Molecular characterization of breast cancer needle core biopsy specimens by the 21-gene Breast Recurrence Score test.

BACKGROUND AND OBJECTIVE: Recent COVID-19 pandemic guidelines recommend genomic assessment of core biopsies to help guide treatment decisions in estrogen receptor (ER)-positive early-stage breast cancer. Herein we characterize biopsy and excisional breast cancer specimens submitted for 21-gene testing. METHODS: US samples submitted to Genomic Health for 21-gene testing (01/2004-04/2020) were assessed by pathologists and analyzed by a standardized quantitative reverse transcription-polymerase chain reaction. Predefined cutoffs were: ESR1 (positive ≥6.5), PGR (positive ≥5.5), and ERBB2 (negative <10.7). ER status by immunohistochemistry (IHC) and lymph node status were determined locally. Median and interquartile range were reported for continuous variables, and total and percent for categorical variables. Distributions were assessed overall, by age, and by nodal involvement. RESULTS: Of 919 701 samples analyzed, 13% were biopsies and 87% were excisions. Initial assay success rates were 94.5% (biopsies) and 97.3% (excisions). ER IHC concordance with central ESR1 was 96.8% (biopsies) and 97.6% (excisions). Biopsy and excisional medians were: Recurrence Score results 16 (each); ESR1 10.2 (each); PGR 7.7 and 7.6; ERBB2 9.4 and 9.2, respectively. CONCLUSIONS: Biopsy submissions for 21-gene testing are common and consistently generate results that are very similar to the experience with excisions. The 21-gene test can be performed reliably on core biopsies.

Association between breast cancer genetic susceptibility variants and terminal duct lobular unit involution of the breast.

Terminal duct lobular units (TDLUs) are the predominant source of future breast cancers, and lack of TDLU involution (higher TDLU counts, higher acini count per TDLU and the product of the two) is a breast cancer risk factor. Numerous breast cancer susceptibility single nucleotide polymorphisms (SNPs) have been identified, but whether they are associated with TDLU involution is unknown. In a pooled analysis of 872 women from two studies, we investigated 62 established breast cancer SNPs and relationships with TDLU involution. Poisson regression models with robust variance were used to calculate adjusted per-allele relative risks (with the non-breast cancer risk allele as the referent) and 95% confidence intervals between TDLU measures and each SNP. All statistical tests were two-sided; P < 0.05 was considered statistically significant. Overall, 36 SNPs (58.1%) were related to higher TDLU counts although this was not statistically significant (p = 0.25). Six of the 62 SNPs (9.7%) were nominally associated with at least one TDLU measure: rs616488 (PEX14), rs11242675 (FOXQ1) and rs6001930 (MKL1) were associated with higher TDLU count (p = 0.047, 0.045 and 0.031, respectively); rs1353747 (PDE4D) and rs6472903 (8q21.11) were associated with higher acini count per TDLU (p = 0.007 and 0.027, respectively); and rs1353747 (PDE4D) and rs204247 (RANBP9) were associated with the product of TDLU and acini counts (p = 0.024 and 0.017, respectively). Our findings suggest breast cancer SNPs may not strongly influence TDLU involution. Agnostic genome-wide association studies of TDLU involution may provide new insights on its biologic underpinnings and breast cancer susceptibility.

Comparison of residual cancer burden, American Joint Committee on Cancer staging and pathologic complete response in breast cancer after neoadjuvant chemotherapy: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657).

PURPOSE: Several pathologic staging systems characterize residual tumor in patients undergoing neoadjuvant chemotherapy for breast cancer. Pathologic complete response (pCR) is now accepted by the Food and Drug Administration as an endpoint for granting accelerated drug approval. Two other systems of post-neoadjuvant pathologic tumor staging-residual cancer burden (RCB) and the American Joint Committee on Cancer post-neoadjuvant therapy staging system (yAJCC)-have been developed to characterize residual tumors when patients do not achieve pCR. The optimal system and the ways in which these systems complement each other have not been fully determined. METHODS: Using data from the I-SPY 1 TRIAL, we compared pCR, RCB, and yAJCC as predictors of early recurrence-free survival (RFS) to identify ways to improve post-neoadjuvant pathologic evaluation. RESULTS: Among 162 patients assessed, pCR identified patients at lowest risk of recurrence, while RCB and yAJCC identified patients at highest risk. Hormone-receptor (HR) and HER2 subtypes further improved risk prediction. Recursive partitioning indicated that triple-negative or HER2+ patients with yAJCC III or RCB 3 have the highest recurrence risk, with an RFS of 27%. Our analysis also highlighted discrepancies between RCB and yAJCC stratification: 31% of patients had discrepant RCB and yAJCC scores. We identified differential treatment of lymph node involvement and tumor cellularity as drivers of these discrepancies. CONCLUSIONS: These data indicate that there is benefit to reporting both RCB and yAJCC for patients in order to identify those at highest risk of relapse.

Ages at menarche- and menopause-related genetic variants in relation to terminal duct lobular unit involution in normal breast tissue.

Reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have been associated with higher breast cancer risk. Younger age at menarche and older age at menopause have been previously related to lower levels of TDLU involution. To determine a possible genetic link, we examined whether single-nucleotide polymorphisms (SNPs) previously established in genome-wide association studies (GWAS) for ages at menarche and menopause are associated with TDLU involution. We conducted a pooled analysis of 862 women from two studies. H&E tissue sections were assessed for numbers of TDLUs and acini/TDLU. Poisson regression models were used to estimate associations of 36 menarche- and 21 menopause-SNPs with TDLU counts, acini counts/TDLU, and the product of these two measures, adjusting for age and study site. Fourteen percent of evaluated SNPs (eight SNPs) were associated with TDLU counts at p < 0.05, suggesting an enrichment of associations with TDLU counts. However, only menopause-SNPs had >50 % that were either significantly or nonsignificantly associated with TDLU measures in the directions consistent with their relationships shown in GWAS. Among ten SNPs that were statistically significantly associated with at least one TDLU involution measure (p < 0.05), seven SNPs (rs466639: RXRG; rs2243803: SLC14A2; rs2292573: GAB2; rs6438424: 3q13.32; rs7606918: METAP1D; rs11668344: TMEM150B; rs1635501: EXO1) were associated in the consistent directions. Our data suggest that the loci associated with ages at menarche and menopause may influence TDLU involution, suggesting some shared genetic mechanisms. However, larger studies are needed to confirm the results.

Feasibility of the internal mammary lymph node flap as a vascularized lymph node transfer: A cadaveric dissection study.

BACKGROUND: We performed cadaveric dissections to examine the feasibility of an internal mammary-based lymph node flap as a donor site for vascularized lymph node transfer. METHODS: Internal mammary vessels and adjacent nodes were dissected in ten fresh cadaver specimens. Surgeon inspection and palpation identified the number of nodes in the specimen. Specimens were examined macro- and microscopically by a pathologist for correlation of lymph node counts. Kappa statistic correlated surgeon- and pathologist-reported node counts. RESULTS: Surgeon- and pathologist-reported node counts were moderately correlated (kappa 0.57). Inspection and palpation correctly predicted node presence or absence in 80% of specimens. Sixty percent of flaps contained between 1 and 3 nodes, with a mean of 2.0 nodes when nodes were present. CONCLUSIONS: Inspection and palpation predicts the presence or absence of nodes in 80% of flaps. Nodes were present in 60% of internal mammary-based flaps, and one to three nodes can be transferred. © 2015 Wiley Periodicals, Inc. Microsurgery 36:485-490, 2016.

Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles.

PURPOSE: To present a method for identifying intrinsic imaging phenotypes in breast cancer tumors and to investigate their association with prognostic gene expression profiles. MATERIALS AND METHODS: The authors retrospectively analyzed dynamic contrast material-enhanced (DCE) magnetic resonance (MR) images of the breast in 56 women (mean age, 55.6 years; age range, 37-74 years) diagnosed with estrogen receptor-positive breast cancer between 2005 and 2010. The study was approved by the institutional review board and compliant with HIPAA. The requirement to obtain informed consent was waived. Primary tumors were assayed with a validated gene expression assay that provides a score for the likelihood of recurrence. A multiparametric imaging phenotype vector was extracted for each tumor by using quantitative morphologic, kinetic, and spatial heterogeneity features. Multivariate linear regression was performed to test associations between DCE MR imaging features and recurrence likelihood. To identify intrinsic imaging phenotypes, hierarchical clustering was performed on the extracted feature vectors. Multivariate logistic regression was used to classify tumors at high versus low or medium risk of recurrence. To determine the additional value of intrinsic phenotypes, the phenotype category was tested as an additional variable. Receiver operating characteristic analysis and the area under the receiver operating characteristic curve (Az) were used to assess classification performance. RESULTS: There was a moderate correlation (r = 0.71, R(2) = 0.50, P < .001) between DCE MR imaging features and the recurrence score. DCE MR imaging features were predictive of recurrence risk as determined by the surrogate assay, with an Az of 0.77 (P < .01). Four dominant imaging phenotypes were detected, with two including only low- and medium-risk tumors. When the phenotype category was used as an additional variable, the Az increased to 0.82 (P < .01). CONCLUSION: Intrinsic imaging phenotypes exist for breast cancer tumors and correlate with recurrence likelihood as determined with gene expression profiling. These imaging biomarkers could ultimately help guide treatment decisions.

Computerized image analysis for identifying triple-negative breast cancers and differentiating them from other molecular subtypes of breast cancer on dynamic contrast-enhanced MR images: a feasibility study.

PURPOSE: To determine the feasibility of using a computer-aided diagnosis (CAD) system to differentiate among triple-negative breast cancer, estrogen receptor (ER)-positive cancer, human epidermal growth factor receptor type 2 (HER2)-positive cancer, and benign fibroadenoma lesions on dynamic contrast material-enhanced (DCE) magnetic resonance (MR) images. MATERIALS AND METHODS: This is a retrospective study of prospectively acquired breast MR imaging data collected from an institutional review board-approved, HIPAA-compliant study between 2002 and 2007. Written informed consent was obtained from all patients. The authors collected DCE MR images from 65 women with 76 breast lesions who had been recruited into a larger study of breast MR imaging. The women had triple-negative (n = 21), ER-positive (n = 25), HER2-positive (n = 18), or fibroadenoma (n = 12) lesions. All lesions were classified as Breast Imaging Reporting and Data System category 4 or higher on the basis of previous imaging. Images were subject to quantitative feature extraction, feed-forward feature selection by means of linear discriminant analysis, and lesion classification by using a support vector machine classifier. The area under the receiver operating characteristic curve (Az) was calculated for each of five lesion classification tasks involving triple-negative breast cancers. RESULTS: For each pair-wise lesion type comparison, linear discriminant analysis helped identify the most discriminatory features, which in conjunction with a support vector machine classifier yielded an Az of 0.73 (95% confidence interval [CI]: 0.59, 0.87) for triple-negative cancer versus all non-triple-negative lesions, 0.74 (95% CI: 0.60, 0.88) for triple-negative cancer versus ER- and HER2-positive cancer, 0.77 (95% CI: 0.63, 0.91) for triple-negative versus ER-positive cancer, 0.74 (95% CI: 0.58, 0.89) for triple-negative versus HER2-positive cancer, and 0.97 (95% CI: 0.91, 1.00) for triple-negative cancer versus fibroadenoma. CONCLUSION: Triple-negative cancers possess certain characteristic features on DCE MR images that can be captured and quantified with CAD, enabling good discrimination of triple-negative cancers from non-triple-negative cancers, as well as between triple-negative cancers and benign fibroadenomas. Such CAD algorithms may provide added diagnostic benefit in identifying the highly aggressive triple-negative cancer phenotype with DCE MR imaging in high-risk women.

Cutaneous metastatic breast carcinoma with clear cell features.

Breast carcinoma remains one of the most common sources of skin metastases in women. Cutaneous breast carcinoma metastases have variable clinical and histopathologic presentations that can make diagnosis challenging. We report a unique case of metastatic breast carcinoma with prominent clear cell features, thus mimicking a xanthomatous process. Dermatopathologists should be aware of this entity given its resemblance to other clear cell infiltrates and neoplasms.

Intraosseous hibernoma: a potential mimic of metastatic carcinoma.

Intraosseous hibernoma is a rare benign bone tumor, with only 3 cases reported in English literature. In this report, we describe a 50-year-old woman with a history of stage IIB breast cancer and posterolateral right hip pain. Imaging studies showed a sclerotic lesion in the right ilium, which was biopsied and showed mildly thickened bone trabeculae and multivacuolated brown fat cells replacing the normal white fat and hematopoietic elements, diagnostic of intraosseous hibernoma.

Chemotherapy response and recurrence-free survival in neoadjuvant breast cancer depends on biomarker profiles: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657).

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥ 3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group.

Computer aided automatic detection of malignant lesions in diffuse optical mammography.

PURPOSE: Computer aided detection (CAD) data analysis procedures are introduced and applied to derive composite diffuse optical tomography (DOT) signatures of malignancy in human breast tissue. In contrast to previous optical mammography analysis schemes, the new statistical approach utilizes optical property distributions across multiple subjects and across the many voxels of each subject. The methodology is tested in a population of 35 biopsy-confirmed malignant lesions. METHODS: DOT CAD employs multiparameter, multivoxel, multisubject measurements to derive a simple function that transforms DOT images of tissue chromophores and scattering into a probability of malignancy tomogram. The formalism incorporates both intrasubject spatial heterogeneity and intersubject distributions of physiological properties derived from a population of cancercontaining breasts (the training set). A weighted combination of physiological parameters from the training set define a malignancy parameter (M), with the weighting factors optimized by logistic regression to separate training-set cancer voxels from training-set healthy voxels. The utility of M is examined, employing 3D DOT images from an additional subjects (the test set). RESULTS: Initial results confirm that the automated technique can produce tomograms that distinguish healthy from malignant tissue. When compared to a gold standard tissue segmentation, this protocol produced an average true positive rate (sensitivity) of 89% and a true negative rate (specificity) of 94% using an empirically chosen probability threshold. CONCLUSIONS: This study suggests that the automated multisubject, multivoxel, multiparameter statistical analysis of diffuse optical data is potentially quite useful, producing tomograms that distinguish healthy from malignant tissue. This type of data analysis may also prove useful for suppression of image artifacts.

Assessing the significance of conserved genomic aberrations using high resolution genomic microarrays.

Genomic aberrations recurrent in a particular cancer type can be important prognostic markers for tumor progression. Typically in early tumorigenesis, cells incur a breakdown of the DNA replication machinery that results in an accumulation of genomic aberrations in the form of duplications, deletions, translocations, and other genomic alterations. Microarray methods allow for finer mapping of these aberrations than has previously been possible; however, data processing and analysis methods have not taken full advantage of this higher resolution. Attention has primarily been given to analysis on the single sample level, where multiple adjacent probes are necessarily used as replicates for the local region containing their target sequences. However, regions of concordant aberration can be short enough to be detected by only one, or very few, array elements. We describe a method called Multiple Sample Analysis for assessing the significance of concordant genomic aberrations across multiple experiments that does not require a-priori definition of aberration calls for each sample. If there are multiple samples, representing a class, then by exploiting the replication across samples our method can detect concordant aberrations at much higher resolution than can be derived from current single sample approaches. Additionally, this method provides a meaningful approach to addressing population-based questions such as determining important regions for a cancer subtype of interest or determining regions of copy number variation in a population. Multiple Sample Analysis also provides single sample aberration calls in the locations of significant concordance, producing high resolution calls per sample, in concordant regions. The approach is demonstrated on a dataset representing a challenging but important resource: breast tumors that have been formalin-fixed, paraffin-embedded, archived, and subsequently UV-laser capture microdissected and hybridized to two-channel BAC arrays using an amplification protocol. We demonstrate the accurate detection on simulated data, and on real datasets involving known regions of aberration within subtypes of breast cancer at a resolution consistent with that of the array. Similarly, we apply our method to previously published datasets, including a 250K SNP array, and verify known results as well as detect novel regions of concordant aberration. The algorithm has been fully implemented and tested and is freely available as a Java application at http://www.cbil.upenn.edu/MSA.

Polygenic risk score for the prediction of breast cancer is related to lesser terminal duct lobular unit involution of the breast.

Terminal duct lobular units (TDLUs) are the predominant anatomical structures where breast cancers originate. Having lesser degrees of age-related TDLU involution, measured as higher TDLUs counts or more epithelial TDLU substructures (acini), is related to increased breast cancer risk among women with benign breast disease (BBD). We evaluated whether a recently developed polygenic risk score (PRS) based on 313-common variants for breast cancer prediction is related to TDLU involution in the background, normal breast tissue, as this could provide mechanistic clues on the genetic predisposition to breast cancer. Among 1398 women without breast cancer, higher values of the PRS were significantly associated with higher TDLU counts (P = 0.004), but not with acini counts (P = 0.808), in histologically normal tissue samples from donors and diagnostic BBD biopsies. Mediation analysis indicated that TDLU counts may explain a modest proportion (≤10%) of the association of the 313-variant PRS with breast cancer risk. These findings suggest that TDLU involution might be an intermediate step in the association between common genetic variation and breast cancer risk.

Mesothelial Inclusions in Pelvic Lymph Nodes Initially Diagnosed as Metastatic Prostate Cancer; the Utility of Second Opinions and Genomic Testing in the Setting of Unexpected Results.

Benign mesothelial inclusions in pelvic lymph nodes may be mistaken for metastatic disease in the setting of pelvic malignancy. In this case-report a patient with Low-Risk prostate cancer (confirmed by biopsy and genomic testing) underwent radical prostatectomy with pelvic lymph node dissection. The initial pathological diagnosis was organ-confined Gleason 3 + 3 = 6 cancer with metastasis to a pelvic lymph node. Upon review of the pathological specimen and immunohistochemical staining the lymph node tissue concerning for metastatic disease was recharacterized as mesothelial in origin. This case illustrates the importance of second opinions and immunohistochemistry for unexpected or unusual pathological findings.

Lymph node content of supraclavicular and thoracodorsal-based axillary flaps for vascularized lymph node transfer.

OBJECTIVE: Microvascular transfer of lymph node flaps has recently gained popularity as a treatment for secondary lymphedema often occurring after axillary, groin, or pelvic lymph node dissections. This study aimed to delineate the lymph node contents and pedicle characteristics of the supraclavicular (SC) and thoracodorsal (TD)-based axillary flaps as well as to compare lymph node quantification of surgeon vs pathologist. METHODS: SC and TD flaps were dissected from fresh female cadavers. The surgeon assessed pedicle characteristics, lymph node content, and anatomy. A pathologist assessed all flaps for gross and microscopic lymph node contents. The κ statistic was used to compare surgeon and pathologist. RESULTS: Ten SC flaps and 10 TD flaps were harvested and quantified. In comparing the SC and TD flaps, there were no statistical differences between artery diameter (3.1 vs 3.2 mm; P = .75) and vein diameter (2.8 vs 3.5 mm; P = .24). The TD flap did have a significantly longer pedicle than the SC flap (4.2 vs 3.2 cm; P = .03). The TD flap was found to be significantly heavier than the SC flap (17.0 ± 4.8 vs 12.9 ± 3.3 g; P = .04). Gross lymph node quantity was similar in the SC and TD flaps (2.5 ± 1.7 vs 1.8 ± 1.2; P = .33). There was good agreement between the surgeon and pathologist in detecting gross lymph nodes in the flaps (SC κ = 0.87, TD κ = 0.61). CONCLUSIONS: The SC and TD flaps have similar lymph node quantity, but the SC flap has higher lymphatic density. A surgeon's estimation of lymph node quantity is reliable and has been verified in this study by comparison to a pathologist's examination.

Serum concentrations of estrogens, sex hormone binding globulin, and androgens and risk of breast hyperplasia in postmenopausal women.

OBJECTIVE: We sought to determine whether serum concentrations of estrogens, androgens, and sex hormone binding globulin in postmenopausal women were related to the presence of mammary hyperplasia, an established breast cancer risk factor. METHODS: Study participants provided serum before breast biopsy or mastectomy in three hospitals in Grand Rapids, Michigan, between 1977 and 1987. A total of 179 subjects with breast hyperplasia were compared with 152 subjects with nonproliferative breast changes that are not associated with increased breast cancer risk. RESULTS: The odds ratios (OR) associated with the three upper quartiles of estradiol in comparison with the lowest quartile were 2.2 [95% confidence interval (95% CI) 1.1-4.6], 2.5 (95% CI, 1.1-5.3), and 4.1 (95% CI, 2.0-8.5; Ptrend = 0.007). The corresponding ORs for bioavailable estradiol, estrone, and estrone sulfate were of generally similar magnitude (Ptrend = 0.003 for bioavailable estradiol, 0.0004 for estrone, and 0.0009 for estrone sulfate). Relative to women concurrently in the lowest tertile for serum estradiol, estrone, and estrone sulfate, women concurrently in the highest tertile for all three hormones had an OR of 5.8 (95% CI, 2.2-15.2). Serum concentrations of sex hormone binding globulin, testosterone, dehydroepiandrosterone, androstenedione, and androstenediol were not associated with risk of hyperplasia. CONCLUSIONS: Serum concentrations of estrogens, but not of androgens or sex hormone binding globulin, were strongly and significantly associated with risk of breast hyperplasia in postmenopausal women, suggesting that estrogens are important early in the pathologic process towards breast cancer.

Breast DCE-MRI Kinetic Heterogeneity Tumor Markers: Preliminary Associations With Neoadjuvant Chemotherapy Response.

The ability to predict response to neoadjuvant chemotherapy for women diagnosed with breast cancer, either before or early on in treatment, is critical to judicious patient selection and tailoring the treatment regimen. In this paper, we investigate the role of contrast agent kinetic heterogeneity features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting treatment response. We propose a set of kinetic statistic descriptors and present preliminary results showing the discriminatory capacity of the proposed descriptors for predicting complete and non-complete responders as assessed from pre-treatment imaging exams. The study population consisted of 15 participants: 8 complete responders and 7 non-complete responders. Using the proposed kinetic features, we trained a leave-one-out logistic regression classifier that performs with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.84 under the ROC. We compare the predictive value of our features against commonly used MRI features including kinetics of the characteristic kinetic curve (CKC), maximum peak enhancement (MPE), hotspot signal enhancement ratio (SER), and longest tumor diameter that give lower AUCs of 0.71, 0.66, 0.64, and 0.54, respectively. Our proposed kinetic statistics thus outperform the conventional kinetic descriptors as well as the classifier using a combination of all the conventional descriptors (i.e., CKC, MPE, SER, and longest diameter), which gives an AUC of 0.74. These findings suggest that heterogeneity-based DCE-MRI kinetic statistics could serve as potential imaging biomarkers for tumor characterization and could be used to improve candidate patient selection even before the start of the neoadjuvant treatment.

Pharmacokinetic Tumor Heterogeneity as a Prognostic Biomarker for Classifying Breast Cancer Recurrence Risk.

GOAL: Heterogeneity in cancer can affect response to therapy and patient prognosis. Histologic measures have classically been used to measure heterogeneity, although a reliable noninvasive measurement is needed both to establish baseline risk of recurrence and monitor response to treatment. Here, we propose using spatiotemporal wavelet kinetic features from dynamic contrast-enhanced magnetic resonance imaging to quantify intratumor heterogeneity in breast cancer. METHODS: Tumor pixels are first partitioned into homogeneous subregions using pharmacokinetic measures. Heterogeneity wavelet kinetic (HetWave) features are then extracted from these partitions to obtain spatiotemporal patterns of the wavelet coefficients and the contrast agent uptake. The HetWave features are evaluated in terms of their prognostic value using a logistic regression classifier with genetic algorithm wrapper-based feature selection to classify breast cancer recurrence risk as determined by a validated gene expression assay. RESULTS: Receiver operating characteristic analysis and area under the curve (AUC) are computed to assess classifier performance using leave-one-out cross validation. The HetWave features outperform other commonly used features (AUC = 0.88 HetWave versus 0.70 standard features). The combination of HetWave and standard features further increases classifier performance (AUCs 0.94). CONCLUSION: The rate of the spatial frequency pattern over the pharmacokinetic partitions can provide valuable prognostic information. SIGNIFICANCE: HetWave could be a powerful feature extraction approach for characterizing tumor heterogeneity, providing valuable prognostic information.

Breast reconstruction with a transverse rectus abdominis myocutaneous flap: spectrum of normal and abnormal MR imaging findings.

The authors retrospectively reviewed their clinical database for cases of breast magnetic resonance (MR) imaging performed in women who had undergone breast reconstruction with a transverse rectus abdominis myocutaneous (TRAM) flap. Patient histories, MR imaging results, and, when available, biopsy results were reviewed. During a 4-year period, 24 neobreasts were imaged in 22 women who had undergone TRAM flap reconstruction after mastectomy. In most of the cases (64%), the indication for MR imaging was a palpable abnormality or pain. In four of 24 cases (17%), recurrent breast cancer was detected. These cases consisted of a local chest wall tumor (n = 2), an infiltrating chest wall tumor (n = 1), and axillary nodal recurrence (n = 1). In all four cases, MR imaging demonstrated a suspicious lesion or abnormality. In 11 of 24 cases (46%), benign findings only were demonstrated. These consisted of localized or diffuse skin thickening, fibrosis, fat necrosis, and seroma. In nine of 24 cases (38%), no pathologic abnormality was identified. MR imaging is useful in detection of locally recurrent tumor in patients who have undergone breast reconstruction with a TRAM flap. MR imaging allows differentiation between benign and malignant findings in patients with palpable abnormalities or pain after TRAM flap reconstruction.

Opportunities for molecular epidemiological research on ductal carcinoma in-situ and breast carcinogenesis: interdisciplinary approaches.

Most invasive breast cancers arise from ductal carcinoma in-situ (DCIS), a non-obligate precursor of invasive breast cancer. Given that the natural history of individual DCIS lesions is unpredictable, many women with DCIS receive extensive treatments, which may include surgery, radiation and endocrine therapy, even though many of these lesions may have limited potential to progress to invasion and metastasize. In contrast to valid concerns about overtreatment, the fact that invasive breast cancers outnumber DCIS lesions by more than three-to-one, suggests that many cancer precursors (particularly DCIS, but LCIS also) progress to invasion prior to detection. Thus, DCIS poses a dual problem of overdiagnosis among some women and failure of early detection among others. These concerns are heightened by the multifold increase in rates of DCIS in conjunction with widespread use of mammographic screening and access to outpatient radiologically-guided biopsies. Accordingly, methods are needed to both specifically detect and identify DCIS lesions with potential to progress to invasive cancer and to discover techniques to triage and conservatively manage indolent cases of DCIS.