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Emerging therapies

Emerging therapies

From photo, to 3D model, through to wound healing

Peyman Gholami from the University of Waterloo. The collaborators on this work are Mohammad Ali Ahmadi Pajouh, Nabiollah Abolfathi, Ghassan Hamarneh and Mohammad Kayvanrad.

A research team headed up at Amirkabir University of Technology in Iran has proposed a novel approach to chronic wound healing. Peyman Gholami and collaborators introduced a framework to produce biologically compatible 3D prints of deep chronic wounds. Such custom made wound fillings could potentially aid with the healing process (IEEE J. Biomed. Health. Informatics doi: 10.1109/JBHI.2017.2743526).

The research group aims to provide a proof-of-concept that integrates various technologies into a unified solution. Such technologies include the almost automatic identification of the wound, the automatic creation of a 3D model and the bioprinting of this model. While these technologies are established in their respective fields, it is their merging that provides a semi-automatic solution to chronic wound healing.

The framework used to produce 3D prints of wounds

An interdisciplinary framework

Gholami’s work begins with an image of a chronic wound found on the body. After applying the pre-processing procedure, the user segments the wound using the LiveWire algorithm, which creates a mask of the wound with minimal user interaction. Once this mask is generated, the image is calibrated to measurements of the height and width of the wound, matching the pixels in the image to the actual size in millimetres. Alongside the measurements of the wound, external measurements of the depth are input into a software system that produces a 3D model of the wound that is compatible with a 3D printer.

The group chose the LiveWire algorithm following comparison with other common segmentation techniques, due to the high values it achieved on baseline performance indicators, including a score of over 97% in accuracy. The other segmentation algorithms examined included region-growing, active contours, Level set, and texture segmentation.

Using the wound coordinates generated from the segmented image and depth information, the researchers produced the computer instructions, containing G-code, for the bioprinting robot. They printed the wound model using bio-ink hydrogel, which consisted of alginate and gelatine, and was then used for cell encapsulation.

Wounds that won’t heal

A recent study on chronic wound detection explains that dealing with chronic wounds is a challenging task for skin pathologists and dermatologists (Wound Repair Regen. 24 181). In normal scenarios, a wound evolves through a set of phases that signify different processes being carried out. Chronic wounds comprise cases where the wound is stuck in one of the phases and doesn’t close or heal properly. Causes include factors such as poor circulation, but can sometimes be linked to other conditions.

Gholami and his collaborators used wound images from patients with diabetes, burns and metabolic conditions – which cause granulation and slough – and metabolic conditions that can cause tissue death. The proposed framework provides a good approach for producing custom made wound fillings.

 

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