Peripheral hyperintense pattern on T2-weighted magnetic resonance imaging (MRI) in breast carcinoma: Correlation with early peripheral enhancement on dynamic MRI and histopathologic findings

Multiparametric MRI-based radiomics nomogram for predicting the hormone receptor status of HER2-positive breast cancer

AIM

To investigate the value of multiparametric magnetic resonance imaging (MRI)-based radiomics nomograms for predicting the hormone receptor (HR) status of HER2-positive breast cancer.

MATERIALS AND METHODS

Patients with HER2-positive invasive breast cancer were divided randomly into training (68 patients) and validation (30 patients) sets. All were classified as either HR-positive (HR+) or negative (HR-) at histopathology. Two radiologists outlined the three-dimensional (3D) volumetric regions of interest (VOI) on the MRI images. Features (n=1,096) were extracted from the T2-weighted imaging (WI), apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE) images separately. Dimensionality was reduced using feature screening. Binary radiomics prediction models were established using a logistic regression classifier and were validated in the validation set. To construct a nomogram, independent predictors were identified using multivariate logistic regression analysis. The predictive efficacy of the model was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

Ten radiomics features were obtained after feature dimensionality reduction based on the merged T2WI, ADC, and DCE images. The diagnostic efficacy of the radiomics signature using the three sequences was better than that of any single sequence (training set AUC: 0.797; validation set AUC: 0.75). Using multivariate logistic regression analysis, the independent predictors for identifying HR status were combined radiomics signature and peritumoural oedema. Nomograms constructed by combining the radiomics signature and peritumoural oedema showed good discrimination in both the training and validation sets (AUC: 0.815 and 0. 805, respectively).

CONCLUSION

A multiparametric MRI-based nomogram incorporating the radiomics signature and peritumoural oedema can assess the HR status of HER2-positive breast cancer. The resulting model can improve diagnostic accuracy, improving patient outcomes.

Triple-negative breast cancer: predictive model of early recurrence based on MRI features

AIM

To develop an integrated model based on preoperative magnetic resonance imaging (MRI) features for predicting early recurrence in patients with triple-negative breast cancer (TNBC).

MATERIALS AND METHODS

Women with TNBC who underwent breast MRI and surgery between 2009 and 2019 were evaluated retrospectively. Two breast radiologists reviewed MRI images independently based on the Breast Imaging Reporting and Data System Lexicon (BI-RADS), and classified the breast oedema scores on T2-weighted imaging (WI) as no oedema, peritumoural oedema, prepectoral oedema, or subcutaneous oedema. The relationship between disease-free survival (DFS) and MRI features was analysed by Cox regression, and a nomogram model was generated based on the results.

RESULTS

150 patients with TNBC were included and divided into a training cohort (n=78) and validation cohort (n=72). MRI features including subcutaneous oedema and rim enhancement showed a tendency to worsen DFS in univariate analysis. Multivariate analysis showed that subcutaneous oedema (p=0.049, HR [95% confidence interval {CI} = 8.24 [1.01-67.52]) and rim enhancement (p=0.016, HR [95% CI] = 4.38 [1.32-14.54]) were independent predictors for DFS. In the nomogram, the areas under the curves (AUCs) of the training cohort was 0.808, and that of the validation cohort was 0.875.

CONCLUSION

The presence of subcutaneous oedema or rim enhancement on preoperative breast MRI was shown to be a good predictor of poor survival outcomes in patients with TNBC.

Breast Cancer Growth on Serial MRI: Volume Doubling Time Based on 3-Dimensional Tumor Volume Assessment

BACKGROUND

The volume doubling time (VDT) of breast cancer was most frequently calculated using the two-dimensional (2D) diameter, which is not reliable for irregular tumors. It was rarely investigated using three-dimensional (3D) imaging with tumor volume on serial magnetic resonance imaging (MRI).

PURPOSE

To investigate the VDT of breast cancer using 3D tumor volume assessment on serial breast MRIs.

STUDY TYPE

Retrospective.

SUBJECTS

Sixty women (age at diagnosis: 57 ± 10 years) with breast cancer, assessed by two or more breast MRI examinations. The median interval time was 791 days (range: 70-3654 days).

FIELD STRENGTH/SEQUENCE

3-T, fast spin-echo T2-weighted imaging (T2WI), single-shot echo-planar diffusion-weighted imaging (DWI), and gradient echo dynamic contrast-enhanced imaging.

ASSESSMENT

Three radiologists independently reviewed the morphological, DWI, and T2WI features of lesions. The whole tumor was segmented to measure the volume on contrast-enhanced images. The exponential growth model was fitted in the 11 patients with at least three MRI examinations. The VDT of breast cancer was calculated using the modified Schwartz equation.

STATISTICAL TESTS

Mann-Whitney U test, Kruskal-Wallis test, Chi-squared test, intraclass correlation coefficients, and Fleiss kappa coefficients. A P-value <0.05 was considered statistically significant. The exponential growth model was evaluated using the adjusted R2 and root mean square error (RMSE).

RESULTS

The median tumor diameter was 9.7 mm and 15.2 mm on the initial and final MRI, respectively. The median adjusted R2 and RMSE of the 11 exponential models were 0.97 and 15.8, respectively. The median VDT was 540 days (range: 68-2424 days). For invasive ductal carcinoma (N = 33), the median VDT of the non-luminal type was shorter than that of the luminal type (178 days vs. 478 days). On initial MRI, breast cancer manifesting as a focus or mass lesion showed a shorter VDT than that of a non-mass enhancement (NME) lesion (median VDT: 426 days vs. 665 days).

DATA CONCLUSION

A shorter VDT was observed in breast cancer manifesting as focus or mass as compared to an NME lesion.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Intramammary edema of invasive breast cancers on MRI T2-weighted fat suppression sequence: Correlation with molecular subtypes and clinical-pathologic prognostic factors

OBJECTIVE

To investigate the associations between different patterns of intramammary edema on preoperative 3.0 T magnetic resonance imaging (MRI) T₂-weighted fat suppression sequence and invasive breast cancer molecular subtypes and clinical-pathologic prognostic factors.

METHODS

Between May 2014 and December 2020, 191 patients with invasive breast cancer who had undergone preoperative MRI and mastectomy or breast-conserving surgery were retrospectively enrolled. The relationships between different patterns of intramammary edema and invasive breast cancer molecular subtypes and clinical-pathologic features were evaluated using the Student's t-test or Mann-Whitney U test and the χ2 test or Fisher's exact test.

RESULTS

Patients with luminal B (HER2 positive), HER2-enriched and triple negative breast cancers respectively had different patterns of intramammary edema (P < 0.001). There was a significant association between intramammary edema and clinical-pathologic factors, including larger tumor size, higher Ki-67 index, lymph node metastasis and lymphovascular invasion (all P < 0.001).

CONCLUSIONS

Intramammary edema may provide added values of predicting molecular subtypes and clinical-pathologic prognosis, enhancing the ability to individualize the treatment of patients with invasive breast cancer.

The Impact of Tumor Edema on T2-Weighted 3T-MRI Invasive Breast Cancer Histological Characterization: A Pilot Radiomics Study

Simple Summary

Breast cancer is the most common cancer in women worldwide. Currently the use of MR is mandatory in staging phase. The standard protocol includes T2-weighted sequences for morphology and signal analysis, T1-weighted images for adding information (i.e., ematic or adipous components), diffusion-weighted sequences which provide information on tissue cellularity, and dynamic post-contrast sequences useful for detecting and locating lesions. Although not considered among the main prognostic factors in current guidelines, tumor-associated edema provides useful information on tumor aggressiveness, and has been shown to be associated with the main histological tumor characteristics. With this work, entitled “The Impact of Tumor Edema on T2-weighted 3T-MRI Invasive Breast Cancer Histological Characterization: a Pilot Radiomics Study”, we want to demonstrate that radiomics edema, based on algorithms that allow the extraction of imaging features not visible to the human eye, can further increase the accuracy in the prediction of histological factors compared to the use of traditional information only.

Abstract

Background: to evaluate the contribution of edema associated with histological features to the prediction of breast cancer (BC) prognosis using T2-weighted MRI radiomics. Methods: 160 patients who underwent staging 3T-MRI from January 2015 to January 2019, with 164 histologically proven invasive BC lesions, were retrospectively reviewed. Patient data (age, menopausal status, family history, hormone therapy), tumor MRI-features (location, margins, enhancement) and histological features (histological type, grading, ER, PgR, HER2, Ki-67 index) were collected. Of the 160 MRI exams, 120 were considered eligible, corresponding to 127 lesions. T2-MRI were used to identify edema, which was classified in four groups: peritumoral, pre-pectoral, subcutaneous, or diffuse. A semi-automatic segmentation of the edema was performed for each lesion, using 3D Slicer open-source software. Main radiomics features were extracted and selected using a wrapper selection method. A Random Forest type classifier was trained to measure the performance of predicting histological factors using semantic features (patient data and MRI features) alone and semantic features associated with edema radiomics features. Results: edema was absent in 37 lesions and present in 127 (62 peritumoral, 26 pre-pectoral, 16 subcutaneous, 23 diffuse). The AUC-classifier obtained by associating edema radiomics with semantic features was always higher compared to the AUC-classifier obtained from semantic features alone, for all five histological classes prediction (0.645 vs. 0.520 for histological type, 0.789 vs. 0.590 for grading, 0.487 vs. 0.466 for ER, 0.659 vs. 0.546 for PgR, and 0.62 vs. 0.573 for Ki67). Conclusions: radiomic features extracted from tumor edema contribute significantly to predicting tumor histology, increasing the accuracy obtained from the combination of patient clinical characteristics and breast imaging data.

Correlation of Peri-Tumoral Edema Determined in T2 Weighted Imaging with Apparent Diffusion Coefficient of Peritumoral Area in Patients with Breast Carcinoma

Background: Breast cancer may result in remodeling of adjacent normal appearing breast tissues. Magnetic resonance imaging (MRI) is increasingly used in the diagnosis and follow-up of breast cancer by means of diffusion weighted imaging, which is based on thermal motion of water molecules in the extracellular fluid. Objectives: We investigated the correlation of visual assessment of peri-tumoral edema with peri-tumoral and tumoral apparent diffusion coefficient (ADC) values. Patients and Methods: In this cross-sectional study, from 2016 to 2018, 78 patients with 89 malignant breast lesions (mean age, 47 years) were examined by 1.5-T breast MRI. The lesions were categorized based on the visual assessment of peri-tumoral edema on T2 weighted imaging (T2WI) into two groups: (A) with edema (36 lesions) and (B) without edema (53 lesions). Measuring ADC values in the contralateral normal breast tissue, peri-tumoral tissue and peri-tumoral-normal tissue ADC ratio were compared between the two groups for all lesions. Results: The number of in situ lesions was higher in group B (7.5% vs 2.7%) with the p value of 0.01. The mean of ADC values in the normal breast tissue was 1.76 × 10-3mm2/s. Tumor ADCs were significantly lower in group A compared to group B (0.95 × 10-3mm2/s vs. 1.11 × 10-3mm2/s) with the P value of 0.003. However, peri-tumoral ADCs were significantly higher in group A (1.82 × 10-3mm2/s vs. 1.53 × 10-3mm2/s) with the p value of 0.005. The peri-tumoral-normal tissue ADC ratio was 0.87 in group B and about 1 in group A. However, the difference between normal tissue ADCs and peri-tumoral ADCs was only significant (P value of 0.005) in group B. The cut-off point value for differentiating normal tissue ADCs and peri-tumoral ADCs was 1.61 × 10-3mm2/s with the sensitivity of 65% and specificity of 70%. Conclusion: Breast cancer with peri-tumoral edema has lower tumoral ADC values, higher peri-tumoral ADC values and lower prevalence of in situ lesions. Visual assessment of peri-tumoral edema on T2WI could predict the tumoral characteristic on diffusion-weighted imaging.

Clinical Imaging of Glycogen-rich Clear Cell Carcinoma of the Breast: A Case Series with Literature Review

Glycogen-rich clear cell carcinoma (GRCC) of the breast is a rare malignant tumor. Most previous reports focused on clinicopathologic findings of GRCC and imaging findings were not precisely described. Here, we report imaging findings of three cases of GRCC along with a literature review. GRCC of the breast was depicted as a mass with irregular or oval shape on mammography and complex cystic and solid composition or focal cystic change on ultrasound. GRCC showed internal high signal intensity on T₂-weighted MRI with rim enhancement after contrast injection. These might suggest the possibility of GRCC in differentiating breast tumors.

Preoperative MRI features associated with lymphovascular invasion in node-negative invasive breast cancer: A propensity-matched analysis

PURPOSE

In node-negative disease, the presence of lymphovascular invasion (LVI) is reported to be an unfavorable prognostic factor. Thus, the aim of this study was to evaluate whether preoperative breast MRI features are associated with LVI in patients with node-negative invasive breast cancer by a propensity-matched analysis.

MATERIALS AND METHODS

Among 389 patients with node-negative invasive ductal breast cancer who had preoperative breast 3.0 Tesla MRI with precontrast T2-weighted fat-suppressed, pre- and dynamic postcontrast T1-weighted fat-suppressed sequences, 61 patients with LVI (LVI group) were matched with 183 patients without LVI (no LVI group) at a ratio of 1:3 in terms of age, histologic grade, tumor size, and hormone receptor status. Two radiologists reviewed the MRI features, following profiles of focal breast edema (peritumoral, prepectoral, subcutaneous), intratumoral T2 signal intensity, adjacent vessel sign, and increased ipsilateral whole-breast vascularity, in addition to 2013 Breast Imaging Reporting and Data System lexicon.

RESULTS

The presence of peritumoral edema (45.9% [28/61] versus 30.6% [56/183], P = 0.030) and adjacent vessel sign (82.0% [50/61] versus 68.3% [125/183], P = 0.041) was significantly associated with LVI. Prepectoral edema was also more frequently observed in the LVI group than in the no LVI group with borderline significance (26.2% [16/61] versus 15.3% [28/183], P = 0.055). In cases of nonmass enhancement, regional enhancement was more frequently found in the LVI group than in the no LVI group (60.0% [3/4] versus 5.9% [1/4], P = 0.042).

CONCLUSION

Preoperative breast MRI features may be associated with LVI in patients with node-negative invasive breast cancer.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1037-1044.

Effectiveness of additional diagnostic parameters in magnetic resonance mammography: a comparative study with the BI-RADS classification and scoring system

OBJECTIVE

This study aims to evaluate the strength of magnetic resonance (MR) lesion descriptors for malignancy and to determine the effectiveness of a scoring system that combines BI-RADS parameters with additional criteria.

MATERIALS AND METHODS

Three hundred thirty-nine histopathologically proven lesions that had undergone MR imaging were analyzed retrospectively. Based on the Fischer scoring system, an optimal cutoff value was calculated for combined parameters. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for all lesions with MR BI-RADS classification without using additional parameters. Finally, the results of the scoring system and MR BI-RADS classification were compared.

RESULTS

The optimal cutoff value according to the total score was calculated as 5. The sensitivity and the specificity of BI-RADS classification were calculated to be 94.20% and 56.12%, respectively. The scoring system using a cutoff value of 5 resulted in a little loss of sensitivity (89.86%) but resulted in a reasonable increase in the specificity (88.49%).

CONCLUSIONS

Additional parameters can improve the specificity of MR imaging. T2-weighted signal features, adjacent vessel sign, unilateral-focal edema, and hook sign were considered as effective parameters.