Abbreviated MR Imaging for Breast Cancer

Analysis of the Value of Quantitative Features in Multimodal MRI Images to Construct a Radio-Omics Model for Breast Cancer Diagnosis

Objective

To analyze the diagnostic value of quantitative features in multimodal magnetic resonance imaging (MRI) images to construct a radio-omics model for breast cancer.

Methods

Ninety-five patients with breast-related diseases from January 2020 to January 2021 were grouped into the benign group (n=57) and malignant group (n=38) according to the pathological findings. All cases were randomized as the training group (n=66) and validation group (n=29) in a 7:3 ratio based on the examination time. All subjects were examined by T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE), and apparent diffusion coefficient (ADC) multimodality MRI. The MRI findings were analyzed against pathological findings. A diagnostic breast cancer radiomics model was constructed. The diagnostic efficacy of the model in the validation group was analyzed, and the diagnostic efficacy was analyzed via the ROC curve.

Results

Fibroadenoma accounted for 49.12% of benign breast diseases, and invasive ductal carcinoma accounted for 73.68% of malignant breast diseases. The sensitivity of T1WI, T2WI, DWI, ADC, and DCE in diagnosing breast cancer was 61.14%, 66.67%, 73.30%, 78.95%, and 85.96%, using the four-fold table method. The area under the curves (AUCs) of T1WI, T2WI, DWI, ADC, and DCE for diagnosing breast cancer were 0.715, 0.769, 0.785, 0.835, and 0.792, respectively. The AUCs of plain scan, diffuse, enhanced, plain scan + diffuse, plain scan + enhanced, enhanced + diffuse, and plain scan + enhanced + diffuse for diagnosing breast cancer were 0.746, 0.798, 0.816, 0.839, 0.890, 0.906, and 0.927, respectively.

Conclusion

The construction of a radio-omics model by quantitative features in multimodal MRI images was valuable in the diagnosis of breast cancer. The value of radio-omics models such as plain scan + enhanced + diffuse was higher than the other models in diagnosing breast cancer and could be widely applied in clinical practice.

Combining Molecular and Radiomic Features for Risk Assessment in Breast Cancer

Breast cancer risk is highly variable within the population and current research is leading the shift toward personalized medicine. By accurately assessing an individual woman's risk, we can reduce the risk of over/undertreatment by preventing unnecessary procedures or by elevating screening procedures. Breast density measured from conventional mammography has been established as one of the most dominant risk factors for breast cancer; however, it is currently limited by its ability to characterize more complex breast parenchymal patterns that have been shown to provide additional information to strengthen cancer risk models. Molecular factors ranging from high penetrance, or high likelihood that a mutation will show signs and symptoms of the disease, to combinations of gene mutations with low penetrance have shown promise for augmenting risk assessment. Although imaging biomarkers and molecular biomarkers have both individually demonstrated improved performance in risk assessment, few studies have evaluated them together. This review aims to highlight the current state of the art in breast cancer risk assessment using imaging and genetic biomarkers.

A three-sequence dynamic contrast enhanced abbreviated MRI protocol to evaluate response to breast cancer neoadjuvant chemotherapy

PURPOSE

To develop an ABP-MRI to evaluate response to NAC for invasive breast carcinoma.

STUDY TYPE

A single-center, cross-sectional study.

SUBJECTS

A consecutive series of 210 women with invasive breast carcinoma who underwent breast MRI after NAC between 2016 and 2020.

FIELD STRENGTH/SEQUENCE

1.5 T / Dynamic contrast-enhanced.

ASSESSMENT

MRI scans were independently reevaluated, with access to dynamic contrast-enhanced without contrast and to the first, second, and third post-contrast time (ABP-MRI 1-3).

STATISTICAL TESTS

The diagnostic performance of the ABP-MRIs and the Full protocol (FP-MRI) were analyzed. The Wilcoxon non-parametric test (p-value <0.050) was used to compare the capability in measuring the most extensive residual lesion.

RESULTS

The median age was 47 (24-80) years. ABP-MRI 1 showed higher specificity (84.6%; 77/91) but a higher probability of false-negatives (16.8%) and lower sensitivity (83.2%; 99/119) than ABP-MRI 2,3 and the FP-MRI, which were identical in specificity (81.3%; 74/91), probability of false-negatives (8.4%), and sensitivity (91.6%; 109/119). ABP-MRI 2 showed a mean underestimation of only 0.03 cm in the measurement of the longest axis of the residual lesion (p = 0.008) with an average reduction in the acquisition time of 75%, compared with the FP-MRI.

CONCLUSION

ABP-MRI 2 showed diagnostic performance equivalent to the FP-MRI with a 75% reduction in the acquisition time.

Correlation Analysis of Pathological Features and Axillary Lymph Node Metastasis in Patients with Invasive Breast Cancer

Objective

To investigate the risk factors of axillary lymph node metastasis in patients with invasive breast cancer.

Methods

This study retrospectively included 122 cases of invasive breast cancer patients admitted to the First Medical Center of PLA General Hospital from January 2019 to September 2020. According to postoperative pathological results, axillary lymph node metastasis was divided into axillary lymph node metastasis (ALNM) group (n =40) and non-axillary lymph node metastasis (NALNM) group (n =82). General demographic information was collected and compared between the two groups. Collected pathological results included lymphovascular invasion (LVI) and the expression of estrogen receptor (ER), progestogen receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 detected by immunohistochemistry. Imaging parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) including apparent diffusion coefficient (ADC), early enhanced rate, and time-intensity curve (TIC) were also included into univariate analysis. The variables with differences between the two groups were compared by univariate analysis, and the related factors of axillary lymph node metastasis were analyzed by logistic regression model.

Results

There was no significant difference in general demographic information between the two groups. No significant differences were found in the positive rates of HER-2, ER, PR, Ki-67, pathological types, and clavicular lymph node metastasis and skin chest wall invasion between the two groups (P > 0.05). The proportion of LVI in ALNM group was significantly higher than that in NALNM group (37.50% vs. 6.10%, P < 0.001). The proportion of breast cancer on the left side in the ALNM group was higher than that in the NALNM group, and the difference was statistically significant (70.00% vs. 47.56%, P = 0.019). There were no significant differences in the imaging parameters obtained by DCE-MRI between the two groups. Binary logistics regression analysis showed that LVI (OR =12.258, 95% CI =3.681-40.812, P < 0.001) and left breast cancer (OR =3.598, 95% CI =1.404-9.219, P = 0.008) were risk factors for axillary lymph node metastasis in patients with invasive breast cancer.

Conclusion

The formation of vascular tumor thrombi in breast cancer tissue and left breast cancer are risk factors for axillary lymph node metastasis in invasive breast cancer and might be helpful for preoperative detailed assessment of the patient's condition.

Breast MRI during pregnancy and lactation: clinical challenges and technical advances

The breast experiences substantial changes in morphology and function during pregnancy and lactation which affects its imaging properties and may reduce the visibility of a concurrent pathological process. The high incidence of benign gestational-related entities may further add complexity to the clinical and radiological evaluation of the breast during the period. Consequently, pregnancy-associated breast cancer (PABC) is often a delayed diagnosis and carries a poor prognosis. This state-of-the-art pictorial review illustrates how despite currently being underutilized, technical advances and new clinical evidence support the use of unenhanced breast MRI during pregnancy and both unenhanced and dynamic-contrast enhanced (DCE) during lactation, to serve as effective supplementary modalities in the diagnostic work-up of PABC.

Implementation of Abbreviated Breast MRI for Screening: AJR Expert Panel Narrative Review

Abbreviated breast MRI (AB-MRI) is being rapidly adopted to harness the high sensitivity of screening MRI while addressing issues related to access, cost, and workflow. The successful implementation of an ABI-MRI program requires collaboration across administrative, operational, financial, technical, and clinical providers. Institutions must be thoughtful in defining AB-MRI patient eligibility and providing recommendations for screening intervals, as existing practices are heterogeneous. Similarly, there is no universally accepted AB-MRI protocol, though guiding principles should harmonize abbreviated and full protocols while being mindful of scan duration and table time. The interpretation of AB-MRI will be a new experience for many radiologists and may require a phased rollout as well as a careful audit of performance metrics over time to ensure benchmark metrics are achieved. AB-MRI finances, which are driven by patient self-payment, will require buy-in from hospital administration with the recognition that downstream revenues will be needed to support initial costs. Finally, successful startup of an AB-MRI program requires active engagement with the larger community of patients and referring providers. As AB-MRI becomes more widely accepted and available, best practices and community standards will continue to evolve to ensure high quality patient care.

Magnetic resonance imaging findings of invasive breast cancer in different histological grades and different histopathological types

BACKGROUND

The aim of this study was to evaluate the magnetic resonance imaging (MRI) findings of invasive breast cancer in different histopathological types (invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC) and mixed ductal-lobular carcinoma (MDLC)) and different histological grades.

METHODS

A retrospective review was made of 1256 patients who underwent breast MRI at our hospital between January 2015 and December 2018. A total of 152 lesions (27 ILC, 102 IDC, 23 MDLC and 20 grade 1, 83 grade 2 and 49 grade 3) were included in the study. All the lesions were evaluated according to size, shape, margin, dynamic curve, ADC value and T2 signal intensity ratio (SIR).

RESULTS

Most of the lesions tended to show type 2 and type 3 dynamic curve, type 1 dynamic curve was more commonly seen in ILC and grade 1 groups. IDC showed higher T2 SIR than the other types and grade 3 showed higher T2 SIR than other grades (p< 0,05) There was no statistically significant difference between the groups according to morphological features and mean ADC values (p > 0,05).

CONCLUSION

T2 SIR and dynamic curve can help the radiologists predict histopathological findings while morphological features and ADC values were not helpful in distinguishing histological types and grades.