Henry Rusinek

Hippocampal hypometabolism predicts cognitive decline from normal aging.

OBJECTIVE This longitudinal study used FDG-PET imaging to predict and monitor cognitive decline from normal aging. METHODS Seventy-seven 50-80-year-old normal (NL) elderly received longitudinal clinical examinations over 6-14 years (561 person-years, mean per person 7.2 years). All subjects had a baseline FDG-PET scan and 55 subjects received follow-up PET exams. Glucose metabolic rates (MRglc) in the hippocampus and cortical regions were examined as predictors and correlates of clinical decline. RESULTS Eleven NL subjects developed dementia, including six with Alzheimers disease (AD), and 19 declined to mild cognitive impairment (MCI), on average 8 years after the baseline exam. The baseline hippocampal MRglc predicted decline from NL to AD (81% accuracy), including two post-mortem confirmed cases, from NL to other dementias (77% accuracy), and from NL to MCI (71% accuracy). Greater rates of hippocampal and cortical MRglc reductions were found in the declining as compared to the non-declining NL. CONCLUSIONS Hippocampal MRglc reductions using FDG-PET during normal aging predict cognitive decline years in advance of the clinical diagnosis. Future studies are needed to increase preclinical specificity in differentiating dementing disorders.

Advanced Liver Fibrosis: Diagnosis with 3D Whole-Liver Perfusion MR Imaging—Initial Experience

Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. The purpose of this study was to prospectively evaluate sensitivity and specificity of various estimated perfusion parameters at three-dimensional (3D) perfusion magnetic resonance (MR) imaging of the liver in the diagnosis of advanced liver fibrosis (stage >or= 3), with histologic analysis, liver function tests, or MR imaging as the reference standard. Whole-liver 3D perfusion MR imaging was performed in 27 patients (17 men, 10 women; mean age, 55 years) after dynamic injection of 8-10 mL of gadopentetate dimeglumine. The following estimated perfusion parameters were measured with a dual-input single-compartment model: absolute arterial blood flow (F(a)), absolute portal venous blood flow (F(p)), absolute total liver blood flow (F(t)) (F(t) = F(a) + F(p)), arterial fraction (ART), portal venous fraction (PV), distribution volume (DV), and mean transit time (MTT) of gadopentetate dimeglumine. Patients were assigned to two groups (those with fibrosis stage <or= 2 and those with fibrosis stage >or= 3), and the nonparametric Mann-Whitney test was used to compare F(a), F(p), F(t), ART, PV, DV, and MTT between groups. Receiver operating characteristic curve analysis was used to assess the utility of perfusion estimates as predictors of advanced liver fibrosis. There were significant differences for all perfusion MR imaging-estimated parameters except F(p) and F(t). There was an increase in F(a), ART, DV, and MTT and a decrease in PV in patients with advanced fibrosis compared with those without advanced fibrosis. DV had the best performance, with an area under the receiver operating characteristic curve of 0.824, a sensitivity of 76.9% (95% confidence interval: 46.2%, 94.7%), and a specificity of 78.5% (95% confidence interval: 49.2%, 95.1%) in the prediction of advanced fibrosis.

Intravoxel Incoherent Motion and Diffusion-Tensor Imaging in Renal Tissue under Hydration and Furosemide Flow Challenges

PURPOSE To assess the reproducibility and the distribution of intravoxel incoherent motion (IVIM) and diffusion-tensor (DT) imaging parameters in healthy renal cortex and medulla at baseline and after hydration or furosemide challenges. MATERIALS AND METHODS Using an institutional review board-approved HIPAA-compliant protocol with written informed consent, IVIM and DT imaging were performed at 3 T in 10 volunteers before and after water loading or furosemide administration. IVIM (apparent diffusion coefficient [ADC], tissue diffusivity [D(t)], perfusion fraction [f(p)], pseudodiffusivity [D(p)]) and DT (mean diffusivity [MD], fractional anisotropy [FA], eigenvalues [λ(i)]) imaging parameters and urine output from serial bladder volumes were calculated. (a)Reproducibility was quantified with coefficient of variation, intraclass correlation coefficient, and Bland-Altman limits of agreement; (b) contrast and challenge response were quantified with analysis of variance; and (c) Pearson correlations were quantified with urine output. RESULTS Good reproducibility was found for ADC, D(t), MD, FA, and λ(i) (average coefficient of variation, 3.7% [cortex] and 5.0% [medulla]), and moderate reproducibility was found for D(p), f(p), and f(p) · D(p) (average coefficient of variation, 18.7% [cortex] and 25.9% [medulla]). Baseline cortical diffusivities significantly exceeded medullary values except D(p), for which medullary values significantly exceeded cortical values, and λ(1,) which showed no contrast. ADC, D(t), MD, and λ(i) increased significantly for both challenges. Medullary diffusivity increases were dominated by transverse diffusion (1.72 ± 0.09 [baseline] to 1.79 ± 0.10 [hydration] μm(2)/msec, P = .0059; or 1.86 ± 0.07 [furosemide] μm(2)/msec, P = .0094). Urine output correlated with cortical ADC with furosemide (r = 0.7, P = .034) and with medullary λ(1) (r = 0.83, P = .0418), λ(2) (r = 0.85, P = .0301), and MD (r = 0.82, P = .045) with hydration. CONCLUSION Diffusion MR metrics are sensitive to flow changes in kidney induced by diuretic challenges. The results of this study suggest that vascular flow, tubular dilation, water reabsorption, and intratubular flow all play important roles in diffusion-weighted imaging contrast.

Optimal k-Space Sampling for Dynamic Contrast-Enhanced MRI with an Application to MR Renography

For time‐resolved acquisitions with k‐space undersampling, a simulation method was developed for selecting imaging parameters based on minimization of errors in signal intensity versus time and physiologic parameters derived from tracer kinetic analysis. Optimization was performed for time‐resolved angiography with stochastic trajectories (TWIST) algorithm applied to contrast‐enhanced MR renography. A realistic 4D phantom comprised of aorta and two kidneys, one healthy and one diseased, was created with ideal tissue time‐enhancement pattern generated using a three‐compartment model with fixed parameters, including glomerular filtration rate (GFR) and renal plasma flow (RPF). TWIST acquisitions with different combinations of sampled central and peripheral k‐space portions were applied to this phantom. Acquisition performance was assessed by the difference between simulated signal intensity (SI) and calculated GFR and RPF and their ideal values. Sampling of the 20% of the center and 1/5 of the periphery of k‐space in phase‐encoding plane and data‐sharing of the remaining 4/5 minimized the errors in SI (<5%), RPF, and GFR (both <10% for both healthy and diseased kidneys). High‐quality dynamic human images were acquired with optimal TWIST parameters and 2.4 sec temporal resolution. The proposed method can be generalized to other dynamic contrast‐enhanced MRI applications, e.g., MR angiography or cancer imaging. Magn Reson Med, 2009.

Optimization of b-value sampling for diffusion-weighted imaging of the kidney

Diffusion‐weighted imaging (DWI) involves data acquisitions at multiple b values. In this paper, we presented a method of selecting the b values that maximize estimation precision of the biexponential analysis of renal DWI data. We developed an error propagation factor for the biexponential model, and proposed to optimize the b‐value samplings by minimizing the error propagation factor. A prospective study of four healthy human subjects (eight kidneys) was done to verify the feasibility of the proposed protocol and to assess the validity of predicted precision for DWI measures, followed by Monte Carlo simulations of DWI signals based on acquired data from renal lesions of 16 subjects. In healthy subjects, the proposed methods improved precision (P = 0.003) and accuracy (P < 0.001) significantly in region‐of‐interest based biexponential analysis. In Monte Carlo simulation of renal lesions, the b‐sampling optimization lowered estimation error by at least 20–30% compared with uniformly distributed b values, and improved the differentiation between malignant and benign lesions significantly. In conclusion, the proposed method has the potential of maximizing the precision and accuracy of the biexponential analysis of renal DWI. Magn Reson Med, 2011.

Performance of an automated segmentation algorithm for 3D MR renography

The accuracy and precision of an automated graph‐cuts (GC) segmentation technique for dynamic contrast‐enhanced (DCE) 3D MR renography (MRR) was analyzed using 18 simulated and 22 clinical datasets. For clinical data, the error was 7.2 ± 6.1 cm3 for the cortex and 6.5 ± 4.6 cm3 for the medulla. The precision of segmentation was 7.1 ± 4.2 cm3 for the cortex and 7.2 ± 2.4 cm3 for the medulla. Compartmental modeling of kidney function in 22 kidneys yielded a renal plasma flow (RPF) error of 7.5% ± 4.5% and single‐kidney GFR error of 13.5% ± 8.8%. The precision was 9.7% ± 6.4% for RPF and 14.8% ± 11.9% for GFR. It took 21 min to segment one kidney using GC, compared to 2.5 hr for manual segmentation. The accuracy and precision in RPF and GFR appear acceptable for clinical use. With expedited image processing, DCE 3D MRR has the potential to expand our knowledge of renal function in individual kidneys and to help diagnose renal insufficiency in a safe and noninvasive manner. Magn Reson Med 57:1159–1167, 2007.

Diffusion-weighted intravoxel incoherent motion imaging of renal tumors with histopathologic correlation

PurposeThe aim of this study was to use intravoxel incoherent motion diffusion-weighted imaging to discriminate subtypes of renal neoplasms and to assess agreement between intravoxel incoherent motion (perfusion fraction, fp) and dynamic contrast-enhanced magnetic resonance imaging (MRI) metrics of tumor vascularity. Subjects and MethodsIn this Health Insurance Portability and Accountability Act–compliant, institutional review board–approved prospective study, 26 patients were imaged at 1.5-T MRI using dynamic contrast-enhanced MRI with high temporal resolution and diffusion-weighted imaging using 8 b values (range, 0-800 s/mm2). Perfusion fraction (fp), tissue diffusivity (Dt), and pseudodiffusivity (Dp) were calculated using biexponential fitting of the diffusion data. Apparent diffusion coefficient (ADC) was calculated with monoexponential fit using 3 b values of 0, 400, and 800 s/mm2. Dynamic contrast-enhanced data were processed with a semiquantitative method to generate model-free parameter cumulative initial area under the curve of gadolinium concentration at 60 seconds (CIAUC60). Perfusion fraction, Dt, Dp, ADC, and CIAUC60 were compared between different subtypes of renal lesions. Perfusion fraction was correlated with CIAUC60. ResultsWe examined 14 clear cell, 4 papillary, 5 chromophobe, and 3 cystic renal cell carcinomas (RCCs). Although fp had higher accuracy (area under the curve, 0.74) for a diagnosis of clear cell RCC compared with Dt or ADC, the combination of fp and Dt had the highest accuracy (area under the curve, 0.78). The combination of fp and Dt diagnosed papillary RCC and cystic RCC with 100% accuracy, and clear cell RCC and chromophobe RCC, with 86.5% accuracy. There was significant strong correlation between fp and CIAUC60 (r = 0.82; P < 0.001). ConclusionIntravoxel incoherent motion parameters fp and Dt can discriminate renal tumor subtypes. Perfusion fraction demonstrates good correlation with CIAUC60 and can assess degree of tumor vascularity without the use of exogenous contrast agent.

Estimates of glomerular filtration rate from MR renography and tracer kinetic models.

To compare six methods for calculating the single‐kidney glomerular filtration rate (GFR) from T1‐weighted magnetic resonance (MR) renography (MRR) against reference radionuclide measurements.

Fully automatic segmentation of the brain from T1-weighted MRI using Bridge Burner algorithm.

To validate Bridge Burner, a new brain segmentation algorithm based on thresholding, connectivity, surface detection, and a new operator of constrained growing.

Characterizing brain oxygen metabolism in patients with multiple sclerosis with T2-relaxation-under-spin-tagging MRI

In this study, venous oxygen saturation and oxygen metabolic changes in multiple sclerosis (MS) patients were assessed using a recently developed T2-relaxation-under-spin-tagging (TRUST) magnetic resonance imaging (MRI), which measures the superior sagittal venous sinus blood oxygenation (Yv) and cerebral metabolic rate of oxygen (CMRO 2 ), an index of global oxygen consumption. Thirty patients with relapsing-remitting MS and 30 age-matched healthy controls were studied using TRUST at 3 T MR. The mean expanded disability status scale (EDSS) of the patients was 2.3 (range, 0 to 5.5). We found significantly increased Yv (P<0.0001) and decreased CMRO 2 (P=0.003) in MS patients (mean±s.d.: 65.9%±5.1% and 138.8±35.4 μmol per 100 g per minute) as compared with healthy control subjects (60.2%±4.0% and 180.2±24.8 μmol per 100 g per minute, respectively), implying decrease of oxygen consumption in MS. There was a significant positive correlation between Yv and EDSS and between Yv and lesion load in MS patients (n=30); on the contrary, there was a significant negative correlation between CMRO 2 and EDSS and between CMRO 2 and lesion load (n=12). There was no correlation between Yv and brain atrophy measures. This study showed preliminary evidence of the potential utility of TRUST in global oxygen metabolism. Our results of significant underutilization of oxygen in MS raise important questions regarding mitochondrial respiratory dysfunction and neurodegeneration of the disease.