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The paper describes a computer tool dedicated to the comprehensive analysis of lung changes in computed tomography (CT) images. The correlation between the dose delivered during radiotherapy and pulmonary fibrosis is offered as an example analysis. The input data, in DICOM (Digital Imaging and Communications in Medicine) format, is provided from CT images and dose distribution models of patients. The CT images are processed using convolution neural networks, and next, the selected slices go through the segmentation and registration algorithms. The results of the analysis are visualized in graphical format and also in numerical parameters calculated based on the images analysis.

Introduction - Thanks to improvement of care, cancer has become a chronic condition. But due to the toxicity of treatment, the importance of supporting the quality of life (QoL) of cancer patients increases. Monitoring and managing QoL relies on data collected by the patient in his/her home environment, its integration, and its analysis, which supports personalization of cancer management recommendations. We review the state-of-the-art of computerized systems that employ Data Science methods to monitor the health status and provide support to cancer patients managed at home. Objective - Our main objective is to analyze the literature to identify open research challenges that a novel decision support system for cancer patients and clinicians will need to address, point to potential solutions, and provide a list of established best-practices to adopt. Methods - We designed a review study, in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzing studies retrieved from PubMed related to monitoring cancer patients in their home environments via sensors and self-reporting: what data is collected, what are the techniques used to collect data, semantically integrate it, infer the patient state from it and deliver coaching/behavior change interventions. Results - Starting from an initial corpus of 819 unique articles, a total of 180 papers were considered in the full-text analysis and 110 were finally included in the review. Our findings are organized and presented in four main sub-topics consisting of data collection, data integration, predictive modeling and patient coaching. Conclusion - Development of modern decision support system for cancer needs to utilize best practices like the use of validated electronic questionnaires for quality of life assessment, adoption of appropriate information modeling standards supplemented by terminologies/ontologies, adherence to FAIR data principles, external validation, stratification of patients in subgroups for better predictive modeling, and adoption of formal behavior change theories. Open research challenges include supporting emotional and social dimensions of well-being, including PROs in predictive modeling, and providing better customization of behavioral interventions for the specific population of cancer patients.

Background Since treatment with immune checkpoint inhibitors (ICIs) is becoming standard therapy for patients with high-risk and advanced melanoma, an increasing number of patients experience treatment-related adverse events such as fatigue. Until now, studies have demonstrated the benefits of using eHealth tools to provide either symptom monitoring or interventions to reduce treatment-related symptoms such as fatigue. However, an eHealth tool that facilitates the combination of both symptom monitoring and symptom management in patients with melanoma treated with ICIs is still needed. Objective In this pilot study, we will explore the use of the CAPABLE (Cancer Patients Better Life Experience) app in providing symptom monitoring, education, and well-being interventions on health-related quality of life (HRQoL) outcomes such as fatigue and physical functioning, as well as patients’ acceptance and usability of using CAPABLE. Methods This prospective, exploratory pilot study will examine changes in fatigue over time in 36 patients with stage III or IV melanoma during treatment with ICI using CAPABLE (a smartphone app and multisensory smartwatch). This cohort will be compared to a prospectively collected cohort of patients with melanoma treated with standard ICI therapy. CAPABLE will be used for a minimum of 3 and a maximum of 6 months. The primary endpoint in this study is the change in fatigue between baseline and 3 and 6 months after the start of treatment. Secondary end points include HRQoL outcomes, usability, and feasibility parameters. Results Study inclusion started in April 2023 and is currently ongoing. Conclusions This pilot study will explore the effect, usability, and feasibility of CAPABLE in patients with melanoma during treatment with ICI. Adding the CAPABLE system to active treatment is hypothesized to decrease fatigue in patients with high-risk and advanced melanoma during treatment with ICIs compared to a control group receiving standard care. The Medical Ethics Committee NedMec (Amsterdam, The Netherlands) granted ethical approval for this study (reference number 22-981/NL81970.000.22). Trial Registration ClinicalTrials.gov NCT05827289; https://clinicaltrials.gov/study/NCT05827289 International Registered Report Identifier (IRRID) DERR1-10.2196/49252

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BACKGROUND Since treatment with immune-checkpoint inhibitors (ICIs) is becoming standard therapy for high-risk and advanced-melanoma patients, an increasing number of patients experience treatment-related adverse events such as fatigue. Until now, studies have demonstrated the benefits of using eHealth tools in providing either symptom monitoring or interventions to reduce treatment-related symptoms like fatigue. However, an eHealth tool that facilitates the combination of both symptom monitoring and symptom management is still needed. OBJECTIVE In this pilot study, we will explore the use of the Cancer Patients Better Life Experience (CAPABLE) application in providing symptom monitoring, education and wellbeing interventions, on health-related quality of life (HRQoL) outcomes such as fatigue and physical functioning, as well as patients’ acceptance of using a system like CAPABLE. METHODS This prospective, exploratory pilot study will examine changes in fatigue over time in 36 patients with stage III/IV melanoma during treatment with ICI using the CAPABLE intervention (a smartphone application and a multi-sensorial smartwatch). This cohort will be compared to a prospectively collected cohort of melanoma patients treated with standard ICI therapy. The CAPABLE application and smartwatch will be used for a minimum of three and a maximum of six months. The primary endpoint in this study is the change in fatigue between baseline, 3 and 6 months after start of treatment. Secondary endpoints include other HRQoL outcomes, usability and feasibility parameters. RESULTS Study inclusion started in April 2023 and is currently ongoing. CONCLUSIONS This pilot study will explore the effect, usability and feasibility of the CAPABLE system in melanoma patients during treatment with ICI. This study will be the first to provide a system developed in collaboration with patients and clinicians that includes symptom monitoring, information provision and wellbeing interventions in one eHealth tool. The Medical Ethics Committee NedMec (Amsterdam, The Netherlands) granted ethical approval for this study under reference number 22-981/NL81970.000.22. CLINICALTRIAL Trial registration number: NCT05827289