Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level classification by using the quantile function. The quantile function provides a more complete description of the heterogeneity within each image, improving image-level classification. We also adapt image augmentation to the MI framework by randomly selecting cropped regions on which to apply MI aggregation during each epoch of training. This provides a mechanism to study the importance of MI learning. We validate our method on five different classification tasks for breast tumor histology and provide a visualization method for interpreting local image classifications that could lead to future insights into tumor heterogeneity

Deciphering intratumor heterogeneity and temporal acquisition of driver events to refine precision medicine

The presence of multiple subclones within tumors mandates understanding of longitudinal and spatial subclonal dynamics. Resolving the spatial and temporal heterogeneity of subclones with cancer driver events may offer insight into therapy response, tumor evolutionary histories and clinical trial design

Long-range interactions and non-extensivity in ferromagnetic spin models

The Ising model with ferromagnetic interactions that decay as $1/r^\alpha$ is analyzed in the non-extensive regime $0\leq\alpha\leq d$, where the thermodynamic limit is not defined. In order to study the asymptotic properties of the model in the $N\rightarrow\infty$ limit ($N$ being the number of spins) we propose a generalization of the Curie-Weiss model, for which the $N\rightarrow\infty$ limit is well defined for all $\alpha\geq 0$. We conjecture that mean field theory is {\it exact} in the last model for all $0\leq\alpha\leq d$. This conjecture is supported by Monte Carlo heat bath simulations in the $d=1$ case. Moreover, we confirm a recently conjectured scaling (Tsallis\cite{Tsallis}) which allows for a unification of extensive ($\alpha>d$) and non-extensive ($0\leq\alpha\leq d$) regimes.Comment: RevTex, 12 pages, 1 eps figur

Dominion cartoon satire as trench culture narratives: complaints, endurance and stoicism

Although Dominion soldiers’ Great War field publications are relatively well known, the way troops created cartoon multi-panel formats in some of them has been neglected as a record of satirical social observation. Visual narrative humour provides a ‘bottom-up’ perspective for journalistic observations that in many cases capture the spirit of the army in terms of stoicism, buoyed by a culture of internal complaints. Troop concerns expressed in the early comic strips of Australians, Canadians, New Zealanders and British were similar. They shared a collective editorial purpose of morale boosting among the ranks through the use of everyday narratives that elevated the anti-heroism of the citizen soldier, portrayed as a transnational everyman in the service of empire. The regenerative value of disparagement humour provided a redefinition of courage as the very act of endurance on the Western Front

Evidence of exactness of the mean field theory in the nonextensive regime of long-range spin models

The q-state Potts model with long-range interactions that decay as 1/r^alpha subjected to an uniform magnetic field on d-dimensional lattices is analized for different values of q in the nonextensive regime (alpha between 0 and d). We also consider the two dimensional antiferromagnetic Ising model with the same type of interactions. The mean field solution and Monte Carlo calculations for the equations of state for these models are compared. We show that, using a derived scaling which properly describes the nonextensive thermodynamic behaviour, both types of calculations show an excellent agreement in all the cases here considered, except for alpha=d. These results allow us to extend to nonextensive magnetic models a previous conjecture which states that the mean field theory is exact for the Ising one.Comment: 10 pages, 4 figure

Causal categories: relativistically interacting processes

A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a `causal category'. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.Comment: 43 pages, lots of figure

Changes in the Management of Patients having Radical Radiotherapy for Lung Cancer during the First Wave of the COVID-19 Pandemic in the UK.

AIMS: In response to the COVID-19 pandemic, guidelines on reduced fractionation for patients treated with curative-intent radiotherapy were published, aimed at reducing the number of hospital attendances and potential exposure of vulnerable patients to minimise the risk of COVID-19 infection. We describe the changes that took place in the management of patients with stage I-III lung cancer from April to October 2020. MATERIALS AND METHODS: Lung Radiotherapy during the COVID-19 Pandemic (COVID-RT Lung) is a prospective multicentre UK cohort study. The inclusion criteria were: patients with stage I-III lung cancer referred for and/or treated with radical radiotherapy between 2nd April and 2nd October 2020. Patients who had had a change in their management and those who continued with standard management were included. Data on demographics, COVID-19 diagnosis, diagnostic work-up, radiotherapy and systemic treatment were collected and reported as counts and percentages. Patient characteristics associated with a change in treatment were analysed using multivariable binary logistic regression. RESULTS: In total, 1553 patients were included (median age 72 years, 49% female); 93 (12%) had a change to their diagnostic investigation and 528 (34%) had a change to their treatment from their centre's standard of care as a result of the COVID-19 pandemic. Age ≥70 years, male gender and stage III disease were associated with a change in treatment on multivariable analysis. Patients who had their treatment changed had a median of 15 fractions of radiotherapy compared with a median of 20 fractions in those who did not have their treatment changed. Low rates of COVID-19 infection were seen during or after radiotherapy, with only 21 patients (1.4%) developing the disease. CONCLUSIONS: The COVID-19 pandemic resulted in changes to patient treatment in line with national recommendations. The main change was an increase in hypofractionation. Further work is ongoing to analyse the impact of these changes on patient outcomes

Implementation of the Time-to-Event Continuous Reassessment Method Design in a Phase I Platform Trial Testing Novel Radiotherapy-Drug Combinations-CONCORDE

\ua9 2022 by American Society of Clinical Oncology. PURPOSE CONCORDE is the first phase I drug-radiotherapy (RT) combination platform in non-small-cell lung cancer, designed to assess multiple different DNA damage response inhibitors in combination with radical thoracic RT. Time-to-event continuous reassessment method (TiTE-CRM) methodology will inform dose escalation individually for each different DNA damage response inhibitor-RT combination and a randomized calibration arm will aid attribution of toxicities. We report in detail the novel statistical design and implementation of the TiTE-CRM in the CONCORDE trial. METHODS Statistical parameters were calibrated following recommendations by Lee and Cheung. Simulations were performed to assess the operating characteristics of the chosen models and were written using modified code from the R package dfcrm. RESULTS The results of the simulation work showed that the proposed statistical model setup can answer the research questions under a wide range of potential scenarios. The proposed models work well under varying levels of recruitment and with multiple adaptations to the original methodology. CONCLUSION The results demonstrate how TiTE-CRM methodology may be used in practice in a complex dose-finding platform study. We propose that this novel phase I design has potential to overcome some of the logistical barriers that for many years have prevented timely development of novel drug-RT combinations

Implementation of the Time-to-Event Continuous Reassessment Method Design in a Phase I Platform Trial Testing Novel Radiotherapy-Drug Combinations-CONCORDE

PURPOSE: CONCORDE is the first phase I drug-radiotherapy (RT) combination platform in non-small-cell lung cancer, designed to assess multiple different DNA damage response inhibitors in combination with radical thoracic RT. Time-to-event continuous reassessment method (TiTE-CRM) methodology will inform dose escalation individually for each different DNA damage response inhibitor-RT combination and a randomized calibration arm will aid attribution of toxicities. We report in detail the novel statistical design and implementation of the TiTE-CRM in the CONCORDE trial. METHODS Statistical parameters were calibrated following recommendations by Lee and Cheung. Simulations were performed to assess the operating characteristics of the chosen models and were written using modified code from the R package dfcrm. RESULTS The results of the simulation work showed that the proposed statistical model setup can answer the research questions under a wide range of potential scenarios. The proposed models work well under varying levels of recruitment and with multiple adaptations to the original methodology. CONCLUSION The results demonstrate how TiTE-CRM methodology may be used in practice in a complex dose-finding platform study. We propose that this novel phase I design has potential to overcome some of the logistical barriers that for many years have prevented timely development of novel drug-RT combinations