Periodic Reporting for period 1 - ScolioSIM (From Skin to Skeleton: Revolutionary Contactless and Non-Ionizing 3D Digital Diagnosis and Monitoring of Spinal Disorders in Adolescents)
Période du rapport: 2020-09-01 au 2022-08-31
Scoliosis is a highly complex 3D musculoskeletal disorder (MSD) of the spine that greatly affects the patient’s health and quality of life, including functional limitations with secondary complications such as respiratory and circulatory dysfunction, pain, as well as cosmetic changes. Scoliosis affects 0.47–5.20% of the global population, and almost 80-90% of the cases develop for an unknown reason (idiopathic), with an alarming estimated prevalence of 36 million new patients worldwide by 2050 according to the World Health Organisation. The main drawback of traditional radiographic (RAD) methods in AIS assessment is their harmful effect on what is an often young, and hence extremely vulnerable population, especially due to multiple radiation exposures while monitoring progression of the disease. As a result, patients are cumulatively exposed to a substantial amount of ionizing radiation, and each exposure increases the risk for malignancy development later in life. The clinical goal and priority are therefore to avoid or reduce application of those methods in AIS monitoring with a clear preference for non-invasive techniques based on visual examination of the patient’s trunk and external deformity measures.
The overarching aim and objectives of the project were to address the challenges associated to assessment and screening of Adolescent Idiopathic Scoliosis (AIS) in a non-invasive manner by investigating the level of accuracy, precision and reliability of optical software solutions (ScolioSIM1.0) developed by the fellow, to validate and improve the accuracy of the Generic Spinal Model (GSM) against radiographic modalities, to implement it into the clinical environment, and to extend it for online AIS monitoring (ScolioSIM2.0→ScolioMedIS).
The achievement of the proposed aim and objectives required a detailed and multidisciplinary approach and involvement of patients, clinicians and experimental study in clinical environment. In terms of results, the ScolioSIM project led to a: 1) better understanding of correlation between spinal deformities and external appearance of the subject with AIS, 2) new protocol for more precise data collection, 3) improved ScolioSIM tool, 4) ScolioMedIS platform for e-monitoring and reporting of AIS deformity and 5) further funding for translational research and development.
The development of better diagnosis and management of AIS as a research focus of ScolioSIM will continue to contribute to the goal of the European Innovation partnership on Active and Healthy Ageing and increasing the quality of life. The ScolioSIM project and its results tackled H2020 EU societal challenges SC1-BHC-06-2020: “Digital Diagnostics - Developing Tools for Supporting Clinical Decisions by Integrating Various Diagnostic Data”, SC1-DTH-13-2020: “Implementation research for scaling up and transfer of innovative solutions involving digital tools for people-centred care”, by development algorithms and tools for innovative 3D digital diagnosis, rapid screening, preventing disabilities among children and archiving datasets on AIS patients. These challenges will be fully addressed once translation of ScolioSIM findings to the low-cost device is completed.
The overarching aim and objectives of the project were to address the challenges associated to assessment and screening of Adolescent Idiopathic Scoliosis (AIS) in a non-invasive manner by investigating the level of accuracy, precision and reliability of optical software solutions (ScolioSIM1.0) developed by the fellow, to validate and improve the accuracy of the Generic Spinal Model (GSM) against radiographic modalities, to implement it into the clinical environment, and to extend it for online AIS monitoring (ScolioSIM2.0→ScolioMedIS).
The achievement of the proposed aim and objectives required a detailed and multidisciplinary approach and involvement of patients, clinicians and experimental study in clinical environment. In terms of results, the ScolioSIM project led to a: 1) better understanding of correlation between spinal deformities and external appearance of the subject with AIS, 2) new protocol for more precise data collection, 3) improved ScolioSIM tool, 4) ScolioMedIS platform for e-monitoring and reporting of AIS deformity and 5) further funding for translational research and development.
The development of better diagnosis and management of AIS as a research focus of ScolioSIM will continue to contribute to the goal of the European Innovation partnership on Active and Healthy Ageing and increasing the quality of life. The ScolioSIM project and its results tackled H2020 EU societal challenges SC1-BHC-06-2020: “Digital Diagnostics - Developing Tools for Supporting Clinical Decisions by Integrating Various Diagnostic Data”, SC1-DTH-13-2020: “Implementation research for scaling up and transfer of innovative solutions involving digital tools for people-centred care”, by development algorithms and tools for innovative 3D digital diagnosis, rapid screening, preventing disabilities among children and archiving datasets on AIS patients. These challenges will be fully addressed once translation of ScolioSIM findings to the low-cost device is completed.
In summary, ScolioSIM achieved its aim and specific objectives. The first stage of the project allowed clinical data collection. Back surfaces of 30 individuals with AIS were digitalised optically and fused with biplanar radiographs generated by the EOS low-dose system. A database of anonymous data was created allowing second stage of activities on developing a novel algorithm for middle spinal alignment (MSA) mapping on biplanar radiographic images. Based on collected datasets, correlation of AIS deformity and external appearance of back surface was investigated using regression models.
In the third stage of the project a machine learning regression tool was developed to enable more precise prediction of the MSA from external digital shape. The ScolioSIM1.0 algorithm was then optimized (performance and precision) and embedded in ScolioMedIS2.0 information system. The tasks of the first phase were related to the development of algorithm for internet AIS monitoring for medical information system for AIS deformity called ScolioMedIS. Algorithms developed during the ScolioSIM project will be improved and tested in two additional clinical studies and integrated in the final low-cost product for non-ionising detection and monitoring of AIS.
In parallel, a wide range of dissemination, communication and exploitation activities were organized in order to maximise the impact of the ScolioSIM project and this process will continue after the end of the fellowship. Finally, the MSCA fellow participated in many carefully chosen and targeted training activities aimed at boosting his excellence with new skills gained and independence prospective.
In the third stage of the project a machine learning regression tool was developed to enable more precise prediction of the MSA from external digital shape. The ScolioSIM1.0 algorithm was then optimized (performance and precision) and embedded in ScolioMedIS2.0 information system. The tasks of the first phase were related to the development of algorithm for internet AIS monitoring for medical information system for AIS deformity called ScolioMedIS. Algorithms developed during the ScolioSIM project will be improved and tested in two additional clinical studies and integrated in the final low-cost product for non-ionising detection and monitoring of AIS.
In parallel, a wide range of dissemination, communication and exploitation activities were organized in order to maximise the impact of the ScolioSIM project and this process will continue after the end of the fellowship. Finally, the MSCA fellow participated in many carefully chosen and targeted training activities aimed at boosting his excellence with new skills gained and independence prospective.
In particular, the ScolioSIM project has highlighted the potentials of using non-invasive and non-ionizing techniques in AIS deformity assessment and monitoring particularly in young and thus vulnerable population such as adolescents. The results offer practical and clear guidance on how to improve diagnostic protocol to reduce number of x-ray investigations per patient during adolescence and as alternative to use optical approaches to predict and visualize AIS deformity from the “skin to inside”.
Preliminary results of the ScolioSIM project also enabled new funding and continuation of the project through the Innosuisse Translational Research Funding (47195.1 IP-LS) “IDIAG 4D Spine: A new low cost, dynamic 3D body scanner for clinical analysis and monitoring of spine pathologies and posture” through which translation of scientific findings into a low-cost device will be conducted. This will also allow fast screening especially in less developed countries where expensive diagnostic technologies are not available.
The results of the ScolioSIM project are aligned with and contribute to both national and European-level priorities around development of solutions for digital diagnostics, people-centred healthcare and healthy aging. The ScoioSIM project has also been disseminated via its website, social media profiles, publications, reaching a wide audience.
Preliminary results of the ScolioSIM project also enabled new funding and continuation of the project through the Innosuisse Translational Research Funding (47195.1 IP-LS) “IDIAG 4D Spine: A new low cost, dynamic 3D body scanner for clinical analysis and monitoring of spine pathologies and posture” through which translation of scientific findings into a low-cost device will be conducted. This will also allow fast screening especially in less developed countries where expensive diagnostic technologies are not available.
The results of the ScolioSIM project are aligned with and contribute to both national and European-level priorities around development of solutions for digital diagnostics, people-centred healthcare and healthy aging. The ScoioSIM project has also been disseminated via its website, social media profiles, publications, reaching a wide audience.