Role of magnetic resonance imaging in evaluating the extent of disease

Can magnetic resonance imaging texture analysis change the breast imaging reporting and data system category of breast lesions?

PURPOSE

This study aimed to reveal magnetic resonance imaging (MRI) texture analysis (TA)'s contribution to categorizing breast lesions according to the Breast Imaging-Reporting and Data System (BI-RADS) lexicon.

METHOD

Two hundred and seventeen women with BI-RADS category 3, 4, and 5 lesions on breast MRI were included in the study. For TA, the region of interest was drawn manually to encompass the entire lesion on the fat-suppressed T2W and the first post-contrast T1W images. To identify the independent predictors of breast cancer, multivariate logistic regression analyses were performed using texture parameters. Estimated benign and malignant groups were formed according to the TA regression model.

RESULTS

Texture parameters extracted from T2WI, including median, gray-level co-occurrence matrix (GLCM) contrast, GLCM correlation, GLCM joint entropy, GLCM sum entropy, and GLCM sum of squares, and parameters extracted from T1WI, including maximum, GLCM contrast, GLCM joint entropy, GLCM sum entropy, were independent predictors of breast cancer. In the estimated new groups according to the TA regression model, 19 (91%) of the benign 4a lesions were downgraded to BI-RADS category 3.

CONCLUSIONS

The addition of quantitative parameters obtained by MRI TA to BI-RADS criteria significantly increased the accuracy rate in differentiating benign and malignant breast lesions. When categorizing BI-RADS 4a lesions, the use of MRI TA in addition to conventional imaging findings may reduce unnecessary biopsy rates.

[MRI-Guided Breast Intervention: Biopsy and Needle Localization]

In Korea, the number of institutions providing breast MRI, as well as the number of breast MRIs, has recently increased. However, MRI-guided procedures, including biopsy and needle localization, are rarely performed compared to ultrasound-guided or stereotactic biopsy. As breast MRI has high sensitivity but limited specificity, lesions detected only on MRI require pathologic confirmation through MRI-guided biopsy or surgical excision with MRI-guided needle localization. Thus, we aimed to review MRI-guided procedures, including their indications, techniques, procedural considerations, and limitations.

Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1

Breast cancer is one of the most pervasive forms of cancer and its inherent intra- and inter-tumor heterogeneity contributes towards its poor prognosis. Multiple studies have reported results from either private institutional data or publicly available datasets. However, current public datasets are limited in terms of having consistency in: a) data quality, b) quality of expert annotation of pathology, and c) availability of baseline results from computational algorithms. To address these limitations, here we propose the enhancement of the I-SPY1 data collection, with uniformly curated data, tumor annotations, and quantitative imaging features. Specifically, the proposed dataset includes a) uniformly processed scans that are harmonized to match intensity and spatial characteristics, facilitating immediate use in computational studies, b) computationally-generated and manually-revised expert annotations of tumor regions, as well as c) a comprehensive set of quantitative imaging (also known as radiomic) features corresponding to the tumor regions. This collection describes our contribution towards repeatable, reproducible, and comparative quantitative studies leading to new predictive, prognostic, and diagnostic assessments.

Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence

PURPOSE

Identifying imaging phenotypes and understanding their relationship with prognostic markers and patient outcomes can allow for a noninvasive assessment of cancer. The purpose of this study was to identify and validate intrinsic imaging phenotypes of breast cancer heterogeneity in preoperative breast dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) scans and evaluate their prognostic performance in predicting 10 years recurrence.

EXPERIMENTAL DESIGN

Pretreatment DCE-MRI scans of 95 women with primary invasive breast cancer with at least 10 years of follow-up from a clinical trial at our institution (2002-2006) were retrospectively analyzed. For each woman, a signal enhancement ratio (SER) map was generated for the entire segmented primary lesion volume from which 60 radiomic features of texture and morphology were extracted. Intrinsic phenotypes of tumor heterogeneity were identified via unsupervised hierarchical clustering of the extracted features. An independent sample of 163 women diagnosed with primary invasive breast cancer (2002-2006), publicly available via The Cancer Imaging Archive, was used to validate phenotype reproducibility.

RESULTS

Three significant phenotypes of low, medium, and high heterogeneity were identified in the discovery cohort and reproduced in the validation cohort (P < 0.01). Kaplan-Meier curves showed statistically significant differences (P < 0.05) in recurrence-free survival (RFS) across phenotypes. Radiomic phenotypes demonstrated added prognostic value (c = 0.73) predicting RFS.

CONCLUSIONS

Intrinsic imaging phenotypes of breast cancer tumor heterogeneity at primary diagnosis can predict 10-year recurrence. The independent and additional prognostic value of imaging heterogeneity phenotypes suggests that radiomic phenotypes can provide a noninvasive characterization of tumor heterogeneity to augment personalized prognosis and treatment.

Role of texture analysis in breast MRI as a cancer biomarker: A review

Breast cancer is a known heterogeneous disease. Current clinically utilized histopathologic biomarkers may undersample tumor heterogeneity, resulting in higher rates of misdiagnosis for breast cancer. MRI can provide a whole-tumor sampling of disease burden and is widely utilized in clinical care. Texture analysis can provide a localized description of breast cancer, with particular emphasis on quantifying breast lesion heterogeneity. The object of this review is to provide an overview of texture analysis applications towards breast cancer diagnosis, prognosis, and treatment response evaluation and review the role of image-based texture features as noninvasive prognostic and predictive biomarkers. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:927-938.

Incidental hepatic lesions detected on breast MRI: Rate of malignancy and implications for utilization

OBJECTIVE

The objective of this study was to determine the rate of malignancy in incidentally detected T2 hyperintense hepatic lesions at breast MRI.

METHODS

Incidental hepatic lesions identified during breast MRI, for which abdominal imaging was recommended, were retrospectively analyzed.

RESULTS

Of the hepatic lesions, 97.3% were benign, and 2.7% were malignant, with a significant association between indication for the breast MRI and the malignancy status of the hepatic lesion (Fisher's Exact, P < 0.0142).

CONCLUSION

Our initial experience suggests the benign nature of incidentally detected T2 hyperintense hepatic lesions at breast MRI in women without a newly diagnosed breast cancer.

False-positive Extra-Mammary Findings in Breast MRI: Another Cause for Concern

Breast magnetic resonance imaging (MRI) has been repeatedly shown to have a high false-positive rate for additional findings in the breast resulting in additional breast imaging and biopsies. We hypothesize that breast MRI is also associated with a high rate of false-positive findings outside of the breast requiring additional evaluation, interventions, and delays in treatment. We performed a retrospective review of all breast MRIs performed on breast cancer patients in 2010 at a single institution. MRI reports were analyzed for extra-mammary findings. The timing and yield of the additional procedures was also analyzed. Three hundred and twenty-seven breast cancer patients (average age = 53.53 ± 11.08 years) had a breast MRI. Incidental, extra-mammary findings were reported in 35/327 patients (10.7%) with a total of 38 incidental findings. The extra-mammary findings were located in the liver (n = 21, 60.0%), thoracic cavity (n = 12, 34.3%), kidneys (n = 1, 2.9%), musculoskeletal system (n = 3, 8.6%), and neck (n = 1, 2.9%). Eighteen of the 35 patients (51.4%) received additional radiographic imaging, 3 (8.6%) received additional laboratory testing, 2 (5.7%) received additional physician referrals and 2 (5.7%) received a biopsy of the finding. The average time to additional procedures in these patients was 14.5 days. None of the incidental, extra-mammary findings were associated with breast cancer or other malignancy. Breast MRI was associated with a high rate (10.7%) of extra-mammary findings, which led to costly additional imaging studies, referrals, and tests. These findings were not associated with breast cancer or other malignancies. Extra-mammary findings highlight an unrecognized adverse consequence of breast MRI.

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.

(1)H MR spectroscopy with external reference solution at 1.5 T for differentiating malignant and benign breast lesions: comparison using qualitative and quantitative approaches

OBJECTIVE

To compare the diagnostic capability of proton ((1)H) magnetic resonance spectroscopy (MRS) in differentiating benign from malignant breast lesions on the basis of qualitative and quantitative approaches.

METHODS

We performed single-voxel (1)H MRS for 208 breast lesions, identified a clear total composite choline compounds (tCho) peak of signal-to-noise of ≥2 to represent malignancy (qualitative approach), and regarded tCho concentration equal to or greater than the cut-off value to represent malignancy (quantitative approach). We compared the diagnostic ability of both approaches using the Akaike information criterion (AIC) and McFadden's R (2).

RESULTS

Histologically, 169 lesions were malignant; 39 were benign. The qualitative approach demonstrated 84.6 % sensitivity and 51.3 % specificity for differentiating malignant and benign lesions. The mean tCho concentration was 1.13 mmol/kg for malignancy, 0.43 mmol/kg for benignity. The optimal cut-off point was 0.61 mmol/kg, use of which achieved 68.1 % sensitivity and 79.4 % specificity. Calculated AIC and R (2) score suggested the superiority of the quantitative approach for differentiating malignancy.

CONCLUSIONS

Quantitative MRS provides higher specificity than qualitative MRS for differentiating malignant from benign lesions and could be more useful as an additional examination in routine breast MR imaging.

Extra-mammary findings in breast MRI

OBJECTIVES

Incidental extra-mammary findings in breast Magnetic Resonance Imaging (MRI) may be benign in nature, but may also represent a metastasis or another important lesion. We aimed to analyse the prevalence and clinical relevance of these unexpected findings.

METHODS

A retrospective review of 1535 breast MRIs was conducted. Only axial sequences were reassessed. Confirmation examinations were obtained in all cases.

RESULTS

285 patients had a confirmed incidental finding, which were located in the liver (51.9%), lung (11.2%), bone (7%), mediastinal lymph nodes (4.2%) or consisted of pleural/pericardial effusion (15.4%). 20.4% of incidental findings were confirmed to be malignant. Positive predictive value for MRI to detect a metastatic lesion was high if located within the bone (89%), lymph nodes (83%) and lung (59%), while it was low if located within the liver (9%) or if it consisted of pleural/pericardial effusion (6%). The axial enhanced sequence showed superior sensitivity to unenhanced images in detecting metastatic lesions, especially if only smaller (≤10 mm.) lesions were considered.

CONCLUSIONS

The prevalence of metastatic incidental extra-mammary findings is not negligible. Particular attention should be to incidental findings located within the lung, bone and mediastinal lymph nodes.