Work packages - Artillery

Breast cancer is the most common cancer in women globally. Rising incidence and improvements in cancer care have contributed to a growing number of breast cancer survivors. As these cancer survivors live longer, and with almost 80% of them being older than 50 years of age, they are at higher risk of developing other chronic diseases and conditions like cardiovascular disease (CVD), weight gain, and osteoporosis.

The risk of chronic diseases is higher women with breast cancer than that of the general population, which is partly explained by treatment induced toxicity (eg. chemotherapy induced cardiotoxicity, radiation induced cardiotoxicity and lung fibrosis) and side effects (eg. hormone therapy induced osteoporosis, systemic therapy related weight gain), and partly by shared risk factors that predispose for breast cancer and other conditions like overweight and less physical exercise. Overall, development of chronic diseases after a breast cancer diagnosis has an unfavorable impact on quality of life and survival.

Most breast cancer patients (60-65%) are treated with radiotherapy. Planning computed tomography (CT)-images are obtained for delineation and computation of radiation dose distribution fields. These CT-images contain information on risk factors for other diseases like CVD (eg. calcifications in the epicardial coronary arteries and aorta) and early signs of osteoporosis. This potentially valuable but unrequested information is currently not systematically assessed nor reported by professionals, largely due to time constraints and unfamiliarity with its potential importance.

In the ARTILLERY project funded by Horizon Europe, we aim to develop, validate, and prospectively evaluate AI systems for automated early detection of chronic disease risk (factors) in women with breast cancer by using routine CT-images.

WP 1

ARTILLERY COORDINATION AND MANAGEMENT

This work package aims to manage the overall day-to-day administrative, legal and financial aspects of ARTILLERY project and facilitate optimal internal and external communication.

WP 2

AI DEVELOPMENT AND VALIDATION

Objectives: In this WP, we will develop AI-based image analysis tools to quantify markers of i) cardiovascular disease (CVD), ii) body composition, iii) osteoporosis and iv) lung and airway abnormalities. Subsequently, we will use these markers to design AI-based models predicting hospitalization and all-cause mortality. Finally, a framework for integration of the designed AI-based image analysis into clinical workflow will be developed.

WP 3

TRAINING AND VALIDATION OF AI SYSTEMS IN BREAST CANCER PATIENTS IN A REAL-WORLD DATA (RWD) REPOSITORY

We will create a Real-World Data (RWD) repository and generate governance for access to, and use of, the RWD repository. The RWD repository will be used to evaluate robustness, reproducibility and clinical added value of AI systems developed in ARTILLERY project.

WP 4

CLINICAL IMPLEMENTATION AND EVALUATION OF AI SYSTEMS

In this work package, we will work towards clinical implementation and evaluation of an AI system- based workflow. Specific goals include: Prioritization of AI systems that are relevant to breast cancer patients and their doctors; Development of manuals / recommendations for healthcare professionals on management of patients identified by AI systems to be at increased risk of chronic diseases; Conduct a decision impact study (ARTILLERY-DI) to evaluate the uptake and acceptability of AI systems in routine care and to measure to what extent the use of AI systems affects clinical decision making.

WP 5

ETHICAL AND LEGAL ASPECTS OF IMPLEMENTATION OF AI-SYSTEMS

The success of any new clinical application greatly depends on the acceptance and trust in the application amongst its end-users, which are in our case patients and healthcare professionals, as well as society (as a whole). The aim of WP5 is to ensure trust and acceptance of imaged-based AI systems in clinical practice amongst patients and healthcare professionals.

WP 6

DISSEMINATION, EXPLOITATION AND COMMUNICATION

In this work package we will ensure efficient and effective dissemination of ARTILLERY’s approaches, goals, and results to stakeholders to maximize the potential societal and scientific impact of the project. Also, we will enable engagement and input from all stakeholders (incl. clinicians, patients, patient organizations, and the public) so that the needs of all groups can be considered to facilitate the uptake of the results.

Methods

A large data repository including routine CT scans of 26.000 women with breast cancer along with relevant patient variables and CVD outcomes will be set-up from multiple hospitals in Europe (i.e., University Medical Center (UMC) Utrecht, Amsterdam UMC, Region Hovedstaden, Champalimaud Foundation).

This repository will be used by computational scientists to develop and train AI systems for early detection of CVD risk. Using the same repository, methodologists will evaluate the validity of these AI systems.

In parallel, clinical practice guidelines for management of patients automatically identified by AI systems to be at increased risk of CVD will be created by a multidisciplinary team of (breast cancer) professionals for patients with increased risk of CVD and identified by AI systems.

In a multicenter prospective decision impact trial, the impact of implementation of the AI systems on patients’ risk profiles, health status and wellbeing will be evaluated. Finally, we will work towards the valorization of trustworthy AI-based software and product development with the aim to guarantee that ethical principles of trustworthy AI-systems in regular breast cancer patients care will be met.