Avtor/Urednik		Pukl, Miha; Keyes, Sarah; Keyes, Mira; Guillaud, Martial D; Volavšek, Metka
Naslov		Multi-scale tissue architecture analysis of favorable-risk prostate cancer
Tip		članek
Vol. in št.		Letnik 61, št. 5
Leto izdaje		2020
Obseg		str. 482-490
ISSN		2466-0493
Jezik		eng
Abstrakt		Purpose Prostate cancer (PCa) with biopsy-based grade group (GG) 1 or 2 characteristics has a favorable outcome, yet some cases still progress after radical prostatectomy and present with biochemical recurrence (BCR). We hypothesized that the multi-scale tissue architecture (MSTA) analysis score would correlate with the aggressive PCa phenotype and could be used as a tool for risk assessment to improve the management of patients with favorable-risk PCa. Materials and Methods MSTA was evaluated in needle-biopsy samples from 115 patients with favorable-risk PCa, as defined by GG1 and GG2, a prostate-specific antigen (PSA) level of <10 ng/mL, a clinical stage of cT1c to cT2b, and general Gleason GG (GGG) and expert pathologist-assessed GG (EGG). Algorithms based on Voronoi diagrams were applied to all Feulgen-thionin-stained diagnostic areas. One hundred tissue architecture features were calculated and an MSTA score, a linear combination of the most discriminant features, was generated. Correlation of MSTA score with BCR and other clinical variables was investigated. Results In a univariate regression model, EGG, clinical stage, and MSTA were significant predictors of BCR (respective p-values: 0.0016, 0.016, and 0.028). Survival analysis showed that patients with a high MSTA score were more likely to experience BCR than were patients with a low MSTA score (odds ratio, 2.9). Combining MSTA with GG assessment resulted in a significant stratification of risk for BCR. Conclusions MSTA score could be used as an objective adjunct risk stratification tool to pathologist assessments and could improve the management of patients with favorable-risk PCa.
Proste vsebinske oznake		rak prostate analiza tkivne zgradbe biokemijska ponovitev prostate cancer tissue architecture analysis biochemical recurrence