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Description
The project aims to develop technology for creating 3D printed custom-made fixing-stretching devices for application in acute inpatient settings. The core idea is to use the widely available 3D scanner Structure Sensor Pro to scan the affected area. The scan will be sent to technical orthopedics for creating the necessary device design. The device shall be printed out on a 3D printer and sent to the clinic.
Within the framework of the experimental development, the costs of remuneration for the project implementation staff, amortization and lease of instrument equipment licenses, outsourcing costs for prototype production and business trips, which are directly related to the development of new technology, are planned. Also, various information and communication activities of the project are planned, such as - opening and closing conference, press release, stand, plates, preparation of video and photo materials.
This technology will allow clinicians to take contact-free measurements. The design of the device will be made by a specialist, trained in creating assistive devices and considering the pressure areas and special patient needs as noted by the doctor. The material for the device is PLA, which is biologically safe, waterproof and lightweight. The device can be easily removed, cleaned and modified. Another advantage of using this technology is the ease of changing specific parameters during wound healing. Although some other splints can also be adjusted after an anatomical change (e.g., thermoplastic splints), these always require patient contact to fit perfectly.
Summary of project results
Major burn injuries result in local release of inflammatory mediators (e.g. histamine, prostaglandins, thromboxane, nitric oxide) that increase capillary permeability inducing systemic inflammatory response syndrome and massive fluid shifts, which result in burn oedema and burn shock.
During this early period in which various pathophysiological changes take place, appropriate fluid management plays a fundamental role.
Various formulas have been developed to calculate the fluid management, all based on the calculation of the percentage of the body surface area injured. Therefore, for the successful acute burn treatment it is extremely important to estimate this injured area with maximum precision.
There are several approaches used by clinicians in estimating the injured area - Lund and Browder chart, patient palm method, Rule of Nines method. Mistakes in assessment using those methods may involve the assessor (inaccurate shading of burned areas on the chart, incorrect calculations), the instrument (need to calculate in fractions, difficulty in portraying lateral areas of the body), or the patient (obesity, breast hypertrophy, amputation, etc.)
We developed a new technology- use of 3D technology for precise detection of burn area percentage of the total body surface- a precise instrument, that remarkably reduces the risk of mistakes in both determining the affected body area and mathematical calculations.
Tested and confirmed the ability of 3D scanning technology to “recognize” the burnt area in a laboratory setting as well as on the healthy volunteers.
Developed the algorithm of determining the burnt area surface using 3D scanning, which includes colour difference detection, regular and irregular areas and flat or curved surfaces
Performed full body scans and partial body scans (subject positioned on back or abdomen) of healthy volunteers.
Developed the algorithm for determining total body surface area using 3D scanning with the same scanning equipment. Given the fact that the patient''s body scan in real life will be incomplete (depending on the injury, the patient will be positioned on the hospital bed on the uninjured side and can not be moved during the scanning), the algorithm includes the correction of the incomplete scan. We verified the results with the scan results of the same study subjects provided by calibrated professional full body scanned at Riga Technical University.
Performed the analysis of the calculated relative burnt area percentage and verified the results with the ones of five different relative burnt area calculation methods.
The developed algorithm yields a precise relative burnt area calculation. Medical institutions can easily obtain and learn 3D scanning technology. To enable wide usage, the calculations must be automated—thus, machine learning using HPC (high-performance computing) must be performed as the next project. The technology development has reached stage TRL 7.
The precision of the above-mentioned burnt area determination methods highly depends on experience, which correlates to the frequency of treating such patients. The new technology will remarkably reduce the risk of mistakes and save medics valuable time. Scanning can be easily learned and is fast.
The new algorithm expands the use of 3D technology in medicine. Currently, 3D technology is most commonly used in orthopaedics and prosthetics and also in surgery in the preparation phase for complicated surgical interventions. 3D scanning and 3D printing are also used in traumatology for immobilization in fracture treatment or postoperative immobilization.
Summary of bilateral results
The input of the collaboration partner was essential to improving our knowledge of burnt injury management, which highly depends on the scope of experience dealing with burnt patients. Consultations and video conferences gave us important information about patient management challenges that we included in the algorithm development.To enable the wide usage of the developed algorithm, the calculations shall be automatized – thus, the machine learning (ML) using HPC (high-performance computing) is what we plan to perform as the next project. We aim at using HPC for calculations as full-colour scans are very large (each scan consists of millions of mesh cloud points) and can be as large as 1 gigabyte per scan per person by using ordinary handheld scanners such as Einstar Shining 3d or similar. To implement ML, we will have to provide a high number of scans to be processed and thus, desktop computers will not be powerful enough to carry out such tasks.We aim to test the automated algorithm by reviewing scans, performing manual calculations, and comparing the results with those of automated calculations. We intend to validate the results with project partners.