Sarah Bond

The segmentation of colorectal MRI images.

One of the key criteria that informs patient management decisions for colorectal cancer is the extent of the shortest distance from the edge of the primary tumour to the edge of the mesorectum, also referred to as circumferential resection margin (CRM). This region is resected during surgery. The CRM is difficult for clinicians to measure accurately, particularly from 2D slice data. We present a method for automatically calculating and visualising the CRM distances in colorectal cancer MR images. We use local phase of the monogenic signal calculated from the MR image intensities to find edge and ridge features within the data. A non-parametric mixture model is then used to describe image intensity values within level set framework in order to segment the mesorectal fascia and the corresponding tumour and lymph nodes, as distinct regions. This segmentation is used to provide an automatic analysis of the shortest distance resection margin, and we show that this is consistent with that of the clinically accepted MERCURY method. We use the segmentation to provide a 3D visualisation of where the resection margin is smallest. Finally, we reconstruct a 3D map of the segmented anatomy. Both the visualisation methods provide a useful tool to aid surgeons in their treatment planning.

Automatic registration of cardiac PET/CT for attenuation correction

Misalignments of images in cardiac Positron Emission Tomography (PET)-CT imaging may lead to erroneous Attenuation Correction (AC) and mis-diagnosis. Such misalignment may be corrected manually prior to reconstruction and clinical assessment; however this step is laborious and may be subject to operator variability. The aim of this study is to assess the performance of an algorithm to automatically align CT to PET prior to AC. We conclude that automatic registration is a viable option for the task of aligning cardiac CT and PET for AC, with a consistency comparable to that of using manual alignment.

Circumferential Resection Margin Assessment on MRI of Rectal Cancer

The circumferential resection margin (CRM) has been shown to be a good predictor of the outcome of the total mesorectal resection surgical procedure in colorectal cancer. The CRM is increasingly used as a key parameter in patient management for colorectal cancer. It has been proposed that CRM can be estimated from MRI volumes taken pre-operatively; but to date the estimation of CRM is slice-based, hence two dimensional. We report a fully three-dimensional method to estimate the CRM, taking account of the MRI slice orientation used during the acquisition process. Prior to this, we segment the rectum and mesorectum. Preliminary results are reported for 10 patient cases, and a further large set are currently being analysed and results will be available at the time of the conference