Delivering computationally-intensive digital patient applications to the clinic: An exemplar solution to predict femoral bone strength from CT data. (September 2021)

• Record Type: Journal Article
• Authors: Benemerito, I.; Griffiths, W.; Allsopp, J.; Furnass, W.; Bhattacharya, P.; Li, X.; Marzo, A.; Wood, S.; Viceconti, M.; Narracott, A.
• Is Part Of: Computer methods and programs in biomedicine. Volume 208(2021)
• Publication Date: 2021-09
• Subjects: Bone strength estimation -- Clinical workflow -- Decision support -- XNAT -- Finite element modelling -- Open source software; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.106200
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: A platform for estimating bone strength from medical images has been developed. Images are de-anonymised before leaving the hospital. DICOM images are automatically transferred from the hospital to the research centre. Transfer of images is based on XNAT and other open source software. Clinical personnel can obtain an estimate of the femur strength in 8 h or less. Abstract: Background and objective: Whilst fragility hip fractures commonly affect elderly people, often causing permanent disability or death, they are rarely addressed in advance through preventive techniques. Quantification of bone strength can help to identify subjects at risk, thus reducing the incidence of fractures in the population. In recent years, researchers have shown that finite element models (FEMs) of the hip joint, derived from computed tomography (CT) images, can predict bone strength more accurately than other techniques currently used in the clinic. The specialised hardware and trained personnel required to perform such analyses, however, limits the widespread adoption of FEMs in clinical contexts. In this manuscript we present CT2S (Computed Tomography To Strength), a system developed in collaboration between The University of Sheffield and Sheffield Teaching Hospitals, designed to streamline access to this complex workflow for clinical end-users. Methods: The system relies on XNAT and makes use of custom apps based on open source software. Available through a website, it allows doctors in the healthcare environment to benefit from FE based bone strength estimation without being exposed to the technical aspects, which are concealed behind a user-friendly interface. Clinicians request the analysis of CT scans of a patient through the website. Using XNAT functionality, the anonymised images are automatically transferred to the University research facility, where an operator processes them and estimates the bone strength through FEM using a combination of open source and commercial software. Following the analysis, the doctor is provided with the results in a structured report. Results: The platform, currently available for research purposes, has been deployed and fully tested in Sheffield, UK. The entire analysis requires processing times ranging from 3.5 to 8 h, depending on the available computational power. Conclusions: The short processing time makes the system compatible with current clinical workflows. The use of open source software and the accurate description of the workflow given here facilitates the deployment in other centres.