OBJECTIVE. In this article, we present the basic principles of diffusion-weighted imaging (DWI) that can aid radiologists in the qualitative and quantitative interpretation of DW images. However, a detailed discussion of the physics of DWI is beyond the scope of this article. A short discussion ensues on the technical aspects of performing DWI in the body. The emerging applications of DWI for tumor detection, tumor characterization, distinguishing tumor tissue from nontumor tissue, and monitoring and predicting treatment response are highlighted. The challenges to widespread adoption of the technique for cancer imaging in the body are discussed. CONCLUSION. DWI derives its image contrast from differences in the motion of water molecules between tissues. Such imaging can be performed quickly without the need for the administration of exogenous contrast medium. The technique yields qualitative and quantitative information that reflects changes at a cellular level and provides unique insights about tumor cellularity and the integrity of cell membranes. Recent advances enable the technique to be widely applied for tumor evaluation in the abdomen and pelvis and have led to the development of whole-body DWI.

https://www.ajronline.org/doi/pdf/10.2214/AJR.06.1403

Diffusion-weighted MRI in the body: applications and challenges in oncology.

Diffusion-Weighted Magnetic Resonance Imaging as a Cancer Biomarker: Consensus and Recommendations

http://facweb.cs.depaul.edu/research/vc/medix/2011/papers/Source2.pdf

Texture analysis of medical images.

Purpose
To evaluate the value of diffusion-weighted imaging (DWI) in distinguishing between benign and malignant breast lesions.

Materials and Methods
Fifty-two female subjects (mean age = 58 years, age range = 25–75 years) with histopathologically proven breast lesions underwent DWI of the breasts with a single-shot echo-planar imaging (EPI) sequence using large b values. The computed mean apparent diffusion coefficients (ADCs) of the breast lesions and cell density were then correlated.

Results
The ADCs varied substantially between benign breast lesions ((1.57 ± 0.23) × 10−3 mm2/second) and malignant breast lesions ((0.97 ± 0.20) × 10−3 mm2/second). In addition, the mean ADCs of the breast lesions correlated well with tumor cellularity (P < 0.01, r = −0.542).

Conclusion
The ADC would be an effective parameter in distinguishing between malignant and benign breast lesions. Further, tumor cellularity has a significant influence on the ADCs obtained in both benign and malignant breast tumors. J. Magn. Reson. Imaging 2002;16:172–178. © 2002 Wiley-Liss, Inc.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jmri.10140

Differentiation of clinically benign and malignant breast lesions using diffusion-weighted imaging.

Purpose: To determine, in a meta-analysis, the diagnostic performance of contrast material–enhanced magnetic resonance (MR) imaging in patients with breast lesions. Materials and Methods: Studies to assess the diagnostic performance of MR imaging in patients suspected of having breast cancer who underwent MR imaging and biopsy from January 1985 through March 2005 were reviewed for inclusion. A summary receiver operating characteristic curve was constructed, and pooled weighted estimates of sensitivity and specificity were calculated by using the recently developed bivariate approach for diagnostic meta-analysis. Results: Of 251 eligible studies, 44 were included in the meta-analysis (sample size range, 14–821; cancer prevalence, 23%–84%). Pooled weighted estimates of sensitivity and specificity were 0.90 (95% confidence interval: 0.88, 0.92) and 0.72 (95% confidence interval: 0.67, 0.77), respectively. The performance of breast MR imaging was influenced by the prevalence of cancer in the studied populatio...

Meta-Analysis of MR Imaging in the Diagnosis of Breast Lesions

Purpose
To investigate the potential of apparent diffusion coefficients (ADCs) in characterizing breast lesions in vivo.

Materials and Methods
Two diffusion-weighted (DW) sequences were implemented on a 1.5 Tesla scanner, with low b-value orthogonal and high b-value tetrahedral sensitized sequences. The orthogonal sequence was evaluated on 16 normal volunteers and 23 patients with known lesion types (six benign and 17 malignant). The tetrahedral sequence was evaluated on a smaller number of subjects: two normal, two malignant, and two benign.

Results
The mean value of the ADC of the malignant tumors was reduced compared to that of the benign lesions and normal tissue. This finding was related to the increased cellularity of the malignant lesions. The ADC values were elevated for all tissue types with the low b-value sequence as compared to the high b-value sequence, indicating contributions from perfusion effects at the low b-values.

Conclusion
The study clearly shows that DW-MRI can help characterize breast lesions in vivo. J. Magn. Reson. Imaging 2002;15:693–704. © 2002 Wiley-Liss, Inc.

In vivo diffusion-weighted MRI of the breast: potential for lesion characterization.

The objective of this study was to determine whether linear discriminant analysis of different independent features of MR images of breast lesions can increase the sensitivity and specificity of this technique. For MR images of 23 benign and 20 malignant breast lesions, three independent classes of features, including characteristics of Gd-DTPA-uptake curve, boundary, and texture were evaluated. The three classes included five, four and eight features each, respectively. Discriminant analysis was applied both within and across the three classes, to find the best combination of features yielding the highest classification accuracy. The highest specificity and sensitivity of the different classes considered independently were as follows: Gd-up-take curves, 83% and 70%; boundary features, 86% and 70%; and texture, 70% and 75%, respectively. A combination of one feature each from the first two classes and age yielded a specificity of 79% and sensitivity of 90%, whereas highest figures of 93% and 95%, respectively, were obtained when a total of 10 features were combined across different classes. Statistical analysis of different independent classes of features in MR images of breast lesions can improve the classification accuracy of this technique significantly.

Flora Anne Lucas-Quesada

Papers

In vivo diffusion-weighted MRI of the breast: potential for lesion characterization.

Multifeature analysis of Gd-enhanced MR images of breast lesions.