Normalized periprostatic fat MRI measurements can predict prostate cancer aggressiveness in men undergoing radical prostatectomy for clinically localised disease
Abstract Periprostatic and pelvic fat have been shown to influence prostate cancer behaviour through the secretion of chemokines and growth factors, acting in a paracrine mode. We have measured periprostatic fat volume (PFV) with normalisation to prostate gland volume on pelvic magnetic resonance im...
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Autores principales: | , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2017
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Materias: | |
Acceso en línea: | https://doaj.org/article/1fc6e14cd68a477182343e822a53d794 |
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Sumario: | Abstract Periprostatic and pelvic fat have been shown to influence prostate cancer behaviour through the secretion of chemokines and growth factors, acting in a paracrine mode. We have measured periprostatic fat volume (PFV) with normalisation to prostate gland volume on pelvic magnetic resonance imaging (MRI) and have correlated this with grade (Gleason score; GS) and pathological staging (pT) of prostate cancer (PCa) following radical prostatectomy (RP). PFV was determined using a segmentation technique on contiguous T1-weighted axial MRI slices from the level of the prostate base to the apex. The abdominal fat area (AFA) and subcutaneous fat thickness (SFT) were measured using T1-weighted axial slices at the level of the umbilicus and the upper border of the symphysis pubis, respectively. PFV was normalised to prostate volume (PV) to account for variations in PV (NPFV = PFV/PV). Patients were stratified into three risk groups according to post-operative GS: ≤6, 7(3 + 4), and ≥7(4 + 3). NPFV was significantly different between the groups (p = 0.001) and positively correlated with post-operative GS (ρ = 0.294, p < 0.001). There was a difference in NPFV between those with upgrading of GS from 6 post prostatectomy (2.43 ± 0.98; n = 26) compared to those who continued to be low grade (1.99 ± 0.82; n = 17); however, this did not reach statistical significance (p = 0.11). |
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