Faculty Bibliography

The significant advances in magnetic resonance imaging (MRI) hardware and software, sequence design, and postprocessing methods have made diffusion-weighted imaging (DWI) an important part of body MRI protocols and have fueled extensive research on quantitative diffusion outside the brain, particularly in the oncologic setting. In this review, we summarize the most up-to-date information on DWI acquisition and clinical applications outside the brain, as discussed in an ISMRM-sponsored symposium held in April 2015. We first introduce recent advances in acquisition, processing, and quality control; then review scientific evidence in major organ systems; and finally describe future directions. J. Magn. Reson. Imaging 2016.

PURPOSE: This study aims to investigate the feasibility of using simultaneous breast MRI and PET to assess the synergy of MR pharmacokinetic and fluorine-18 fluorodeoxyglucose (F-FDG) uptake data to characterize tumor aggressiveness in terms of metastatic burden and Ki67 status. METHODS: Twelve consecutive patients underwent breast and whole-body PET/MRI. During the MR scan, PET events were simultaneously accumulated. MR contrast kinetic model parametric maps were computed using the extended Tofts model, including the volume transfer constant between blood plasma and the interstitial space (K), the transfer constant from the interstitial space to the blood plasma (kep), and the plasmatic volume fraction (Vp). RESULTS: Patients with systemic metastases had a significantly lower kep compared to those with local disease (0.45 vs. 0.99 min, P = 0.011). Metastatic burden correlated positively with K and standardized uptake value (SUV), and negatively with kep. Ki67 positive tumors had a significantly greater K compared to Ki67 negative tumors (0.29 vs. 0.45 min, P = 0.03). A negative correlation was found between metabolic tumor volume and transfer constant (K or Kep). CONCLUSION: These preliminary results suggest that MR pharmacokinetic parameters and FDG-PET may aid in the assessment of tumor aggressiveness and metastatic potential. Future studies are warranted with a larger cohort to further assess the role of pharmacokinetic modeling in simultaneous PET/MRI imaging.

PURPOSE: To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. MATERIALS AND METHODS: This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 +/- 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. RESULTS: The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. CONCLUSION: Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. KEY POINTS: * Novel IVIM biomarkers characterize heterogeneous breast cancer. * Histogram analysis enables quantification of tumour heterogeneity. * IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

PURPOSE: The aim of the study was to assess whether magnetic resonance imaging (MRI) characteristics can distinguish benign from malignant part-solid pulmonary nodules and predict the aggressiveness of the latter. We also sought to compare MRI-derived parameters with morphologic and physiological values derived from conventional examinations such as computed tomography and positron emission tomography/computed tomography. MATERIALS AND METHODS: This was an institutional review board-approved pilot study of 28 participants (23 women, mean age 73.5+/-13.8 y) with 32 biopsy-proven lesions. 3-T unenhanced pulmonary MRI examinations were performed with regions of interest drawn around lesions for T1, T2, T2*, and diffusion-weighted sequences. Apparent diffusion coefficient (ADC) and T2* values were calculated. Two weeks later the regions of interest were redrawn. MRI parameters were compared with lesion pathology, maximal standard uptake value (SUVmax), and Hounsfield units (HU). MRI lesion visibility was correlated with solid component size and the percentage of solid component. Intraobserver and interobserver agreements were determined. RESULTS: Only ADC values correlated with malignancy (P<0.05). ADC>/=1.28 mum/ms predicted malignancy with 83.3% sensitivity (area under the curve 0.79). ADC and T2* correlated with adenocarcinoma subtypes (P<0.05). No MRI parameters predicted tumor differentiation (P>0.11). SUVmax did not correlate with any MRI parameters (P>0.56). Visibility on T1-weighted images correlated with the percentage of solid components (P<0.03). T1 and T2 values showed significant correlation with HU measurements of the entire nodule (P<0.001 and P<0.024, respectively) and HU measurements of solid components (P=0.031 and 0.008, respectively). CONCLUSIONS: 3 T MRI with quantitative ADC values demonstrated potential for discriminating benign part-solid pulmonary nodules from malignant lesions. ADC and T2* values correlated with adenocarcinoma subtypes. No MRI parameters correlated with SUVmax. T1 and T2 values showed significant correlation with HU measurements of the entire nodule and of the solid components.

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.

When diffusion biomarkers display transient changes, i.e. in muscle following exercise, traditional diffusion-tensor imaging (DTI) methods lack the temporal resolution to resolve the dynamics. This article presents an MRI method for dynamic diffusion-tensor acquisitions on a clinical 3T scanner. This method, the Single-Line Multiple-Echo Diffusion-Tensor Acquisition Technique (SL-MEDITATE), achieves a high temporal resolution (4 s) by rapid diffusion encoding through the acquisition of multiple echoes with unique diffusion sensitization and limiting the readout to a single line volume. The method is demonstrated in a rotating anisotropic phantom, a flow phantom with adjustable flow speed and in vivo skeletal calf muscle of healthy volunteers following a plantar flexion exercise. The rotating and flow-varying phantom experiments show that SL-MEDITATE correctly identifies the rotation of the first diffusion eigenvector and the changes in diffusion-tensor parameter magnitudes, respectively. Immediately following exercise, the in vivo mean diffusivity (MD) time courses show, before the well-known increase, an initial decrease that is not typically observed in traditional DTI. In conclusion, SL-MEDITATE can be used to capture transient changes in tissue anisotropy in a single line. Future progress might allow for dynamic DTI when combined with appropriate k-space trajectories and compressed sensing reconstruction

PURPOSE: We used a combined intravoxel incoherent motion-diffusion tensor imaging (IVIM-DTI) methodology to distinguish structural from flow effects on renal diffusion anisotropy. METHODS: Eight volunteers were examined with IVIM-DTI at 3T with 20 diffusion directions and 10 b-values. Mean diffusivity (MD) and fractional anisotropy (FA) from DTI analysis were calculated for low (b 200 s/mm2 ), and full b-value ranges. IVIM-parameters perfusion-fraction fP , pseudo-diffusivity Dp , and tissue-diffusivity Dt were first calculated independently on a voxelwise basis for all directions. After estimating a fixed isotropic fp from these data, global anisotropies of Dt and Dp in the cortex and medulla were determined in a constrained cylindrical description and visualized using polar plots and cosine scatterplots. RESULTS: For all b-value ranges, medullary FA was significantly higher than that of the cortex. The corticomedullary difference was smaller for the high b-value range. Significantly higher fp and Dt were determined for the cortex and showed a significantly higher directional variance in the medulla. Polar plot analysis displayed nearly isotropic Dp and Dt in the cortex and anisotropy in the medulla. CONCLUSION: Both flow and microstructure apparently contribute to the medullary diffusion anisotropy. The described novel method may be useful in separating decreased tubular flow from irreversible structural tubular damage, for example, in diabetic nephropathy or during allograft rejection. Magn Reson Med, 2014. (c) 2014 Wiley Periodicals, Inc.

Radial spin-echo diffusion imaging allows motion-robust imaging of tissues with very low T2 values like articular cartilage with high spatial resolution and signal-to-noise ratio (SNR). However, in vivo measurements are challenging, due to the significantly slower data acquisition speed of spin-echo sequences and the less efficient k-space coverage of radial sampling, which raises the demand for accelerated protocols by means of undersampling. This work introduces a new reconstruction approach for undersampled diffusion-tensor imaging (DTI). A model-based reconstruction implicitly exploits redundancies in the diffusion-weighted images by reducing the number of unknowns in the optimization problem and compressed sensing is performed directly in the target quantitative domain by imposing a total variation (TV) constraint on the elements of the diffusion tensor. Experiments were performed for an anisotropic phantom and the knee and brain of healthy volunteers (three and two volunteers, respectively). Evaluation of the new approach was conducted by comparing the results with reconstructions performed with gridding, combined parallel imaging and compressed sensing and a recently proposed model-based approach. The experiments demonstrated improvements in terms of reduction of noise and streaking artifacts in the quantitative parameter maps, as well as a reduction of angular dispersion of the primary eigenvector when using the proposed method, without introducing systematic errors into the maps. This may enable an essential reduction of the acquisition time in radial spin-echo diffusion-tensor imaging without degrading parameter quantification and/or SNR

PURPOSE: The aim of this study was to determine if voxel-based histogram analysis of intravoxel incoherent motion imaging (IVIM) parameters can differentiate various subtypes of renal tumors, including benign and malignant lesions. SUBJECTS AND METHODS: A total of 44 patients with renal tumors who underwent surgery and had histopathology available were included in this Health Insurance Portability and Accountability Act-compliant, institutional review board-approved, single-institution prospective study. In addition to routine renal magnetic resonance imaging examination performed on a 1.5-T system, all patients were imaged with axial diffusion-weighted imaging using 8 b values (range, 0-800 s/mm). A biexponential model was fitted to the diffusion signal data using a segmented algorithm to extract the IVIM parameters perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) for each voxel. Mean and histogram measures of heterogeneity (standard deviation, skewness, and kurtosis) of IVIM parameters were correlated with pathology results of tumor subtype using unequal variance t tests to compare subtypes in terms of each measure. Correction for multiple comparisons was accomplished using the Tukey honestly significant difference procedure. RESULTS: A total of 44 renal tumors including 23 clear cell (ccRCC), 4 papillary (pRCC), 5 chromophobe, and 5 cystic renal cell carcinomas, as well as benign lesions, 4 oncocytomas (Onc) and 3 angiomyolipomas (AMLs), were included in our analysis. Mean IVIM parameters fp and Dt differentiated 8 of 15 pairs of renal tumors. Histogram analysis of IVIM parameters differentiated 9 of 15 subtype pairs. One subtype pair (ccRCC vs pRCC) was differentiated by mean analysis but not by histogram analysis. However, 2 other subtype pairs (AML vs Onc and ccRCC vs Onc) were differentiated by histogram distribution parameters exclusively. The standard deviation of Dt [sigma(Dt)] differentiated ccRCC (0.362 +/- 0.136 x 10 mm/s) from AML (0.199 +/- 0.043 x 10 mm/s) (P = 0.002). Kurtosis of fp separated Onc (2.767 +/- 1.299) from AML (-0.325 +/- 0.279; P = 0.001), ccRCC (0.612 +/- 1.139; P = 0.042), and pRCC (0.308 +/- 0.730; P = 0.025). CONCLUSIONS: Intravoxel incoherent motion imaging parameters with inclusion of histogram measures of heterogeneity can help differentiate malignant from benign lesions as well as various subtypes of renal cancers.