Periodic Reporting for period 1 - CINDERELLA (Clinical Validation of an AI-based approach to improve the shared decision-making process and outcomes in Breast Cancer Patients proposed for Locoregional treatment)
Periodo di rendicontazione: 2022-06-01 al 2023-11-30
Breast cancer is the most commonly diagnosed cancer worldwide, with an estimated 2.3 million new cases each year. Breast cancer treatment consists of different options comprising surgery and radiotherapy in the majority of patients (also designated as loco-regional treatment).
The evolution of loco-regional treatments has been impressive over the last decades. Breast surgery has evolved from the radical mastectomy approach to breast conservation whenever possible and immediate reconstruction when mastectomy is necessary. In addition, oncoplastic techniques also help to obtain better aesthetic results. Radiotherapy has also evolved, and different approaches lead to improved results without compromising surgical outcomes.
Despite the good news, the choice between different surgeries remains strongly influenced by aesthetic concerns when the results of cancer treatment are comparable. Patients experience great difficulty in choosing the type of surgery to have because they cannot easily foresee how they will become. Approximately one third of breast cancer patients worldwide experience disappointment with the aesthetic results. Patient dissatisfaction can have a negative psychological impact, affecting self-image and overall quality of life.
The CINDERELLA project proposes to integrate artificial intelligence to predict individual aesthetic outcomes and provide a tool to guide evidence-based clinical decisions in breast cancer treatment.
Using a previously developed software to classify the aesthetic results of breast cancer loco-regional treatment (BreLO AI) integrated into a web-based digital health platform developed specifically for breast cancer loco-regional treatment, we developed the CINDERELLA APProach.
The CINDERELLA APP is a unique product designed specifically for women that are going to be submitted to loco-regional breast cancer treatment. Besides the integration of the AI tool, it contains state-of-the-art information and videos about breast cancer loco-regional treatment in 6 languages. Using image matching, this tool will predict loco-regional outcomes for individual patients. Photographs of patients’ torsos will be matched with the closest resembling images of women who have undergone the same surgery, allowing patients the possibility to visualize the results in a more realistic way.
This approach aims to increase patient satisfaction, reduce psychological distress and revision surgeries, and improve overall quality of life.
The CINDERELLA trial will evaluate whether the application helps to meet expectations and improve quality of life. Continuous improvement for subsequent cases will be achieved by feeding post-surgery data (clinical and photographic information) into the AI platform.
This trial will be practice-changing in terms of patient education and shared decision-making. This innovative CINDERELLA APProach aims to overcome any miscommunication and potential limitations in patient or physician understanding of the potential outcomes of locoregional treatment of breast cancer.
The CINDERELLA APProach could pave the way for similar tools in other locoregional treatments that affect patients' aesthetic appearance, becoming a pioneering communication tool in healthcare.
The evolution of loco-regional treatments has been impressive over the last decades. Breast surgery has evolved from the radical mastectomy approach to breast conservation whenever possible and immediate reconstruction when mastectomy is necessary. In addition, oncoplastic techniques also help to obtain better aesthetic results. Radiotherapy has also evolved, and different approaches lead to improved results without compromising surgical outcomes.
Despite the good news, the choice between different surgeries remains strongly influenced by aesthetic concerns when the results of cancer treatment are comparable. Patients experience great difficulty in choosing the type of surgery to have because they cannot easily foresee how they will become. Approximately one third of breast cancer patients worldwide experience disappointment with the aesthetic results. Patient dissatisfaction can have a negative psychological impact, affecting self-image and overall quality of life.
The CINDERELLA project proposes to integrate artificial intelligence to predict individual aesthetic outcomes and provide a tool to guide evidence-based clinical decisions in breast cancer treatment.
Using a previously developed software to classify the aesthetic results of breast cancer loco-regional treatment (BreLO AI) integrated into a web-based digital health platform developed specifically for breast cancer loco-regional treatment, we developed the CINDERELLA APProach.
The CINDERELLA APP is a unique product designed specifically for women that are going to be submitted to loco-regional breast cancer treatment. Besides the integration of the AI tool, it contains state-of-the-art information and videos about breast cancer loco-regional treatment in 6 languages. Using image matching, this tool will predict loco-regional outcomes for individual patients. Photographs of patients’ torsos will be matched with the closest resembling images of women who have undergone the same surgery, allowing patients the possibility to visualize the results in a more realistic way.
This approach aims to increase patient satisfaction, reduce psychological distress and revision surgeries, and improve overall quality of life.
The CINDERELLA trial will evaluate whether the application helps to meet expectations and improve quality of life. Continuous improvement for subsequent cases will be achieved by feeding post-surgery data (clinical and photographic information) into the AI platform.
This trial will be practice-changing in terms of patient education and shared decision-making. This innovative CINDERELLA APProach aims to overcome any miscommunication and potential limitations in patient or physician understanding of the potential outcomes of locoregional treatment of breast cancer.
The CINDERELLA APProach could pave the way for similar tools in other locoregional treatments that affect patients' aesthetic appearance, becoming a pioneering communication tool in healthcare.
The work carried out during the first 18 months of the project essentially consisted of developing the structure that would allow the clinical trial to be initiated.
All contents of the CINDERELLA APP were developed in terms of structure and information in all 6 languages. Contents were carefully revised regarding scientific knowledge. State-of-the-art surgical and nurses videos were prepared along with the audio and voice contents in each language. The information was structured in three different levels for all subjects allowing patients to choose between more detailed or less detailed information.
The Integration of the CINDERELLA APP and the BreLO AI was carefully tested to allow real-time use during the Clinical Trial.
All participating centers approved the trial, which officially started in August 2023.
All contents of the CINDERELLA APP were developed in terms of structure and information in all 6 languages. Contents were carefully revised regarding scientific knowledge. State-of-the-art surgical and nurses videos were prepared along with the audio and voice contents in each language. The information was structured in three different levels for all subjects allowing patients to choose between more detailed or less detailed information.
The Integration of the CINDERELLA APP and the BreLO AI was carefully tested to allow real-time use during the Clinical Trial.
All participating centers approved the trial, which officially started in August 2023.
At the 18th month of the project (November 2023), no results are available yet as the trial is still ongoing.
The developed tools are working but results are not expected before the end of the clinical trial.
The developed tools are working but results are not expected before the end of the clinical trial.