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.     

Diffusional kurtosis MRI of the lower leg: changes caused by passive muscle elongation and shortening

Diffusional kurtosis MRI (DKI) quantifies the deviation of water diffusion from a Gaussian distribution. We investigated the influence of passive elongation and shortening of the lower leg muscles on the DKI parameters D (diffusion coefficient) and K (kurtosis). After approval by the local ethics committee, eight healthy volunteers (age, 29.1 ± 2.9 years) underwent MRI of the lower leg at 3 T. Diffusion‐weighted images were acquired with 10 different b values at three ankle positions (passive dorsiflexion 10°, neutral position 0°, passive plantar flexion 40°). Parametrical maps of D and K were obtained by voxel‐wise fitting of the signal intensities using a non‐linear Levenberg–Marquardt algorithm. D and K were measured in the tibialis anterior, medial and lateral gastrocnemius, and soleus muscles. In the neutral position, D and K values were in the range between 1.66–1.79 × 10^–3 mm²/s and 0.21–0.39, respectively. D and K increased with passive shortening, and decreased with passive elongation, which could also be illustrated on the parametrical maps. In dorsiflexion, D (p < 0.01) and K (p = 0.036) were higher in the tibialis anterior than in the medial gastrocnemius. In plantar flexion, the opposite was found for K (p = 0.035). DKI parameters in the lower leg muscles are significantly influenced by the ankle joint position, indicating that the diffusion of water molecules in skeletal muscle deviates from a Gaussian distribution depending on muscle tonus. Copyright © 2016 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 of the prostate without susceptibility artifacts: Undersampled multi‐shot turbo‐STEAM with rotated radial trajectories

The aim of this study was to develop and evaluate a clinically feasible approach to diffusion‐weighted (DW) MRI of the prostate without susceptibility‐induced artifacts. The proposed method relies on an undersampled multi‐shot DW turbo‐STEAM sequence with rotated radial trajectories and a multi‐step inverse reconstruction with denoised multi‐shot phase maps. The total acquisition time was below 6 min for a resolution of 1.4 × 1.4 × 3.5 mm³ and six directions at b = 600 s mm^?2. Studies of eight healthy subjects and two patients with prostate cancer were performed at 3 T employing an 18‐channel body‐array coil and elements of the spine coil. The method was compared with conventional DW echo‐planar imaging (EPI) of the prostate. The results confirm that DW STEAM MRI avoids geometric distortions and false image intensities, which were present for both single‐shot EPI (ssEPI) and readout‐segmented EPI, particularly near the intestinal wall of the prostate. Quantitative accuracy of the apparent diffusion coefficient (ADC) was validated with use of a numerical phantom providing ground truth. ADC values in the central prostate gland of healthy subjects were consistent with those measured using ssEPI and with literature data. Preliminary results for patients with prostate cancer revealed a correct anatomical localization of lesions with respect to T₂‐weighted MRI in both mean DW STEAM images and ADC maps. In summary, DW STEAM MRI of the prostate offers clinically relevant advantages for the diagnosis of prostate cancer compared with state‐of‐the‐art EPI‐based approaches. The method warrants extended clinical trials.     

Diffusion‐prepared stimulated‐echo turbo spin echo (DPsti‐TSE): An eddy current‐insensitive sequence for three‐dimensional high‐resolution and undistorted diffusion‐weighted imaging

In this study, we present a new three‐dimensional (3D), diffusion‐prepared turbo spin echo sequence based on a stimulated‐echo read‐out (DPsti‐TSE) enabling high‐resolution and undistorted diffusion‐weighted imaging (DWI). A dephasing gradient in the diffusion preparation module and rephasing gradients in the turbo spin echo module create stimulated echoes, which prevent signal loss caused by eddy currents. Near to perfect agreement of apparent diffusion coefficient (ADC) values between DPsti‐TSE and diffusion‐weighted echo planar imaging (DW‐EPI) was demonstrated in both phantom transient signal experiments and phantom imaging experiments. High‐resolution and undistorted DPsti‐TSE was demonstrated in vivo in prostate and carotid vessel wall. 3D whole‐prostate DWI was achieved with four b values in only 6 min. Undistorted ADC maps of the prostate peripheral zone were obtained at low and high imaging resolutions with no change in mean ADC values [(1.60 ± 0.10) × 10^?3 versus (1.60 ± 0.02) × 10^?3 mm²/s]. High‐resolution 3D DWI of the carotid vessel wall was achieved in 12 min, with consistent ADC values [(1.40 ± 0.23) × 10^?3 mm²/s] across different subjects, as well as slice locations through the imaging volume. This study shows that DPsti‐TSE can serve as a robust 3D diffusion‐weighted sequence and is an attractive alternative to the traditional two‐dimensional DW‐EPI approaches.     

Regulation of alveolar gas conductance by NO in man,as based on studies with NO donors and inhibitors of NO production

Aim: Nitric oxide (NO) is a mediator of the pulmonary vessel tone and permeability. We hypothesized that it may also regulate the alveolar‐capillary membrane gas conductance and lung diffusion capacity. Methods: In 20 healthy subjects (age = 23 ± 3 years) we measured lung diffusion capacity for carbon monoxide (DLco), its determinants (membrane conductance, D_m, and pulmonary capillary blood volume, V_c), systolic pulmonary artery pressure (PAPs) and pulmonary vascular resistance (PVR). Measurements were performed before and after administration of N^g ‐monomethyl‐l ‐arginine (l ‐NMMA, 0.5 mg kg^?1 min^?1), as a NO production inhibitor, and l ‐arginine (l ‐Arg, 0.5 mg kg^?1 min¹) as a NO pathway activator. The effects of l ‐NMMA were also tested in combination with active l ‐Arg and inactive stereoisomer d ‐Arg vehicled by 150 mL of 5%d ‐glucose solution. For l ‐Arg and l ‐NMMA, saline (150 mL) was also tested as a vehicle. Results: l ‐NMMA reduced D_m (?41%P < 0.01), DLco (?20%, P < 0.01) and cardiac output (CO), and increased PAPs and PVR. In 10 additional subjects, a dose of l ‐NMMA of 0.03 mg kg^?1 min¹ infused in the main stem of the pulmonary artery was able to lower D_m (?32%, P < 0.01) despite no effect on PVR and CO. D_m depression was significantly greater when l ‐NMMA was vehicled by saline than by glucose. l ‐Arg but not d ‐Arg abolished the effects of l ‐NMMA. l ‐Arg alone increased D_m (+14%, P < 0.01). Conclusion: The findings indicate that NO mediates the respiratory effects of l ‐NMMA and l ‐Arg, and is involved in the physiology of the alveolar‐capillary membrane gas conductance in humans. NO deficiency may cause an excessive endothelial sodium exchange/water conduction and fluid leakage in alveolar interstitial space, lengthening the air–blood path and depressing diffusion capacity.     

Dynamic Light Scattering of Rigid Rods – A Universal Relationship on the Apparent Diffusion Coefficient as Revealed by Numerical Studies and Its Use for Rod Length Determination

Numerical simulations are performed to study the diffusion behaviors of rigid rods examined by dynamic light scattering (DLS). It was identified that the apparent diffusion coefficient, D_p, determined by DLS obeys a universal relationship D_p/D_G = f(qL) = 1.1804 + 0.1764 × tanh [11.799× tan^?1(qL) ‐17.169], where D_G, L, and q are the mass‐of‐center diffusion coefficient, length of the rod, and scattering vector, respectively. This relationship delineates the DLS experiments into weak (qL < 4.0), intermediate (4.0 < qL < 20.0), and strong translation–rotation coupling regime (qL > 20.0). In weak (strong) coupling regime, D_p is a measure of D_G (D_// ‐ longitudinal diffusion coefficient) of the rods. In addition, if DLS is performed in the intermediate coupling regime, the rod length can be determined by solving D_p/D_G = f(qL).     

Diffusion tensor imaging of renal ischemia reperfusion injury in an experimental model

Renal ischemia reperfusion injury (IRI) is a major cause of acute renal failure. It occurs in various clinical settings such as renal transplantation, shock and vascular surgery. Serum creatinine level has been used as an index for estimating the degree of renal functional loss in renal IRI. However, it only evaluates the global renal function. In this study, diffusion tensor imaging (DTI) was used to characterize renal IRI in an experimental rat model. Spin‐echo echo‐planar DTI with b‐value of 300 s/mm² and 6 diffusion gradient directions was performed at 7 T in 8 Sprague‐Dawley (SD) with 60‐min unilateral renal IRI and 8 normal SD rats. Apparent diffusion coefficient (ADC), directional diffusivities and fractional anisotropy (FA) were measured at the acute stage of IRI. The IR‐injured animals were also examined by diffusion‐weighted imaging with 7 b‐values up to 1000 s/mm² to estimate true diffusion coefficient (D_true) and perfusion fraction (P_fraction) using a bi‐compartmental model. ADC of injured renal cortex (1.69 ± 0.24 × 10^?3 mm²/s) was significantly lower (p < 0.01) than that of contralateral intact cortex (2.03 ± 0.35 × 10^?3 mm²/s). Meanwhile, both ADC and FA of IR‐injured medulla (1.37 ± 0.27 × 10^?3 mm²/s and 0.28 ± 0.04, respectively) were significantly less (p < 0.01) than those of contralateral intact medulla (2.01 ± 0.38 × 10^?3 mm²/s and 0.36 ± 0.04, respectively). The bi‐compartmental model analysis revealed the decrease in D_true and P_fraction in the IR‐injured kidneys. Kidney histology showed widespread cell swelling and erythrocyte congestion in both cortex and medulla, and cell necrosis/apoptosis and cast formation in medulla. These experimental findings demonstrated that DTI can probe both structural and functional information of kidneys following renal IRI. Copyright © 2010 John Wiley & Sons, Ltd.     

VERDICT‐AMICO: Ultrafast fitting algorithm for non‐invasive prostate microstructure characterization

VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumours) estimates and maps microstructural features of cancerous tissue non‐invasively using diffusion MRI. The main purpose of this study is to address the high computational time of microstructural model fitting for prostate diagnosis, while retaining utility in terms of tumour conspicuity and repeatability. In this work, we adapt the accelerated microstructure imaging via convex optimization (AMICO) framework to linearize the estimation of VERDICT parameters for the prostate gland. We compare the original non‐linear fitting of VERDICT with the linear fitting, quantifying accuracy with synthetic data, and computational time and reliability (performance and precision) in eight patients. We also assess the repeatability (scan‐rescan) of the parameters. Comparison of the original VERDICT fitting versus VERDICT‐AMICO showed that the linearized fitting (1) is more accurate in simulation for a signal‐to‐noise ratio of 20 dB; (2) reduces the processing time by three orders of magnitude, from 6.55 seconds/voxel to 1.78 milliseconds/voxel; (3) estimates parameters more precisely; (4) produces similar parametric maps and (5) produces similar estimated parameters with a high Pearson correlation between implementations, r² > 0.7. The VERDICT‐AMICO estimates also show high levels of repeatability. Finally, we demonstrate that VERDICT‐AMICO can estimate an extra diffusivity parameter without losing tumour conspicuity and retains the fitting advantages. VERDICT‐AMICO provides microstructural maps for prostate cancer characterization in seconds.     

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.     

Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine‐19 MRI

Fluorine‐19 (¹⁹F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non‐invasive quantification of inflammation and cell tracking, but suffers from a low signal‐to‐noise ratio and extended scan time. To address this limitation, we tested the hypotheses that a ¹⁹F MRI pulse sequence that combines a specific undersampling regime with signal averaging has both increased sensitivity and robustness against motion artifacts compared with a non‐averaged fully sampled pulse sequence, when both datasets are reconstructed with compressed sensing. As a proof of principle, numerical simulations and phantom experiments were performed on selected variable ranges to characterize the point spread function of undersampling patterns, as well as the vulnerability to noise of undersampling and reconstruction parameters with paired numbers of x signal averages and acceleration factor x (NAx ‐AFx ). The numerical simulations demonstrated that a probability density function that uses 25% of the samples to fully sample the k‐space central area allowed for an optimal balance between limited blurring and artifact incoherence. At all investigated noise levels, the Dice similarity coefficient (DSC) strongly depended on the regularization parameters and acceleration factor. In phantoms, the motion robustness of an NA8‐AF8 undersampling pattern versus NA1‐AF1 was evaluated with simulated and real motion patterns. Differences were assessed with the DSC, which was consistently higher for the NA8‐AF8 compared with the NA1‐AF1 strategy, for both simulated and real cyclic motion patterns (P < 0.001). Both strategies were validated in vivo in mice (n = 2) injected with perfluoropolyether. Here, the images displayed a sharper delineation of the liver with the NA8‐AF8 strategy than with the NA1‐AF1 strategy. In conclusion, we validated the hypotheses that in ¹⁹F MRI the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts.     

The effects of noise in cardiac diffusion tensor imaging and the benefits of averaging complex data

There is growing interest in cardiac diffusion tensor imaging (cDTI), but, unlike other diffusion MRI applications, there has been little investigation of the effects of noise on the parameters typically derived. One method of mitigating noise floor effects when there are multiple image averages, as in cDTI, is to average the complex rather than the magnitude data, but the phase contains contributions from bulk motion, which must be removed first. The effects of noise on the mean diffusivity (MD), fractional anisotropy (FA), helical angle (HA) and absolute secondary eigenvector angle (E2A) were simulated with various diffusion weightings (b values). The effect of averaging complex versus magnitude images was investigated. In vivo cDTI was performed in 10 healthy subjects with b = 500, 1000, 1500 and 2000 s/mm². A technique for removing the motion‐induced component of the image phase present in vivo was implemented by subtracting a low‐resolution copy of the phase from the original images before averaging the complex images. MD, FA, E2A and the transmural gradient in HA were compared for un‐averaged, magnitude‐ and complex‐averaged reconstructions. Simulations demonstrated an over‐estimation of FA and MD at low b values and an under‐estimation at high b values. The transition is relatively signal‐to‐noise ratio (SNR) independent and occurs at a higher b value for FA (b = 1000–1250 s/mm²) than MD (b ≈ 250 s/mm²). E2A is under‐estimated at low and high b values with a transition at b ≈ 1000 s/mm², whereas the bias in HA is comparatively small. The under‐estimation of FA and MD at high b values is caused by noise floor effects, which can be mitigated by averaging the complex data. Understanding the parameters of interest and the effects of noise informs the selection of the optimal b values. When complex data are available, they should be used to maximise the benefit from the acquisition of multiple averages. The combination of complex data is also a valuable step towards segmented acquisitions. Copyright © 2016 John Wiley & Sons, Ltd.     

Inelastische Lichtstreuung von Cellulosenitratlösungen

A homodyne light beat spectrometer equipped with an argon ion laser and a correlator is described and used to study the behaviour of the threadlike molecules of cellulose nitrate in dilute solution. By this technique it was possible to measure the translation diffusion coefficient D even of the undegraded native cellulose, which exhibits a very low D (<10^?7 cm² s^?1) and was hitherto only very approximately known because the conventional methods, which observe the alteration of a concentration difference, are quite inaccurate at these low diffusion velocities.     

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.     

Diffusion-weighted MRI in early chemotherapy response evaluation of patients with diffuse large B-cell lymphoma--a pilot study: comparison with 2-deoxy-2-fluoro- D-glucose-positron emission tomography/computed tomography

To determine the feasibility of diffusion‐weighted MRI (DWI) in the evaluation of the early chemotherapeutic response in patients with aggressive non‐Hodgkin's lymphoma (NHL), eight patients with histologically proven diffuse large B‐cell lymphoma were imaged by MRI, including DWI, and positron emission tomography/computed tomography (PET/CT) before treatment (E1), and after 1 week (E2) and two cycles (E3) of chemotherapy. In all patients, whole‐body screening using T₁‐ and T₂‐weighted images in the coronal plane was performed. To quantitatively evaluate the chemotherapeutic response, axial images including DWI were acquired. Apparent diffusion coefficient (ADC) maps were reconstructed, and the ADC value of the tumor was measured. In addition, the tumor volume was estimated on axial T₂‐weighted images. The maximum standardized uptake value (SUV_max) and active tumor volume were measured on fused PET/CT images. Lymphomas showed high signal intensity on DW images and low signal intensity on ADC maps, except for necrotic foci. The mean pre‐therapy ADC was 0.71 × 10^?3 mm²/s; it increased by 77% at E2 (p < 0.05) and 24% more at E3 (insignificant); the total increase was 106% (p < 0.05). The mean tumor volume by MRI was 276 mL at baseline; it decreased by 58% at E2 (p < 0.05) and 65% more at E3 (p < 0.05), giving a total decrease of 84% (p < 0.05). All the imaged pre‐therapy tumors were strongly positive on PET/CT, with a mean SUV_max of 20. The SUV_max decreased by 60% at E2 (p < 0.05) and 59% more at E3 (p < 0.05), giving a total decrease of 83% (p < 0.05). The active tumor burden decreased by 66% at E2 (p < 0.05). At baseline, both central and peripheral tumor ADC values correlated inversely with SUV_max (p < 0.05), and also correlated inversely with active tumor burden on PET/CT and with tumor volume on MRI at E2 (p < 0.05). In conclusion, the results of DWI in combination with whole‐body MRI were comparable with those of integrated PET/CT. Copyright © 2011 John Wiley & Sons, Ltd.     

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis

The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter‐rater variability and the expenditure of time associated with manual assessment. We describe a deep learning‐based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS‐positive (CVS⁺) and 448 CVS‐negative (CVS^?) lesions. A 3D convolutional neural network (“CVSnet”) was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS⁺/CVS^? lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion‐wise and subject‐wise and compared with a state‐of‐the‐art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion‐wise median balanced accuracy of 81%, and subject‐wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was ~ 600‐fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion‐wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.     

Simultaneous use of individual and joint regularization terms in compressive sensing: Joint reconstruction of multi‐channel multi‐contrast MRI acquisitions

Multi‐contrast images are commonly acquired together to maximize complementary diagnostic information, albeit at the expense of longer scan times. A time‐efficient strategy to acquire high‐quality multi‐contrast images is to accelerate individual sequences and then reconstruct undersampled data with joint regularization terms that leverage common information across contrasts. However, these terms can cause features that are unique to a subset of contrasts to leak into the other contrasts. Such leakage‐of‐features may appear as artificial tissues, thereby misleading diagnosis. The goal of this study is to develop a compressive sensing method for multi‐channel multi‐contrast magnetic resonance imaging (MRI) that optimally utilizes shared information while preventing feature leakage. Joint regularization terms group sparsity and colour total variation are used to exploit common features across images while individual sparsity and total variation are also used to prevent leakage of distinct features across contrasts. The multi‐channel multi‐contrast reconstruction problem is solved via a fast algorithm based on Alternating Direction Method of Multipliers. The proposed method is compared against using only individual and only joint regularization terms in reconstruction. Comparisons were performed on single‐channel simulated and multi‐channel in‐vivo datasets in terms of reconstruction quality and neuroradiologist reader scores. The proposed method demonstrates rapid convergence and improved image quality for both simulated and in‐vivo datasets. Furthermore, while reconstructions that solely use joint regularization terms are prone to leakage‐of‐features, the proposed method reliably avoids leakage via simultaneous use of joint and individual terms, thereby holding great promise for clinical use.     

Quantitative MRI in murine radiation‐induced rectocolitis: comparison with histopathological inflammation score

Murine radiation‐induced rectocolitis is considered to be a relevant animal model of gastrointestinal inflammation. The purpose of our study was to compare quantitative MRI and histopathological features in this gastrointestinal inflammation model. Radiation rectocolitis was induced by localized single‐dose radiation (27 Gy) in Sprague‐Dawley rats. T₂‐weighted, T₁‐weighted and diffusion‐weighted MRI was performed at 7 T in 16 rats between 2 and 4 weeks after irradiation and in 10 control rats. Rats were sacrificed and the histopathological inflammation score of the colorectal samples was assessed. The irradiated rats showed significant increase in colorectal wall thickness (2.1 ± 0.3 mm versus 0.8 ± 0.3 mm in control rats, P < 0.0001), normalized T₂ signal intensity (4 ± 0.8 versus 2 ± 0.4 AU, P < 0.0001), normalized T₁ signal intensity (1.4 ± 0.1 versus 1.1 ± 0.2 AU, P = 0.0009) and apparent and pure diffusion coefficients (ADC and D) (2.06 × 10^?3 ± 0.34 versus 1.51 × 10^?3 ± 0.23 mm²/s, P = 0.0004, and 1.97 × 10^?3 ± 0.43 mm²/s versus 1.48 × 10^?3 ± 0.29 mm²/s, P = 0.008, respectively). Colorectal wall thickness (r = 0.84, P < 0.0001), normalized T₂ signal intensity (r = 0.85, P < 0.0001) and ADC (r = 0.80, P < 0.0001) were strongly correlated with the histopathological inflammation score, whereas normalized T₁ signal intensity and D were moderately correlated (r = 0.64, P = 0.0006, and r = 0.65, P = 0.0003, respectively). High‐field MRI features of single‐dose radiation‐induced rectocolitis in rats differ significantly from those of control rats. Quantitative MRI characteristics, especially wall thickness, normalized T₂ signal intensity, ADC and D, are potential markers of the histopathological inflammation score.     

Fickian diffusion of erucamide (13‐cis‐docosenamide) in poly(laurolactam) (Nylon 12) (PA‐12)

Diffusion of erucamide (13‐cis‐docosenamide) [H₃C— (—CH₂—)₁₁—HC=CH—(—CH₂—)₇—CO— NH₂] (eru) in poly(laurolactam) (Nylon 12) (PA‐12) has been studied in a temperature range from 343 to 353 K. In previous investigations on the diffusion of eru in isotactic poly(propylene) (i‐PP) it was found that the diffusion took place by a non‐Fickian mechanism. This feature was explained by taking into account the microstructure of i‐PP films and the incompatibility of eru and i‐PP. The same experimental method to determine the concentration profiles was previously employed in this system. The experimental profiles have been compared with theoretical curves based on solutions of Fick's diffusion equation for the best fitting, with the appropriate boundary conditions. The measured concentration profiles show a good agreement with the Fickian law. Values of the diffusion coefficient D in the range from 10^–10 to 10^–11 cm²·s^–1 have been obtained. The activation energy for diffusion (E_d) has been calculated from the D values in the temperature range investigated assuming an Arrhenius‐type behaviour. The activation energy has been calculated as E_d = 156 kJ·mol^–1. The values of diffusion coefficients and activation energy are in the range found for some other additives. By using Fujita's equation a good correlation between diffusion coefficient and free volume fraction estimated by means of the Williams‐Landel‐Ferry equation have been found.