Active control of mid-wavelength infrared non-linearity in silicon photonic crystal slab

Natural materials' inherently weak nonlinear response demands the design of artificial substitutes to avoid optically large samples and complex phase-matching techniques. Silicon photonic crystals are promising artificial materials for this quest. Their nonlinear properties can be modulated optically, paving the way for applications ranging from ultrafast information processing to quantum technologies. A two-dimensional 15-μm-thick silicon photonic structure, comprising a hexagonal array of air holes traversing the slab's thickness, has been designed to support a guided resonance for the light with a wavelength of 4-μm. At the resonance conditions, a transverse mode of the light is strongly confined between the holes in the "veins" of the silicon component. Owing to the confinement, the structure exhibits a ratio of nonlinear to linear absorption coefficients threefold higher than the uniform silicon slab of the same thickness. A customised time-resolved Z-scan method with provisions to accommodate ultrafast pump-probe measurements was used to investigate and quantify the non-linear response. We show that optically pumping free charge carriers into the structure decouples the incoming light from the resonance and reduces the non-linear response. The time-resolved measurements suggest that the decoupling is a relatively long-lived effect on the scale comparable to the non-radiative recombination in the bulk material. Moreover, we demonstrate that the excited free carriers are not the source of the nonlinearity, as this property is determined by the structure design.

Research participants may not recall their participation but have a better understanding of alternative management options than patients in routine care

BACKGROUND

Patient understanding of care interventions, of the clinical uncertainty, and of their participation in clinical research is often poor. We hypothesized that compared to routine care, patients would better understand the prevailing uncertainty when they participated in research.

METHODS

A questionnaire was administered to patients at the time they attended a follow-up neurovascular clinic 4 to 52 weeks after a care episode where they did or did not participate in a clinical trial. Patients were not reminded whether they had previously participated in a clinical trial. Questions concerned their understanding of the risks/benefits of interventions, the availability of alternative options, whether their personal opinion was taken into consideration, the reason for the final decision, their confidence at having received the best management, and whether they had been research participants.

RESULTS

Between June 2019 and June 2020, 167 patients were recruited; 71 had truly been research participants, while 96 had not. A greater proportion of research patients were aware of the existence of management alternatives (65% versus 44%; P=0.008). Patients of both groups believed their personal opinion counted in the final decision (76% versus 70%), and patients were equally confident that they had received the best management (94%). Research patients believed they had participated in research 46% of the time, compared to 12% of routine care patients (P=0.003).

CONCLUSION

Many patients do not recall that they participated in a clinical trial, but they have a better understanding of the clinical uncertainty and of the availability of alternative management options.

Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group

PURPOSE

Rhabdomyosarcoma (RMS) is an aggressive soft-tissue sarcoma, which primarily occurs in children and young adults. We previously reported specific genomic alterations in RMS, which strongly correlated with survival; however, predicting these mutations or high-risk disease at diagnosis remains a significant challenge. In this study, we utilized convolutional neural networks (CNN) to learn histologic features associated with driver mutations and outcome using hematoxylin and eosin (H&E) images of RMS.

EXPERIMENTAL DESIGN

Digital whole slide H&E images were collected from clinically annotated diagnostic tumor samples from 321 patients with RMS enrolled in Children's Oncology Group (COG) trials (1998-2017). Patches were extracted and fed into deep learning CNNs to learn features associated with mutations and relative event-free survival risk. The performance of the trained models was evaluated against independent test sample data (n = 136) or holdout test data.

RESULTS

The trained CNN could accurately classify alveolar RMS, a high-risk subtype associated with PAX3/7-FOXO1 fusion genes, with an ROC of 0.85 on an independent test dataset. CNN models trained on mutationally-annotated samples identified tumors with RAS pathway with a ROC of 0.67, and high-risk mutations in MYOD1 or TP53 with a ROC of 0.97 and 0.63, respectively. Remarkably, CNN models were superior in predicting event-free and overall survival compared with current molecular-clinical risk stratification.

CONCLUSIONS

This study demonstrates that high-risk features, including those associated with certain mutations, can be readily identified at diagnosis using deep learning. CNNs are a powerful tool for diagnostic and prognostic prediction of rhabdomyosarcoma, which will be tested in prospective COG clinical trials.

Understanding the research-care demarcation and why it must be revised

BACKGROUND

A clean-cut separation between research and care was artificially created at the time of the Belmont report more than 40 years ago. The demarcation was initially controversial but eventually was implemented for political reasons. We examine why it must be revised.

METHODS

We review historical research scandals as well as the theoretical basis for the Belmont demarcation. We then discuss consequences on medical practice and propose an alternative.

DISCUSSION

Most research scandals involved abusing human beings supposedly for the sake of science. Belmont commissioners were aware the research/care problem was double-headed. While research subjects should be protected from abuse in the research context, patients need to be protected from unvalidated medical and surgical interventions in the care context. For political reasons the Commission recommended the regulation of research but to leave medical practice untouched. Thus the Commission had to distinguish research from care. The notion of 'generalizable knowledge' was introduced to define and regulate research, but the inadvertent result was that by trying to protect research subjects, the regulation has not only failed to protect all other patients, but also encouraged the widespread practice of unvalidated interventions within the care context. The notion of validated care should be re-introduced into a proper analysis of the care-research demarcation, for care research is an integral ingredient of a good medical practice.

CONCLUSION

The research-care demarcation should be revised to leave room for the validated/unvalidated care distinction. Care research, essential to guide medical practice, should be facilitated at all levels.

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies

BACKGROUND

The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples.

RESULTS

We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy.

CONCLUSIONS

A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

The Adapted Firesetting Assessment Scale: reliability and validity

BACKGROUND

The Adapted Firesetting Assessment Scale was developed for use with adults with developmental disabilities targeting fire-related factors thought to be associated with deliberate firesetting behaviour (i.e. attitudes towards fire, fire interest, fire normalisation, identification with fire and fire safety awareness). However, the psychometric properties of the scale are yet to be evaluated.

METHOD

The reliability, validity, comprehensibility, relevance and comprehensiveness of the Adapted Firesetting Assessment Scale were evaluated. Fifty-nine adults with developmental disabilities, some of whom had a history of firesetting, completed the Adapted Firesetting Assessment Scale on two occasions. Feedback about the questionnaire was sought from both participants and professionals.

RESULTS

The AFAS has acceptable internal consistency and excellent test-retest reliability. The attitudes towards fire, fire normalisation, poor fire safety subscales and total scores discriminated firesetters from non-firesetters. Content analysis of feedback indicated items of the AFAS were understood, relevant, accessible and comprehensible.

CONCLUSION

A larger study is needed to examine the factor structure of the AFAS.

Abstract 466: Predicting survival of rhabdomyosarcoma patients based on deep learning of H&E images

Background: Rhabdomyosarcoma (RMS) is an aggressive soft tissue tumor in children and young adults, accounting for 350-400 new cases annually in the US. Diagnosis of RMS is defined by the expression of genes related to skeletal muscle differentiation and can be further subclassified based on histological patterns (embryonal, ERMS; alveolar, ARMS; spindle/sclerosing, SSRMS). Genetic studies have found that the presence of a PAX fusion gene (FP-RMS), which is present in many ARMS tumors, correlates with poor outcome. Subsequent studies have identified additional genetic alterations (ex. TP53 or MYOD1 mutations) which also display distinct histological features and are associated with poor outcome. As a result, there is a growing need to identify these mutations to improve risk stratification. The goal of this study is to develop and test deep learning algorithms from diagnostic H&E images of RMS tumors which can aid in the diagnosis, mutation prediction and risk stratification for RMS patients.

Methods: De-identified RMS patient samples were collected from tissue banking studies from Children’s Oncology Group (n=275), University Hospital Zurich (n=250) and Memorial Sloan Kettering (n=10). H&E stains on whole slides or TMAs were digitally scanned and used for analysis. Clinical information including clinical risk group, event-free survival, and genomic findings were used as available for training and testing. Convolutional neural networks (CNN) using EfficientNet were trained using K-fold cross validation to classify tumor histology, mutation probability, and risk stratification and tested against randomly selected samples or independent datasets when available.

Results: The developed AI algorithm was able to classify tissue as ARMS (FP-RMS), ERMS (FN-RMS), stroma and necrosis with an average weighted intersect-over-union of 0.74 when compared to an expert pathologist annotation. A second deep learning algorithm developed specifically for distinguishing FP-RMS from FN-RMS displayed excellent sensitivity (FP-RMS=0.88) and specificity (FP-RMS=0.86) when tested against an independent RMS TMA dataset. Algorithms were also trained to predict mutations in MYOD1, RAS pathway genes, and TP53 and displayed good performance with ROC values of 0.96, 0.68, and 0.64, respectively. Lastly, we developed an algorithm to provide a Cox proportional hazard prediction based on H&E images. The resulting algorithm was capable of predicting EFS with similar accuracy as current clinical risk group assessment with improved ability to distinguish intermediate and high risk patients.

Conclusions: Deep learning with convolutional neural networks provides pathologist-independent classification of RMS patients from simple H&E images. These AI algorithms can provide probabilities of prognostically relevant genetic alterations and survival which will ultimately contribute to better risk stratification of RMS patients.

Citation Format: David Milewski, Hyun Jung, G. Thomas Brown, Yanling Liu, Jack Collins, Marc Ladanyi, Erin Rudzinski, Javed Khan. Predicting survival of rhabdomyosarcoma patients based on deep learning of H&E images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 466.

Taming non-radiative recombination in Si nanocrystals interlinked in a porous network

A range of the distinctive physical properties, comprising high surface-to-volume ratio, possibility to achieve mechanical and chemical stability after a tailored treatment, controlled quantum confinement and the room-temperature photoluminescence, combined with mass production capabilities offer porous silicon unmatched capabilities required for the development of electro-optical devices. Yet, the mechanism of the charge carrier dynamics remains poorly controlled and understood. In particular, non-radiative recombination, often the main process of the excited carrier's decay, has not been adequately comprehended to this day. Here we show, that the recombination mechanism critically depends on the composition of surface passivation. That is, hydrogen passivated material exhibits Shockley-Read-Hall type of decay, while for oxidised surfaces, it proceeds by two orders of magnitude faster and exclusively through the Auger process. Moreover, it is possible to control the source of recombination in the same sample by applying a cyclic sequence of hydrogenation-oxidation-hydrogenation processes, and, consequently switching on-demand between Shockley-Read-Hall and Auger recombinations. Remarkably, irregardless of the recombination mechanism, the rate constant scales inversely with the average volume of individual silicon nanocrystals contained in the material. Thus, the type of the non-radiative recombination is established by the composition of the passivation, while its rate depends on the degree of the charge carriers' quantum confinement.

A Systematic Review of Autistic People and the Criminal Justice System: An Update of King and Murphy (2014)

The purpose of this paper was to determine whether recommendations made by King & Murphy (Journal of Autism and Developmental Disorders 44:2717-2733, 2014) in their review of the evidence on autistic people in contact with the criminal justice system (CJS) have been addressed. Research published since 2013 was systematically examined and synthesised. The quality of 47 papers was assessed using the Mixed Methods Appraisal Tool. Findings suggest a limited amount of good quality research has been conducted that has focused on improving our understanding of autistic people in contact with the CJS since 2013. Methodological limitations make direct comparisons between autistic and non-autistic offenders difficult. Autistic people commit a range of crimes and appear to have unique characteristics that warrant further exploration (i.e., vulnerabilities, motivations for offending).

183 A Systematic Review of Sample Size Calculations in High-Profile Surgical Trials That Use Patient-Reported Outcome Measures

Background

Patient reported outcome measures (PROMs) are increasingly recognised as a measure of treatment efficacy in randomised controlled trials (RCTs). It can be difficult to determine meaningful target differences in PROM scores for sample size calculations and this can risk over-recruitment and/or erroneous trial conclusions. The Difference ELicitation in TriAls (DELTA2) statement sets recommendations for sample size calculations in RCTs including target difference determination. We aimed to evaluate sample size calculations from high-profile surgical RCTs that used PROMs as their primary outcome, against DELTA2 standards, with a focus on target differences.

Method

Pubmed was systematically searched for surgical RCTs published in the five highest ranking journals, by Thomson Reuters impact factor, for medicine and surgery. Studies were included if surgery was the intervention and/or comparator arm, and a PROM was the primary outcome. Surgery was defined as using instrumentation to change macro-anatomy with the aim of improving health. Data were extracted with a piloted data collection sheet that included the DELTA2 reporting recommendations.

Results

Most target differences used in sample size calculations were determined with suboptimal techniques and target difference justification was overall poor. In this sample, £28 million of UK public research spending supported trials with poor target difference justification.

Conclusions

In this sample of trials, sample size calculations were generally not reported to DELTA2 standards. There was frequent use of sub-optimal methods to determine the target difference. This risks over-recruitment and/or erroneous trial conclusions. Clinicians should be aware of these potential pitfalls when interpreting published trials.

Real-time Detection of Patient Head Position and Cephalometric Landmarks from Neuro-Interventional Procedure Images Using Machine Learning for Patient Eye-Lens Dose Prediction

A deep learning (DL) model has been developed to estimate patient-lens dose in real-time for given exposure and geometric conditions during fluoroscopically-guided neuro-interventional procedures. Parameters input into the DL model for dose prediction include the patient head shift from isocenter and cephalometric landmark locations as a surrogate for head size. Machine learning (ML) models were investigated to automatically detect these parameters from the in-procedure fluoroscopic image. Fluoroscopic images of a Kyoto Kagaku anthropomorphic head phantom were taken at various known X (transverse) and Y (longitudinal) shifts, as well as different magnification modes, to create an image database. For each image, anatomical landmark coordinate locations were obtained manually using ImageJ and are used as ground-truth labels for training. This database was then used to train the two separate ML models. One ML model predicts the patient head shift in both the X and Y directions and the other model predicts the coordinates of the anatomical landmarks. From the coordinates, the distance between these anatomical landmarks is calculated, and input into the DL dose-prediction model. Model performance was evaluated using mean absolute error (MAE) and mean absolute percentage error (MAPE) for the head-shift and landmark-coordinate models, respectively. The goal is to implement these two separate models into the Dose Tracking System (DTS) developed by our group. This would allow the DTS to automatically detect the patient head size and position for eye-lens dose prediction and eliminate the need for manual input by the clinical staff.

141 New Guidelines to Reduce Unnecessary Blood Tests, Delayed Discharge and Costs Following Robot Assisted Radical Prostatectomy

Objectives

Routine postoperative blood tests (POBT) following robot assisted radical prostatectomy (RARP) are used to evaluate the impact of surgery on pre-existing co-morbidities and to detect early complications. This practice dates back to an era of open surgery, when blood loss and complication rates were higher. We propose new guidelines to improve the specificity of POBT.

Method

The cases of 1040 consecutive patients who underwent a primary or salvage RARP at two large tertiary urology centres in the United Kingdom were retrospectively reviewed to form new guidelines. The new guidelines were prospectively validated in a sample of 300 patients.

Results

Derivation Dataset: 3% and 5% had intra- and post-operative Clavien-Dindo complications, respectively. 15% had clinical concerns postoperatively. 0.9% required perioperative transfusion. 78% had routine blood tests without clinical concerns, none of whom developed a complication. 98% of complications were suspected by clinical judgement. 6% of patients had a discharge delay of ≥ 1 day due to delayed or incomplete blood tests. Validation Dataset: No significant difference existed in complication, clinical concern or transfusion rates between the derivation and validation datasets. Number of POBT requested reduced by 73% (p < 0.001). The new guidelines improved POBT sensitivity for complications from 98% to 100% and specificity from 0% to 74%. Discharge delays reduced from 6% to 0% (p = 0.008). Cost savings were £178 per patient.

Conclusions

Postoperative complications and transfusion following RARP are rare. Routine POBT without clinical indication are unnecessary and inefficient. A guideline-based approach to POBT can reduce costs and optimise discharge without compromising patient safety or care.

1420 ViRtual prOficiency Based prOgression for Robotic Training (VROBOT): A Prospective Cohort Study Protocol

Introduction

Robotic surgery is an evolving field that requires specialist training. Historically, robotic surgery training has lacked standardisation. Recently, training centres have introduced proficiency-based modules and curriculums to certify and progress the skills of novice robotic surgeons. However, training tends to be self-directed and non-interactive. Limited interactive teaching does exist but can be inaccessible and expensive. We aim to validate the effectiveness of the current Fundamentals of Robotic Surgery (FRS) training curriculum with the addition of interactive virtual classroom teaching.

Method

16 novice surgical trainees will be assigned to two training groups. The interventions will be implemented following a one-week robotic skills induction. Both groups will receive access to the FRS curriculum for one week. The intervention group will additionally receive virtual classroom robotic skills training. The primary outcome will be the objective performance scores after training using a synthetic model based on task errors, time taken and contact pressure. In week 3, each group will receive the alternate intervention and objective performance scores will be measured to determine the trajectory of scores.

Results

Significant objective performance improvement following the intervention will be indicative of intervention quality.

Conclusions

This will be the first feasibility study evaluating the efficacy of interactive virtual robotic surgery training. It will determine the effect size of virtual classroom training on the development of basic robotic surgical skills in addition to the proficiency-based FRS curriculum. The findings will assist the development and implementation of further resource-efficient virtual robotic surgical skills training programs.

Complications of combination intranasal corticosteroids and anti-retroviral therapy

BACKGROUND

Intranasal corticosteroids are widely used for management of many upper airway diseases because of their ability to effectively deliver local relief of inflammation.

CASE REPORT

This paper presents the case of a 51-year-old man with human immunodeficiency virus treated with ritonavir who was started on fluticasone intranasal spray for presumed chronic rhinosinusitis. Months after starting this therapy, he developed symptoms of Cushing's syndrome and avascular necrosis of the shoulder due to the pharmacological interactions between fluticasone and ritonavir.

CONCLUSION

Although intranasal corticosteroids are deemed a low-risk route of drug administration, clinicians need to be vigilant in appropriately prescribing corticosteroids in the setting of drug potentiators, particularly in these high-risk patients. Alternative corticosteroids such as beclomethasone dipropionate should be considered in such cases.

Gold nanoplasmonic particles in tunable porous silicon 3D scaffolds for ultra-low concentration detection by SERS

A composite material of plasmonic nanoparticles embedded in a scaffold of nano-porous silicon offers unmatched capabilities for use as a SERS substrate. The marriage of these components presents an exclusive combination of tightly focused amplification of Localised Surface Plasmon (LSP) fields inside the material with an extremely high surface-to-volume ratio. This provides favourable conditions for a single molecule or extremely low concentration detection by SERS. In this work the advantage of the composite is demonstrated by SERS detection of Methylene Blue at a concentration as low as a few picomolars. We systematically investigate the plasmonic properties of the material by imaging its morphology, establishing its composition and the effect on the LSP resonance optical spectra.

A Study of GP Workload and Satisfaction

Aims In this novel study in the Irish setting, we quantified the number items managed per General Practitioner (GP) consult, how each item is managed, and impact on a GP's job satisfaction. Methods Participating GPs at two surgeries completed a questionnaire - integrated into the practice management software - after each consultation that satisfied the inclusion criteria during a four-week period. Results Due to feasibility constraints, 500 of 857 (58.3%) completed questionnaires were randomly selected for our sample. GPs manage an average of 1.76 items per consultation. Older patients presented with more items. Greater number of presenting items led to less being managed on the day 71% (n=5) for 5 items vs. 95.2% (n= 246) for 1 item, longer consultation duration (mean = 14.63 minutes (4-45) and decreased GP satisfaction, mean 8/10 (2-10). Conclusion Increasing the number of items in a GP consultation has a statistically significant effect on duration of consultation, how each item is managed, and even GP satisfaction.