Table 1.
Summary of papers dealing with pre-transplantation phase
| Author, year | Type of digital pathology | Number of patients/biopsies | Type of biopsy | Intervention | Controls or comparisons | Outcomes/Aim of the study | Results |
|---|---|---|---|---|---|---|---|
| Minervini etal., 2001 | Static | 102 | Various case types, among which 5 donor FS liver biopsies | Consultant telepathology review | Referring pathologist original diagnosis | Agreement rates, descriptive | 86% agreement and 14% (only 3% major) disagreement between referring and consultant pathologist |
| Li etal., 2002 | LM plus DIA | 102 | Donor kidney biopsy | DIA software assessment | None | Glomerular volume and sclerosis in different age groups | Glomerular size and global sclerosis increase with age |
| Benkoel etal., 2003 | Confocal laser microscopy plus DIA | 30 | Donor liver biopsy, preimplantation and postreperfusion | DIA assessment of IHC staining for ICAM-1 | None | Difference in ICAM-1 expression between preimplantation and postreperfusion biopsies | Higher expression of ICAM-1 in sinusoidal endothelial cells in postreperfusion biopsies |
| Benkoel etal., 2003 | Confocal laser microscopy plus DIA | 30 | Donor liver biopsy, preimplantation and postreperfusion | DIA assessment of IHC staining for F-actin | None | Difference in F-actin expression between preimplantation and postreperfusion biopsies | Significantly lower expression of F-actin in postreperfusion biopsies |
| Benkoel etal., 2003 | Confocal laser microscopy plus DIA | 30 | Donor liver biopsy, preimplantation and postreperfusion | DIA assessment of IHC staining for NaK-ATPase | None | Difference in NaK-ATPase expression between preimplantation and postreperfusion biopsies | Significantly lower expression of NaK-ATPase in postreperfusion biopsies |
| Marsman etal., 2004 | LM plus DIA | 49 | Donor liver biopsy, FS | DIA software assessment | Pathologist with glass slide | Percentage of total fat, microvesicular and macrovesicular steatosis; correlation with liver function indices, graft and patient survival | Significant correlation between pathologist and software for macrovesicular steatosis and total fat; significant association of macrovesicular steatosis and graft survival both when assessed by pathologist or software |
| Niclauss etal., 2008 | Static, stereo- microscope plus DIA | 12 | Pancreatic islets preparations | Computerized by 2 software and manual counting on digital images | Manual counting at microscope | Number, islet equivalents and purity of islet preparation | Total islet number, equivalents number, and purity were much better correlated between digital manual and computerized analyses than between standard manual and computerized analyses |
| Kissler etal., 2009 | LM plus DIA | 12 | Pancreatic islets preparations | Computerized by software on digital image | Manual counting on digital image | Accuracy, intra- and inter-observer reproducibility for both modalities by means of CV | Digital image analysis is reliable for islet counting, with the advantage of permanent records and quality assurance |
| Biesterfield etal., 2012 | Static LM, point grid counting | 120 | Donor liver biopsy, cut in half for FS and FFPE | Point grid counting | Conventional LM | Interobserver agreement for FS and FFPE, correlation between macro- and micro-vesicular steatosis | Substantial agreement (κ>0.60) and high correlation (r>0.80) between observers and types of steatosis; no advantage for point grid analysis |
| Native etal., 2013 | LM plus DIA | 9 patients, 54 images |
Donor liver biopsy | Model-based segmentation method algorithm | Expert pathologists with LM | Correlation between pathologists’ assessments and automated image analysis-based evaluations of ld-MaS percentages | New algorithm proposed significantly improves separation between large and small macrovesicular lipid droplets (specificity 93.7%, sensibility 99.3%) and correlation with pathologists’ ld-MaS percentage assessments (r=0.97) |
| Gymr etal., 2015 | LM plus DIA | 42 | Pancreatic islets preparations | Automated by software on digital image | Manual counting at LM | Correlation of modalities for total islet number, equivalent number, and purity; intraobserver variability | High correlation between modalities for total islet and equivalent number; high intraobserver reproducibility for the use of software |
| Wang etal., 2015 | LM plus DIA | 25 patients, 84 samples |
Pancreatic islets preparations | Computerized by software on digital image | Manual counting on digital image | Correlation of modalities for total islet number, equivalent number, and purity | Significantly high correlation between modalities; not significant difference for total counts |
| Mammas etal., 2015 | Not clearly defined | 518 images | Donor kidney, liver and pancreas | Diagnosis on digital image on 4 different viewing devices | Diagnosis of reference pathologist, not stated if with LM or digital | Accuracy of diagnosis with different viewing devices | The desktop and the experimental telemedicine platform are more reliable than tablet and mobile phone devices |
| Buchwald etal., 2016 | LM plus DIA | 3 patients, 14 samples |
Pancreatic islets preparations | Computerized by software on digital image | Manual counting at LM | Correlation of modalities for total islet number, equivalent number, and purity; intraobserver variability | Very good overall correlation between modalities; lower intraobserver variability for DIA |
| Eccher etal., 2016 | WSI | 62 patients, 124 biopsies |
Donor kidney wedge biopsy | Pathologist with WSI | Pathologist with glass slide | Intra- and inter-observer reproducibility with weighted Cohen k index | Very high intraobserver agreement (κ=0.961) for WSI and glass slide; slightly lower (κ=0.863) interobserver agreement for WSI than glass slide (κ=0.903) |
| Osband etal., 2016 | Virtual microscope, not otherwise specified | 23 kidneys | Donor kidney wedge biopsy, FS | Experienced pathologist with virtual microscope | On-site pathologist | Time to biopsy read | Shorter time to biopsy read with virtual microscope; improved time to local acceptance but not cold ischemia time or DGF rate |
| Liapis etal., 2017 | WSI | 40 | Donor kidney biopsy | Experienced pathologist with WSI | None | Intraclass correlation coefficient for various parameters of score | Modest agreement among pathologist, only number of glomeruli, sclerosed glomeruli and interstitial fibrosis with ICC >0.5 |
| Cima etal., 2018 | WSI | 28 | 16 donor kidney wedge biopsy, FS 12 donor liver biopsy, FS | Scoring with WSI | Scoring with glass slide | Accuracy rate; intraobserver concordance with weighted Cohen k index; sensibility, specificity, PPV, NPV | 86% accuracy rate, high intraobserver concordance (κ=0.91); 96%, 75%, 96%, 75% sensibility, specificity, PPV, NPV, respectively |
| Marsh etal., 2018 | WSI | 17 patients, 48 biopsy images |
Donor kidney biopsy, FS | Patch-based model and fully convolutional model on WSI | Expert pathologist scoring with WSI | Comparison between the two models and with pathologist’s assessment on WSI in counting total glomeruli and sclerosed glomeruli | Fully convolutional model substantially outperforming the model trained on image patches of isolated glomeruli, in terms of both accuracy and speed |
CV: Coefficient of variation, DIA: Digital image analysis, FFPE: Formalin-fixed, paraffin-embedded, FS: Frozen section, LM: Light microscopy, ld-MaS: Large droplet Macrovesicular steatosis, NPV: Negative predictive value, PPV: Positive predictive value, WSI: Whole slide imaging, ICAM-1: Intercellular adhesion molecule-1, DGF: Delayed graft function, IHC: Immunohistochemistry, ICC: Islet cell counter