Automated, quantitative assessment of epidermal necrosis expression resulting from skin exposure to beta radiation
| Autor: | J. Daniel Bourland, Olga V Pen, Nancy D. Kock, Peter A Antinozzi, Mac B. Robinson, Jeffrey S. Willey |
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| Rok vydání: | 2019 |
| Předmět: |
Swine
0206 medical engineering 02 engineering and technology Sample pool 030218 nuclear medicine & medical imaging Automation Necrosis 03 medical and health sciences 0302 clinical medicine Biopsy Quantitative assessment Animals Medicine Grading (tumors) General Nursing Skin medicine.diagnostic_test business.industry Skin exposure Significant difference 020601 biomedical engineering Beta Particles Pathologists Radiation Injuries Experimental Epidermal necrosis Automated algorithm Feasibility Studies Female business Algorithms Biomedical engineering |
| Zdroj: | Biomedical Physics & Engineering Express. 6:015007 |
| ISSN: | 2057-1976 |
| DOI: | 10.1088/2057-1976/ab5612 |
| Popis: | Purpose Radiation skin injuries are difficult to quantitatively assess. Various scoring scales exist based on visual images and can be used in quantitative form for histological scoring. As an alternative to human scoring systems, an automated, quantitative system is proposed to provide unbiased scoring of radiation skin injury biopsy samples, with comparisons to human-based scoring systems. Materials and methods A unique algorithm was developed and tested on a sample pool obtained from in-vivo beta radiation experiments with a porcine model. The grading results achieved by the developed algorithm and those provided by an expert histopathologist are compared. Results The extent of the epidermal necrosis is quantified in terms of the number of dead cells and their respective distribution across the length of the samples. The accuracy of the grading performed by the automated algorithm is comparable to that of a trained histopathologist, as demonstrated by statistically significant difference between the grades. Conclusions This study demonstrates the feasibility of the proposed method as a potential tool designed to aid in the histopathological analysis of the tissues affected by beta radiation exposure. An expanded study with a larger sample pool is recommended to further improve the accuracy of the proposed algorithm. |
| Databáze: | OpenAIRE |
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