White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis.

T2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006-0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

Development of an abdominal phantom for the validation of an oligometastatic disease diagnosis workflow.

PURPOSE: The liver is a common site for metastatic disease, which is a challenging and life-threatening condition with a grim prognosis and outcome. We propose a standardized workflow for the diagnosis of oligometastatic disease (OMD), as a gold standard workflow has not been established yet. The envisioned workflow comprises the acquisition of a multimodal image data set, novel image processing techniques, and cone beam computed tomography (CBCT)-guided biopsy for subsequent molecular subtyping. By combining morphological, molecular, and functional information about the tumor, a patient-specific treatment planning is possible. We designed and manufactured an abdominal liver phantom that we used to demonstrate multimodal image acquisition, image processing, and biopsy of the OMD diagnosis workflow. METHODS: The anthropomorphic abdominal phantom contains a rib cage, a portal vein, lungs, a liver with six lesions, and a hepatic vessel tree. This phantom incorporates three different lesion types with varying visibility under computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography CT (PET-CT), which reflects clinical reality. The phantom is puncturable and the size of the corpus and the organs is comparable to those of a real human abdomen. By using several modern additive manufacturing techniques, the manufacturing process is reproducible and allows to incorporate patient-specific anatomies. As a first step of the OMD diagnosis workflow, a preinterventional CT, MRI, and PET-CT data set of the phantom was acquired. The image information was fused using image registration and organ information was extracted via image segmentation. A CBCT-guided needle puncture experiment was performed, where all six liver lesions were punctured with coaxial biopsy needles. RESULTS: Qualitative observation of the image data and quantitative evaluation using contrast-to-noise ratio (CNR) confirms that one lesion type is visible only in MRI and not CT. The other two lesion types are visible in CT and MRI. The CBCT-guided needle placement was performed for all six lesions, including those visible only in MRI and not CBCT. This was possible by successfully merging multimodal preinterventional image data. Lungs, bones, and liver vessels serve as realistic inhibitions during needle path planning. CONCLUSIONS: We have developed a reusable abdominal phantom that has been used to validate a standardized OMD diagnosis workflow. Utilizing the phantom, we have been able to show that a multimodal imaging pipeline is advantageous for a comprehensive detection of liver lesions. In a CBCT-guided needle placement experiment we have punctured lesions that are invisible in CBCT using registered preinterventional MRI scans for needle path planning.

Acceleration of Magnetic Resonance Fingerprinting Reconstruction Using Denoising and Self-Attention Pyramidal Convolutional Neural Network.

Magnetic resonance fingerprinting (MRF) based on echo-planar imaging (EPI) enables whole-brain imaging to rapidly obtain T1 and T2* relaxation time maps. Reconstructing parametric maps from the MRF scanned baselines by the inner-product method is computationally expensive. We aimed to accelerate the reconstruction of parametric maps for MRF-EPI by using a deep learning model. The proposed approach uses a two-stage model that first eliminates noise and then regresses the parametric maps. Parametric maps obtained by dictionary matching were used as a reference and compared with the prediction results of the two-stage model. MRF-EPI scans were collected from 32 subjects. The signal-to-noise ratio increased significantly after the noise removal by the denoising model. For prediction with scans in the testing dataset, the mean absolute percentage errors between the standard and the final two-stage model were 3.1%, 3.2%, and 1.9% for T1, and 2.6%, 2.3%, and 2.8% for T2* in gray matter, white matter, and lesion locations, respectively. Our proposed two-stage deep learning model can effectively remove noise and accurately reconstruct MRF-EPI parametric maps, increasing the speed of reconstruction and reducing the storage space required by dictionaries.

Consensus-Based Technical Recommendations for Clinical Translation of Renal Phase Contrast MRI.

BACKGROUND: Phase-contrast (PC) MRI is a feasible and valid noninvasive technique to measure renal artery blood flow, showing potential to support diagnosis and monitoring of renal diseases. However, the variability in measured renal blood flow values across studies is large, most likely due to differences in PC-MRI acquisition and processing. Standardized acquisition and processing protocols are therefore needed to minimize this variability and maximize the potential of renal PC-MRI as a clinically useful tool. PURPOSE: To build technical recommendations for the acquisition, processing, and analysis of renal 2D PC-MRI data in human subjects to promote standardization of renal blood flow measurements and facilitate the comparability of results across scanners and in multicenter clinical studies. STUDY TYPE: Systematic consensus process using a modified Delphi method. POPULATION: Not applicable. SEQUENCE FIELD/STRENGTH: Renal fast gradient echo-based 2D PC-MRI. ASSESSMENT: An international panel of 27 experts from Europe, the USA, Australia, and Japan with 6 (interquartile range 4-10) years of experience in 2D PC-MRI formulated consensus statements on renal 2D PC-MRI in two rounds of surveys. Starting from a recently published systematic review article, literature-based and data-driven statements regarding patient preparation, hardware, acquisition protocol, analysis steps, and data reporting were formulated. STATISTICAL TESTS: Consensus was defined as ≥75% unanimity in response, and a clear preference was defined as 60-74% agreement among the experts. RESULTS: Among 60 statements, 57 (95%) achieved consensus after the second-round survey, while the remaining three showed a clear preference. Consensus statements resulted in specific recommendations for subject preparation, 2D renal PC-MRI data acquisition, processing, and reporting. DATA CONCLUSION: These recommendations might promote a widespread adoption of renal PC-MRI, and may help foster the set-up of multicenter studies aimed at defining reference values and building larger and more definitive evidence, and will facilitate clinical translation of PC-MRI. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.

Magnetic Resonance Imaging compatible Elastic Loading Mechanism (MELM): A minimal footprint device for MR imaging under load.

Quantitative Magnetic Resonance Imaging (MRI) can enable early diagnosis of knee cartilage damage if imaging is performed during the application of load. Mechanical loading via ropes, pulleys and suspended weights can be obstructive and require adaptations to the patient table. In this paper, a new lightweight MRI-compatible elastic loading mechanism is introduced. The new device showed sufficient linearity (|α/ß| = 0.42 ± 0.25), reproducibility (CoV = 5 ± 2%), and stability (CoV = 0.5 ± 0.1%). In vivo and ex vivo scans confirmed the ability of the device to exert sufficient force to study the knee cartilage under loading conditions, inducing up to a 29% decrease in $T_2^{\ast}$ of the central medial cartilage. With this device mechanical loading can become more accessible for researchers and clinicians, thus facilitating the translational use of MRI biomarkers for the detection of cartilage deterioration.

First experiences of local pulse wave velocity measurements in 4D-MRI in focally stented femoropopliteal arteries.

Background: In peripheral arterial disease (PAD) the femoropopliteal (FP) artery is the most frequently recanalized lower limb artery. Stent-based interventions change the biomechanical properties of FP arteries. However, no clinical tool for functional imaging is established for quantitative measurements in vivo. Four-dimensional-flow magnetic resonance imaging enables a detailed evaluation of the hemodynamics of the central and - more challenging - the peripheral arteries. The present study aimed to determine the feasibility of assessing pulse wave velocities (PWV) as a marker of vessel stiffness in PAD patients with multiple spot stents and to compare the values with age-matched subjects and young-adult healthy subjects. Patients and methods: Contrast-free 4D-flow MRI was performed in seven PAD patients with focally stented FP arteries, five age-matched subjects after exclusion of PAD, and five young, healthy adults. PWV values were calculated from flow curves by using the foot-to-foot method. Results: Four-D-flow MRI sequences offering high spatial and temporal resolution enables quantification of flow velocity measurements and estimation of PWVs. Assessment of segmental PWV as a surrogate of vascular stiffness in focally stented femoral arteries is feasible. PWV values across all groups were 15.6±5.2 m/s, 13.3±4.1 m/s, and 9.9±2.2 m/s in PAD patients, senior-aged volunteers, and young-adult volunteers respectively. PWV values in PAD patients were similar with those in the senior-aged volunteers group (15.6±5.2 vs. 13.3 ±4.1 years, p=0.43). However, when compared to the young-adult volunteers, PAD patients had a statistically significantly higher mean local PWV (15.6±5.2 m/s vs. 9.9±2.2 m/s, p<0.05). Conclusions: Calculating segmental PWV in the femoral arteries is feasible in PAD patients with focally stented FP arteries. PWV values in PAD patients were similar to those in senior-aged volunteers, both of which were higher than in young-adult volunteers.

Lesion probability mapping in MS patients using a regression network on MR fingerprinting.

BACKGROUND: To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to [Formula: see text], [Formula: see text], NAWM, and GM- probability maps. METHODS: We performed MRF-EPI measurements in 42 patients with multiple sclerosis and 6 healthy volunteers along two sites. A U-net was trained to reconstruct the denoised and distortion corrected [Formula: see text] and [Formula: see text] maps, and to additionally generate NAWM-, GM-, and WM lesion probability maps. RESULTS: WM lesions were predicted with a dice coefficient of [Formula: see text] and a lesion detection rate of [Formula: see text] for a threshold of 33%. The network jointly enabled accurate [Formula: see text] and [Formula: see text] times with relative deviations of 5.2% and 5.1% and average dice coefficients of [Formula: see text] and [Formula: see text] for NAWM and GM after binarizing with a threshold of 80%. CONCLUSION: DL is a promising tool for the prediction of lesion probability maps in a fraction of time. These might be of clinical interest for the WM lesion analysis in MS patients.

Free-breathing simultaneous T1 , T2 , and T2∗ quantification in the myocardium.

PURPOSE: To implement a free-breathing sequence for simultaneous quantification of T1 , T2 , and T2∗ for comprehensive tissue characterization of the myocardium in a single scan using a multi-gradient-echo readout with saturation and T2 preparation pulses. METHODS: In the proposed Saturation And T2 -prepared Relaxometry with Navigator-gating (SATURN) technique, a series of multi-gradient-echo (GRE) images with different magnetization preparations was acquired during free breathing. A total of 35 images were acquired in 26.5 ± 14.9 seconds using multiple saturation times and T2 preparation durations and with imaging at 5 echo times. Bloch simulations and phantom experiments were used to validate a 5-parameter fit model for accurate relaxometry. Free-breathing simultaneous T1 , T2 , and T2∗ measurements were performed in 10 healthy volunteers and 2 patients using SATURN at 3T and quantitatively compared to conventional single-parameter methods such as SASHA for T1 , T2 -prepared bSSFP, and multi-GRE for T2∗ . RESULTS: Simulations confirmed accurate fitting with the 5-parameter model. Phantom measurements showed good agreement with the reference methods in the relevant range for in vivo measurements. Compared to single-parameter methods comparable accuracy was achieved. SATURN produced in vivo parameter maps that were visually comparable to single-parameter methods. No significant difference between T1 , T2 , and T2∗ times acquired with SATURN and single-parameter methods was shown in quantitative measurements (SATURN T1=1573±86ms , T2=33.2±3.6ms , T2∗=25.3±6.1ms ; conventional methods: T1=1544±107ms , T2=33.2±3.6ms , T2∗=23.8±5.5ms ; P>.2 ) CONCLUSION: SATURN enables simultaneous quantification of T1 , T2 , and T2∗ in the myocardium for comprehensive tissue characterization with co-registered maps, in a single scan with good agreement to single-parameter methods.

Accelerated white matter lesion analysis based on simultaneous T1 and T2∗ quantification using magnetic resonance fingerprinting and deep learning.

PURPOSE: To develop an accelerated postprocessing pipeline for reproducible and efficient assessment of white matter lesions using quantitative magnetic resonance fingerprinting (MRF) and deep learning. METHODS: MRF using echo-planar imaging (EPI) scans with varying repetition and echo times were acquired for whole brain quantification of T1 and T2∗ in 50 subjects with multiple sclerosis (MS) and 10 healthy volunteers along 2 centers. MRF T1 and T2∗ parametric maps were distortion corrected and denoised. A CNN was trained to reconstruct the T1 and T2∗ parametric maps, and the WM and GM probability maps. RESULTS: Deep learning-based postprocessing reduced reconstruction and image processing times from hours to a few seconds while maintaining high accuracy, reliability, and precision. Mean absolute error performed the best for T1 (deviations 5.6%) and the logarithmic hyperbolic cosinus loss the best for T2∗ (deviations 6.0%). CONCLUSIONS: MRF is a fast and robust tool for quantitative T1 and T2∗ mapping. Its long reconstruction and several postprocessing steps can be facilitated and accelerated using deep learning.

Correction to: Phase-contrast magnetic resonance imaging to assess renal perfusion: a systematic review and statement paper.

The article Phase­contrast magnetic resonance imaging to assess renal perfusion: a systematic review and statement paper, written by Giulia Villa, Steffen Ringgaard, Ingo Hermann, Rebecca Noble, Paolo Brambilla, Dinah S. Khatir, Frank G. Zöllner, Susan T. Francis, Nicholas M. Selby, Andrea Remuzzi and Anna Caroli, was originally published electronically on the publisher's internet portal on 17 August 2019 without open access.

Towards measuring the effect of flow in blood T 1 assessed in a flow phantom and in vivo.

Measurement of the blood T 1 time using conventional myocardial T 1 mapping methods has gained clinical significance in the context of extracellular volume (ECV) mapping and synthetic hematocrit (Hct). However, its accuracy is potentially compromised by in-flow of non-inverted/non-saturated spins and in-flow of spins which are not partially saturated from previous imaging pulses. Bloch simulations were used to analyze various flow effects separately. T 1 measurements of gadolinium doped water were performed using a flow phantom with adjustable flow velocities at 3 T. Additionally, in vivo blood T 1 measurements were performed in 6 healthy subjects (26 ± 5 years, 2 female). To study the T 1 time as a function of the instantaneous flow velocity, T 1 times were evaluated in an axial imaging slice of the descending aorta. Velocity encoded cine measurements were performed to quantify the flow velocity throughout the cardiac cycle. Simulation results show more than 30% loss in accuracy for 10% non-prepared in-flowing spins. However, in- and out-flow to the imaging plane only demonstrated minor impact on the T 1 time. Phantom T 1 times were decreased by up to 200 ms in the flow phantom, due to in-flow of non-prepared spins. High flow velocities cause in-flow of spins that lack partial saturation from the imaging pulses but only lead to negligible T 1 time deviation (less than 30 ms). In vivo measurements confirm a substantial variation of the T 1 time depending on the flow velocity. The highest aortic T 1 times are observed at the time point of minimal flow with increased flow velocity leading to reduction of the measured T 1 time by up to [Formula: see text] at peak velocity. In this work we attempt to dissect the effects of flow on T 1 times, by using simulations, well-controlled, simplified phantom setup and the linear flow pattern in the descending aorta in vivo.

Magnetic resonance fingerprinting for simultaneous renal T1 and T2* mapping in a single breath-hold.

PURPOSE: To evaluate the use of magnetic resonance fingerprinting (MRF) for simultaneous quantification of T1 and T2∗ in a single breath-hold in the kidneys. METHODS: The proposed kidney MRF sequence was based on MRF echo-planar imaging. Thirty-five measurements per slice and overall 4 slices were measured in 15.4 seconds. Group matching was performed for in-line quantification of T1 and T2∗ . Images were acquired in a phantom and 8 healthy volunteers in coronal orientation. To evaluate our approach, region of interests were drawn in the kidneys to calculate mean values and standard deviations of the T1 and T2∗ times. Precision was calculated across multiple repeated MRF scans. Gaussian filtering is applied on baseline images to improve SNR and match stability. RESULTS: T1 and T2∗ times acquired with MRF in the phantom showed good agreement with reference measurements and conventional mapping methods with deviations of less than 5% for T1 and less than 10% for T2∗ . Baseline images in vivo were free of artifacts and relaxation times yielded good agreement with conventional methods and literature (deviation T1:7±4% , T2∗:6±3% ). CONCLUSIONS: In this feasibility study, the proposed renal MRF sequence resulted in accurate T1 and T2∗ quantification in a single breath-hold.

Phase-contrast magnetic resonance imaging to assess renal perfusion: a systematic review and statement paper.

OBJECTIVE: Phase-contrast magnetic resonance imaging (PC-MRI) is a non-invasive method used to compute blood flow velocity and volume. This systematic review aims to discuss the current status of renal PC-MRI and provide practical recommendations which could inform future clinical studies and its adoption in clinical practice. METHODOLOGY: A comprehensive search of all the PC-MRI studies in human healthy subjects or patients related to the kidneys was performed. RESULTS: A total of 39 studies were included in which PC-MRI was used to measure renal blood flow (RBF) alongside other derivative hemodynamic parameters. PC-MRI generally showed good correlation with gold standard methods of RBF measurement, both in vitro and in vivo, and good reproducibility. Despite PC-MRI not being routinely used in clinical practice, there are several clinical studies showing its potential to support diagnosis and monitoring of renal diseases, in particular renovascular disease, chronic kidney disease and autosomal dominant polycystic kidney disease. DISCUSSION: Renal PC-MRI shows promise as a non-invasive technique to reliably measure RBF, both in healthy volunteers and in patients with renal disease. Future multicentric studies are needed to provide definitive normative ranges and to demonstrate the clinical potential of PC-MRI, likely as part of a multi-parametric renal MRI protocol.

Renal fibrosis is the common feature of autosomal dominant tubulointerstitial kidney diseases caused by mutations in mucin 1 or uromodulin.

For decades, ill-defined autosomal dominant renal diseases have been reported, which originate from tubular cells and lead to tubular atrophy and interstitial fibrosis. These diseases are clinically indistinguishable, but caused by mutations in at least four different genes: UMOD, HNF1B, REN, and, as recently described, MUC1. Affected family members show renal fibrosis in the biopsy and gradually declining renal function, with renal failure usually occurring between the third and sixth decade of life. Here we describe 10 families and define eligibility criteria to consider this type of inherited disease, as well as propose a practicable approach for diagnosis. In contrast to what the frequently used term 'Medullary Cystic Kidney Disease' implies, development of (medullary) cysts is neither an early nor a typical feature, as determined by MRI. In addition to Sanger and gene panel sequencing of the four genes, we established SNaPshot minisequencing for the predescribed cytosine duplication within a distinct repeat region of MUC1 causing a frameshift. A mutation was found in 7 of 9 families (3 in UMOD and 4 in MUC1), with one indeterminate (UMOD p.T62P). On the basis of clinical and pathological characteristics we propose the term 'Autosomal Dominant Tubulointerstitial Kidney Disease' as an improved terminology. This should enhance recognition and correct diagnosis of affected individuals, facilitate genetic counseling, and stimulate research into the underlying pathophysiology.