The concept of diffusion magnetic resonance (MR) imaging emerged in the mid-1980s, together with the first images of water diffusion in the human brain, as a way to probe tissue structure at a microscopic scale, although the images were acquired at a millimetric scale. Since then, diffusion MR imaging has become a pillar of modern clinical imaging. Diffusion MR imaging has mainly been used to investigate neurologic disorders. A dramatic application of diffusion MR imaging has been acute brain ischemia, providing patients with the opportunity to receive suitable treatment at a stage when brain tissue might still be salvageable, thus avoiding terrible handicaps. On the other hand, it was found that water diffusion is anisotropic in white matter, because axon membranes limit molecular movement perpendicularly to the nerve fibers. This feature can be exploited to produce stunning maps of the orientation in space of the white matter tracts and brain connections in just a few minutes. Diffusion MR imaging is now also rapidly expanding in oncology, for the detection of malignant lesions and metastases, as well as monitoring. Water diffusion is usually largely decreased in malignant tissues, and body diffusion MR imaging, which does not require any tracer injection, is rapidly becoming a modality of choice to detect, characterize, or even stage malignant lesions, especially for breast or prostate cancer. After a brief summary of the key methodological concepts beyond diffusion MR imaging, this article will give a review of the clinical literature, mainly focusing on current outstanding issues, followed by some innovative proposals for future improvements.

https://pubs.rsna.org/doi/pdf/10.1148/radiol.2015150244

Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future.

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

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Diffusion-weighted breast MRI: Clinical applications and emerging techniques

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.

/pdf/diffusion-weighted-imaging-of-the-breast-a-consensus-and-207ltjym8c.pdf

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

ObjectivesThe purpose of this study was to explore the potential of non-Gaussian diffusion and perfusion magnetic resonance imaging (MRI) using intravoxel incoherent motion (IVIM) MRI for the diagnosis of breast lesions.Materials and MethodsThis study included 26 women with breast lesions. Diffusion

http://clinical-mri.com/wp-content/uploads/2015/03/Quantitative_Non_Gaussian_Diffusion_and_Intravoxel.4.pdf

Quantitative Non-Gaussian Diffusion and Intravoxel Incoherent Motion Magnetic Resonance Imaging Differentiation of Malignant and Benign Breast Lesions

Diffusion weighted magnetic resonance imaging of the breast: protocol optimization, interpretation, and clinical applications.

OBJECTIVES: To investigate the ability of parametric diffusion tensor imaging (DTI), applied at 3 Tesla, to dissect breast tissue architecture and evaluate breast lesions. MATERIALS AND METHODS: All protocols were approved and a signed informed consent was obtained from all subjects. The study included 21 healthy women, 26 women with 33 malignant lesions, and 14 women with 20 benign lesions. Images were recorded at 3 Tesla with a protocol optimized for breast DTI at a spatial resolution of 1.9 × 1.9 × (2-2.5) mm3. Image processing algorithms and software, applied at pixel resolution, yielded vector maps of prime diffusion direction and parametric maps of the 3 orthogonal diffusion coefficients and of the fractional anisotropy and maximal anisotropy. RESULTS: The DTI-derived vector maps and parametric maps revealed the architecture of the entire mammary fibroglandular tissue and allowed a reliable detection of malignant lesions. Cancer lesions exhibited significantly lower values of the orthogonal diffusion coefficients, λ1, λ2, λ3, and of the maximal anisotropy index λ1-λ3 as compared with normal breast tissue (P < 0.0001) and to benign breast lesions (P < 0.0009 and 0.004, respectively). Maps of λ1 exhibited the highest contrast-to-noise ratio enabling delineation of the cancer lesions. These maps also provided high sensitivity/specificity of 95.6%/97.7% for differentiating cancers from benign lesions, which were similar to the sensitivity/specificity of dynamic contrast-enhanced magnetic resonance imaging of 94.8%/92.9%. Maps of λ1-λ3 provided a secondary independent diagnostic parameter with high sensitivity of 92.3%, but low specificity of 69.5% for differentiating cancers from benign lesions. CONCLUSION: Mapping the diffusion tensor parameters at high spatial resolution provides a potential novel means for dissecting breast architecture. Parametric maps of λ1 and λ1-λ3 facilitate the detection and diagnosis of breast cancer.

Parametric diffusion tensor imaging of the breast

The breast diffusion-tensor parameters are not sensitive to menstrual cycle changes, whereas lactation and long-term use of hormone replacement therapy do not affect diffusion parameters.

https://pubs.rsna.org/doi/pdf/10.1148/radiol.14132084

Diffusion-Tensor MR Imaging of the Breast: Hormonal Regulation

PURPOSE To evaluate whether the various anisotropy indices derived from breast diffusion tensor imaging (DTI) can characterize the healthy breast structure and differentiate cancer from normal breast tissue. MATERIALS AND METHODS Six healthy volunteers and retrospectively selected 24 breast cancer patients were imaged at 3T. DTI included two b-values 0 and 700 sec/mm2 with 20-64 gradient directions and TE of 120 or 90 msec. The normalized anisotropy indices: fractional anisotropy (FA), relative anisotropy (RA), and 1-volume ratio (1-VR), as well as the absolute maximal anisotropy index (λ1 -λ3 ) were compared. RESULTS The spatial distribution of the various anisotropy indices in healthy volunteers exhibited a high congruence (Pearson correlation coefficients range: 0.79-1.0). All indices showed a statistically significant reduction (P < 0.001) following shortening of the diffusion time. Significantly lower λ1 -λ3 values were found in cancers as compared to normal breast tissue (P < 6.0 × 10-7 ), while the values of the normalized indices in cancers were not significantly different from those in normal breast tissue (P < 0.65 for FA, P < 0.6 for RA, and P < 0.2 for 1-VR). The contrast-to-noise ratio of λ1 -λ3 was significantly higher (P < 0.001) than those of the normalized anisotropy indices, and the area under the curve in a receiver operating characteristic analysis exhibited the highest value for λ1 -λ3 (0.89 ± 0.04 vs. 0.51-0.54 for the other anisotropy indices). CONCLUSION Water diffusion anisotropy in the healthy breast can be similarly mapped by the normalized indices and by λ1 -λ3 . However, the normalized anisotropy indices fail to differentiate cancer from normal breast tissue, whereas λ1 -λ3 can assist in differentiating cancer from normal breast tissue. J. Magn. Reson. Imaging 2016;44:1624-1632.

Can diffusion tensor anisotropy indices assist in breast cancer detection

Objective
We evaluated a functional three-dimensional (3D) infrared imaging system (3DIRI) coupled with multiparametric computer analysis for risk assessment of breast cancer. The technique provides objective risk assessment for the presence of a malignant tumour based on automated parameters derived from a clinically known training set.

A novel functional infrared imaging system coupled with multiparametric computerised analysis for risk assessment of breast cancer

Purpose

Evaluating the usefulness of diffusion-weighted spatio-temporal encoding (SPEN) methods to provide quantitative apparent diffusion coefficient (ADC)-based characterizations of healthy and malignant human breast tissues, in comparison with results obtained using techniques based on spin-echo echo planar imaging (SE-EPI).



Methods

Twelve healthy volunteers and six breast cancer patients were scanned at 3T using scanner-supplied diffusion-weighted imaging EPI sequences, as well as two fully refocused SPEN variants programmed in-house. Suitable codes were written to process the data, including calculations of the actual b-values and retrieval of the ADC maps.



Results

Systematically better images were afforded by the SPEN scans, with negligible geometrical distortions and markedly weaker ghosting artifacts arising from either fat tissues or from strongly emitting areas such as cysts. SPEN-derived images provided improved characterizations of the fibroglandular tissues and of the lesions' contours. When translated into the calculation of the ADC maps, there were no significant differences between the mean ADCs derived from SPEN and SE-EPI: if reliable images were available, both techniques showed that ADCs decreased by nearly two-fold in the malignant lesion areas.



Conclusion

SPEN-based sequences yielded diffusion-weighted breast images with minimal artifacts and distortions, enabling the calculation of improved ADC maps and the identification of decreased ADCs in malignant regions. Magn Reson Med 73:2163–2173, 2015. © 2014 Wiley Periodicals, Inc.

Myra Shapiro-Feinberg

Papers

Parametric diffusion tensor imaging of the breast

Diffusion-Tensor MR Imaging of the Breast: Hormonal Regulation

Can diffusion tensor anisotropy indices assist in breast cancer detection

A novel functional infrared imaging system coupled with multiparametric computerised analysis for risk assessment of breast cancer

Overcoming limitations in diffusion-weighted MRI of breast by spatio-temporal encoding