Tumor-induced lymph node alterations detected by MRI lymphography using gadolinium nanoparticles.

Contrast-enhanced MRI lymphography shows potential to identify alterations in lymph drainage through lymph nodes (LNs) in cancer and other diseases. MRI studies have typically used low molecular weight gadolinium contrast agents, however larger gadolinium-loaded nanoparticles possess characteristics that could improve the specificity and sensitivity of lymphography. The performance of three gadolinium contrast agents with different sizes and properties was compared by 3T MRI after subcutaneous injection. Mice bearing B16-F10 melanoma footpad tumors were imaged to assess tumor-induced alterations in lymph drainage through tumor-draining popliteal and inguinal LNs versus contralateral uninvolved drainage. Gadolinium lipid nanoparticles were able to identify tumor-induced alterations in contrast agent drainage into the popliteal LN, while lower molecular weight or albumin-binding gadolinium agents were less effective. All of the contrast agents distributed in foci around the cortex and medulla of tumor-draining popliteal LNs, while they were restricted to the cortex of non-draining LNs. Surprisingly, second-tier tumor-draining inguinal LNs exhibited reduced uptake, indicating that tumors can also divert LN drainage. These characteristics of tumor-induced lymph drainage could be useful for diagnosis of LN pathology in cancer and other diseases. The preferential uptake of nanoparticle contrasts into tumor-draining LNs could also allow selective targeting of therapies to tumor-draining LNs.

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).

Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI.

Recent investigations have shown that tumors may be distinguished from benign lesions in the breast based on differences in apparent diffusion coefficient (ADC) values. The goal of this study was to assess the magnitude of normal variations in the measured ADC of breast parenchyma during the menstrual cycle. Eight healthy female subjects were scanned once a week for 4 weeks, using a diffusion-weighted single-shot fast spin-echo (DW-SSFSE) sequence. The ADC of breast fibroglandular tissue was calculated for each woman at each time point. Results showed a trend of decreased ADC during the second week of the cycle, and increased ADC during the final week. However, no significant influence of menstrual cycle on breast ADC values was identified. The results of this study show that the normal fluctuation of breast ADC is relatively small, and the coefficient of variation was determined to be 5.5% for our group of volunteers during a menstrual cycle. Nonetheless, breast diffusion measurements for tumor differentiation and evaluation of treatment response should be interpreted with consideration of normal variability.

Semi-automated analysis for MRI of breast tumors.

Magnetic resonance imaging (MRI) techniques have the potential to greatly improve breast cancer detection, diagnosis, and treatment. Currently, a major problem associated with breast MRI is the overwhelming amount of data acquired during an exam, and the time-intensive analysis required to evaluate the images. We have developed a software platform for semi-automated analysis to assess both the tumor extent and overall grade or severity based on our diagnostic criteria. In a test subset of over 50 patients, the automated program produced results more accurate overall than those measurements taken manually, with a reduction in time for analysis from approximately 45 minutes down to 5 minutes per patient study.