Quantitative Apparent Diffusion Coefficient measurements obtained by 3-Tesla MRI are correlated with biomarkers of bladder cancer proliferative activity - Abstract

PURPOSE: To investigate the association between Apparent Diffusion Coefficient (ADC) values and cell cycle and proliferative biomarkers (p53, p21, Ki67,) in order to establish its potential role as a noninvasive biomarker for prediction of cell cycle, proliferative activity and biological aggressiveness in bladder cancer.

MATERIALS AND METHODS: Patients with bladder cancer who underwent 3,0 Tesla DW-MRI of the bladder before TUR-B or radical cystectomy were eligible for this prospective IRB-approved study. Histological specimen were immunohistochemically stained for the following markers: p53, p21 and ki67. Two board-certified uropathologists reviewed the specimens blinded to DW-MRI results. Histological grade and T-stage were classified according to the WHO 2004 and the 2009 TNM classification, respectively. Nonparametric univariate and multivariate statistics including correlation, logistic regression and ROC analysis were applied.

RESULTS: Muscle invasive bladder cancer was histologically confirmed in 10 out of 41 patients. All examined tissue biomarkers were significantly correlated with ADC values (p< 0.05, respectively). Based on multivariate analysis, p53 and ADC are both independent prognostic factors for muscle invasiveness of bladder cancer (>/ = T2). (p = 0.013 and p = 0.018).

CONCLUSION: ADC values are associated with cell cycle and proliferative biomarkers and do thereby reflect invasive and proliferative potential in bladder cancer. ADC and p53 are both independent prognostic factors for muscle invasiveness in bladder cancer.

Written by:
Sevcenco S, Haitel A, Ponhold L, Susani M, Fajkovic H, Shariat SF, Hiess M, Spick C, Szarvas T, Baltzer PA.   Are you the author?
Department of Urology, Medical University of Vienna, Vienna, Austria; Department of Pathology, Medical University of Vienna, Vienna, Austria; Department of Biomedical Imaging and Image-guided therapy, Medical University of Vienna, Vienna, Austria.

Reference: PLoS One. 2014 Sep 9;9(9):e106866.
doi: 10.1371/journal.pone.0106866


PubMed Abstract
PMID: 25202965

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