Lung parenchyma and structure visualisation in paediatric chest MRI: a comparison of different short and ultra-short echo time protocols.

AIM: To evaluate image quality acquired at lung imaging using magnetic resonance imaging (MRI) sequences using short and ultra-short (UTE) echo times (TEs) with different acquisition strategies (breath-hold, prospective, and retrospective gating) in paediatric patients and in healthy volunteers. MATERIALS AND METHODS: End-inspiratory and end-expiratory three-dimensional (3D) spoiled gradient (SPGR3D) and 3D zero echo-time (ZTE3D), and 3D UTE free-breathing (UTE3D), prospective projection navigated radial ZTE3D (ZTE3D vnav), and four-dimensional ZTE (ZTE4D) were performed using a 1.5 T MRI system. For quantitative assessment, the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) values were calculated. To evaluate image quality, qualitative scoring was undertaken on all sequences to evaluate depiction of intrapulmonary vessels, fissures, bronchi, imaging noise, artefacts, and overall acceptability. RESULTS: Eight cystic fibrosis (CF) patients (median age 14 years, range 13-17 years), seven children with history of prematurity with or without bronchopulmonary dysplasia (BPD; median 10 years, range 10-11 years), and 10 healthy volunteers (median 32 years, range 20-52 years) were included in the study. ZTE3D vnav provided the most reliable output in terms of image quality, although scan time was highly dependent on navigator triggering efficiency and respiratory pattern. CONCLUSIONS: Best image quality was achieved with prospective ZTE3D and UTE3D readouts both in children and volunteers. The current implementation of retrospective ZTE3D readout (ZTE4D) did not provide diagnostic image quality but rather introduced artefacts over the entire imaging volume mimicking lung pathology.

Deep learning for improving ZTE MRI images in free breathing.

INTRODUCTION: Despite a growing interest in lung MRI, its broader use in a clinical setting remains challenging. Several factors limit the image quality of lung MRI, such as the extremely short T2 and T2* relaxation times of the lung parenchyma and cardiac and breathing motion. Zero Echo Time (ZTE) sequences are sensitive to short T2 and T2* species paving the way to improved "CT-like" MR images. To overcome this limitation, a retrospective respiratory gated version of ZTE (ZTE4D) which can obtain images in 16 different respiratory phases during free breathing was developed. Initial performance of ZTE4D have shown motion artifacts. To improve image quality, deep learning with fully convolutional neural networks (FCNNs) has been proposed. CNNs has been widely used for MR imaging, but it has not been used for improving free-breathing lung imaging yet. Our proposed pipeline facilitates the clinical work with patients showing difficulties/uncapable to perform breath-holding, or when the different gating techniques are not efficient due to the irregular respiratory pace. MATERIALS AND METHODS: After signed informed consent and IRB approval, ZTE4D free breathing and breath-hold ZTE3D images were obtained from 10 healthy volunteers on a 1.5 T MRI scanner (GE Healthcare Signa Artist, Waukesha, WI). ZTE4D acquisition captured all 16 phases of the respiratory cycle. For the ZTE breath-hold, the subjects were instructed to hold their breath in 5 different inflation levels ranging from full expiration to full inspiration. The training dataset consisting of ZTE-BH images of 10 volunteers was split into 8 volunteers for training, 1 for validation and 1 for testing. In total 800 ZTE breath-hold images were constructed by adding Gaussian noise and performing image transformations (translations, rotations) to imitate the effect of motion in the respiratory cycle, and blurring from varying diaphragm positions, as it appears for ZTE4D. These sets were used to train a FCNN model to remove the artificially added noise and transformations from the ZTE breath-hold images and reproduce the original quality of the images. Mean squared error (MSE) was used as loss function. The remaining 2 healthy volunteer's ZTE4D images were used to test the model and qualitatively assess the predicted images. RESULTS: Our model obtained a MSE of 0.09% on the training set and 0.135% on the validation set. When tested on unseen data the predicted images from our model improved the contrast of the pulmonary parenchyma against air filled regions (airways or air trapping). The SNR of the lung parenchyma was quantitatively improved by a factor of 1.98 and the CNR lung- blood, which is indicating the visibility of the intrapulmonary vessels, was improved by 4.2%. Our network was able to reduce ghosting artifacts, such as diaphragm movement and blurring, and enhancing image quality. DISCUSSION: Free-breathing 3D and 4D lung imaging with MRI is feasible, however its quality is not yet acceptable for clinical use. This can be improved with deep learning techniques. Our FCNN improves the visual image quality and reduces artifacts of free-breathing ZTE4D. Our main goal was rather to remove ghosting artifacts from the ZTE4D images, to improve diagnostic quality of the images. As main results of the network, diaphragm contour increased with sharper edges by visual inspection and less blurring of the anatomical structures and lung parenchyma. CONCLUSION: With FCNNs, image quality of free breathing ZTE4D lung MRI can be improved and enable better visualization of the lung parenchyma in different respiratory phases.

Fractional order vs. exponential fitting in UTE MR imaging of the patellar tendon.

PURPOSE: Quantification of the T2∗ relaxation time constant is relevant in various magnetic resonance imaging applications. Mono- or bi-exponential models are typically used to determine these parameters. However, in case of complex, heterogeneous tissues these models could lead to inaccurate results. We compared a model, provided by the fractional-order extension of the Bloch equation with the conventional models. METHODS: Axial 3D ultra-short echo time (UTE) scans were acquired using a 3.0 T MRI and a 16-channel surface coil. After image registration, voxel-wise T2∗ was quantified with mono-exponential, bi-exponential and fractional-order fitting. We evaluated all three models repeatability and the bias of their derived parameters by fitting at various noise levels. To investigate the effect of the SNR for the different models, a Monte-Carlo experiment with 1000 repeats was performed for different noise levels for one subject. For a cross-sectional investigation, we used the mean fitted values of the ROIs in five volunteers. RESULTS: Comparing the mono-exponential and the fractional order T2∗ maps, the fractional order fitting method yielded enhanced contrast and an improved delineation of the different tissues. In the case of the bi-exponential method, the long T2∗ component map demonstrated the anatomy clearly with high contrast. Simulations showed a nonzero bias of the parameters for all three mathematical models. ROI based fitting showed that the T2∗ values were different depending on the applied method, and they differed most for the patellar tendon in all subjects. CONCLUSIONS: In high SNR cases, the fractional order and bi-exponential models are both performing well with low bias. However, in all observed cases, one of the bi-exponential components has high standard deviation in T2∗. The bi-exponential model is suitable for T2∗ mapping, but we recommend using the fractional order model for cases of low SNR.

Laboratory prototype for experimental validation of MR-guided radiofrequency head and neck hyperthermia.

Clinical studies have established a strong benefit from adjuvant mild hyperthermia (HT) to radio- and chemotherapy for many tumor sites, including the head and neck (H&N). The recently developed HYPERcollar allows the application of local radiofrequency HT to tumors in the entire H&N. Treatment quality is optimized using electromagnetic and thermal simulators and, whenever placement risk is tolerable, assessed using invasively placed thermometers. To replace the current invasive procedure, we are investigating whether magnetic resonance (MR) thermometry can be exploited for continuous and 3D thermal dose assessment. In this work, we used our simulation tools to design an MR compatible laboratory prototype applicator. By simulations and measurements, we showed that the redesigned patch antennas are well matched to 50 Ω (S11<-10 dB). Simulations also show that, using 300 W input power, a maximum specific absorption rate (SAR) of 100 W kg(-1) and a temperature increase of 4.5 °C in 6 min is feasible at the center of a cylindrical fat/muscle phantom. Temperature measurements using the MR scanner confirmed the focused heating capabilities and MR compatibility of the setup. We conclude that the laboratory applicator provides the possibility for experimental assessment of the feasibility of hybrid MR-HT in the H&N region. This versatile design allows rigorous analysis of MR thermometry accuracy in increasingly complex phantoms that mimic patients' anatomies and thermodynamic characteristics.

In vivo MRI mapping of iron oxide-labeled stem cells transplanted in the heart.

In various stem cell therapy approaches poor cell survival has been recognized as an important factor limiting therapeutic efficacy. Therefore noninvasive monitoring of cell fate is warranted for developing clinically effective stem cell therapy. In this study we investigated the use of voxel-based R2 mapping as a tool to monitor the fate of iron oxide-labeled cells in the myocardium. Mesenchymal stem cells were transduced with the luciferase gene, labeled with ferumoxide particles and injected in the myocardium of healthy rats. Cell fate was monitored over a period of 8 weeks by bioluminescence and quantitative magnetic resonance imaging. Bioluminescence signal increased during the first week followed by a steep decrease to undetectable levels during the second week. MR imaging showed a sharp increase in R2 values shortly after injection at the injection site, followed by a very gradual decrease of R2 over a period of 8 weeks. No difference in the appearances on R2-weighted images was observed between living and dead cells over the entire time period studied. No significant correlation between the bioluminescence optical data and R2 values was observed and quantitative R2 mapping appeared not suitable for the in vivo assessment of stem cell. These results do not follow previous in vitro reports where it was proposed that living cells may be distinguished from dead cells on the basis of the R2 relaxivities (intracellular and extracellular iron oxides). Cell proliferation, cell migration, cell death, extracellular superparamagnetic iron oxide dispersion and aggregation exhibit different relaxivities. In vivo these processes happen simultaneously, making quantification very complex, if not impossible.

Reproducibility of 3D delayed gadolinium enhanced MRI of cartilage (dGEMRIC) of the knee at 3.0 T in patients with early stage osteoarthritis.

OBJECTIVES: To assess the reproducibility of 3D delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) at 3 T in early stage knee osteoarthritis (OA) patients. METHODS: In 20 patients, 3D dGEMRIC at 3 T was acquired twice within 7 days. To correct for patient motion during acquisition, all images were rigidly registered in 3D. Eight anatomical cartilage ROIs were analysed on both images of each patient. Capability of dGEMRIC to yield T1 maps that reproducibly distinguish spatial differences in cartilage quality was assessed in two ROIs within a single slice in each patient. Reproducibility was assessed using ICCs and Bland-Altman plots. RESULTS: ICCs ranged from 0.87 to 0.95, indicating good reproducibility. T1 maps revealed reproducible spatial differences in cartilage quality (ICC 0.79). Based on the Bland-Altman plots, we defined a threshold of 95 ms to determine if a change in dGEMRIC outcome in longitudinal research was statistically significant. CONCLUSIONS: 3D knee dGEMRIC at 3 T combined with 3D image registration is a highly reproducible measure of cartilage quality in early stage OA. Therefore, dGEMRIC may be a valuable tool in the non-invasive evaluation of cartilage quality changes in longitudinal research in patients with early stage OA and focal cartilage defects.