Faculty Bibliography

RATIONALE AND OBJECTIVES: To investigate whether quantitative kinetic analysis of lesions and background parenchyma in breast magnetic resonance imaging can elucidate differences between BRCA carriers and sporadic controls with high risk for breast cancer. MATERIALS AND METHODS: Fifty-nine BRCA and 59 control cases (49 benign, 10 malignant) were examined in this study. Principal component analysis was applied for quantitative analysis of dynamic signal in background parenchyma (B) and lesion (L) in terms of initial enhancement ratio (IER) and delayed enhancement ratio (DER). RESULTS: Control B-IER, B-DER, L-IER, and L-DER were higher than BRCA cases in all women and in women with benign lesions; statistically significant differences in B-IER and B-DER (all women: P = 0.02 and P = 0.02, respectively; benign only: P = 0.005 and P = 0.005, respectively). In the control cohort, B-IER and B-DER were higher in the premenopausal women than in the postmenopausal women (P = 0.013 and 0.003, respectively), but not in the BRCA cohort; this led to significant differences in B-IER and B-DER between the control and the BRCA groups in the premenopausal women (P = 0.01 and 0.01, respectively) but not in the postmenopausal women. CONCLUSION: Results suggest possible differences in the vascular properties of background parenchyma between BRCA carriers and noncarriers and its association with menopausal status.

BACKGROUND: To evaluate the influence of temporal sparsity regularization and radial undersampling on compressed sensing reconstruction of dynamic contrast-enhanced (DCE) MRI, using the iterative Golden-angle RAdial Sparse Parallel (iGRASP) MRI technique in the setting of breast cancer evaluation. METHODS: DCE-MRI examinations of the breast (n = 7) were conducted using iGRASP at 3 Tesla. Images were reconstructed with five different radial undersampling schemes corresponding to temporal resolutions between 2 and 13.4 s/frame and with four different weights for temporal sparsity regularization (lambda = 0.1, 0.5, 2, and 6 times of noise level). Image similarity to time-averaged reference images was assessed by two breast radiologists and using quantitative metrics. Temporal similarity was measured in terms of wash-in slope and contrast kinetic model parameters. RESULTS: iGRASP images reconstructed with lambda = 2 and 5.1 s/frame had significantly (P < 0.05) higher similarity to time-averaged reference images than the images with other reconstruction parameters (mutual information (MI) >5%), in agreement with the assessment of two breast radiologists. Higher undersampling (temporal resolution < 5.1 s/frame) required stronger temporal sparsity regularization (lambda >/= 2) to remove streaking aliasing artifacts (MI > 23% between lambda = 2 and 0.5). The difference between the kinetic-model transfer rates of benign and malignant groups decreased as temporal resolution decreased (82% between 2 and 13.4 s/frame). CONCLUSION: This study demonstrates objective spatial and temporal similarity measures can be used to assess the influence of sparsity constraint and undersampling in compressed sensing DCE-MRI and also shows that the iGRASP method provides the flexibility of optimizing these reconstruction parameters in the postprocessing stage using the same acquired data. J. Magn. Reson. Imaging 2015.

OBJECTIVE: This review article explores recent advancements in PET/MRI for clinical oncologic imaging. CONCLUSION: Radiologists should understand the technical considerations that have made PET/MRI feasible within clinical workflows, the role of PET tracers for imaging various molecular targets in oncology, and advantages of hybrid PET/MRI compared with PET/CT. To facilitate this understanding, we discuss clinical examples (including gliomas, breast cancer, bone metastases, prostate cancer, bladder cancer, gynecologic malignancy, and lymphoma) as well as future directions, challenges, and areas for continued technical optimization for PET/MRI.

The role of breast MRI in patients with newly diagnosed breast cancer is controversial. Preoperative MRI is highly sensitive and accurate in assessing tumor size, extensive intraductal component (EIC), and in detection of additional sites of disease. It also has utility in assessing chest wall, nipple-areolar complex, and nodal involvement. Yet there are conflicting results in whether the use of preoperative MRI improves re-excision rate, local recurrence rate, and ultimately, survival. MRI has also been associated with overestimation of disease and increased mastectomy rates, and may contribute to treatment delay. Nevertheless, certain subgroups of patients may benefit more from preoperative MRI than others, including those with invasive lobular cancer (ILC), dense breasts, and those at elevated risk for breast cancer

PURPOSE: To evaluate the relationship between mammographic breast density (MBD), background parenchymal enhancement (BPE), and fibroglandular tissue (FGT) in women with breast cancer (BC) and at high risk for developing BC. METHODS: Our institutional database was queried for patients who underwent mammography and MRI. RESULTS: Four hundred three (85%) had BC and 72 (15%) were at high risk. MBD (P=.0005), BPE (P<.0001), and FGT (P=.02) were all higher in high-risk women compared to the BC group. CONCLUSIONS: Higher levels of MBD, BPE and FGT are seen in women at higher risk for developing BC when compared to women with BC.

PURPOSE: To compare fitting methods and sampling strategies, including the implementation of an optimized b-value selection for improved estimation of intravoxel incoherent motion (IVIM) parameters in breast cancer. METHODS: Fourteen patients (age, 48.4 +/- 14.27 years) with cancerous lesions underwent 3 Tesla breast MRI examination for a HIPAA-compliant, institutional review board approved diffusion MR study. IVIM biomarkers were calculated using "free" versus "segmented" fitting for conventional or optimized (repetitions of key b-values) b-value selection. Monte Carlo simulations were performed over a range of IVIM parameters to evaluate methods of analysis. Relative bias values, relative error, and coefficients of variation (CV) were obtained for assessment of methods. Statistical paired t-tests were used for comparison of experimental mean values and errors from each fitting and sampling method. RESULTS: Comparison of the different analysis/sampling methods in simulations and experiments showed that the "segmented" analysis and the optimized method have higher precision and accuracy, in general, compared with "free" fitting of conventional sampling when considering all parameters. Regarding relative bias, IVIM parameters fp and Dt differed significantly between "segmented" and "free" fitting methods. CONCLUSION: IVIM analysis may improve using optimized selection and "segmented" analysis, potentially enabling better differentiation of breast cancer subtypes and monitoring of treatment. Magn Reson Med, 2014. (c) 2014 Wiley Periodicals, Inc.

OBJECTIVE: To measure background parenchymal enhancement (BPE) and compare with other contrast enhancement values and diffusion-weighted MRI parameters in healthy and cancerous breast tissue at the clinical level. MATERIALS AND METHODS: This HIPAA-compliant, IRB approved retrospective study enrolled 77 patients (38 patients with breast cancer - mean age 51.8+/-10.0 years; 39 high-risk patients for screening evaluation - mean age 46.3+/-11.7 years), who underwent contrast-enhanced 3T breast MRI. Contrast enhanced MRI and diffusion-weighted imaging were performed to quantify BPE, lesion contrast enhancement, and apparent diffusion coefficient (ADC) metrics in fibroglandular tissue (FGT) and lesions. RESULTS: BPE did not correlate with ADC values. Mean BPE for the lesion-bearing patients was higher (43.9%) compared to that of the high-risk screening patients (28.3%, p=0.004). Significant correlation (r=0.37, p<0.05) was found between BPE and lesion contrast enhancement. CONCLUSION: No significant association was observed between parenchymal or lesion enhancement with conventional apparent diffusion metrics, suggesting that proliferative processes are not co-regulated in cancerous and parenchymal tissue.