Ryan, Maggie

Pancreatic exocrine insufficiency (PEI) is an under-recognised cause of chronic diarrhoea in patients with neuroendocrine tumours (NETs). If left untreated or undertreated, PEI can lead to complications such as oxalate nephropathy (ON), which may result in loss of kidney function and potentially limit oncologic treatment options, including peptide receptor radionuclide therapy (PRRT). We present a man in his late 60s with a small bowel NET who developed persistent, uncontrolled diarrhoea for several years. The diarrhoea was attributed to multiple factors, including secretory NET (ie, carcinoid syndrome), bile acid diarrhoea and PEI secondary to somatostatin analogue therapy. Due to financial constraints, the patient was unable to consistently take pancreatic enzyme replacement therapy (PERT). Years after the diagnosis of NET, the patient developed a new onset worsening of kidney function. Further work-up, including a kidney biopsy, confirmed ON, which significantly limited subsequent treatment options, including PRRT. Routine screening for PEI and early initiation of PERT should be considered in all NET patients with chronic diarrhoea to prevent ON and preserve future treatment options.

AbstractBackgroundComputer‐assisted scoring is gaining prominence in the evaluation of renal histology; however, much of the focus has been on identifying larger objects such as glomeruli. Total inflammation impacts graft outcome, and its quantification requires tools to identify objects at the cellular level or smaller. The goal of the current study was to use CD45 stained slides coupled with image analysis tools to quantify the amount of non‐glomerular inflammation within the cortex.MethodsSixty renal transplant whole slide images were used for digital image analysis. Multiple thresholding methods using pixel intensity and object size were used to identify inflammation in the cortex. Additionally, convolutional neural networks were used to separate glomeruli from other objects in the cortex. This combined measure of inflammation was then correlated with rescored Banff total inflammation classification and outcomes.ResultsIdentification of glomeruli on biopsies had high fidelity (mean pixelwise dice coefficient of .858). Continuous total inflammation scores correlated well with Banff rescoring (maximum Pearson correlation .824). A separate set of thresholds resulted in a significant correlation with alloimmune graft loss.ConclusionsAutomated scoring of inflammation showed a high correlation with Banff scoring. Digital image analysis provides a powerful tool for analysis of renal pathology, not only because it is reproducible and can be automated, but also because it provides much more granular data for studies.