PURPOSE: Multi-parametric MRI often under- or over-estimates the pathological cancer volume.
The aim of this study was to develop a novel method to estimate prostate cancer volume using MR/US-fusion biopsy-proven cancer core-length.
PATIENTS AND METHODS: A total of 81 consecutive clinically localized prostate cancer patients with MR/US-fusion targeted biopsy-proven cancer who subsequently underwent radical prostatectomy were retrospectively analyzed. As 7 patients had two MRI-visible lesions, 88 lesions were analyzed. The dimensions and estimated lesion volume of MR-visible lesions were calculated using ADC maps. The modified formula for estimating cancer volume was defined as the formula of vertical stretching the AP-dimension of the MR-based 3D model in which the MR-estimated lesion-AP-dimension was replaced with MR/US-targeted biopsy-proven cancer core-length. Agreement of the pathological cancer volume (PCV) with the MR-estimated-volume (MCV) or the novel modified-volume was assessed using a Bland-Altman plot.
RESULTS: MR/US fusion biopsy-proven cancer core-length (r=0.824, p< 0.001) was a stronger predictor of the actual pathological cancer-AP-dimension than the MR-estimated lesion-AP-dimension (r=0.607, p< 0.001). MR/US-targeted biopsy-proven cancer core-length was correlated with PCV (r=0.773, p< 0.001). The modified formula for estimating cancer volume demonstrated a stronger correlation with PCV (r=0.824, p< 0.001) than the MCV (r=0.724, p< 0.001). Agreement of the modified-volume with PCV improved than that of MCV in a Bland-Altman plot analysis. The predictability was more enhanced in the subset of cancer lesions with the volume ≤ 2 ml (i.e., if spherical in shape, it was approximately 16 mm in diameter).
CONCLUSION: Combining MRI-estimated cancer volume with MR/US-fusion biopsy-proven cancer core-length improved cancer volume predictability.
Written by:
Matsugasumi T, Baco E, Palmer S, Aron M, Sato Y, Fukuda N, Süer E, Bernhard JC, Nakagawa H, Azhar RA, Gill IS, Ukimura O. Are you the author?
USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Urology, Kyoto Prefectural University of Medicine, Kyoto, Japan; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Imaging-based Computational Biomedicine Laboratory, Graduate School of Information Science Nara Institute of Science and Technology, Nara, Japan; USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Urology Department, King Abdulaziz University, Jeddah, Saudi Arabia.
Reference: J Urol. 2015 Apr 22. pii: S0022-5347(15)03853-7.
doi: 10.1016/j.juro.2015.04.075
PubMed Abstract
PMID: 25912496