Development of patient-specific 3D models from histopathological samples for applications in radiation therapy
•Cell and nucleus size may impact the biological effects of radiation therapy.•Automated methods extract cell and nucleus size from histopathological samples.•3D tissue models are developed using patient specific information.•Tissue models containing cells and nuclei have applications in microdosime...
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| Published in | Physica medica Vol. 81; pp. 162 - 169 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Italy
Elsevier Ltd
01.01.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1120-1797 1724-191X 1724-191X |
| DOI | 10.1016/j.ejmp.2020.12.009 |
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| Abstract | •Cell and nucleus size may impact the biological effects of radiation therapy.•Automated methods extract cell and nucleus size from histopathological samples.•3D tissue models are developed using patient specific information.•Tissue models containing cells and nuclei have applications in microdosimetry.
The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry.
Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples.
The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively.
Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated. |
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| AbstractList | The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated. •Cell and nucleus size may impact the biological effects of radiation therapy.•Automated methods extract cell and nucleus size from histopathological samples.•3D tissue models are developed using patient specific information.•Tissue models containing cells and nuclei have applications in microdosimetry. The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated. The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated.The biological effects of ionizing radiation depend on the tissue, tumor type, radiation quality, and patient-specific factors. Inter-patient variation in cell/nucleus size may influence patient-specific dose response. However, this variability in dose response is not well investigated due to lack of available cell/nucleus size data. The aim of this study was to develop methods to derive cell/nucleus size distributions from digital images of 2D histopathological samples and use them to build digital 3D models for use in cellular dosimetry. Nineteen of sixty hematoxylin and eosin stained lung adenocarcinoma samples investigated passed exclusion criterion to be analyzed in the study. A difference of gaussians blob detection algorithm was used to identify nucleus centers and quantify cell spacing. Hematoxylin content was measured to determine nucleus radius. Pouring simulations were conducted to generate one-hundred 3D models containing volumes of equivalent cell spacing and nuclei radius to those in histopathological samples. The nuclei radius distributions of non-tumoral and cancerous regions appearing in the same slide were significantly different (p < 0.01) in all samples analyzed. The median nuclear-cytoplasmic ratio was 0.36 for non-tumoral cells and 0.50 for cancerous cells. The average cellular and nucleus packing densities in the 3D models generated were 65.9% (SD: 1.5%) and 13.3% (SD: 0.3%) respectively. Software to determine cell spacing and nuclei radius from histopathological samples was developed. 3D digital tissue models containing volumes with equivalent cell spacing, nucleus radius, and packing density to cancerous tissues were generated. |
| Author | Camilleri-Broët, Sophie Enger, Shirin A. Torres, Jose Poole, Christopher M. Vallières, Martin Rayes, Roni F. Spicer, Jonathan D. DeCunha, Joseph M. |
| Author_xml | – sequence: 1 givenname: Joseph M. surname: DeCunha fullname: DeCunha, Joseph M. email: joseph.decunha@mail.mcgill.ca organization: Medical Physics Unit, Department of Oncology, Faculty of Medicine, McGill University, Montréal, Québec, Canada – sequence: 2 givenname: Christopher M. surname: Poole fullname: Poole, Christopher M. organization: Radiation Analytics Pty Ltd, Sunshine Coast, Australia – sequence: 3 givenname: Martin orcidid: 0000-0001-7639-8172 surname: Vallières fullname: Vallières, Martin organization: Department of Computer Science, University of Sherbrooke, Sherbrooke, Québec, Canada – sequence: 4 givenname: Jose surname: Torres fullname: Torres, Jose organization: Department of Pathology, Faculty of Medicine, McGill University, Montréal, Québec, Canada – sequence: 5 givenname: Sophie surname: Camilleri-Broët fullname: Camilleri-Broët, Sophie organization: Department of Pathology, Faculty of Medicine, McGill University, Montréal, Québec, Canada – sequence: 6 givenname: Roni F. surname: Rayes fullname: Rayes, Roni F. organization: Cancer Research Program and the LD MacLean Surgical Research Laboratories, Department of Surgery, Division of Upper GI and Thoracic Surgery, Research Institute of the McGill University Health Center, Montréal, Québec, Canada – sequence: 7 givenname: Jonathan D. surname: Spicer fullname: Spicer, Jonathan D. organization: Cancer Research Program and the LD MacLean Surgical Research Laboratories, Department of Surgery, Division of Upper GI and Thoracic Surgery, Research Institute of the McGill University Health Center, Montréal, Québec, Canada – sequence: 8 givenname: Shirin A. surname: Enger fullname: Enger, Shirin A. organization: Medical Physics Unit, Department of Oncology, Faculty of Medicine, McGill University, Montréal, Québec, Canada |
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| Keywords | Cellular dosimetry Microdosimetry Histopathology Patient-specific |
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