Application Of Magnetic Resonance Imaging Research Articles

“ROLE OF FETAL MRI IN EVALUATION OF CONGENITAL ANOMALIES”

When US evaluation of the second and third-trimester foetus is limited, MR imaging might be used as a supplemental test. Due to a lack of an acceptable acoustic window, US is often limited in cases of oligohydramnios or breech presentation. In both cases, however, MR imaging can clearly show the foetal anatomy in detail. Ossification of the calvaria[1], which inhibits view of the posterior fossa at US, can also impede third trimester foetal assessment. US frequently suggests intracranial pathologic abnormalities such as posterior fossa anomalies (Chiari II syndrome, cerebellar aplasia or hypoplasia). MR imaging can corroborate the US findings, and it can also provide a diagnosis in some circumstances, such as neuronal migrational anomalies. MR imaging certainly has the advantage of being able to analyse the foetus in many planes within a greater field of view. T1-weighted MR imaging can show acute and chronic germinal matrix bleeding, as well as ischemia alterations. Although ultrasound is helpful in detecting corpus callosum abnormalities, it can miss many of the central nervous system problems associated with corpus callosum agenesis. Because the prognosis of agenesis of the corpus callosum is so unpredictable, detecting concomitant central system defects on MR imaging can help with prenatal and postnatal medical care. Although the majority of prenatal MR imaging applications are related to the cranial nervous system, new developments in foetal surgical intervention have expanded the utility of foetal MR imaging in thoracoabdominal illness detection. Fetal MR imaging can help diagnose abnormalities such congenital cystic adenomatoid malformation, congenital diaphragmatic hernia, cystic hygroma, and bronchopulmonary sequestration. Accurate assessment of foetal lung and liver sizes is critical in foetal surgical planning and postnatal prognosis in the case of congenital diaphragmatic hernia. Some high-risk pregnancies may also benefit from obstetric MR imaging, according to preliminary research. With a combination of foetal weight estimates and liver volume measurements, birth weight may be correctly predicted and the diagnosis of intrauterine growth retardation or macrosomia can be made with confidence.

A Survey on Convolutional Neural Networks for MRI Analysis

As of late, Convolutional Neural Networks have been very successful in segmentation and classification tasks. Magnetic resonance imaging (MRI) is a favored medical imaging method that comes up with interesting information for the diagnosis of different diseases.MR method is getting to be exceptionally well-known due to its non-invasive rule and for this reason, automated processing of this sort of image is getting noticed. MRI is effectively and widely used for tumor detection. Brain tumor detection is a popular medical application of MRI. Automating segmentation using CNN assists radiologists to lessen the high manual workload of tumor evaluation. CNN classification accuracy depends on network parameters and training data. CNN has the benefit of learning image features automatically directly out of multi-modal MRI images. In this survey paper, we have presented a summary of CNN's recent advancement in its technique applied on MRI images. The aim of this survey is to discuss various architectures and factors affecting the performance of CNN for learning features from different available MRI datasets. Based on the survey, section III (CNN for MRI analysis) comprises three subsections: A) MRI data and processing, B) CNN dimensionality, C) CNN architectures.

Double-crossed radiofrequency coil with improved uniformity for rodent MRI at 7 T

A transceiver volume coil for High Field Magnetic Resonance Imaging was developed based on Temnikov’s NMR probe coil. The critical advantage of this design is that requires only one trimmer capacitor for both tuning and matching. Electromagnetic simulations of our coil were compared to a four-rung birdcage coil to evaluate their performances. A transceiver coil prototype, called the double-cross coil and a birdcage coil were built to compare and contrast their feasibility. Both coil prototypes were operated in the linear mode. Experimental quality factors were Qu/Ql=101/45 for the double-cross coil and Qu/Ql=105/43 for the birdcage coil. Phantom images were acquired to test the viability of each coil for high field magnetic resonance imaging applications. The signal-to-noise ratios, noise factors and uniformity values were also calculated: 85.26/0.74/44.48 for the double-cross coil and 76.54/1.9/65.65 for the birdcage coil. These volume coils showed similar performance, but the double-cross coil has better uniformity and a slightly lower noise figure than the birdcage coil. A remarkable agreement of experimental and simulated B1 was obtained for the double-cross coil. These experimental and numerical results demonstrate the feasibility of the double-cross volume coil with better uniformity for rodent magnetic resonance imaging at 7 T.

Water‐dispersible Gadolinium Oxide Nanoplates as an Effective Positive Magnetic Resonance Imaging Contrast Agent

AbstractGadolinium oxide (Gd2O3) nanoplates have been successfully synthesized by thermal decomposition method in the presence of oleic acid and oleylamine as surfactants. As a result, the nanoplates have average edge length and thickness around 10 nm and 1.1 nm, respectively. The hydrophobic OA/OM capped Gd2O3 nanoplates were encapsulated with amphiphilic poly (maleic anhydride‐alt‐1‐octadecene) polymer (PMAO) for phase transfer into aqueous media. The obtained Gd2O3@PMAO showed a hydrodynamic size of 32 nm with good dispersion in water solvent and stable in wide range of pH (pH=2÷11) and at electrolyte concentrations as high as NaCl 380 mM. In addition, the in vitro toxicity tests confirmed the biocompatibility of Gd2O3@PMAO nanoplates. The magnetic resonance imaging (MRI) result exhibited the r1 of Gd2O3@PMAO nanoplates (16.95 mM−1s−1) is four times higher than that of clinically used Gd‐DTPA. These results suggest that the PMAO coated ‐Gd2O3 nanoplates are potential T1 contrast agents for in vivo MRI application.

On the reliability of deep learning-based classification for Alzheimer's disease: Multi-cohorts, multi-vendors, multi-protocols, and head-to-head validation.

Structural changes in the brain due to Alzheimer’s disease dementia (ADD) can be observed through brain T1-weighted magnetic resonance imaging (MRI) images. Many ADD diagnostic studies using brain MRI images have been conducted with machine-learning and deep-learning models. Although reliability is a key in clinical application and applicability of low-resolution MRI (LRMRI) is a key to broad clinical application, both are not sufficiently studied in the deep-learning area. In this study, we developed a 2-dimensional convolutional neural network-based classification model by adopting several methods, such as using instance normalization layer, Mixup, and sharpness aware minimization. To train the model, MRI images from 2,765 cognitively normal individuals and 1,192 patients with ADD from the Samsung medical center cohort were exploited. To assess the reliability of our classification model, we designed external validation in multiple scenarios: (1) multi-cohort validation using four additional cohort datasets including more than 30 different centers in multiple countries, (2) multi-vendor validation using three different MRI vendor subgroups, (3) LRMRI image validation, and finally, (4) head-to-head validation using ten pairs of MRI images from ten individual subjects scanned in two different centers. For multi-cohort validation, we used the MRI images from 739 subjects from the Alzheimer’s Disease Neuroimaging Initiative cohort, 125 subjects from the Dementia Platform of Korea cohort, 234 subjects from the Premier cohort, and 139 subjects from the Gachon University Gil Medical Center. We further assessed classification performance across different vendors and protocols for each dataset. We achieved a mean AUC and classification accuracy of 0.9868 and 0.9482 in 5-fold cross-validation. In external validation, we obtained a comparable AUC of 0.9396 and classification accuracy of 0.8757 to other cross-validation studies in the ADNI cohorts. Furthermore, we observed the possibility of broad clinical application through LRMRI image validation by achieving a mean AUC and classification accuracy of 0.9404 and 0.8765 at cross-validation and AUC and classification accuracy of 0.8749 and 0.8281 at the ADNI cohort external validation.

Novel Numerical Basis Sets for Electromagnetic Field Expansion in Arbitrary Inhomogeneous Objects.

We investigated how to construct low-order subspace basis sets to accurately represent electromagnetic fields generated within inhomogeneous arbitrary objects by radio-frequency sources external to a Huygen's surface. The basis generation relies on the singular value decomposition of Green's functions integro-differential operators which makes it feasible to derive a reduced-order yet stable model. We present a detailed study of the theoretical and numerical requisites for generating such basis, and show how it can be used to calculate performance limits in magnetic resonance imaging applications. Finally, we propose a novel numerical framework for the computation of characteristic modes of arbitrary inhomogeneous objects. We validated accuracy and convergence properties of the numerical basis against a complete analytical basis in the case of a uniform spherical object. We showed that the discretization of the Huygens's surface has a minimal effect on the accuracy of the calculations, which mainly depended on the electromagnetic solver resolution and order of approximation.

Impact of Sex and Cardiovascular Risk Factors on Myocardial T1, Extracellular Volume Fraction, and T2 at 3 Tesla: Results From the Population-Based, Hamburg City Health Study.

Reliable reference intervals are crucial for clinical application of myocardial T1 and T2 mapping cardiovascular magnetic resonance imaging. This study evaluated the impact of sex and cardiovascular risk factors on myocardial T1, extracellular volume fraction (ECV), and T2 at 3T in the population-based HCHS (Hamburg City Health Study). The final study sample consisted of 1576 consecutive HCHS participants between 46 and 78 years without prevalent heart disease, including 1020 (67.3%) participants with hypertension and 110 (7.5%) with diabetes. T1 and T2 mapping were performed on a 3T scanner using 5b(3b)3b modified Look-Locker inversion recovery and T2 prepared, fast-low-angle shot sequence, respectively. Stepwise regression analyses were performed to identify variables with an independent impact on T1, ECV, and T2. Reference intervals were defined as the interval between the 2.5% and 97.5% quantiles. Sex was the major independent influencing factor of myocardial native T1, ECV, and T2. Female patients had significantly higher upper limits of reference intervals for native T1 (1112-1261 versus 1079-1241 ms), ECV (23%-33% versus 22%-32%), and T2 (36-46 versus 35-45 ms) compared with male patients (all P<0.001). Cardiovascular risk factors, such as diabetes and hypertension, did not systematically affect native T1. There was an independent association of T2 by hypertension and, to a lesser degree, by left ventricular mass, heart rate (all P<0.001), and body mass index (P=0.001). Sex needs to be considered as the major, independent influencing factor for clinical application of myocardial T1, ECV, and T2 measurements. Consequently, sex-specific reference intervals should be used in clinical routine. Our findings suggest that there is no need for specific reference intervals for myocardial T1 and ECV measurements in individuals with cardiovascular risk factors. However, hypertension should be considered as an additional factor for clinical application of T2 measurements. URL: https://www. gov; Unique identifier: NCT03934957.

Iron oxide nanoparticle targeting mechanism and its application in tumor magnetic resonance imaging and therapy.

Iron oxide nanoparticles (IONPs) can be applied to targeted drug delivery, targeted diagnosis and treatment of tumors due to their easy preparation, good biocompatibility, low biotoxicity, high imaging quality, high magnetothermal sensitivity and stable targeting after certain surface modifications. However, the complexity of the mechanism of action and their properties has led to there being few clinical applications of IONPs. This review first describes the targeting mechanisms of IONPs and their toxicity issues, then discusses the applications of IONP targeting studies in tumor MRI. Finally, the applications of IONP targeting in tumor therapy are listed. The authorsshow the advantages of targeting IONPs and hope that the review will increase the possibility of converting IONPs from biomedical applications to clinical applications.

HIWDNet: A hybrid image-wavelet domain network for fast magnetic resonance image reconstruction

The application of Magnetic Resonance Imaging (MRI) is limited due to the long acquisition time of k-space signals. Recently, many deep learning-based MR image reconstruction methods have been proposed to reduce acquisition time and improve MRI image quality by reconstructing images from under-sampled k-space data. However, these methods suffer from two shortcomings. Firstly, the reconstruction network are mainly designed in the image domain or frequency domain, while ignoring the characteristics of time-frequency features in the wavelet domain. In addition, the existing cross-domain methods design the same reconstruction network in different transform domains, so that the network cannot learn targeted information for different domains. To solve the above problems, we propose a Hybrid Image-Wavelet Domain Reconstruction Network (HIWDNet) for fast MRI reconstruction. Specifically, we employ Cross-scale Dense Feature Fusion Module (CDFFM) in the image domain to reconstruct the basic structure of MR images, while introducing Region Adaptive Artifact Removal Module (RAARM) to remove aliasing artifacts in large areas. Then, a Wavelet Sub-band Reconstruction Module (WSRM) is proposed to refine wavelet sub-bands to improve the accuracy of HIWDNet. The proposed method is evaluated in different sampling modes on the fastMRI dataset, the CC359 dataset and the IXI dataset. Extensive experimental results show that HIWDNet achieves better results on both SSIM and PSNR evaluation metrics compared with other methods.

Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation.

Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation. However, deep learning models are not trusted in the clinical routine due to failing silently on out-of-distribution (OOD) data. We propose a lightweight OOD detection method that leverages the Mahalanobis distance in the feature space and seamlessly integrates into state-of-the-art segmentation pipelines. The simple approach can even augment pre-trained models with clinically relevant uncertainty quantification. We validate our method across four chest CT distribution shifts and two magnetic resonance imaging applications, namely segmentation of the hippocampus and the prostate. Our results show that the proposed method effectively detects far- and near-OOD samples across all explored scenarios.

QMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data

The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several neuroimaging modalities. Traditionally, BIDS had a strong focus on functional magnetic resonance imaging (MRI) datasets and lacked guidance on how to store multimodal structural MRI datasets. Here, we present and describe the BIDS Extension Proposal 001 (BEP001), which adds a range of quantitative MRI (qMRI) applications to the BIDS. In general, the aim of qMRI is to characterize brain microstructure by quantifying the physical MR parameters of the tissue via computational, biophysical models. By proposing this new standard, we envision standardization of qMRI through multicenter dissemination of interoperable datasets. This way, BIDS can act as a catalyst of convergence between qMRI methods development and application-driven neuroimaging studies that can help develop quantitative biomarkers for neural tissue characterization. In conclusion, this BIDS extension offers a common ground for developers to exchange novel imaging data and tools, reducing the entrance barrier for qMRI in the field of neuroimaging.

Vascular and Vasogenic Manifestations of Systemic ANCA-Associated Vasculitis with Renal Involvement in Non-Contrast Brain MRI in Patients with Acute Disease Onset.

Background. Data concerning central nervous system (CNS) alterations in ANCA-associated vasculitis with renal involvement (AAVR) are sparse. The study aimed to assess vascular and vasogenic brain alterations in patients with acute onset of AAVR and the applicability of non-contrast magnetic resonance imaging (MRI) techniques in this diagnosis. Methods. Thirty-eight patients with acute onset of AAVR were included in the study. BVAS/WG, c-ANCA, p-ANCA, renal function and perfusion, neurological assessment, and brain MRI were performed. Results. Cerebral vascular alternating narrowing and dilatation (VAND) was detected in 42.1% of patients, and the black-blood was significantly more diagnostic than the TOF technique (p < 0.001). VAND occurrence was independently associated with the concentration of p-ANCA. The vasogenic white matter lesions (VWML) were found in 94.4% of patients, and in their detection, SWAN was significantly better than the FLAIR technique (p = 0.002). The number of VWML correlated with age and cranial nerve damage. Hemosiderin deposits were found in 21.6% of patients and were associated with a gait impairment and paresthesia. Conclusions. Vascular and vasogenic alterations in the CNS are frequent in patients with acute onset of systemic ANCA-associated vasculitis with renal involvement. Non-contrast MRI is useful in the diagnosis of brain vasculitis.

Correlating Magnetic Hyperthermia and Magnetic Resonance Imaging Contrast Performance of Cubic Iron Oxide Nanoparticles with Crystal Structural Integrity.

Magnetic iron oxide nanoparticles have multiple biomedical applications in AC-field hyperthermia and magnetic resonance imaging (MRI) contrast enhancement. Here, two cubic particle suspensions are analyzed in detail, one suspension displayed strong magnetic heating and MRI contrast efficacies, while the other responded weakly. This is despite them having almost identical size, morphology, and colloidal dispersion. Aberration-corrected scanning transmission electron microscopy, electron energy loss spectroscopy, and high-resolution transmission electron microscopy analysis confirmed that the spinel phase Fe3O4 was present in both samples and identified prominent crystal lattice defects for the weakly responding one. These are interpreted as frustrating the orientation of the moment within the cubic crystals. The relationship between crystal integrity and the moment magnitude and dynamics is elucidated for the case of fully dispersed single nanocubes, and its connection with the emergent hyperthermia and MRI contrast responses is established.

Study on the Diagnostic Value of Contrast-Enhanced Ultrasound and Magnetic Resonance Imaging in Prostate Cancer.

Objective The aim is to study the different roles of single and joint application of magnetic resonance imaging (MRI) and contrast-enhanced ultrasound (CEUS) in prostate malignant tumors. Methods 72 patients with prostate masses who underwent CEUS and MRI examination in our hospital from October 2021 and March 2022 were enrolled in this research. The differentially diagnostic roles of CEUS, MRI, and CEUS combined MRI for prostate cancer was assessed on basis of pathological findings as the reference standard. The specificity and sensitivity of the joint application for prostate malignant tumors with various prostate-specific antigen (PSA) levels were also evaluated. Results The sensitivity of CEUS, MRI, and the joint application for prostate cancer were 72.1%, 74.4%, and 90.7%, respectively. Compared with single application, the sensitivity of CEUS combined with MRI was significantly higher. The specificity of MRI, CEUS, and the combination of the two for prostate cancer were 82.8%, 79.3%, and 89.7%, respectively, and the statistical differences for specificity were not found. The area under ROC curve (AUC) of CEUS combined with MRI in prostate malignant tumor diagnosis was obviously more than that of CEUS and MRI (P < 0.05). CEUS combined with MRI has relative high sensitivity in these patients with different levels of PSA. Conclusions Contrast-enhanced ultrasound combined with MRI can significantly improve the sensitivity and specificity of prostate cancer diagnosis so that patients can be better diagnosed in advance.

A Mouse Holder for Awake Functional Imaging in Unanesthetized Mice: Applications in 31P Spectroscopy, Manganese-Enhanced Magnetic Resonance Imaging Studies, and Resting-State Functional Magnetic Resonance Imaging.

Anesthesia is often used in preclinical imaging studies that incorporate mouse or rat models. However, multiple reports indicate that anesthesia has significant physiological impacts. Thus, there has been great interest in performing imaging studies in awake, unanesthetized animals to obtain accurate results without the confounding physiological effects of anesthesia. Here, we describe a newly designed mouse holder that is interfaceable with existing MRI systems and enables awake in vivo mouse imaging. This holder significantly reduces head movement of the awake animal compared to previously designed holders and allows for the acquisition of improved anatomical images. In addition to applications in anatomical T2-weighted magnetic resonance imaging (MRI), we also describe applications in acquiring 31P spectra, manganese-enhanced magnetic resonance imaging (MEMRI) transport rates and resting-state functional magnetic resonance imaging (rs-fMRI) in awake animals and describe a successful conditioning paradigm for awake imaging. These data demonstrate significant differences in 31P spectra, MEMRI transport rates, and rs-fMRI connectivity between anesthetized and awake animals, emphasizing the importance of performing functional studies in unanesthetized animals. Furthermore, these studies demonstrate that the mouse holder presented here is easy to construct and use, compatible with standard Bruker systems for mouse imaging, and provides rigorous results in awake mice.

Current MRI Methods for the Assessment of Pathologic Prostate: A Brief Review for Clinicians.

The application of Magnetic Resonance Imaging (MRI) have helped in different modalities for prostate cancer management, from early detection to treatment planning and follow-up, the evolution of MRI techniques allows to obtain not only anatomical but also functional information to take advantage of prostate cancer detection and staging while supplying prognostic and predictive biomarkers. This review presents conventional and advanced MRI techniques (known as multiparametric MRI) that allow functional and quantitative assessment of the normal prostate gland and its correlation with prostate cancer. Additional topics include the epidemiology of prostate cancer following the Global Burden Diseases Cancer Collaboration 2018, the clinical anatomy of the prostate gland, and the lower urinary tract; we also mention some aspects of the diagnosis performance in ultrasound. We end the review with a brief explanation about the anatomical foundation of external-beam planning radiotherapy.

High-Precision Control Method for High-Power MRI Gradient Power Amplifiers

In magnetic resonance imaging (MRI), high-power gradient power amplifiers (GPAs) are required to drive the gradient coils to generate strong and high-fidelity gradient fields. High precision is an essential requirement for the GPAs since precision directly impacts MRI imaging quality. Various aspects of the GPA have been the subject of research in the past years; however, high-precision GPA control that meets the stringent requirements of MRI applications is still a challenge. This article proposes a novel multi-rational-delay variables state space control method and an efficient out-of-band signal injection method to achieve GPA control accuracy at the level of one part per million at MVA output power levels. First, a systematic modeling and design method of the state space controller for high-power GPA is introduced utilizing state vectors with multi-rational-delay variables. This method improves the GPA dynamic performance significantly. Second, an efficient out-of-band signal injection method is presented to further improve the control precision at low output current, enabling the fulfillment of the challenging high-precision MRI requirements over the full GPA output range. Finally, the high-precision control method is validated in a GPA demonstrator with 500 A/1000 V output. Key results are a 30% improvement in current pulse reproducibility with respect to the conventional control method and a factor of 2.5 less noise at low currents. These experimental results validate the proposed novel method for the high-precision control of GPAs in MRI applications and prove its capability to contribute to significantly improved MRI image quality.

Black Bone MRI for Virtual Surgical Planning in Craniomaxillofacial Surgery.

Advances in computer-aided design and computer-aided manufacturing software have improved translational applications of virtual surgical planning (VSP) in craniomaxillofacial surgery, allowing for precise and accurate fabrication of cutting guides, stereolithographic models, and custom implants. High-resolution computed tomography (CT) imaging has traditionally been the gold standard imaging modality for VSP in craniomaxillofacial surgery but delivers ionizing radiation. Black bone magnetic resonance imaging (MRI) reduces the risks related to radiation exposure and has comparable functionality when compared with CT for VSP. Our group has studied the accuracy of utilizing black bone MRI in planning and executing several types of craniofacial surgeries, including cranial vault remodeling, maxillary advancement, and mandibular reconstruction using fibular bone. Here, we review clinical applications of black bone MRI pertaining to VSP and three-dimensional (3D)-printed guide creation for craniomaxillofacial surgery. Herein, we review the existing literature and our institutional experience comparing black bone MRI and CT in VSP-generated 3D model creation in cadaveric craniofacial surgeries including cranial vault reconstruction, maxillary advancement, and mandibular reconstruction with fibular free flap. Cadaver studies have demonstrated the ability to perform VSP and execute the procedure based on black bone MRI data and achieve outcomes similar to CT when performed for cranial vault reshaping, maxillary advancement, and mandibular reconstruction with free fibula. Limitations of the technology include increased time and costs of the MRI compared with CT and the possible need for general anesthesia or sedation in the pediatric population. VSP and 3D surgical guide creation can be performed using black bone MRI with comparable accuracy to high-resolution CT scans in a wide variety of craniofacial reconstructions. Successful segmentation, VSP, and 3D printing of accurate guides from black bone MRI demonstrate potential to change the preoperative planning standard of care. Black bone MRI also reduces exposure to ionizing radiation, which is of particular concern for the pediatric population or patients undergoing multiple scans.

Reporter Genes for Brain Imaging Using MRI, SPECT and PET.

The use of molecular imaging technologies for brain imaging can not only play an important supporting role in disease diagnosis and treatment but can also be used to deeply study brain functions. Recently, with the support of reporter gene technology, optical imaging has achieved a breakthrough in brain function studies at the molecular level. Reporter gene technology based on traditional clinical imaging modalities is also expanding. By benefiting from the deeper imaging depths and wider imaging ranges now possible, these methods have led to breakthroughs in preclinical and clinical research. This article focuses on the applications of magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) reporter gene technologies for use in brain imaging. The tracking of cell therapies and gene therapies is the most successful and widely used application of these techniques. Meanwhile, breakthroughs have been achieved in the research and development of reporter genes and their imaging probe pairs with respect to brain function research. This paper introduces the imaging principles and classifications of the reporter gene technologies of these imaging modalities, lists the relevant brain imaging applications, reviews their characteristics, and discusses the opportunities and challenges faced by clinical imaging modalities based on reporter gene technology. The conclusion is provided in the last section.

Special Issue on Clinical Applications of Magnetic Resonance Imaging in Genitourinary Cancers

In the field of oncologic imaging, MRI represents one of the most powerful diagnostic tools at physicians’ disposal, with its superb contrast resolution and its capability to assess both the morphological and functional features of neoplasms [...]