AAPM task group report 288: Recommendations for guiding radiotherapy event narratives.

Incident reporting and learning systems provide an opportunity to identify systemic vulnerabilities that contribute to incidents and potentially degrade quality. The narrative of an incident is intended to provide a clear, easy to understand description of an incident. Unclear, incomplete or poorly organized narratives compromise the ability to learn from them.

A Scalable Radiomics- and Natural Language Processing-Based Machine Learning Pipeline to Distinguish Between Painful and Painless Thoracic Spinal Bone Metastases: Retrospective Algorithm Development and Validation Study.

Background: The identification of objective pain biomarkers can contribute to an improved understanding of pain, as well as its prognosis and better management. Hence, it has the potential to improve the quality of life of patients with cancer. Artificial intelligence can aid in the extraction of objective pain biomarkers for patients with cancer with bone metastases (BMs).

In-Home Respite Care Services Available to Families With Palliative Care Needs in Quebec: Novel Digital Environmental Scan.

Background: Caregiving dyads in palliative care are confronted with complex care needs. Respite care services can be highly beneficial in alleviating the caregiving burden, supporting survivorship and dying at home. Yet, respite care services are difficult to locate and access in the province of Quebec, Canada, particularly when navigating ubiquitous sources of online health information of varying quality.

The use of dose surface maps as a tool to investigate spatial dose delivery accuracy for the rectum during prostate radiotherapy.

Purpose: This study aims to address the lack of spatial dose comparisons of planned and delivered rectal doses during prostate radiotherapy by using dose-surface maps (DSMs) to analyze dose delivery accuracy and comparing these results to those derived using DVHs.

Methods: Two independent cohorts were used in this study: twenty patients treated with 36.25 Gy in five fractions (SBRT) and 20 treated with 60 Gy in 20 fractions (IMRT).

More than one way to skin a dose volume: the impact of dose-surface map calculation approach on study reproducibility.

Dose-surface maps (DSMs) provide spatial representations of the radiation dose to organ surfaces during radiotherapy and are a valuable tool for identifying dose deposition patterns that are predictive of radiation toxicities. Over the years, many different DSM calculation approaches have been introduced and used in dose-outcome studies. However, little consideration has been given to how these calculation approaches may be impacting the reproducibility of studies in the field.

Design and implementation of a prototype radiotherapy menu in a patient portal.

Purpose: Radiotherapy patients often face undue anxiety due to misconceptions about radiation and their inability to visualize their upcoming treatments. Access to their personal treatment plans is one way in which pre-treatment anxiety may be reduced. But radiotherapy data are quite complex, requiring specialized software for display and necessitating personalized explanations for patients to understand them.

Single-cell DNA sequencing-a potential dosimetric tool.

We hypothesised that single-cell whole-genome sequencing has the potential to detect mutational differences in the genomes of the cells that are irradiated with different doses of radiation and we set out to test our hypothesis using in silico and in vitro experiments. In this manuscript, we present our findings from a Monte Carlo single-cell irradiation simulation performed in TOPAS-nBio using a custom-built geometric nuclear deoxyribonucleic acid (DNA) model, which predicts a significant dose dependence of the number of cluster damages per cell as a function of radiation dose. We also present preliminary experimental results, obtained from single-cell whole-genome DNA sequencing analysis performed on cells irradiated with different doses of radiation, showing promising agreement with the simulation results.

A Monte Carlo study on the impact of indirect action on neutron relative biological effectiveness.

Recent Monte Carlo studies have linked the energy-dependent risk of neutron-induced stochastic effects to the relative biological effectiveness (RBE) of neutrons in inflicting difficult-to-repair clusters of lesions in nuclear deoxyribonucleic acid (DNA). However, an investigation on the damaging effects of indirect radiation action is missing from such studies. In this work, we extended our group's existing simulation pipeline by incorporating and validating a model for indirect action.

Experimental validation of a novel method of dose accumulation for the rectum.

Background: Dose-surface maps (DSMs) are an increasingly popular tool to evaluate spatial dose-outcome relationships for the rectum. Recently, DSM addition has been proposed as an alternative method of dose accumulation from deformable registration-based techniques. In this study, we performed the first experimental investigation of the accuracy at which DSM accumulation can capture the total dose delivered to a rectum's surface in the presence of inter-fraction motion.

Information and Communication Technologies to Support the Provision of Respite Care Services: Scoping Review.

Background: Respite care is one of the most frequently requested support services by family caregivers. Yet, too often, respite care services are inaccessible, due in part to families' lack of knowledge regarding available services and a lack of service flexibility. Information and communication technologies (ICTs) may help to improve the flexibility of services available and families' knowledge of such services.

Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.

Purpose: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships.

Methods And Materials: The American Association of Physicists in Medicine's Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders' collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs.

A study of indirect action's impact on simulated neutron-induced DNA damage.

The risk of radiobiological stochastic effects associated with neutrons is strongly energy dependent. Recent Monte Carlo studies simulating neutron-irradiated nuclear DNA have demonstrated that this energy dependence is correlated with the relative biological effectiveness (RBE) of neutrons to inflict DNA damage clusters that contain difficult-to-repair double-strand breaks. However, these previous investigations were either limited to modeling direct radiation action or considered the effects of both direct and indirect action together without distinguishing between the two.

"Informal Caregiver" in Nursing: An Evolutionary Concept Analysis.

The informal caregiver experience has surged as a research topic in health care, including in nursing. However, the "informal" language is controversial, lacking conceptual clarity. Without a common understanding of who an "informal caregiver" may be, nurses may fail to consistently identify informal caregivers requiring support.

Technical note: rtdsm-An open-source software for radiotherapy dose-surface map generation and analysis.

Background: Dose-outcome studies in radiation oncology have historically excluded spatial information due to dose-volume histograms being the most dominant source of dosimetric information. In recent years, dose-surface maps (DSMs) have become increasingly popular for characterization of spatial dose distributions and identification of radiosensitive subregions for hollow organs. However, methodological variations and lack of open-source, publicly offered code-sharing between research groups have limited reproducibility and wider adoption.

Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest.

Radiomics-based machine learning classifiers have shown potential for detecting bone metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current radiomics models require large datasets of images with expert-segmented 3D regions of interest (ROIs). Full ROI segmentation is time consuming and oncologists often outline just RT treatment fields in clinical practice.

Striving to Fill in Gaps between Clinical Practice and Standards: The Evolution of a Pan-Canadian Approach to Patient-Reported Outcomes Use.

Despite the known importance and necessity of the standardized collection and use of patient-reported outcomes (PROs), there remain challenges to successful clinical implementation. Facilitated through a quality improvement initiative spearheaded by the Canadian Partnership for Quality Radiotherapy (CPQR), and now guided by the Canadian Association of Radiation Oncology (CARO)'s Quality and Standards Committee, patient representatives and early-adopter radiation treatment programs continue to champion the expansion of PROs initiatives across the country. The current review discusses the evolution of a pan-Canadian approach to PROs use, striving to fill in gaps between clinical practice and guideline recommendations through multi-centre and multidisciplinary collaboration.

High-Accuracy Relative Biological Effectiveness Values Following Low-Dose Thermal Neutron Exposures Support Bimodal Quality Factor Response with Neutron Energy.

Theoretical evaluations indicate the radiation weighting factor for thermal neutrons differs from the current International Commission on Radiological Protection (ICRP) recommended value of 2.5, which has radiation protection implications for high-energy radiotherapy, inside spacecraft, on the lunar or Martian surface, and in nuclear reactor workplaces. We examined the relative biological effectiveness (RBE) of DNA damage generated by thermal neutrons compared to gamma radiation.

Developing an mHealth Application to Coordinate Nurse-Provided Respite Care Services for Families Coping With Palliative-Stage Cancer: Protocol for a User-Centered Design Study.

Background: Patients living with palliative-stage cancer frequently require intensive care from their family caregivers. Without adequate community support services, patients are at risk of receiving inadequate care, and family caregivers are at risk for depression and poor health. For such families, in-home respite care can be invaluable, particularly when the services are flexible and staffed by trusted care providers, such as nurses.

Natural language processing and machine learning to assist radiation oncology incident learning.

Purpose: To develop a Natural Language Processing (NLP) and Machine Learning (ML) pipeline that can be integrated into an Incident Learning System (ILS) to assist radiation oncology incident learning by semi-automating incident classification. Our goal was to develop ML models that can generate label recommendations, arranged according to their likelihoods, for three data elements in Canadian NSIR-RT taxonomy.

Methods: Over 6000 incident reports were gathered from the Canadian national ILS as well as our local ILS database.

Towards the characterization of neutron carcinogenesis through direct action simulations of clustered DNA damage.

Neutron exposure poses a unique radiation protection concern because neutrons have a large, energy-dependent relative biological effectiveness (RBE) for stochastic effects. Recent computational studies on the microdosimetric properties of neutron dose deposition have implicated clustered DNA damage as a likely contributor to this marked energy dependence. So far, publications have focused solely on neutron RBE for inducing clusters of DNA damage containing two or more DNA double strand breaks (DSBs).

Development of a generalizable natural language processing pipeline to extract physician-reported pain from clinical reports: Generated using publicly-available datasets and tested on institutional clinical reports for cancer patients with bone metastases.

Objective: The majority of cancer patients suffer from severe pain at the advanced stage of their illness. In most cases, cancer pain is underestimated by clinical staff and is not properly managed until it reaches a critical stage. Therefore, detecting and addressing cancer pain early can potentially improve the quality of life of cancer patients.

Satisfaction among Cancer Patients Undergoing Radiotherapy during the COVID-19 Pandemic: An Institutional Experience.

The COVID-19 pandemic has shifted oncology practices to prioritize patient safety while maintaining necessary treatment delivery. We obtained patient feedback on pandemic-based practices in our radiotherapy department to improve quality of patient care and amend policies as needed. We developed a piloted questionnaire which quantitatively and qualitatively assessed patients' pandemic-related concerns and satisfaction with specific elements of their care.

Acceptability of a Patient Portal (Opal) in HIV Clinical Care: A Feasibility Study.

Opal (opalmedapps.com), a patient portal in use at the Cedars Cancer Centre of the McGill University Health Centre (MUHC) (Montreal, Canada), gives cancer patients access to their medical records, collects information on patient-reported outcome measures (PROMs), and has demonstrated patient satisfaction with care. This feasibility study aims to evaluate Opal's potential acceptability in the context of HIV care.

Exploring Cancer Patients' Perceptions of Accessing and Experience with Using the Educational Material in the Opal Patient Portal.

Purpose: Opal is a new patient-centered mobile application that gives cancer patients access to their real time medical data in conjunction with disease- and treatment-specific patient education material. Few studies have focused on patients' experiences with such mobile applications. This study's objectives were to (1) explore cancer patients' perceptions of accessing the educational materials through Opal and (2) explore their experiences using these educational materials.