Dataset Information

Renal Medullary and Cortical Correlates in Fibrosis, Epithelial Mass, Microvascularity, and Microanatomy Using Whole Slide Image Analysis Morphometry.

ABSTRACT: Renal tubulointerstitial injury often leads to interstitial fibrosis and tubular atrophy (IF/TA). IF/TA is typically assessed in the renal cortex and can be objectively quantitated with computerized image analysis (IA). However, the human medulla accounts for a substantial proportion of the nephron; therefore, medullary scarring will have important cortical consequences and may parallel overall chronic renal injury. Trichrome, periodic acid-Schiff (PAS), and collagen III immunohistochemistry (IHC) were visually examined and quantitated on scanned whole slide images (WSIs) (N = 67 cases). When tuned to measure fibrosis, IA of trichrome and Trichrome-PAS (T-P) WSIs correlated for all anatomic compartments (among cortex, medulla, and entire tissue, r = 0.84 to 0.89, P all <0.0001); and collagen III deposition correlated between compartments (r = 0.69 to 0.89, P <0.0001 to 0.0002); however, trichrome and T-P measures did not correlate with collagen deposition, suggesting heterogeneous contributions to extracellular matrix deposition. Epithelial cell mass (EPCM) correlated between cortex and medulla when measured with cytokeratin IHC and with the trichrome red portion (r = 0.85 and 0.66, respectively, all P < 0.0001). Visual assessment also correlated between compartments for fibrosis and EPCM. Correlations were found between increasing medullary inner stripe (IS) width and fibrosis in all of the tissue and the medulla by trichrome morphometry (r = 0.56, P < 0.0001, and r = 0.48, P = 0.00008, respectively). Weak correlations were found between increasing IS width and decreasing visual assessment of all tissue EPCM. Microvessel density (MVD) and microvessel area (MVA) measured using a MVD algorithm applied to CD34 IHC correlated significantly between all compartments (r = 0.76 to 0.87 for MVD and 0.71 to 0.87 for MVA, P all < 0.0001). Overall, these findings demonstrate the interrelatedness of the cortex and medulla and the importance of considering the renal parenchyma as a whole.

SUBMITTER: Farris AB

PROVIDER: S-EPMC5004931 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Renal Medullary and Cortical Correlates in Fibrosis, Epithelial Mass, Microvascularity, and Microanatomy Using Whole Slide Image Analysis Morphometry.

Farris Alton B AB Ellis Carla L CL Rogers Thomas E TE Lawson Diane D Cohen Cynthia C Rosen Seymour S

PloS one 20160830 8

Renal tubulointerstitial injury often leads to interstitial fibrosis and tubular atrophy (IF/TA). IF/TA is typically assessed in the renal cortex and can be objectively quantitated with computerized image analysis (IA). However, the human medulla accounts for a substantial proportion of the nephron; therefore, medullary scarring will have important cortical consequences and may parallel overall chronic renal injury. Trichrome, periodic acid-Schiff (PAS), and collagen III immunohistochemistry (IH ...[more]

PMID: 27575381

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Project description:For a method to be widely adopted in medical research or clinical practice, it needs to be reproducible so that clinicians and regulators can have confidence in its use. Machine learning and deep learning have a particular set of challenges around reproducibility. Small differences in the settings or the data used for training a model can lead to large differences in the outcomes of experiments. In this work, three top-performing algorithms from the Camelyon grand challenges are reproduced using only information presented in the associated papers and the results are then compared to those reported. Seemingly minor details were found to be critical to performance and yet their importance is difficult to appreciate until the actual reproduction is attempted. We observed that authors generally describe the key technical aspects of their models well but fail to maintain the same reporting standards when it comes to data preprocessing which is essential to reproducibility. As an important contribution of the present study and its findings, we introduce a reproducibility checklist that tabulates information that needs to be reported in histopathology ML-based work in order to make it reproducible. Author summary For a method to be used a lot in medical research or clinical practice, it needs to be able to be reproduced so that people can trust it. Machine learning and deep learning have some challenges around this. For example, small changes in how a model is trained can lead to significant changes in the results of experiments. This makes it essential that researchers report how they do things in enough detail for the results of their experiments to be reproducible. In this work, we looked at three different algorithms used for digital pathology image analysis. We tried to reproduce them using only the information reported in their papers. We confirmed that even minor details could be essential. Authors often do not report all the details needed to reproduce their work. We also created a checklist of things that need to be reported to help other researchers make their work reproducible.

Dataset Information

Renal Medullary and Cortical Correlates in Fibrosis, Epithelial Mass, Microvascularity, and Microanatomy Using Whole Slide Image Analysis Morphometry.

Publications

Renal Medullary and Cortical Correlates in Fibrosis, Epithelial Mass, Microvascularity, and Microanatomy Using Whole Slide Image Analysis Morphometry.

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