Literature DB >> 23771073

Correlations between intratumoral vascular network and tumoral architecture in prostatic adenocarcinoma.

I E Pleşea1, A Stoiculescu, M Serbănescu, D O Alexandru, M Man, O T Pop, R M Pleşea.   

Abstract

The authors made a preliminary assessment of possible correlations between the intratumoral vascular density (IVD) and the architectural tumoral patterns described by Gleason. The studied material consisted of samples obtained by transurethral resection from 34 patients diagnosed with prostatic adenocarcinoma. Ten fields, five for dominant and five for secondary identified patterns of each case, with no necrosis were selected randomly from CD34 immunomarked sections using ×20 objective. IVD increased with Gleason pattern both for the entire group, but also for "solid" phenotype group of subtypes up to pattern 4, respectively subtype 4B. In "necrotizing" phenotype group of subtypes, IVD had a decreasing trend from the better-differentiated subtypes to the poorest one. These preliminary data showed that the intratumoral vascular network reacts differently to the loss of tumoral differentiation in the two groups of Gleason subtypes suggesting the existence of two different populations of malignant cells.

Entities:  

Mesh:

Year:  2013        PMID: 23771073

Source DB:  PubMed          Journal:  Rom J Morphol Embryol        ISSN: 1220-0522            Impact factor:   1.033


  3 in total

1.  High-frequency ultrasound: an essential non-invasive tool for the pre-therapeutic assessment of basal cell carcinoma.

Authors:  Raluca Maria Bungărdean; Mircea Sebastian Şerbănescu; Horaţiu Alexandru Colosi; Maria Crişan
Journal:  Rom J Morphol Embryol       Date:  2021 Apr-Jun       Impact factor: 1.033

2.  Nodular and Micronodular Basal Cell Carcinoma Subtypes Are Different Tumors Based on Their Morphological Architecture and Their Interaction with the Surrounding Stroma.

Authors:  Mircea-Sebastian Șerbănescu; Raluca Maria Bungărdean; Carmen Georgiu; Maria Crișan
Journal:  Diagnostics (Basel)       Date:  2022-07-05

3.  Automated Gleason grading of prostate cancer using transfer learning from general-purpose deep-learning networks.

Authors:  Mircea Sebastian Şerbănescu; Nicolae Cătălin Manea; Liliana Streba; Smaranda Belciug; Iancu Emil Pleşea; Ionica Pirici; Raluca Maria Bungărdean; Răzvan Mihail Pleşea
Journal:  Rom J Morphol Embryol       Date:  2020       Impact factor: 1.033

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.