Assessment of diffusion parameters by intravoxel incoherent motion MRI in head and neck squamous cell carcinoma

The objectives of this study were to assess the diffusion parameters derived from intravoxel incoherent motion (IVIM) MRI in head and neck squamous cell carcinoma (HNSCC) and to investigate the agreement between different methods of tumor delineation and two numerical methods to extract the perfusion fraction f. Thirty‐seven untreated patients with histopathologically confirmed primary HNSCC were included retrospectively in the study. The entire volume of the primary tumor was outlined on diffusion‐weighted images using co‐registered morphological images as a guide to the tumor location. Apparent diffusion coefficient (ADC) and IVIM diffusion parameters were estimated considering the largest tumor section as well as the entire tumor volume. A bi‐exponential fit was implemented to extract f, D (pure diffusion coefficient) and D* (pseudo‐diffusion coefficient). A second simplified method, based on an asymptotic extrapolation, was used to determine f. The agreement between ADC and IVIM diffusion parameters derived from the delineation of single and multiple slices, and between the two f estimations, was assessed by Bland–Altman plots. The inter‐slice variability of ADC and IVIM diffusion parameters was evaluated. The Kruskal–Wallis test was used to investigate whether the tumor location had a statistically significant influence on the values of the parameters. Comparing the tumor delineation methods, a better accordance was found for ADC and D, with a mean percentage difference of less than 2%. Larger discrepancies were found for f and D*, with mean differences of 4.5% and 5.5%, respectively. When comparing the two f estimation methods, small mean differences were found (<3.5%), suggesting that the two methods may be considered as equivalent for the assessment of f in our patient population. The observed ADC and IVIM diffusion parameters were dependent on the anatomic site of the lesion, carcinoma of the nasopharynx showing more homogeneous and dissimilar estimations than other HNSCCs. Copyright © 2013 John Wiley & Sons, Ltd.     

Triggered intravoxel incoherent motion MRI for the assessment of calf muscle perfusion during isometric intermittent exercise

The main aim of this paper was to propose triggered intravoxel incoherent motion (IVIM) imaging sequences for the evaluation of perfusion changes in calf muscles before, during and after isometric intermittent exercise. Twelve healthy volunteers were involved in the study. The subjects were asked to perform intermittent isometric plantar flexions inside the MRI bore. MRI of the calf muscles was performed on a 3.0 T scanner and diffusion‐weighted (DW) images were obtained using eight different b values (0 to 500 s/mm²). Acquisitions were performed at rest, during exercise and in the subsequent recovery phase. A motion‐triggered echo‐planar imaging DW sequence was implemented to avoid movement artifacts. Image quality was evaluated using the average edge strength (AES) as a quantitative metric to assess the motion artifact effect. IVIM parameters (diffusion D, perfusion fraction f and pseudo‐diffusion D*) were estimated using a segmented fitting approach and evaluated in gastrocnemius and soleus muscles. No differences were observed in quality of IVIM images between resting state and triggered exercise, whereas the non‐triggered images acquired during exercise had a significantly lower value of AES (reduction of more than 20%). The isometric intermittent plantar‐flexion exercise induced an increase of all IVIM parameters (D by 10%; f by 90%; D* by 124%; fD* by 260%), in agreement with the increased muscle perfusion occurring during exercise. Finally, IVIM parameters reverted to the resting values within 3 min during the recovery phase. In conclusion, the IVIM approach, if properly adapted using motion‐triggered sequences, seems to be a promising method to investigate muscle perfusion during isometric exercise.     

Stroke assessment with intravoxel incoherent motion diffusion‐weighted MRI

Intravoxel incoherent motion (IVIM) diffusion‐weighted MRI can simultaneously measure diffusion and perfusion characteristics in a non‐invasive way. This study aimed to determine the potential utility of IVIM in characterizing brain diffusion and perfusion properties for clinical stroke. The multi‐b‐value diffusion‐weighted images of 101 patients diagnosed with acute/subacute ischemic stroke were retrospectively evaluated. The diffusion coefficient D, representing the water apparent diffusivity, was obtained by fitting the diffusion data with increasing high b‐values to a simple mono‐exponential model. The IVIM‐derived perfusion parameters, pseudodiffusion coefficient D*, vascular volume fraction f and blood flow‐related parameter fD*, were calculated with the bi‐exponential model. Additionally, the apparent diffusion coefficient (ADC) was fitted according to the mono‐exponential model using all b‐values. The diffusion parameters for the ischemic lesion and normal contralateral region were measured in each patient. Statistical analysis was performed using the paired Student t‐test and Pearson correlation test. Diffusion data in both the ischemic lesion and normal contralateral region followed the IVIM bi‐exponential behavior, and the IVIM model showed better goodness of fit than the mono‐exponential model with lower Akaike information criterion values. The paired Student t‐test revealed significant differences for all diffusion parameters (all P < 0.001) except D* (P = 0.218) between ischemic and normal areas. For all patients in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001) and f (r = 0.541, P < 0.001; r = 0.262, P = 0.008); significant correlation was also found between ADC and fD* in the ischemic region (r = 0.254, P = 0.010). For all pixels within the region of interest from a representative subject in both ischemic and normal regions, ADC was significantly positively correlated with D (both r = 1, both P < 0.001), f (r = 0.823, P < 0.001; r = 0.652, P < 0.001) and fD* (r = 0.294, P < 0.001; r = 0.340, P < 0.001). These findings may have clinical implications for the use of IVIM imaging in the assessment and management of acute/subacute stroke patients. Copyright © 2016 John Wiley & Sons, Ltd.     

Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion‐weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion‐related volume (f) in patients with high‐grade gliomas were generated. Maps of F_p (plasma flow), v_p (vascular plasma volume), PS (permeability surface–area product), v_e (extravascular, extracellular volume), E (extraction ratio), k_e (influx ratio into the interstitium), and t_c (vascular transit time) from dynamic contrast‐enhanced (DCE) and dynamic susceptibility contrast‐enhanced (DSC) MRI were also generated. A region‐of‐interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC‐derived v_p and t_c in healthy brain tissue. Concerning the tumor regions, F_p was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non‐significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and k_e in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC‐ and DCE‐derived metrics. Copyright © 2014 John Wiley & Sons, Ltd.     

Multi‐centre reproducibility of diffusion MRI parameters for clinical sequences in the brain

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra‐voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences. An ice–water phantom and nine healthy volunteers were scanned across fives centres on eight scanners (four Siemens 1.5T, four Philips 3T). The mean ADC, IVIM parameters (diffusion coefficient D and perfusion fraction f) and DTI parameters (mean diffusivity MD and fractional anisotropy FA), were measured in grey matter, white matter and specific brain sub‐regions. A mixed effect model was used to measure the intra‐ and inter‐scanner coefficient of variation (CV) for each of the five parameters. ADC, D, MD and FA had a good intra‐ and inter‐scanner reproducibility in both grey and white matter, with a CV ranging between 1% and 7.4%; mean 2.6%. Other brain regions also showed high levels of reproducibility except for small structures such as the choroid plexus. The IVIM parameter f had a higher intra‐scanner CV of 8.4% and inter‐scanner CV of 24.8%. No major difference in the inter‐scanner CV for ADC, D, MD and FA was observed when analysing the 1.5T and 3T scanners separately. ADC, D, MD and FA all showed good intra‐scanner reproducibility, with the inter‐scanner reproducibility being comparable or faring slightly worse, suggesting that using data from multiple scanners does not have an adverse effect compared with using data from the same scanner. The IVIM parameter f had a poorer inter‐scanner CV when scanners of different field strengths were combined, and the parameter was also affected by the scan acquisition resolution. This study shows that the majority of diffusion MRI derived parameters are robust across 1.5T and 3T scanners and suitable for use in multi‐centre clinical studies and trials. © 2015 The Authors NMR in Biomedicine Published by John Wiley & Sons Ltd.     

Reliable estimation of brain intravoxel incoherent motion parameters using denoised diffusion‐weighted MRI

In this study, we evaluate whether diffusion‐weighted magnetic resonance imaging (DW‐MRI) data after denoising can provide a reliable estimation of brain intravoxel incoherent motion (IVIM) perfusion parameters. Brain DW‐MRI was performed in five healthy volunteers on a 3 T clinical scanner with 12 different b‐values ranging from 0 to 1000 s/mm². DW‐MRI data denoised using the proposed method were fitted with a biexponential model to extract perfusion fraction (PF), diffusion coefficient (D) and pseudo‐diffusion coefficient (D*). To further evaluate the accuracy and precision of parameter estimation, IVIM parametric images obtained from one volunteer were used to resimulate the DW‐MRI data using the biexponential model with the same b‐values. Rician noise was added to generate DW‐MRI data with various signal‐to‐noise ratio (SNR) levels. The experimental results showed that the denoised DW‐MRI data yielded precise estimates for all IVIM parameters. We also found that IVIM parameters were significantly different between gray matter and white matter (P < 0.05), except for D* (P = 0.6). Our simulation results show that the proposed image denoising method displays good performance in estimating IVIM parameters (both bias and coefficient of variation were <12% for PF, D and D*) in the presence of different levels of simulated Rician noise (SNR_b=0 = 20‐40). Simulations and experiments show that brain DW‐MRI data after denoising can provide a reliable estimation of IVIM parameters.     

Differentiating the histologic grades of gliomas preoperatively using amide proton transfer‐weighted (APTW) and intravoxel incoherent motion MRI

The purpose of this work was to investigate the diagnostic performance of amide proton transfer‐weighted (APTW) and intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the preoperative grading of gliomas. Fifty‐one patients with suspected gliomas were recruited and underwent a preoperative MRI examination that included APTW and IVIM sequences. All cases were confirmed by postsurgical histopathology. APTW signal intensity, true diffusion coefficient (D), perfusion fraction (f) and pseudo‐diffusion coefficient (D*) were applied to assess the solid tumor component and contralateral normal‐appearing white matter. The relative APTW signal intensity (rAPTW) was also used. Independent‐sample and paired‐sample t‐tests were used to compare differences in MRI parameters between low‐grade glioma (LGG) and high‐grade glioma (HGG) groups. The diagnostic performance was assessed with the receiver operating characteristic curve. Twenty‐six patients were pathologically diagnosed with LGG and 25 were diagnosed with HGG. APTW, rAPTW and f values were significantly higher (all p < 0.001), whereas D values were significantly lower (p < 0.001) in the HGG group than in the LGG group. There was no significant difference between D* values for the two groups. rAPTW had an area under the curve (AUC) of 0.957, with a sensitivity of 100% and a specificity of 84.6%, followed by APTW, f, D and D*. The combined use of APTW and IVIM showed the best diagnostic performance, with an AUC of 0.986. In conclusion, APTW and IVIM, as two promising supplementary sequences for routine MRI, could be valuable in differentiating LGGs from HGGs.     

Intravoxel incoherent motion imaging kinetics during chemoradiotherapy for human papillomavirus‐associated squamous cell carcinoma of the oropharynx: preliminary results from a prospective pilot study

This study aims to identify the temporal kinetics of intravoxel incoherent motion (IVIM) MRI in patients with human papillomavirus‐associated (HPV+) oropharyngeal squamous cell carcinoma. Patients were enrolled under an Institutional Review Board (IRB)‐approved protocol as part of an ongoing prospective clinical trial. All patients underwent two MRI studies: a baseline scan before chemoradiotherapy and a mid‐treatment scan 3–4 weeks after treatment initiation. Parametric maps representing pure diffusion coefficient (D), pseudo‐diffusion coefficient (D*), perfusion fraction (f) and apparent diffusion coefficient (ADC) were generated. The Mann–Whitney U‐test was used to assess the temporal variation of IVIM metrics. Bayesian quadratic discriminant analysis (QDA) was used to evaluate the extent to which mid‐treatment changes in IVIM metrics could be combined to predict sites that would achieve complete response (CR) in multivariate analysis. Thirty‐one patients were included in the final analysis with 59 lesions. Pretreatment ADC and D values of the CR lesions (n = 19) were significantly lower than those of non‐CR lesions (n = 33). Mid‐treatment ADC, D and f values were significantly higher (p < 0.0001) than pretreatment values for all lesions. Each increase in normalized ΔADC of size 0.1 yielded a 1.45‐fold increase in the odds of CR (p < 0.0003), each increase in normalized ΔD of size 0.1 yielded a 1.53‐fold increase in the odds of CR (p < 0.0002), and each unit increase in Δf yielded a 2.29‐fold increase in the odds of CR (p < 0.02). Combined ΔD and ΔADC were integrated into a multivariate prediction model and attained an AUC of 0.87 (95% confidence interval: 0.79, 0.96), as well as a sensitivity of 0.63, specificity of 0.85 and accuracy of 0.78, under leave‐one‐out cross‐validation. In conclusion, IVIM is feasible and potentially useful in the prediction and assessment of the early response of HPV+ oropharyngeal squamous cell carcinoma to chemoradiotherapy. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparing diagnostic accuracy of luminal water imaging with diffusion‐weighted and dynamic contrast‐enhanced MRI in prostate cancer: A quantitative MRI study

Luminal water imaging (LWI) is a new MRI T₂ mapping technique that has been developed with the aim of diagnosis of prostate carcinoma (PCa). This technique measures the fractional amount of luminal water in prostate tissue, and has shown promising preliminary results in detection of PCa. To include LWI in clinical settings, further investigation on the accuracy of this technique is required. In this study, we compare the diagnostic accuracy of LWI with those of diffusion‐weighted imaging (DWI) and dynamic contrast‐enhanced (DCE) MRI in detection and grading of PCa. Fifteen patients with biopsy‐proven PCa consented to participate in this ethics‐board‐approved prospective study. Patients were examined with LWI, DWI, and DCE sequences at 3 T prior to radical prostatectomy. Maps of MRI parameters were generated and registered to whole‐mount histology. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of individual and combined MR parameters. Correlation with Gleason score (GS) was evaluated using Spearman's rank correlation test. The results show that area under the ROC curve (AUC) obtained from LWI was equal to or higher than the AUC obtained from DWI, DCE, or their combination, in peripheral zone (0.98 versus 0.90, 0.89, and 0.91 respectively), transition zone (0.99 versus 0.98, n/a, and 0.98), and the entire prostate (0.85 versus 0.81, 0.75, and 0.84). The strongest correlation with GS was achieved from LWI (ρ = ?0.81 ± 0.09, P < 0.001). Results of this pilot study show that LWI performs equally well as, or better than, DWI and DCE in detection of PCa. LWI provides significantly higher correlation with GS than DWI and DCE. This technique can potentially be included in clinical MRI protocols to improve characterization of tumors. However, considering the small size of the patient population in this study, a further study with a larger cohort of patients and broader range of GS is required to confirm the findings and draw a firm conclusion on the applicability of LWI in clinical settings.     

Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model

The effective delivery of a therapeutic drug to the core of a tumor is often impeded by physiological barriers, such as the interstitial fluid pressure (IFP). There are a number of therapies that can decrease IFP and induce tumor vascular normalization. However, a lack of a noninvasive means to measure IFP hinders the utilization of such a window of opportunity for the maximization of the treatment response. Thus, the purpose of this study was to investigate the feasibility of using intravoxel incoherent motion (IVIM) diffusion parameters as noninvasive imaging biomarkers for IFP. Mice bearing the 4T1 mammary carcinoma model were studied using diffusion‐weighted imaging (DWI), immediately followed by wick‐in‐needle IFP measurement. Voxelwise analysis was conducted with a conventional monoexponential diffusion model, as well as a biexponential model taking IVIM into account. There was no significant correlation of IFP with either the median apparent diffusion coefficient from the monoexponential model (r = 0.11, p = 0.78) or the median tissue diffusivity from the biexponential model (r = 0.30, p = 0.44). However, IFP was correlated with the median pseudo‐diffusivity (D_p) of apparent vascular voxels (r = 0.76, p = 0.02) and with the median product of the perfusion fraction and pseudo‐diffusivity (f_pD_p) of apparent vascular voxels (r = 0.77, p = 0.02). Although the effect of IVIM in tumors has been reported previously, to our knowledge, this study represents the first direct comparison of IVIM metrics with IFP, with the results supporting the feasibility of the use of IVIM DWI metrics as noninvasive biomarkers for tumor IFP. Copyright © 2011 John Wiley & Sons, Ltd.     

Dynamic intravoxel incoherent motion imaging of skeletal muscle at rest and after exercise

The purpose of this work was to demonstrate the feasibility of intravoxel incoherent motion imaging (IVIM) for non‐invasive quantification of perfusion and diffusion effects in skeletal muscle at rest and following exercise. After IRB approval, eight healthy volunteers underwent diffusion‐weighted MRI of the forearm at 3 T and eight different b values between 0 and 500 s/mm² with a temporal resolution of 57 s per dataset. Dynamic images were acquired before and after a standardized handgrip exercise. Diffusion (D) and pseudodiffusion (D*) coefficients as well as the perfusion fraction (F_P) were measured in regions of interest in the flexor digitorum superficialis and profundus (FDS/FDP), brachioradialis, and extensor carpi radialis longus and brevis muscles by using a multi‐step bi‐exponential analysis in MATLAB. Parametrical maps were calculated voxel‐wise. Differences in D, D*, and F_P between muscle groups and between time points were calculated using a repeated measures analysis of variance with post hoc Bonferroni tests. Mean values and standard deviations at rest were the following: D*, 28.5 ± 11.4 × 10^?3 mm²/s; F_P, 0.03 ± 0.01; D, 1.45 ± 0.09 × 10^?3 mm²/s. Changes of IVIM parameters were clearly visible on the parametrical maps. In the FDS/FDP, D* increased by 289 ± 236% (p < 0.029), F_P by 138 ± 58% (p < 0.01), and D by 17 ± 9% (p < 0.01). A significant increase of IVIM parameters could also be detected in the brachioradialis muscle, which however was significantly lower than in the FDS/FDP. After 20 min, all parameters were still significantly elevated in the FDS/FDP but not in the brachioradialis muscle compared with the resting state. The IVIM approach allows simultaneous quantification of muscle perfusion and diffusion effects at rest and following exercise. It may thus provide a useful alternative to other non‐invasive methods such as arterial spin labeling. Possible fields of interest for this technique include perfusion‐related muscle diseases, such as peripheral arterial occlusive disease. Copyright © 2014 John Wiley & Sons, Ltd.     

Diffusion‐weighted MRI with intravoxel incoherent motion modeling for assessment of muscle perfusion in the thigh during post‐exercise hyperemia in younger and older adults

Aging is associated with impaired endothelium‐dependent vasodilation that leads to muscle perfusion impairment and contributes to organ dysfunction. Impaired muscle perfusion may result in inadequate delivery of oxygen and nutrients during and after muscle contraction, leading to muscle damage. The ability to study the relationship between perfusion and muscle damage has been limited using traditional muscle perfusion measures, which are invasive and risky. To overcome this limitation, we optimized a diffusion‐weighted MRI sequence and validated an intravoxel incoherent motion (IVIM) analysis based on Monte Carlo simulation to study muscle perfusion impairment with aging during post‐exercise hyperemia. Simulation results demonstrated that the bias of IVIM‐derived perfusion fraction (f_p ) and diffusion of water molecules in extra‐vascular tissue (D ) ranged from ?3.3% to 14% and from ?16.5% to 0.002%, respectively, in the optimized experimental condition. The dispersion in f_p and D ranged from 3.2% to 9.5% and from 0.9% to 1.1%, respectively. The mid‐thigh of the left leg of four younger (21–30 year old) and four older (60–90 year old) healthy females was studied using the optimized protocol at baseline and at seven time increments occurring every 3.25 min following in‐magnet dynamic knee extension exercise performed using a MR‐compatible ergometer with a workload of 0.4 bar for 2.5 min. After exercise, both f_p and D significantly increased in the rectus femoris (active muscle during exercise) but not in adductor magnus (inactive muscle), reflecting the fact that the local increase in perfusion with both groups showed a maximum value in the second post‐exercise time‐point. A significantly greater increase in perfusion from the baseline (p < 0.05) was observed in the younger group (37 ± 12.05%) compared with the older group (17.57 ± 15.92%) at the first post‐exercise measurement. This work establishes a reliable non‐invasive method that can be used to study the effects of aging on dynamic changes in muscle perfusion as they relate to important measures of physical function.     

A novel bayesian approach with conditional autoregressive specification for intravoxel incoherent motion diffusion‐weighted MRI

The Intra‐Voxel Incoherent Motion (IVIM) model is largely adopted to estimate slow and fast diffusion coefficients of water molecules in biological tissues, which are used in cancer applications. The most reported fitting approach is a voxel‐wise segmented non‐linear least square, whereas Bayesian approaches with a direct fit, also considering spatial regularization, were proposed too. In this work a novel segmented Bayesian method was proposed, also in combination with a spatial regularization through a Conditional Autoregressive (CAR) prior specification. The two segmented Bayesian approaches, with and without CAR specification, were compared with two standard least‐square and a direct Bayesian fitting methods. All approaches were tested on simulated images and real data of patients with head‐and‐neck and rectal cancer. Estimation accuracy and maps noisiness were quantified on simulated images, whereas the coefficient of variation and the goodness of fit were evaluated for real data. Both versions of the segmented Bayesian approach outperformed the standard methods on simulated images for pseudo‐diffusion (D^?) and perfusion fraction (f), whilst the segmented least‐square fitting remained the less biased for the diffusion coefficient (D). On real data, Bayesian approaches provided the less noisy maps, and the two Bayesian methods without CAR generally estimated lower values for f and D^? coefficients with respect to the other approaches. The proposed segmented Bayesian approaches were superior, in terms of estimation accuracy and maps quality, to the direct Bayesian model and the least‐square fittings. The CAR method improved the estimation accuracy, especially for D^?.     

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

This study aimed to demonstrate a reliable automatic segmentation method for independently separating reduced diffusion and decreased perfusion areas in ischemic stroke brains using constrained nonnegative matrix factorization (cNMF) pattern recognition in directional intravoxel incoherent motion MRI (IVIM‐MRI). First, the feasibility of cNMF‐based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for S₀‐normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from S₀‐normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM‐MRI experiments (x, y and z diffusion‐gradient directions, 20 b values at 7 T) were performed for normal (n = 4), sacrificed (n = 1, no flow) and ischemic stroke models (n = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double‐exponential fitting. Consistent with the simulation, the double‐exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion‐gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF‐based pattern recognition.     

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.     

Multi‐parametric MRI characterization of inflammation in murine skeletal muscle

Myopathies often display a common set of complex pathologies that include muscle weakness, inflammation, compromised membrane integrity, fat deposition, and fibrosis. Multi‐parametric, quantitative, non‐invasive imaging approaches may be able to resolve these individual pathological components. The goal of this study was to use multi‐parametric MRI to investigate inflammation as an isolated pathological feature. Proton relaxation, diffusion tensor imaging (DTI), quantitative magnetization transfer (qMT‐MRI), and dynamic contrast enhanced (DCE‐MRI) parameters were calculated from data acquired in a single imaging session conducted 6–8 hours following the injection of λ‐carrageenan, a local inflammatory agent. T₂ increased in the inflamed muscle and transitioned to bi‐exponential behavior. In diffusion measurements, all three eigenvalues and the apparent diffusion coefficient increased, but λ₃ had the largest relative change. Analysis of the qMT data revealed that the T₁ of the free pool and the observed T₁ both increased in the inflamed tissue, while the ratio of exchanging spins in the solid pool to those in the free water pool (the pool size ratio) significantly decreased. DCE‐MRI data also supported observations of an increase in extracellular volume. These findings enriched the understanding of the relation between multiple quantitative MRI parameters and an isolated inflammatory pathology, and may potentially be employed for other single or complex myopathy models. Copyright © 2014 John Wiley & Sons, Ltd.     

Quantification of microcirculatory parameters by joint analysis of flow‐compensated and non‐flow‐compensated intravoxel incoherent motion (IVIM) data

The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow‐compensated and non‐flow‐compensated motion‐encoded MRI data. A double diffusion encoding sequence capable of switching between flow‐compensated and non‐flow‐compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow‐compensated and non‐flow‐compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit. © 2016 The Authors NMR in Biomedicine published by John Wiley & Sons Ltd.     

Assessment of the need for DCE MRI in the detection of dominant lesions in the whole gland: Correlation between histology and MRI of prostate cancer

The purpose of this study was to evaluate the utility of dynamic contrast‐enhanced magnetic resonance imaging (DCE MRI) in the detection of dominant prostate tumors with multi‐parametric MRI of the whole gland. Combined diffusion tensor imaging (DTI) and DCE MRI from 16 patients with biopsy‐proven prostate cancer and no previous treatment were acquired with a 3.0‐T MRI scanner prior to radical prostatectomy, and used to identify dominant tumors. MRI results were validated by whole‐mount histology. Paired t‐test and Wilcoxon test, logistic generalized linear mixed effect models and receiver operating characteristic (ROC) analyses were used for the estimation of the statistical significance of the results. In the peripheral zone (PZ), the areas under the ROC curve (ROC‐AUC) were 0.98 (sensitivity, 96%; specificity, 98%) for DTI, 0.96 (sensitivity, 92%; specificity, 97%) for DCE and 0.99 (sensitivity, 98%; specificity, 98%) for DTI + DCE. In the entire prostate, the ROC‐AUC values were 0.96 (sensitivity, 84%; specificity, 95%) for DTI, 0.87 (sensitivity, 45%; specificity, 94%) for DCE and 0.96 (sensitivity, 88%; specificity, 98%) for DTI + DCE. The increase in ROC‐AUC by the addition of DCE was not statistically significant in either PZ or the entire prostate. The results of this study have shown that DTI identified dominant tumors with high accuracy in both PZ and the entire prostate, whereas the inclusion of DCE MRI had no significant impact on the identification of either PZ or entire prostate dominant lesions. Our results suggest that the inclusion of DCE MRI may not increase the accuracy of dominant lesion detection, allowing for faster, better tolerated imaging studies.     

Interrelations of muscle functional MRI,diffusion‐weighted MRI and 31P‐MRS in exercised lower back muscles

Exercise‐induced changes of transverse proton relaxation time (T₂), tissue perfusion and metabolic turnover were investigated in the lower back muscles of volunteers by applying muscle functional MRI (mfMRI) and diffusion‐weighted imaging (DWI) before and after as well as dynamic ³¹P‐MRS during the exercise. Inner (M. multifidus, MF) and outer lower back muscles (M. erector spinae, ES) were examined in 14 healthy young men performing a sustained isometric trunk‐extension. Significant phosphocreatine (PCr) depletions ranging from 30% (ES) to 34% (MF) and Pi accumulations between 95% (left ES) and 120%–140% (MF muscles and right ES) were observed during the exercise, which were accompanied by significantly decreased pH values in all muscles (?pH ≈ –0.05). Baseline T₂ values were similar across all investigated muscles (approximately 27 ms at 3 T), but revealed right–left asymmetric increases (T₂,_inc) after the exercise (right ES/MF: T₂,_inc = 11.8/9.7%; left ES/MF: T₂,_inc = 4.6/8.9%). Analyzed muscles also showed load‐induced increases in molecular diffusion D (p = .007) and perfusion fraction f (p = .002). The latter parameter was significantly higher in the MF than in the ES muscles both at rest and post exercise. Changes in PCr (p = .03), diffusion (p < .01) and perfusion (p = .03) were strongly associated with T_2,inc, and linear mixed model analysis revealed that changes in PCr and perfusion both affect T_2,inc (p < .001). These findings support previous assumptions that T₂ changes are not only an intra‐cellular phenomenon resulting from metabolic stress but are also affected by increased perfusion in loaded muscles. Copyright © 2014 John Wiley & Sons, Ltd.     

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T

Artificial neural networks (ANNs) were used for voxel‐wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least‐squares regression (LSR) and state‐of‐the‐art multi‐step fitting (LSR‐MS) in Monte‐Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR‐MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo‐diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR‐MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR‐MS, 19%; LSR, 8%), D* (ANN, 21%; LSR‐MS, 25%; LSR, 23%) and K (ANN, 0%; LSR‐MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR‐MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state‐of‐the‐art method LSR‐MS with several advantages in the estimation of IVIM–kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times.