Savannah C. Partridge

Quantitative Diffusion-Weighted Imaging as an Adjunct to Conventional Breast MRI for Improved Positive Predictive Value

OBJECTIVE The purpose of our study was to investigate whether adding diffusion-weighted imaging (DWI) to dynamic contrast-enhanced MRI (DCE-MRI) could improve the positive predictive value (PPV) of breast MRI. MATERIALS AND METHODS The retrospective study included 70 women with 83 suspicious breast lesions on DCE-MRI (BI-RADS 4 or 5) who underwent subsequent biopsy. DWI was acquired during clinical breast MRI using b = 0 and 600 s/mm(2). Apparent diffusion coefficient (ADC) values were compared for benign and malignant lesions. PPV was calculated for DCE-MRI alone (based on biopsy recommendations) and DCE-MRI plus DWI (adding an ADC threshold) for the same set of lesions. Results were further compared by lesion type (mass, nonmasslike enhancement) and size. RESULTS Of the 83 suspicious lesions, 52 were benign and 31 were malignant (11 ductal carcinoma in situ [DCIS], 20 invasive carcinoma). Both DCIS (mean ADC, 1.31 +/- 0.24 x 10(-3) mm(2)/s) and invasive carcinoma (mean ADC, 1.29 +/- 0.29 x 10(-3) mm(2)/s) exhibited lower mean ADC than benign lesions (1.70 +/- 0.44 x 10(-3) mm(2)/s, p < 0.001). Applying an ADC threshold of 1.81 x 10(-3) mm(2)/s for 100% sensitivity produced a PPV of 47% versus 37% for DCE-MRI alone, which would have avoided biopsy for 33% (17/52) of benign lesions without missing any cancers. DWI increased PPV similarly for masses and nonmasslike enhancement and preferentially improved PPV for smaller (< or = 1 cm) versus larger lesions. CONCLUSION DWI shows potential for improving the PPV of breast MRI for lesions of varied types and sizes. However, considerable overlap in ADC of benign and malignant lesions necessitates validation of these findings in larger studies.

Quantitative diffusion tensor MRI fiber tractography of sensorimotor white matter development in premature infants.

Diffusion tensor MRI (DTI) fiber tracking is the first non-invasive and in vivo technique for the delineation and quantitation of specific white matter pathways. In this study, quantitative fiber tracking was used to assess the structural development of the motor tract and somatosensory radiation in premature human newborns. These pathways are unmyelinated in the youngest premature infants and begin to myelinate during late preterm maturation. Previous studies have only been able to delineate parts of these pathways that could be manually outlined in 2D based on anatomical landmarks. Furthermore, these previous studies could not separate motor and sensory regions. A high-sensitivity neonatal head coil was employed in conjunction with an MR-compatible incubator to perform high-resolution imaging of the premature infant brain. The motor and somatosensory tracts were successfully delineated with 3D DTI fiber tracking in 37 exams of preterm newborns between 28 and 43 weeks gestational age. Both streamline deterministic and probabilistic methods were employed to perform quantitative fiber tractography. Tract-specific measurements of diffusion parameters including fractional anisotropy, directionally averaged diffusivity, and eigenvalues were obtained from the motor and sensory pathways. Using both deterministic and probabilistic fiber tracking, all tract-specific diffusion parameters were found to be significantly correlated with age and the motor tracts were found to have higher anisotropy and lower diffusivity than the sensory pathway. By segmenting the 3D fiber tracks by slice, measurements from different axial levels of the brain were found to vary with region and age. In summary, deterministic and probabilistic DTI fiber tracking methods were used to quantify the developmental changes of motor and somatosensory pathways in premature infants.

Tractography‐based quantitation of diffusion tensor imaging parameters in white matter tracts of preterm newborns

To evaluate the feasibility of performing diffusion tensor tractography (DTT) to map and quantify the pyramidal white matter tracts of premature newborns.

Differential diagnosis of mammographically and clinically occult breast lesions on diffusion‐weighted MRI

To investigate the diagnostic performance of diffusion‐weighted imaging (DWI) for mammographically and clinically occult breast lesions.

Apparent Diffusion Coefficient Values for Discriminating Benign and Malignant Breast MRI Lesions: Effects of Lesion Type and Size

OBJECTIVE The purpose of this study was to determine whether lesion type and size affect discrimination of benign and malignant breast lesions with diffusion-weighted MRI. MATERIALS AND METHODS This study included 91 women with 116 breast lesions identified with dynamic contrast-enhanced MRI. Diffusion-weighted images were acquired during clinical breast MRI at b values of 0 and 600 s/mm(2). Differences in the apparent diffusion coefficients (ADCs) of benign and malignant lesions were compared by lesion type (mass or nonmasslike enhancement) and size (<or= 1 cm or > 1 cm), and receiver operating characteristics analysis was performed to evaluate diagnostic performance based on ADC thresholds. RESULTS Sixteen of 71 masses and 13 of 45 lesions with nonmasslike enhancement were malignant. The mean ADC was significantly lower for malignant than for benign lesions for both masses (mean difference, 0.49 x 10(-3) mm(2)/s; p < 0.001) and lesions with nonmasslike enhancement (mean difference, 0.20 x 10(-3) mm(2)/s; p = 0.02). The area under the receiver operating characteristics curve (AUC) was greater for masses (AUC, 0.80) than for lesions with nonmasslike enhancement (AUC, 0.66). The mean ADC for malignant masses (1.25 x 10(-3) mm(2)/s) was lower than that for malignant lesions with nonmasslike enhancement (1.41 x 10(-3) mm(2)/s; p = 0.07). The median lesion size was 1.1 cm (range, 0.5-8.3 cm); 45 of 71 masses (63%) measured 1 cm or smaller, and 37 of 45 lesions with nonmasslike enhancement (82%) were larger than 1 cm. There was no relation (p > 0.05) between ADC value and lesion size for benign or malignant lesions, and there were no differences in AUC based on lesion size (p > 0.05). CONCLUSION Diffusion-weighted MRI shows promise in differentiation of benign and malignant masses and lesions with nonmasslike enhancement found at breast MRI and is not affected by lesion size. However, ADC measurements may be more useful for discriminating masses than for discriminating lesions with nonmasslike enhancement.

Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors.

To investigate whether diffusion tensor imaging (DTI) measures of anisotropy in breast tumors are different from normal breast tissue and can improve the discrimination between benign and malignant lesions.

Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast-enhanced kinetics

This study investigated the relationship between apparent diffusion coefficient (ADC) measures and dynamic contrast‐enhanced magnetic resonance imaging (MRI) kinetics in breast lesions and evaluated the relative diagnostic value of each quantitative parameter. Seventy‐seven women with 100 breast lesions (27 malignant and 73 benign) underwent both dynamic contrast‐enhanced MRI and diffusion weighted MRI. Dynamic contrast‐enhanced MRI kinetic parameters included peak initial enhancement, predominant delayed kinetic curve type (persistent, plateau, or washout), and worst delayed kinetic curve type (washout > plateau > persistent). Associations between ADC and dynamic contrast‐enhanced MRI kinetic parameters and predictions of malignancy were evaluated. Results showed that ADC was significantly associated with predominant curve type (ADC was higher for lesions exhibiting predominantly persistent enhancement compared with those exhibiting predominantly washout or plateau, P = 0.006), but was not significantly associated with peak initial enhancement or worst curve type (P > 0.05). Univariate analysis showed significant differences between benign and malignant lesions in both ADC (P < 0.001) and worst curve (P = 0.003). In multivariate analysis, worst curve type and ADC were significant independent predictors of benign versus malignant outcome and in combination produced the highest area under the receiver operating characteristic curve (0.85 and 0.78 with 5‐fold cross validation). Magn Reson Med, 2011.

Pyramidal tract maturation after brain injury in newborns with heart disease

Our objective was to quantify white matter tract development in term newborns with congenital heart disease, a population at high risk for perioperative brain injury, using magnetic resonance imaging diffusion tensor tractography (DTT).

Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?

PURPOSE To investigate whether qualitative magnetic resonance (MR) imaging assessments of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT), and mammographic density are associated with risk of developing breast cancer in women who are at high risk. MATERIALS AND METHODS In this institutional review board-approved HIPAA-compliant retrospective study, all screening breast MR images obtained from January 2006 to December 2011 in women aged 18 years or older and at high risk for but without a history of breast cancer were identified. Women in whom breast cancer was diagnosed after index MR imaging comprised the cancer cohort, and one-to-one matching (age and BRCA status) of each woman with breast cancer to a control subject was performed by using MR images obtained in women who did not develop breast cancer with follow-up time maximized. Amount of BPE, BPE pattern (peripheral vs central), amount of FGT at MR imaging, and mammographic density were assessed on index images. Imaging features were compared between cancer and control cohorts by using conditional logistic regression. RESULTS Twenty-three women at high risk (mean age, 47 years ± 10 [standard deviation]; six women had BRCA mutations) with no history of breast cancer underwent screening breast MR imaging; in these women, a diagnosis of breast cancer (invasive, n = 12; in situ, n = 11) was made during the follow-up interval. Women with mild, moderate, or marked BPE were nine times more likely to receive a diagnosis of breast cancer during the follow-up interval than were those with minimal BPE (P = .007; odds ratio = 9.0; 95% confidence interval: 1.1, 71.0). BPE pattern, MR imaging amount of FGT, and mammographic density were not significantly different between the cohorts (P = .5, P = .5, and P = .4, respectively). CONCLUSION Greater BPE was associated with a higher probability of developing breast cancer in women at high risk for cancer and warrants further study.

Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements.

Promising recent investigations have shown that breast malignancies exhibit restricted diffusion on diffusion-weighted imaging (DWI) and may be distinguished from normal tissue and benign lesions in the breast based on differences in apparent diffusion coefficient (ADC) values. In this study, we assessed the influence of intravoxel fat signal on breast diffusion measures by comparing ADC values obtained using a diffusion-weighted single shot fast spin-echo sequence with and without fat suppression. The influence of breast density on ADC measures was also evaluated. ADC values were calculated for both tumor and normal fibroglandular tissue in a group of 21 women with diagnosed breast cancer. There were systematic underestimations of ADC for both tumor and normal breast tissue due to intravoxel contribution from fat signal on non-fat-suppressed DWI. This ADC underestimation was more pronounced for normal tissue values (mean difference=40%) than for tumors (mean difference=27%, P<.001) and was worse in women with low breast tissue density vs. those with extremely dense breasts (P<.05 for both tumor and normal tissue). Tumor conspicuity measured by contrast-to-noise ratio was significantly higher on ADC maps created with fat suppression and was not significantly associated with breast density. In summary, robust fat suppression is important for accurate breast ADC measures and optimal lesion conspicuity on DWI.