Scientific Data

SignificanceFunctional near-infrared spectroscopy (fNIRS) presents an opportunity to study human brains in every-day activities and environments. However, achieving robust measurements under such dynamic condition remains a significant challenge. AimThe modular optical brain imaging (MOBI) system is designed to enhance optode-to-scalp coupling and provide real-time probe 3-D shape estimation to improve the use of fNIRS in everyday conditions. ApproachThe MOBI system utilizes a bendable and lig...

While recent advances in intracortical brain-computer interfaces (iBCI) have demonstrated the ability to restore motor and communication functions, such demonstrations have generally been confined to controlled experimental settings and have required bulky laboratory hardware. Here, we developed and evaluated a self-contained portable iBCI that enabled the user to interact with various computer programs. The iBCI, which weighs 1.5 kg, consists of digital headstages, a small signal processing hub...

Oxford COVID-19 Database (OxCOVID19 Database) is a comprehensive source of information related to the COVID-19 pandemic. This relational database contains time-series data on epidemiology, government responses, mobility, weather and more across time and space for all countries at the national level, and for more than 50 countries at the regional level. It is curated from a variety of (wherever available) official sources. Its purpose is to facilitate the analysis of the spread of SARS-CoV-2 viru...

SignificanceWe present NIRDuino: an Open-source Android(R)-configurable, modular, and Bluetooth-enabled fNIRS system that allows researchers to perform neuroimaging studies with up to eight emitters and 16 detectors. The complete system (including Android tablet) can be assembled for less than $1000, and the emitters and detectors can be arranged in any configuration to achieve the desired short and long channels required for their study. AimThe system has been designed with non-engineers in mi...

Spectral CT has been increasingly implemented clinically for its better characterization and quantification of materials through its multi-energy results. It also facilitates calculation of physical density utilizing the Alvarez-Macovski model without approximations. These spectral physical density quantifications allow for non-invasive mass measurements and temperature evaluations by manipulating the definition of physical density and thermal volumetric expansion, respectively. To develop the m...

PurposeRobust positron emission tomography (PET) research increasingly requires reliable ground-truth activity distributions, yet clinical data and physical phantoms cannot provide them fully. This work introduces MuPET (multiphysics PET), a computational framework that bridges mass-transport physics simulation with image domain noise modeling to generate realistic, synthetic PET images. MethodsTracer transport and radioactive decay within a custom phantom geometry were modeled via decay diffus...

IntroductionAutomatic whole brain and lesion segmentation at 7T presents challenges, primarily from bias fields and susceptibility artifacts. Recent advances in segmentation methods, namely using atlas-free and multi-contrast (for example, using T1-weighted, T2-weighted, fluid attenuated inversion recovery or FLAIR images) can enhance segmentation performance, however perfect registration at high fields remain a challenge primarily from distortion effects. We sought to use deep-learning algorith...

Globally, there is a lack of consolidation and thus sharing of critical mortality estimates which can serve as an early warning of the severity of a humanitarian crisis. This lack of a comprehensive view may mask critical situations, and impact on which crises are more measured and visible to the humanitarian community. This ultimately affects the allocation of scarce humanitarian resources. Somalia is a country marked by recurrent drought, armed conflict, food insecurity and malnutrition. To f...

We present the design and implementation of a data curation framework to generate a large-scale clinical brain imaging dataset suitable for artificial intelligence (AI) enabled image analysis, accessible through the Brain Health Data (BHD) initiative. The raw data accessible through the BHD includes approximately 417K magnetic resonance imaging (MRI) and 846K computerized tomography (CT) head scans, linked electronic health records (EHRs), and associated free-text imaging reports from clinical p...

PurposeParotid whole-gland magnetic resonance (MR) T1 intensity, thresholded at the 90th percentile (T1 P90), has been previously reported to be a candidate MR imaging biomarker (MR-IBM) for improved prediction of xerostomia development after radiotherapy. Although P90 was previously derived from the parotid glands of T1-weighted MRI, in this study, we aim to validate P90 in an external cohort using fat only images reconstructed from a T1 Dixon MRI sequence, as well as determining alternative T1...

ObjectiveTo establish the local diagnostic reference levels (LDRLs) for trunk multi-slice CT (MSCT) examinations in the Gaza Strip, Palestine. MethodA cross-sectional study of adult oncology patients undergoing trunk MSCT at two governmental hospitals in Gaza Strip; Al Shifa Medical Complex (SMC) and Al Aqsa Hospital (AMH), using an adapted dose survey booklet. Data collected from July 2019 to March 2020 included patient characteristics, volumetric CT dose index (CTDIvol) and dose length produc...

ObjectivesTo determine the utility of low-flip angle "black bone" magnetic resonance imaging (MRI) for cortical mandibular bone assessment by comparing interdentium cortical measurements and inter-observer morphometric variability in relation to computed tomography (CT). MethodsQuantification of cortical mandible bone width was performed as per Hamada et al. at 15 cross-sectional interdentium locations on pre-treatment black bone MRI and CT for 15 oropharyngeal cancer patients, with inter-obser...

IntroductionDiffusion-weighted imaging (DWI) on MRI-linear accelerator (MR-linac) systems can potentially be used for monitoring treatment response and adaptive radiotherapy in head and neck cancers (HNC) but requires extensive validation. We perform technical validation to compare six total DWI sequences on an MR-linac and MR simulator (MR sim) in patients, volunteers, and phantoms. MethodsTen human papillomavirus-positive oropharyngeal cancer patients and ten volunteers underwent DWI on a 1.5...

BackgroundMuch of the worlds historical and current epidemiological data remains locked in static formats, such as PDF situation reports or image-based surveillance bulletins. Recovering this data for spatial analysis typically requires proprietary software (e.g., ArcGIS) or laborious manual entry, which is prone to transcription errors. MethodsI developed Map Liberator, an open-source application built in R and Shiny. It provides a split-screen digitisation interface that allows users to overl...

Background and PurposeTo detect changes in apparent diffusion coefficient (ADC) values during radiation therapy for biological image-guided adaptive radiation therapy, the variability in ADC must be characterized. We evaluated the reproducibility of ADC values in head and neck cancers on a 1.5T MR-linac. Methods39 head and neck cancer patients (36 primary tumors, 55 lymph nodes) were imaged with echo-planar imaging diffusion-weighted MRI on a 1.5T MR-linac at two time points before the start of...

DRLs for CT part used in PET/CT examinations are limited. The aim was to execute the second phase of the national DRL for CT part of PET/CT imaging operating in KW, in support of optimisation and dose reduction as imaging technology is advancing. In this multicentre collaborative PET centers (No:8) audit, data collection was restricted to the adult oncology patients due to a limited number of the other studies and also due to the National MOH Ethical Committee recommendation. The CTDIvol, DLP an...

Access to Magnetic Resonance Imaging (MRI) across developing countries from being prohibitive to scarcely available. For example, eleven countries in Africa have no scanners. One critical limitation is the absence of skilled manpower required for MRI usage. Some of these challenges can be mitigated using autonomous MRI (AMRI) operation. In this work, we demonstrate AMRI to simplify MRI workflow by separating the required intelligence and user interaction from the acquisition hardware. AMRI consi...

PurposeSingle-energy computed tomography (CT) often suffers from poor contrast, yet it remains critical for effec-tive radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) x-ray sources and thus already possess the hardware needed for dual-energy (DE) CT. There exists an unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts. ApproachA toy model comprising a single-line integral through a two-mater...

Brain atlases and templates are at the heart of neuroimaging analyses, for which they facilitate multimodal registration, enable group comparisons and provide anatomical reference. However, as atlas-based approaches rely on correspondence mapping between images they perform poorly in the presence of structural pathology. Whilst several strategies exist to overcome this problem, their performance is often dependent on the type, size and homogeneity of any lesions present. We therefore propose a n...

Gamma Knife (GK) radiosurgery is a non-invasive treatment modality which allows single fraction delivery of focused radiation to one or more brain targets. Treatment planning mostly involves manual placement and shaping of shots to conform the prescribed dose to a surgical target. This process can be time consuming and labour intensive. An automated method is needed to determine the optimum combination of treatment parameters to decrease planning time and chance for operator-related error. Recen...