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OBJECTIVE: Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers. MATERIALS AND METHODS: In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length. RESULTS: Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001). CONCLUSIONS: These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.
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BACKGROUND: Monoexponential apparent diffusion coefficient (ADC) and biexponential intravoxel incoherent motion (IVIM) analysis of diffusion-weighted imaging is helpful in the characterization of breast tumors. However, repeatability/reproducibility studies across scanners and across sites are scarce. PURPOSE: To evaluate the repeatability and reproducibility of ADC and IVIM parameters (tissue diffusivity (Dt ), perfusion fraction (Fp ) and pseudo-diffusion (Dp )) within and across sites employing MRI scanners from different vendors utilizing 16-channel breast array coils in a breast diffusion phantom. STUDY TYPE: Phantom repeatability. PHANTOM: A breast phantom containing tubes of different polyvinylpyrrolidone (PVP) concentrations, water, fat, and sponge flow chambers, together with an MR-compatible liquid crystal (LC) thermometer. FIELD STRENGTH/SEQUENCE: Bipolar gradient twice-refocused spin echo sequence and monopolar gradient single spin echo sequence at 3 T. ASSESSMENT: Studies were performed twice in each of two scanners, located at different sites, on each of 2 days, resulting in four studies per scanner. ADCs of the PVP and water were normalized to the vendor-provided calibrated values at the temperature indicated by the LC thermometer for repeatability/reproducibility comparisons. STATISTICAL TESTS: ADC and IVIM repeatability and reproducibility within and across sites were estimated via the within-system coefficient of variation (wCV). Pearson correlation coefficient (r) was also computed between IVIM metrics and flow speed. A P value <0.05 was considered statistically significant. RESULTS: ADC and Dt demonstrated excellent repeatability (<2%; <3%, respectively) and reproducibility (both <5%) at the two sites. Fp and Dp exhibited good repeatability (mean of two sites 3.67% and 5.59%, respectively) and moderate reproducibility (mean of two sites 15.96% and 13.3%, respectively). The mean intersite reproducibility (%) of Fp /Dp /Dt was 50.96/13.68/5.59, respectively. Fp and Dt demonstrated high correlations with flow speed while Dp showed lower correlations. Fp correlations with flow speed were significant at both sites. DATA CONCLUSION: IVIM reproducibility results were promising and similar to ADC, particularly for Dt . The results were reproducible within both sites, and a progressive trend toward reproducibility across sites except for Fp . LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.
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PURPOSE: Diffusion-weighted imaging (DWI) of the abdomen has increased dramatically for both research and clinical purposes. Motion and static field inhomogeneity related challenges limit image quality of abdominopelvic imaging with the most conventional echo-planar imaging (EPI) pulse sequence. While reversed phase encoded imaging is increasingly used to facilitate distortion correction, it typically assumes one motion independent magnetic field distribution. In this study, we describe a more generalized workflow for the case of kidney DWI in which the field inhomogeneity at multiple respiratory phases is mapped and used to correct all images in a multi-contrast DWI series. METHODS: In this HIPAA-compliant and IRB-approved prospective study, 8 volunteers (6 M, ages 28-51) had abdominal imaging performed in a 3 T MRI system (MAGNETOM Prisma; Siemens Healthcare, Erlangen, Germany) with ECG gating. Coronal oblique T2-weighted HASTE images were collected for anatomical reference. Sagittal phase-contrast (PC) MRI images through the left renal artery were collected to determine systolic and diastolic phases. Cardiac triggered oblique coronal DWI were collected at 10 b-values between 0 and 800 s/mm2 and 12 directions. DWI series were distortion corrected using field maps generated by forward and reversed phase encoded b = 0 images collected over the full respiratory cycle and matched by respiratory phase. Morphologic accuracy, intraseries spatial variability, and diffusion tensor imaging (DTI) metrics mean diffusivity (MD) and fractional anisotropy (FA) were compared for results generated with no distortion correction, correction with only one respiratory bin, and correction with multiple respiratory bins across the breathing cycle. RESULTS: Computed field maps showed significant variation in static field with kidney laterality, region, and respiratory phase. Distortion corrected images showed significantly better registration to morphologic images than uncorrected images; for the left kidney, the multiple bin correction outperformed one bin correction. Line profile analysis showed significantly reduced spatial variation with multiple bins than one bin correction. DTI metrics were mostly similar between correction methods, with some differences observed in MD between uncorrected and corrected datasets. CONCLUSIONS: Our results indicate improved morphology of kidney DWI and derived parametric maps as well as reduced variability over the full image series using the motion-resolved distortion correction. This work highlights some morphologic and quantitative metric improvements can be obtained for kidney DWI when distortion correction is performed in a respiratory-resolved manner.
Subject(s)
Diffusion Magnetic Resonance Imaging , Diffusion Tensor Imaging , Humans , Adult , Middle Aged , Prospective Studies , Diffusion Magnetic Resonance Imaging/methods , Magnetic Resonance Imaging , Kidney/diagnostic imaging , Echo-Planar Imaging/methods , MotionABSTRACT
BACKGROUND: Renal diffusion-weighted imaging (DWI) involves microstructure and microcirculation, quantified with diffusion tensor imaging (DTI), intravoxel incoherent motion (IVIM), and hybrid models. A better understanding of their contrast may increase specificity. PURPOSE: To measure modulation of DWI with cardiac phase and flow-compensated (FC) diffusion gradient waveforms. STUDY TYPE: Prospective. POPULATION: Six healthy volunteers (ages: 22-48 years, five females), water phantom. FIELD STRENGTH/SEQUENCE: 3-T, prototype DWI sequence with 2D echo-planar imaging, and bipolar (BP) or FC gradients. 2D Half-Fourier Single-shot Turbo-spin-Echo (HASTE). Multiple-phase 2D spoiled gradient-echo phase contrast (PC) MRI. ASSESSMENT: BP and FC water signal decays were qualitatively compared. Renal arteries and velocities were visualized on PC-MRI. Systolic (peak velocity), diastolic (end stable velocity), and pre-systolic (before peak velocity) phases were identified. Following mutual information-based retrospective self-registration of DWI within each kidney, and Marchenko-Pastur Principal Component Analysis (MPPCA) denoising, combined IVIM-DTI analysis estimated mean diffusivity (MD), fractional anisotropy (FA), and eigenvalues (λi) from tissue diffusivity (Dt ), perfusion fraction (fp ), and pseudodiffusivity (Dp , Dp,axial , Dp,radial ), for each tissue (cortex/medulla, segmented on b0/FA respectively), phase, and waveform (BP, FC). Monte Carlo water diffusion simulations aided data interpretation. STATISTICAL TESTS: Mixed model regression probed differences between tissue types and pulse sequences. Univariate general linear model analysis probed variations among cardiac phases. Spearman correlations were measured between diffusion metrics and renal artery velocities. Statistical significance level was set at P < 0.05. RESULTS: Water BP and FC signal decays showed no differences. Significant pulse sequence dependence occurred for λ1 , λ3 , FA, Dp , fp , Dp,axial , Dp,radial in cortex and medulla, and medullary λ2 . Significant cortex/medulla differences occurred with BP for all metrics except MD (systole [P = 0.224]; diastole [P = 0.556]). Significant phase dependence occurred for Dp , Dp,axial , Dp,radial for BP and medullary λ1 , λ2 , λ3 , MD for FC. FA correlated significantly with velocity. Monte Carlo simulations indicated medullary measurements were consistent with a 34 µm tubule diameter. DATA CONCLUSION: Cardiac gating and flow compensation modulate of measurements of renal diffusion. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 2.
Subject(s)
Diffusion Tensor Imaging , Kidney , Female , Humans , Young Adult , Adult , Middle Aged , Diffusion Tensor Imaging/methods , Anisotropy , Prospective Studies , Retrospective Studies , Kidney/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Motion , WaterABSTRACT
The purpose of this work was to refine a previously published model of prostate diffusion by incorporating improved estimates of cellular diffusivity obtained by Monte Carlo simulation. Stromal and epithelial cell size and intracellular volume fraction in different grades of cancer were determined from histological images. Diffusion in different mixtures of cells, corresponding to different tumor grades, was simulated and cellular apparent diffusion coefficient and kurtosis values determined. These values were incorporated into the previously published model of prostate diffusion and model predictions compared with values found in the literature. Stromal cell radius and intracellular volume fraction were 3.74 ± 0.96 µm and 13 ± 3% respectively in normal peripheral zone (PZ), and were similar in all grades of cancer. Epithelial cell radius and intracellular volume fraction were 3.40 ± 0.15 µm and 45 ± 5% respectively in normal PZ, rising to 4.75 ± 0.20 µm and 70 ± 8% in high grade cancer. Cellular apparent diffusion coefficient and kurtosis were 1.02 µm2 ms-1 and 0.58 respectively in normal PZ, and 0.61 µm2 ms-1 and 1.15 in high grade cancer (variation in simulation values are less than 0.1%). Agreement between model predictions and measurements were good, with a mean square error of 0.22 µm2 ms-1 . Incorporation of cellular diffusion coefficient and kurtosis values obtained by Monte Carlo simulation into a model of prostate diffusion gives good agreement with published results.
Subject(s)
Monte Carlo Method , Prostate/pathology , Prostatic Neoplasms/pathology , Diffusion , Humans , MaleABSTRACT
PURPOSE: Quantitative diffusion MRI has frequently been studied as a means of grading prostate cancer. Interpretation of results is complicated by the nature of prostate tissue, which consists of four distinct compartments: vascular, ductal lumen, epithelium, and stroma. Current diffusion measurements are an ill-defined weighted average of these compartments. In this study, prostate diffusion is analyzed in terms of a model that takes explicit account of tissue compartmentalization, exchange effects, and the non-Gaussian behavior of tissue diffusion. METHOD: The model assumes that exchange between the cellular (ie, stromal plus epithelial) and the vascular and ductal compartments is slow. Ductal and cellular diffusion characteristics are estimated by Monte Carlo simulation and a two-compartment exchange model, respectively. Vascular pseudodiffusion is represented by an additional signal at b = 0. Most model parameters are obtained either from published data or by comparing model predictions with the published results from 41 studies. Model prediction error is estimated using 10-fold cross-validation. RESULTS: Agreement between model predictions and published results is good. The model satisfactorily explains the variability of ADC estimates found in the literature. CONCLUSION: A reliable model that predicts the diffusion behavior of benign and cancerous prostate tissue of different Gleason scores has been developed. Magn Reson Med 78:316-326, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Subject(s)
Body Water/chemistry , Body Water/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Image Interpretation, Computer-Assisted/methods , Models, Biological , Prostatic Neoplasms/chemistry , Prostatic Neoplasms/diagnostic imaging , Algorithms , Computer Simulation , Diffusion , Humans , Image Enhancement/methods , Male , Models, Statistical , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
PURPOSE: Diffusion MRI is used frequently to assess prostate cancer. The prostate consists of cellular tissue surrounding fluid filled ducts. Here, the diffusion properties of the ductal fluid alone were studied. Monte Carlo simulations were used to investigate ductal residence times to determine whether ducts can be regarded as forming a separate compartment and whether ductal radius could determine the Apparent Diffusion Coefficient (ADC) of the ductal fluid. METHODS: Random walks were simulated in cavities. Average residence times were estimated for permeable cavities. Signal reductions resulting from application of a Stejskal-Tanner pulse sequence were calculated in impermeable cavities. Simulations were repeated for cavities of different radii and different diffusion times. RESULTS: Residence times are at least comparable with diffusion times even in relatively high grade tumors. ADCs asymptotically approach theoretical limiting values. At large radii and short diffusion times, ADCs are similar to free diffusion. At small radii and long diffusion times, ADCs are reduced toward zero, and kurtosis approaches a value of -1.2. CONCLUSIONS: Restricted diffusion in cavities of similar sizes to prostate ducts may reduce ductal ADCs. This may contribute to reductions in total ADC seen in prostate cancer. Magn Reson Med 77:1671-1677, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
Subject(s)
Artifacts , Body Fluids/chemistry , Body Fluids/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Prostatic Neoplasms/chemistry , Prostatic Neoplasms/diagnostic imaging , Computer Simulation , Diffusion , Humans , Image Interpretation, Computer-Assisted/methods , Male , Models, Biological , Models, Statistical , Monte Carlo Method , Prostatic Neoplasms/pathology , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Mono-exponential kurtosis model is routinely fitted on diffusion weighted, magnetic resonance imaging data to describe non-Gaussian diffusion. Here, the purpose was to optimize acquisitions for this model to minimize the errors in estimating diffusion coefficient and kurtosis. Similar to a previous study, covariance matrix calculations were used, and coefficients of variation in estimating each parameter of this model were calculated. The acquisition parameter, b values, varied in discrete grids to find the optimum ones that minimize the coefficient of variation in estimating the two non-Gaussian parameters. Also, the effect of variation of the target values on the optimized values was investigated. Additionally, the results were benchmarked with Monte Carlo noise simulations. Simple correlations were found between the optimized b values and target values of diffusion and kurtosis. For small target values of the two parameters, there is higher chance of having significant errors; this is caused by maximum b value limits imposed by the scanner than the mathematical bounds. The results here, cover a wide range of parameters D and K so that they could be used in many directionally averaged diffusion weighted cases such as head and neck, prostate, etc.
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PURPOSE: To determine the echo times that provide the greatest precision in measurements of prostate T2s. T2 relaxation time measurements in the prostate are complicated by the structure of prostate tissue, which consists of fluid-filled glands surrounded by epithelial and stromal cells. Since the glands are large relative to diffusion distances, there is little water exchange between the two compartments and T2s are biexponential. Because the relative size and characteristics of the two compartments change in prostate tumors, accurate measurement of the characteristics of each may provide useful information on tumor grade. MATERIALS AND METHODS: T2s were measured in a group of 25 men with biopsy-proven prostate cancer. Subjects were scanned at 3T with a 16-echo turbo-spin echo T2-mapping sequence. Normal prostate T2s were measured in areas showing no disease. Optimum echo times for measurement of normal prostate T2s were found by calculating the covariance matrix, which provides estimates of parameter variance. Echo times that minimize T2 variance were then found by searching over grids of different echo times. Optima for four to eight echo acquisitions were found. Optima were tested by Monte Carlo simulation. RESULTS: Fast and slow T2s were 60 msec and 360 msec, respectively. The fast signal fraction was 0.6. Optimum echo times were between 0 and 780 msec, depending on the number of echoes acquired. CONCLUSION: Use of optimum echo times can substantially improve the precision of biexponential T2 measurements. This optimization is anticipated to improve prostate cancer characterization using T2 measurements.