DWI is a non-contrast MRI parameter, which measures the random movement of water molecules, i.e., Brownian movement, and depicts the diffusivity of the examined tissues. DWI provides a strong surrogate marker for tissue microstructure, membrane integrity, and cell density, and can be quantified by calculating the apparent diffusion coefficient (ADC) [59]. Changes in tissue water diffusion properties can be helpful for the detection and characterization of pathological processes in any part of the body [59, 60]. New developments in imaging techniques (e.g., parallel imaging) and hardware (stronger gradient systems and multi-channel coils) have overcome previous limitations (susceptibility and respiratory motion artifacts) and DWI has been implemented in oncologic imaging in multiple organs. In general, malignant tissue tends to have more restricted diffusion and lower ADC values compared to normal tissue due to the high cellular density and abundance of intra- and intercellular membranes [61].

DWI for breast cancer diagnosis has been evaluated with encouraging results by numerous studies using different ADC thresholds and b-values [62–64]. Bogner et al. compared the diagnostic quality of DWI schemes with respect to ADC accuracy, ADC precision, and DWI contrast-to-noise ratio (CNR) for different types of lesions and breast tissue at 3 T [65]. They concluded that optimal ADC determination and DWI quality at 3 T was found with a combined b-value protocol of 50 and 850 s/mm², yielding a diagnostic accuracy of 96 % (Fig. 15.2). In a recent meta-analysis including 26 studies, Dorrius et al. [66] confirmed that ADC values of breast lesions are strongly influenced by the choice of b values. For the most accurate differentiation of benign and malignant lesions, the combination of b = 0 and 1000 s/mm² was recommended. Nevertheless, there is a consensus that, in general, breast cancer has lower ADC values compared to healthy breast tissue [43, 62, 67], that the specificity of DWI (75–84 %) is higher than DCE-MRI (67–72 %), and that DWI is a promising imaging biomarker that provides additional functional information to DCE-MRI [68]. DWI also can be easily integrated into a standard MR imaging protocol [11, 13, 69].

Several authors recommended cut-off thresholds to discriminate benign and malignant lesions [65, 69–73]. A very low ADC value (<1.25 × 10⁻³ mm²/s) is specific for malignancy, whereas high ADC values (>1.4 × 10⁻³ mm²/s) are indicative of benignity. Intermediate ADC values are rather unspecific. In a recent study, Spick et al. [74] applied hierarchized ADC thresholds to suspicious breast lesions only visible on DCE MR, and concluded that up to 35 % of MR-guided biopsies could have been omitted when using a high ADC threshold of >1.4 × 10⁻³ mm²/s.

In addition to the differentiation of benign and malignant breast tumors, DWI can potentially be used as a non-invasive biomarker for tumor receptor status and tumor grading. Martinicich et al. [75] found that breast cancers characterized by high cellularity or a higher number of mitoses have lower ADC values. Similar observations have been published about triple-negative breast cancers, which are associated with higher ADC values compared to ER+ and HER2/neu-enriched tumors [76–79]. In contrast, mucinous carcinoma usually presents ADC values similar to benign lesions, most likely due to the presence of both low cellularity and mucin-rich compartments [68]. Bickel et al. evaluated whether ADC with DWI at 3 T can be used as an imaging biomarker to differentiate invasive breast cancer from noninvasive ductal carcinoma in situ (DCIS). In that study, in addition to being used as an imaging biomarker for the diagnosis of breast cancer, ADC seemed to be a valuable noninvasive quantitative biomarker to assess breast cancer invasiveness, and thus, has the potential to reduce over-diagnosis and subsequent over-treatment [80]. Another promising application for DWI is the monitoring of breast cancer treatment. ADC values are very sensitive to changes in tumor cellularity and necrosis. The cytotoxic effect of anticancer drugs increases the Brownian movements in damaged tissues and is reflected by an increase in ADC values which occurs earlier than lesion size changes or vascularity, as measured with DCE-MRI, suggesting DWI can provide a valuable early indication of treatment efficacy [81, 82]. Park et al. [83] studied the potential of DWI in the prediction of response to neo-adjuvant chemotherapy in breast cancer patients. Patients with a low pretreatment ADC tended to respond better to chemotherapy. The best pretreatment ADC cutoff with which to differentiate between responders and nonresponders was 1.17 × 10⁻³ mm²/s, which yielded a sensitivity of 94 % and a specificity of 71 %. Richards et al. [84] found that pretreatment tumor ADC values differed between intrinsic subtypes and were predictive of pathologic response in triple-negative tumors. However, the literature presents divergent results for the assessment of pre-chemotherapy ADC, and more data to fully elucidate the role of ADC as a potential biomarker for predicting the response to neoadjuvant treatment in the breast is warranted [61, 82, 85, 86].

Several advanced modeling approaches for DWI to extract more biologically relevant information are currently under investigation.

MRS is a non-invasive technique that reflects the chemical composition of tissue by providing spatially localized signal spectra with spectral peaks representing the structure and concentration of different chemical compounds in the region of interest. Based on these signal spectra, which provide information about the varying levels of associated detectable metabolites, MRS is able to differentiate tissue conditions such as normal, benign, malignant, necrotic, or hypoxic. It has been demonstrated that, in breast imaging, the additional application of ¹H-MRS aids in the characterization of breast tumors [102, 103]. In breast imaging, the additional value of ¹H-MRS is based on the detection of choline (Cho). The Cho peak observed in vivo is located at approximately 3.2 ppm and is a composite of several different Cho-containing compounds, such as free choline, phosphocholine, and glycerophosphocholine, and is commonly referred to as total Cho (tCho). Cho is involved in cell membrane turnover and is thus considered an imaging biomarker of cell proliferation. In breast cancer, the elevated Cho signal is thought to result from a combination of increased intracellular phosphocholine concentration and increased cell density in the tumor. At low field-strengths, a choline peak is not regularly identified in normal breast tissue [103, 104], and therefore, its presence helps in the differentiation of benign from malignant lesions [105–107]. ¹H-MRS can be performed as single-voxel or multi-voxel MRS. Single-voxel spectroscopy provides a single spatially localized spectrum that represents the average chemical signal from a 3D voxel placed in the lesion detected with DCE-MRI. In multi-voxel MRS using chemical shift, a larger volume is excited, producing a spatially resolved grid of spectra. For a detailed review of acquisition techniques and analysis of breast MRS, refer to a recent review article by Bolan et al. [105]. Assessment of the recorded tCho as an indicator of breast malignancy can be performed either qualitatively—detection of the presence of a tCho peak, semi-quantitatively—measurement of tCho SNR, peak height, or peak integral, or as an absolute quantification—calculation of tCho concentration with water as an internal reference or using an external standard. A detrimental effect of contrast agents on ¹H-MRS has been described in both experimental and clinical settings, and therefore, the possibility of altered tCho signal intensities after contrast medium injection have to be considered when calculating absolute tCho quantification [103, 105, 108, 109]. Due to the challenging image acquisition and post-processing, the clinical value of proton ¹H-MRS remains controversial. Nevertheless, several studies, mainly performed at 1.5 T and using single-voxel approaches, have demonstrated that ¹H-MRS can improve diagnostic accuracy in breast cancer diagnosis [10]. In a recent meta-analysis, which included 19 studies, Baltzer et al. [23] evaluated the diagnostic performance and feasibility of ¹H-MRS for differentiating malignant and benign breast lesions. The pooled sensitivity and specificity of ¹H-MRS was 73 % and 88 %, respectively. There was a substantial heterogeneity of sensitivity in the studies (42–100 %), whereas specificity showed little variation. The meta-analysis did not show any significant performance advantages of 3 T over 1.5 T field strength or multivoxel over single-voxel techniques, or qualitative over quantitative tCho assessments. However the numbers of studies using 3 T (2/19) and MRSI (3/19) were small. ¹H-MRS seems to be limited in the diagnosis of early breast cancer and small breast tumors as well as in non-mass-enhancing lesions.

Recently, Gruber et al. [110] developed a high-spatial-resolution 3D ¹H-MRSI protocol at 3 T, designed to cover a large fraction of the breast in a clinically acceptable measurement time of 12–15 min with excellent data quality (Fig. 15.3). In that study, with a Cho SNR threshold level of 2.6, 3D ¹H-MRSI provided a sensitivity of 97 % and a specificity of 84 % in breast cancer diagnosis.

¹H-MRSI might also be a valuable tool in the assessment of the response to neoadjuvant chemotherapy [102, 111, 112]. Studies indicate that breast tumor tCho levels and the changes in these levels during treatment are reflective of treatment-induced alterations in cell proliferation prior to any changes in tumor size. ¹H-MRSI can, therefore, provide an early predictive imaging biomarker of treatment response. Meisamy et al. demonstrated that MRS of the breast was able to detect a change in Cho concentration from baseline (before receiving chemo) within 24 h of administration of the first dose of the regimen. This change had a statistically significant positive correlation with change in final size (p = 0.001) [104]. In addition, Shin et al. showed that the tCho of tumors was higher in invasive versus in situ cancers and correlated this with several prognostic factors, including nuclear grade, histologic grade, and estrogen receptor (ER) status [106]. Therefore, it can be expected that the addition of 1H-MRSI of the breast will offer a substantial advantage over contrast-enhanced MRI of the breast alone in the prediction of response to neoadjuvant chemotherapy.

In addition, tCho seems to be indicative not only of an increased proliferation, but also a hallmark of imminent malignant transformation [113, 114]. Recently, Ramadan et al. [115] demonstrated that, in BRCA-1 and BRCA-2 carriers, healthy breast tissue is likely to differ from each other as well as from non-mutation carriers with regard to levels of triglycerides, unsaturated fatty acids, and cholesterol in the absence any other imaging findings. Further studies are warranted, but if these findings may be confirmed there might be relevant clinical implications for the screening of high-risk women.

Available data suggests that the addition of functional MRI parameters, in combination with DCE-MRI, may provide additional specificity [23, 24]. Multiparametric MRI of the breast simultaneously and non-invasively acquires multiple imaging biomarkers, and thus, has the potential to significantly improve breast cancer diagnosis, staging, and assessment of treatment response. Several recent studies have assessed multiparametric MRI using DCE-MRI and DWI for breast cancer diagnosis and have demonstrated that an increased diagnostic accuracy in breast cancer diagnosis could be achieved [116, 117]. To solve the dilemma of how to combine the unique information from DCE-MRI and DWI, and to implement multiparametric MRI in the clinical routine, several different approaches have been explored. Pinker et al. [13] developed a reading scheme that adapted ADC thresholds to the assigned BI-RADS® classification. In that study, the sensitivity of the BI-RADS®-adapted reading was not significantly different from the high sensitivity of DCE-MRI (p = 0.4), whereas the BI-RADS®-adapted reading maximized specificity to 89.4 %, which was significantly higher compared to DCE-MRI alone (p < 0.001). The authors concluded that BI-RADS®-adapted reading, combining DCE-MRI and DWI, improves diagnostic accuracy and is fast and easy to use in routine clinical practice (Fig. 15.4). In a different approach, Baltzer et al. [118] investigated the improvements in specificity of breast MRI by integrating ADC values with DCE-MRI using a simple sum score. The additional integration of ADC scores achieved an improved specificity (92.4 %) compared to DCE-MR-only reading (specificity of 81.8 %), with no false-negative results. Pinker et al. compared the diagnostic accuracy of DCE-MRI as a single parameter to multiparametric MRI with two (DCE-MRI and DWI) and three (DCE-MRI, DWI and 1H-MRSI) parameters in breast cancer diagnosis. Multiparametric MRI with three parameters yielded significantly higher AUCs (0.936) compared to DCE-MRI alone (0.814) (p < 0.001). Multiparametric MRI with just two parameters at 3 T did not yield higher AUCs (0.808) than DCE-MRI alone (0.814). Multiparametric MRI with three parameters resulted in elimination of false-negative lesions and significantly reduced the false-positives (p = 0.002) (Figs. 15.5 and 15.6). The authors concluded that multiparametric MRI with three parameters increases the diagnostic accuracy of breast cancer, compared to DCE-MRI alone and MP MRI with two parameters, and should be considered for future implementation in breast cancer care [11].

Recently, the concept of multiparametric imaging has been extended to ultra-high-field MRI. Pinker et al. evaluated the clinical application of multiparametric MRI using DCE-MRI and DWI at 7 T and its impact on diagnostic accuracy in breast cancer diagnosis [12]. Multiparametric MRI, combining high-resolution DCE-MRI and DWI at 7 T, yielded a sensitivity and specificity of 100 % and 88.2 %, respectively, with an AUC of 0.941, which was significantly greater than DCE-MRI (p = 0.003), with a sensitivity and specificity of 100 % and 53.2 %, respectively, with an AUC of 0.765, and greater than DWI, with a sensitivity and specificity of 93.1 % and 88.2 %, respectively, with an AUC of 0.907 (Fig. 15.7). In that study, multiparametric MRI of the breast at 7 T accurately detected all cancers, reduced false-positives from eight with DCE-MRI to two (Fig. 15.8), and thus, could have obviated unnecessary breast biopsies (p = 0.031). In a very recent study, Schmitz et al. investigated multiparametric MRI with three parameters, i.e., DCE-MRI, DWI, and phosphorus spectroscopy (31P MRSI) at 7 T for the characterization of breast cancer [119]. The authors concluded that multiparametric 7 T breast MRI with three parameters is feasible in the clinical setting and shows an association between ADC and tumor grade, and between 31P MRSI and mitotic count.

In their multi-step development, cancers have acquired several biological capabilities, such as sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis,s and activating invasion and metastasis [175–179]. To elucidate these hallmarks of cancer, imaging techniques have to be equally sophisticated and multilayered. Both MP MRI and PET of the breast can visualize different processes involved in cancer development and progression, thus providing morphologic, functional, metabolic, and molecular information about breast tumors. To overcome the individual limitations of morphologic and functional imaging techniques, hybrid imaging systems have been developed and introduced into the clinical routine. Initial studies investigating fused [¹⁸F]FDG PET and DCE-MRI for breast cancer diagnosis demonstrated that fused [¹⁸F]FDG PET/MRI provides accurate morphological and functional data and has the potential to emerge as an all-encompassing alternative to conventional multi-technique tumor staging [180–183]. However, in these studies, the functional information provided by [¹⁸F]FDG PET was merely combined with the morphologic and limited functional information of DCE-MRI. Pinker et al. investigated multiparametric PET/MRI using DCE-MRI, DWI, ¹H-MRSI, and ¹⁸FDG for the assessment of breast tumors at 3 T [184]. The authors demonstrated that MP [¹⁸F]FDG PET/MRI provided an improved differentiation of benign and malignant breast tumors when several MRI and PET parameters are combined. In addition, the authors concluded that MP [¹⁸F]FDG PET/MRI may lead to a reduction of unnecessary breast biopsies of up to 50 % (Fig. 15.11). In a recent feasibility study, Pinker et al. investigated combined PET/MRI of breast tumors in eight patients with DCE-MRI, DWI, the radiotracer [¹⁸F]FDG, and the hypoxia tracer [¹⁸F]FMISO (refer to Sect. 15.5.1) at 3 T (Fig. 15.12), and correlated MRI and PET parameters with pathological features, grading, proliferation-rate (ki67), immuno-histochemistry, and the clinical endpoints metastasis and death. Preliminary results showed several moderate to excellent correlations between quantitative imaging markers, grading, receptor status, and proliferation rate (Fig. 15.13) [185]. Multiparametric criteria provided independent information. DCE-MRI, [¹⁸F]FDG- and [¹⁸F]FMISO-avidity strongly correlated with the presence of metastasis [r = 0.75 (p < 0.01), 0.63 (p = 0.212), and 0.58 (p = 0.093)] and death [r = 0.60 (p = 0.09), 0.62 (p = 0.08), 0.56 (p = 0.11)]. Multiparametric [¹⁸F]FDG /[¹⁸F]FMISO PET/MRI provides quantitative prognostic information in breast cancer patients, and thus, might have the potential to enable tailored therapy through improved risk stratification.