Prostate tumour volumes: evaluation of the agreement between magnetic resonance imaging and histology using novel co-registration software.
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- Record sourced from PubMed, PMID 24673731.
- Also identified by DOI 10.1111/bju.12750 and PMC identifier 4714042.
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Abstract
To evaluate the agreement between prostate tumour volume determined using multiparametric magnetic resonance imaging (MRI) and that determined by histological assessment, using detailed software-assisted co-registration. A total of 37 patients who underwent 3T multiparametric MRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC], dynamic contrast-enhanced [DCE] imaging) were included. A radiologist traced the borders of suspicious lesions on T2WI and ADC and assigned a suspicion score of between 2 and 5, while a uropathologist traced the borders of tumours on histopathological photographs. Software was used to co-register MRI and three-dimensional digital reconstructions of radical prostatectomy specimens and to compute imaging and histopathological volumes. Agreement in volumes between MRI and histology was assessed using Bland-Altman plots and stratified by tumour characteristics. Among 50 tumours, the mean differences (95% limits of agreement) in MRI relative to histology were -32% (-128 to +65%) on T2WI and -47% (-143 to +49%) on ADC. For all tumour subsets, volume underestimation was more marked on ADC maps (mean difference ranging from -57 to -16%) than on T2WI (mean difference ranging from -45 to +2%). The 95% limits of agreement were wide for all comparisons, with the lower 95% limit ranging between -77 and -143% across assessments. Volume underestimation was more marked for tumours with a Gleason score ≥7 or a MRI suspicion score 4 or 5. Volume estimates of prostate cancer using MRI tended to substantially underestimate histopathological volumes, with a wide variability in extent of underestimation across cases. These findings have implications for efforts to use MRI to guide risk assessment.
Medical subject headings
- Magnetic Resonance Imaging
- Prostatic Neoplasms
- Software
- Tumor Burden