ABSTRACT
Our aim was to evaluate the impact of the accuracy of image segmentation techniques on establishing an overlap between pre-treatment and post-treatment functional tumour volumes in 18FDG-PET/CT imaging. Simulated images and a clinical cohort were considered. Three different configurations (large, small or non-existent overlap) of a single simulated example was used to elucidate the behaviour of each approach. Fifty-four oesophageal and head and neck (H&N) cancer patients treated with radiochemotherapy with both pre- and post-treatment PET/CT scans were retrospectively analysed. Images were registered and volumes were determined using combinations of thresholds and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Four overlap metrics were calculated. The simulations showed that thresholds lead to biased overlap estimation and that accurate metrics are obtained despite spatially inaccurate volumes. In the clinical dataset, only 17 patients exhibited residual uptake smaller than the pre-treatment volume. Overlaps obtained with FLAB were consistently moderate for esophageal and low for H&N cases across all metrics. Overlaps obtained using threshold combinations varied greatly depending on thresholds and metrics. In both cases overlaps were variable across patients. Our findings do not support optimisation of radiotherapy planning based on pre-treatment 18FDG-PET/CT image definition of high-uptake sub-volumes. Combinations of thresholds may have led to overestimation of overlaps in previous studies.
Subject(s)
Esophageal Neoplasms/diagnostic imaging , Head and Neck Neoplasms/diagnostic imaging , Image Processing, Computer-Assisted/methods , Positron Emission Tomography Computed Tomography/methods , Radiotherapy Planning, Computer-Assisted/methods , Chemoradiotherapy/methods , Computer Simulation , Datasets as Topic , Esophageal Neoplasms/therapy , Fluorodeoxyglucose F18/administration & dosage , Head and Neck Neoplasms/therapy , Humans , Retrospective Studies , Treatment Outcome , Tumor Burden/drug effects , Tumor Burden/radiation effectsABSTRACT
PURPOSE: In prostate radiotherapy, dose distribution may be calculated on CT images, while the MRI can be used to enhance soft tissue visualization. Therefore, a registration between MR and CT images could improve the overall treatment planning process, by improving visualization with a demonstrated interobserver delineation variability when segmenting the prostate, which in turn can lead to a more precise planning. This registration must compensate for prostate deformations caused by changes in size and form between the acquisitions of both modalities. METHODS: We present a fully automatic MRI/CT nonrigid registration method for prostate radiotherapy treatment planning. The proposed registration methodology is a two-step registration process involving both a rigid and a nonrigid registration step. The registration is constrained to volumes of interest in order to improve robustness and computational efficiency. The method is based on the maximization of the mutual information in combination with a deformation field parameterized by cubic B-Splines. RESULTS: The proposed method was validated on eight clinical patient datasets. Quantitative evaluation, using Hausdorff distance between prostate volumes in both images, indicated that the overall registration errors is 1.6 ± 0.2 mm, with a maximum error of less than 2.3 mm, for all patient datasets considered in this study. CONCLUSIONS: The proposed approach provides a promising solution for an effective and accurate prostate radiotherapy treatment planning since it satisfies the desired clinical accuracy.
