Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies
Yi Z, Salem F, Menon MC, Keung K, Xi C, Hultin S, Haroon Al Rasheed MR, Li L, Su F, Sun Z, Wei C, Huang W, Fredericks S, Lin Q, Banu K, Wong G, Rogers NM, Farouk S, Cravedi P, Shingde M, Smith RN, Rosales IA, O'Connell PJ, Colvin RB, Murphy B, Zhang W. Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies. Kidney International 2021, 101: 288-298. PMID: 34757124, PMCID: PMC10285669, DOI: 10.1016/j.kint.2021.09.028.Peer-Reviewed Original ResearchConceptsGraft lossTransplant biopsiesDamage scoreBanff scoresPathological lesionsOne-year graft lossPost-transplant graft lossGlomerular filtration rate declineIntermediate-risk groupKidney allograft failurePost-transplant biopsiesKidney transplant biopsiesMononuclear leukocyte infiltrationTissue compartmentsMononuclear leukocyte infiltrateProtocol biopsiesAllograft failureTransplant recipientsClinical predictorsTubular atrophyGraft damageRisk stratificationInterstitial fibrosisLeukocyte infiltrationLeukocyte infiltrate