Submission and approval of the first Periodic Reporting of iToBoS project

The first Periodic Reporting corresponding to the period M1-M18 was submitted to the EC on November 24th, 2022 (M20) and it was officially approved on January 25th, 2023. 

Along this reporting period, 27 deliverables and 9 draft deliverables have been submitted and 2 milestones have been achieved. In total, 8 project meetings have been organized: 4 General Assembly meetings, 3 Project Management Board meetings and 1 Advisory Board meeting. Additionally, several WP meetings and other project meetings have been organized by the Project Coordinator.

The project Grant Agreement (GA) and Consortium Agreement (CA) have been prepared and signed.

The bi-annual technical and financial reports of the consortium (M1-M6, M7-M12 and M13-M18) have been coordinated, monitored and reviewed by the Project Coordinator.

On the first 18 months, the project has advanced in several fronts. First, the overall architecture behind the iToBoS concept has been defined, specifying the system requirements and ensuring interoperability between each of the main modules of the project. This definition included not only the algorithms used for image processing, 3D reconstruction, lesion detection and classification, data integration and anonymization, but also the tools for applying machine learning to the gathered data and the full body scanner hardware to collect the skin images.

One of the main advances of this first period is the definition and validation of the high-resolution imaging module (HRIM), including the design of the liquid lenses for image acquisition. We have also advanced in the design and integration of this HRIM in the total body scanner. In this sense, a first prototype of the total body scanner was designed and the development of a prototype arch was completed (with some parts still pending to arrive by the end of the first reporting period, due to lack of components in the market). Given the materials shortage in the market, and the delays that this imposed in the design of the scanner prototype, a contingency plan has been implemented to keep advancing in the development of the AI cognitive assistant for early detection of melanoma. This contingency plan is based on the acquisition of skin images using the best total body scanner that could be found in the market (VECTRA360 by Canfield). The team also started to develop the tools for image ingestion, as well as the anonymization and masking tools both for the images and the patient data. In this sense, we have defined the specific demographic and clinical data from the patients to be used by the AI, together with the lesion images. Secondly, a number of tasks such as lesion detection, lesion classification and development of eXplainable AI (XAI) have started by using public image datasets, allowing the advance in these domains. Moreover, both ethical risks as well as ethical opportunities, such as being able to detect melanoma earlier or personalizing the diagnostics, have been assessed during this first period. All the medical research ethics aspects have been addressed and the clinical protocols for the use of the VECTRA images and the patient’s data have been submitted to the corresponding ethical committees. Finally, a patient engagement plan with touch points and educational needs has been developed, specifying how iToBoS will engage with the broader patient community. And regarding outreach, the consortium has defined and implemented the dissemination and communication strategy of iToBoS to set the guidelines, actions and tools to channel the efforts aimed at achieving a wide impact of the project among the target audience to extend the results and benefits of the project to the society in general.