Exercise-induced calf muscle hyperemia quantified with dynamic blood oxygen level-dependent (BOLD) imaging.

Muscle hyperemia in exercise is usually the combined result of increased cardiac output and local muscle vasodilation, with the latter reflecting muscle's capacity for increased blood perfusion to support exercise. In this study, we aim to quantify muscle's vasodilation capability with dynamic BOLD imaging. A deoxyhemoglobin-kinetics model is proposed to analyze dynamic BOLD signals acquired during exercise recovery, deriving a hyperemia index (HI) for a muscle group of interest. We demonstrated the method's validity with calf muscles of healthy subjects who performed plantar flexion for muscle stimulation. In a test with exercise load incrementally increasing from 0 to 16 lbs., gastrocnemius HI showed considerable variance among the 4 subjects, but with a consistent trend, i.e. low at light load (e.g. 0-6 lbs) and linearly increasing at heavy load. The high variability among different subjects was confirmed with the other 10 subjects who exercised with a same moderate load of 8 lbs., with coefficient of variance among subjects' medial gastrocnemius 87.8%, lateral gastrocnemius 111.8% and soleus 132.3%. These findings align with the fact that intensive exercise induces high muscle hyperemia, but a comparison among different subjects is hard to make, presumably due to the subjects' different rate of oxygen utilization. For the same 10 subjects who exercised with load of 8 lbs., we also performed dynamic contrast enhanced (DCE) MRI to measure muscle perfusion (F). With a moderate correlation of 0.654, HI and F displayed three distinctive responses of calf muscles: soleus of all the subjects were in the cluster of low F and low HI, and gastrocnemius of most subjects had high F and either low or high HI. This finding suggests that parameter F encapsulates blood flow through vessels of all sizes, but BOLD-derived HI focuses on capillary flow and therefore is a more specific indicator of muscle vasodilation. In conclusion, the proposed hyperemia index has the potential of quantitatively assessing muscle vasodilation induced with exercise.

Accurate exclusion of kidney regions affected by susceptibility artifact in blood oxygenation level-dependent (BOLD) images using deep-learning-based segmentation.

Susceptibility artifact (SA) is common in renal blood oxygenation level-dependent (BOLD) images, and including the SA-affected region could induce much error in renal oxygenation quantification. In this paper, we propose to exclude kidney regions affected by SA in gradient echo images with different echo times (TE), based on a deep-learning segmentation approach. For kidney segmentation, a ResUNet was trained with 4000 CT images and then tuned with 60 BOLD images. Verified by a Monte Carlo simulation, the presence of SA leads to a bilinear pattern for the segmented area of kidney as function of TE, and the segmented kidney in the image of turning point's TE would exclude SA-affected regions. To evaluate the accuracy of excluding SA-affected regions, we compared the SA-free segmentations by the proposed method against manual segmentation by an experienced user for BOLD images of 35 subjects, and found DICE of 93.9% ± 3.4%. For 10 kidneys with severe SA, the DICE was 94.5% ± 1.7%, for 14 with moderate SA, 92.8% ± 4.7%, and for 46 with mild or no SA, 94.3% ± 3.8%. For the three sub-groups of kidneys, correction of SA led to a decrease of R2* of 8.5 ± 2.8, 4.7 ± 1.8, and 1.6 ± 0.9 s-1, respectively. In conclusion, the proposed method is capable of segmenting kidneys in BOLD images and at the same time excluding SA-affected region in a fully automatic way, therefore can potentially improve both speed and accuracy of the quantification procedure of renal BOLD data.

Exercise-induced calf muscle hyperemia: Rapid mapping of magnetic resonance imaging using deep learning approach.

Exercise-induced hyperemia in calf muscles was recently shown to be quantifiable with high-resolution magnetic resonance imaging (MRI). However, processing of the MRI data to obtain muscle-perfusion maps is time-consuming. This study proposes to substantially accelerate the mapping of muscle perfusion using a deep-learning method called artificial neural network (NN). Forty-eight MRI scans were acquired from 21 healthy subjects and patients with peripheral artery disease (PAD). For optimal training of NN, different training-data sets were compared, investigating the effect of data diversity and reference perfusion accuracy. Reference perfusion was estimated by tracer kinetic model fitting initialized with multiple values (multigrid model fitting). Result: The NN method was much faster than tracer kinetic model fitting. To generate a perfusion map of matrix 128 × 128 on a same computer, multigrid model fitting took about 80 min, single-grid or regular model fitting about 3 min, while the NN method took about 1 s. Compared to the reference values, NN trained with a diverse group gave estimates with mean absolute error (MAE) of 15.9 ml/min/100g and correlation coefficient (R) of 0.949, significantly more accurate than regular model fitting (MAE 22.3 ml/min/100g, R 0.889, p < .001). Conclusion: the NN method enables rapid perfusion mapping, and if properly trained, estimates perfusion with accuracy comparable to multigrid model fitting.

Renal perfusion imaging by MRI.

Renal perfusion can be quantitatively assessed by multiple magnetic resonance imaging (MRI) methods, including dynamic contrast enhanced (DCE), arterial spin labeling (ASL), and diffusion-weighted imaging with intravoxel incoherent motion (IVIM) analysis. In this review we summarize the advances in the field of renal-perfusion MRI over the past 5 years. The review starts with a brief introduction of relevant MRI methods, followed by a discussion of recent technical developments. In the main section of the review, we examine the clinical and preclinical applications for three disease populations: chronic kidney disease, renal transplant, and renal tumors. The DCE method has been routinely used for assessing renal tumors but not other renal diseases. As a noncontrast alternative, ASL was extensively explored in both preclinical and clinical applications and showed much promise. Protocol standardization for the methods is desperately needed, and then large-scale clinical trials for the methods can be initiated prior to their broad clinical use. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:369-379.

Consensus-based technical recommendations for clinical translation of renal BOLD MRI.

Harmonization of acquisition and analysis protocols is an important step in the validation of BOLD MRI as a renal biomarker. This harmonization initiative provides technical recommendations based on a consensus report with the aim to move towards standardized protocols that facilitate clinical translation and comparison of data across sites. We used a recently published systematic review paper, which included a detailed summary of renal BOLD MRI technical parameters and areas of investigation in its supplementary material, as the starting point in developing the survey questionnaires for seeking consensus. Survey data were collected via the Delphi consensus process from 24 researchers on renal BOLD MRI exam preparation, data acquisition, data analysis, and interpretation. Consensus was defined as ≥ 75% unanimity in response. Among 31 survey questions, 14 achieved consensus resolution, 12 showed clear respondent preference (65-74% agreement), and 5 showed equal (50/50%) split in opinion among respondents. Recommendations for subject preparation, data acquisition, processing and reporting are given based on the survey results and review of the literature. These technical recommendations are aimed towards increased inter-site harmonization, a first step towards standardization of renal BOLD MRI protocols across sites. We expect this to be an iterative process updated dynamically based on progress in the field.

Consensus-based technical recommendations for clinical translation of renal ASL MRI.

OBJECTIVES: This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. METHODS: An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. RESULTS: Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. DISCUSSION: This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding.

Exercise-stimulated arterial transit time in calf muscles measured by dynamic contrast-enhanced magnetic resonance imaging.

The primary goal of this study was to evaluate arterial transit time (ATT) in exercise-stimulated calf muscles as a promising indicator of muscle function. Following plantar flexion, ATT was measured by dynamic contrast-enhanced (DCE) MRI in young and elderly healthy subjects and patients with peripheral artery disease (PAD). In the young healthy subjects, gastrocnemius ATT decreased significantly (P < 0.01) from 4.3 ± 1.5 to 2.4 ± 0.4 sec when exercise load increased from 4 lbs to 16 lbs. For the same load of 4 lbs, gastrocnemius ATT was lower in the elderly healthy subjects (3.2 ± 1.1 sec; P = 0.08) and in the PAD patients (2.4 ± 1.2 sec; P = 0.02) than in the young healthy subjects. While the sensitivity of the exercise-stimulated ATT is diagnostically useful, it poses a challenge for arterial spin labeling (ASL), a noncontrast MRI method for measuring muscle perfusion. As a secondary goal of this study, we assessed the impact of ATT on ASL-measured perfusion with ASL data of multiple post labeling delays (PLDs) acquired from a healthy subject. Perfusion varied substantially with PLD in the activated gastrocnemius, which can be attributed to the ATT variability as verified by a simulation. In conclusion, muscle ATT is sensitive to exercise intensity, and it potentially reflects the functional impact of aging and PAD on calf muscles. For precise measurement of exercise-stimulated muscle perfusion, it is recommended that ATT be considered when quantifying muscle ASL data.

Exercise-induced calf muscle hyperemia: quantitative mapping with low-dose dynamic contrast enhanced magnetic resonance imaging.

Peripheral artery disease (PAD) in the lower extremities often leads to intermittent claudication. In the present study, we proposed a low-dose DCE MRI protocol for quantifying calf muscle perfusion stimulated with plantar flexion and multiple new metrics for interpreting perfusion maps, including the ratio of gastrocnemius over soleus perfusion (G/S; for assessing the vascular redistribution between the two muscles) and muscle perfusion normalized by whole body perfusion (for quantifying the muscle's active hyperemia). Twenty-eight human subjects participated in this Institutional Review Board-approved study, with 10 healthy subjects ( group A) for assessing interday reproducibility and 8 healthy subjects ( group B) for exploring the relationship between plantar-flexion load and induced muscle perfusion. In a pilot group of five elderly healthy subjects and five patients with PAD ( group C), we proposed a protocol that measured perfusion for a low-intensity exercise and for an exhaustion exercise in a single MRI session. In group A, perfusion estimates for calf muscles were highly reproducible, with correlation coefficients of 0.90-0.93. In group B, gastrocnemius perfusion increased linearly with the exercise workload ( P < 0.05). With the low-intensity exercise, patients with PAD in group C showed substantially lower gastrocnemius perfusion compared with elderly healthy subjects [43.4 (SD 23.5) vs. 106.7 (SD 73.2) ml·min-1·100 g-1]. With exhaustion exercise, G/S [1.0 (SD 0.4)] for patients with PAD was lower than both its low-intensity level [1.9 (SD 1.3)] and the level in elderly healthy subjects [2.7 (SD 2.1)]. In conclusion, the proposed MRI protocol and the new metrics are feasible for quantifying exercise-induced muscle hyperemia, a promising functional test of PAD. NEW & NOTEWORTHY To quantitatively map exercise-induced hyperemia in calf muscles, we proposed a high-resolution MRI method shown to be highly reproducible and sensitive to exercise load. With the use of low contrast, it is feasible to measure calf muscle hyperemia for both low-intensity and exhaustion exercises in a single MRI session. The newly proposed metrics for interpreting perfusion maps are promising for quantifying intermuscle vascular redistribution or a muscle's active hyperemia.

Sampling arterial input function (AIF) from peripheral arteries: Comparison of a temporospatial-feature based method against conventional manual method.

It is often difficult to accurately localize small arteries in images of peripheral organs, and even more so with vascular abnormality vasculatures, including collateral arteries, in peripheral artery disease (PAD). This poses a challenge for manually sampling arterial input function (AIF) in quantifying dynamic contrast-enhanced (DCE) MRI data of peripheral organs. In this study, we designed a multi-step screening approach that utilizes both the temporal and spatial information of the dynamic images, and is presumably suitable for localizing small and unpredictable peripheral arteries. In 41 DCE MRI datasets acquired from human calf muscles, the proposed method took <5 s on average for sampling AIF for each case, much more efficient than the manual sampling method; AIFs by the two methods were comparable, with Pearson's correlation coefficient of 0.983 ±â€¯0.004 (p-value < 0.01) and relative difference of 2.4% ±â€¯2.6%. In conclusion, the proposed temporospatial-feature based method enables efficient and accurate sampling of AIF from peripheral arteries, and would improve measurement precision and inter-observer consistency for quantitative DCE MRI of peripheral tissues.

Quantitative characterization of glomerular fibrosis with magnetic resonance imaging: a feasibility study in a rat glomerulonephritis model.

Glomerular fibrosis occurs in the early stages of multiple renal diseases, including hypertensive and diabetic nephropathy. Conventional assessment of glomerular fibrosis relies on kidney biopsy, which is invasive and does not reflect physiological aspects such as blood perfusion. In this study, we sought to assess potential changes of cortical perfusion and microstructure at different degrees of glomerular fibrosis using magnetic resonance imaging (MRI). A rat model of glomerular fibrosis was induced by injecting anti-Thy-1 monoclonal antibody OX-7 to promote mesangial extracellular matrix proliferation. For six rats on day 5 and five rats on day 12 after the induction, we measured renal cortical perfusion and spin-spin relaxation time (T2) in a 3-Tesla MRI scanner. T2 reflects tissue microstructural changes. Glomerular fibrosis severity was evaluated by histological analysis and proteinuria. Four rats without fibrosis were included as controls. In the control rats, the periodic acid-Schiff (PAS)-positive area was 22 ± 1% of total glomerular tuft, which increased significantly to 56 ± 12% and 45 ± 10% in the day 5 and day 12 fibrotic groups, respectively ( P < 0.01). For the three groups (control, day 5, and day 12 after OX-7 injection), cortical perfusion was 7.27 ± 2.54, 3.78 ± 2.17, and 3.32 ± 2.62 ml·min-1·g-1, respectively, decreasing with fibrosis severity ( P < 0.01), and cortical T2 was 75.2 ± 4.6, 84.1 ± 3.0, and 87.9 ± 5.6 ms, respectively ( P < 0.01). In conclusion, extracellular matrix proliferation in glomerular mesangial cells severely diminished blood flow through the glomeruli and also altered cortical microstructure to increase cortical T2. The MRI-measured parameters are proven to be sensitive markers for characterizing glomerular fibrosis.

Magnetic Resonance Imaging of the Fibrotic Kidney.

Magnetic resonance imaging (MRI) has been used for many years for anatomic evaluation of the kidney. Recently developed methods attempt to go beyond anatomy to give information about the health and function of the kidneys. Several methods, including diffusion-weighted MRI, renal blood oxygen level-dependent MRI, renal MR elastography, and renal susceptibility imaging, show promise for providing unique insight into kidney function and severity of fibrosis. However, substantial limitations in accuracy and practicality limit the immediate clinical application of each method. Further development and improvement are necessary to achieve the ideal of a noninvasive image-based measure of renal fibrosis. Our brief review provides a short explanation of these emerging MRI methods and outlines the promising initial results obtained with each as well as current limitations and barriers to clinical implementation.

Functional Magnetic Resonance Imaging of the Kidneys-With and Without Gadolinium-Based Contrast.

Assessment of renal function with magnetic resonance imaging (MRI) has been actively explored in the past decade. In this review, we introduce the principle of MRI and review recent progress of MRI methods (contrast enhanced and noncontrast) in assessing renal function. Contrast-enhanced MRI using ultra-low dose of gadolinium-based agent has been validated for measuring single-kidney glomerular filtration rate and renal plasma flow accurately. For routine functional test, contrast-enhanced MRI may not replace the simple serum-creatinine method. However, for patients with renal diseases, it is often worthy to perform MRI to accurately monitor renal function, particularly for the diseased kidney. As contrast-enhanced MRI is already an established clinical tool for characterizing renal structural abnormalities, including renal mass and ureteral obstruction, it is possible to adapt the clinical MRI protocol to measure single-kidney glomerular filtration rate and renal plasma flow, as demonstrated by recent studies. What makes MRI unique is the promise of its noncontrast methods. These methods include arterial spin labeling for tissue perfusion, blood oxygen-level dependent for blood and tissue oxygenation, and diffusion-weighted imaging for water diffusion. For each method, we reviewed recent findings and summarized challenges.

BOLD quantified renal pO2 is sensitive to pharmacological challenges in rats.

PURPOSE: Blood oxygen level-dependent (BOLD) MRI has been effectively used to monitor changes in renal oxygenation. However, R2* (or T2*) is not specific to blood oxygenation and is dependent on other factors. This study investigates the use of a statistical model that takes these factors into account and maps BOLD MRI measurements to blood pO2. METHODS: Spin echo and gradient echo images were obtained in six Sprague-Dawley rats and R2 and R2* maps were computed. Measurements were made at baseline, post-nitric oxide synthase inhibitor (L-NAME), and post-furosemide administration. A simulation of each region was performed to map R2' (computed as R2*-R2) to blood pO2. RESULTS: At baseline, blood pO2 in the outer medulla was 30.5 ± 1.2 mmHg and 51.9 ± 5.2 mmHg in the cortex, in agreement with previous invasive studies. Blood pO2 was found to decrease within the outer medulla following L-NAME (P < 0.05) and increase after furosemide (P < 0.05). Blood pO2 in the cortex increased following furosemide (P < 0.05). CONCLUSIONS: Model-derived blood pO2 is sensitive to pharmacological challenges, and baseline pO2 is comparable to literature values. Reporting pO2 instead of R2* could lead to a greater clinical impact of renal BOLD MRI and facilitate the identification of hypoxic regions. Magn Reson Med 78:297-302, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Renal plasma flow (RPF) measured with multiple-inversion-time arterial spin labeling (ASL) and tracer kinetic analysis: Validation against a dynamic contrast-enhancement method.

PURPOSE: To propose and validate a method for accurately quantifying renal plasma flow (RPF) with arterial spin labeling (ASL). MATERIALS AND METHODS: The proposed method employs a tracer-kinetic approach and derives perfusion from the slope of the ASL difference signal sampled at multiple inversion-times (TIs). To validate the method's accuracy, we performed a HIPAA-compliant and IRB-approved study with 15 subjects (9 male, 6 female; age range 24-73) to compare RPF estimates obtained from ASL to those from a more established dynamic contrast-enhanced (DCE) MRI method. We also investigated the impact of TI-sampling density on the accuracy of estimated RPF. RESULTS: Good agreement was found between ASL- and DCE-measured RPF, with a mean difference of 9±30ml/min and a correlation coefficient R=0.92 when ASL signals were acquired at 16 TIs and a mean difference of 9±57ml/min and R=0.81 when ASL signals were acquired at 5 TIs. RPF estimated from ASL signals acquired at only 2 TIs (400 and 1200ms) showed a low correlation with DCE-measured values (R=0.30). CONCLUSION: The proposed ASL method is capable of measuring RPF with an accuracy that is comparable to DCE MRI. At least 5 TIs are recommended for the ASL acquisition to ensure reliability of RPF measurements.

Optimization of saturation-recovery dynamic contrast-enhanced MRI acquisition protocol: monte carlo simulation approach demonstrated with gadolinium MR renography.

Dynamic contrast-enhanced (DCE) MRI is widely used for the measurement of tissue perfusion and to assess organ function. MR renography, which is acquired using a DCE sequence, can measure renal perfusion, filtration and concentrating ability. Optimization of the DCE acquisition protocol is important for the minimization of the error propagation from the acquired signals to the estimated parameters, thus improving the precision of the parameters. Critical to the optimization of contrast-enhanced T1 -weighted protocols is the balance of the T1 -shortening effect across the range of gadolinium (Gd) contrast concentration in the tissue of interest. In this study, we demonstrate a Monte Carlo simulation approach for the optimization of DCE MRI, in which a saturation-recovery T1 -weighted gradient echo sequence is simulated and the impact of injected dose (D) and time delay (TD, for saturation recovery) is tested. The results show that high D and/or high TD cause saturation of the peak arterial signals and lead to an overestimation of renal plasma flow (RPF) and glomerular filtration rate (GFR). However, the use of low TD (e.g. 100 ms) and low D leads to similar errors in RPF and GFR, because of the Rician bias in the pre-contrast arterial signals. Our patient study including 22 human subjects compared TD values of 100 and 300 ms after the injection of 4 mL of Gd contrast for MR renography. At TD = 100 ms, we computed an RPF value of 157.2 ± 51.7 mL/min and a GFR of 33.3 ± 11.6 mL/min. These results were all significantly higher than the parameter estimates at TD = 300 ms: RPF = 143.4 ± 48.8 mL/min (p = 0.0006) and GFR = 30.2 ± 11.5 mL/min (p = 0.0015). In conclusion, appropriate optimization of the DCE MRI protocol using simulation can effectively improve the precision and, potentially, the accuracy of the measured parameters. Copyright © 2016 John Wiley & Sons, Ltd.

Assessment of renal function using intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI.

PURPOSE: To assess the correlation between each of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in renal parenchyma with renal function, in a cohort of patients with chronic liver disease. MATERIALS AND METHODS: Thirty patients with liver disease underwent abdominal MRI at 1.5T, including a coronal respiratory-triggered IVIM-DWI sequence and a coronal 3D FLASH DCE-MRI acquisition. Diffusion signals in the renal cortex and medulla were fitted to the IVIM model to estimate the diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (PF). The apparent diffusion coefficient (ADC) was calculated using all b-values. The glomerular filtration rate (GFR), cortical and medullary renal plasma flow (RPF), mean transit times (MTT) of vascular and tubular compartments and the whole kidney, were calculated from DCE-MRI data by fitting to a three-compartment model. The estimated GFR (eGFR) was calculated from serum creatinine measured 30 ± 27 days of MRI. RESULTS: ADC, PF, and RPF were significantly higher in renal cortex vs. medulla (P < 10(-5) ). DCE-MRI GFR significantly correlated with, but underestimated, eGFR (Spearman's r/P = 0.49/0.01). IVIM-DWI parameters were not significantly correlated with eGFR. DCE-MRI GFR correlated weakly with D (cortex, r/P = 0.3/0.03; medulla r/P = 0.27/0.05) and ADC (cortex r/P = 0.28/0.04; medulla r/P = 0.34/0.01). Weak correlations were observed for pooled cortical and medullar RPF with PF (r/P = 0.32/10(-3) ) and with ADC (r/P = 0.29/0.0025). Significant negative correlations were observed for vascular MTT with cortical D* (r/P = -0.38/0.004) and D*×PF (r/P = -0.34/0.01). CONCLUSION: The weak correlations between renal IVIM and DCE-MRI perfusion parameters imply that these functional measures could be complementary. J. Magn. Reson. Imaging 2016;44:317-326.

Application of separable parameter space techniques to multi-tracer PET compartment modeling.

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

Dynamic contrast-enhanced quantitative susceptibility mapping with ultrashort echo time MRI for evaluating renal function.

Dynamic contrast-enhanced (DCE) MRI can provide key insight into renal function. DCE MRI is typically achieved through an injection of a gadolinium (Gd)-based contrast agent, which has desirable T1 quenching and tracer kinetics. However, significant T2* blooming effects and signal voids can arise when Gd becomes very concentrated, especially in the renal medulla and pelvis. One MRI sequence designed to alleviate T2* effects is the ultrashort echo time (UTE) sequence. In the present study, we observed T2* blooming in the inner medulla of the mouse kidney, despite using UTE at an echo time of 20 microseconds and a low dose of 0.03 mmol/kg Gd. We applied quantitative susceptibility mapping (QSM) and resolved the signal void into a positive susceptibility signal. The susceptibility values [in parts per million (ppm)] were converted into molar concentrations of Gd using a calibration curve. We determined the concentrating mechanism (referred to as the concentrating index) as a ratio of maximum Gd concentration in the inner medulla to the renal artery. The concentrating index was assessed longitudinally over a 17-wk course (3, 5, 7, 9, 13, 17 wk of age). We conclude that the UTE-based DCE method is limited in resolving extreme T2* content caused by the kidney's strong concentrating mechanism. QSM was able to resolve and confirm the source of the blooming effect to be the large positive susceptibility of concentrated Gd. UTE with QSM can complement traditional magnitude UTE and offer a powerful tool to study renal pathophysiology.

Performance of an efficient image-registration algorithm in processing MR renography data.

PURPOSE: To evaluate the performance of an edge-based registration technique in correcting for respiratory motion artifacts in magnetic resonance renographic (MRR) data and to examine the efficiency of a semiautomatic software package in processing renographic data from a cohort of clinical patients. MATERIALS AND METHODS: The developed software incorporates an image-registration algorithm based on the generalized Hough transform of edge maps. It was used to estimate glomerular filtration rate (GFR), renal plasma flow (RPF), and mean transit time (MTT) from 36 patients who underwent free-breathing MRR at 3T using saturation-recovery turbo-FLASH. The processing time required for each patient was recorded. Renal parameter estimates and model-fitting residues from the software were compared to those from a previously reported technique. Interreader variability in the software was quantified by the standard deviation of parameter estimates among three readers. GFR estimates from our software were also compared to a reference standard from nuclear medicine. RESULTS: The time taken to process one patient's data with the software averaged 12 ± 4 minutes. The applied image registration effectively reduced motion artifacts in dynamic images by providing renal tracer-retention curves with significantly smaller fitting residues (P < 0.01) than unregistered data or data registered by the previously reported technique. Interreader variability was less than 10% for all parameters. GFR estimates from the proposed method showed greater concordance with reference values (P < 0.05). CONCLUSION: These results suggest that the proposed software can process MRR data efficiently and accurately. Its incorporated registration technique based on the generalized Hough transform effectively reduces respiratory motion artifacts in free-breathing renographic acquisitions.

Comparison of fitting methods and b-value sampling strategies for intravoxel incoherent motion in breast cancer.

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.