Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model
In clinical and experimental human pancreatic islet transplantations, establishing pretransplant assessments that accurately predict transplantation outcomes is crucial. Conventional in vitro viability assessment that relies on manual counting of viable islets is a routine pretransplant assessment....
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2020-05-01
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| Series: | Cell Transplantation |
| Online Access: | https://doi.org/10.1177/0963689720919444 |
| _version_ | 1818119125362278400 |
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| author | Mayra Salgado Nelson Gonzalez Leonard Medrano Jeffrey Rawson Keiko Omori Meirigeng Qi Ismail Al-Abdullah Fouad Kandeel Yoko Mullen Hirotake Komatsu |
| author_facet | Mayra Salgado Nelson Gonzalez Leonard Medrano Jeffrey Rawson Keiko Omori Meirigeng Qi Ismail Al-Abdullah Fouad Kandeel Yoko Mullen Hirotake Komatsu |
| author_sort | Mayra Salgado |
| collection | DOAJ |
| description | In clinical and experimental human pancreatic islet transplantations, establishing pretransplant assessments that accurately predict transplantation outcomes is crucial. Conventional in vitro viability assessment that relies on manual counting of viable islets is a routine pretransplant assessment. However, this method does not correlate with transplantation outcomes; to improve the method, we recently introduced a semi-automated method using imaging software to objectively determine area-based viability. The goal of the present study was to correlate semi-automated viability assessment with posttransplantation outcomes of human islet transplantations in diabetic immunodeficient mice, the gold standard for in vivo functional assessment of isolated human islets. We collected data from 61 human islet isolations and 188 subsequent in vivo mouse transplantations. We assessed islet viability by fluorescein diacetate and propidium iodide staining using both the conventional and semi-automated method. Transplantations of 1,200 islet equivalents under the kidney capsule were performed in streptozotocin-induced diabetic immunodeficient mice. Among the pretransplant variables, including donor factors and post-isolation assessments, viability measured using the semi-automated method demonstrated a strong influence on in vivo islet transplantation outcomes in multivariate analysis. We calculated an optimized cutoff value (96.1%) for viability measured using the semi-automated method and showed a significant difference in diabetes reversal rate for islets with viability above this cutoff (77% reversal) vs. below this cutoff (49% reversal). We performed a detailed analysis to show that both the objective measurement and the improved area-based scoring system, which distinguished between small and large islets, were key features of the semi-automated method that allowed for precise evaluation of viability. Taken together, our results suggest that semi-automated viability assessment offers a promising alternative pretransplant assessment over conventional manual assessment to predict human islet transplantation outcomes. |
| first_indexed | 2024-12-11T05:05:14Z |
| format | Article |
| id | doaj.art-c7cb8a39c60b45a99de58012b10d4783 |
| institution | Directory Open Access Journal |
| issn | 1555-3892 |
| language | English |
| last_indexed | 2024-12-11T05:05:14Z |
| publishDate | 2020-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Cell Transplantation |
| spelling | doaj.art-c7cb8a39c60b45a99de58012b10d47832022-12-22T01:20:03ZengSAGE PublishingCell Transplantation1555-38922020-05-012910.1177/0963689720919444Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse ModelMayra Salgado0Nelson Gonzalez1Leonard Medrano2Jeffrey Rawson3Keiko Omori4Meirigeng Qi5Ismail Al-Abdullah6Fouad Kandeel7Yoko Mullen8Hirotake Komatsu9 Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA Department of Translational Research & Cellular Therapeutics, Beckman Research Institute of City of Hope, Duarte, CA, USA In clinical and experimental human pancreatic islet transplantations, establishing pretransplant assessments that accurately predict transplantation outcomes is crucial. Conventional in vitro viability assessment that relies on manual counting of viable islets is a routine pretransplant assessment. However, this method does not correlate with transplantation outcomes; to improve the method, we recently introduced a semi-automated method using imaging software to objectively determine area-based viability. The goal of the present study was to correlate semi-automated viability assessment with posttransplantation outcomes of human islet transplantations in diabetic immunodeficient mice, the gold standard for in vivo functional assessment of isolated human islets. We collected data from 61 human islet isolations and 188 subsequent in vivo mouse transplantations. We assessed islet viability by fluorescein diacetate and propidium iodide staining using both the conventional and semi-automated method. Transplantations of 1,200 islet equivalents under the kidney capsule were performed in streptozotocin-induced diabetic immunodeficient mice. Among the pretransplant variables, including donor factors and post-isolation assessments, viability measured using the semi-automated method demonstrated a strong influence on in vivo islet transplantation outcomes in multivariate analysis. We calculated an optimized cutoff value (96.1%) for viability measured using the semi-automated method and showed a significant difference in diabetes reversal rate for islets with viability above this cutoff (77% reversal) vs. below this cutoff (49% reversal). We performed a detailed analysis to show that both the objective measurement and the improved area-based scoring system, which distinguished between small and large islets, were key features of the semi-automated method that allowed for precise evaluation of viability. Taken together, our results suggest that semi-automated viability assessment offers a promising alternative pretransplant assessment over conventional manual assessment to predict human islet transplantation outcomes.https://doi.org/10.1177/0963689720919444 |
| spellingShingle | Mayra Salgado Nelson Gonzalez Leonard Medrano Jeffrey Rawson Keiko Omori Meirigeng Qi Ismail Al-Abdullah Fouad Kandeel Yoko Mullen Hirotake Komatsu Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model Cell Transplantation |
| title | Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model |
| title_full | Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model |
| title_fullStr | Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model |
| title_full_unstemmed | Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model |
| title_short | Semi-Automated Assessment of Human Islet Viability Predicts Transplantation Outcomes in a Diabetic Mouse Model |
| title_sort | semi automated assessment of human islet viability predicts transplantation outcomes in a diabetic mouse model |
| url | https://doi.org/10.1177/0963689720919444 |
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