The Past, Present, and Future of the Brain Imaging Data Structure (BIDS).

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Positron emission tomography and magnetic resonance imaging of the brain in experimental human malaria, a prospective cohort study.

Cerebral malaria is the most serious manifestation of severe falciparum malaria. Sequestration of infected red blood cells and microvascular dysfunction are key contributing processes. Whether these processes occur in early stage disease prior to clinical manifestations is unknown. To help localize and understand these processes during the early stages of infection, we performed 18-F fluorodeoxyglucose positron emission tomography/magnetic resonance imaging in volunteers with Plasmodium falciparum induced blood stage malaria (IBSM) infection, and compared results to individuals with P. vivax infection, in whom coma is rare. Seven healthy, malaria-naïve participants underwent imaging at baseline, and at early symptom onset a median 9 days following inoculation (n = 4 P. falciparum, n = 3 P. vivax). Participants with P. falciparum infection demonstrated marked lability in radiotracer uptake across all regions of the brain, exceeding expected normal variation (within subject coefficient of variation (wCV): 14.4%) compared to the relatively stable uptake in participants with P. vivax infection (wCV: 3.5%). No consistent imaging changes suggestive of microvascular dysfunction were observed in either group. Neuroimaging in early IBSM studies is safe and technically feasible, with preliminary results suggesting that differences in brain tropism between P. falciparum and P. vivax may occur very early in infection.

A novel semiautomated method for background activity and biological tumour volume definition to improve standardisation of 18F-FET PET imaging in glioblastoma.

BACKGROUND: Multicentre clinical trials evaluating the role of 18F-Fluoroethyl-L-tyrosine (18F-FET) PET as a diagnostic biomarker in glioma management have highlighted a need for standardised methods of data analysis. 18F-FET uptake normalised against background in the contralateral brain is a standard imaging technique to delineate the biological tumour volume (BTV). Quantitative analysis of 18F-FET PET images requires a consistent and robust background activity. Currently, defining background activity involves the manual selection of an arbitrary region of interest, a process that is subject to large variability. This study aims to eliminate methodological errors in background activity definition through the introduction of a semiautomated method for region of interest selection. A new method for background activity definition, involving the semiautomated generation of mirror-image (MI) reference regions, was compared with the current state-of-the-art method, involving manually drawing crescent-shape (gCS) reference regions. The MI and gCS methods were tested by measuring values of background activity and resulting BTV of 18F-FET PET scans of ten patients with recurrent glioblastoma multiforme generated from inputs provided by seven readers. To assess intra-reader variability, each scan was evaluated six times by each reader. Intra- and inter-reader variability in background activity and BTV definition was assessed by means of coefficient of variation. RESULTS: Compared to the gCS method, the MI method showed significantly lower intra- and inter-reader variability both in background activity and in BTV definition. CONCLUSIONS: The proposed semiautomated MI method minimises intra- and inter-reader variability, providing a valuable approach for standardisation of 18F-FET PET quantitative parameters. Trial registration ANZCTR, ACTRN12618001346268. Registered 9 August 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374253.

Automated COVID-19 diagnosis and prognosis with medical imaging and who is publishing: a systematic review.

OBJECTIVES:  To conduct a systematic survey of published techniques for automated diagnosis and prognosis of COVID-19 diseases using medical imaging, assessing the validity of reported performance and investigating the proposed clinical use-case. To conduct a scoping review into the authors publishing such work. METHODS:  The Scopus database was queried and studies were screened for article type, and minimum source normalized impact per paper and citations, before manual relevance assessment and a bias assessment derived from a subset of the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). The number of failures of the full CLAIM was adopted as a surrogate for risk-of-bias. Methodological and performance measurements were collected from each technique. Each study was assessed by one author. Comparisons were evaluated for significance with a two-sided independent t-test. FINDINGS:  Of 1002 studies identified, 390 remained after screening and 81 after relevance and bias exclusion. The ratio of exclusion for bias was 71%, indicative of a high level of bias in the field. The mean number of CLAIM failures per study was 8.3 ± 3.9 [1,17] (mean ± standard deviation [min,max]). 58% of methods performed diagnosis versus 31% prognosis. Of the diagnostic methods, 38% differentiated COVID-19 from healthy controls. For diagnostic techniques, area under the receiver operating curve (AUC) = 0.924 ± 0.074 [0.810,0.991] and accuracy = 91.7% ± 6.4 [79.0,99.0]. For prognostic techniques, AUC = 0.836 ± 0.126 [0.605,0.980] and accuracy = 78.4% ± 9.4 [62.5,98.0]. CLAIM failures did not correlate with performance, providing confidence that the highest results were not driven by biased papers. Deep learning techniques reported higher AUC (p < 0.05) and accuracy (p < 0.05), but no difference in CLAIM failures was identified. INTERPRETATION:  A majority of papers focus on the less clinically impactful diagnosis task, contrasted with prognosis, with a significant portion performing a clinically unnecessary task of differentiating COVID-19 from healthy. Authors should consider the clinical scenario in which their work would be deployed when developing techniques. Nevertheless, studies report superb performance in a potentially impactful application. Future work is warranted in translating techniques into clinical tools.

Motion estimation and correction for simultaneous PET/MR using SIRF and CIL.

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF's recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF's integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.

Positron emission tomography and magnetic resonance imaging in experimental human malaria to identify organ-specific changes in morphology and glucose metabolism: A prospective cohort study.

BACKGROUND: Plasmodium vivax has been proposed to infect and replicate in the human spleen and bone marrow. Compared to Plasmodium falciparum, which is known to undergo microvascular tissue sequestration, little is known about the behavior of P. vivax outside of the circulating compartment. This may be due in part to difficulties in studying parasite location and activity in life. METHODS AND FINDINGS: To identify organ-specific changes during the early stages of P. vivax infection, we performed 18-F fluorodeoxyglucose (FDG) positron emission tomography/magnetic resonance imaging (PET/MRI) at baseline and just prior to onset of clinical illness in P. vivax experimentally induced blood-stage malaria (IBSM) and compared findings to P. falciparum IBSM. Seven healthy, malaria-naive participants were enrolled from 3 IBSM trials: NCT02867059, ACTRN12616000174482, and ACTRN12619001085167. Imaging took place between 2016 and 2019 at the Herston Imaging Research Facility, Australia. Postinoculation imaging was performed after a median of 9 days in both species (n = 3 P. vivax; n = 4 P. falciparum). All participants were aged between 19 and 23 years, and 6/7 were male. Splenic volume (P. vivax: +28.8% [confidence interval (CI) +10.3% to +57.3%], P. falciparum: +22.9 [CI -15.3% to +61.1%]) and radiotracer uptake (P. vivax: +15.5% [CI -0.7% to +31.7%], P. falciparum: +5.5% [CI +1.4% to +9.6%]) increased following infection with each species, but more so in P. vivax infection (volume: p = 0.72, radiotracer uptake: p = 0.036). There was no change in FDG uptake in the bone marrow (P. vivax: +4.6% [CI -15.9% to +25.0%], P. falciparum: +3.2% [CI -3.2% to +9.6%]) or liver (P. vivax: +6.2% [CI -8.7% to +21.1%], P. falciparum: -1.4% [CI -4.6% to +1.8%]) following infection with either species. In participants with P. vivax, hemoglobin, hematocrit, and platelet count decreased from baseline at the time of postinoculation imaging. Decrements in hemoglobin and hematocrit were significantly greater in participants with P. vivax infection compared to P. falciparum. The main limitations of this study are the small sample size and the inability of this tracer to differentiate between host and parasite metabolic activity. CONCLUSIONS: PET/MRI indicated greater splenic tropism and metabolic activity in early P. vivax infection compared to P. falciparum, supporting the hypothesis of splenic accumulation of P. vivax very early in infection. The absence of uptake in the bone marrow and liver suggests that, at least in early infection, these tissues do not harbor a large parasite biomass or do not provoke a prominent metabolic response. PET/MRI is a safe and noninvasive method to evaluate infection-associated organ changes in morphology and glucose metabolism.

Flexible numerical simulation framework for dynamic PET-MR data.

This paper presents a simulation framework for dynamic PET-MR. The main focus of this framework is to provide motion-resolved MR and PET data and ground truth motion information. This can be used in the optimisation and quantitative evaluation of image registration and in assessing the error propagation due to inaccuracies in motion estimation in complex motion-compensated reconstruction algorithms. Contrast and tracer kinetics can also be simulated and are available as ground truth information. To closely emulate medical examination, input and output of the simulation are files in standardised open-source raw data formats. This enables the use of existing raw data as a template input and ensures seamless integration of the output into existing reconstruction pipelines. The proposed framework was validated in PET-MR and image registration applications. It was used to simulate a FDG-PET-MR scan with cardiac and respiratory motion. Ground truth motion information could be utilised to optimise parameters for PET and synergistic PET-MR image registration. In addition, a free-breathing dynamic contrast enhancement (DCE) abdominal scan of a patient with hepatic lesions was simulated. In order to correct for breathing motion, a motion-corrected image reconstruction scheme was used and a Toft's model was fit to the DCE data to obtain quantitative DCE-MRI parameters. Utilising the ground truth motion information, the dependency of quantitative DCE-MR images on the accuracy of the motion estimation was evaluated. We demonstrated that respiratory motion had to be available with an average accuracy of at least the spatial resolution of the DCE-MR images in order to ensure an improvement in lesions visualisation and quantification compared to no motion correction. The proposed framework provides a valuable tool with a wide range of scientific PET and MR applications and will be available as part of the open-source project Synergistic Image Reconstruction Framework (SIRF).

PET motion correction in context of integrated PET/MR: Current techniques, limitations, and future projections.

Patient motion is an important consideration in modern PET image reconstruction. Advances in PET technology mean motion has an increasingly important influence on resulting image quality. Motion-induced artifacts can have adverse effects on clinical outcomes, including missed diagnoses and oversized radiotherapy treatment volumes. This review aims to summarize the wide variety of motion correction techniques available in PET and combined PET/CT and PET/MR, with a focus on the latter. A general framework for the motion correction of PET images is presented, consisting of acquisition, modeling, and correction stages. Methods for measuring, modeling, and correcting motion and associated artifacts, both in literature and commercially available, are presented, and their relative merits are contrasted. Identified limitations of current methods include modeling of aperiodic and/or unpredictable motion, attaining adequate temporal resolution for motion correction in dynamic kinetic modeling acquisitions, and maintaining availability of the MR in PET/MR scans for diagnostic acquisitions. Finally, avenues for future investigation are discussed, with a focus on improvements that could improve PET image quality, and that are practical in the clinical environment.