Diffusion-tensor MR imaging of the breast: hormonal regulation

MRI of the Lactating Breast

The breasts undergo marked physiologic changes during lactation that can make conventional imaging evaluation with mammography and US challenging. MRI can be a valuable diagnostic aid to differentiate physiologic and benign processes from malignancy in patients who are lactating. In addition, MRI may allow more accurate delineation of disease involvement than does conventional imaging and assists in locoregional staging, screening of the contralateral breast, assessment of response to neoadjuvant chemotherapy, and surgical planning. Although the American College of Radiology recommends against patients undergoing contrast-enhanced MRI during pregnancy because of fetal safety concerns, contrast-enhanced MRI is safe during lactation. As more women delay childbearing, the incidence of pregnancy-associated breast cancer (PABC) and breast cancer in lactating women beyond the 1st year after pregnancy is increasing. Thus, MRI is increasingly being performed in lactating women for diagnostic evaluation and screening of patients at high risk. PABC is associated with a worse prognosis than that of non-PABCs, with delays in diagnosis contributing to an increased likelihood of advanced-stage disease at diagnosis. Familiarity with the MRI features of the lactating breast and the appearance of various pathologic conditions is essential to avoid diagnostic pitfalls and prevent delays in cancer diagnosis and treatment. The authors review clinical indications for breast MRI during lactation, describe characteristic features of the lactating breast at MRI, and compare MRI features of a spectrum of benign and malignant breast abnormalities. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Chikarmane in this issue.

Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy

BACKGROUND

Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST).

PURPOSE

To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST.

STUDY TYPE

Prospective.

POPULATION

Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR).

FIELD STRENGTH/SEQUENCE

3.0 T/reduced field of view single-shot echo-planar DTI sequence.

ASSESSMENT

Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery.

STATISTICAL TESTS

Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant.

RESULTS

47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s).

DATA CONCLUSION

Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 4.

Ultrafast DCE-MRI for discriminating pregnancy-associated breast cancer lesions from lactation related background parenchymal enhancement

OBJECTIVE

To investigate the utility of ultrafast dynamic-contrast-enhanced (DCE) MRI in visualization and quantitative characterization of pregnancy-associated breast cancer (PABC) and its differentiation from background-parenchymal-enhancement (BPE) among lactating patients.

MATERIALS AND METHODS

Twenty-nine lactating participants, including 10 PABC patients and 19 healthy controls, were scanned on 3-T MRI using a conventional DCE protocol interleaved with a golden-angle radial sparse parallel (GRASP) ultrafast sequence for the initial phase. The timing of the visualization of PABC lesions was compared to lactational BPE. Contrast-noise ratio (CNR) was compared between the ultrafast and conventional DCE sequences. The differences in each group's ultrafast-derived kinetic parameters including maximal slope (MS), time to enhancement (TTE), and area under the curve (AUC) were statistically examined using the Mann-Whitney test and receiver operator characteristic (ROC) curve analysis.

RESULTS

On ultrafast MRI, breast cancer lesions enhanced earlier than BPE (p < 0.0001), enabling breast cancer visualization freed from lactation BPE. A higher CNR was found for ultrafast acquisitions vs. conventional DCE (p < 0.05). Significant differences in AUC, MS, and TTE values were found between the tumor and BPE (p < 0.05), with ROC-derived AUC of 0.86 ± 0.06, 0.82 ± 0.07, and 0.68 ± 0.08, respectively. The BPE grades of the lactating PABC patients were reduced as compared with the healthy lactating controls (p < 0.005).

CONCLUSION

Ultrafast DCE MRI allows BPE-free visualization of lesions, improved tumor conspicuity, and kinetic quantification of breast cancer during lactation. Implementation of this method may assist in the utilization of breast MRI for lactating patients.

CLINICAL RELEVANCE

The ultrafast sequence appears to be superior to conventional DCE MRI in the challenging evaluation of the lactating breast. Thus, supporting its possible utilization in the setting of high-risk screening during lactation and the diagnostic workup of PABC.

KEY POINTS

• Differences in the enhancement slope of cancer relative to BPE allowed the optimal visualization of PABC lesions on mid-acquisitions of ultrafast DCE, in which the tumor enhanced prior to the background parenchyma. • The conspicuity of PABC lesions on top of the lactation-related BPE was increased using an ultrafast sequence as compared with conventional DCE MRI. • Ultrafast-derived maps provided further characterization and parametric contrast between PABC lesions and lactation-related BPE.

MRI can accurately diagnose breast cancer during lactation

OBJECTIVE

To test the diagnostic performance of breast dynamic contrast-enhanced (DCE) MRI during lactation.

MATERIALS AND METHODS

Datasets of 198 lactating patients, including 66 pregnancy-associated breast cancer (PABC) patients and 132 controls, who were scanned by DCE on 1.5-T MRI, were retrospectively evaluated. Six blinded, expert radiologists independently read a single DCE maximal intensity projection (MIP) image for each case and were asked to determine whether malignancy was suspected and the background-parenchymal-enhancement (BPE) grade. Likewise, computer-aided diagnosis CAD MIP images were independently read by the readers. Contrast-to-noise ratio (CNR) analysis was measured and compared among four consecutive acquisitions of DCE subtraction images.

RESULTS

For MIP-DCE images, the readers achieved the following means: sensitivity 93.3%, specificity 80.3%, positive-predictive-value 70.4, negative-predictive-value 96.2, and diagnostic accuracy of 84.6%, with a substantial inter-rater agreement (Kappa = 0.673, p value < 0.001). Most false-positive interpretations were attributed to either the MIP presentation, an underlying benign lesion, or an asymmetric appearance due to prior treatments. CAD's derived diagnostic accuracy was similar (p = 0.41). BPE grades were significantly increased in the healthy controls compared to the PABC cohort (p < 0.001). CNR significantly decreased by 11-13% in each of the four post-contrast images (p < 0.001).

CONCLUSION

Breast DCE MRI maintains its high efficiency among the lactating population, probably due to a vascular-steal phenomenon, which causes a significant reduction of BPE in cancer cases. Upon validation by prospective, multicenter trials, this study could open up the opportunity for breast MRI to be indicated in the screening and diagnosis of lactating patients, with the aim of facilitating an earlier diagnosis of PABC.

KEY POINTS

• A single DCE MIP image was sufficient to reach a mean sensitivity of 93.3% and NPV of 96.2%, to stress the high efficiency of breast MRI during lactation. • Reduction in BPE among PABC patients compared to the lactating controls suggests that several factors, including a possible vascular steal phenomenon, may affect cancer patients. • Reduction in CNR along four consecutive post-contrast acquisitions highlights the differences in breast carcinoma and BPE kinetics and explains the sufficient conspicuity on the first subtracted image.

Probing lipids relaxation times in breast cancer using magnetic resonance spectroscopic fingerprinting

OBJECTIVES

To investigate the clinical relevance of the relaxation times of lipids within breast cancer and normal fibroglandular tissue in vivo, using magnetic resonance spectroscopic fingerprinting (MRSF).

METHODS

Twelve patients with biopsy-confirmed breast cancer and 14 healthy controls were prospectively scanned at 3 T using a protocol consisting of diffusion tensor imaging (DTI), MRSF, and dynamic contrast-enhanced (DCE) MRI. Single-voxel MRSF data was recorded from the tumor (patients) - identified using DTI - or normal fibroglandular tissue (controls), in under 20 s. MRSF data was analyzed using in-house software. Linear mixed model analysis was used to compare the relaxation times of lipids in breast cancer VOIs vs. normal fibroglandular tissue.

RESULTS

Seven distinguished lipid metabolite peaks were identified and their relaxation times were recorded. Of them, several exhibited statistically significant changes between controls and patients, with strong significance (p < 10^-3) recorded for several of the lipid resonances at 1.3 ppm (T₁ = 355 ± 17 ms vs. 389 ± 27 ms), 4.1 ppm (T₁ = 255 ± 86 ms vs. 127 ± 33 ms), 5.22 ppm (T₁ = 724 ± 81 ms vs. 516 ± 62 ms), and 5.31 ppm (T₂ = 56 ± 5 ms vs. 44 ± 3.5 ms, respectively).

CONCLUSIONS

The application of MRSF to breast cancer imaging is feasible and achievable in clinically relevant scan time. Further studies are required to verify and comprehend the underling biological mechanism behind the differences in lipid relaxation times in cancer and normal fibroglandular tissue.

KEY POINTS

•The relaxation times of lipids in breast tissue are potential markers for quantitative characterization of the normal fibroglandular tissue and cancer. •Lipid relaxation times can be acquired rapidly in a clinically relevant manner using a single-voxel technique, termed MRSF. •Relaxation times of T₁ at 1.3 ppm, 4.1 ppm, and 5.22 ppm, as well as of T₂ at 5.31 ppm, were significantly different between measurements within breast cancer and the normal fibroglandular tissue.

Viscoelastic Liquid Matrix with Faster Bulk Relaxation Time Reinforces the Cell Cycle Arrest Induction of the Breast Cancer Cells via Oxidative Stress

The reactivating of disseminated dormant breast cancer cells in a soft viscoelastic matrix is mostly correlated with metastasis. Metastasis occurs due to rapid stress relaxation owing to matrix remodeling. Here, we demonstrate the possibility of promoting the permanent cell cycle arrest of breast cancer cells on a viscoelastic liquid substrate. By controlling the molecular weight of the hydrophobic molten polymer, poly(ε-caprolactone-co-D,L-lactide) within 35-63 g/mol, this study highlights that MCF7 cells can sense a 1000 times narrower relaxation time range (80-290 ms) compared to other studies by using a crosslinked hydrogel system. We propose that the rapid bulk relaxation response of the substrate promotes more reactive oxygen species generation in the formed semi-3D multicellular aggregates of breast cancer cells. Our finding sheds light on the potential role of bulk stress relaxation in a viscous-dominant viscoelastic matrix in controlling the cell cycle arrest depth of breast cancer cells.

Diffusion Breast MRI: Current Standard and Emerging Techniques

The role of diffusion weighted imaging (DWI) as a biomarker has been the subject of active investigation in the field of breast radiology. By quantifying the random motion of water within a voxel of tissue, DWI provides indirect metrics that reveal cellularity and architectural features. Studies show that data obtained from DWI may provide information related to the characterization, prognosis, and treatment response of breast cancer. The incorporation of DWI in breast imaging demonstrates its potential to serve as a non-invasive tool to help guide diagnosis and treatment. In this review, current technical literature of diffusion-weighted breast imaging will be discussed, in addition to clinical applications, advanced techniques, and emerging use in the field of radiomics.

Assessing the influence of the menstrual cycle on APT CEST-MRI in the human breast

PURPOSE

In fibroglandular breast tissue, conventional dynamic contrast-enhanced MR-mammography is known to be affected by water content changes during the menstrual cycle. Likewise, amide proton transfer (APT) chemical exchange saturation transfer (CEST)-MRI might be inherently prone to the menstrual cycle, as CEST signals are indirectly detected via the water signal. The purpose of this study was to investigate the influence of the menstrual cycle on APT CEST-MRI in fibroglandular breast tissue.

METHOD

Ten healthy premenopausal women (19-34 years) were included in this IRB approved prospective study and examined twice during their menstrual cycle. Examination one and two were performed during the first half (day 2-8) and the second half (day 15-21) of the menstrual cycle, respectively. As a reference for the APT signal in malignant breast tumor tissue, previously reported data of nine breast cancer patients were included in this study. CEST-MRI (B₁ = 0.7μT) was performed on a 7 T whole-body scanner followed by a multi-Lorentzian fit analysis. The APT signal was corrected for B₀/B₁-field inhomogeneities, fat signal contribution, and relaxation effects of the water signal and evaluated in the fibroglandular breast tissue. Intra-individual APT signal differences between examination one and two were compared using the Wilcoxon signed-rank test. The level of significance was set at p < 0.05.

RESULTS

The APT signal showed no significant difference in the fibroglandular breast tissue of healthy premenopausal volunteers throughout the menstrual cycle (p = 1.00) (examination 1 vs. examination 2: mean and standard deviation = 3.24 ± 0.68%Hz vs. 3.30 ± 0.73%Hz, median and IQR = 3.36%Hz and 0.87%Hz vs. 3.38%Hz and 0.71%Hz).

CONCLUSION

The present study provides an important basis for the clinical application of APT CEST-MRI as an additional contrast mechanism in MR-mammography, as menstrual cycle-related APT signal fluctuations seem to be negligible compared to the APT signal increase in breast cancer tissue.

Breast MRI during pregnancy and lactation: clinical challenges and technical advances

The breast experiences substantial changes in morphology and function during pregnancy and lactation which affects its imaging properties and may reduce the visibility of a concurrent pathological process. The high incidence of benign gestational-related entities may further add complexity to the clinical and radiological evaluation of the breast during the period. Consequently, pregnancy-associated breast cancer (PABC) is often a delayed diagnosis and carries a poor prognosis. This state-of-the-art pictorial review illustrates how despite currently being underutilized, technical advances and new clinical evidence support the use of unenhanced breast MRI during pregnancy and both unenhanced and dynamic-contrast enhanced (DCE) during lactation, to serve as effective supplementary modalities in the diagnostic work-up of PABC.

Background parenchymal enhancement and uptake as breast cancer imaging biomarkers: A state-of-the-art review

Within the past decade, background parenchymal enhancement (BPE) and background parenchymal uptake (BPU) have emerged as novel imaging-derived biomarkers in the diagnosis and treatment monitoring of breast cancer. Growing evidence supports the role of breast parenchyma vascularity and metabolic activity as probable risk factors for breast cancer development. Furthermore, in the presence of a newly-diagnosed breast cancer, added clinically-relevant data was surprisingly found in the respective imaging properties of the non-affected contralateral breast. Evaluation of the contralateral BPE and BPU have been found to be especially instrumental in predicting the prognosis of a patient with breast cancer and even anticipating their response to neoadjuvant chemotherapy. Simultaneously, further research has found a link between these two biomarkers, even though they represent different physical properties. The aim of this review is to provide an up to date summary of the current clinical applications of BPE and BPU as breast cancer imaging biomarkers with the hope that it propels their further usage in clinical practice.

MRI of the Lactating Breast: Computer-Aided Diagnosis False Positive Rates and Background Parenchymal Enhancement Kinetic Features

RATIONALE AND OBJECTIVES

To investigate the application of computer-added diagnosis (CAD) in dynamic contrast-enhanced (DCE) MRI of the healthy lactating breast, focusing on false-positive rates and background parenchymal enhancement (BPE) coloring patterns in comparison with breast cancer features in non-lactating patients.

MATERIALS AND METHODS

The study population was composed of 58 healthy lactating patients and control groups of 113 healthy premenopausal non-lactating patients and 55 premenopausal non-lactating patients with newly-diagnosed breast cancer. Patients were scanned on 1.5-T MRI using conventional DCE protocol. A retrospective analysis of DCE-derived CAD properties was conducted using a commercial software that is regularly utilized in our routine radiological work-up. Qualitative morphological characterization and automatically-obtained quantitative parametric measurements of the BPE-induced CAD coloring were categorized and subgroups' trends and differences between the lactating and cancer cohorts were statistically assessed.

RESULTS

CAD false-positive coloring was found in the majority of lactating cases (87%). Lactation BPE coloring was characteristically non-mass enhancement (NME)-like shaped (87%), bilateral (79%) and symmetric (64%), whereas, unilateral coloring was associated with prior irradiation (p <0.0001). Inter-individual variability in CAD appearance of both scoring-grade and kinetic-curve dominance was found among the lactating cohort. When compared with healthy non-lactating controls, CAD false positive probability was significantly increased [Odds ratio 40.2, p <0001], while in comparison with the breast cancer cohort, CAD features were mostly inconclusive, even though increased size parameters were significantly associated with lactation-BPE (p <0.00001).

CONCLUSION

BPE was identified as a common source for false-positive CAD coloring on breast DCE-MRI among lactating population. Despite several typical characteristics, overlapping features with breast malignancy warrant a careful evaluation and clinical correlation in all cases with suspected lactation induced CAD coloring.

Current Recommendations for Breast Imaging of the Pregnant and Lactating Patient

During pregnancy and lactation, the breast undergoes unique changes that manifest as varied clinical and imaging findings. Understanding the expected physiologic changes of the breast as well as recognizing the best imaging modalities for a given clinical scenario can help the radiologist identify the abnormalities arising during this time. Discussion with the patient about the safety of breast imaging can reassure patients and improve management. This article reviews the physiologic changes of the breast during pregnancy and lactation; the safety and utility of various imaging modalities; upto-date consensus on screening guidelines; recommendations for diagnostic evaluation of breast pain, palpable abnormalities, and nipple discharge; and recommendations regarding advanced modalities such as breast MRI. In addition, the commonly encountered benign and malignant entities affecting these patients are discussed.

Physiologic and hypermetabolic breast 18-F FDG uptake on PET/CT during lactation

OBJECTIVE

To investigate the patterns of breast cancer-related and lactation-related ¹⁸F-FDG uptake in breasts of lactating patients with pregnancy-associated breast cancer (PABC) and without breast cancer.

METHODS

¹⁸F-FDG-PET/CT datasets of 16 lactating patients with PABC and 16 non-breast cancer lactating patients (controls) were retrospectively evaluated. Uptake was assessed in the tumor and non-affected lactating tissue of the PABC group, and in healthy lactating breasts of the control group, using maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), and breast-SUVmax/liver-SUVmean ratio. Statistical tests were used to evaluate differences and correlations between the groups.

RESULTS

Physiological uptake in non-breast cancer lactating patients' breasts was characteristically high regardless of active malignancy status other than breast cancer (SUVmax = 5.0 ± 1.7, n = 32 breasts). Uptake correlated highly between the two breasts (r = 0.61, p = 0.01), but was not correlated with age or lactation duration (p = 0.24 and p = 0.61, respectively). Among PABC patients, the tumors demonstrated high ¹⁸F-FDG uptake (SUVmax = 7.8 ± 7.2, n = 16), which was 326-643% higher than the mostly low physiological FDG uptake observed in the non-affected lactating parenchyma of these patients (SUVmax = 2.1 ± 1.1). Overall, ¹⁸F-FDG uptake in lactating breasts of PABC patients was significantly decreased by 59% (p < 0.0001) compared with that of lactating controls without breast cancer.

CONCLUSION

¹⁸F-FDG uptake in lactating tissue of PABC patients is markedly lower compared with the characteristically high physiological uptake among lactating patients without breast cancer. Consequently, breast tumors visualized by ¹⁸F-FDG uptake in PET/CT were comfortably depicted on top of the background ¹⁸F-FDG uptake in lactating tissue of PABC patients.

KEY POINTS

• FDG uptake in the breast is characteristically high among lactating patients regardless of the presence of an active malignancy other than breast cancer. • FDG uptake in non-affected lactating breast tissue is significantly lower among PABC patients compared with that in lactating women who do not have breast cancer. • In pregnancy-associated breast cancer patients, ¹⁸F-FDG uptake is markedly increased in the breast tumor compared with uptake in the non-affected lactating tissue, enabling its prompt visualization on PET/CT.

Effect of IV Administration of a Gadolinium-Based Contrast Agent on Breast Diffusion-Tensor Imaging

OBJECTIVE. The purpose of this study was to quantify changes in diffusion-tensor imaging (DTI) parameters before and after IV administration of a gadolinium-based contrast agent (GBCA) and explore the influence of those parameters on breast cancer diagnosis. SUBJECTS AND METHODS. A prospective cohort of 26 women with BI-RADS categories 0, 4, 5, or 6 underwent 3-T breast MRI with sequential DTI before GBCA administration and immediately after. Quantitative image analysis using dedicated DTI software yielded parametric DTI maps of each directional diffusion coefficient (DDC), mean diffusivity, and maximal anisotropy of the lesions and normal tissue. The color maps were evaluated and the lesion DTI parameters were compared before and after GBCA administration using appropriate statistical tests. RESULTS. Of the cohort, 58% had cancer (13 infiltrating ductal carcinoma, two ductal carcinoma in situ) and 42% had benign or normal results. All breast cancers were visually detected in the DDC λ₁ maps before and after GBCA administration. Mean cancer size derived from λ₁ maps before GBCA administration was 15.3 mm (range, 3.3-72.3 mm), and was not statistically significantly different from the size derived after GBCA administration of 17.3 mm (range, 3.9-71.0 mm). After GBCA administration, the cancers exhibited statistically significantly lower DDCs, mean diffusivity, and b0 intensity (p < 0.05), and no change in maximal anisotropy compared with before GBCA administration, whereas these parameters in normal and benign lesions did not change significantly after GBCA administration. The mean AUC values before and after GBCA administration, ranging from 0.735 to 0.985 and from 0.867 to 0.990, respectively, were not statistically significantly different for all parameters aside from λ₃. CONCLUSION. Diagnostic accuracy using DTI was equivalent before and after GBCA administration, despite a change in the values of the DTI parameters. However, the limitations in standardization of contrast enhancement implies that unenhanced diffusion measurements should be preferred.

Diffusion-weighted imaging of the breast-a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group

The European Society of Breast Radiology (EUSOBI) established an International Breast DWI working group. The working group consists of clinical breast MRI experts, MRI physicists, and representatives from large vendors of MRI equipment, invited based upon proven expertise in breast MRI and/or in particular breast DWI, representing 25 sites from 16 countries. The aims of the working group are (a) to promote the use of breast DWI into clinical practice by issuing consensus statements and initiate collaborative research where appropriate; (b) to define necessary standards and provide practical guidance for clinical application of breast DWI; (c) to develop a standardized and translatable multisite multivendor quality assurance protocol, especially for multisite research studies; (d) to find consensus on optimal methods for image processing/analysis, visualization, and interpretation; and (e) to work collaboratively with system vendors to improve breast DWI sequences. First consensus recommendations, presented in this paper, include acquisition parameters for standard breast DWI sequences including specifications of b values, fat saturation, spatial resolution, and repetition and echo times. To describe lesions in an objective way, levels of diffusion restriction/hindrance in the breast have been defined based on the published literature on breast DWI. The use of a small ROI placed on the darkest part of the lesion on the ADC map, avoiding necrotic, noisy or non-enhancing lesion voxels is currently recommended. The working group emphasizes the need for standardization and quality assurance before ADC thresholds are applied. The working group encourages further research in advanced diffusion techniques and tailored DWI strategies for specific indications.

Key Points

• The working group considers breast DWI an essential part of a multiparametric breast MRI protocol and encourages its use.

• Basic requirements for routine clinical application of breast DWI are provided, including recommendations on b values, fat saturation, spatial resolution, and other sequence parameters.

• Diffusion levels in breast lesions are defined based on meta-analysis data and methods to obtain a reliable ADC value are detailed.

Application of in vivo MR methods in the study of breast cancer metabolism

In the last two decades, various in vivo MR methodologies have been evaluated for their potential in the study of cancer metabolism. During malignant transformation, metabolic alterations occur, leading to morphological and functional changes. Among various MR methods, in vivo MRS has been extensively used in breast cancer to study the metabolism of cells, tissues or whole organs. It provides biochemical information at the metabolite level. Altered choline, phospholipid and energy metabolism has been documented using proton (¹ H), phosphorus (³¹ P) and carbon (¹³ C) isotopes. Increased levels of choline-containing compounds, phosphomonoesters and phosphodiesters in breast cancer, which are indicative of altered choline and phospholipid metabolism, have been reported using in vivo, in vitro and ex vivo NMR studies. These changes are reversed on successful therapy, which depends on the treatment regimen given. Monitoring the various tumor intermediary metabolic pathways using nuclear spin hyperpolarization of ¹³ C-labeled substrates by dynamic nuclear polarization has also been recently reported. Furthermore, the utility of various methods such as diffusion, dynamic contrast and perfusion MRI have also been evaluated to study breast tumor metabolism. Parameters such as tumor volume, apparent diffusion coefficient, volume transfer coefficient and extracellular volume ratio are estimated. These parameters provide information on the changes in tumor microstructure, microenvironment, abnormal vasculature, permeability and grade of the tumor. Such changes seen during cancer progression are due to alterations in the tumor metabolism, leading to changes in cell architecture. Due to architectural changes, the tissue mechanical properties are altered; this can be studied using magnetic resonance elastography, which measures the elastic properties of tissues. Moreover, these structural MRI methods can be used to investigate the effect of therapy-induced changes in tumor characteristics. This review discusses the potential of various in vivo MR methodologies in the study of breast cancer metabolism.

The Diffusion Tensor Imaging Properties of the Normal Testicles at 3 Tesla Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

The testicles are structured in a well-defined microtubular network formation, which is expected to be reflected in high anisotropic diffusivity. However, preliminary studies reported on low values of fractional-anisotropy (FA) in the normal testicles. Our aim was to design and apply a diffusion-tensor imaging (DTI) protocol in order to elucidate the diffusivity properties of the testicles and their determining factors.

MATERIALS AND METHODS

16 healthy volunteers were prospectively scanned at 3T. The protocol included T₂-weighted and DTI sequences, the latter using 24 directional diffusion gradients and 3 b-values (0, 100, and 700 s/mm²) that were separated for analysis based on the reference b-value of 0 or 100 s/mm². Image processing of the two DTI datasets yielded the diffusion vector maps and parametric maps of their corresponding principal diffusion coefficients λ₁, λ₂, λ₃, mean diffusivity and FA.

RESULTS

The results demonstrated the feasibility of DTI to provide parametric maps of the testicles. The diffusion tensor parameters obtained using the pair of 0 and 700 s/mm² b-values, exhibited relatively low diffusivity, with mean λ₁ values of 1.36 ± 0.21 × 10^-3 mm²/s and low anisotropy, with mean FA values of 0.13 ± 0.05. Analysis of DTI using the 100 and 700 s/mm² b-values yielded a slight decrease in the diffusivity of 4%-5%, whereas FA remained similar.

CONCLUSION

The diffusivity of the normal testicles is relatively slow, closed-to isotropic and hardly affected by the low b-values regime exclusion. Thus, DTI parameters of the normal testicles are neither dictated by the underlying architectural anisotropy nor microperfusion effects.

Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role

Diffusion-weighted imaging (DWI) of the breast is a MRI sequence that shows several advantages when compared to the dynamic contrast-enhanced sequence: it does not need intravenous contrast, it is relatively quick and easy to implement (artifacts notwithstanding). In this review, the current applications of DWI for lesion characterization and prognosis as well as for response evaluation are analyzed from the point of view of the necessary steps to become a useful surrogate of underlying biological processes (tissue architecture and cellularity): from the proof of concept, to the proof of mechanism, the proof of principle and finally the proof of effectiveness. Future applications of DWI in screening, DWI modeling and radiomics are also discussed.

Variability of non-Gaussian diffusion MRI and intravoxel incoherent motion (IVIM) measurements in the breast

We prospectively examined the variability of non-Gaussian diffusion magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) measurements with different numbers of b-values and excitations in normal breast tissue and breast lesions. Thirteen volunteers and fourteen patients with breast lesions (seven malignant, eight benign; one patient had bilateral lesions) were recruited in this prospective study (approved by the Internal Review Board). Diffusion-weighted MRI was performed with 16 b-values (0–2500 s/mm² with one number of excitations [NEX]) and five b-values (0–2500 s/mm², 3 NEX), using a 3T breast MRI. Intravoxel incoherent motion (flowing blood volume fraction [fIVIM] and pseudodiffusion coefficient [D*]) and non-Gaussian diffusion (theoretical apparent diffusion coefficient [ADC] at b value of 0 sec/mm² [ADC₀] and kurtosis [K]) parameters were estimated from IVIM and Kurtosis models using 16 b-values, and synthetic apparent diffusion coefficient (sADC) values were obtained from two key b-values. The variabilities between and within subjects and between different diffusion acquisition methods were estimated. There were no statistical differences in ADC₀, K, or sADC values between the different b-values or NEX. A good agreement of diffusion parameters was observed between 16 b-values (one NEX), five b-values (one NEX), and five b-values (three NEX) in normal breast tissue or breast lesions. Insufficient agreement was observed for IVIM parameters. There were no statistical differences in the non-Gaussian diffusion MRI estimated values obtained from a different number of b-values or excitations in normal breast tissue or breast lesions. These data suggest that a limited MRI protocol using a few b-values might be relevant in a clinical setting for the estimation of non-Gaussian diffusion MRI parameters in normal breast tissue and breast lesions.

Implementing diffusion-weighted MRI for body imaging in prospective multicentre trials: current considerations and future perspectives

For body imaging, diffusion-weighted MRI may be used for tumour detection, staging, prognostic information, assessing response and follow-up. Disease detection and staging involve qualitative, subjective assessment of images, whereas for prognosis, progression or response, quantitative evaluation of the apparent diffusion coefficient (ADC) is required. Validation and qualification of ADC in multicentre trials involves examination of i) technical performance to determine biomarker bias and reproducibility and ii) biological performance to interrogate a specific aspect of biology or to forecast outcome. Unfortunately, the variety of acquisition and analysis methodologies employed at different centres make ADC values non-comparable between them. This invalidates implementation in multicentre trials and limits utility of ADC as a biomarker. This article reviews the factors contributing to ADC variability in terms of data acquisition and analysis. Hardware and software considerations are discussed when implementing standardised protocols across multi-vendor platforms together with methods for quality assurance and quality control. Processes of data collection, archiving, curation, analysis, central reading and handling incidental findings are considered in the conduct of multicentre trials. Data protection and good clinical practice are essential prerequisites. Developing international consensus of procedures is critical to successful validation if ADC is to become a useful biomarker in oncology.

KEY POINTS

• Standardised acquisition/analysis allows quantification of imaging biomarkers in multicentre trials. • Establishing "precision" of the measurement in the multicentre context is essential. • A repository with traceable data of known provenance promotes further research.

Intravoxel incoherent motion (IVIM) and non-Gaussian diffusion MRI of the lactating breast

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Breastfeeding significantly affects IVIM and non-Gaussian diffusion parameters.

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The distribution of ADC₀ values becomes more heterogeneous after breastfeeding.

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Care needs to be taken in interpreting DWI data in lactating breasts.

Purpose

To investigate the effect of breastfeeding on IVIM and non-Gaussian diffusion MRI in the breast.

Materials and methods

An IRB approved prospective study enrolled seventeen volunteers (12 in lactation and 5 with post-weaning, range 31–43 years; mean 35.4 years). IVIM (f_IVIM and D*) and non-Gaussian diffusion (ADC₀ and K) parameters using 16 b values, plus synthetic apparent diffusion coefficients (sADCs) from 2 key b values (b = 200 and 1500 s/mm²) were calculated using regions of interest. ADC₀ maps of the whole breast were generated and their contrast patterns were evaluated by two independent readers using retroareolar and segmental semi-quantitative scores. To compare the diffusion and IVIM parameters, Wilcoxon signed rank tests were used between pre- and post-breastfeeding and Mann-Whitney tests were used between post-weaning and pre- or post-breastfeeding.

Results

ADC₀ and sADC values significantly decreased post-breastfeeding (1.90 vs. 1.72 × 10⁻³ mm²/s, P < 0.001 and 1.39 vs. 1.25 × 10⁻³ mm²/s, P < 0.001) while K values significantly increased (0.33 vs. 0.44, P < 0.05). f_IVIM values significantly increased after breastfeeding (1.97 vs. 2.97%, P < 0.01). No significant difference was found in D* values. There was significant heterogeneity in ADC₀ maps post-breastfeeding, both in retroareolar and segmental scores (P < 0.0001 and =0.0001).

Conclusion

IVIM and non-Gaussian diffusion parameters significantly changed between pre- and post-breastfeeding status, and care needs to be taken in interpreting diffusion-weighted imaging (DWI) data in lactating breasts.

Monitoring In-Vivo the Mammary Gland Microstructure during Morphogenesis from Lactation to Post-Weaning Using Diffusion Tensor MRI

Lactation and the return to the pre-conception state during post-weaning are regulated by hormonal induced processes that modify the microstructure of the mammary gland, leading to changes in the features of the ductal / glandular tissue, the stroma and the fat tissue. These changes create a challenge in the radiological workup of breast disorder during lactation and early post-weaning. Here we present non-invasive MRI protocols designed to record in vivo high spatial resolution, T₂-weighted images and diffusion tensor images of the entire mammary gland. Advanced imaging processing tools enabled tracking the changes in the anatomical and microstructural features of the mammary gland from the time of lactation to post-weaning. Specifically, by using diffusion tensor imaging (DTI) it was possible to quantitatively distinguish between the ductal / glandular tissue distention during lactation and the post-weaning involution. The application of the T₂-weighted imaging and DTI is completely safe, non-invasive and uses intrinsic contrast based on differences in transverse relaxation rates and water diffusion rates in various directions, respectively. This study provides a basis for further in-vivo monitoring of changes during the mammary developmental stages, as well as identifying changes due to malignant transformation in patients with pregnancy associated breast cancer (PABC).

Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for?

Diffusion-weighted imaging holds the potential to improve the diagnosis and biological characterization of pancreatic disease, and in particular pancreatic cancer, which exhibits decreased values of the apparent diffusion coefficient (ADC). Yet, variable and overlapping ADC values have been reported for the healthy and the pathological pancreas, including for cancer and other benign conditions. This controversy reflects the complexity of probing the water-diffusion process in the pancreas, which is dependent upon multiple biological factors within this organ's unique physiological environment. In recent years, extensive studies have investigated the correlation between tissue properties including cellularity, vascularity, fibrosis, secretion and microstructure and pancreatic diffusivity. Understanding how the various physiological and pathological features and the underlying functional processes affect the diffusion measurement may serve to optimize the method for improved diagnostic gain. Therefore, the aim of the present review article is to elucidate the relationship between pancreatic tissue characteristics and diffusion MRI measurement.

Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers

Purpose:

To assess the diagnostic performance of readout-segmented echo-planar diffusion tensor imaging (DTI based on rs-EPI) for breast cancer and to determine the correlation between the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values obtained from DTI based on rs-EPI with prognostic markers of invasive breast cancer.

Materials and Methods:

This retrospective study examined 80 pathologically proven breast lesions (22 benign and 58 malignant lesions) of 80 patients who underwent both diffusion-weighted imaging based on single-shot echo-planar imaging (DWI based on ss-EPI) and DTI based on rs-EPI with b-values of 0 and 1000. We identified and compared the diagnostic performances of the DWI based on ss-EPI and the DTI based on rs-EPI using ADCs by conducting a receiver-operating-characteristics (ROC) analysis. We determined the correlations between the ADCs and the prognostic markers and those of the FA values and the same markers.

Results:

The median ADCs of the benign and malignant lesions based on the ss-EPI were 1.57 and 1.2 × 10⁻³ mm²/sec, and those based on the rs-EPI were 1.53 and 1.09 × 10⁻³ mm²/sec, respectively. The area under the curve on the ROC analysis based on rs-EPI (0.924) was greater than that based on ss-EPI (0.897). There were no significant correlations between the ADCs and the prognostic markers, but there were significant correlations between the FA values and the estrogen receptor status, a proliferative marker, the nuclear grade and the intrinsic subtype.

Conclusion:

For breast cancer, DTI based on rs-EPI had superior diagnostic performance compared to DWI based on ss-EPI. Compared with the ADCs, the FA values were more closely correlated with prognostic markers of invasive breast cancer.

Diffusion-weighted breast MRI: Clinical applications and emerging techniques

Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2016 J. Magn. Reson. Imaging 2017;45:337-355.

Assessing Detection, Discrimination, and Risk of Breast Cancer According to Anisotropy Parameters of Diffusion Tensor Imaging

BACKGROUND The aim of this study was to investigate whether the anisotropy parameters are helpful in the detection and discrimination of breast cancers, and to determine its value in predicting the risk of cancers. MATERIAL AND METHODS There were 56 patients with 56 lesions (34 malignant, 22 benign) included in the study. DTI was performed in every patient and apparent diffusion coefficient (ADC), fractional anisotropy (FA), and eigenvalues E1, E2, and E3 were measured in every lesion and the normal breast tissue. RESULTS ADC, FA, and eigenvalues of E1, E2, E3, and E1-E3 in breast cancers were all significantly lower than in normal tissue (P<0.001 for all) with mean reduction of (32 ± 17)%, (24 ± 13)%, (33 ± 19)%, (32 ± 17)%, (31 ± 18)%, and (37 ± 20)% for ADC, FA, E1, E2, E3, and E1-E3, respectively. These parameters were also statistically lower in cancers than in benign lesions (P<0.01 for all), except FA (P>0.05). ADC, E1, E2, and E3 were very similar in discriminating breast cancers and benign lesions, with area under the curve (AUC) 0.885-0.898, sensitivity 73.5-85.3%, and specificity 90.9-100%. CONCLUSIONS ADC, E1, E2, E3, and E1-E3 are much lower in breast cancers than in normal tissue and benign lesions. The reduction of ADC, E1, E2, E3, and E1-E3 of a mass in the breast is highly associated with the risk of breast cancer, but the FA has no utility in breast cancer risk prediction.

Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status

The purpose of this study was to investigate prospectively whether the apparent diffusion coefficients (ADCs) of both breast cancer and normal fibroglandular tissue vary with the menstrual cycle and menopausal status. Institutional review board approval was obtained, and informed consent was obtained from each participant. Fifty-seven women (29 premenopausal, 28 postmenopausal) with newly diagnosed breast cancer underwent diffusion-weighted imaging twice (interval 12-20 days) before surgery. Two radiologists independently measured ADC of breast cancer and normal contralateral breast tissue, and we quantified the differences according to the phases of menstrual cycle and menopausal status. With normal fibroglandular tissue, ADC was significantly lower in postmenopausal than in premenopausal women (P = 0.035). In premenopausal women, ADC did not differ significantly between proliferative and secretory phases in either breast cancer or normal fibroglandular tissue (P = 0.969 and P = 0.519, respectively). In postmenopausal women, no significant differences were found between ADCs measured at different time intervals in either breast cancer or normal fibroglandular tissue (P = 0.948 and P = 0.961, respectively). The within-subject variability of the ADC measurements was quantified using the coefficient of variation (CV) and was small: the mean CVs of tumor ADC were 2.90 % (premenopausal) and 3.43 % (postmenopausal), and those of fibroglandular tissue ADC were 4.37 % (premenopausal) and 2.55 % (postmenopausal). Both intra- and interobserver agreements were excellent for ADC measurements, with intraclass correlation coefficients in the range of 0.834-0.974. In conclusion, the measured ADCs of breast cancer and normal fibroglandular tissue were not affected significantly by menstrual cycle, and the measurements were highly reproducible both within and between observers.

Predicting liver metastasis of gastrointestinal tract cancer by diffusion-weighted imaging of apparent diffusion coefficient values

AIM: To determine if efficacy of chemotherapy on liver metastasis of gastrointestinal tract cancer can be predicted by apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI).

METHODS: In total, 86 patients with liver metastasis of gastrointestinal tract cancer (156 metastatic lesions) diagnosed in our hospital were included in this study. The maximum diameters of these tumors were compared with each other before treatment, 2 wk after treatment, and 12 wk after treatment. Selected patients were classified as the effective group and the ineffective group, depending on the maximum diameter of the tumor after 12 wk of treatment; and the ADC values at different treatment times between the two groups were compared. Spearman rank correlation was used to analyze the relationship between ADC value and tumor diameter. Receiver operating characteristic curve (ROC curve) was used to analyze the ADC values before treatment to predict the patient’s sensitivity and specificity degree of efficacy to the chemotherapy.

RESULTS: There was no difference in age between the two groups and in maximum tumor diameter before treatment and 2 wk after treatment. However, after 12 wk of treatment, maximum tumor diameter in the effective group was significantly lower than that in the ineffective group (P < 0.05). Before treatment, ADC values in the ineffective group were significantly higher than those in the effective group (P < 0.05). There was no difference in ADC values between the effective and ineffective groups after 2 and 12 wk of treatment. However, ADC values were significantly higher after 2 and 12 wk of treatment compared to before treatment in the effective group (P < 0.05). Spearman rank correlation analysis showed that ADC value before treatment and the reduced percentage of the maximum tumor diameter after 12 wk of treatment were negatively correlated, while the increase in the percentage of the ADC value 12 wk after treatment and the decrease in the percentage of the maximum tumor diameter were significantly positively correlated. The results of the ROC curve showed that ADC value with a chemotherapy ineffective threshold value of 1.14 × 10^-3 mm²/s before treatment had a sensitivity and specificity of 94.3% and 76.7%, respectively.

CONCLUSION: DWI ADC values can be used to predict the response of patients with liver metastasis of gastrointestinal tract cancer to chemotherapy with high sensitivity and relatively high specificity.

Various diffusion magnetic resonance imaging techniques for pancreatic cancer

Pancreatic cancer is one of the most common malignant tumors and remains a treatment-refractory cancer with a poor prognosis. Currently, the diagnosis of pancreatic neoplasm depends mainly on imaging and which methods are conducive to detecting small lesions. Compared to the other techniques, magnetic resonance imaging (MRI) has irreplaceable advantages and can provide valuable information unattainable with other noninvasive or minimally invasive imaging techniques. Advances in MR hardware and pulse sequence design have particularly improved the quality and robustness of MRI of the pancreas. Diffusion MR imaging serves as one of the common functional MRI techniques and is the only technique that can be used to reflect the diffusion movement of water molecules in vivo. It is generally known that diffusion properties depend on the characterization of intrinsic features of tissue microdynamics and microstructure. With the improvement of the diffusion models, diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique to the more complex. In this review, the various diffusion MRI techniques for pancreatic cancer are discussed, including conventional diffusion weighted imaging (DWI), multi-b DWI based on intra-voxel incoherent motion theory, diffusion tensor imaging and diffusion kurtosis imaging. The principles, main parameters, advantages and limitations of these techniques, as well as future directions for pancreatic diffusion imaging are also discussed.

Diffusion tensor imaging in the normal breast: influences of fibroglandular tissue composition and background parenchymal enhancement

OBJECTIVE

To evaluate effects of fibroglandular tissue (FGT) composition and background parenchymal enhancement (BPE) on diffusion tensor imaging (DTI) parameters in normal breast tissue.

METHODS

DTI analysis was performed on 35 breasts with regions of interest drawn to include only normal tissue. Breasts were dichotomized by FGT composition and by BPE; DTI parameters were compared.

RESULTS

The λ1 principal diffusion coefficient was lower in breasts with moderate/marked BPE versus those with minimal/mild BPE (P=.039). All other parameters were unaffected.

CONCLUSION

λ1 is sensitive to differences in BPE within normal breast tissue that should be taken into account in DTI evaluation.

Effect of menstrual cycle and menopausal status on apparent diffusion coefficient values and detectability of invasive ductal carcinoma on diffusion-weighted MRI

The purpose of this study was to determine whether the apparent diffusion coefficient (ADC) and tumor detectability based on diffusion-weighted imaging (DWI) are affected by the menstrual cycle or menopausal status in breast cancer patients. Institutional review board approval was obtained, and the requirement for informed consent was waived. A total of 124 women with invasive ductal carcinoma not otherwise specified (IDC NOS) who underwent breast MRI with DWI were included in this study. Two radiologists retrospectively measured the ADCs of tumor and contralateral normal glandular tissue and scored the tumor detectability. The ADCs and detectability were compared to menstrual cycle and menopausal status, based on patient questionnaires. ADCs of tumors and contralateral tissue were significantly lower in postmenopausal women than in premenopausal women (P = 0.006 and P < 0.001, respectively). Tumor detectability did not differ significantly between the premenopausal and postmenopausal groups (P = 0.454). Normalized ADCs were not significantly lower in postmenopausal women compared to premenopausal women (P = 0.880). There was no statistically significant difference in the absolute, contralateral, and normalized ADCs (P = 0.091, 0.809, and 0.299, respectively), and the tumor detectability (P = 0.680) according to the menstrual cycle. Although ADCs of the IDC and normal glandular tissue in postmenopausal women were significantly lower than those in premenopausal women, the menstrual cycle did not affect tumor detectability and ADCs of IDC.

Diffusion tensor magnetic resonance imaging of the pancreas

PURPOSE

To develop a diffusion-tensor-imaging (DTI) protocol that is sensitive to the complex diffusion and perfusion properties of the healthy and malignant pancreas tissues.

MATERIALS AND METHODS

Twenty-eight healthy volunteers and nine patients with pancreatic-ductal-adenocacinoma (PDAC), were scanned at 3T with T2-weighted and DTI sequences. Healthy volunteers were also scanned with multi-b diffusion-weighted-imaging (DWI), whereas a standard clinical protocol complemented the PDAC patients' scans. Image processing at pixel resolution yielded parametric maps of three directional diffusion coefficients λ1, λ2, λ3, apparent diffusion coefficient (ADC), and fractional anisotropy (FA), as well as a λ1-vector map, and a main diffusion-direction map.

RESULTS

DTI measurements of healthy pancreatic tissue at b-values 0,500 s/mm² yielded: λ1 = (2.65±0.35)×10⁻³, λ2 = (1.87±0.22)×10⁻³, λ3 = (1.20±0.18)×10⁻³, ADC = (1.91±0.22)×10⁻³ (all in mm²/s units) and FA = 0.38±0.06. Using b-values of 100,500 s/mm² led to a significant reduction in λ1, λ2, λ3 and ADC (p<.0001) and a significant increase (p<0.0001) in FA. The reduction in the diffusion coefficients suggested a contribution of a fast intra-voxel-incoherent-motion (IVIM) component at b≤100 s/mm², which was confirmed by the multi-b DWI results. In PDACs, λ1, λ2, λ3 and ADC in both 0,500 s/mm² and 100,500 s/mm² b-values sets, as well as the reduction in these diffusion coefficients between the two sets, were significantly lower in comparison to the distal normal pancreatic tissue, suggesting higher cellularity and diminution of the fast-IVIM component in the cancer tissue.

CONCLUSION

DTI using two reference b-values 0 and 100 s/mm² enabled characterization of the water diffusion and anisotropy of the healthy pancreas, taking into account a contribution of IVIM. The reduction in the diffusion coefficients of PDAC, as compared to normal pancreatic tissue, and the smaller change in these coefficients in PDAC when the reference b-value was modified from 0 to 100 s/mm², helped identifying the presence of malignancy.

Microscopic diffusion properties of fixed breast tissue: Preliminary findings

PURPOSE

To investigate the microscopic diffusion properties of formalin-fixed breast tissue.

METHODS

Diffusion microimaging was performed at 16.4T with 40-μm isotropic voxels on two normal and two cancer tissue samples from four patients. Results were correlated with histology of the samples.

RESULTS

Diffusion-weighted images and mean diffusivity maps demonstrated distinct diffusivity differences between breast tissue components. Mean diffusivity (MD) in normal tissue was 0.59 ± 0.24 μm(2) /ms for gland lobule (voxels containing epithelium and intralobular stroma) and 1.23 ± 0.34 μm(2) /ms for interlobular fibrous stroma. In the cancer samples, MD = 0.45 ± 0.23 μm(2) /ms for invasive ductal carcinoma (voxels contain epithelium and intralobular stroma) and 0.61 ± 0.35 μm(2) /ms for ductal carcinoma in situ. There were significant MD differences between all tissue components (P < 0.005), except between gland lobule and ductal carcinoma in situ (P = 0.71). The low diffusivity of epithelium-rich cancer tissue and of normal epithelium relative to its supporting fibrous stroma was similar to that reported for prostate tissue and the esophageal wall.

CONCLUSION

Diffusion microimaging demonstrates distinct diffusivity differences between breast tissue glandular structures. Low diffusivity may be a distinctive feature of mammalian epithelia.

Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.