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Use of light-weight foaming polylactic acid as a lung-equivalent material in 3D printed phantomsNARA Subscribed
The 3D printing of lung-equivalent phantoms using conventional polylactic acid (PLA) filaments requires the use of low in-fill printing densities, which can produce substantial density heterogeneities from the air gaps within the resulting prints. Light-weight foaming PLA filaments produce microscopic air bubbles when heated to 3D printing temperatures. In this study, the expansion of foaming PLA filament was characterised for...
A structure-based gamma evaluation method for identifying clinically relevant dose differences in organs at riskNARA Subscribed
Gamma evaluation is currently the most widely used dose comparison method for patient specific quality assurance (PSQA). However, existing methods for normalising the dose difference, using either the dose at the global maximum dose point or at each local point, can respectively lead to under- and over-sensitivity to dose differences in organ-at-risk structures. This may be of concern for plan evaluation from clinical perspect...
Targeting de novo loss-of-function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes ProjectNARA Subscribed
Background Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient’s phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP...
Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severityNARA Subscribed
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the pr...
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