Science granting councils in Sub-Saharan Africa: trends and tensions

This article documents recent trends in science funding support in Sub-Saharan Africa (SSA). We analyse these trends at the SSA regional level alongside a summary of four case studies of science funding in four Science Granting Councils (SGCs) in East Africa. Our findings support the literature on science funding in SSA regarding low levels of funding, cross-country engagement, and the need for capacity building. However, we also find there are tensions among funding and policy actors around the perceived ways in which investment in science will benefit society. We argue that the narratives and logics of science funders and their roots in ‘Republic of Science’ vs. ‘Embedded Autonomy’ rationales for SGC activity must be more transparent to enable critical engagement with the ideas being used to justify spending

Pupillary Responses to High-Irradiance Blue Light Correlate with Glaucoma Severity

PurposeTo evaluate whether a chromatic pupillometry test can be used to detect impaired function of intrinsically photosensitive retinal ganglion cells (ipRGCs) in patients with primary open-angle glaucoma (POAG) and to determine if pupillary responses correlate with optic nerve damage and visual loss.DesignCross-sectional study.ParticipantsOne hundred sixty-one healthy controls recruited from a community polyclinic (55 men; 151 ethnic Chinese) and 40 POAG patients recruited from a glaucoma clinic (22 men; 35 ethnic Chinese) 50 years of age or older.MethodsSubjects underwent monocular exposure to narrowband blue light (469 nm) or red light (631 nm) using a modified Ganzfeld dome. Each light stimulus was increased gradually over 2 minutes to activate sequentially the rods, cones, and ipRGCs that mediate the pupillary light reflex. Pupil diameter was recorded using an infrared pupillography system.Main Outcome MeasuresPupillary responses to blue light and red light were compared between control subjects and those with POAG by constructing dose-response curves across a wide range of corneal irradiances (7–14 log photons/cm2 per second). In patients with POAG, pupillary responses were evaluated relative to standard automated perimetry testing (Humphrey Visual Field [HVF]; Carl Zeiss Meditec, Dublin, CA) and scanning laser ophthalmoscopy parameters (Heidelberg Retinal Tomography [HRT]; Heidelberg Engineering, Heidelberg, Germany).ResultsThe pupillary light reflex was reduced in patients with POAG only at higher irradiance levels, corresponding to the range of activation of ipRGCs. Pupillary responses to high-irradiance blue light associated more strongly with disease severity compared with responses to red light, with a significant linear correlation observed between pupil diameter and HVF mean deviation (r = −0.44; P = 0.005) as well as HRT linear cup-to-disc ratio (r = 0.61; P < 0.001) and several other optic nerve head parameters.ConclusionsIn glaucomatous eyes, reduced pupillary responses to high-irradiance blue light were associated with greater visual field loss and optic disc cupping. In POAG, a short chromatic pupillometry test that evaluates the function of ipRGCs can be used to estimate the degree of damage to retinal ganglion cells that mediate image-forming vision. This approach could prove useful in detecting glaucoma

Brain and Head-and-Neck MRI in Immobilization Mask: A Practical Solution for MR-Only Radiotherapy

In brain/head-and-neck radiotherapy (RT), thermoplastic immobilization masks guarantee reproducible patient positioning in treatment position between MRI, CT, and irradiation. Since immobilization masks do not fit in the diagnostic MR head/head-and-neck coils, flexible surface coils are used for MRI imaging in clinical practice. These coils are placed around the head/neck, in contact with the immobilization masks. However, the positioning of these flexible coils is technician dependent, thus leading to poor image reproducibility. Additionally, flexible surface coils have an inferior signal-to-noise-ratio (SNR) compared to diagnostic coils. The aim of this work was to create a new immobilization setup which fits into the diagnostic MR coils in order to enhance MR image quality and reproducibility. For this purpose, a practical immobilization setup was constructed. The performances of the standard clinical and the proposed setups were compared with four tests: SNR, image quality, motion restriction, and reproducibility of inter-fraction subject positioning. The new immobilization setup resulted in 3.4 times higher SNR values on average than the standard setup, except directly below the flexible surface coils where similar SNR was observed. Overall, the image quality was superior for brain/head-and-neck images acquired with the proposed RT setup. Comparable motion restriction in feet-head/left-right directions (maximum motion ≈1 mm) and comparable inter-fraction repositioning accuracy (mean inter-fraction movement 1 ± 0.5 mm) were observed for the standard and the new setup

Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy.

To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time adaptation, motion must be quickly estimated with low latency. The motion estimate is used to adapt the radiation beam to the current anatomy, yielding a more conformal dose distribution. As the MR acquisition is the largest component of latency, deep learning (DL) may reduce the total latency by enabling much higher undersampling factors compared to conventional reconstruction and motion estimation methods. The benefit of DL on image reconstruction and motion estimation was investigated for obtaining accurate deformation vector fields (DVFs) with high temporal resolution and minimal latency. 2D cine MRI acquired at 1.5 T from 135 abdominal cancer patients were retrospectively included in this study. Undersampled radial golden angle acquisitions were retrospectively simulated. DVFs were computed using different combinations of conventional- and DL-based methods for image reconstruction and motion estimation, allowing a comparison of four approaches to achieve real-time motion estimation. The four approaches were evaluated based on the end-point-error and root-mean-square error compared to a ground-truth optical flow estimate on fully-sampled images, the structural similarity (SSIM) after registration and time necessary to acquire k-space, reconstruct an image and estimate motion. The lowest DVF error and highest SSIM were obtained using conventional methods up to [Formula: see text]. For undersampling factors [Formula: see text], the lowest DVF error and highest SSIM were obtained using conventional image reconstruction and DL-based motion estimation. We have found that, with this combination, accurate DVFs can be obtained up to [Formula: see text] with an average root-mean-square error up to 1 millimeter and an SSIM greater than 0.8 after registration, taking 60 milliseconds. High-quality 2D DVFs from highly undersampled k-space can be obtained with a high temporal resolution with conventional image reconstruction and a deep learning-based motion estimation approach for real-time adaptive MRI-guided radiotherapy

Nuts and bolts of 4D-MRI for radiotherapy

Magnetic resonance imaging (MRI) is increasingly being used in the radiotherapy workflow because of its superior soft tissue contrast and high flexibility in contrast. In addition to anatomical and functional imaging, MRI can also be used to characterize the physiologically induced motion of both the tumor and organs-at-risk. Respiratory-correlated 4D-MRI has gained large interest as an alternative to 4D-CT for the characterization of respiratory motion throughout the thorax and abdomen. These 4D-MRI data sets consist of three spatial dimensions and the respiratory phase or amplitude over the fourth dimension (opposed to time-resolved 4D-MRI that represents time in the fourth dimension). Over the last 15 years numerous methods have been presented in literature. This review article provides a comprehensive overview of the various 4D-MRI techniques, and describes the differences in MRI data acquisition and 4D data set generation from a methodological point of view. The current status and future perspective of these techniques are highlighted, and the requirements for safe introduction into the clinic (e.g. method validation) are discussed

Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T

Compared with conventional MRI, diffusion tensor imaging (DTI) is more prone to thermal noise and motion. Optimized sampling schemes have been proposed that reduce the propagation of noise. At 3 T, however, motion may play a more dominant role than noise. Although the effects of noise at 3 T are less compared with 1.5 T because of the higher signal-to-noise ratio, motion is independent of field strength and will persist. To improve the reliability of clinical DTI at 3 T, it is important to know to what extent noise and motion contribute to the uncertainties of the DTI indices. In this study, the effects of noise- and motion-related signal uncertainties are disentangled using in vivo measurements and computer simulations. For six clinically standard available sampling schemes, the reproducibility was assessed in vivo, with and without motion correction applied. Additionally, motion and noise simulations were performed to determine the relative contributions of motion and noise to the uncertainties of the mean diffusivity (MD) and fractional anisotropy (FA). It is shown that the contributions of noise and motion are of the same order of magnitude at 3 T. Similar to the propagation of noise, the propagation of motion-related signal perturbations is also influenced by the choice of sampling scheme. Sampling schemes with only six diffusion directions demonstrated a lower reproducibility compared with schemes with 15 and 32 directions and feature a positive bias for the FA in relatively isotropic tissue. Motion correction helps improving the precision and accuracy of DTI indices

Assessing and minimizing the effects of noise and motion in clinical DTI at 3 T

\u3cp\u3eCompared with conventional MRI, diffusion tensor imaging (DTI) is more prone to thermal noise and motion. Optimized sampling schemes have been proposed that reduce the propagation of noise. At 3 T, however, motion may play a more dominant role than noise. Although the effects of noise at 3 T are less compared with 1.5 T because of the higher signal-to-noise ratio, motion is independent of field strength and will persist. To improve the reliability of clinical DTI at 3 T, it is important to know to what extent noise and motion contribute to the uncertainties of the DTI indices. In this study, the effects of noise- and motion-related signal uncertainties are disentangled using in vivo measurements and computer simulations. For six clinically standard available sampling schemes, the reproducibility was assessed in vivo, with and without motion correction applied. Additionally, motion and noise simulations were performed to determine the relative contributions of motion and noise to the uncertainties of the mean diffusivity (MD) and fractional anisotropy (FA). It is shown that the contributions of noise and motion are of the same order of magnitude at 3 T. Similar to the propagation of noise, the propagation of motion-related signal perturbations is also influenced by the choice of sampling scheme. Sampling schemes with only six diffusion directions demonstrated a lower reproducibility compared with schemes with 15 and 32 directions and feature a positive bias for the FA in relatively isotropic tissue. Motion correction helps improving the precision and accuracy of DTI indices.\u3c/p\u3

MRI B 0 homogeneity and geometric distortion with continuous linac gantry rotation on an Elekta Unity MR-linac

This work aimed to quantify any principal magnetic field (B 0) inhomogeneity and changes in MR image geometric distortion with continuous linac gantry rotation on an Elekta Unity MR-linac. This situation occurs for around a second between treatment beams during current image guided radiotherapy treatment and would occur frequently in foreseeable real-time adaptive radiotherapy treatment. Pixel by pixel maps of B 0 inhomogeneity were obtained via repeated high temporal resolution pulse sequences with the linac gantry static at 36 gantry angles spaced ten degrees apart, and in continuous rotation at both 1 and 2 rpm. Individual B 0 maps were subtracted from average maps across all data and the residual peak to peak inhomogeneity was calculated for each. The bulk geometric shift and change in physical extent of a 10 cm diameter spherical flood phantom during continuous linac gantry rotation at 1 and 2 rpm was compared to the static gantry case for two pulse sequences: the real-time clinical monitoring bFFE sequence and a non-clinical EPI sequence, chosen for its susceptibility to geometric distortion. The peak to peak inhomogeneity in the deviation-from-average ppm maps, plotted against gantry angle with the gantry in continuous rotation at 1 and 2 rpm were negligibly different from equivalent data obtained with the gantry static. The real-time clinical monitoring pulse sequence was shown to give negligible geometric distortion during continuous gantry motion, whilst a non-clinical EPI sequence showed bulk shifts of the order of one pixel and gantry angle dependent changes in extent, demonstrating the sensitivity of the chosen method. MR imaging on the Elekta Unity MR-Linac with the gantry in continuous motion is negligibly different from the static gantry case with current clinical pulse sequences. Real-time tracking and treatment plan adaptation using MR images obtained with the linac gantry in motion is possible

MRI B 0 homogeneity and geometric distortion with continuous linac gantry rotation on an Elekta Unity MR-linac

This work aimed to quantify any principal magnetic field (B 0) inhomogeneity and changes in MR image geometric distortion with continuous linac gantry rotation on an Elekta Unity MR-linac. This situation occurs for around a second between treatment beams during current image guided radiotherapy treatment and would occur frequently in foreseeable real-time adaptive radiotherapy treatment. Pixel by pixel maps of B 0 inhomogeneity were obtained via repeated high temporal resolution pulse sequences with the linac gantry static at 36 gantry angles spaced ten degrees apart, and in continuous rotation at both 1 and 2 rpm. Individual B 0 maps were subtracted from average maps across all data and the residual peak to peak inhomogeneity was calculated for each. The bulk geometric shift and change in physical extent of a 10 cm diameter spherical flood phantom during continuous linac gantry rotation at 1 and 2 rpm was compared to the static gantry case for two pulse sequences: the real-time clinical monitoring bFFE sequence and a non-clinical EPI sequence, chosen for its susceptibility to geometric distortion. The peak to peak inhomogeneity in the deviation-from-average ppm maps, plotted against gantry angle with the gantry in continuous rotation at 1 and 2 rpm were negligibly different from equivalent data obtained with the gantry static. The real-time clinical monitoring pulse sequence was shown to give negligible geometric distortion during continuous gantry motion, whilst a non-clinical EPI sequence showed bulk shifts of the order of one pixel and gantry angle dependent changes in extent, demonstrating the sensitivity of the chosen method. MR imaging on the Elekta Unity MR-Linac with the gantry in continuous motion is negligibly different from the static gantry case with current clinical pulse sequences. Real-time tracking and treatment plan adaptation using MR images obtained with the linac gantry in motion is possible

3D multi-slab diffusion-weighted readout-segmented EPI with real-time cardiac-reordered k-space acquisition

Purpose: The aim of this study was to develop, implement, and demonstrate a three‐dimensional (3D) extension of the readout‐segmented echo‐planar imaging (rs‐EPI) sequence for diffusion imaging. Theory and Methods: Potential k‐space acquisition schemes were assessed by simulating their associated spatial point spread functions. Motion‐induced phase artifacts were also simulated to test navigator corrections and a real‐time reordering of the k‐space acquisition relative to the cardiac cycle. The cardiac reordering strategy preferentially chooses readout segments closer to the center of 3D k‐space during diastole. Motion‐induced phase artifacts were quantified by calculating the voxel‐wise temporal variation in a set of repeated diffusion‐weighted acquisitions. Based on the results of these simulations, a 2D navigated multi‐slab rs‐EPI sequence with real‐time cardiac reordering was implemented. The multi‐slab implementation enables signal‐to‐noise ratio‐optimal repetition times of 1–2 s. Results: Cardiac reordering was validated in simulations and in vivo using the multi‐slab rs‐EPI sequence. In comparisons with standard k‐space acquisitions, cardiac reordering was shown to reduce the variability due to motion‐induced phase artifacts by 30–50%. High‐resolution diffusion tensor imaging data acquired with the cardiac‐reordered multi‐slab rs‐EPI sequence are presented. Conclusion: A 3D multi‐slab rs‐EPI sequence with cardiac reordering has been demonstrated in vivo and is shown to provide high‐quality 3D diffusion‐weighted data sets