Abstract

Breast cancer is the second leading cause of cancer death among US women, and the chance of a woman developing breast cancer sometime during her lifetime is one in eight. Early detection and diagnosis to allow appropriate locoregional and systemic treatment are key to improve the odds of surviving its diagnosis. Emerging data also suggest that different breast cancer subtypes (phenotypes) may respond differently to available adjuvant therapies. There is a growing understanding that not all patients benefit equally from systemic therapies, and therapeutic approaches are being increasingly personalized based on predictive biomarkers of clinical benefit. Optimal use of established and novel radiological imaging methods, such as magnetic resonance imaging and positron emission tomography, which have different biophysical mechanisms can simultaneously identify key functional parameters. These methods provide unique multiparametric radiological signatures of breast cancer, that will improve the accuracy of early diagnosis, help select appropriate therapies for early stage disease, and allow early assessment of therapeutic benefit.

Patients with early stage breast cancer have a reasonable chance of surviving their diagnosis. The key to effective treatment to reduce mortality is early detection to allow appropriate locoregional therapy and selection of systemic therapies most likely to improve survival. In view of an improved understanding of predictive biomarkers of clinical benefit for certain breast cancer phenotypes, and the need to evaluate early on clinical benefit, in 2012 the US Food and Drug Administration released a draft guidance for industry on the use of preoperative systemic therapy and response assessment at surgery as a path toward drug approval for early stage breast cancer (1).

A fundamental challenge for determining early treatment response in breast cancer is characterizing the underlying tumor microenvironment during the initial treatment cycles, and developing a tissue signature of these characteristics for accurate diagnosis. Remarkable progress has recently occurred in the diagnosis and detection of breast cancer, using advanced radiological imaging, and these methods may allow a more efficient monitoring of treatment response. As an example, the use of advanced functional magnetic resonance imaging (MRI) and positron emission tomography (PET) parameters appears to offer insight into biological changes in the tumor during treatment. Consequently, there is a critical need to develop noninvasive radiological methods to directly visualize treatment effects and provide metrics to determine early on the efficacy of new molecularly targeted cancer therapies. Current treatment response metrics for imaging using bi-dimensional tumor measurements, like the REsponse Criteria in Solid Tumors (RECIST) criteria (2,3), are suboptimal for evaluating treatment response as they do not allow the assessment of functional tumor parameters of the tumor that occur before anatomical changes become apparent (4,5).

Breast lesions are also heterogeneous and are composed of phenotypically and functionally distinct cell populations. This heterogeneity results in different radiological image characteristics that could be explored clinically, and functional MRI parameters with biological significance are needed to better discern these tumor characteristics. Malignant lesions commonly show a rapid uptake of contrast agent, followed by washout due to increased vascularity and permeability, and dynamic contrast-enhanced (DCE)-MRI can image this behavior. Diffusion-weighted imaging (DWI), with the apparent diffusion coefficient of water (DWI/ADC), can also provide functional and metabolic information about the changes in the diffusion of endogenous water molecules within the intra- and intercellular environments. The ADC map can then be used as a quantitative biophysical parameter derived from DWI, and a measure of cellularity of the lesion, such that a decreased ADC value indicates restricted diffusion (high cellularity), whereas, an increased ADC value indicates little or no restricted diffusion of water. As another example, the standard uptake value (SUV) derived from PET imaging provides a measure of the glycolic rate of the tumor. Consequently, these and other potential functional radiological metrics may allow a more accurate real-time assessment of underlying tumor pathophysiology. These can then be explored for diagnostic and treatment monitoring purposes, such as for the early assessment of response to neoadjuvant systemic therapies.

Breast Cancer Detection and Diagnosis Methods

Clinical radiological methods for the detection and diagnosis of breast abnormalities are X-ray mammography, ultrasound, MRI, and PET. Breast MRI has a high sensitivity (~95%) and a moderate specificity (~85) using DCE pulse sequences (6). Other modalities, such as PET, are used for systemic staging and evaluation of potentially metastatic disease outside the primary tumor site using different radiotracers (7,8). Recent technology developments have to led to a “localized” PET device termed positron emission mammography to unilateral image breast tissue (9,10). These high-resolution devices can be as accurate as MRI and may be of great use in patients who cannot undergo MRI for safety reasons.

Multiparametric Breast Imaging

Typical clinical breast MRI protocols include T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and fat-suppressed T1 DCE sequences using gadolinium chelates. High-resolution gadolinium-enhanced images together with DCE MRI are main components of breast MRI and is used to differentiate benign from malignant lesions based on the uptake, distribution, and wash out of the contrast agent (11–13). In addition, with the recent introduction of advanced MRI sequences, such as DWI, magnetic resonance spectroscopy (MRS), sodium (23Na), and pharmacokinetic (PK) DCE MRI, we can begin to explore multiparametric approaches for breast imaging to investigate the molecular underpinning of the breast parenchyma and the tumor microenvironment (14–17). Specifically, these newer methods can provide information about the vascularity, cellularity, biochemical, and molecular-level environment of the tumor before and after systemic therapy, as detailed below and shown in Figure 1.

Figure 1.

A representative multiparametric breast MRI dataset on a 43-y-old woman with a triple-negative cT3N1 invasive ductal carcinoma. The MRI sagittal sequences include T1- and T2-weighted imaging (T1WI and T2WI) and functional sequences of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping, PK-DCE-MRI, and sodium images. Top row: T1WI with DWI images at different b values (b = 500–1000 second/mm2). Middle row: T2WI with ADC maps, PK-DCE MRI and sodium images demonstrating the different lesion characteristics. Bottom row: Enlarged regions of the breast lesion, which shows the excellent characterization of the two lesions obtained with the functional MRI. The ADC map demonstrates that there are two distinct regions, one with a necrotic core that has high ADC map values (2.5±0.29×10−3 mm2/second), high sodium values (105mM), and peripheral rim enhancement on the DCE MRI (inferior mass). Whereas, there is low ADC map values (1.05±0.20×10−3 mm2/second), high sodium values (79mM) and increased PK-DCE uptake within the superior mass. PK-DCE MRI, pharmacokinetic-dynamic contrast-enhanced magnetic resonance imaging.

Figure 1.

A representative multiparametric breast MRI dataset on a 43-y-old woman with a triple-negative cT3N1 invasive ductal carcinoma. The MRI sagittal sequences include T1- and T2-weighted imaging (T1WI and T2WI) and functional sequences of diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) mapping, PK-DCE-MRI, and sodium images. Top row: T1WI with DWI images at different b values (b = 500–1000 second/mm2). Middle row: T2WI with ADC maps, PK-DCE MRI and sodium images demonstrating the different lesion characteristics. Bottom row: Enlarged regions of the breast lesion, which shows the excellent characterization of the two lesions obtained with the functional MRI. The ADC map demonstrates that there are two distinct regions, one with a necrotic core that has high ADC map values (2.5±0.29×10−3 mm2/second), high sodium values (105mM), and peripheral rim enhancement on the DCE MRI (inferior mass). Whereas, there is low ADC map values (1.05±0.20×10−3 mm2/second), high sodium values (79mM) and increased PK-DCE uptake within the superior mass. PK-DCE MRI, pharmacokinetic-dynamic contrast-enhanced magnetic resonance imaging.

Advanced Breast MRI Sequences

Dynamic and PK Contrast Enhancement and MRI

Breast lesions undergo angiogenesis and develop an increased vascular supply to support their growth. This growth leads to tumors that are heterogeneous and have different physiological characteristics than normal breast glandular tissue, which can be evaluated by DCE-MR.

The vascular profile of breast tissue after contrast uptake involves several different qualitative or semiqualitative metrics. For example, the shape of the signal intensity time curve, calculation of the maximum enhancement, and time-to-peak enhancement are used to classify the morphology of the lesion (13). In addition, PK modeling approaches can quantify the tumor blood flow, tumor microvasculature, and capillary permeability (18,19). Specifically, different vascular parameters can be obtained, such as the rate of maximum enhancement, which is reflective of the vascular volume and the permeability of the vessels, while the magnitude of enhancement reflects the extravascular/extracellular leakage space. PK DCE MRI provides quantitative metrics of the volume transfer constant which characterize the transfer of gadolinium from the plasma (Ktrans [min−1]), the fractional volume of the extracellular extravascular space (EVF), that is, the leakage (ve [%]), and the transfer rate constant (kep [min−1]), which describes the reflux of the contrast agent from the extravascular extracellular compartment into the plasma compartment. These parameters are related by the mathematical formula (kep = Ktrans/ve) and recent studies have shown that they are useful in developing a vascular profile of the tumor. Several reports have begun to combine the architectural and dynamic features obtained with PK DCE-MR, with promising results that provide important functional information (20–22).

Diffusion-Weighted Imaging

DWI can bring valuable information in addition to other imaging parameters. Moreover, DWI also provides an important quantitative biophysical parameter, called the ADC of water. The ADC is an indicator of the movement of water within the tissue and provides an average value of the flow and distance a water molecule has moved which is related to the pathophysiology of the tumor. A low ADC reflects a “reduced” (restricted) flow of water, whereas an high ADC indicates no restricted water flow within the tissue. The ADC map will reflect these changes and serve as a radiological biomarker of the tissue response to treatment (23,24). These changes on DWI are seen before they are apparent on anatomical imaging (23,25). In general, water movement can be restricted by compacted or proliferating cells, which enables the ADC to be a marker of tumor density or cellularity, such that, a highly cellular region will have low ADC and an area with low cellularity will exhibit a high ADC value. This phenomenon has been demonstrated in several studies to differentiate between benign and malignant lesions (26,27) and metastatic lesions (28). Moreover, recent reports have confirmed that the ADC is a valuable radiological marker of treatment response in breast cancer (29,30). Thus, integrating DWI in a breast imaging treatment protocol is very important.

Magnetic Resonance Spectroscopy

Magnetic Resonance Spectroscopy (MRS) provides important information about the biochemical and metabolic environment of breast tissue, where concentrations of water, choline (Cho), lactate, creatine (Cr), and lipids can be detected in breast tissue. The typical spectroscopic profile for breast tissue consists of water (4.7 parts per million [ppm], choline (Cho, 3.2 ppm), creatine (Cr, 3.0 ppm), and lipids (1.3 ppm). MRS can demonstrate differences between the metabolic profile of normal tissue and the tumor environment. For example, studies have indicated that increased choline signal or concentration is considered the spectroscopic hallmark of cancer (31), whereas little or no Cho is evidence of normal tissue (32,33). Choline-containing compounds are involved in membrane turnover (phospholipid synthesis and degradation) and consist of several compounds, including phosphocholine, glycerophosphocholine, and free choline. Moreover, changes in the concentration of Cho are increasingly being used as an intermediate radiological biomarker for the detection and monitoring of treatment response. Since Cho is involved in membrane turnover, treatment response can be seen within 24 hours to 1 week after the first cycle of chemotherapy (34–38).

Sodium MRI

Sodium (Na) is abundant in most tissues and has important biological implications. Sodium is a potentially sensitive indicator of cellular integrity, and therefore, could be useful in assessing the therapeutic response to interventions that disrupt the cellular structure, such as targeted therapeutics. For example, tumor growth generates a change in intracellular metabolism as part of the signaling mechanism that initiates cell division in the microenvironment of the tumor. These changes in tumor and the surrounding tissue result in an increased intracellular Na+ concentration, Na+/H+ transporter, and Na+/K+-ATP-ase activity, and have been linked to tumor malignancy (39,40). These changes in the cellular level sodium concentration within different tissue types after treatment must be monitored by advanced MRI methods (38,41). Thus, sodium MRI methods will have immense potential value for the molecular assessment of tissue to determine treatment response in patients.

PET and Computed Tomography

PET/computed tomography (CT) imaging is an effective method to determine treatment response in breast cancer using glucose analog 18F fluorodeoxyglucose (18FDG), because tumors have increased glucose metabolism (7,42). After injection of 18FDG, the SUVlean within the tumor region is determined by the signal intensity on the PET scans, and serves as a metric of glucose utilization and is linked to tumor type and pathological status. In general, an SUVlean unit of one is considered normal, whereas, an SUVlean unit greater than approximately 2.5 is considered suspicious of malignancy and needs clinical correlation, especially if uptake is focal. Visual patterns and absolute uptake are important parameters to assess the breast for the presence of cancer. Other radiotracers, such as 18fluorothymidine, have been used to measure treatment response based on the proliferation of cells in tumors, notably thymidine kinase activity (43,44), and perfusion tracers (15O should be Oxygen-water) are being investigated in combination with 18FDG, with some success (45,46). In addition, a new PET response metric has been developed [the PET Response Criteria in Solid Tumors or PERCIST, Wahl et al. (47)], which if validated may allow the functional assessment of early metabolic changes and treatment response in patients receiving primary systemic therapy.

Whole-Body Multiparametric MRI and PET/CT in Metastatic Disease

Recent technological developments in MRI technology, including gradient systems, radiofrequency coils, and “rolling bed” methods have changed the paradigm from “local” to “whole-body” imaging; thus, whole-body MRI has been introduced as a new and much sought after concept (28,48,49). As noted above, recent studies have shown that DWI with ADC mapping can provide valuable information along with radiological imaging methods, and potentially provide a new functional metric for the detection and evaluation of treatment response in metastatic disease. Current efforts are underway to implement and use whole-body-MRI (DWI and T2WI) with PET/CT for the investigation and characterization of metastatic lesions in patients. We demonstrate these methods in a metastatic breast patient in Figure 2.

Figure 2.

Top row: Typical multiparametric radiological data of WB-MRI (T2WI and DWI/ADC mapping) and PET/CT on a 47-y-old woman with progressive metastatic breast cancer. The WB-DWI with ADC mapping in left iliac show the metastatic lesions. Bottom row: Excellent delineation of the lesions are noted on the MRI and PET/CT images (enlarged views). The ADC values in the pelvic metastatic lesions (white arrows) were at/above 1.1±0.13×10−3 mm2/second with ADC map values in the normal right iliac (yellow arrows) of 0.44±0.23×10−3 mm2/second. Corresponding PET/CT images confirm the metastatic lesions had elevated SUVlean values. These whole-body methods demonstrate the power of using multimodality imaging to detect and characterize metastatic lesions. Note additional metastases in the liver (white arrows, top row). ADC = apparent diffusion coefficient; DWI = diffusion-weighted imaging; PET/CT = positron emission tomography/computed tomography; SUV = standard uptake value; WB-MRI = whole-body magnetic resonance imaging.

Figure 2.

Top row: Typical multiparametric radiological data of WB-MRI (T2WI and DWI/ADC mapping) and PET/CT on a 47-y-old woman with progressive metastatic breast cancer. The WB-DWI with ADC mapping in left iliac show the metastatic lesions. Bottom row: Excellent delineation of the lesions are noted on the MRI and PET/CT images (enlarged views). The ADC values in the pelvic metastatic lesions (white arrows) were at/above 1.1±0.13×10−3 mm2/second with ADC map values in the normal right iliac (yellow arrows) of 0.44±0.23×10−3 mm2/second. Corresponding PET/CT images confirm the metastatic lesions had elevated SUVlean values. These whole-body methods demonstrate the power of using multimodality imaging to detect and characterize metastatic lesions. Note additional metastases in the liver (white arrows, top row). ADC = apparent diffusion coefficient; DWI = diffusion-weighted imaging; PET/CT = positron emission tomography/computed tomography; SUV = standard uptake value; WB-MRI = whole-body magnetic resonance imaging.

Multiparametric and Multimodality Imaging of Treatment Response in Breast Cancer Patients

Monitoring preoperative chemotherapy in operable breast cancers remains a challenge. Fortunately, the ability to distinguish early response to treatment using radiological imaging is offering new hope in meeting this challenge and characterizing the tumor and surrounding tissue. Several studies have offered preliminary evidence that single-modality approaches, either MRI or PET/CT, provide potentially valuable information that can be used in the characterization of treatment response using the pathological response as an endpoint. For example, using DCE-MRI as a marker of the vascularity of the tumor and early treatment response, a recent meta-analysis showed that DCE metrics had a sensitivity of 68% and a specificity of 91%, with likelihood ratios (LR) of LR+ (7.48) and LR− (0.36) (29). Similar results were shown in another study, where DCE-MRI tumor volume had a response prediction rate of greater than 65%, and the rate of prediction with Ktrans rate was 85% (22,50). In addition, the use of DWI/ADC mapping in monitoring treatment response in breast cancer has a high sensitivity and specificity. In particular, increases in the ADC value after the first round of chemotherapy are indicative of response, as reflected by changes in the cellularity and water diffusivity. A meta-analysis of several studies has shown that this effect of increased ADC value is consistent with pathological response, with sensitivity of 93% and a specificity of 82%. Moreover, the LR were significant [LR+ = 5.09 and LR− = 0.090 (29,51)]. This is consistent with our data in patients with operable disease (Figure 3).

Figure 3.

Demonstration of functional MRI and PET/CT in a 53 year old woman with locally advanced breast cancer undergoing primary systemic treatment (PST). A) Baseline imaging for evaluation and staging of the lesion before PST. The ADC map values in glandular tissue were; ADC = 1.8±0.24×10−3 mm2/second and within the lesion, ADC = 0.85±0.29×10−3 mm2/second. The PK-DCE demonstrated increased Ktrans values (see Part C-upper right) with a RECIST measure of 6.5cm. The SUVlean determined from the PET was elevated (SUVlean = 9.3). B) Similar imaging was performed on day 7–8 after the first cycle of treatment. Clear radiological response is noted, increased ADC map values within the lesion (68%: ADC = 1.4±0.39×10−3 mm2/second) with decreased Ktrans values and generalized decreased contrast uptake. The RECIST measure decreased by 15% (5.5cm). C) There is a shift of the Ktrans values from high to low regions, and of the extravascular fraction (EVF) from low to high regions in the joint histogram, and also on the color maps from PK-DCE of the breast lesion the tumor displayed mostly high permeability red voxels before treatment and mostly green voxels (decreasing permeability and increasing EVF) after treatment. At surgery, this patient was a pathological partial responder (pCR) with 0.6cm residual tumor. ADC = apparent diffusion coefficient; PET/CT = positron emission tomography/computed tomography; PK-DCE MRI = pharmacokinetic-dynamic contrast-enhanced magnetic resonance imaging; SUV = standard uptake value.

Figure 3.

Demonstration of functional MRI and PET/CT in a 53 year old woman with locally advanced breast cancer undergoing primary systemic treatment (PST). A) Baseline imaging for evaluation and staging of the lesion before PST. The ADC map values in glandular tissue were; ADC = 1.8±0.24×10−3 mm2/second and within the lesion, ADC = 0.85±0.29×10−3 mm2/second. The PK-DCE demonstrated increased Ktrans values (see Part C-upper right) with a RECIST measure of 6.5cm. The SUVlean determined from the PET was elevated (SUVlean = 9.3). B) Similar imaging was performed on day 7–8 after the first cycle of treatment. Clear radiological response is noted, increased ADC map values within the lesion (68%: ADC = 1.4±0.39×10−3 mm2/second) with decreased Ktrans values and generalized decreased contrast uptake. The RECIST measure decreased by 15% (5.5cm). C) There is a shift of the Ktrans values from high to low regions, and of the extravascular fraction (EVF) from low to high regions in the joint histogram, and also on the color maps from PK-DCE of the breast lesion the tumor displayed mostly high permeability red voxels before treatment and mostly green voxels (decreasing permeability and increasing EVF) after treatment. At surgery, this patient was a pathological partial responder (pCR) with 0.6cm residual tumor. ADC = apparent diffusion coefficient; PET/CT = positron emission tomography/computed tomography; PK-DCE MRI = pharmacokinetic-dynamic contrast-enhanced magnetic resonance imaging; SUV = standard uptake value.

Moreover, other MRI metrics (MRS and sodium MRI) have been shown to be useful in characterizing treatment response. Significant decreases (>40%) in choline within the tumor have been reported in several studies after the first or second cycle of treatment, with high sensitivities (86%–90%) and specificities (~91%) in detecting responders from nonresponders (35–38,52). Some of these changes in choline levels were noted within 24 hours of treatment, and, in most cases, only the responders had large declines in choline (35). Finally, a few studies have looked at the sodium concentration in patients undergoing PST, where the changes in sodium concentration after the first cycle of treatment was predictive of pathological response (38).

Similar reports have shown that changes in the SUV derived from PET are predictive of response. Indeed, large decreases in the SUV have been noted after the first and second cycles of treatment, with the largest after the second cycle (7,51,53). Predictive response rates range from 16% to 29%, with sensitivities between 64% and 91% and specificities of 53%–74% (53–56). Moreover, with the development of a new PET response marker, PERCIST, the use of the SUV could become a standardized measure of treatment response (47). However, there are still some questions regarding the timing and the cutoff values of the SUV during treatment and this is still being explored. But, the evidence indicates that the best response rates can be determined after the second cycle of treatment (53,54).

The potential and real advantage of using advanced radiological imaging methods lies in the combination of MRI and PET to obtain the most information possible about the early treatment response in patients (Figures 2 and 3). For example, when combining MRI and PET, we can exploit the best of each modality’s characteristics to better understand both normal tissue behavior and tumor response to treatment. A few studies have investigated the use of combined MRI and PET to monitor and assess residual disease in locally advanced breast cancer during PST (41,51,57–61). In these studies, there were significant decreases in the MRI and SUV metrics in responders compared with nonresponders. Other studies have used histological metrics (Ki67) and lesion phenotypes, and found significant correlation to changes in the radiological parameters in patients (41,56,62). Taken together, the results demonstrate the feasibility of using multiparametric MRI and PET/CT metrics as radiological biomarkers for monitoring response to PST in patients with operable breast cancer.

Conclusion

In summary, diagnostic tools with greater accuracy and more effective estimates of early therapeutic benefit are needed to further improve the odds of surviving breast cancer. New approaches that combine functional metrics derived from multiparametric MRI and multimodality PET/CT imaging are being actively pursued. These methods offer the potential for a comprehensive evaluation and the development of a tissue signature of the complex tumor microenvironment, and many are now undergoing clinical testing as main endpoints of prospective clinical trials testing neoadjuvant therapies. These methods allow the evaluation of early changes in vascularity and cellularity, along with biochemical changes and glucose metabolism that may precede standard morphological changes. These measures, once properly evaluated regarding their clinical utility, maybe in the future become important tools in our goal of developing more personalized treatments for specific breast cancer subtypes and improve long-term survival outcomes.

Funding

This work was supported by the National Institutes of Health grant numbers: P50CA103175, 5P30CA006973 (IRAT), U01CA070095, U01CA140204 and Siemens Medical Grant: JHU-2012-MR-86-01-36819.

We thank the reviewers for their comments and Mary McAllister, MA for her assistance.

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