Magnetic resonance in the detection of breast cancers of different histological types

"Pulsed Hypoxia" Gradually Reprograms Breast Cancer Fibroblasts into Pro-Tumorigenic Cells via Mesenchymal-Epithelial Transition

Hypoxia arises in most growing solid tumors and can lead to pleotropic effects that potentially increase tumor aggressiveness and resistance to therapy through regulation of the expression of genes associated with the epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET). The main goal of the current work was to obtain and investigate the intermediate phenotype of tumor cells undergoing the hypoxia-dependent transition from fibroblast to epithelial morphology. Primary breast cancer fibroblasts BrC4f, being cancer-associated fibroblasts, were subjected to one or two rounds of "pulsed hypoxia" (PH). PH induced transformation of fibroblast-shaped cells to semi-epithelial cells. Western blot analysis, fluorescent microscopy and flow cytometry of transformed cells demonstrated the decrease in the mesenchymal markers vimentin and N-cad and an increase in the epithelial marker E-cad. These cells kept mesenchymal markers αSMA and S100A4 and high ALDH activity. Real-time PCR data of the cells after one (BrC4f_Hyp1) and two (BrC4f_Hyp2) rounds of PH showed consistent up-regulation of TWIST1 gene as an early response and ZEB1/2 and SLUG transcriptional activity as a subsequent response. Reversion of BrC4f_Hyp2 cells to normoxia conditions converted them to epithelial-like cells (BrC4e) with decreased expression of EMT genes and up-regulation of MET-related OVOL2 and c-MYC genes. Transplantation of BrC4f and BrC4f_Hyp2 cells into SCID mice showed the acceleration of tumor growth up to 61.6% for BrC4f_Hyp2 cells. To summarize, rounds of PH imitate the MET process of tumorigenesis in which cancer-associated fibroblasts pass through intermediate stages and become more aggressive epithelial-like tumor cells.

Efficacy of breast MRI for surgical decision in patients with breast cancer: ductal carcinoma in situ versus invasive ductal carcinoma

Background

Preoperative breast magnetic resonance imaging (MRI) provides more information than mammography and ultrasonography for determining the surgical plan for patients with breast cancer. This study aimed to determine whether breast MRI is more useful for patients with ductal carcinoma in situ (DCIS) lesions than for those with invasive ductal carcinoma (IDC).

Methods

A total of 1113 patients with breast cancer underwent mammography, ultrasonography, and additional breast MRI before surgery. The patients were divided into 2 groups: DCIS (n = 199) and IDC (n = 914), and their clinicopathological characteristics and oncological outcomes were compared. Breast surgery was classified as follows: conventional breast-conserving surgery (Group 1), partial mastectomy with volume displacement (Group 2), partial mastectomy with volume replacement (Group 3), and total mastectomy with or without reconstruction (Group 4). The initial surgical plan (based on routine mammography and ultrasonography) and final surgical plan (after additional breast MRI) were compared between the 2 groups. The change in surgical plan was defined as group shifting between the initial and final surgical plans.

Results

Changes (both increasing and decreasing) in surgical plans were more common in the DCIS group than in the IDC group (P <  0.001). These changes may be attributed to the increased extent of suspicious lesions on breast MRI, detection of additional daughter nodules, multifocality or multicentricity, and suspicious findings on mammography or ultrasonography but benign findings on breast MRI. Furthermore, the positive margin incidence in frozen biopsy was not different (P = 0.138).

Conclusions

Preoperative breast MRI may provide more information for determining the surgical plan for patients with DCIS than for those with IDC.

Initial experience of dedicated breast PET imaging of ER+ breast cancers using [F-18]fluoroestradiol

Dedicated breast positron emission tomography (dbPET) is an emerging technology with high sensitivity and spatial resolution that enables detection of sub-centimeter lesions and depiction of intratumoral heterogeneity. In this study, we report our initial experience with dbPET using [F-18]fluoroestradiol (FES) in assessing ER+ primary breast cancers. Six patients with >90% ER+ and HER2- breast cancers were imaged with dbPET and breast MRI. Two patients had ILC, three had IDC, and one had an unknown primary tumor. One ILC patient was treated with letrozole, and another patient with IDC was treated with neoadjuvant chemotherapy without endocrine treatment. In this small cohort, we observed FES uptake in ER+ primary breast tumors with specificity to ER demonstrated in a case with tamoxifen blockade. FES uptake in ILC had a diffused pattern compared to the distinct circumscribed pattern in IDC. In evaluating treatment response, the reduction of SUVmax was observed with residual disease in an ILC patient treated with letrozole, and an IDC patient treated with chemotherapy. Future study is critical to understand the change in FES SUVmax after endocrine therapy and to consider other tracer uptake metrics with SUVmax to describe ER-rich breast cancer. Limitations include variations of FES uptake in different ER+ breast cancer diseases and exclusion of posterior tissues and axillary regions. However, FES-dbPET has a high potential for clinical utility, especially in measuring response to neoadjuvant endocrine treatment. Further development to improve the field of view and studies with a larger cohort of ER+ breast cancer patients are warranted.

Discrimination between breast invasive ductal carcinomas and benign lesions by optimizing quantitative parameters derived from dynamic contrast-enhanced MRI using a semi-automatic method

BACKGROUND

To propose a semi-automatic method for distinguishing invasive ductal carcinomas from benign lesions on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

METHODS

142 cases were included. In the conventional method, the region of interest for a breast lesion was drawn manually and the corresponding mean time-signal intensity curve (TIC) was qualitatively categorized. Only one quantitative parameter was obtained: the maximum slope of increase (MSI). By contrast, the proposed method extracted the suspicious breast lesion semi-automatically. Besides MSI, more quantitative parameters reflecting perfusion information were derived from the mean TIC and lesion region, including the signal intensity slope (SI_slope), initial percentage of enhancement, percentage of peak enhancement, early signal enhancement ratio, and second enhancement percentage. The mean TIC was categorized quantitatively according to the value of SI_slope. Regression models were established. The diagnostic performance differed between the new and conventional methods according to the Wilcoxon rank-sum test and receiver operating characteristic analysis.

RESULTS

According to the TIC categorization results, the accuracies of the traditional and the new method were 59.16% and 76.05%, respectively (P < 0.05). The accuracy was 63.35% for MSI, which was derived from the manual method. For the semi-automatic method, the accuracies were 81.0% and 78.9% for the lesion region and the corresponding mean TIC regression models, respectively.

CONCLUSIONS

The results demonstrate that our proposed semi-automatic method is beneficial for discriminating breast IDCs and benign lesions based on DCE-MRI, and this method should be considered as a supplementary tool for subjective diagnosis by clinical radiologists.

Magnetic Resonance Angiography Shows Increased Arterial Blood Supply Associated with Murine Mammary Cancer

Breast cancer is a major cause of morbidity and mortality in Western women. Tumor neoangiogenesis, the formation of new blood vessels from pre-existing ones, may be used as a prognostic marker for cancer progression. Clinical practice uses dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to detect cancers based on increased blood flow and capillary permeability. However, DCE-MRI requires repeated injections of contrast media. Therefore we explored the use of noninvasive time-of-flight (TOF) MR angiography for serial studies of mouse mammary glands to measure the number and size of arteries feeding mammary glands with and without cancer. Virgin female C3(1) SV40 TAg mice (n=9), aged 18-20 weeks, were imaged on a 9.4 Tesla small animal scanner. Multislice T₂-weighted (T2W) images and TOF-MRI angiograms were acquired over inguinal mouse mammary glands. The data were analyzed to determine tumor burden in each mammary gland and the volume of arteries feeding each mammary gland. After in vivo MRI, inguinal mammary glands were excised and fixed in formalin for histology. TOF angiography detected arteries with a diameter as small as 0.1 mm feeding the mammary glands. A significant correlation (r=0.79; p< 0.0001) was found between tumor volume and the arterial blood volume measured in mammary glands. Mammary arterial blood volumes ranging from 0.08 mm³ to 3.81 mm³ were measured. Tumors and blood vessels found on in vivo T2W and TOF images, respectively, were confirmed with ex vivo histological images. These results demonstrate increased recruitment of arteries to mammary glands with cancer, likely associated with neoangiogenesis. Neoangiogenesis may be detected by TOF angiography without injection of contrast agents. This would be very useful in mouse models where repeat placement of I.V. lines is challenging. In addition, analogous methods could be tested in humans to evaluate the vasculature of suspicious lesions without using contrast agents.

Discrimination between malignant and benign mass-like lesions from breast dynamic contrast enhanced MRI: semi-automatic vs. manual analysis of the signal time-intensity curves

Purpose: To investigate the performance of a new semi-automatic method for analyzing the signal time-intensity curve (TIC) obtained by breast dynamic contrast enhancement (DCE)-MRI.

Methods: In the conventional method, a circular region of interest was drawn manually onto the map reflecting the maximum slope of increase (MSI) to delineate the suspicious lesions. The mean TIC was determined subjectively as one of three different wash-out patterns. In the new method, the lesion area was identified semi-automatically. The mean TIC was categorized quantitatively. In addition to the MSI, other quantitative parameters were calculated, including the signal intensity slope (SI_slope), initial percentage of enhancement (E_initial), percentage of peak enhancement (E_peak), early signal enhancement ratio (ESER), and second enhancement percentage (SEP). The performances were compared with receiver operating characteristic (ROC) analysis and Wilcoxon's test.

Results: For TIC categorization results, the diagnostic accuracy rates were 61.54% with the traditional manual method and 76.92% with the new method. For the mean MSI values from the manual method, the accuracy was 63.41%. For the mean TIC derived using the semi-automatic method, the diagnostic accuracy were 82.05% for SI_slope, 67.31% for MSI, 61.53% for E_initial, 64.75% for E_peak, 64.74% for ESER, and 52.56% for SEP, respectively. For the lesion regions identified by the semi-automatic method, the diagnostic accuracy for above mentioned parameters were 80.13%, 69.87%, 61.54%, 63.47%, 64.74% and 55.13%, respectively.

Conclusion: With respect to the analysis of TIC from breast DCE-MRI, the results demonstrated that the new method increased the diagnostic accuracy, and should be considered as a supplementary tool for distinguishing benign and malignant lesions.

Quantitative discrimination between invasive ductal carcinomas and benign lesions based on semi-automatic analysis of time intensity curves from breast dynamic contrast enhanced MRI

Background

Traditional subjective method for the analysis of time-intensity curves (TICs) from breast dynamic contrast enhanced MRI (DCE-MRI) presented a low specificity. Hence, a semi-automatic quantitative method was proposed and evaluated for distinguishing invasive ductal carcinomas from benign lesions.

Materials and methods

In the traditional method, the lesion was extracted by placing a region of interest (ROI) manually. The mean curve of the TICs from the ROI was subjectively classified as one of three patterns. Only one quantitative parameter, the mean value of maximum slope of increase (MSI), was provided. In the new method, the lesion was identified semi-automatically, and the mean curve was classified quantitatively. Some additional parameters, the signal intensity slope (SI_slope), initial percentage of enhancement (E_initial), percentage of peak enhancement (E_peak), early signal enhancement ratio (ESER), and second enhancement percentage (SEP) were derived from the mean curves as well as the lesion areas. Wilcoxon’s test and receiver operating characteristic (ROC) analyses were performed, and P < 0.05 was considered significant.

Results

According to the TIC classification results, the accuracies were 59.16% for the traditional manual method and 76.05% for the new method (P < 0.05). For the mean MSI values from the manual method, the accuracy was 63.35%. For the mean TICs derived from the semi-automatic method, the accuracies were 77.47% for SI_slope, 65.24% for MSI, 58.45% for E_initial, 66.20% for E_peak, 71.83% for ESER, and 54.93% for SEP, respectively. For the lesion regions identified by the semi-automatic method, the accuracies were 73.24%, 72.54%, 58.45%, 62.68%, 64.09%, and 55.64%, respectively.

Conclusion

Compared with traditional subjective method, the semi-automatic quantitative method proposed in this study showed a higher performance, and should be used as a supplementary tool to aid radiologist's subjective interpretation.