Portal de Periódicos da CAPES

O030 Image-analysis algorithm to determine quality of cold perfusion in kidney transplantation

2022; Oxford University Press; Volume: 109; Issue: Supplement_4 Linguagem: Inglês

10.1093/bjs/znac242.030

1365-2168

Samuel Tingle, ER Thompson, Lucy Bates, Chloe Connelly, Sam Colenutt, Martin R. Turner, Hassan Ugail, Russell Hodgetts, BM Thomson, Neil Sheerin, Colin Wilson,

Organ Transplantation Techniques and Outcomes

Abstract Introduction Surgeon assessment of visual ‘quality of perfusion’ (QOP) influences kidney discard and predicts transplant outcome. However, this assessment is subjective and bias-prone. We aimed to design an application utilising a smartphone camera to make this assessment objective and enhance decision making. Methods The QOP in photographs of backbench kidneys was graded from 1 (ideal) to 5 (very poor) by three independent surgeons. A training cohort was used to develop an image-analysis algorithm, which was validated in a separate cohort. Results Analysing surgeon scores of 174 kidney images revealed that inter-rater agreement was good for kidneys displaying the best (rated 1) and worst (rated 4 or 5) QOP. However, for intermediate scores inter-rater agreement was poor. Inter-rater agreement between surgeons decreased as they graded more images; as surgeons fatigued, their ability to classify images worsened. A training cohort (n=174 kidneys) was used for algorithm development. First, small regions within each image were mapped within the CEILAB colour-space, where well-perfused and poorly perfused areas show clear separation. To generate a score for each kidney these regions are compared with ideally flushed kidney tissue. Testing our algorithm (validation cohort - n=29 kidneys) revealed strong correlation between image-analysis QOP score and surgeon assessment, r=0.789 (0.587–0.899), P<0.001. Conclusion Surgeon inter-rater agreement on kidney QOP is low for kidneys with borderline QOP and worsens with fatigue. We provide a QOP score utilising an image-analysis algorithm, which correlates with surgeon scoring. With additional images and training this could provide an objective, numerical, point-of-care assessment of organ quality. Take-home message Current visual assessment of transplant organ quality is subjective and bias-prone. This body of work attempts to create a point-of-care image-analysis application to provide an objective numeric organ quality score.