•Introduce conversion tools for different vendors.•Explain conversion basics.•Present methods to detect and correctproblems.
Clinical imaging data are typically stored and transferred in the DICOM ...format, whereas the NIfTI format has been widely adopted by scientists in the neuroimaging community. Therefore, a vital initial step in processing the data is to convert images from the complicated DICOM format to the much simpler NIfTI format. While there are a number of tools that usually handle DICOM to NIfTI conversion seamlessly, some variations can disrupt this process.
We provide some insight into the challenges faced with image conversion. First, different manufacturers implement the DICOM format differently which complicates the conversion. Second, different modalities and sub-modalities may need special treatment during conversion. Lastly, the image transferring and archiving can also impact the DICOM conversion.
We present results in several error-prone domains, including the slice order for functional imaging, phase encoding direction for distortion correction, effect of diffusion gradient direction, and effect of gantry correction for some imaging modality.
Conversion tools are often designed for a specific manufacturer or modality. The tools and insight we present here are aimed at different manufacturers or modalities.
The imaging conversion is complicated by the variation of images. An understanding of the conversion basics can be helpful for identifying the source of the error. Here we provide users with simple methods for detecting and correcting problems. This also serves as an overview for developers who wish to either develop their own tools or adapt the open source tools created by the authors.
Functional neuroimaging techniques have transformed our ability to probe the neurobiological basis of behaviour and are increasingly being applied by the wider neuroscience community. However, ...concerns have recently been raised that the conclusions that are drawn from some human neuroimaging studies are either spurious or not generalizable. Problems such as low statistical power, flexibility in data analysis, software errors and a lack of direct replication apply to many fields, but perhaps particularly to functional MRI. Here, we discuss these problems, outline current and suggested best practices, and describe how we think the field should evolve to produce the most meaningful and reliable answers to neuroscientific questions.
Pooling magnetic resonance imaging (MRI) data across research studies, or utilizing shared data from imaging repositories, presents exceptional opportunities to advance and enhance reproducibility of ...neuroscience research. However, scanner confounds hinder pooling data collected on different scanners or across software and hardware upgrades on the same scanner, even when all acquisition protocols are harmonized. These confounds reduce power and can lead to spurious findings. Unfortunately, methods to address this problem are scant. In this study, we propose a novel denoising approach that implements a data-driven linked independent component analysis (LICA) to identify scanner-related effects for removal from multimodal MRI to denoise scanner effects. We utilized multi-study data to test our proposed method that were collected on a single 3T scanner, pre- and post-software and major hardware upgrades and using different acquisition parameters. Our proposed denoising method shows a greater reduction of scanner-related variance compared with standard GLM confound regression or ICA-based single-modality denoising. Although we did not test it here, for combining data across different scanners, LICA should prove even better at identifying scanner effects as between-scanner variability is generally much larger than within-scanner variability. Our method has great promise for denoising scanner effects in multi-study and in large-scale multi-site studies that may be confounded by scanner differences.
Summary Cerebral small vessel disease (SVD) is a common accompaniment of ageing. Features seen on neuroimaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, ...perivascular spaces, microbleeds, and brain atrophy. SVD can present as a stroke or cognitive decline, or can have few or no symptoms. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive deficits, physical disabilities, and other symptoms of neurodegeneration. Terminology and definitions for imaging the features of SVD vary widely, which is also true for protocols for image acquisition and image analysis. This lack of consistency hampers progress in identifying the contribution of SVD to the pathophysiology and clinical features of common neurodegenerative diseases. We are an international working group from the Centres of Excellence in Neurodegeneration. We completed a structured process to develop definitions and imaging standards for markers and consequences of SVD. We aimed to achieve the following: first, to provide a common advisory about terms and definitions for features visible on MRI; second, to suggest minimum standards for image acquisition and analysis; third, to agree on standards for scientific reporting of changes related to SVD on neuroimaging; and fourth, to review emerging imaging methods for detection and quantification of preclinical manifestations of SVD. Our findings and recommendations apply to research studies, and can be used in the clinical setting to standardise image interpretation, acquisition, and reporting. This Position Paper summarises the main outcomes of this international effort to provide the STandards for ReportIng Vascular changes on nEuroimaging (STRIVE).
Radiological examination of the brain is a critical determinant of stroke care pathways. Accessible neuroimaging is essential to detect the presence of intracerebral hemorrhage (ICH). Conventional ...magnetic resonance imaging (MRI) operates at high magnetic field strength (1.5-3 T), which requires an access-controlled environment, rendering MRI often inaccessible. We demonstrate the use of a low-field MRI (0.064 T) for ICH evaluation. Patients were imaged using conventional neuroimaging (non-contrast computerized tomography (CT) or 1.5/3 T MRI) and portable MRI (pMRI) at Yale New Haven Hospital from July 2018 to November 2020. Two board-certified neuroradiologists evaluated a total of 144 pMRI examinations (56 ICH, 48 acute ischemic stroke, 40 healthy controls) and one ICH imaging core lab researcher reviewed the cases of disagreement. Raters correctly detected ICH in 45 of 56 cases (80.4% sensitivity, 95%CI: 0.68-0.90). Blood-negative cases were correctly identified in 85 of 88 cases (96.6% specificity, 95%CI: 0.90-0.99). Manually segmented hematoma volumes and ABC/2 estimated volumes on pMRI correlate with conventional imaging volumes (ICC = 0.955, p = 1.69e-30 and ICC = 0.875, p = 1.66e-8, respectively). Hematoma volumes measured on pMRI correlate with NIH stroke scale (NIHSS) and clinical outcome (mRS) at discharge for manual and ABC/2 volumes. Low-field pMRI may be useful in bringing advanced MRI technology to resource-limited settings.
Differentiating bipolar disorder (BD) from recurrent unipolar depression (UD) is a major clinical challenge. Main reasons for this include the higher prevalence of depressive relative to hypo/manic ...symptoms during the course of BD illness and the high prevalence of subthreshold manic symptoms in both BD and UD depression. Identifying objective markers of BD might help improve accuracy in differentiating between BD and UD depression, to ultimately optimize clinical and functional outcome for all depressed individuals. Yet, only eight neuroimaging studies to date have directly compared UD and BD depressed individuals. Findings from these studies suggest more widespread abnormalities in white matter connectivity and white matter hyperintensities in BD than UD depression, habenula volume reductions in BD but not UD depression, and differential patterns of functional abnormalities in emotion regulation and attentional control neural circuitry in the two depression types. These findings suggest different pathophysiologic processes, especially in emotion regulation, reward, and attentional control neural circuitry in BD versus UD depression. This review thereby serves as a call to action to highlight the pressing need for more neuroimaging studies, using larger samples sizes, comparing BD and UD depressed individuals. These future studies should also include dimensional approaches, studies of at-risk individuals, and more novel neuroimaging approaches, such as connectivity analysis and machine learning. Ultimately, these approaches might provide biomarkers to identify individuals at future risk for BD versus UD and biological targets for more personalized treatment and new treatment developments for BD and UD depression.
Increasing numbers of 7 T (7 T) magnetic resonance imaging (MRI) scanners are in research and clinical use. 7 T MRI can increase the scanning speed, spatial resolution and contrast-to-noise-ratio of ...many neuroimaging protocols, but technical challenges in implementation have been addressed in a variety of ways across sites. In order to facilitate multi-centre studies and ensure consistency of findings across sites, it is desirable that 7 T MRI sites implement common high-quality neuroimaging protocols that can accommodate different scanner models and software versions.
With the installation of several new 7 T MRI scanners in the United Kingdom, the UK7T Network was established with an aim to create a set of harmonized structural and functional neuroimaging sequences and protocols. The Network currently includes five sites, which use three different scanner platforms, provided by two different vendors.
Here we describe the harmonization of functional and anatomical imaging protocols across the three different scanner models, detailing the necessary changes to pulse sequences and reconstruction methods. The harmonized sequences are fully described, along with implementation details. Example datasets acquired from the same subject on all Network scanners are made available. Based on these data, an evaluation of the harmonization is provided. In addition, the implementation and validation of a common system calibration process is described.
•Harmonised neuroimaging is established on 7 tesla MRI scanners at five sites.•Efficacy of harmonisation is demonstrated with scans on one subject at all sites.•Common calibration protocols achieve better standardisation than vendor’s own.•Protocols and data are available online for all current 7 tesla scanner models.
Following early efforts in applying nuclear magnetic resonance (NMR) spectroscopy to study biological processes in intact systems, and particularly since the introduction of 4 T human scanners circa ...1990, rapid progress was made in imaging and spectroscopy studies of humans at 4 T and animal models at 9.4 T, leading to the introduction of 7 T and higher magnetic fields for human investigation at about the turn of the century. Work conducted on these platforms has provided numerous technological solutions to challenges posed at these ultrahigh fields, and demonstrated the existence of significant advantages in signal-to-noise ratio and biological information content. Primary difference from lower fields is the deviation from the near field regime at the radiofrequencies (RF) corresponding to hydrogen resonance conditions. At such ultrahigh fields, the RF is characterized by attenuated traveling waves in the human body, which leads to image non-uniformities for a given sample-coil configuration because of destructive and constructive interferences. These non-uniformities were initially considered detrimental to progress of imaging at high field strengths. However, they are advantageous for parallel imaging in signal reception and transmission, two critical technologies that account, to a large extend, for the success of ultrahigh fields. With these technologies and improvements in instrumentation and imaging methods, today ultrahigh fields have provided unprecedented gains in imaging of brain function and anatomy, and started to make inroads into investigation of the human torso and extremities. As extensive as they are, these gains still constitute a prelude to what is to come given the increasingly larger effort committed to ultrahigh field research and development of ever better instrumentation and techniques.
•Development of ultrahigh magnetic field MRI for human imaging.•Functional brain imaging (fMRI) at ultrahigh magnetic fields; cortical columns and layers.•Solutions to Ultrahigh field challenges: Power deposition (SAR), transmit RF and static magnetic field inhomogeneities.•Multichannel RF (B1) transmit and transmit pulses.•Highly accelerated imaging for high resolution whole brain coverage; Human Brain Connectome at ultrahigh fields.
Diffuse correlation spectroscopy (DCS) uses the temporal fluctuations of near-infrared (NIR) light to measure cerebral blood flow (CBF) non-invasively. Here, we provide a brief history of DCS ...applications in the brain with an emphasis on the underlying physical ideas, common instrumentation and validation. Then we describe recent clinical research that employs DCS-measured CBF as a biomarker of patient well-being, and as an indicator of hemodynamic and metabolic responses to functional stimuli.
•Diffuse correlation spectroscopy (DCS) for clinical and functional neuroimaging.•Optical measurement of cerebral blood flow (CBF) with DCS is presented.•Hybrid fNIRS and fDCS is presented as a method to measure cerebral metabolism.
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