Semi-automated construction of patient individualised clinical target volumes for radiotherapy treatment of glioblastoma utilising diffusion tensor decomposition maps.

OBJECTIVES: Glioblastoma multiforme (GBM) is a highly infiltrative primary brain tumour with an aggressive clinical course. Diffusion tensor imaging (DT-MRI or DTI) is a recently developed technique capable of visualising subclinical tumour spread into adjacent brain tissue. Tensor decomposition through p and q maps can be used for planning of treatment. Our objective was to develop a tool to automate the segmentation of DTI decomposed p and q maps in GBM patients in order to inform construction of radiotherapy target volumes. METHODS: Chan-Vese level set model is applied to segment the p map using the q map as its initial starting point. The reason of choosing this model is because of the robustness of this model on either conventional MRI or only DTI. The method was applied on a data set consisting of 50 patients having their gross tumour volume delineated on their q map and Chan-Vese level set model uses these superimposed masks to incorporate the infiltrative edges. RESULTS: The expansion of tumour boundary from q map to p map is clearly visible in all cases and the Dice coefficient (DC) showed a mean similarity of 74% across all 50 patients between the manually segmented ground truth p map and the level set automatic segmentation. CONCLUSION: Automated segmentation of the tumour infiltration boundary using DTI and tensor decomposition is possible using Chan-Vese level set methods to expand q map to p map. We have provided initial validation of this technique against manual contours performed by experienced clinicians. ADVANCES IN KNOWLEDGE: This novel automated technique to generate p maps has the potential to individualise radiation treatment volumes and act as a decision support tool for the treating oncologist.This study was funded by an NIHR Clinician Scientist Fellowship for a SJP, project reference NIHR/CS/009/011. The research was supported by the NIHR Brain Injury MedTech Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge and the NIHR Cambridge BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Also, RR is supported as part of the CRUK-funded PRaM-GBM study (C9216/A19732). NVIDIA Corporation is gratefully acknowledged for the donation of two Titan X GPUs for our research

Towards Quantitative Evaluation of Tissue Absorption Coefficients Using Light Fluence Correction in Optoacoustic Tomography.

Optoacoustic tomography is a fast developing imaging modality, combining the high contrast available from optical excitation of tissue with the high resolution and penetration depth of ultrasound detection. Light is subject to both absorption and scattering when traveling through tissue; adequate knowledge of tissue optical properties and hence the spatial fluence distribution is required to create an optoacoustic image that is directly proportional to chromophore concentrations at all depths. Using data from a commercial multispectral optoacoustic tomography (MSOT) system, we implemented an iterative optimization for fluence correction based on a finite-element implementation of the delta-Eddington approximation to the Radiative Transfer Equation (RTE). We demonstrate a linear relationship between the image intensity and absorption coefficients across multiple wavelengths and depths in phantoms. We also demonstrate improved feature visibility and spectral recovery at depth in phantoms and with in vivo measurements, suggesting our approach could in the future enable quantitative extraction of tissue absorption coefficients in biological tissue.This work was funded by the EPSRC-CRUK Cancer Imaging Centre in Cambridge and Manchester (C197/A16465); CRUK (C47594/A16267, C14303/A17197); EU FP7 framework programme (FP7-PEOPLE-2013-CIG-630729) and the University of Cambridge EPSRC Impact Acceleration Account via a Partnership Development Award.This is the author accepted manuscript. The final version is available from the Institute of Electrical and Electronics Engineers via http://dx.doi.org/10.1109/TMI.2016.260719

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements