Radiomic models based on magnetic resonance imaging predict the spatial distribution of CD8+ tumor-infiltrating lymphocytes in breast cancer.

Infiltration of CD8+ T cells and their spatial contexture, represented by immunophenotype, predict the prognosis and therapeutic response in breast cancer. However, a non-surgical method using radiomics to evaluate breast cancer immunophenotype has not been explored. Here, we assessed the CD8+ T cell-based immunophenotype in patients with breast cancer undergoing upfront surgery (n = 182). We extracted radiomic features from the four phases of dynamic contrast-enhanced magnetic resonance imaging, and randomly divided the patients into training (n = 137) and validation (n = 45) cohorts. For predicting the immunophenotypes, radiomic models (RMs) that combined the four phases demonstrated superior performance to those derived from a single phase. For discriminating the inflamed tumor from the non-inflamed tumor, the feature-based combination model from the whole tumor (RM-wholeFC) showed high performance in both training (area under the receiver operating characteristic curve [AUC] = 0.973) and validation cohorts (AUC = 0.985). Similarly, the feature-based combination model from the peripheral tumor (RM-periFC) discriminated between immune-desert and excluded tumors with high performance in both training (AUC = 0.993) and validation cohorts (AUC = 0.984). Both RM-wholeFC and RM-periFC demonstrated good to excellent performance for every molecular subtype. Furthermore, in patients who underwent neoadjuvant chemotherapy (n = 64), pre-treatment images showed that tumors exhibiting complete response to neoadjuvant chemotherapy had significantly higher scores from RM-wholeFC and lower scores from RM-periFC. Our RMs predicted the immunophenotype of breast cancer based on the spatial distribution of CD8+ T cells with high accuracy. This approach can be used to stratify patients non-invasively based on the status of the tumor-immune microenvironment.

Malignancy risk of thyroid nodules with nonshadowing echogenic foci.

PURPOSE: This study was conducted to determine the malignancy risk and diagnostic value of various types of nonshadowing echogenic foci (NEF) in the risk stratification of thyroid nodules. METHODS: A total of 1,018 consecutive thyroid nodules (≥1 cm) with final diagnoses were included. The presence of NEF was determined and types of NEF were classified according to the presence of a comet tail artifact (CTA), location, and size through a prospective evaluation. The associations with malignancy, malignancy risk, and diagnostic value of various types of NEF were assessed. RESULTS: Intrasolid punctate NEF without CTA was the only type of NEF that was an independent predictor of malignancy (P<0.001). The malignancy risk of intrasolid punctate NEF without CTA was substantially higher in solid hypoechoic nodules than in isoechoic or nonsolid nodules (71.3% vs. 9.2%, P<0.001). In solid hypoechoic nodules, slightly increased sensitivity (70.8% vs. 67.9%) for malignancy and a similar malignancy risk (71.4% vs. 71.3%) were observed for intrasolid punctate NEF (with or without CTA) and intrasolid punctate NEF without CTA, respectively. NEF with CTA at the margin of the cystic component was not associated with malignancy or benignity in nonsolid nodules (P>0.05). CONCLUSION: Intrasolid punctate NEF without CTA was the only independent predictor of malignancy. However, solid hypoechoic nodules with intrasolid punctate NEF should be classified as high-suspicion nodules regardless of coexisting CTA. Other types of NEF had no added value for detecting malignancy compared to intrasolid punctate NEF without CTA.

Shear-wave elastography in thyroid ultrasound: Can be a predictor of extrathyroidal extension and cervical lymph node metastasis in papillary thyroid carcinoma?

ABSTRACT: This study aimed to investigate whether extrathyroidal extension (ETE) and cervical lymph node metastasis (LNM) can be predicted using elasticity parameters of shear-wave elastography (SWE) combined with B-mode ultrasound (US) of papillary thyroid carcinomas (PTCs).We retrospectively reviewed 111 patients who underwent preoperative SWE evaluation among PTC patients from July 1, 2016 to June 20, 2018. Patients were divided into 2 groups based on the presence or absence of ETE based on pathology reports. Univariate and multivariate analyses of clinical and radiologic features including B-mode US features, US patterns, and SWE parameters were performed. These analyses were repeated in LNM positive and negative groups. The diagnostic performance of SWE parameters were also evaluated.Of the 111 patients, 33 had ETE, 78 did not have ETE, 44 had LNM, and 67 did not have LNM. A taller-than-wide shape and T3 stage on US were associated with ETE. Female sex, total thyroidectomy, and T3 stage on US were associated with LNM. When B-mode US and SWE were combined, there was no improvement in diagnostic performance.Combination of SWE and B-mode US findings is not useful for predicting ETE and LNM status in PTC patients.

Diagnosis of thyroid nodules on ultrasonography by a deep convolutional neural network.

The purpose of this study was to evaluate and compare the diagnostic performances of the deep convolutional neural network (CNN) and expert radiologists for differentiating thyroid nodules on ultrasonography (US), and to validate the results in multicenter data sets. This multicenter retrospective study collected 15,375 US images of thyroid nodules for algorithm development (n = 13,560, Severance Hospital, SH training set), the internal test (n = 634, SH test set), and the external test (n = 781, Samsung Medical Center, SMC set; n = 200, CHA Bundang Medical Center, CBMC set; n = 200, Kyung Hee University Hospital, KUH set). Two individual CNNs and two classification ensembles (CNNE1 and CNNE2) were tested to differentiate malignant and benign thyroid nodules. CNNs demonstrated high area under the curves (AUCs) to diagnose malignant thyroid nodules (0.898-0.937 for the internal test set and 0.821-0.885 for the external test sets). AUC was significantly higher for CNNE2 than radiologists in the SH test set (0.932 vs. 0.840, P < 0.001). AUC was not significantly different between CNNE2 and radiologists in the external test sets (P = 0.113, 0.126, and 0.690). CNN showed diagnostic performances comparable to expert radiologists for differentiating thyroid nodules on US in both the internal and external test sets.

Diagnostic Performance of a Combination of Shear Wave Elastography and B-Mode Ultrasonography in Differentiating Benign From Malignant Thyroid Nodules.

OBJECTIVES: This study was conducted to compare clinicopathologic and radiologic factors between benign and malignant thyroid nodules and to evaluate the diagnostic performance of shear wave elastography (SWE) combined with B-mode ultrasonography (US) in differentiating malignant from benign thyroid nodules. METHODS: This retrospective study included 92 consecutive patients with 95 thyroid nodules examined on B-mode US and SWE before US-guided fine-needle aspiration biopsy or surgical excision. B-mode US findings (composition, echogenicity, margin, shape, and calcification) and SWE elasticity parameters (maximum [Emax], mean, minimum, and nodule-to-normal parenchymal ratio of elasticity) were reviewed and compared between benign and malignant thyroid nodules. The diagnostic performance of B-mode US and SWE for predicting malignant thyroid nodules was analyzed. The optimal cutoff values of elasticity parameters for identifying malignancy were determined. Diagnostic performance was compared between B-mode US only, SWE only, and the combination of B-mode US with SWE. RESULTS: On multivariate logistic regression analysis, age (odds ratio [OR], 0.90; P=0.028), a taller-than-wide shape (OR, 11.3; P=0.040), the presence of calcifications (OR, 15.0; P=0.021), and Emax (OR, 1.22; P=0.021) were independent predictors of malignancy in thyroid nodules. The combined use of B-mode US findings and SWE yielded improvements in sensitivity, the positive predictive value, the negative predictive value, and accuracy compared with the use of B-mode US findings only, but with no statistical significance. CONCLUSION: When SWE was combined with B-mode US, the diagnostic performance was better than when only B-mode US was used, although the difference was not statistically significant.

Comparison of Diagnostic Performance of B-Mode Ultrasonography and Shear Wave Elastography in Cervical Lymph Nodes.

The purpose of this study was to compare the diagnostic performance of B-mode ultrasonography (US) and shear wave elastography (SWE) for differentiating benign from malignant cervical lymph nodes (LNs). This study evaluated 130 cervical LNs in 127 patients. On conventional B-mode US, short-axis and long-axis diameters, long-to-short-axis ratio, cortical morphology, border, and presence of necrosis or calcification were evaluated. Maximum elasticity value (Emax) was collected for SWE. The area under the receiver operator characteristic curve (AUC), sensitivity, and specificity of B-mode US features and SWE were compared. Final histopathologic results showed 89 benign and 41 metastatic LNs. Among the B-mode US features, cortical morphology had the highest AUC (0.884). When 54 kPa of Emax was applied as a cutoff value, the SWE showed significantly lower AUC than cortical morphology (0.734, P = 0.02). Both sensitivity and specificity for cortical morphology on B-mode US were higher than for Emax (80.5% vs 65.9%, P = 0.212 and 89.9% vs 76.4%, P = 0.026, respectively). Conventional B-mode US resulted in higher diagnostic yield than SWE in evaluating cervical LNs in our study. However, further studies on potential factors that may affect the SWE velocity are needed to validate the diagnostic value of SWE.

Shear wave elastography for the diagnosis of small (≤2 cm) breast lesions: added value and factors associated with false results.

OBJECTIVE: We compared the diagnostic performance of B-mode ultrasound, shear wave elastography (SWE), and combined B-mode ultrasound and SWE in small breast lesions (≤ 2 cm), and evaluated the factors associated with false SWE results. METHODS: A total of 428 small breast lesions (≤ 2 cm) of 415 consecutive patients between August 2013 and February 2017 were included. The diagnostic performance of each set was evaluated using the area under the receiver operating characteristic curve (AUC) analysis. Histologic diagnosis was used as reference standard. Multivariate logistic regression analyses identified the factors associated with false SWE results. RESULTS: Of 428 lesions, 142 (33.2%) were malignant and 286 (66.8%) were benign. The AUC of the combined modality was higher than that of B-mode ultrasound (0.792 vs 0.572, p < 0.001) and that of SWE was higher than that of B-mode ultrasound (0.718 vs 0.572, p < 0.001). Multivariate analysis showed that the smaller lesion size and in situ cancer were associated with false negative, and patient's age, high-risk lesion, shorter distance from the skin or chest wall, and deeper breast thickness were associated with false positive (all p < 0.05). CONCLUSIONS: The addition of SWE to B-mode ultrasound could improve the diagnostic performance in ≤ 2 cm lesions. However, ultrasound lesion size, pathology, and lesion location are likely to affect the SWE value and result in false results. ADVANCES IN KNOWLEDGE: Despite the diagnostic usefulness of SWE in small breast lesions (≤ 2 cm), ultrasound lesion size, pathology, and lesion location were associated with false results.

Ultrasonographic features associated with false-negative and false-positive results of extrathyroidal extensions in papillary thyroid microcarcinoma.

PURPOSE: To assess the ultrasonographic features affect accuracy of extrathyroid extension (ETE) evaluation on preoperative ultrasonography (US) in papillary thyroid microcarcinoma (PTMC). METHODS: Of the total patients who underwent thyroid surgery, 516 patients with a tumor measuring less than 1 cm on preoperative US were enrolled in this study. One blinded head and neck radiologist reviewed the preoperative US images to evaluate the US features of PTMC, and the pathologic reports were reviewed. The diagnostic accuracy rates, including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, were calculated, and the factors associated with false-negative and false-positive results for ETE were analyzed. RESULTS: The sensitivity, specificity, PPV, NPV, and accuracy for predicting ETE according to sonographic criteria were 32.8%, 87.5%, 51.0%, 76.6%, and 71.7%, respectively. Non-adjacent to the trachea and unilateral lesion on US were significant factors associated with false-negative results. CONCLUSION: Size, shape, and location of PTMC on US are important factors that affect the US results in ETE evaluation.

Diagnostic performances of shear-wave elastography and B-mode ultrasound to differentiate benign and malignant breast lesions: the emphasis on the cutoff value of qualitative and quantitative parameters.

PURPOSE: To investigate the most effective cutoff values for shear-wave elastography (SWE) for differentiating benign and malignant breast lesions and to evaluate the diagnostic performance of quantitative and qualitative SWE in combination with B-mode ultrasound (US). METHODS: 209 breast lesions from 200 patients were evaluated with B-mode US and SWE. Pathologic results determined by US-guided core needle biopsy or surgical excisions were used as a reference standard. Qualitative (four-color pattern) and quantitative analyses (Emean, Emax, SD, and E ratio) were performed. The cut-off values were defined using Youden's index. The diagnostic performance of B-mode US and combination of B-mode US with four-color pattern or quantitative parameters were compared. RESULTS: Of the 209 breast lesions, 102 were benign and 107 were malignant. All qualitative and quantitative SWE parameters had significantly higher specificity, positive predictive value (PPV), and accuracy compared to B-mode US (p < 0.001). The optimal cutoff values for the Emax, Emean, SD and E ratio were 145.7 kPa, 89.1 kPa, 11.9, and 3.84, respectively. The optimal cutoff for color pattern was between 3 and 4. Combined B-mode US and Emax had the highest improvement, from 17.65% to 98.04% for specificity and from 58.85% to 82.78% for accuracy, with a decrease in sensitivity compared with B-mode. CONCLUSION: Quantitative and qualitative SWE combined with B-mode US improved the accuracy to differentiate benign from malignant lesions. Emax (cutoff, 145.7 kPa) appeared to be the most discriminatory parameter.

Differentiation of benign and metastatic axillary lymph nodes in breast cancer: additive value of shear wave elastography to B-mode ultrasound.

OBJECTIVES: The purpose of this study is to evaluate the additive value of shear wave elastography (SWE) for differentiating benign and metastatic axillary lymph nodes (LNs) in breast cancer. MATERIALS AND METHODS: The area under the receiver operating characteristic curve, sensitivity, and specificity of B-mode US, SWE, and combined modality were compared for 54 suspicious LNs. RESULTS: After combining information from SWE, sensitivity was significantly higher for combined modality than for B-mode US alone (94.12% vs. 82.35%, p = 0.046) without a decrease in specificity. CONCLUSION: Combined B-mode US and SWE may improve detection of metastatic axillary LNs in patients with breast cancer.

Tumor stiffness measured by quantitative and qualitative shear wave elastography of breast cancer.

OBJECTIVE: To correlate clinicoradiologic and pathological features of breast cancer with quantitative and qualitative shear wave elastographic parameters. METHODS: 82 breast cancers in 75 patients examined by B-mode ultrasound and shear wave elastography (SWE) were included. SWE parameters including quantitative factors [maximum elasticity (Emax), mean elasticity (Emean), elasticity ratio (Eratio) and standard deviation (SD)] and qualitative factor (color pattern) were correlated with clinicoradiologic and pathological features using univariate and multivariate linear regression analyses. RESULTS: Presence of symptoms and larger tumor size on ultrasound were significantly associated with higher Emax, Emean, Eratio, and SD (all p < 0.05) on univariate analysis. Older age was significantly correlated with higher Emax and Emean (p = 0.026, 0.018). Lymphovascular invasion and larger pathologic size were significantly associated with higher Emax (p = 0.036, 0.043) and SD (p < 0.001, 0.019). No immunohistochemical biomarkers were significantly correlated with SWE parameters. There was no significant correlation between color pattern and any variable. Multivariate logistic regression analysis showed that the symptom, tumor size on ultrasound and lymphovascular invasion were independent factors that influenced the SWE values. CONCLUSION: Tumor stiffness as measured by SWE and B-mode ultrasound could help predict cancer prognosis. Advances in knowledge: Clinicoradiologic factors had correlation with quantitative and qualitative SWE parameters. Using SWE parameters and B-mode ultrasound, we can predict breast cancer prognosis.

Breast lesions diagnosed by ultrasound-guided core needle biopsy: Can shearwave elastography predict histologic upgrade after surgery or vaccuum assisted excision?

PURPOSE: To compare breast stiffness based on shear-wave elastography (SWE) quantitative parameters with histopathologic results diagnosed by ultrasound (US)-guided core needle biopsy (CNB) to determine their association with upgrade rates after surgical excision or follow-up US as well as clinico-radiologic differences between upgrade and non-upgrade groups. MATERIALS AND METHODS: This retrospective study enrolled 225 breast lesions from 225 patients, including 159 benign lesions, 38 high risk lesions and 28 ductal carcinoma in situ (DCIS) diagnosed by US-guided CNB. Quantitative SWE parameters of breast lesions were measured before CNB and compared according to histopathologic results (benign, high risk and DCIS) and lesion size (<20 mm and >20 mm). Clinico-radiologic and pathologic factors were compared between upgrade and non-upgrade groups after surgical excision or follow-up US. RESULTS: After surgical excision or follow-up US after more than one year, 29 lesions were upgraded for an overall upgrade rate of 12.9% (29/225). There were significant differences between upgrade and non-upgrade groups in age, mammographic category, US category, and sonographic features, including shape, margin, orientation, imaging-histologic correlation and E ratio. Patients with lesion upgrade were much older and had lesions characterized by significantly higher mammographic and US category (>4b), irregular shape, nonparallel orientation, microlobulated or angular margin, calcification in a mass, larger size on US (>20 mm) and greater imaging-histologic discordance. Multivariate analysis showed only mean and minimum elasticity values displayed a borderline association with histologic underestimation. CONCLUSION: Upgrade of breast lesions diagnosed by US-guided CNB can be predicted using Emean and Emin among quantitative SWE parameters.

Applying Data-driven Imaging Biomarker in Mammography for Breast Cancer Screening: Preliminary Study.

We assessed the feasibility of a data-driven imaging biomarker based on weakly supervised learning (DIB; an imaging biomarker derived from large-scale medical image data with deep learning technology) in mammography (DIB-MG). A total of 29,107 digital mammograms from five institutions (4,339 cancer cases and 24,768 normal cases) were included. After matching patients' age, breast density, and equipment, 1,238 and 1,238 cases were chosen as validation and test sets, respectively, and the remainder were used for training. The core algorithm of DIB-MG is a deep convolutional neural network; a deep learning algorithm specialized for images. Each sample (case) is an exam composed of 4-view images (RCC, RMLO, LCC, and LMLO). For each case in a training set, the cancer probability inferred from DIB-MG is compared with the per-case ground-truth label. Then the model parameters in DIB-MG are updated based on the error between the prediction and the ground-truth. At the operating point (threshold) of 0.5, sensitivity was 75.6% and 76.1% when specificity was 90.2% and 88.5%, and AUC was 0.903 and 0.906 for the validation and test sets, respectively. This research showed the potential of DIB-MG as a screening tool for breast cancer.

Comparison and Combination of Strain and Shear Wave Elastography of Breast Masses for Differentiation of Benign and Malignant Lesions by Quantitative Assessment: Preliminary Study.

OBJECTIVES: To compare the diagnostic performance of strain and shear wave elastography of breast masses for quantitative assessment in differentiating benign and malignant lesions and to evaluate the diagnostic accuracy of combined strain and shear wave elastography. METHODS: Between January and February 2016, 37 women with 45 breast masses underwent both strain and shear wave ultrasound (US) elastographic examinations. The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) final assessment on B-mode US imaging was assessed. We calculated strain ratios for strain elastography and the mean elasticity value and elasticity ratio of the lesion to fat for shear wave elastography. Diagnostic performances were compared by using the area under the receiver operating characteristic curve (AUC). RESULTS: The 37 women had a mean age of 47.4 years (range, 20-79 years). Of the 45 lesions, 20 were malignant, and 25 were benign. The AUCs for elasticity values on strain and shear wave elastography showed no significant differences (strain ratio, 0.929; mean elasticity, 0.898; and elasticity ratio, 0.868; P > .05). After selectively downgrading BI-RADS category 4a lesions based on strain and shear wave elastographic cutoffs, the AUCs for the combined sets of B-mode US and elastography were improved (B-mode + strain, 0.940; B-mode + shear wave; 0.964; and B-mode, 0.724; P < .001). Combined strain and shear wave elastography showed significantly higher diagnostic accuracy than each individual elastographic modality (P = .031). CONCLUSIONS: These preliminary results showed that strain and shear wave elastography had similar diagnostic performance. The addition of strain and shear wave elastography to B-mode US improved diagnostic performance. The combination of strain and shear wave elastography results in a higher diagnostic yield than each individual elastographic modality.

Preoperative Axillary Lymph Node Evaluation in Breast Cancer: Current Issues and Literature Review.

Axillary lymph node (ALN) status is an important prognostic factor for overall breast cancer survival. In current clinical practice, ALN status is evaluated before surgery via multimodal imaging and physical examination. Mammography is typically suboptimal for complete ALN evaluation. Currently, ultrasonography is widely used to evaluate ALN status; nonetheless, results may vary according to operator. Ultrasonography is the primary imaging modality for evaluating ALN status. Other imaging modalities including contrast-enhanced magnetic resonance imaging, computed tomography, and positron emission tomography/computed tomography can play additional roles in axillary nodal staging.The purpose of this article is (1) to review the strengths and weaknesses of current imaging modalities for nodal staging in breast cancer patients and (2) to discuss updated guidelines for ALN management with regard to preoperative ALN imaging.

Incidentally Found Postoperative Spindle Cell Nodule of the Breast 6 Months After Ultrasound-Guided Vacuum-Assisted Excision.

Postoperative spindle cell nodule (PSCN) is a very rare pathologic complication that can occur in association with a recent core needle biopsy, surgery, or trauma. Cases of PSCN have been reported in the lower genitourinary tract, endometrium, and thyroid but are rare in the breast. Herein, we report an ultrasound-guided biopsy-proven PSCN after ultrasound-guided vacuum-assisted excision in the breast.

Estimation of T2* Relaxation Time of Breast Cancer: Correlation with Clinical, Imaging and Pathological Features.

OBJECTIVE: The purpose of this study was to estimate the T2* relaxation time in breast cancer, and to evaluate the association between the T2* value with clinical-imaging-pathological features of breast cancer. MATERIALS AND METHODS: Between January 2011 and July 2013, 107 consecutive women with 107 breast cancers underwent multi-echo T2*-weighted imaging on a 3T clinical magnetic resonance imaging system. The Student's t test and one-way analysis of variance were used to compare the T2* values of cancer for different groups, based on the clinical-imaging-pathological features. In addition, multiple linear regression analysis was performed to find independent predictive factors associated with the T2* values. RESULTS: Of the 107 breast cancers, 92 were invasive and 15 were ductal carcinoma in situ (DCIS). The mean T2* value of invasive cancers was significantly longer than that of DCIS (p = 0.029). Signal intensity on T2-weighted imaging (T2WI) and histologic grade of invasive breast cancers showed significant correlation with T2* relaxation time in univariate and multivariate analysis. Breast cancer groups with higher signal intensity on T2WI showed longer T2* relaxation time (p = 0.005). Cancer groups with higher histologic grade showed longer T2* relaxation time (p = 0.017). CONCLUSION: The T2* value is significantly longer in invasive cancer than in DCIS. In invasive cancers, T2* relaxation time is significantly longer in higher histologic grades and high signal intensity on T2WI. Based on these preliminary data, quantitative T2* mapping has the potential to be useful in the characterization of breast cancer.

Risk Stratification For Axillary Lymph Node Metastases in Breast Cancer Patients: What Clinicopathological and Radiological Factors of Primary Breast Cancer Can Predict Preoperatively Axillary Lymph Node Metastases?

This study was to investigate clinicopathological features including immunohistochemical subtype and radiological factors of primary breast cancer to predict axillary lymph node metastasis (ALNM) and preoperative risk stratification.From June 2004 to May 2014, 369 breast cancer patients (mean age, 54.7 years; range, 29-82 years) who underwent surgical axillary node sampling were included. Two radiologists retrospectively reviewed clinicopathological features, initial mammography, and initial breast ultrasonography (US). Univariate and multivariate logistic regression analyses were used to evaluate associations between ALNM and variables. Odds ratio with 95% confidence interval and risk of ALNM were calculated.Among 369 patients, 117 (31.7%) had ALNM and 252 (68.3%) had no ALNM revealed surgically. On multivariate analysis, four factors showed positive association with ALNM: the presence of symptoms (P < 0.001), triple-negative breast cancer subtype (P = 0.001), mass size on US (>10 mm, P < 0.001), and Breast Imaging Reporting and Data System category on US (≥4c, P < 0.001). The significant risk of ALNM was particularly seen in patients with two or more factors (2, P = 0.013; 3, P < 0.001; 4, P < 0.001).The estimated risks of ALNM increased in patients with two, three, and four factors with odds ratios of 5.5, 14.3, and 60.0, respectively.The presence of symptoms, triple-negative breast cancer subtype, larger size mass on US (>10 mm), and higher Breast Imaging Reporting and Data System category on US (≥4c) were positively associated with ALNM. Radiologically, US findings are significant factors that can affect the decision making process regarding ALNM. Based on risk stratification, the possibility of ALNM can be better predicted if 2 or more associated factors existed preoperatively.

Immunohistochemical Subtypes of Breast Cancer: Correlation with Clinicopathological and Radiological Factors.

BACKGROUND: The relationship between biomarkers and imaging features is important because imaging findings can predict molecular features. OBJECTIVES: To investigate the relationship between clinicopathologic and radiologic factors and the immunohistochemical (IHC) profiles associated with breast cancer. PATIENTS AND METHODS: From December 2004 to September 2013, 200 patients (mean age, 56 years; range, 29 - 82 years) were diagnosed with breast cancer and underwent surgery at our institution. Their medical records were reviewed to determine age, symptom presence, mammographic findings (including mass, asymmetry, microcalcifications, or negativity), sonographic Breast Imaging-Reporting and Data System (BI-RADS) category, pathologic type of cancer (invasive ductal, mucinous, medullary, or papillary carcinoma), histologic grade, T-stage, and IHC subtypes. Based on the IHC profiles, tumor subtypes were classified as luminal A, luminal B, human epidermal growth factor receptor 2 (HER2) enriched, or triple-negative (TN) cancers. Using univariate and multivariate logistic regression analyses, we looked for correlations between four IHC subtypes and two IHC subtypes (TN and non-triple negative [non-TN]) and clinicopathologic and radiologic factors, respectively. RESULTS: Based on our univariate analyses with the four subtypes, the TN subtype showed a higher incidence of masses on mammography compared to the other subtypes (P = 0.037), and the TN subtype also tended to have the highest histologic grade among the subtypes (P < 0.001). With regard to the two IHC subtypes, the TN subtype had a significant association with medullary cancer (P = 0.021), higher histologic grade (grade 3; P < 0.001), and higher T stage (T2; P = 0.027) compared to the non-TN subtypes. In a multivariate logistic regression analysis of the clinicoradiologic factors compared to luminal A, the HER2 subtype had a significant association with BI-RADS category 4b (odds ratio [OR], 9.005; 95% confidence interval [CI], 1.414 - 57.348; P = 0.020) and borderline significance with category 4c (OR, 4.669; 95% CI, 0.970 - 22.468; P = 0.055). In a multivariate logistic regression analysis of the clinicoradiologic factors associated with the non-TN subtypes, the TN subtype was significantly correlated with medullary carcinoma (OR, 7.092; 95% CI, 1.149 - 43.772; P = 0.035). CONCLUSION: These results suggest that patients with the TN subtypes are more likely to have higher-histologic-grade tumors and medullary cancer. The HER2 subtype was typically associated with a higher BI-RADS category.

False-negative results of breast MR computer-aided evaluation in patients with breast cancer: correlation with clinicopathologic and radiologic factors.

PURPOSE: To investigate clinicopathologic and radiologic factors associated with false-negative results of magnetic resonance computer aided evaluation (MR-CAE) of breast MR imaging (MRI) in breast cancer patients. MATERIALS AND METHODS: A total of 135 breast cancer patients who underwent preoperative breast MR-CAE were included. False-negative and true-positive MR-CAE results were compared in terms of clinicopathologic and radiologic features. Univariate and multivariate analyses were used to evaluate independent factors associated with false-negative results. RESULT: Six of 135 cancer patients (4.4%) were false negative on MRI. CONCLUSION: Breast cancer with false-negative results on MR-CAE was classified as a lower BI-RADS category on breast ultrasound than true-positive results on MR-CAE.