Evaluating lupus nephritis presents significant challenges, with pathological evaluation requiring the participation of experienced pathologists, as well as being timeconsuming and prone to human error and misjudgement. Here, Wei Juan Wong explains how a combination of whole-slide imaging and artificial intelligence accelerates this important work.
Lupus nephritis (LN) is a chronic inflammatory kidney disease. It occurs when lupus autoantibodies affect structures in the kidneys that filter out waste. In addition to kidney inflammation, LN can lead to blood/protein in urine, high blood pressure, impaired kidney function, or even kidney failure. Up to 30% of LN patients develop kidney failure,1 after which only dialysis or kidney transplant treatment is possible.
Lupus nephritis occurs frequently (40–60%) in people who have systemic lupus erythematosus (SLE),2 which is more commonly known as lupus. A goal of lupus research is to accelerate the process of identifying and evaluating LN in biopsied samples to increase the potential for early detection and help improve the disease prognosis.
This article explores the challenges of evaluating LN and ways to overcome them with modern research tools. Discover how a combination of whole-slide imaging and artificial intelligence (AI) accelerates this important work.
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