Donna Plecha

Application of Raman Spectroscopy to Identify Microcalcifications and Underlying Breast Lesions at Stereotactic Core Needle Biopsy

Microcalcifications are a feature of diagnostic significance on a mammogram and a target for stereotactic breast needle biopsy. Here, we report development of a Raman spectroscopy technique to simultaneously identify microcalcification status and diagnose the underlying breast lesion, in real-time, during stereotactic core needle biopsy procedures. Raman spectra were obtained ex vivo from 146 tissue sites from fresh stereotactic breast needle biopsy tissue cores from 33 patients, including 50 normal tissue sites, 77 lesions with microcalcifications, and 19 lesions without microcalcifications, using a compact clinical system. The Raman spectra were modeled on the basis of the breast tissue components, and a support vector machine framework was used to develop a single-step diagnostic algorithm to distinguish normal tissue, fibrocystic change (FCC), fibroadenoma, and breast cancer, in the absence and presence of microcalcifications. This algorithm was subjected to leave-one-site-out cross-validation, yielding a positive predictive value, negative predictive value, sensitivity, and specificity of 100%, 95.6%, 62.5%, and 100% for diagnosis of breast cancer (with or without microcalcifications) and an overall accuracy of 82.2% for classification into specific categories of normal tissue, FCC, fibroadenoma, or breast cancer (with and without microcalcifications). Notably, the majority of breast cancers diagnosed are ductal carcinoma in situ (DCIS), the most common lesion associated with microcalcifications, which could not be diagnosed using previous Raman algorithm(s). Our study shows the potential of Raman spectroscopy to concomitantly detect microcalcifications and diagnose associated lesions, including DCIS, and thus provide real-time feedback to radiologists during such biopsy procedures, reducing nondiagnostic and false-negative biopsies.

Raman spectroscopy: a real-time tool for identifying microcalcifications during stereotactic breast core needle biopsies

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. We present here a Raman spectroscopic tool for detecting microcalcifications in breast tissue based on their chemical composition. We collected ex vivo Raman spectra from 159 tissue sites in fresh stereotactic breast needle biopsies from 33 patients, including 54 normal sites, 75 lesions with microcalcifications and 30 lesions without microcalcifications. Application of our Raman technique resulted in a positive predictive value of 97% for detecting microcalcifications. This study shows that Raman spectroscopy has the potential to detect microcalcifications during stereotactic breast core biopsies and provide real-time feedback to radiologists, thus reducing non-diagnostic and false negative biopsies.

18F-FDG PET/CT for Monitoring of Treatment Response in Breast Cancer

Changes in tumor metabolic activity have been shown to be an early indicator of treatment effectiveness for breast cancer, mainly in the neoadjuvant setting. The histopathologic response at the completion of chemotherapy has been used as the reference standard for assessment of the accuracy of 18F-FDG PET in predicting a response during systemic treatment. Although a pathologic complete response (pCR) remains an important positive prognostic factor for an individual patient, a recent metaanalysis could validate pCR as a surrogate marker for patient outcomes only in aggressive breast cancer subtypes. For establishment of the clinical application of metabolic treatment response studies, larger series of specific breast cancer subtypes—including hormone receptor–positive, human epidermal growth factor receptor 2–positive, and triple-negative breast cancers—are necessary. In addition, thresholds for relative changes in 18F-FDG uptake to distinguish between responding and nonresponding tumors need to be validated for different systemic treatment approaches, with progression-free survival and overall survival as references. A PET-based treatment stratification is applicable clinically only if valid alternative therapies are available. Of note, patients who do not achieve a pCR might still benefit from neoadjuvant therapy enabling breast-conserving surgery. In the metastatic setting, residual tumor metabolic activity after the initiation of systemic therapy is an indicator of active disease, whereas a complete resolution of metabolic activity is predictive of a successful treatment response.

Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI

BackgroundIn this study, we evaluated the ability of radiomic textural analysis of intratumoral and peritumoral regions on pretreatment breast cancer dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC).MethodsA total of 117 patients who had received NAC were retrospectively analyzed. Within the intratumoral and peritumoral regions of T1-weighted contrast-enhanced MRI scans, a total of 99 radiomic textural features were computed at multiple phases. Feature selection was used to identify a set of top pCR-associated features from within a training set (n = 78), which were then used to train multiple machine learning classifiers to predict the likelihood of pCR for a given patient. Classifiers were then independently tested on 39 patients. Experiments were repeated separately among hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+, HER2−) and triple-negative or HER2+ (TN/HER2+) tumors via threefold cross-validation to determine whether receptor status-specific analysis could improve classification performance.ResultsAmong all patients, a combined intratumoral and peritumoral radiomic feature set yielded a maximum AUC of 0.78 ± 0.030 within the training set and 0.74 within the independent testing set using a diagonal linear discriminant analysis (DLDA) classifier. Receptor status-specific feature discovery and classification enabled improved prediction of pCR, yielding maximum AUCs of 0.83 ± 0.025 within the HR+, HER2− group using DLDA and 0.93 ± 0.018 within the TN/HER2+ group using a naive Bayes classifier. In HR+, HER2− breast cancers, non-pCR was characterized by elevated peritumoral heterogeneity during initial contrast enhancement. However, TN/HER2+ tumors were best characterized by a speckled enhancement pattern within the peritumoral region of nonresponders. Radiomic features were found to strongly predict pCR independent of choice of classifier, suggesting their robustness as response predictors.ConclusionsThrough a combined intratumoral and peritumoral radiomics approach, we could successfully predict pCR to NAC from pretreatment breast DCE-MRI, both with and without a priori knowledge of receptor status. Further, our findings suggest that the radiomic features most predictive of response vary across different receptor subtypes.

Development and comparative assessment of Raman spectroscopic classification algorithms for lesion discrimination in stereotactic breast biopsies with microcalcifications.

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. Here, we develop and compare different approaches for developing Raman classification algorithms to diagnose invasive and in situ breast cancer, fibrocystic change and fibroadenoma that can be associated with microcalcifications. In this study, Raman spectra were acquired from tissue cores obtained from fresh breast biopsies and analyzed using a constituent-based breast model. Diagnostic algorithms based on the breast model fit coefficients were devised using logistic regression, C4.5 decision tree classification, k-nearest neighbor (k -NN) and support vector machine (SVM) analysis, and subjected to leave-one-out cross validation. The best performing algorithm was based on SVM analysis (with radial basis function), which yielded a positive predictive value of 100% and negative predictive value of 96% for cancer diagnosis. Importantly, these results demonstrate that Raman spectroscopy provides adequate diagnostic information for lesion discrimination even in the presence of microcalcifications, which to the best of our knowledge has not been previously reported.

Neglecting to Screen Women Between the Ages of 40 and 49 Years With Mammography: What Is the Impact on Breast Cancer Diagnosis?

OBJECTIVE The purpose of this study was to compare breast cancer stage at diagnosis in two groups of women between 40 and 49 years old: women undergoing screening mammography and women with a symptom needing diagnostic workup. This comparison is indicative of the impact of forgoing screening in this age group, as recommended by the United States Preventive Services Task Force. MATERIALS AND METHODS A retrospective chart review was used to collect the results of imaging-guided core needle biopsies performed in women between the ages of 40 and 49 years from January 1, 2008, to December 31, 2009. In patients diagnosed with breast cancer or a high-risk lesion, the reason for presentation, pathology, tumor size, stage, and receptor characteristics were recorded. The chi-square test was used for statistical analysis. RESULTS Of 108 primary breast cancers, 71 were detected in the screened group and 37 in the unscreened group. The screened group was significantly more likely to be diagnosed with ductal carcinoma in situ than the unscreened group (22 vs 1, chi-square = 11.6, p = 0.001). Furthermore, screened patients with invasive carcinoma were significantly more likely to be diagnosed at earlier stages (chi-square = 5.02, p = 0.025). The size of invasive breast cancer in the screened group was significantly smaller as well (chi-square = 9.3, p = 0.002). Of the high-risk lesions, atypical ductal hyperplasia (n = 29) and lobular carcinoma in situ (n = 8) were most frequently seen. CONCLUSION Breast cancer patients undergoing screening mammography were diagnosed at earlier stages with smaller tumors. Screening also allows detection of high-risk lesions, which may prompt chemoprevention and lower subsequent breast cancer risk. We continue to support screening mammography in women between the ages of 40 and 49 years.

A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores.

To identify computer extracted imaging features for estrogen receptor (ER)-positive breast cancers on dynamic contrast en-hanced (DCE)-MRI that are correlated with the low and high OncotypeDX risk categories. We collected 96 ER-positivebreast lesions with low (<18, N = 55) and high (>30, N = 41) OncotypeDX recurrence scores. Each lesion was quantitatively charac-terize via 6 shape features, 3 pharmacokinetics, 4 enhancement kinetics, 4 intensity kinetics, 148 textural kinetics, 5 dynamic histogram of oriented gradient (DHoG), and 6 dynamic local binary pattern (DLBP) features. The extracted features were evaluated by a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish low and high OncotypeDX risk categories. Classification performance was evaluated by area under the receiver operator characteristic curve (Az). The DHoG and DLBP achieved Az values of 0.84 and 0.80, respectively. The 6 top features identified via feature selection were subsequently combined with the LDA classifier to yield an Az of 0.87. The correlation analysis showed that DHoG (ρ = 0.85, P < 0.001) and DLBP (ρ = 0.83, P < 0.01) were significantly associated with the low and high risk classifications from the OncotypeDX assay. Our results indicated that computer extracted texture features of DCE-MRI were highly correlated with the high and low OncotypeDX risk categories for ER-positive cancers.

Diagnostic power of diffuse reflectance spectroscopy for targeted detection of breast lesions with microcalcifications

Microcalcifications geographically target the location of abnormalities within the breast and are of critical importance in breast cancer diagnosis. However, despite stereotactic guidance, core needle biopsy fails to retrieve microcalcifications in up to 15% of patients. Here, we introduce an approach based on diffuse reflectance spectroscopy for detection of microcalcifications that focuses on variations in optical absorption stemming from the calcified clusters and the associated cross-linking molecules. In this study, diffuse reflectance spectra are acquired ex vivo from 203 sites in fresh biopsy tissue cores from 23 patients undergoing stereotactic breast needle biopsies. By correlating the spectra with the corresponding radiographic and histologic assessment, we have developed a support vector machine-derived decision algorithm, which shows high diagnostic power (positive predictive value and negative predictive value of 97% and 88%, respectively) for diagnosis of lesions with microcalcifications. We further show that these results are robust and not due to any spurious correlations. We attribute our findings to the presence of proteins (such as elastin), and desmosine and isodesmosine cross-linkers in the microcalcifications. It is important to note that the performance of the diffuse reflectance decision algorithm is comparable to one derived from the corresponding Raman spectra, and the considerably higher intensity of the reflectance signal enables the detection of the targeted lesions in a fraction of the spectral acquisition time. Our findings create a unique landscape for spectroscopic validation of breast core needle biopsy for detection of microcalcifications that can substantially improve the likelihood of an adequate, diagnostic biopsy in the first attempt.

Neglecting to screen women between 40 and 49 years old with mammography: What is the impact on treatment morbidity and potential risk reduction?

OBJECTIVE The purpose of this study is to determine whether there were significant differences with respect to treatment recommendations, stage at diagnosis, and identification of high-risk lesions for women 40-49 years old undergoing screening mammography (screened) compared to women with a symptom needing a diagnostic evaluation (nonscreened). MATERIALS AND METHODS We reviewed the pathology results of all imaging-guided biopsies performed at the three breast center locations of University Hospitals Case Medical Center from January 1, 2008, to December 31, 2011. In patients diagnosed with a high-risk lesion or breast cancer, the reason for presentation, pathology, tumor size, stage, receptor characteristics, and treatment were recorded. The chi-square test was used for statistical analysis. RESULTS Of 230 primary breast cancers, 149 were in the screened group and 81 were considered nonscreened. Nonscreened patients were more likely to undergo chemotherapy (p = 0.042). Eighty-one percent of the high-risk lesions were diagnosed in the screened patients. Screened patients with cancer were significantly more likely to receive a diagnosis at earlier stages (p = 0.001), to have negative axillary lymph nodes (p = 0.005), and to have smaller tumors (p < 0.001). CONCLUSION In addition to the benefits of receiving a diagnosis at earlier stages, with smaller tumors and node negativity, patients with breast cancer undergoing screening mammography aged 40-49 years are less likely to require chemotherapy and its associated morbidities. The majority of high-risk lesions were diagnosed in the screened group, which may lead to the benefit of chemoprevention, lowering their risk of subsequent breast cancer, or screening with MRI, which may diagnose future mammographically occult malignancies.

Precision of Raman spectroscopy measurements in detection of microcalcifications in breast needle biopsies.

Microcalcifications are an early mammographic sign of breast cancer and a target for stereotactic breast needle biopsy. We developed Raman spectroscopy decision algorithms to detect breast microcalcifications, based on fit coefficients (FC) derived by modeling tissue Raman spectra as a linear combination of the Raman spectra of 9 chemical and morphologic components of breast tissue. However, little or no information is available on the precision of such measurements and its effect on the ability of Raman spectroscopy to make predictions for breast microcalcification detection. Here we report the precision, that is, the closeness of agreement between replicate Raman spectral measurements--and the model FC derived from them--obtained ex vivo from fresh breast biopsies from patients undergoing stereotactic breast needle biopsy, using a compact clinical Raman system. The coefficients of variation of the model FC averaged 0.03 for normal breast tissue sites, 0.12 for breast lesions without, and 0.22 for breast lesions with microcalcifications. Imprecision in the FC resulted in diagnostic discordance among replicates only for line-sitters, that is, tissue sites with FC values near the decision line or plane. The source of this imprecision and their implications for the use of Raman spectroscopy for guidance of stereotactic breast biopsies for microcalcifications are also discussed. In summary, we conclude that the precision of Raman spectroscopy measurements in breast tissue obtained using our compact clinical system is more than adequate to make accurate and repeatable predictions of microcalcifications in breast tissue using decision algorithms based on model FC. This provides strong evidence of the potential of Raman spectroscopy guidance of stereotactic breast needle biopsies for microcalcifications.