in diagnosing breast tumors.

Image fusion of Ultrasound Computer Tomography volumes with X-ray mammograms using a biomechanical model based 2D/3D registration

Ultrasound Computer Tomography (USCT) is a promising breast imaging modality under development. Comparison to a standard method like mammography is essential for further development. Due to significant differences in image dimensionality and compression state of the breast, correlating USCT images and X-ray mammograms is challenging. In this paper we present a 2D/3D registration method to improve the spatial correspondence and allow direct comparison of the images. It is based on biomechanical modeling of the breast and simulation of the mammographic compression. We investigate the effect of including patient-specific material parameters estimated automatically from USCT images. The method was systematically evaluated using numerical phantoms and in-vivo data. The average registration accuracy using the automated registration was 11.9mm. Based on the registered images a method for analysis of the diagnostic value of the USCT images was developed and initially applied to analyze sound speed and attenuation images based on X-ray mammograms as ground truth. Combining sound speed and attenuation allows differentiating lesions from surrounding tissue. Overlaying this information on mammograms, combines quantitative and morphological information for multimodal diagnosis.

Classification of breast tumors using sonographic texture analysis

OBJECTIVES

The purpose of this study was to evaluate a computer-aided diagnostic system with texture analysis to improve radiologists' accuracy in identification of breast tumors as malignant or benign.

METHODS

The database included 20 benign and 12 malignant tumors. We extracted 300 statistical texture features as descriptors for each selected region of interest in 3 normalization schemes (default, μ - 3σ, and μ + 3σ, where μ and σ were the mean value and standard deviation, respectively, of the gray-level intensity and 1%-99%). Then features determined by the Fisher coefficient and the lowest probability of classification error + average correlation coefficient yielded the 10 best and most effective features. We analyzed these features under 2 standardization states (standard and nonstandard). For texture analysis of the breast tumors, we applied principle component, linear discriminant, and nonlinear discriminant analyses. First-nearest neighbor classification was performed for the features resulting from the principle component and linear discriminant analyses. Nonlinear discriminant analysis features were classified by an artificial neural network. Receiver operating characteristic curve analysis was used for examining the performance of the texture analysis methods.

RESULTS

Standard feature parameters extracted by the Fisher coefficient under the default and 3σ normalization schemes via nonlinear discriminant analysis showed high performance for discrimination between benign and malignant tumors, with sensitivity of 94.28%, specificity of 100%, accuracy of 97.80%, and an area under the receiver operating characteristic curve of 0.9714.

CONCLUSIONS

Texture analysis is a reliable method and has the potential to be used effectively for classification of benign and malignant tumors on breast sonography.

Small breast lesion classification performance using the normalized axial-shear strain area feature

Breast cancers that are found and confirmed because they are causing symptoms tend to be larger and are more likely to have already spread to the lymph nodes and beyond. Thus, early detection and confirmation are of paramount importance. The normalized axial-shear strain area (NASSA) feature from the axial-shear strain elastogram (ASSE) has been shown to be a feature that can identify the boundary-bonding conditions that are indicative of the presence of cancer. Recently, we investigated and reported on the potential of the NASSA feature for breast lesion classification into fibroadenomas and cancers. In this article, we investigate the size distribution of the lesions that were part of the previous study and analyze classification performance specifically on small lesions (<10 mm diameter). A total of 33 biopsy-proven malignant tumors and 30 fibroadenomas were part of the study that involved three observers blinded to the Breast Imaging Reporting and Data System (BIRADS) ultrasound scores. The observers outlined the lesions on the sonograms and the lesion size (maximum circle-equivalent diameter in millimeters) was computed from this outline. The ASSE was automatically segmented and color-overlaid on the sonogram, and the NASSA feature from ASSE was computed semi-automatically. Receiver operating characteristic curves were then generated for the subset of cases involving small lesions. Box plots were produced for the two different lesion size groups, small and large, from a logistic regression classifier that was built previously. The results of our study show that approximately 38% and 22% of the fibroadenomas and cancers, respectively, were small. Furthermore, it was found that the NASSA feature resulted in a perfect classification of the small lesions, both in the training data and in the cross-validation. For lesions <10 mm the difference in fibroadenoma and cancer mean scores was 0.73 ± 0.13 (p < 0.001), whereas lesions >10 mm had a difference of 0.52 ± 0.24 (p < 0.001). The results also showed that the small lesions actually had better classification than the larger lesions (>10 mm). These results suggest that the ASSE feature can work equally well, even on small lesions, to improve the standard ultrasound BIRADS-based breast lesion classification of fibroadenoma and malignant tumors.

Clinical value of radiofrequency ultrasonic local estimators in classifying breast lesions

OBJECTIVES

We sought to summarize the features of radiofrequency ultrasonic local estimator (RULES) images of benign and malignant masses and to explore the diagnostic value of RULES scores to identify breast lumps.

METHODS

A total of 81 women with a mean age ± SD of 41.33 ± 12.03 years (range, 19-68 years) with 82 lesions seen at our hospital were included in this study. Inclusion criteria were Breast Imaging Reporting and Data System grade 2 to 5 breast lesions, preoperative 2-dimensional (2D) ultrasound (US) examinations and RULES image acquisition, no treatment before the US examinations, surgical resection in our hospital, and histopathologic results. Each RULES characteristic was scored on the basis of expected values for malignant characteristics, and this RULES scoring system was assessed by a receiver operating characteristic curve.

RESULTS

Of the 82 lesions, 45 were benign, and 37 were malignant. Malignancy was associated with multiple colors, red as the main color, colors distributed in 3 or more locations, aggregated colors, and more than half of the area filled with colors. A RULES score of 7 had the highest sum of sensitivity (67.6%) and specificity (95.6%) and the highest accuracy (82.9%) for diagnosis of malignancy. When 2D US imaging a Breast Imaging Reporting and Data System category of 4 was combined with a RULES score of 4 to detect breast cancer, the sensitivity was 83.8%; the specificity was 93.3%; and the accuracy increased to 89.0%.

CONCLUSIONS

The use of RULES images and characteristics is helpful in differentiating benign and malignant breast lesions. Diagnostic accuracy can be improved by combining 2D US imaging and RULES.

Classification of breast computed tomography data

Differences in breast tissue composition are important determinants in assessing risk, identifying disease in images and following changes over time. This paper presents an algorithm for tissue classification that separates breast tissue into its three primary constituents of skin, fat and glandular tissue. We have designed and built a dedicated breast CT scanner. Fifty-five normal volunteers and patients with mammographically identified breast lesions were scanned. Breast CT voxel data were filtered using a 5 pt median filter and the image histogram was computed. A two compartment Gaussian fit of histogram data was used to provide an initial estimate of tissue compartments. After histogram analysis, data were input to region-growing algorithms and classified as to belonging to skin, fat or gland based on their value and architectural features. Once tissues were classified, a more detailed analysis of glandular tissue patterns and a more quantitative analysis of breast composition was made. Algorithm performance assessment demonstrated very good or excellent agreement between algorithm and radiologist observers in 97.7% of the segmented data. We observed that even in dense breasts the fraction of glandular tissue seldom exceeded 50%. For most individuals the composition is better characterized as being a 70% (fat)-30% (gland) composition than a 50% (fat)-50% (gland) composition.

Breast cancer cell-targeted oxidative stress: enhancement of cancer cell uptake of conjugated linoleic acid, activation of p53, and inhibition of proliferation

We investigated the mechanism of inhibition of cell proliferation by mixed isomers of CLA (9-cis, 11-trans CLA; 10-trans, 12-cis CLA) on human, non-tumorigenic MCF10A cells that were derived from mammary ductal epithelial cells and MCF7 cells that were derived from a well differentiation mammary adenocarcinoma. When treated in the log phase of growth, the uptake of CLA by MCF7 exceeded the levels measured in MCF10A cells. Treatment with CLA in the presence of HPO doubled the incorporation of CLA in MCF7 cells, independent of the isomer, but reduced the incorporation of CLA by MCF10A cells. CLA caused tumor cell-targeted increased expression of 4-hydroxy-2-nonenal (4HNE), a product of lipid peroxidation, and decreased proliferation in MCF7 cells, as measured by the incorporation of bromodeoxyuridine (BrdU) and expression of phosphorylated histone H3, and the effects of CLA in combination with HPO on mitosis were greater than the effects of either agent alone. Decreased cell proliferation in CLA-treated MCF7 cells coincided with increased nuclear localization of phosphorylated, activated p53 protein, and decreased nuclear localization of the transcription factor FKHRSer256. Importantly, CLA-treated MCF7 cells were more sensitive than MCF10A cells to HPO-induced 4HNE, expression of p53, and decreased mitotic activity. These studies suggest that tumor cell-targeted increased sensitivity to oxidative stress and activation of p53 play important roles in the regulation of human breast cancer cell proliferation by CLA.

Quantitative target sizes for breast tumor detection prior to metastasis: a prerequisite to rational design of 4D scanners for breast screening

It is important to determine a breast cancer tumor target size for new screening equipment and molecular detection. Records of women aged 40-69 years diagnosed in 1988-1997 with a nonmetastasized, node-negative, or node-positive T1-stage breast cancer were abstracted from the Surveillance, Epidemiology, and End Results (SEER) public-use database. The linear, Gompertzian, lognormal, and power-exponential models of the effect of tumor size on breast cancer specific mortality were compared using corresponding transforms of size in multivariate Cox proportional hazard models. Criteria for comparison were the linearization of the size transforms and the Nagelkerke R2N index for the Cox models. Our results show that the assumption of a linear effect of tumor size was rejected by the linearity test (P=0.05). The Gompertzian, lognormal, and power-exponential transforms satisfied the test with P-values of 0.08, 0.29, and 0.14, respectively. The corresponding R2N were 0.08410, 0.08420, and 0.08414, respectively, showing a marginally best fit with the lognormal model, which was selected as a model for small tumors. The lognormal function with unadjusted crude death rates gave a lognormal-location parameter of 25 and shape parameter of 1.7, while the corresponding values in multivariate models were 18 and 2, respectively. The derivation of the lognormal model indicates tumor growth acceleration starting at 3 mm (unadjusted crude data) or 2 mm (multivariate model). The breast cancer tumor target size for screening equipment, whether by imaging or molecular detection, is therefore 2 mm.

Modeling the effect of tumor size in early breast cancer

SUMMARY BACKGROUND DATA

The purpose of this study was to determine the type of relationship between tumor size and mortality in early breast carcinoma.

METHODS

The data was abstracted from 83,686 cases registered in the Surveillance, Epidemiology, and End Results Program of women diagnosed with primary breast carcinoma between 1988 and 1997 presenting with a T1-T2 lesion and no metastasis in whom axillary node dissection was performed: 58,070 women were node-negative (N0) and 25,616 were node-positive (N+). End point was death from any cause. Tumor size was modeled as a continuous variable by proportional hazards using a generalized additive models procedure.

RESULTS

Functionally, a Gompertzian expression exp(-exp(-(size-15)/10)) provided a good fit to the effect of tumor size (in millimeters) on mortality, irrespective of nodal status. Quantitatively, for tumor size between 3 and 50 mm, the increase of crude cumulative death rate (number of observed deaths divided by the number of patients at risk) increased with size from 10% to 25% for N0 and from 20% to 40% for N+.

CONCLUSIONS

The functional relationship of tumor size with mortality is concordant with current knowledge of tumor growth. However, its qualitative and quantitative independence of nodal status is in contradiction with the prevailing concept of sequential disease progression from primary tumor to regional nodes. This argues against the perception that nodal metastases are caused by the primary tumor.

Differentiation of benign and malignant sub-1 cm breast lesions using dynamic contrast enhanced MRI

The purpose of this work is to assess the additional benefit of MRI-based morphology and quantification of contrast enhancement in the differential diagnosis of sub-1cm breast lesions. Forty-three women with suspected breast cancer were examined using X-ray mammography, ultrasound mammography, and MRI. Dynamic contrast imaging was performed and relative enhancement at various time-points was calculated. The dynamic data was also processed using a two-compartment pharmacokinetic model. Radiological interpretation of high-resolution post-contrast images revealed a similar accuracy (69%) compared to X-ray mammography (69%) and ultrasound mammography (67%). The best individual parameter calculated from the dynamic images was found to be the exchange rate constant which revealed a diagnostic accuracy of 0.74 +/- 0.08. When information from the post-contrast images and dynamic data was combined in a logistic regression model a diagnostic accuracy of 0.92 +/- 0.03 was achieved. In conclusion, MR imaging of small breast lesions is feasible and the incorporation of quantitative MR derived parameters is beneficial.

Correlation of tumor volume and surface area with lymph node status in patients with multifocal/multicentric breast carcinoma

BACKGROUND

Multicentric breast carcinomas have a higher frequency of axillary lymph node metastasis than unifocal tumors of similar stage. It remains unclear whether this merely reflects larger tumor volumes or a different biologic behavior. The authors have shown previously that when aggregate tumor diameter are used for staging, unifocal and multifocal tumors have a similar frequency of axillary lymph node metastasis. However, summing diameter overestimates actual tumor volume because volume is proportional to the third power of the diameter. Therefore, the aim of the current study was to reanalyze the relation between size and axillary lymph node status by correcting for tumor volumes and surface areas.

METHODS

Volumes and surface areas of 122 breast tumor specimens with multiple macroscopic nodules (two foci: n = 95; three foci: n = 22; three foci: n = 5) were calculated by approximating the shape of each tumor nodule to an ellipsoid (for volume) or to a prolate spheroid (for area). For comparison, the authors used an internal control series, comprised of 469 macroscopic unifocal tumors. For all patients, multiple assessments of largest tumor size and combined size of all foci were correlated with the status of axillary lymph nodes. The associations between lymph node status, tumor volume or area, and multifocality were modeled using univariate and multivariate logistic regression.

RESULTS

When either the largest or the aggregate tumor volume was used as a size estimate, tumor specimens with multiple nodules had a higher frequency of lymph node involvement compared with unifocal tumors of a similar volume or area. The odds ratio (OR) for having positive lymph nodes was 2.34 for aggregate volume measurement (P < 0.001). Surface area estimates yielded similar results (OR = 2.2, P < 0.001).

CONCLUSIONS

Breast tumors with multiple macroscopic nodules had a different biology, with a propensity to dissemination at smaller tumor volumes (i.e., there was another factor besides volume alone that accounted for the differences in behavior).

Invasive Cancers Detected after Breast Cancer Screening Yielded a Negative Result: Relationship of Mammographic Density to Tumor Prognostic Factors

PURPOSE

To evaluate common breast tumor prognostic characteristics, including estrogen receptor (ER) status, grade, size, and method of detection, in relationship to mammographic density.

MATERIALS AND METHODS

The study involved 121 women who had negative results at both screening mammography and breast physical examination within 17 months before a diagnosis of breast cancer. Mammographic density was classified according to Breast Imaging Reporting and Data System patterns 1 through 4 (where 1 indicates a fatty breast and 4 indicates a dense breast). Axillary nodal status and tumor histologic ER status, histologic grade, size, stage, and method of detection (mammography alone, palpation alone, or both palpation and mammography) were analyzed by density category and tested for statistically significant differences across categories by using analysis of variance.

RESULTS

Statistically significant differences (P <.05) by density category were found for the following variables: ER positivity (15 of 15 tumors in category 1 breasts, 32 of 41 tumors in category 2 breasts, 37 of 49 tumors in category 3 breasts, and eight of 16 tumors in category 4 breasts were ER positive), occurrence of grade 1 tumors (eight, 11, 19, and four tumors in category 1, category 2, category 3, and category 4 breasts, respectively, were grade 1), mean tumor size (11.3, 13.0, 14.7, and 19.7 mm for category 1, category 2, category 3, and category 4 breasts, respectively), detection with mammography alone (13, 31, 36, and four tumors in category 1, category 2, category 3, and category 4 breasts, respectively, were detected with mammography alone), and occurrence of stage I tumors (10, 25, 28, and five tumors in category 1, category 2, category 3, and category 4 breasts, respectively, were stage I).

CONCLUSION

In women with negative results at clinical and mammographic screening within 17 months before breast tumor detection, subsequently diagnosed cancers tend to be ER negative, of higher grade, and larger in size in those with dense tissue patterns than in those with fat patterns.

Texture analysis of lesions in breast ultrasound images

We investigate the use of Haralick's texture features and posterior acoustic attenuation descriptors (PAAD) for the characterization of ultrasound (US) breast lesions. 71 lesions (24 cyst, 21 benign solid mass and 26 malignant solid masses) were manually segmented on two-dimensional breast US images. 28 Haralick's descriptors and two PAAD were evaluated on these segmented lesions. Mean of Sum Average, Range of Sum Entropy and the second PAAD best discriminated cysts from noncysts. Range of Correlation and the second PAAD best discriminated solid malignant from benign lesions. Computerized analysis of breast US images can increase the specificity of breast sonography by providing a better characterization of solid lesions.

Survival from primary breast cancer after routine clinical use of mammography

Clinical trials indicate that mammography provides a substantial breast cancer survival benefit; however, there is a need to demonstrate that this benefit extends to clinical practice and to determine the extent that current reductions in mortality are attributable to regular screening or adjuvant systemic therapy. Mammography was used routinely at our institution across a broad age range, in an era when most patients received no adjuvant systemic therapy. We examined breast cancer survival for a cohort of 678 stage I-III primary invasive breast cancer patients accrued from 1971 to 1990, and followed to 1996; 18% received adjuvant hormonal therapy and 15% received adjuvant chemotherapy. There were 61 women less than 40 years old; 136, 40-49 years; 341, 50-69 years; 140, > or =70 years. Factors available for multivariate investigations were age (years), tumor size (cm), nodal status (N-, Nx, N+), ER (fmol/mg protein), PgR (fmol/mg protein), adjuvant radiotherapy (no, yes), adjuvant hormonal therapy (no, yes), and adjuvant chemotherapy (no, yes). Forward stepwise multivariate regression with log-normal survival analysis was used to examine the effects of these factors on disease-specific survival. Ten-year survival by tumor size was adjusted for the effects of other significant factors. For women less than 40 years of age, 10-year survival at the T1a, T1b, T1c, and T2 cut-points for tumor size is, respectively, 0.77, 0.74, 0.67, 0.44; for 40-49 years it is 0.92, 0.90, 0.85, 0.62; for 50-69 years it is 0.81, 0.79, 0.75, 0.62; for > or =70 years it is 0.84, 0.81, 0.73, 0.44. With routine use of clinical mammography and up to 26 years of follow-up, we found breast cancer survival to be significantly better (p< or = 0.05) for all women with smaller tumors and that survival indicated a change in natural disease history with early detection. The Canadian National Breast Screening Study (NBSS) controls had significantly smaller tumors (p < 0.001) than our patients, which may indicate access to mammography outside of the NBSS that reduced the apparent survival benefit for clinical trial mammography.

Pathologic analysis of tumor size and lymph node status in multifocal/multicentric breast carcinoma

BACKGROUND

For unifocal invasive breast carcinoma, increasing tumor diameter predictably correlates with a greater frequency of lymph node involvement, thereby facilitating treatment decisions. In invasive breast tumors presenting with multiple nodules, however, it is unclear whether tumor size correlates with lymph node dissemination in a similar manner.

METHODS

The authors analyzed a series of 101 invasive breast carcinomas presenting with multiple macroscopically apparent lesions (2 foci: n = 77; 3: n = 20; 4: n = 4). Two different assessments of the tumor size (diameter of largest focus and combined diameter of all the foci) were then correlated with the status of axillary lymph nodes. For comparison with unifocal tumors, the authors used both external and internal control series (the latter consisting of 469 patients from their institution). The associations between lymph node status, tumor size, and multifocality were modeled using univariate and multivariate logistic regression, for each modality of tumor size assessment.

RESULTS

The logistic curves for multifocal and unifocal tumors were significantly different when the largest diameter was used as a tumor size estimate. Multifocal cases had higher frequencies of lymph node involvement than unifocal lesions of similar size category. In a multivariate logistic regression, the odds ratio of positive lymph node status in multifocal versus unifocal cases was 2.8 using largest diameter as a tumor size estimate (P < 0.0001). When the combined diameter assessment was used, however, the regression curve of multifocal cases was similar to that of unifocal cases, and the frequency of lymph node positivity was not significantly different in multifocal versus unifocal cases of the same size (odds ratio, 1.4; P = 0.13).

CONCLUSIONS

The authors' results show that, if aggregate diameters are used, unifocal and multifocal breast carcinomas are similar with respect to frequency of regional lymph node metastasis. Currently used algorithms, which use the diameter of the largest nodule, result in understaging of multifocal breast carcinomas due to underestimation of actual tumor size.

Comparing the performance of mammographic enhancement algorithms: a preference study

OBJECTIVE

The objective of this study was to compare the performance of four image enhancement algorithms on secondarily digitized (i.e., digitized from film) mammograms containing masses and microcalcifications of known pathology in a clinical soft-copy display setting.

MATERIALS AND METHODS

Four different image processing algorithms (adaptive unsharp masking, contrast-limited adaptive histogram equalization, adaptive neighborhood contrast enhancement, and wavelet-based enhancement) were applied to one image of secondarily digitized mammograms of forty cases (10 each of benign and malignant masses and 10 each of benign and malignant microcalcifications). The four enhanced images and the one unenhanced image were displayed randomly across three high-resolution monitors. Four expert mammographers ranked the unenhanced and the four enhanced images from 1 (best) to 5 (worst).

RESULTS

For microcalcifications, the adaptive neighborhood contrast enhancement algorithm was the most preferred in 49% of the interpretations, the wavelet-based enhancement in 28%, and the unenhanced image in 13%. For masses, the unenhanced image was the most preferred in 58% of cases, followed by the unsharp masking algorithm (28%).

CONCLUSION

Appropriate image enhancement improves the visibility of microcalcifications. Among the different algorithms, the adaptive neighborhood contrast enhancement algorithm was preferred most often. For masses, no significant improvement was observed with any of these image processing approaches compared with the unenhanced image. Different image processing approaches may need to be used, depending on the type of lesion. This study has implications for the practice of digital mammography.

Probe with chest shielding for improved breast MRI

The design and construction of an RF coil system for use in MR breast imaging is described. The two-ring, tuned Helmholtz coil, with its axis perpendicular to the chest, surrounds a single pendant breast and is coupled both internally and to the MRI transmitter/receiver by mutual induction. The addition of two symmetrical RF shields minimizes losses in the chest and significantly improves performance. Images obtained from eight healthy volunteers showed that the coil permitted imaging of breasts of diverse size with an in-plane resolution of 0.27 x 0.27 mm and a slice thickness of less than 2 mm at a field strength of 3 T as well as 1.5 T. The use of shields with surface coils in general is advocated as a method for improving signal-to-noise ratio. Magn Reson Med 43:917-920, 2000.

Assessment of tumor size for multifocal primary breast cancer

BACKGROUND

Tumor size affects the choice of surgical procedure and patient prognosis. It is standardly assessed as the largest unidimensional measurement and, for multifocal disease, as the largest size of the largest focus. We examine some different methods of assessing tumor size: the standard method; the sum of the largest sizes for all foci; surface area; and volume.

METHODS

Data for a cohort of 678 primary invasive breast cancer patients accrued from 1971 to 1990 were updated to 1996; there were 571 patients with unifocal disease and 107 patients with multifocal disease. We used step-wise Cox regression to investigate the effects on time to death of the prognostic factors tumor size (estimated in one of the four ways), age, nodal status, ER, PgR, adjuvant radiotherapy, adjuvant hormonal therapy, and adjuvant chemotherapy. We also examined the association between tumor focality and nodal status.

RESULTS

For all patients, tumor size was included in the multivariate model, regardless of estimation method. For patients with multifocal disease, tumor size was included in the final model only when it was estimated as the total surface area (P = .03) or volume (P = .01) of the foci. More multifocal patients were N+ (P = .056).

CONCLUSIONS

For patients with multifocal disease, the significance association with mortality for total surface area or volume may imply a biologic relevance or mode of tumor activity for the foci.