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Objective: In breast diffusion-weighted imaging (DWI), the apparent diffusion coefficient (ADC) is used to discriminate between malignant and benign lesions. As ADC estimates can be affected by the weighting factors, our goal was to determine the optimal pair of b-values for discriminating breast lesions at 3.0 T., Methods: 152 females with 157 lesions (89 malignant and 68 benign) underwent breast MRI, including a DWI sequence sampling six b-values 50, 200, 400, 600, 800 and 1000 s mm(-2). ADC values were computed from different pairs of b-values and compared with ADC obtained by fitting the six b-values using a mono-exponential diffusion model (ADCall). Cut-off ADC values were determined and diagnostic performance evaluated by receiver operating characteristic analysis using Youden statistics. Mean ADCs were determined for normal tissue and lesions. Differences were evaluated by lesion and histological types., Results: Considering the cut-off values 1.46 and 1.49 × 10(3)mm(2) s(-1), the pairs 50, 1000 and 200, 800 s mm(-2) showed the highest accuracy, 77.5% and 75.4% with areas under the curve 84.4% and 84.2%, respectively. The best pair for ADC quantification was 50, 1000 s mm(-2) with 38/49 true-negative and 69/89 true-positive cases respectively; mean ADCs were 1.86 ± 0.46, 1.77 ± 0.37 and 1.15 ± 0.46 × 10(-3) mm(2) s(-1) for normal, benign and malignant lesions. There were no significant differences in these ADC values when compared with ADCall (ADC calculated from the full set of b - values) [difference = 0.0075 × 10(-3) mm(2) s(-1); confidence interval 95%: (-0.0036; 0.0186); p = 0.18]., Conclusion: The diagnostic performance in differentiating malignant and benign lesions was most accurate for the b-value pair 50, 1000 s mm(-2)., Advances in Knowledge: The best b-value pair for lesion discrimination and characterization through ADC quantification was 50, 1000 s mm(-2).

Aim: To evaluate the performance of diffusion-weighted imaging (DWI) at 3 T for the detection and characterization of breast lesions., Materials and Methods: Magnetic resonance imaging (MRI) of the breast, including DWI single-shot spin-echo echo planar images (SS-SE-EPI; eight b-values, 50-3000 s/mm(2)), were acquired in women with a clinical indication for breast MRI. The exclusion criteria were as follows: (1) previous breast surgery, radiotherapy and/or chemotherapy within the prior 48 months (14 women); (2) only cystic lesions (one woman); (3) no detectable enhancing lesion at dynamic contrast-enhanced (DCE)-MRI (15 women); and (4) breast implants (four women). MRI results were corroborated by histopathology or imaging follow-up. Apparent diffusion coefficients (ADCs) were estimated for lesions and normal glandular tissue. Differences in the ADC between tissue types were evaluated and the sensitivity and specificity of the method calculated by receiver operating characteristics (ROC) curves., Results: The final cohort comprised 53 patients with 59 lesions. Histopathology was obtained for 58 lesions. One lesion was validated as benign on imaging follow-up. Mean ADCs of 1.99 ± 0.27 × 10(-3) mm(2)/s, 1.08 ± 0.25 × 10(-3) mm(2)/s, and 1.74 ± 0.35 × 10(-3) mm(2)/s were obtained for normal tissue, malignant, and benign lesions, respectively. Mean ADCs of malignancies were significantly lower than those of benign lesions (p < 0.001) and normal tissue (p < 0.0001). The sensitivity and specificity for stratifying lesions, considering an ADC threshold of 1.41 × 10(-3) mm(2)/s, were 94.3% and 87.5%, respectively; accuracy was 91.5%., Conclusion: DWI proved useful for the detection and characterization of breast lesions in the present sample. ADC values provide a high diagnostic performance for differentiation between benign and malignant lesions., (Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.)

The medial geniculate body (MGB) of the thalamus is a key component of the auditory system. It is involved in relaying and transforming auditory information to the cortex and in top-down modulation of processing in the midbrain, brainstem, and ear. Functional imaging investigations of this region in humans, however, have been limited by the difficulty of distinguishing MGB from other thalamic nuclei. Here, we introduce two methods for reliably delineating MGB anatomically in individuals based on conventional and diffusion MRI data. The first uses high-resolution proton density weighted scanning optimized for subcortical grey-white contrast. The second uses diffusion-weighted imaging and probabilistic tractography to automatically segment the medial and lateral geniculate nuclei from surrounding structures based on their distinctive patterns of connectivity to the rest of the brain. Both methods produce highly replicable results that are consistent with published atlases. Importantly, both methods rely on commonly available imaging sequences and standard hardware, a significant advantage over previously described approaches. In addition to providing useful approaches for identifying the MGB and LGN in vivo, our study offers further validation of diffusion tractography for the parcellation of grey matter regions on the basis of their connectivity patterns.

A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate., (Copyright 2003 Wiley-Liss, Inc.)