R Zakaria1, K Das2, M Bhojak2, M Radon2, V Sluming3, C Walker4, M D Jenkinson4. 1. Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK; Institute of Integrative Biology, University of Liverpool, Liverpool, UK. Electronic address: rzakaria@nhs.net. 2. Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK. 3. Magnetic resonance and image analysis research centre (MARIARC), University of Liverpool, Liverpool, UK. 4. Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK.
Abstract
BACKGROUND AND PURPOSE: Diffusion MRI characteristics have been used as biomarkers to guide prognosis in cerebral pathologies including brain metastases. The measurement of ADC is often described poorly in clinical and research studies with little detail given to the practical considerations of where to place ROIs, which post processing software package to use and how reproducible the resulting metrics will be. METHOD: We investigated a series of 12 patients with brain metastases and preoperative DWI. Three post processing platforms were used. ROI were placed over the tumour, peritumoural region and across the brain-tumour interface. These recordings were made by a neurosurgeon and a neuroradiologist. Inter-intra-observer variability was assessed using Bland-Altman analysis. An exploratory analysis of DWI with overall survival and tumour type was made. RESULTS: There was excellent correlation between the software packages used for all measures including assessing the whole tumour, selective regions with lowest ADC, the change of ADC across the brain-tumour interface and the relation of the tumour ADC to peritumoural regions and the normal white matter. There was no significant inter- or intra-observer variability for repeated readings. There were significant differences in the mean values obtained using different methodologies and different metrics had differing relationships to overall survival and primary tumour of origin. CONCLUSION: Diffusion weighted MRI metrics offer promise as potential non-invasive biomarkers in brain metastases and a variety of metrics have been shown to be reliably measured using differing platforms and observers.
BACKGROUND AND PURPOSE: Diffusion MRI characteristics have been used as biomarkers to guide prognosis in cerebral pathologies including brain metastases. The measurement of ADC is often described poorly in clinical and research studies with little detail given to the practical considerations of where to place ROIs, which post processing software package to use and how reproducible the resulting metrics will be. METHOD: We investigated a series of 12 patients with brain metastases and preoperative DWI. Three post processing platforms were used. ROI were placed over the tumour, peritumoural region and across the brain-tumour interface. These recordings were made by a neurosurgeon and a neuroradiologist. Inter-intra-observer variability was assessed using Bland-Altman analysis. An exploratory analysis of DWI with overall survival and tumour type was made. RESULTS: There was excellent correlation between the software packages used for all measures including assessing the whole tumour, selective regions with lowest ADC, the change of ADC across the brain-tumour interface and the relation of the tumour ADC to peritumoural regions and the normal white matter. There was no significant inter- or intra-observer variability for repeated readings. There were significant differences in the mean values obtained using different methodologies and different metrics had differing relationships to overall survival and primary tumour of origin. CONCLUSION: Diffusion weighted MRI metrics offer promise as potential non-invasive biomarkers in brain metastases and a variety of metrics have been shown to be reliably measured using differing platforms and observers.
Authors: Rasheed Zakaria; Yin Jie Chen; David M Hughes; Sumei Wang; Sanjeev Chawla; Harish Poptani; Anna S Berghoff; Matthias Preusser; Michael D Jenkinson; Suyash Mohan Journal: Cancer Imaging Date: 2020-02-07 Impact factor: 3.909
Authors: Rasheed Zakaria; Kumar Das; Mark Radon; Maneesh Bhojak; Philip R Rudland; Vanessa Sluming; Michael D Jenkinson Journal: BMC Med Imaging Date: 2014-08-03 Impact factor: 1.930