Vascular characterisation of triple negative breast carcinomas using dynamic MRI

Combination of IVIM with DCE-MRI for diagnostic and prognostic evaluation of breast cancer

PURPOSE

To identify the most effective combination of DCE-MRI (Ktrans,Kep) and IVIM (D,f) and analyze the correlations of these parameters with prognostic indicators (ER, PR, and HER2, Ki-67 index, axillary lymph node (ALN) and tumor size) to improve the diagnostic and prognostic efficiency in breast cancer.

METHODS

This is a prospective study. We performed T1WI, T2WI, IVIM, DCE-MRI at 3 T MRI examinations on benign and malignant breast lesions that met the inclusion criteria. We also collected pathological results of corresponding lesions, including ER, PR, and HER2, Ki-67 index, axillary lymph node (ALN) and tumor size. The diagnostic efficacy of DCE-MRI, IVIM imaging, and their combination for benign and malignant breast lesions was assessed. Correlations between the DCE-MRI and IVIM parameters and prognostic indicators were assessed.

RESULTS

Overall,59 female patients with 62 lesions (22 benign lesions and 40 malignant lesions) were included in this study. The malignant group showed significantly lower D values (p < 0.05) and significantly higher Ktrans, Kep, and f values (p < 0.05). The AUC values of DCE, IVIM, DCE + IVIM were 0.828, 0.882, 0.901. Ktrans, Kep, D and f values were correlated with the pathological grade (p < 0.05); Ktrans was negatively correlated with ER expression (r = -0.519, p < 0.05); Kep was correlated with PR expression and the Ki-67 index (r = -0.489, 0.330, p < 0.05); the DCE and IVIM parameters showed no significant correlations with the HER2 and ALN (p > 0.05). Tumor diameter was correlated with the Kep, D and f values (r = 0.246, -0.278, 0.293; p < 0.05).

CONCLUSION

IVIM and DCE-MRI allowed differential diagnosis of benign and malignant breast lesions, and their combination showed significantly better diagnostic efficiency. DCE- and IVIM-derived parameters showed correlations with some prognostic factors for breast cancer.

Affinity of PET-MRI Tracers for Hypoxic Cells in Breast Cancer: A Systematic Review

Tumour hypoxia is a known microenvironmental culprit for treatment resistance, tumour recurrence and promotion of metastatic spread. Despite the long-known existence of this factor within the tumour milieu, hypoxia is still one of the greatest challenges in cancer management. The transition from invasive and less reliable detection methods to more accurate and non-invasive ways to identify and quantify hypoxia was a long process that eventually led to the promising results showed by functional imaging techniques. Hybrid imaging, such as PET-CT, has the great advantage of combining the structural or anatomical image (offered by CT) with the functional or metabolic one (offered by PET). However, in the context of hypoxia, it is only the PET image taken after appropriate radiotracer administration that would supply hypoxia-specific information. To overcome this limitation, the development of the latest hybrid imaging systems, such as PET-MRI, enables a synergistic approach towards hypoxia imaging, with both methods having the potential to provide functional information on the tumour microenvironment. This study is designed as a systematic review of the literature on the newest developments of PET-MRI for the imaging of hypoxic cells in breast cancer. The analysis includes the affinity of various PET-MRI tracers for hypoxia in this patient group as well as the correlations between PET-specific and MRI-specific parameters, to offer a broader view on the potential for the widespread clinical implementation of this hybrid imaging technique.

A multiparametric approach to predict triple-negative breast cancer including parameters derived from ultrafast dynamic contrast-enhanced MRI

OBJECTIVE

Triple-negative breast cancer (TNBC) is a highly proliferative breast cancer subtype. We aimed to identify TNBC among invasive cancers presenting as masses using maximum slope (MS) and time to enhancement (TTE) measured on ultrafast (UF) DCE-MRI, ADC measured on DWI, and rim enhancement on UF DCE-MRI and early-phase DCE-MRI.

METHODS

This retrospective single-center study, between December 2015 and May 2020, included patients with breast cancer presenting as masses. Early-phase DCE-MRI was performed immediately after UF DCE-MRI. Interrater agreements were evaluated using the intraclass correlation coefficient (ICC) and Cohen's kappa. Univariate and multivariate logistic regression analyses of the MRI parameters, lesion size, and patient age were performed to predict TNBC and create a prediction model. The programmed death-ligand 1 (PD-L1) expression statuses of the patients with TNBCs were also evaluated.

RESULTS

In total, 187 women (mean age, 58 years ± 12.9 [standard deviation]) with 191 lesions (33 TNBCs) were evaluated. The ICC for MS, TTE, ADC, and lesion size were 0.95, 0.97, 0.83, and 0.99, respectively. The kappa values of rim enhancements on UF and early-phase DCE-MRI were 0.88 and 0.84, respectively. MS on UF DCE-MRI and rim enhancement on early-phase DCE-MRI remained significant parameters after multivariate analyses. The prediction model created using these significant parameters yielded an area under the curve of 0.74 (95% CI, 0.65, 0.84). The PD-L1-expressing TNBCs tended to have higher rim enhancement rates than the non-PD-L1-expressing TNBCs.

CONCLUSION

A multiparametric model using UF and early-phase DCE-MRI parameters may be a potential imaging biomarker to identify TNBCs.

CLINICAL RELEVANCE STATEMENT

Prediction of TNBC or non-TNBC at an early point of diagnosis is crucial for appropriate management. This study offers the potential of UF and early-phase DCE-MRI to offer a solution to this clinical issue.

KEY POINTS

• It is crucial to predict TNBC at an early clinical period. • Parameters on UF DCE-MRI and early-phase conventional DCE-MRI help in predicting TNBC. • Prediction of TNBC by MRI may be useful in determining appropriate clinical management.

Identification of the Benignity and Malignancy of BI-RADS 4 Breast Lesions Based on a Combined Quantitative Model of Dynamic Contrast-Enhanced MRI and Intravoxel Incoherent Motion

The aim of this study was to explore whether intravoxel incoherent motion (IVIM) combined with a dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative model can improve the ability to distinguish between benign and malignant BI-RADS 4 breast lesions. We enrolled 100 patients who underwent breast MRI at our institution and extracted the quantitative parameters of lesions with a post-processing workstation. Statistical differences in these parameters between benign and malignant BI-RADS 4 lesions were assessed using a two independent samples t-test or a Mann-Whitney U test. Binary logistic regression analysis was performed to establish five diagnostic models (model_{_ADC}, model_{_IVIM}, model_{_DCE}, model_{_DCE+ADC}, and model_{_DCE+IVIM}). Receiver operating characteristic (ROC) curves, leave-one-out cross-validation, and the Delong test were used to assess and compare the diagnostic performance of these models. The model_{_DCE+IVIM} showed the highest area under the curve (AUC) of 0.903 (95% confidence interval (CI): 0.828-0.953, sensitivity: 87.50%, specificity: 85.00%), which was significantly higher than that of model_{_ADC} (p = 0.014) and model_{_IVIM} (p = 0.033). The model_{_ADC} had the lowest diagnostic performance (AUC = 0.768, 95%CI: 0.672-0.846) but was not significantly different from model_{_IVIM} (p = 0.168). The united quantitative model with DCE-MRI and IVIM could improve the ability to evaluate the malignancy in BI-RADS 4 lesions, and unnecessary breast biopsies may be obviated.

A Simultaneous Multiparametric 18F-FDG PET/MRI Radiomics Model for the Diagnosis of Triple Negative Breast Cancer

Simple Summary

In this study, we aimed to build a machine-learning predictive model for the identification of triple negative breast cancer, the most aggressive subtype, using quantitative parameters and radiomics features extracted from tumor lesions on hybrid PET/MRI. The good performance of the model supports the hypothesis that hybrid PET/MRI can provide quantitative data able to non-invasively detect tumor biological characteristics using artificial intelligence software and further encourages the conduction of additional studies for this purpose.

Abstract

Purpose: To investigate whether a machine learning (ML)-based radiomics model applied to ¹⁸F-FDG PET/MRI is effective in molecular subtyping of breast cancer (BC) and specifically in discriminating triple negative (TN) from other molecular subtypes of BC. Methods: Eighty-six patients with 98 BC lesions (Luminal A = 10, Luminal B = 51, HER2+ = 12, TN = 25) were included and underwent simultaneous ¹⁸F-FDG PET/MRI of the breast. A 3D segmentation of BC lesion was performed on T2w, DCE, DWI and PET images. Quantitative diffusion and metabolic parameters were calculated and radiomics features extracted. Data were selected using the LASSO regression and used by a fine gaussian support vector machine (SVM) classifier with a 5-fold cross validation for identification of TNBC lesions. Results: Eight radiomics models were built based on different combinations of quantitative parameters and/or radiomic features. The best performance (AUROC 0.887, accuracy 82.8%, sensitivity 79.7%, specificity 86%, PPV 85.3%, NPV 80.8%) was found for the model combining first order, neighborhood gray level dependence matrix and size zone matrix-based radiomics features extracted from ADC and PET images. Conclusion: A ML-based radiomics model applied to ¹⁸F-FDG PET/MRI is able to non-invasively discriminate TNBC lesions from other BC molecular subtypes with high accuracy. In a future perspective, a “virtual biopsy” might be performed with radiomics signatures.

Correlation of dynamic contrast-enhanced MRI and diffusion-weighted MR imaging with prognostic factors and subtypes of breast cancers

Objective

To determine the preoperative magnetic resonance imaging (MRI) findings of breast cancer on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DWI) in different molecular subtypes.

Materials and methods

A retrospective study was conducted on 116 breast cancer subjects who underwent preoperative MRI and surgery or biopsy. Three radiologists retrospectively assessed the morphological and kinetic characteristics on DCE-MRI and tumor detectability on DWI, by using apparent diffusion coefficient (ADC) values of lesions. The clinicopathologic and MRI features of four subtypes were compared. The correlation between clinical and MRI findings with molecular subtypes was evaluated using the chi-square and ANOVA tests, while the Mann–Whitney test was used to analyze the relationship between ADC and prognostic factors.

Results

One hundred and sixteen women diagnosed with breast cancer confirmed by surgery or biopsy had the following subtypes of breast cancer: luminal A (27, 23.3%), luminal B (56, 48.2%), HER2 positive (14, 12.1%), and triple-negative breast cancer (TNBC) (19, 16.4%), respectively. Among the subtypes, significant differences were found in axillary node metastasis, histological grade, tumor shape, rim enhancement, margin, lesion type, intratumoral T2 signal intensity, Ki-67 index, and paratumoral enhancement (p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, and p = 0.02, respectively). On DWI, the mean ADC value of TNBC (0.910 × 10⁻³ mm²/s) was the lowest compared to luminal A (1.477×10⁻³ mm²/s), luminal B (0.955 × 10⁻³ mm²/s), and HER2 positive (0.996 × 10⁻³ mm²/s) (p < 0.001). Analysis of the correlation between different prognostic factors and ADC value showed that only axillary lymph node status and ADC value had a statistically significant difference (p = 0.009).

Conclusion

The morphologic features of MRI can be used as imaging biomarkers to identify the molecular subtypes of breast cancer. In addition, quantitative assessments of ADC values on DWI may also provide biological clues about molecular subtypes.

Correlation of magnetic resonance imaging quantitative parameters and apparent diffusion coefficient value with pathological breast cancer

BACKGROUND

China ranks 120^th worldwide for the incidence of breast cancer and 163^rd for mortality. Early screening, diagnosis, and timely determination of the optimal treatment plan can help ensure clinical efficacy and prognosis.

AIM

To investigate the relationship between quantitative magnetic resonance imaging parameters, apparent diffusion coefficient value, pathological immunohistochemical status, and patient prognosis.

METHODS

A total of 108 patients with breast cancer (breast cancer group) and 110 patients with benign breast tumors (benign group) confirmed by pathological examination at our Hospital from September 2013 to August 2016 were selected. All patients had undergone preoperative magnetic resonance imaging (MRI) examinations, and the quantitative parameters of MRI and apparent diffusion coefficient (ADC) values for the two groups were compared. The MRI quantitative parameters and ADC values of patients with different estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor-2 expression were statistically analyzed. The relationship between the quantitative parameters of MRI and ADC values and patient recurrence was analyzed using receiver operating curves.

RESULTS

The measured values of the quantitative parameters of MRI- Ktrans, Kep, and Ve in the breast cancer group were higher than those in the benign group; the ADC value in the breast cancer group was lower than that in the benign group, and the difference was statistically significant (P < 0.05). The Ktrans, Ve, and ADC values in patients with ER-positive breast cancer were significantly lower than those in patients with negative ER expression (P < 0.05). After 5 years of follow-up, 22 patients with breast cancer experienced postoperative recurrence. The Kep, Ve, and ADC values of the recurrence group were significantly lower than those of the non-recurrence group, and the difference was statistically significant (P < 0.05).

CONCLUSION

MRI quantitative parameters and ADC are related to the expression of breast cancer-related immunological receptor factors and have certain clinical value in assessing postoperative recurrence in patients.

Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review

Magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast cancer detection. This systematic review investigated the role of quantitative MRI features in classifying molecular subtypes of breast cancer. We performed a literature search of articles published on the application of quantitative MRI features in invasive breast cancer molecular subtype classification in PubMed from 1 January 2002 to 30 September 2021. Of the 1275 studies identified, 106 studies with a total of 12,989 patients fulfilled the inclusion criteria. Bias was assessed based using the Quality Assessment of Diagnostic Studies. All studies were case-controlled and research-based. Most studies assessed quantitative MRI features using dynamic contrast-enhanced (DCE) kinetic features and apparent diffusion coefficient (ADC) values. We present a summary of the quantitative MRI features and their correlations with breast cancer subtypes. In DCE studies, conflicting results have been reported; therefore, we performed a meta-analysis. Significant differences in the time intensity curve patterns were observed between receptor statuses. In 10 studies, including a total of 1276 lesions, the pooled difference in proportions of type Ⅲ curves (wash-out) between oestrogen receptor-positive and -negative cancers was not significant (95% confidence interval (CI): [−0.10, 0.03]). In nine studies, including a total of 1070 lesions, the pooled difference in proportions of type 3 curves between human epidermal growth factor receptor 2-positive and -negative cancers was significant (95% CI: [0.01, 0.14]). In six studies including a total of 622 lesions, the pooled difference in proportions of type 3 curves between the high and low Ki-67 groups was significant (95% CI: [0.17, 0.44]). However, the type 3 curve itself is a nonspecific finding in breast cancer. Many studies have examined the relationship between mean ADC and breast cancer subtypes; however, the ADC values overlapped significantly between subtypes. The heterogeneity of ADC using kurtosis or difference, diffusion tensor imaging parameters, and relaxation time was reported recently with promising results; however, current evidence is limited, and further studies are required to explore these potential applications.

Quantitative parameters of magnetic resonance imaging cannot predict human epidermal growth factor receptor 2 (HER2) status in rectal cancer

PURPOSE

To retrospectively investigate whether magnetic resonance imaging (MRI) quantitative parameters can differentiate human epidermal growth factor receptor 2 (HER2) status in rectal cancer.

MATERIALS AND METHODS

This study included 89 patients with surgically confirmed rectal cancer who underwent preoperative MRI from June 2014 to May 2019. Patients were divided into three groups: HER2 negative (HER2-Neg); HER2-low expression (HER2-L); and HER2 positive (HER2-Pos). Quantitative perfusion parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) Tofts model (pharmacokinetic blood dual compartment model) were listed as follows: volume transfer constant (K^trans), rate constant (K_ep), and extracellular volume ratio (V_e). The mean, minimum, and maximum apparent diffusion coefficient (ADC) values at standard (800 s/mm²) b-values were obtained with diffusion-weighted imaging (DWI). Clinicopathologic characteristics and quantitative parameters were compared by Fisher's exact test and one-way analysis of variance (ANOVA), respectively.

RESULTS

The 89 patients included 52 (58.4%) with HER2-Neg, 31 (34.8%) with HER2-L, and 6 (6.8%) with HER2-Pos states. Fisher's exact test showed that clinicopathologic characteristics among the three groups were not significantly different (p = 0.281 to 1.000). Likewise, there were no associations between HER2 status and any quantitative parameters, including K^trans (p = 0.296), K_ep (p = 0.290), V_e (p = 0.184), ADC_mean (p = 0.181), ADC_min (p = 0.143), or ADC_max (p = 0.058).

CONCLUSION

Quantitative perfusion parameters (K^trans, K_ep, V_e) and ADC values were not able to discriminate HER2 status in patients with rectal cancer or evaluate treatment response in real time.

Correlation of DCE-MRI Perfusion Parameters and Molecular Biology of Breast Infiltrating Ductal Carcinoma

Objective

We aimed to investigate the correlation of the perfusion parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with the molecular biological expression of breast infiltrating ductal carcinoma (IDC) in order to guide appropriate therapeutic advice and clinical outcome prediction.

Materials and Methods

In a prospective analysis of 67 patients with breast IDC, preoperative DCE-MRI and routine MRI images were obtained. The double-chamber model (extended Tofts model) was employed to calculate the perfusion parameters. Postoperative pathological immunohistochemistry was examined, including human epidermal growth factor receptor 2 (HER-2), estrogen receptor (ER), progesterone receptor (PR), cell nuclear-associated antigen (Ki-67), cytokeratin 5/6 (CK5/6), and epidermal growth factor receptor (EGFR). Statistical analysis was applied to explore the relationship between the perfusion parameters and the molecular biomarkers of breast cancer.

Results

A total of 67 lesions were included in our study. The mean maximum diameter of lesions was 4.48 ± 1.73 cm. Perfusion parameters had no correlation with tumor diameters (p > 0.05). The volume transfer constant (K ^trans) and the rate constant (k _ep) had positive correlations with Ki-67 (p < 0.05). The plasma volume ratio (v _p) had a statistical difference between CK5/6 positivity and CK5/6 negativity. The maximum rising slope (MAX Slope) was higher in HER-2-enriched tumors than that in luminal A or B tumors (p < 0.05). k _ep was higher in HER-2-enriched tumors than that in luminal A tumors (p < 0.05). The extravascular extracellular space volume fraction (v _e) was higher in triple-negative tumors than that in HER-2-enriched and in luminal A and B tumors (p < 0.05). The time to peak enhancement (TTP) was lower in HER-2-enriched tumors than that in luminal A and B tumors (p < 0.05). Maximum concentration (MAX Conc) was higher in triple-negative tumors than that in luminal B tumors (p < 0.05).

Conclusion

DCE-MRI perfusion parameters can behave as a noninvasive tool to assess the molecular biological expression and the molecular subtypes of breast IDC. They may aid in predicting breast IDC invasiveness, metastasis, and prognosis.

A multicompartment model for intratumor tissue-specific analysis of DCE-MRI using non-negative matrix factorization

PURPOSE

A pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data is subject to inaccuracy and instability partly owing to the partial volume effect (PVE). We proposed a new multicompartment model for a tissue-specific pharmacokinetic analysis in DCE-MRI data to solve the PVE problem and to provide better kinetic parameter maps.

METHODS

We introduced an independent parameter named fractional volumes of tissue compartments in each DCE-MRI pixel to construct a new linear separable multicompartment model, which simultaneously estimates the pixel-wise time-concentration curves and fractional volumes without the need of the pure-pixel assumption. This simplified convex optimization model was solved using a special type of non-negative matrix factorization (NMF) algorithm called the minimum-volume constraint NMF (MVC-NMF).

RESULTS

To test the model, synthetic datasets were established based on the general pharmacokinetic parameters. On well-designed synthetic data, the proposed model reached lower bias and lower root mean square fitting error compared to the state-of-the-art algorithm in different noise levels. In addition, the real dataset from QIN-BREAST-DCE-MRI was analyzed, and we observed an improved pharmacokinetic parameter estimation to distinguish the treatment response to chemotherapy applied to breast cancer.

CONCLUSION

Our model improved the accuracy and stability of the tissue-specific estimation of the fractional volumes and kinetic parameters in DCE-MRI data, and improved the robustness to noise, providing more accurate kinetics for more precise prognosis and therapeutic response evaluation using DCE-MRI.

Hypoxia and perfusion in breast cancer: simultaneous assessment using PET/MR imaging

OBJECTIVES

Hypoxia is associated with poor prognosis and treatment resistance in breast cancer. However, the temporally variant nature of hypoxia can complicate interpretation of imaging findings. We explored the relationship between hypoxia and vascular function in breast tumours through combined 18F-fluoromisonidazole (18 F-FMISO) PET/MRI, with simultaneous assessment circumventing the effect of temporal variation in hypoxia and perfusion.

METHODS

Women with histologically confirmed, primary breast cancer underwent a simultaneous 18F-FMISO-PET/MR examination. Tumour hypoxia was assessed using influx rate constant Ki and hypoxic fractions (%HF), while parameters of vascular function (Ktrans, kep, ve, vp) and cellularity (ADC) were derived from dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI, respectively. Additional correlates included histological subtype, grade and size. Relationships between imaging variables were assessed using Pearson correlation (r).

RESULTS

Twenty-nine women with 32 lesions were assessed. Hypoxic fractions > 1% were observed in 6/32 (19%) cancers, while 18/32 (56%) tumours showed a %HF of zero. The presence of hypoxia in lesions was independent of histological subtype or grade. Mean tumour Ktrans correlated negatively with Ki (r = - 0.38, p = 0.04) and %HF (r = - 0.33, p = 0.04), though parametric maps exhibited intratumoural heterogeneity with hypoxic regions colocalising with both hypo- and hyperperfused areas. No correlation was observed between ADC and DCE-MRI or PET parameters. %HF correlated positively with lesion size (r = 0.63, p = 0.001).

CONCLUSION

Hypoxia measured by 18F-FMISO-PET correlated negatively with Ktrans from DCE-MRI, supporting the hypothesis of perfusion-driven hypoxia in breast cancer. Intratumoural hypoxia-perfusion relationships were heterogeneous, suggesting that combined assessment may be needed for disease characterisation, which could be achieved using simultaneous multimodality imaging.

KEY POINTS

• At the tumour level, hypoxia measured by 18F-FMISO-PET was negatively correlated with perfusion measured by DCE-MRI, which supports the hypothesis of perfusion-driven hypoxia in breast cancer. • No associations were observed between 18F-FMISO-PET parameters and tumour histology or grade, but tumour hypoxic fractions increased with lesion size. • Intratumoural hypoxia-perfusion relationships were heterogeneous, suggesting that the combined hypoxia-perfusion status of tumours may need to be considered for disease characterisation, which can be achieved via simultaneous multimodality imaging as reported here.

Assessing the accuracy of conventional gadolinium-enhanced breast MRI in measuring the nodal response to neoadjuvant chemotherapy (NAC) in breast cancer

Management of the axilla in the era of neoadjuvant chemotherapy for breast cancer is evolving. The aim of this study is to determine if conventional gadolinium-enhanced breast MRI can aid in evaluation of the response to neoadjuvant chemotherapy in the axilla. A retrospective review of a prospectively maintained database of patients undergoing neoadjuvant chemotherapy for breast cancer was performed. Pre and post-neoadjuvant chemotherapy MRI reports for node-positive patients were examined in conjunction with demographic data, treatment type, and final histopathology reports. One-hundred and fourteen patients with breast cancer undergoing neoadjuvant chemotherapy were included in the study. The sensitivity of magnetic resonance imaging in detecting nodal response post-neoadjuvant chemotherapy was 33.93% and the specificity was 82.76%. Magnetic resonance imaging had a positive predictive value of 65.52% and a negative predictive value of 56.47%. MRI was found to be most specific in the detection of triple-negative cancer response. Specificity was 100% in this group and sensitivity was 75%. Magnetic resonance imaging has a relatively high specificity in detecting nodal response post-neoadjuvant chemotherapy but has a low sensitivity. Alone it cannot be relied upon to identify active axillary malignancy post-neoadjuvant chemotherapy. However, given its increased specificity among certain subgroups, it may have a role in super-selecting patients suitable for sentinel lymph node biopsy post-neoadjuvant chemotherapy.

Soft tissue sarcoma: can dynamic contrast-enhanced (DCE) MRI be used to predict the histological grade?

OBJECTIVE

To determine if dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters reflect histological grade of soft tissue sarcoma (STS) MATERIALS AND METHODS: The medical records of 50 patients diagnosed with pathologically confirmed STS were retrospectively reviewed. Each STS was assessed with conventional contrast-enhanced MRI and DCE-MRI using a 3.0-T MRI system. The conventional MRI characteristics of low-grade (grade 1) and high-grade (grade 2 and grade 3) tumors were analyzed. Semi-quantitative parameters, including iAUC and TTP, and quantitative parameters, including K^trans, K_ep, and V_e, were derived from DCE-MRI. The diagnostic performances and optimal thresholds of various combinations of DCE-MRI parameters for predicting histological grades of STS were investigated using receiver operator characteristic (ROC) curves.

RESULTS

On conventional MRI, high-grade STSs were significantly larger (≥ 5 cm) and more likely to show a heterogeneous signal intensity on T₂WI (> 75%), peritumoral hyperintensity on T₂WI, or tumor necrosis (> 50%) compared with low-grade STS. On DCE-MRI, iAUC, TTP, K^trans, and K_ep were significant predictors of STS histological grade. K^trans had a high diagnostic value for differentiating between high-grade and low-grade STSs. The combination of iAUC, TTP, and K^trans yielded a higher AUC value (0.841) than the other models.

CONCLUSION

High-grade STSs were usually larger than low-grade STSs, had unclear boundaries, a heterogeneous signal intensity on T2-weighted image (T₂WI), and extensive necrosis. On DCE-MRI, iAUC, TTP, K^trans, and K_ep could differentiate between high-grade and low-grade STSs. The combination of iAUC, TTP, and K^trans had a high diagnostic performance for differentiating between STS histological grades.

The Key Characteristics of Carcinogens: Relationship to the Hallmarks of Cancer, Relevant Biomarkers, and Assays to Measure Them

The key characteristics (KC) of human carcinogens provide a uniform approach to evaluating mechanistic evidence in cancer hazard identification. Refinements to the approach were requested by organizations and individuals applying the KCs. We assembled an expert committee with knowledge of carcinogenesis and experience in applying the KCs in cancer hazard identification. We leveraged this expertise and examined the literature to more clearly describe each KC, identify current and emerging assays and in vivo biomarkers that can be used to measure them, and make recommendations for future assay development. We found that the KCs are clearly distinct from the Hallmarks of Cancer, that interrelationships among the KCs can be leveraged to strengthen the KC approach (and an understanding of environmental carcinogenesis), and that the KC approach is applicable to the systematic evaluation of a broad range of potential cancer hazards in vivo and in vitro We identified gaps in coverage of the KCs by current assays. Future efforts should expand the breadth, specificity, and sensitivity of validated assays and biomarkers that can measure the 10 KCs. Refinement of the KC approach will enhance and accelerate carcinogen identification, a first step in cancer prevention.See all articles in this CEBP Focus section, "Environmental Carcinogenesis: Pathways to Prevention."

Evaluating the Relationship Between Dynamic Contrast-Enhanced MRI (DCE-MRI) Parameters and Pathological Characteristics in Breast Cancer

BACKGROUND

Dynamic contrast-enhanced MRI (DCE-MRI) is used to evaluate tumor microvasculature. However, studies demonstrating an association between perfusion parameters derived from DCE-MRI and histopathologic characteristics are limited to a small set of histopathologic factors, and the results are inconsistent.

PURPOSE

To evaluate the relationship between DCE-MRI perfusion parameters and common histopathologic tumor characteristics used to predict angiogenesis and determine prognosis in breast cancer.

STUDY TYPE

Retrospective.

POPULATION

In all, 105 breast cancer patients with invasive ductal carcinoma (122 lesions).

FIELD STRENGTH/SEQUENCE

3.0T, turbo spin-echo (TSE) T₁ -weighted, fat-suppressed T₂ -weighted, TSE T₂ -weighted, and dynamic unenhanced and contrast-enhanced 3D T₁ high-resolution isotropic volume examination.

ASSESSMENT

One reviewer obtained perfusion parameters (K^trans , k_ep , v_e , and v_p ) of each breast cancer from DCE MRI using the extended Tofts model with a fixed baseline T₁ value and a population-based arterial input function. The relationship between DCE-MRI perfusion parameters and histopathologic tumor characteristics used to predict angiogenesis and determine prognosis was evaluated.

STATISTICAL TESTS

Student's t-test, Mann-Whitney U-test, analysis of variance (ANOVA), and Kruskal-Wallis test were used.

RESULTS

Triple-negative breast cancers exhibited higher K^trans and k_ep than luminal cancers (P < 0.05). Estrogen receptor (ER)-negative tumors showed higher K^trans than ER-positive tumors (P < 0.05). Progesterone receptor (PR)-negative tumors presented higher v_e than PR-positive tumors (P < 0.05). Tumors with higher Ki-67 showed higher k_ep than tumors with lower Ki-67 (P < 0.05). P53-positive tumors exhibited higher K^trans and k_ep than p53-negative tumors (P < 0.05). Higher histologic grade tumors (grade II/III) presented higher K^trans , k_ep , v_p (P < 0.05) than grade I tumors. Tumors with LVSI presented higher K^trans and k_ep than tumors without LVSI (P < 0.05).

DATA CONCLUSION

Breast cancer presenting higher K^trans and k_ep on DCE-MRI was associated with poor prognostic histopathologic factors. Therefore, pretreatment DCE-MRI perfusion parameters may be useful imaging biomarkers for the evaluation of tumor prognosis and angiogenesis.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Development of a Non-invasive Assessment of Hypoxia and Neovascularization with Magnetic Resonance Imaging in Benign and Malignant Breast Tumors: Initial Results

PURPOSE

To develop a novel magnetic resonance imaging (MRI) approach for the noninvasive assessment of hypoxia and neovascularization in breast tumors.

PROCEDURES

In this IRB-approved prospective study, 20 patients with suspicious breast lesions (BI-RADS 4/5) underwent multiparametric breast MRI including quantitative BOLD (qBOLD) and vascular architecture mapping (VAM). Custom-made in-house MatLab software was used for qBOLD and VAM data postprocessing and calculation of quantitative MRI biomarker maps of oxygen extraction fraction (OEF), metabolic rate of oxygen (MRO₂), and mitochondrial oxygen tension (mitoPO₂) to measure tissue hypoxia and neovascularization including vascular architecture including microvessel radius (VSI), density (MVD), and type (MTI). Histopathology was used as standard of reference. Appropriate statistics were performed to assess and compare correlations between MRI biomarkers for hypoxia and neovascularization.

RESULTS

qBOLD and VAM data with good quality were obtained from all patients with 13 invasive ductal carcinoma (IDC) and 7 benign breast tumors with a lesion diameter of at least 10 mm in all spatial directions. MRI biomarker maps of oxygen metabolism and neovascularization demonstrated intratumoral spatial heterogeneity with a broad range of biomarker values. Bulk tumor neovasculature consisted of draining venous microvasculature with slow flowing blood. High OEF and low mitoPO₂ were associated with low MVD and vice versa. The heterogeneous pattern of MRO₂ values showed spatial congruence with VSI. IDCs showed significantly higher MRO₂ (P = 0.007), lower mitoPO₂ (P = 0.021), higher MVD (P = 0.005), and lower (i.e., more pathologic) MTI (P = 0.001) compared with benign breast tumors. These results indicate that IDCs consume more oxygen and are more hypoxic and neovascularized than benign tumors.

CONCLUSIONS

We developed a novel MRI approach for the noninvasive assessment of hypoxia and neovascularization in benign and malignant breast tumors that can be easily integrated in a diagnostic MRI protocol and provides insight into intratumoral heterogeneity.

Kinetic volume analysis on dynamic contrast-enhanced MRI of triple-negative breast cancer: associations with survival outcomes

OBJECTIVE

To evaluate the associations between computer-aided diagnosis (CAD)-generated kinetic volume parameters and survival in triple-negative breast cancer (TNBC) patients.

METHODS

40 patients with TNBC who underwent pre-operative MRI between March 2008 and March 2014 were included. We analyzed CAD-generated parameters on dynamic contrast-enhanced MRI, visual MRI assessment, and histopathological data. Cox proportional hazards models were used to determine associations with survival outcomes.

RESULTS

12 of the 40 (30.0%) patients experienced recurrence and 7 died of breast cancer after a median follow-up of 73.6 months. In multivariate analysis, higher percentage volume (%V) with more than 200% initial enhancement rate correlated with worse disease-specific survival (hazard ratio, 1.12; 95% confidence interval, 1.02-1.22; p-value, 0.014) and higher %V with more than 100% initial enhancement rate followed by persistent curve type at 30% threshold correlated with worse disease-specific survival (hazard ratio, 1.33; 95% confidence interval, 1.10-1.61; p-value, 0.004) and disease-free survival (hazard ratio, 1.27; 95% confidence interval, 1.12-1.43; p-value, 0.000).

CONCLUSION

CAD-generated kinetic volume parameters may correlate with survival in TNBC patients. Further study would be necessary to validate our results on larger cohorts.

ADVANCES IN KNOWLEDGE

CAD generated kinetic volume parameters on breast MRI can predict recurrence and survival outcome of patients in TNBC. Varying the enhancement threshold improved the predictive performance of CAD generated kinetic volume parameter.

Identification of long non‑coding RNA‑mediated transcriptional dysregulation triplets reveals global patterns and prognostic biomarkers for ER+/PR+, HER2‑ and triple negative breast cancer

Breast cancer (BRCA) is the most common type of cancer in adult females. Estrogen receptor (ER)⁺/progesterone receptor (PR)⁺, human epidermal-growth factor receptor 2 (HER2)⁻ BRCA and triple-negative breast cancer (TNBC) are two important subtypes of this disease. Long non-coding RNA (lncRNA)-mediated transcriptional dysregulation triplets (lncTDTs) may contribute to the development of cancer; however, the precise functional roles of lncTDTs in ER⁺/PR⁺, HER2⁻ BRCA and TNBC require further investigation. In the present study, an integrated and computational approach was conducted to identify lncTDTs based on transcription factor (TF), gene, lncRNA expression profiles and experimentally verified TF-gene interactions. The regulatory patterns of these lncTDTs are complex and differed in ER⁺/PR⁺, HER2⁻ BRCA and TNBC. Of note, five common lncTDTs were reported for these BRCA subtypes. Functional analysis revealed lncTDTs to be enriched in the PI3K/AKT signaling pathway within the two BRCA subtypes. Additionally, certain lncTDTs were associated with survival and may be considered candidate prognostic biomarkers for BRCA subtypes. Collectively, the results of the present study provide novel insight into the functions and mechanisms of lncRNAs in ER⁺/PR⁺, HER2⁻ BRCA and TNBC, and may aid the development of targeted treatments against certain subtypes of BRCA.

Morphological and Semiquantitative Kinetic Analysis on Dynamic Contrast Enhanced MRI in Triple Negative Breast Cancer Patients

RATIONALE AND OBJECTIVES

The aim of this study was to retrospectly investigate the association between different breast cancer (BC) immunohistochemical subtypes and morphological and semiquantitative kinetic analysis on breast magnetic resonance imaging (MRI) performed before surgery treatment. Specifically we aimed to assess MRI features of triple-negative breast cancer (TNBC) compared to the other BC subtypes (nTNBC).

MATERIALS AND METHODS

Patients undergone to breast MRI and then diagnosed with BC by core-needle biopsy were included. The MRI morphological and kinetic features were studied. Parametric and non-parametric tests were used, as appropriate.

RESULTS

Seventy-five BC patients were considered, 30 patients included in TNBC Group and 45 patients included in nTNBC Group. We found in TNBC Group a greater mean lesion size (P <0.001), a rim enhancement imaging (P=0.003), and a higher intratumoral signal intensity on T2-weighted images (P=0.03) with respect to nTNBC Group. We noticed that TNBC patients presented a lower grade of BPE when compared to the nTBC Group (P< 0.02). TNBC Group showed lower EPeak values (P=0.003) and higher SER values (P=0.02) with respect to the nTNBC Group. In addition, stratifying kinetics parameters according to the tumor grade, the TNBC Group presented higher tumor grade (G3) (P< 0.005) and this subgroup had higher SER values when compared to TNBCs showing a lower tumor grade (G1 and G2) (P=0.03).

CONCLUSION

After validation by large-scale studies, the morphological and semiquantitative kinetic analysis on dynamic contrast enhanced MRI may help in the pretreatment risk stratification of patients with TNBC and in evidence-based clinical decision support.

A pilot study of low-dose CT perfusion imaging (LDCTPI) technology in patients with triple-negative breast cancer

PURPOSE

To investigate associations between the clinicopathologic features and CT perfusion parameters of triple-negative breast cancer (TNBC) and non-TNBC using low-dose computed tomography perfusion imaging (LDCTPI), and to find potential clinical applications in the prognosis assessment of TNBC.

MATERIALS AND METHODS

A total of 60 patients with breast cancer confirmed by pathological examination were studied prospectively using LDCTPI on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using a tumor perfusion protocol in the CT perfusion software package to measure 2 parameters namely, blood flow (BF), and permeability surface (PS) area product. Patients were grouped into TNBC (n = 27) and non-TNBC (n = 33) subtypes. Associations between these two subtypes and clinicopathologic characteristics were evaluated by both univariate and multivariate logistic regression. CT perfusion parameters values were compared for clinicopathologic characteristics using independent 2-sample t test.

RESULTS

TNBC displayed higher CT perfusion parameters values (BF: 57.56±10.94 vs 52.70±7.79 mL/100 g/min, p = 0.006; PS: 38.98±9.46 vs 33.39±8.07 mL/100 g/min, p = 0.001) than non-TNBC. In addition, breast cancer with poorly histologic grade or positive Ki-67 expression showed higher BF and PS values than those with well and moderately histologic grade or negative Ki-67 expression (p < 0.05). TNBC had poorer histologic grade (P = 0.032) and higher Ki-67 expression (P = 0.013) than non-TNBC.

CONCLUSION

LDCTPI is a functional imaging technology from the perspective of hemodynamics with potential of clinical applications. The BF and PS values were higher in TNBC patient group than non-TNBC group. TNBC patients also have poorer clinicopathologic outcome.

Histogram analysis of quantitative pharmacokinetic parameters on DCE-MRI: correlations with prognostic factors and molecular subtypes in breast cancer

BACKGROUND

Breast cancer heterogeneity influences poor prognoses thorough therapy resistance. This study quantitatively evaluated intratumoral heterogeneity through a histogram analysis of dynamic contrast-enhanced MRI (DCE-MRI) pharmacokinetic parameters, and determined correlations with prognostic factors and molecular subtypes.

METHODS

We retrospectively investigated 101 invasive ductal breast cancers from 99 women who underwent preoperative DCE-MRI between July 2012 and November 2014. Pharmacokinetic parameters (K^trans, k_ep, and v_e) were obtained by the Tofts model. For each parameter, the mean, standard deviation, coefficient of variation, skewness, and kurtosis values of tumor were calculated, and prognostic factors and subtypes associations were assessed.

RESULTS

The mean of v_e was lower in cancers with high Ki-67 than in cancers with low Ki-67 (P = 0.002). The coefficient of variation of v_e was higher in cancers with estrogen receptor negativity than in cancers with estrogen receptor positivity (P < 0.001). The coefficient of variation of v_e was also higher in cancers with high Ki-67 than in cancers with low Ki-67 (P < 0.001). The skewness of v_e was higher in cancers with high nuclear grade than in cancers with low nuclear grade (P = 0.006). Triple-negative cancers showed higher v_e coefficient of variation than did those with luminal A (P < 0.001) and B (P = 0.006).

CONCLUSIONS

Various v_e parameters correlated with breast cancer prognostic factors and molecular subtypes.

Use of diffusion kurtosis imaging and quantitative dynamic contrast-enhanced MRI for the differentiation of breast tumors

BACKGROUND

Breast MRI is a sensitive imaging technique to assess breast cancer but its effectiveness still remains to be improved.

PURPOSE

To evaluate the diagnostic performance of diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and quantitative dynamic contrast-enhanced (DCE)-MRI in differentiating malignant from benign breast lesions independently or jointly and to explore whether correlations exist among these parameters.

STUDY TYPE

Retrospective.

POPULATION

In all, 106 patients with breast lesions (47 malignant, 59 benign).

SEQUENCE

DKI sequence with seven b values and quantitative DCE sequence on 3.0T MRI.

ASSESSMENT

Diffusion parameters (mean diffusivity [MD], mean diffusivity [MK], and apparent diffusion coefficient [ADC]) from DKI and DWI and perfusion parameters from DCE (K^trans , k_ep , v_e , and v_p ) were calculated by two experienced radiologists after postprocessing. Disagreement between the two observers was resolved by consensus.

STATISTICAL TESTS

The parameters in benign and malignant lesions were compared by Student's t-test. The diagnostic performances of DKI and quantitative DCE, either alone or in combination, were evaluated by receiver operating characteristic (ROC) analysis. The Spearman correlation test was used to evaluate correlations among the diffusion parameters and perfusion parameters.

RESULTS

MK, MD, ADC, K^trans , and k_ep values were significantly different between breast cancer and benign lesions (P < 0.05). MK from DKI demonstrated the highest AUC of 0.849, which is significantly higher than ADC derived from conventional DWI (z = 3.345, P = 0.0008). The specificity of DCE-MRI-derived parameters was improved when combining diffusion parameters, such as ADC and MK. The highest diagnostic specificity (93.2%) was obtained when k_ep and ADC were combined. k_ep was correlated moderately positively with MK (r = 0.516) and moderately negatively with MD (r = -0.527). K^trans was weakly positively correlated with MK with an r of 0.398 and weakly negatively correlated with MD with an r of -0.450.

DATA CONCLUSION

DKI is more valuable than conventional DWI in distinguishing between benign and malignant breast lesions. DKI exhibits promise as a quantitative technique to augment quantitative DCE-MRI. Diffusion parameters derived from DKI were statistically correlated with perfusion parameters from quantitative DCE-MRI.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1358-1366.

Total choline quantification measured by 1H MR spectroscopy as early predictor of response after neoadjuvant treatment for locally advanced breast cancer: The impact of immunohistochemical status

BACKGROUND

Validation of new biomarkers is essential for the early evaluation of neoadjuvant treatments.

PURPOSE

To determine whether measurements of total choline (tCho) by 1H spectroscopy could predict morphological or pathological complete response (pCR) of neoadjuvant treatment and whether breast cancer subgroups are related to prediction accuracy.

STUDY TYPE

Prospective, nonrandomized, monocentric, diagnostic study.

POPULATION

Sixty patients were initially included with 39 women participating in the final cohort.

FIELD STRENGTH/SEQUENCE

A 1.5T scanner was used for acquisition and MRS was performed using the syngo GRACE sequence.

ASSESSMENT

MRS and MRI examinations were performed at baseline (TP1), 24-72 hours after first chemotherapy (TP2), after the end of anthracycline treatment (TP3), and MRI only after the end of taxane treatment (TP4). Early (EMR) and late (LMR) morphological response were defined as %ΔDmax13 or %ΔDmax14, respectively. Responders were patients with %ΔDmax >30. Pathological complete response (pCR) patients achieved a residual cancer burden score of 0.

STATISTICAL TESTS

T-test, receiver operating characteristic (ROC) curves, multiple regression, logistic regression, one-way analysis of variance (ANOVA) analysis were used for the analysis.

RESULTS

At TP1 there was a significant difference between response groups for tCho1 concerning EMR prediction (P = 0.05) and pCR (P < 0.05) and for K_ep 1 (P = 0.03) concerning LMR prediction. At TP2, no modification of tCho and other parameters could predict response. At TP3, ΔtCho, ΔDmax, and ΔVol could predict LMR (P < 0.05 for all parameters), pCR (P < 0.05 for all parameters), and ΔK^trans could predict only pCR (P = 0.04). Logistic regression at baseline showed the highest area under the curve (AUC) of 0.9 for prediction of pCR. The triple negative (TN) subgroup showed significantly higher tCho at baseline (P = 0.02) and higher ΔtCho levels at TP3 (P < 0.05).

DATA CONCLUSION

Baseline measurements of tCho in combination with clinicopathological criteria could predict non-pCR with a high AUC. Furthermore, tCho quantification for prediction of pCR was more sensitive for TN tumors.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2018;48:982-993.

Contrast agents in dynamic contrast-enhanced magnetic resonance imaging

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive method to assess angiogenesis, which is widely used in clinical applications including diagnosis, monitoring therapy response and prognosis estimation in cancer patients. Contrast agents play a crucial role in DCE-MRI and should be carefully selected in order to improve accuracy in DCE-MRI examination. Over the past decades, there was much progress in the development of optimal contrast agents in DCE-MRI. In this review, we describe the recent research advances in this field and discuss properties of contrast agents, as well as their advantages and disadvantages. Finally, we discuss the research perspectives for improving this promising imaging method.

Light-Activated Core-Shell Nanoparticles for Spatiotemporally Specific Treatment of Metastatic Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) tumors are heterogeneous, with mesenchymal-like cells at their core and fast proliferating cells on the periphery. It is desirable and beneficial to treat TNBC cells of different phenotypes with the most appropriate drugs. Here, we report a 78 nm, chlorin e6-, docetaxel-, and anti-Twist siRNA-containing polymeric nanoparticle (CDTN) with spatiotemporally specific activity when irradiated by light. Under conditions mimicking superficial tumor tissue with sufficient light input, TNBC cells are mainly killed by the photodynamic therapy (PDT) function of CDTNs. In contrast, under conditions mimicking deep tumor tissue with weak light input, PDT potentiates chemotherapy (CT) and gene therapy (GT) by facilitating the endolysosomal escape of CDTNs. Compared with free drugs, CDTNs improve the intratumoral exposure of docetaxel and anti-Twist siRNA by 2.5- and 2-fold, respectively. When combined with laser irradiation applied at the time of maximal intratumoral accumulation, the CDTNs significantly inhibit the growth of primary tumors and their lung metastasis (both >80%) by killing the peripheral cells, mainly through PDT and prohibiting the growth and metastasis of deep cells through PDT as enhanced CT and GT. On the contrary, dual-modality nanomedicine lacking CT, GT, or PDT showed fast primary tumor growth, poor metastasis control, or both, respectively. This study reveals the spatiotemporally specific mechanism of CDTNs in treating metastatic TNBC and highlights the importance of combined therapy in treating TNBC.

Comparing Accuracy of Mammography and Magnetic Resonance Imaging for Residual Calcified Lesions in Breast Cancer Patients Undergoing Neoadjuvant Systemic Therapy

BACKGROUND

Neoadjuvant systemic therapy (NST) is performed to increase the rate of breast-conserving surgery in advanced breast cancer patients. Although magnetic resonance imaging (MRI) is accurate in predicting residual cancer, if calcification remains, the issue of whether to perform the surgery on the basis of the residual tumor prediction range in mammography (MMG) or MRI has not yet been elucidated. This study aimed to estimate the accuracy of predicting residual tumor after NST for residual microcalcification on mammographic and enhancing lesion on MRI.

PATIENTS AND METHODS

This was a single-center, retrospective study. We included breast cancer patients who underwent NST, had microcalcifications in the post-NST MMG, and underwent surgery from January 2, 2013 to December 30, 2014 at Asan Medical Center. Patients with post-NST MMG as well as MRI were included. Final pathologic tumor size with histopathology and biomarker status were obtained postoperatively.

RESULTS

In total, 151 patients were included in this study. Overall, MRI correlated better than MMG in predicting the tumor size (intraclass correlation coefficient [ICC], 0.769 vs. 0.651). For hormone receptor (HR)-positive (HR⁺)/HER2^- subtype, MMG had higher correlation than MRI (ICC = 0.747 vs. 0.575). In HR^- subtype, MRI had a strong correlation with pathology (HR^-/HER2⁺ or triple negative (TN), ICC = 0.939 vs. 0.750), whereas MMG tended to overestimate the tumor size (HR^-/HER2⁺ or TN, ICC = 0.543 vs. 0.479).

CONCLUSION

Post-NST residual microcalcifications on MMG have a lower correlation with residual tumor size than MRI. Other than HR⁺/HER2^- subtype, the extent of calcifications on preoperative evaluation might not be accurate in evaluating the residual extent of the tumor after NST.

Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis

Purpose

This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis.

Materials and Methods

Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis.

Results

Low-risk tumors showed significantly lower K^trans and K_epvalues (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. K^trans and K_ep values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers.

Conclusions

The prediction parameter using K^trans, K_ep, and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.

DCE- and DW-MRI as early imaging biomarkers of treatment response in a preclinical model of triple negative breast cancer

This work evaluates quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) parameters as early biomarkers of response in a preclinical model of triple negative breast cancer (TNBC). The standard Tofts' model of DCE-MRI returns estimates of the volume transfer constant (K^trans ) and the extravascular extracellular volume fraction (v_e ). DW-MRI returns estimates of the apparent diffusion coefficient (ADC). Mice (n = 38) were injected subcutaneously with MDA-MB-231. Tumors were grown to approximately 275 mm³ and sorted into the following groups: saline controls, low-dose Abraxane (15 mg/kg) and high-dose Abraxane (25 mg/kg). Animals were imaged at days zero, one and three. On day three, tumors were extracted for immunohistochemistry. The positive percentage change in ADC on day one was significantly higher in both treatment groups relative to the control group (p < 0.05). In addition, the positive percentage change in K^trans was significantly higher than controls (p < 0.05) on day one for the high-dose group and on days one and three for the low-dose group. The percentage change in tumor volume was significantly different between the high-dose and control groups on day three (p = 0.006). Histology confirmed differences at day three through reduced numbers of proliferating cells (Ki67 staining) in the high-dose group (p = 0.03) and low-dose group (p = 0.052) compared with the control group. Co-immunofluorescent staining of vascular maturity [using von Willebrand Factor (vWF) and α-smooth muscle actin (α-SMA)] indicated significantly higher vascular maturation in the low-dose group compared with the controls on day three (p = 0.03), and trending towards significance in the high-dose group compared with controls on day three (p = 0.052). These results from quantitative imaging with histological validation indicate that ADC and K^trans have the potential to serve as early biomarkers of treatment response in murine studies of TNBC.

Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype

Purpose

To investigate associations between the clinicopathologic features and MRI features of triple-negative breast cancer (TNBC) and ER-positive breast cancer (BC) via apparent diffusion coefficient (ADC) histogram analysis.

Materials and methods

In this study, 221 breast cancer patients with pre-operative MRI performed from August 2009 to March 2015 were included in a retrospective analysis. All patients had a pathologically confirmed diagnosis of invasive carcinoma and were grouped into ER-positive (149) or triple-negative (72) subtypes. DWI rim sign and various ADC parameters (mean; mode; 25, 50, and 75 percentiles; skewness; and kurtosis) between ER-positive and TNBC were compared using whole-lesion ADC histogram analysis. Univariate and multivariate regression analyses were used for statistical comparison.

Results

DWI rim signs were detected in 42.3% and 41.7% of ER-positive subtype and TNBC, respectively (P = 0.931). TNBC had poorer histologic grade (P<0.001) and higher Ki-67 expression (P <0.001) than ER-positive subtype BC. TNBC displayed higher ADC parameters (mean, mode, 50th & 75th percentiles, kurtosis on univariate analysis, all P<0.001; only kurtosis on multivariate anaylsis; P<0.001) than ER-positive subtype BC. TNBC had significantly more recurrence events than ER-positive subtype BC on univarate analysis (9.7% (7/72) vs. 2.7% (4/149), P = 0.035).

Conclusion

Poorer clinicopathologic outcomes were found in TNBC. Whole-lesion ADC histogram analysis revealed ADC kurtosis to be higher in TNBC than ER-positive subtype BC.

Rim sign and histogram analysis of apparent diffusion coefficient values on diffusion-weighted MRI in triple-negative breast cancer: Comparison with ER-positive subtype

PURPOSE

To investigate associations between the clinicopathologic features and MRI features of triple-negative breast cancer (TNBC) and ER-positive breast cancer (BC) via apparent diffusion coefficient (ADC) histogram analysis.

MATERIALS AND METHODS

In this study, 221 breast cancer patients with pre-operative MRI performed from August 2009 to March 2015 were included in a retrospective analysis. All patients had a pathologically confirmed diagnosis of invasive carcinoma and were grouped into ER-positive (149) or triple-negative (72) subtypes. DWI rim sign and various ADC parameters (mean; mode; 25, 50, and 75 percentiles; skewness; and kurtosis) between ER-positive and TNBC were compared using whole-lesion ADC histogram analysis. Univariate and multivariate regression analyses were used for statistical comparison.

RESULTS

DWI rim signs were detected in 42.3% and 41.7% of ER-positive subtype and TNBC, respectively (P = 0.931). TNBC had poorer histologic grade (P<0.001) and higher Ki-67 expression (P <0.001) than ER-positive subtype BC. TNBC displayed higher ADC parameters (mean, mode, 50th & 75th percentiles, kurtosis on univariate analysis, all P<0.001; only kurtosis on multivariate anaylsis; P<0.001) than ER-positive subtype BC. TNBC had significantly more recurrence events than ER-positive subtype BC on univarate analysis (9.7% (7/72) vs. 2.7% (4/149), P = 0.035).

CONCLUSION

Poorer clinicopathologic outcomes were found in TNBC. Whole-lesion ADC histogram analysis revealed ADC kurtosis to be higher in TNBC than ER-positive subtype BC.

Dynamic Contrast-Enhanced MRI Perfusion Parameters as Imaging Biomarkers of Angiogenesis

Hypoxia in the tumor microenvironment is the leading factor in angiogenesis. Angiogenesis can be identified by dynamic contrast-enhanced breast MRI (DCE MRI). Here we investigate the relationship between perfusion parameters on DCE MRI and angiogenic and prognostic factors in patients with invasive ductal carcinoma (IDC). Perfusion parameters (K^trans, k_ep and v_e) of 81 IDC were obtained using histogram analysis. Twenty-fifth, 50th and 75th percentile values were calculated and were analyzed for association with microvessel density (MVD), vascular endothelial growth factor (VEGF) and conventional prognostic factors. Correlation between MVD and v_e50 was positive (r = 0.33). K^trans₅₀ was higher in tumors larger than 2 cm than in tumors smaller than 2 cm. In multivariate analysis, K^trans₅₀ was affected by tumor size and MVD with 12.8% explanation. There was significant association between K^trans₅₀ and tumor size and MVD. Therefore we conclude that DCE MRI perfusion parameters are potential imaging biomarkers for prediction of tumor angiogenesis and aggressiveness.

Effect of MR Imaging Contrast Thresholds on Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes: A Subgroup Analysis of the ACRIN 6657/I-SPY 1 TRIAL

Functional tumor volume (FTV) measurements by dynamic contrast-enhanced magnetic resonance imaging can predict treatment outcomes for women receiving neoadjuvant chemotherapy for breast cancer. Here, we explore whether the contrast thresholds used to define FTV could be adjusted by breast cancer subtype to improve predictive performance. Absolute FTV and percent change in FTV (ΔFTV) at sequential time-points during treatment were calculated and investigated as predictors of pathologic complete response at surgery. Early percent enhancement threshold (PEt) and signal enhancement ratio threshold (SER_t) were varied. The predictive performance of resulting FTV predictors was evaluated using the area under the receiver operating characteristic curve. A total number of 116 patients were studied both as a full cohort and in the following groups defined by hormone receptor (HR) and HER2 receptor subtype: 45 HR+/HER2−, 39 HER2+, and 30 triple negatives. High AUCs were found at different ranges of PE_t and SER_t levels in different subtypes. Findings from this study suggest that the predictive performance to treatment response by MRI varies by contrast thresholds, and that pathologic complete response prediction may be improved through subtype-specific contrast enhancement thresholds. A validation study is underway with a larger patient population.

Residual Mammographic Microcalcifications and Enhancing Lesions on MRI After Neoadjuvant Systemic Chemotherapy for Locally Advanced Breast Cancer: Correlation with Histopathologic Residual Tumor Size

PURPOSE

To evaluate the accuracy of residual microcalcifications on mammogram (MG) in predicting the extent of the residual tumor after neoadjuvant systemic treatment (NST) in patients with locally advanced breast cancer and to evaluate factors affecting the accuracy of MG microcalcifications using magnetic resonance imaging (MRI) as a reference.

METHODS

The patients who underwent NST and showed suspicious microcalcifications on MG comprised our study population. Clinicopathologic and imaging (MG, MRI) findings were investigated. Agreement between image findings and pathology was assessed and factors affecting the discrepancy were analyzed.

RESULTS

Among 207 patients, 196 had residual invasive ductal carcinoma or ductal carcinoma-in-situ (mean size, 3.78 cm). The overall agreement of residual microcalcifications on MG predicting residual tumor extents was lower than MRI in all tumor subtypes (intraclass correlation coefficient [ICC] = 0.368 and 0.723, p < 0.0001). The agreement of residual MG microcalcifications and pathology was highest in HR(+)/HER2(+) tumors and lowest in the triple-negative tumors (ICC = 0.417 and 0.205, respectively). Multivariate linear regression analysis revealed that a size discrepancy between microcalcifications and histopathology was correlated with molecular subtype (p = 0.005). In HR(+)/HER2(-) and triple-negative subtypes, the mean extents of residual microcalcification were smaller than residual cancer, and overestimation of tumor extent was more frequent in HR(+)/HER2(+) and HR(-)/HER2(+) tumors.

CONCLUSIONS

The extent of microcalcifications on MG after NST showed an overall lower correlation with the extent of the pathologic residual tumor than enhancing lesions on MRI. The accuracy of residual tumor evaluation after NST with MG and MRI is affected by their molecular subtype.

Evaluation with 3.0-T MR imaging: predicting the pathological response of triple-negative breast cancer treated with anthracycline and taxane neoadjuvant chemotherapy

BACKGROUND

Triple-negative breast cancer (TNBC) which expresses neither hormonal receptors nor HER-2 is associated with poor prognosis and shorter survival. Several studies have suggested that TNBC patients attaining pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) show a longer survival than those without pCR.

PURPOSE

To assess the accuracy of 3.0-T breast magnetic resonance imaging (MRI) in predicting pCR and to evaluate the clinicoradiologic factors affecting the diagnostic accuracy of 3.0-T breast MRI in TNBC patients treated with anthracycline and taxane (ACD).

MATERIAL AND METHODS

This retrospective study was approved by the institutional review board; patient consent was not required. Between 2009 and 2012, 35 TNBC patients with 3.0-T breast MRI prior to (n = 26) or after (n = 35) NAC were included. MRI findings were reviewed according to pCR to chemotherapy. The diagnostic accuracy of 3.0-T breast MRI for predicting pCR and the clinicoradiological factors affecting MRI accuracy and response to NAC were analyzed.

RESULTS

3.0-T MRI following NAC with ACD accurately predicted pCR in 91.4% of TNBC patients. The residual tumor size between pathology and 3.0-T MRI in non-pCR cases showed a higher correlation in the Ki-67-positive TNBC group (r = 0.947) than in the Ki-67 negative group (r = 0.375) with statistical trends (P = 0.069). Pre-treatment MRI in the non-pCR group compared to the pCR group showed a larger tumor size (P = 0.030) and non-mass presentation (P = 0.015).

CONCLUSION

3.0-T MRI in TNBC patients following NAC with ACD showed a high accuracy for predicting pCR to NAC. Ki-67 can affect the diagnostic accuracy of 3.0-T MRI for pCR to NAC with ACD in TNBC patients.

Prognostic Significance of Tumor-Infiltrating Lymphocytes and the Tertiary Lymphoid Structures in HER2-Positive Breast Cancer Treated With Adjuvant Trastuzumab

OBJECTIVES

Tumor-infiltrating lymphocytes (TILs) have prognostic significance in breast cancer. The tertiary lymphoid structure (TLS) is related to the influx of TILs, and expression of major histocompatibility complex (MHC) I in tumor cells is necessary for the effective action of TILs.

METHODS

We retrospectively evaluated the relationship of TILs and TLS and the expression of MHC I in 447 HER2-positive breast cancers treated with chemotherapy and 1 year of trastuzumab.

RESULTS

TILs were more abundant in hormone receptor (HR)-/HER2+ tumors than in HR+/HER2+ tumors. HR-/HER2+ breast cancers with abundant TILs showed a higher histologic grade, the absence of lymphovascular invasion, the presence of peritumoral lymphocytic infiltration, moderate to abundant TLSs in adjacent tissue, and stronger HLA-ABC and HLA-A expression. Abundant TILs and the absence of lymphovascular invasion were found to be good, independent prognostic factors for disease-free survival in patients with HR-/HER2+ breast cancer. The level of TILs was not associated with the patients' prognosis in HR+ tumors.

CONCLUSIONS

Abundant TILs are an independent prognostic factor in HR-/HER2+ breast cancers. Evaluation of TILs in HR-/HER2+ breast cancers may provide valuable information regarding the prognosis of patients treated using adjuvant chemotherapy and trastuzumab.

MRI phenotype of breast cancer: Kinetic assessment for molecular subtypes

PURPOSE

To evaluate the dynamic contrast-enhanced magnetic resonance imaging (MRI) kinetic characteristics of newly diagnosed breast cancer molecular subtypes.

MATERIALS AND METHODS

Breast MRI examinations of 112 patients with newly diagnosed breast cancer were reviewed. Cases of newly diagnosed invasive ductal carcinoma were sorted by molecular subtype (28 TN, 11 HER2 +, 73 Lum A/B) and MRI field strength, with lesion segmentation and kinetic analyses performed on a dedicated workstation. For kinetic assessment, 50% and 100% thresholds were employed for display of medium and rapid uptake. Kinetic profiles in terms of percent volume for six kinetic types (medium-persistent, medium-plateau, medium-washout, fast-persistent, fast-plateau, fast-washout) relative to the whole volume of the lesion were obtained. Statistical analysis of the kinetic profiles was performed using Welch's t-test.

RESULTS

Percent volume of HER2-positive lesions with >100% uptake at early phase on 3T strength MRI exams was significantly greater compared with luminal A/B (93.8 ± 0.92 vs. 77.3 ± 7.2; P < 0.01) and triple negative (93.8 ± 0.92 vs. 81.3 ± 8.2; P < 0.05) subtypes. The >50% early phase uptake for HER2+ lesions was also higher than Lum A/B (99.1 ± 0.73 vs. 93.6 ± 3.05; P < 0.01) at 3T. In the 1.5T subgroup the percent volume of HER2+ tumors with >50% and >100% early phase uptake trended higher than Lum A/B lesions without reaching significance.

CONCLUSION

The percent volume of HER2-positive tumors demonstrating rapid early contrast uptake is significantly increased compared to other molecular subtypes.

Imaging of Tumor Angiogenesis for Radiologists--Part 2: Clinical Utility

Angiogenesis is a key cancer hallmark involved in tumor growth and metastasis development. Angiogenesis and tumor microenvironment significantly influence the response of tumors to therapies. Imaging techniques have changed our understanding of the process of angiogenesis, the resulting vascular performance, and the tumor microenvironment. This article reviews the status and potential clinical value of the imaging modalities used to assess the status of tumor vasculature in vivo, before, during, and after treatment.

Intraindividual, randomized comparison of the macrocyclic contrast agents gadobutrol and gadoterate meglumine in breast magnetic resonance imaging

OBJECTIVES

To compare intraindividually two macrocyclic contrast agents - gadobutrol and gadoterate meglumine (Gd-DOTA) - for dynamic and quantitative assessment of relative enhancement (RE) in benign and malignant breast lesions.

METHODS

This was an ethically approved, prospective, single-centre, randomized, crossover study in 52 women with suspected breast lesions referred for magnetic resonance imaging (MRI). Each patient underwent one examination with gadobutrol and one with Gd-DOTA (0.1 mmol/kg BW) on a 1.5 T system 1 - 7 days apart. Dynamic, T1-weighted, 3D gradient echo sequences were acquired under identical conditions. Quantitative evaluation with at least three regions of interest (ROI) per lesion was performed. Primary endpoint was RE during the initial postcontrast phase after the first and second dynamic acquisition, and peak RE. All lesions were histologically proven; differences between the examinations were evaluated.

RESULTS

Forty-five patients with a total of 11 benign and 34 malignant lesions were assessed. Mean RE was significantly higher for gadobutrol than Gd-DOTA (p < 0.0001). Gadobutrol showed significantly less washout (64.4 %) than Gd-DOTA (75.4 %) in malignant lesions (p = 0.048) CONCLUSIONS: Gadobutrol has higher RE values compared with Gd-DOTA, whereas Gd-DOTA shows more marked washout in malignant lesions. This might improve the detection of breast lesions and influence the specificity of breast MRI-imaging.