Identification of Gastritis Subtypes by Convolutional Neuronal Networks on Histological Images of Antrum and Corpus Biopsies
Abstract
:1. Introduction
2. Results
2.1. Patient Cohort, Annotation, Image Patches Extraction and Subset Analysis
2.2. CNN Training, Validation, and Model Selection
2.2.1. Antrum Classification Model
2.2.2. Corpus Classification Model
2.3. Image Patch Prediction Results for the Validation and Test Set
3. Discussion
4. Materials and Methods
4.1. Patient Cohort and Scanning of Tissue Slides
4.2. Region Annotation and Image Patch Extraction
4.3. Nomenclature of Image Patches and Encoding of Diagnosis
4.4. Hardware and Software
4.5. Analytical Subsets
4.6. Convolutional Neuronal Networks
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Set/Region | Antrum Image Patches, n (%) | Corpus Image Patches, n (%) |
---|---|---|
Overall (patients n = 135, image patches n = 1230) | 682 | 548 |
Training (patients n = 62 with both) | (+19 patients with only antrum) | (+11 patients with only corpus) |
LI | 265 (57) | 133 (37) |
SI | 197 (43) | 108 (30) |
A gastritis | / | 122 (34) |
Validation (patients n = 21) | ||
LI | 64 (57) | 21 (25) |
SI | 48 (43) | 29 (35) |
A gastritis | / | 34 (41) |
Test (patients n = 22) | ||
LI | 84 (78) | 38 (38) |
SI | 24 (22) | 14 (14) |
A gastritis | / | 49 (49) |
Antrum Classifier | Corpus Classifier | ||||
---|---|---|---|---|---|
Confusion Matrix (by Image Patches) | LI Predicted | SI Predicted | LI Predicted | SI Predicted | A Gastritis Predicted |
LI true | 54 | 10 | 27 | 3 | 4 |
SI true | 16 | 32 | 0 | 21 | 0 |
A gastritis true | / | / | 5 | 16 | 8 |
Statistics | |||||
Accuracy (95% CI) | 0.77 (0.68–0.84) | 0.67 (0.55–0.77) | |||
Classes | LI vs. SI | LI vs. other | SI vs. other | A gastritis vs. other | |
Sensitivity | 0.77 | 0.53 | 0.67 | 0.84 | |
Specificity | 0.76 | 1.00 | 0.71 | 0.87 | |
Positive predictive value | 0.84 | 1.00 | 0.28 | 0.79 | |
Negative predictive value | 0.67 | 0.70 | 0.93 | 0.90 |
Antrum Classifier | Corpus Classifier | ||||
---|---|---|---|---|---|
Confusion Matrix (by Image Patches) | LI Predicted | SI Predicted | LI Predicted | SI Predicted | A Gastritis Predicted |
LI true | 76 | 8 | 27 | 20 | 2 |
SI true | 8 | 16 | 6 | 26 | 6 |
A gastritis true | / | / | 7 | 3 | 4 |
Statistics | |||||
Accuracy (95% CI) | 0.85 (0.77–0.91) | 0.56 (0.46–0.66) | |||
Classes | LI vs. SI | LI vs. other | SI vs. other | A gastritis vs. other | |
Sensitivity | 0.90 | 0.53 | 0.33 | 0.68 | |
Specificity | 0.67 | 0.77 | 0.89 | 0.64 | |
Positive predictive value | 0.90 | 0.68 | 0.29 | 0.55 | |
Negative predictive value | 0.67 | 0.63 | 0.91 | 0.75 |
Gastritis Classifier | |||
---|---|---|---|
Confusion Matrix (by Patient, n = 17) | A Gastritis Predicted | B Gastritis Predicted | C Gastritis Predicted |
A gastritis true | 7 | 0 | 1 |
B gastritis true | 1 | 3 | 0 |
C gastritis true | 0 | 0 | 5 |
Statistics | |||
Accuracy (95% CI) | 0.84 (0.64–0.96) | ||
Classes | A vs. other | B vs. other | C vs. other |
Sensitivity | 0.88 | 1.00 | 0.83 |
Specificity | 0.89 | 0.93 | 1.00 |
Positive predictive value | 0.88 | 0.75 | 1.00 |
Negative predictive value | 0.89 | 1.00 | 0.92 |
Overall Gastritis Diagnosis | Antrum Finding/Classifier Result | Corpus Finding/Classifier Result |
---|---|---|
A | SI | A gastritis |
B | SI | SI |
B | SI | LI |
A | LI | A gastritis |
B | LI | SI |
C | LI | LI |
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Steinbuss, G.; Kriegsmann, K.; Kriegsmann, M. Identification of Gastritis Subtypes by Convolutional Neuronal Networks on Histological Images of Antrum and Corpus Biopsies. Int. J. Mol. Sci. 2020, 21, 6652. https://doi.org/10.3390/ijms21186652
Steinbuss G, Kriegsmann K, Kriegsmann M. Identification of Gastritis Subtypes by Convolutional Neuronal Networks on Histological Images of Antrum and Corpus Biopsies. International Journal of Molecular Sciences. 2020; 21(18):6652. https://doi.org/10.3390/ijms21186652
Chicago/Turabian StyleSteinbuss, Georg, Katharina Kriegsmann, and Mark Kriegsmann. 2020. "Identification of Gastritis Subtypes by Convolutional Neuronal Networks on Histological Images of Antrum and Corpus Biopsies" International Journal of Molecular Sciences 21, no. 18: 6652. https://doi.org/10.3390/ijms21186652