Properties of the Vascular Networks in Malignant Tumors
This work presents an analysis for real and synthetic angiogenic networks using a tomography image that obtains a portrait of a vascular network. After the image conversion into a binary format it is possible to measure various network properties, which includes the average path length, the clusteri...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-01-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/22/2/166 |
| _version_ | 1828354550487056384 |
|---|---|
| author | Juan Carlos Chimal-Eguía Erandi Castillo-Montiel Ricardo T. Paez-Hernández |
| author_facet | Juan Carlos Chimal-Eguía Erandi Castillo-Montiel Ricardo T. Paez-Hernández |
| author_sort | Juan Carlos Chimal-Eguía |
| collection | DOAJ |
| description | This work presents an analysis for real and synthetic angiogenic networks using a tomography image that obtains a portrait of a vascular network. After the image conversion into a binary format it is possible to measure various network properties, which includes the average path length, the clustering coefficient, the degree distribution and the fractal dimension. When comparing the observed properties with that produced by the Invasion Percolation algorithm (IPA), we observe that there exist differences between the properties obtained by the real and the synthetic networks produced by the IPA algorithm. Taking into account the former, a new algorithm which models the expansion of an angiogenic network through randomly heuristic rules is proposed. When comparing this new algorithm with the real networks it is observed that now both share some properties. Once creating synthetic networks, we prove the robustness of the network by subjecting the original angiogenic and the synthetic networks to the removal of the most connected nodes, and see to what extent the properties changed. Using this concept of robustness, in a very naive fashion it is possible to launch a hypothetical proposal for a therapeutic treatment based on the robustness of the network. |
| first_indexed | 2024-04-14T02:26:29Z |
| format | Article |
| id | doaj.art-5f108641160644a6a3360186637e98ed |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-14T02:26:29Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-5f108641160644a6a3360186637e98ed2022-12-22T02:17:52ZengMDPI AGEntropy1099-43002020-01-0122216610.3390/e22020166e22020166Properties of the Vascular Networks in Malignant TumorsJuan Carlos Chimal-Eguía0Erandi Castillo-Montiel1Ricardo T. Paez-Hernández2Centro de Investigación en Computación del Instituto Politécnico Nacional, Av. Miguel Othon de Mendizabal s/n. Col. La Escalera, Ciudad de México CP 07738, MexicoDepartment of Técnologias WEB, Instituto Politécnico Nacional (IPN) - Centro Nacional de Cálculo (CENAC), Av. Luis Enrique Erro S/N, Unidad Profesional Adolfo López Mateos, Zacatenco, Gustavo A. Madero, Ciudad de México CP 07738, MexicoÁrea de Física de Procesos Irreversibles, Departamento de Ciencias Básicas, Universidad Autónoma Metropolitana, U-Azcapotzalco, Av. San Pablo 180, Col.Reynosa, Ciudad de México CP 02200, MexicoThis work presents an analysis for real and synthetic angiogenic networks using a tomography image that obtains a portrait of a vascular network. After the image conversion into a binary format it is possible to measure various network properties, which includes the average path length, the clustering coefficient, the degree distribution and the fractal dimension. When comparing the observed properties with that produced by the Invasion Percolation algorithm (IPA), we observe that there exist differences between the properties obtained by the real and the synthetic networks produced by the IPA algorithm. Taking into account the former, a new algorithm which models the expansion of an angiogenic network through randomly heuristic rules is proposed. When comparing this new algorithm with the real networks it is observed that now both share some properties. Once creating synthetic networks, we prove the robustness of the network by subjecting the original angiogenic and the synthetic networks to the removal of the most connected nodes, and see to what extent the properties changed. Using this concept of robustness, in a very naive fashion it is possible to launch a hypothetical proposal for a therapeutic treatment based on the robustness of the network.https://www.mdpi.com/1099-4300/22/2/166complex networksangiogenesisnetwork properties |
| spellingShingle | Juan Carlos Chimal-Eguía Erandi Castillo-Montiel Ricardo T. Paez-Hernández Properties of the Vascular Networks in Malignant Tumors Entropy complex networks angiogenesis network properties |
| title | Properties of the Vascular Networks in Malignant Tumors |
| title_full | Properties of the Vascular Networks in Malignant Tumors |
| title_fullStr | Properties of the Vascular Networks in Malignant Tumors |
| title_full_unstemmed | Properties of the Vascular Networks in Malignant Tumors |
| title_short | Properties of the Vascular Networks in Malignant Tumors |
| title_sort | properties of the vascular networks in malignant tumors |
| topic | complex networks angiogenesis network properties |
| url | https://www.mdpi.com/1099-4300/22/2/166 |
| work_keys_str_mv | AT juancarloschimaleguia propertiesofthevascularnetworksinmalignanttumors AT erandicastillomontiel propertiesofthevascularnetworksinmalignanttumors AT ricardotpaezhernandez propertiesofthevascularnetworksinmalignanttumors |