Towards the production of radiotherapy treatment shells on 3D printers using data derived from DICOM CT and MRI: preclinical feasibility studies

Background: Immobilisation for patients undergoing brain or head and neck radiotherapy is achieved using perspex or thermoplastic devices that require direct moulding to patient anatomy. The mould room visit can be distressing for patients and the shells do not always fit perfectly. In addition the mould room process can be time consuming. With recent developments in three-dimensional (3D) printing technologies comes the potential to generate a treatment shell directly from a computer model of a patient. Typically, a patient requiring radiotherapy treatment will have had a computed tomography (CT) scan and if a computer model of a shell could be obtained directly from the CT data it would reduce patient distress, reduce visits, obtain a close fitting shell and possibly enable the patient to start their radiotherapy treatment more quickly. Purpose: This paper focuses on the first stage of generating the front part of the shell and investigates the dosimetric properties of the materials to show the feasibility of 3D printer materials for the production of a radiotherapy treatment shell. Materials and methods: Computer algorithms are used to segment the surface of the patient’s head from CT and MRI datasets. After segmentation approaches are used to construct a 3D model suitable for printing on a 3D printer. To ensure that 3D printing is feasible the properties of a set of 3D printing materials are tested. Conclusions: The majority of the possible candidate 3D printing materials tested result in very similar attenuation of a therapeutic radiotherapy beam as the Orfit soft-drape masks currently in use in many UK radiotherapy centres. The costs involved in 3D printing are reducing and the applications to medicine are becoming more widely adopted. In this paper we show that 3D printing of bespoke radiotherapy masks is feasible and warrants further investigation

MicroRNA-155 is induced during the macrophage inflammatory response

The mammalian inflammatory response to infection involves the induction of several hundred genes, a process that must be carefully regulated to achieve pathogen clearance and prevent the consequences of unregulated expression, such as cancer. Recently, microRNAs (miRNAs) have emerged as a class of gene expression regulators that has also been linked to cancer. However, the relationship between inflammation, innate immunity, and miRNA expression is just beginning to be explored. In the present study, we use microarray technology to identify miRNAs induced in primary murine macrophages after exposure to polyriboinosinic:polyribocytidylic acid or the cytokine IFN-{beta}. miR-155 was the only miRNA of those tested that was substantially up-regulated by both stimuli. It also was induced by several Toll-like receptor ligands through myeloid differentiation factor 88- or TRIF-dependent pathways, whereas up-regulation by IFNs was shown to involve TNF-{alpha} autocrine signaling. Pharmacological inhibition of the kinase JNK blocked induction of miR-155 in response to either polyriboinosinic:polyribocytidylic acid or TNF-{alpha}, suggesting that miR-155-inducing signals use the JNK pathway. Together, these findings characterize miR-155 as a common target of a broad range of inflammatory mediators. Importantly, because miR-155 is known to function as an oncogene, these observations identify a potential link between inflammation and cancer

Adversarial AI Testcases for Maritime Autonomous Systems

Contemporary maritime operations such as shipping are a vital component constituting global trade and defence. The evolution towards maritime autonomous systems, often providing significant benefits (e.g., cost, physical safety), requires the utilisation of artificial intelligence (AI) to automate the functions of a conventional crew. However, unsecured AI systems can be plagued with vulnerabilities naturally inherent within complex AI models. The adversarial AI threat, primarily only evaluated in a laboratory environment, increases the likelihood of strategic adversarial exploitation and attacks on mission-critical AI, including maritime autonomous systems. This work evaluates AI threats to maritime autonomous systems in situ. The results show that multiple attacks can be used against real-world maritime autonomous systems with a range of lethality. However, the effects of AI attacks vary in a dynamic and complex environment from that proposed in lower entropy laboratory environments. We propose a set of adversarial test examples and demonstrate their use, specifically in the marine environment. The results of this paper highlight security risks and deliver a set of principles to mitigate threats to AI, throughout the AI lifecycle, in an evolving threat landscape.</jats:p

Some estimates of Wang-Yau quasilocal energy

Given a spacelike 2-surface $\Sigma$ in a spacetime $N$ and a constant future timelike unit vector $T_0$ in $\R^{3,1}$, we derive upper and lower estimates of Wang-Yau quasilocal energy $E(\Sigma, X, T_0)$ for a given isometric embedding $X$ of $\Sigma$ into a flat 3-slice in $\R^{3,1}$. The quantity $E(\Sigma, X, T_0)$ itself depends on the choice of $X$, however the infimum of $E(\Sigma, X, T_0)$ over $T_0$ does not. In particular, when $\Sigma$ lies in a time symmetric 3-slice in $N$ and has nonnegative Brown-York quasilocal mass \mby(\Sigma), our estimates show that $\inf\limits_{T_0}E(\Sigma, X, T_0)$ equals \mby (\Sigma). We also study the spatial limit of $\inf\limits_{T_0}E(S_r,X_r,T_0)$, where $S_r$ is a large coordinate sphere in a fixed end of an asymptotically flat initial data set $(M, g, p)$ and $X_r$ is an isometric embeddings of $S_r$ into $\mathbb{R}^3 \subset \mathbb{R}^{3,1}$. We show that if $(M, g, p)$ has future timelike ADM energy-momentum, then $\lim\limits_{r\to\infty}\inf\limits_{T_0}E(S_r,X_r,T_0)$ equals the ADM mass of $(M, g, p)$.Comment: 17 page

Multilinear Wavelets: A Statistical Shape Space for Human Faces

We present a statistical model for $3$D human faces in varying expression, which decomposes the surface of the face using a wavelet transform, and learns many localized, decorrelated multilinear models on the resulting coefficients. Using this model we are able to reconstruct faces from noisy and occluded $3$D face scans, and facial motion sequences. Accurate reconstruction of face shape is important for applications such as tele-presence and gaming. The localized and multi-scale nature of our model allows for recovery of fine-scale detail while retaining robustness to severe noise and occlusion, and is computationally efficient and scalable. We validate these properties experimentally on challenging data in the form of static scans and motion sequences. We show that in comparison to a global multilinear model, our model better preserves fine detail and is computationally faster, while in comparison to a localized PCA model, our model better handles variation in expression, is faster, and allows us to fix identity parameters for a given subject.Comment: 10 pages, 7 figures; accepted to ECCV 201

Low-Cost On-Chip Clock Jitter Measurement Scheme

In this paper, we present a low-cost, on-chip clock jitter digital measurement scheme for high performance microprocessors. It enables in situ jitter measurement during the test or debug phase. It provides very high measurement resolution and accuracy, despite the possible presence of power supply noise (representing a major source of clock jitter), at low area and power costs. The achieved resolution is scalable with technology node and can in principle be increased as much as desired, at low additional costs in terms of area overhead and power consumption. We show that, for the case of high performance microprocessors employing ring oscillators (ROs) to measure process parameter variations (PPVs), our jitter measurement scheme can be implemented by reusing part of such ROs, thus allowing to measure clock jitter with a very limited cost increase compared with PPV measurement only, and with no impact on parameter variation measurement resolution

Gender dimorphism and age of onset in malignant peripheral nerve sheath tumor preclinical models and human patients.

BackgroundGender-based differences in disease onset in murine models of malignant peripheral nerve sheath tumor (MPNST) and in patients with Neurofibromatosis type-1-(NF-1)-associated or spontaneous MPNST has not been well studied.MethodsForty-three mGFAP-Cre+;Ptenloxp/+;LSL-K-rasG12D/+ mice were observed for tumor development and evaluated for gender disparity in age of MPNST onset. Patient data from the prospectively collected UCLA sarcoma database (1974-2011, n = 113 MPNST patients) and 39 published studies on MPNST patients (n = 916) were analyzed for age of onset differences between sexes and between NF-1 and spontaneous MPNST patients.ResultsOur murine model showed gender-based differences in MPNST onset, with males developing MPNST significantly earlier than females (142 vs. 162 days, p = 0.015). In the UCLA patient population, males also developed MPNST earlier than females (median age 35 vs. 39.5 years, p = 0.048). Patients with NF-1-associated MPNST had significantly earlier age of onset compared to spontaneous MPNST (median age 33 vs. 39 years, p = 0.007). However, expanded analysis of 916 published MPNST cases revealed no significant age difference in MPNST onset between males and females. Similar to the UCLA dataset, patients with NF-1 developed MPNST at a significantly younger age than spontaneous MPNST patients (p &lt; 0.0001, median age 28 vs. 41 years) and this disparity was maintained across North American, European, and Asian populations.ConclusionsAlthough our preclinical model and single-institution patient cohort show gender dimorphism in MPNST onset, no significant gender disparity was detected in the larger MPNST patient meta-dataset. NF-1 patients develop MPNST 13 years earlier than patients with spontaneous MPNST, with little geographical variance

Plasma cholesterol levels and brain development in preterm newborns.

BackgroundTo assess whether postnatal plasma cholesterol levels are associated with microstructural and macrostructural regional brain development in preterm newborns.MethodsSixty preterm newborns (born 24-32 weeks gestational age) were assessed using MRI studies soon after birth and again at term-equivalent age. Blood samples were obtained within 7 days of each MRI scan to analyze for plasma cholesterol and lathosterol (a marker of endogenous cholesterol synthesis) levels. Outcomes were assessed at 3 years using the Bayley Scales of Infant Development, Third Edition.ResultsEarly plasma lathosterol levels were associated with increased axial and radial diffusivities and increased volume of the subcortical white matter. Early plasma cholesterol levels were associated with increased volume of the cerebellum. Early plasma lathosterol levels were associated with a 2-point decrease in motor scores at 3 years.ConclusionsHigher early endogenous cholesterol synthesis is associated with worse microstructural measures and larger volumes in the subcortical white matter that may signify regional edema and worse motor outcomes. Higher early cholesterol is associated with improved cerebellar volumes. Further work is needed to better understand how the balance of cholesterol supply and endogenous synthesis impacts preterm brain development, especially if these may be modifiable factors to improve outcomes

Spin Waves in Detwinned BaFe2_2As2_2

Understanding magnetic interactions in the parent compounds of high-temperature superconductors forms the basis for determining their role for the mechanism of superconductivity. For parent compounds of iron pnictide superconductors such as $A$Fe$_2$As$_2$ ($A=$ Ba, Ca, Sr), although spin excitations have been mapped out throughout the entire Brillouin zone (BZ), measurements were carried out on twinned samples and did not allow for a conclusive determination of the spin dynamics. Here we use inelastic neutron scattering to completely map out spin excitations of $\sim$100\% detwinned BaFe$_2$As$_2$. By comparing observed spectra with theoretical calculations, we conclude that the spin excitations can be well described by an itinerant model with important contributions from electronic correlations.Comment: 6 pages, 4 figures, with supplemental materia