Faculty Bibliography

PURPOSE: The aim of this study was to assess the uncertainty in estimation of MR tracer kinetic parameters and water exchange rates in T1-weighted dynamic contrast enhanced (DCE) MRI. METHODS: Simulated DCE-MRI data were used to assess four kinetic models; general kinetic model with a vascular compartment (GKM2), GKM2 combined with water exchange (SSM2), adiabatic approximation of the tissue homogeneity model (ATH), and ATH combined with water exchange (ATHX). RESULTS: In GKM2 and SSM2, increase in transfer constant (K(trans)) led to underestimation of vascular volume fraction (vb), and increase in vb led to overestimation of K(trans). Such coupling between K(trans) and vb was not observed in ATH and ATHX. The precision of estimated intracellular water lifetime (taui) was substantially improved in both SSM2 and ATHX when K(trans) > 0.3 min(-1). K(trans) and vb from ATHX model had significantly smaller errors than those from ATH model (P < 0.05). CONCLUSION: The results of this study demonstrated the feasibility of measuring taui from DCE-MRI data albeit low precision. While the inclusion of water exchange improved the accuracy of K(trans), vb, and the interstitial volume fraction estimation (ve), it lowered the precision of other kinetic model parameters within the conditions investigated in this study.

High-resolution microscopic magnetic resonance imaging (muMRI) and diffusion tensor imaging (DTI) were performed to characterize brain structural abnormalities in a mouse model of mucopolysaccharidosis type VII (MPS VII). Microscopic magnetic resonance imaging demonstrated a decrease in the volume of anterior commissure and corpus callosum and a slight increase in the volume of the hippocampus in MPS VII versus wild-type mice. Diffusion tensor imaging indices were analyzed in gray and white matter. In vivo and ex vivo DTI demonstrated significantly reduced fractional anisotropy in the anterior commissure, corpus callosum, external capsule, and hippocampus in MPS VII versus control brains. Significantly increased mean diffusivity was also found in the anterior commissure and corpus callosum from ex vivo DTI. Significantly reduced linear anisotropy was observed from the hippocampus from in vivo DTI, whereas significantly decreased planar anisotropy and spherical anisotropy were observed in the external capsule from only ex vivo DTI. There were corresponding morphologic differences in the brains of MPS VII mice by hematoxylin and eosin staining. Luxol fast blue staining demonstrated less intense staining of the corpus callosum and external capsule; myelin abnormalities in the corpus callosum were also demonstrated quantitatively in toluidine blue-stained sections and confirmed by electron microscopy. These results demonstrate the potential for muMRI and DTI for quantitative assessment of brain pathology in murine models of brain diseases.

The incidence of ductal carcinoma in situ (DCIS) has increased over the past few decades and now accounts for over 20% of newly diagnosed cases of breast cancer. Although the detection of DCIS has increased with the advent of widespread mammography screening, it is essential to have a more accurate assessment of the extent of DCIS for successful breast conservation therapy. Recent studies evaluating the detection of DCIS with magnetic resonance (MR) imaging have used high spatial resolution techniques and have increasingly been performed to screen a high-risk population as well as to evaluate the extent of disease. This work has shown that MR imaging is the most sensitive modality currently available for identifying DCIS and is more accurate than mammography in evaluating the extent of DCIS. MR imaging is particularly sensitive for identifying high-grade and intermediate-grade DCIS. DCIS may have variable morphologic features on MR images, with non-mass enhancement morphology being the most common manifestation. Less commonly, DCIS may also manifest as a mass on MR images, in which case it is most likely to be irregular. The kinetics of DCIS are also variable, with fast uptake and a plateau curve reported as the most common kinetic pattern. Additional MR imaging tools such as diffusion-weighted imaging and quantitative kinetic analysis combined with the benefit of high field strength, such as 3 T, may increase the sensitivity and specificity of breast MR imaging in the detection of DCIS. (c) RSNA, 2013.

PURPOSE: To assess dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) tracer pharmacokinetic parameters obtained with Generalized Kinetic Model (GKM) and extended Shutter Speed Model (SSM2) in renal tumors stratified by histologic subtypes. MATERIALS AND METHODS: In all, 24 patients with renal tumors were imaged at 1.5 T utilizing DCE-MRI with high temporal resolution (1.2 sec/temporal frame) prior to surgery. Tracer kinetic analysis was performed for the entire tumor using individualized aortic input function. GKM and SSM2 were employed to generate transfer constant (K(trans) ), plasma volume, and interstitial volume. These parameters, and DeltaK(trans) (K(trans) SSM2 - K(trans) GKM) were compared between tumors stratified by histologic subtype. RESULTS: There were 25 renal tumors: 15 clear cell, 4 papillary, 3 chromophobe, and 3 oncocytoma/oncocytic subtype. K(trans) GKM was significantly higher in chromophobe compared to other subtypes (P < 0.01). Using K(trans) GKM > 1.0 min(-1) , chromophobe were diagnosed with 100% sensitivity and 90.9% specificity. K(trans) SSM2 was higher than K(trans) GKM for all renal tumors except for all chromophobe and two clear cell subtype. Using K(trans) GKM > 1.0 min(-1) and Delta K(trans) < 0, chromophobe could be discriminated from other lesions with 100% accuracy. CONCLUSION: K(trans) obtained with GKM and SSM2 analysis can potentially discriminate chromophobe from other renal lesions with high accuracy. J. Magn. Reson. Imaging 2013;. (c) 2013 Wiley Periodicals, Inc.

Purpose:To develop and apply a semiautomatic method of segmenting fibroglandular tissue to quantify magnetic resonance (MR) imaging contrast material-enhancement kinetics of breast background parenchyma (BP) and lesions throughout the phases of the menstrual cycle in women with benign and malignant lesions.Materials and Methods:The institutional review board approved this retrospective HIPAA-compliant study, and informed consent was waived. From December 2008 to August 2011, 58 premenopausal women who had undergone contrast material-enhanced MR imaging and MR imaging-guided biopsy were identified. The longest time from the start of the last known period was 34 days. One lesion per patient (37 benign and 21 malignant) was analyzed. The patient groups were stratified according to the week of the menstrual cycle when MR imaging was performed. A method based on principal component analysis (PCA) was applied for quantitative analysis of signal enhancement in the BP and lesions by using the percentage of slope and percentage of enhancement. Linear regression and the Mann-Whitney U test were used to assess the association between the kinetic parameters and the week of the menstrual cycle.Results:In the women with benign lesions, percentages of slope and enhancement for both BP and lesions during week 2 were significantly (P < .05) lower than those in week 4. Percentage of enhancement in the lesion in week 2 was lower than that in week 3 (P < .05). The MR images of women with malignant lesions showed no significant difference between the weeks for any of the parameters. There was a strong positive correlation between lesion and BP percentage of slope (r = 0.72) and between lesion and BP percentage of enhancement (r = 0.67) in the benign group. There was also a significant (P = .03) difference in lesion percentage of slope between the benign and malignant groups at week 2.Conclusion:The PCA-based method can quantify contrast enhancement kinetics of BP semiautomatically, and kinetics of BP and lesions vary according to the week of the menstrual cycle in benign but not in malignant lesions.(c) RSNA, 2013.

PURPOSE: To assess two methods of fat and fibroglandular tissue (FGT) segmentation for measuring breast MRI FGT volume and FGT%, the volume percentage of FGT in the breast, in longitudinal studies. MATERIALS AND METHODS: Nine premenopausal women provided one MRI per week for 4 weeks during a natural menstrual cycle for a total of 36 datasets. We compared a fuzzy c-means (FC) and a 3-point Dixon segmentation method for estimation of changes in FGT volume and FGT% across the menstrual cycle. We also assessed whether differences due to changes in positioning each week could be minimized by coregistration, i.e., the application of the breast boundary selected at one visit to images obtained at other visits. RESULTS: FC and Dixon FGT volume were highly correlated (r = 0.93, P < 0.001), as was FC and Dixon FGT% (r = 0.86, P = 0.01), although Dixon measurements were on average 10-20% higher. Although FGT measured by both methods showed the expected pattern of increase during the menstrual cycle, the magnitude, and for one woman the direction, of change varied according to the method used. Measurements of FGT for coregistered images were in close agreement with those for which the boundaries were determined independently. CONCLUSION: The method of segmentation of fat and FGT tissue may have an impact on the results of longitudinal studies of changes in breast MRI FGT. J. Magn. Reson. Imaging 2012;. (c) 2012 Wiley Periodicals, Inc.

OBJECTIVES: We conducted a pilot study to identify whether MRI parameters are sensitive to hormone-induced changes in the breast during the natural menstrual cycle and whether changes could also be observed during an oral contraceptive (OC) cycle. MATERIALS AND METHODS: The New York University Langone Medical Center Institutional Review Board approved this HIPAA-compliant prospective study. All participants provided written informed consent. Participants were aged 24-31 years.We measured several non-contrast breast MRI parameters during each week of a single menstrual cycle (among 9 women) and OC cycle (among 8 women). Hormones were measured to confirm ovulation and classify menstrual cycle phase among naturally cycling women and to monitor OC compliance among OC users. We investigated how the non-contrast MRI parameters of breast fibroglandular tissue (FGT), apparent diffusion coefficient (ADC), magnetization transfer ratio (MTR), and transverse relaxation time (T2) varied over the natural and the OC cycles. RESULTS: We observed significant increases in MRI FGT% and ADC in FGT, and longer T2 in FGT in the luteal vs. follicular phase of the menstrual cycle. We did not observe any consistent pattern of change for any of the MRI parameters among women using OCs. CONCLUSIONS: MRI is sensitive to hormone-induced breast tissue changes during the menstrual cycle. Larger studies are needed to assess whether MRI is also sensitive to the effects of exogenous hormones, such as various OC formulations, on the breast tissue of young premenopausal women.

PURPOSE: To evaluate feasibility of using magnetization transfer ratio (MTR) in conjunction with dynamic contrast-enhanced MRI (DCE-MRI) for differentiation of benign and malignant breast lesions at 3 Tesla. MATERIALS AND METHODS: This prospective study was IRB and HIPAA compliant. DCE-MRI scans followed by MT imaging were performed on 41 patients. Regions of interest (ROIs) were drawn on co-registered MTR and DCE postcontrast images for breast structures, including benign lesions (BL) and malignant lesions (ML). Initial enhancement ratio (IER) and delayed enhancement ratio (DER) were calculated, as were normalized MTR, DER, and IER (NMTR, NDER, NIER) values. Diagnostic accuracy analysis was performed. RESULTS: Mean MTR in ML was lower than in BL (P < 0.05); mean DER and mean IER in ML were significantly higher than in BL (P < 0.01, P < 0.001). NMTR, NDER, and NIER were significantly lower in ML versus BL (P < 0.007, P < 0.001, P < 0.001). IER had highest diagnostic accuracy (77.6%), sensitivity (86.2%), and area under the ROC curve (.879). MTR specificity was 100%. Logistic regression modeling with NMTR and NIER yielded best results for BL versus ML (sensitivity 93.1%, specificity 80%, AUC 0.884, accuracy 83.7%). CONCLUSION: Isolated quantitative DCE analysis may increase specificity of breast MR for differentiating BL and ML. DCE-MRI with NMTR may produce a robust means of evaluating breast lesions. J. Magn. Reson. Imaging 2013;37:138-145. (c) 2012 Wiley Periodicals, Inc.

OBJECTIVE: The objective of our study was to predict response to chemoradiation therapy in patients with head and neck squamous cell carcinoma (HNSCC) by combined use of diffusion-weighted imaging (DWI) and high-spatial-resolution, high-temporal-resolution dynamic contrast-enhanced MRI (DCE-MRI) parameters from primary tumors and metastatic nodes. SUBJECTS AND METHODS: Thirty-two patients underwent pretreatment DWI and DCE-MRI using a modified radial imaging sequence. Postprocessing of data included motion-correction algorithms to reduce motion artifacts. The median apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), extracellular extravascular volume fraction (v(e)), and plasma volume fraction (v(p)) were computed from primary tumors and nodal masses. The quality of the DCE-MRI maps was estimated using a threshold median chi-square value of 0.10 or less. Multivariate logistic regression and receiver operating characteristic curve analyses were used to determine the best model to discriminate responders from nonresponders. RESULTS: Acceptable chi(2) values were observed from 84% of primary tumors and 100% of nodal masses. Five patients with unsatisfactory DCE-MRI data were excluded and DCE-MRI data for three patients who died of unrelated causes were censored from analysis. The median follow-up for the remaining patients (n = 24) was 23.72 months. When ADC and DCE-MRI parameters (K(trans), v(e), v(p)) from both primary tumors and nodal masses were incorporated into multivariate logistic regression analyses, a considerably higher discriminative accuracy (area under the curve [AUC] = 0.85) with a sensitivity of 81.3% and specificity of 75% was observed in differentiating responders (n = 16) from nonresponders (n = 8). CONCLUSION: The combined use of DWI and DCE-MRI parameters from both primary tumors and nodal masses may aid in prediction of response to chemoradiation therapy in patients with HNSCC.

Diffusion tensor imaging (DTI) is highly sensitive in detecting brain structure and connectivity phenotypes in autism spectrum disorders (ASD). Since one of the core symptoms of ASD is reduced sociability (reduced tendency to seek social interaction), we hypothesized that DTI will be sensitive in detecting neural phenotypes that correlate with decreased sociability in mouse models. Relative to C57BL/6J (B6) mice, juvenile BALB/cJ mice show reduced sociability. We performed social approach test in a three-chambered apparatus and in-vivo longitudinal DTI at post-natal days 30, 50 and 70 days-of-age in BALB/cJ (n=32) and B6 (n=15) mice to assess the correlation between DTI and sociability and to evaluate differences in DTI parameters between these two strains. Fractional anisotropy (FA) and mean diffusivity (MD) values from in-vivo DTI data were analyzed from white matter (corpus callosum, internal and external capsule) and gray matter (cerebral cortex, frontal motor cortex, hippocampus, thalamus and amygdaloid) regions based on their relevance to ASD. A moderate but significant (p<0.05) negative correlation between sociability and FA in hippocampus and frontal motor cortex was noted for BALB/cJ mice at 30 days-of-age. Significant differences in FA and MD values between BALB/cJ and B6 mice were observed in most white and gray matter areas at all three time points. Significant differences in developmental trajectories of FA and MD values from thalamus and frontal motor cortex were also observed between BALB/cJ and B6, indicating relative under-connectivity in BALB/cJ mice. These results indicate that DTI may be used as an in-vivo, non-invasive imaging method to assess developmental trajectories of brain connectivity in mouse models of neurodevelopmental and behavioral disorders.