[Artificial intelligence in kidney transplant pathology]

BACKGROUND

Artificial intelligence (AI) systems have showed promising results in digital pathology, including digital nephropathology and specifically also kidney transplant pathology.

AIM

Summarize the current state of research and limitations in the field of AI in kidney transplant pathology diagnostics and provide a future outlook.

MATERIALS AND METHODS

Literature search in PubMed and Web of Science using the search terms "deep learning", "transplant", and "kidney". Based on these results and studies cited in the identified literature, a selection was made of studies that have a histopathological focus and use AI to improve kidney transplant diagnostics.

RESULTS AND CONCLUSION

Many studies have already made important contributions, particularly to the automation of the quantification of some histopathological lesions in nephropathology. This likely can be extended to automatically quantify all relevant lesions for a kidney transplant, such as Banff lesions. Important limitations and challenges exist in the collection of representative data sets and the updates of Banff classification, making large-scale studies challenging. The already positive study results make future AI support in kidney transplant pathology appear likely.

Next-Generation Morphometry for pathomics-data mining in histopathology

Pathology diagnostics relies on the assessment of morphology by trained experts, which remains subjective and qualitative. Here we developed a framework for large-scale histomorphometry (FLASH) performing deep learning-based semantic segmentation and subsequent large-scale extraction of interpretable, quantitative, morphometric features in non-tumour kidney histology. We use two internal and three external, multi-centre cohorts to analyse over 1000 kidney biopsies and nephrectomies. By associating morphometric features with clinical parameters, we confirm previous concepts and reveal unexpected relations. We show that the extracted features are independent predictors of long-term clinical outcomes in IgA-nephropathy. We introduce single-structure morphometric analysis by applying techniques from single-cell transcriptomics, identifying distinct glomerular populations and morphometric phenotypes along a trajectory of disease progression. Our study provides a concept for Next-generation Morphometry (NGM), enabling comprehensive quantitative pathology data mining, i.e., pathomics.

MO062: Pan-Disease Segmentation and Feature Extraction for Large-Scale Digital Nephropathology

BACKGROUND AND AIMS

Nephropathology is essential for the diagnosis of kidney diseases. Deep learning-based image analyses, including segmentation of kidney histology, open new possibilities for reproducible quantitative precision pathology. Current segmentation approaches in kidney histology focused on specific use cases. Here, we developed a framework for automated segmentation and quantification of a wide spectrum of non-neoplastic kidney diseases.

METHOD

We trained U-Net Convolutional Neural Networks (CNNs) for two streamlined tasks: (i) detection of kidney tissue and (ii) instance segmentation of relevant histological structures, i.e. glomeruli, tubules and arteries. These were used to segment 1103 Whole-Slide-Images (WSIs) from four cohorts, including two external datasets for multi-center validation. In total, 35 features from 51 445 glomeruli, 4016 792 tubules and 362 471 arteries were extracted, generating 30 million morphometric data points. Morphometry data were associated with clinical and pathology data.

RESULTS

Kidney tissue was precisely outlined by the tissue segmentation CNN. The structure segmentation CNN for histology provided accurate results on WSI-level despite difficult histopathological morphologies such as crescents, segmental sclerosis, tubular casts or arteriosclerosis. Quantitative analyses of morphological alterations of glomeruli revealed, for example, an increased glomerular area in membranous glomerulonephritis and all cases characterized with nephrotic range proteinuria independent of the underlying disease, and decrease in glomerular tuft circularity in pauci-immune glomerulonephritis, especially in cases with severe loss of kidney function. Principal component analysis of multiple glomerular, tubular and interstitial features stratified based on estimated glomerular filtration rate identified CKD-relevant morphological alterations of glomeruli and the tubulointerstitium. Image extraction of morphometric outliers enabled fast-track visual assessment of severe lesions.

CONCLUSION

Segmentation and large-scale quantitative feature extraction enable reproducible quantitative analysis of kidney morphology, opening new possibilities for digital precision nephropathology.

Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology

Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to routine use, it is important to evaluate their predictive performance and obtain regulatory approval. This assessment requires appropriate test datasets. However, compiling such datasets is challenging and specific recommendations are missing. A committee of various stakeholders, including commercial AI developers, pathologists, and researchers, discussed key aspects and conducted extensive literature reviews on test datasets in pathology. Here, we summarize the results and derive general recommendations on compiling test datasets. We address several questions: Which and how many images are needed? How to deal with low-prevalence subsets? How can potential bias be detected? How should datasets be reported? What are the regulatory requirements in different countries? The recommendations are intended to help AI developers demonstrate the utility of their products and to help pathologists and regulatory agencies verify reported performance measures. Further research is needed to formulate criteria for sufficiently representative test datasets so that AI solutions can operate with less user intervention and better support diagnostic workflows in the future.

Genetic polymorphisms of the DNA repair gene MPG may be associated with susceptibility to rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease and can lead to deformities and severe disabilities, due to irreversible damage of tendons, joints, and bones. A previous study indicated that a DNA repair system was involved in the development of RA. In this study, we investigated the association of four N-methylpurine-DNA glycosylase (MPG) gene polymorphisms (rs3176364, rs710079, rs2858056, and rs2541632) with susceptibility to RA in 384 Taiwanese individuals (192 RA patients and 192 control subjects). Our data show a statistically significant difference in genotype frequency distributions at rs710079 and rs2858056 SNPs between RA patients and control groups (P = 0.040 and 0.029, respectively). Our data also indicated that individuals with the GG genotype at rs2858056 SNP may have a higher risk of developing RA. In addition, compared with the haplotype frequencies between case and control groups, individuals with the GCGC haplotype appeared to be at a greater risk of RA progression (P = 0.003, OR = 1.75; 95% CI = 1.20-1.55). Our results suggest that rs710079 and rs2858056 polymorphisms and the GCGC haplotype in the MPG gene are associated with the risk of RA progression, and thus may be used as molecular markers of RA if they are confirmed by further research.

Increased phonon scattering by nanograins and point defects in nanostructured silicon with a low concentration of germanium

The mechanism for phonon scattering by nanostructures and by point defects in nanostructured silicon (Si) and the silicon germanium (Ge) alloy and their thermoelectric properties are investigated. We found that the thermal conductivity is reduced by a factor of 10 in nanostructured Si in comparison with bulk crystalline Si. However, nanosize interfaces are not as effective as point defects in scattering phonons with wavelengths shorter than 1 nm. We further found that a 5 at. % Ge replacing Si is very efficient in scattering phonons shorter than 1 nm, resulting in a further thermal conductivity reduction by a factor of 2, thereby leading to a thermoelectric figure of merit 0.95 for Si95Ge5, similar to that of large grained Si80Ge20 alloys.

Interactions between a rotating polarized sphere and a stationary one in an electric field

Precise measurement of the attracting force between two polarized spheres inside an electric field indicates that the rotation of one sphere along the axis perpendicular to the electric field reduces the attracting force between them. The important difference between the experimental results and the existing theory indicated that this reduction is due to several factors. In addition to the reduction of polarization due to the free surface charges, the rotation may also weaken the local field near the rotating sphere, making the main contribution to the reduction of the attracting force. Moreover, the experiment also suggests that the polarization due to the molecular polarizability cannot be ignored.

Pathogenicity and drug susceptibility of the Pasteurella anatis isolated in chickens in Taiwan

A strain of Pasteurella anatis (PA) was isolated from the sinus of an adult leghorn laying chicken with sinusitis, nasal discharge, drop in egg production, and low mortality, symptoms initially thought to indicate infectious coryza. The tiny, smooth, whitish colonies were identified as PA. To compare its pathogenicity with that of commercial broilers, nine groups, 10 birds per group, of 10-day-old broilers were individually inoculated with the strain of PA, Pasteurella multocida (PM), or Escherichia coli (EC) by intravenous, intraperitoneal, intramuscular, or subcutaneous inoculation. The PA was determined to cause the signs, lesions, and septicemic death, which are similar to the symptoms of PM or EC infection. At 1 wk postinfection (PI), the mortality rate was between that of PM and EC infection at 1 wk PI. Twenty antimicrobial-containing discs were evaluated, and the isolate was highly sensitive to cetiofer, amoxicillin, lincopectin, and furazolidone. Furthermore, it was moderately sensitive to tetracycline and enrofloxacin and only slightly sensitive to cephalothin, chloramphenicol, flumequine, nalidixic acid, neomycin, oxolinic acid, streptomycin, and trimethoprim. The PA infection was treated successfully with amoxicillin.

Temporal trends and molecular epidemiology of HIV-1 infection in Taiwan from 1988 to 1998

Eight hundred and seventy-nine HIV-1-infected patients (comprising 46% of reported HIV-1/AIDS cases in Taiwan) were recruited for this study of the molecular epidemiology of HIV-1 in Taiwan from 1988 to 1998. HIV-1 subtypes were determined using a modified peptide-enzyme immunoassay complemented with DNA sequencing and phylogenetic analysis. Of the 807 HIV-1 infected men, 68.2% were infected with HIV-1B, 29.5% with HIV-1 circulating recombinant form (CRF)01_AE and 2.3% with other subtypes. Of the 72 HIV-1-infected women, 72.2% were infected with HIV-1 CRF01_AE, 13.9% with HIV-1B, and 13.9% with other subtypes. All of 8 foreign-born, Southeast Asian women and 6 of 7 (85.7%) Taiwan-native female commercial sex workers were infected with HIV-1 CRF01_AE. Fourteen of the 33 (42.4%) heterosexual married men with CRF01_AE had transmitted HIV-1 to their wives, whereas only 1 of 17 (5.9%) men with HIV-1 B had transmitted HIV-1 to their spouses (p < .01). Of 18 heterosexual male injecting drug users, 1 of 12 (8.5%) with HIV-1B and 5 of 6 (83.3%) with HIV-1 CRF01_AE had had sexual contact with female commercial sex workers (p < .01). Therefore, in this population, CRF01_AE was preferentially associated with heterosexual risk groups, a finding compatible with differences in transmission capability between B and non-B subtypes.