A three-year study of brain atrophy after autologous hematopoietic stem cell transplantation in rapidly evolving secondary progressive multiple sclerosis

BACKGROUND AND PURPOSE: In multiple sclerosis (MS), autologous hematopoietic stem cell transplantation (AHSCT) induces a profound suppression of clinical activity and MR imaging-detectable inflammation, but it may be associated with a rapid brain volume loss in the months subsequent to treatment. The aim of this study was to assess how AHSCT affects medium-term evolution of brain atrophy in MS. MATERIALS AND METHODS: MR imaging scans of the brain from 14 patients with rapidly evolving secondary-progressive MS obtained 3 months before and every year after AHSCT for 3 years were analyzed. Baseline normalized brain volumes and longitudinal percentage of brain volume changes (PBVCs) were assessed using the Structural Image Evaluation of Normalized Atrophy software. RESULTS: The median decrease of brain volume was 1.92% over the first year after AHSCT and then declined to 1.35% at the second year and to 0.69% at the third year. The number of enhancing lesions seen on the pretreatment scans was significantly correlated with the PBVCs between baseline and month 12 (r = -0.62; P = .02); no correlation was found with the PBVCs measured over the second and third years. CONCLUSIONS: After AHSCT, the rate of brain tissue loss in patients with MS declines dramatically after the first 2 years. The initial rapid development of brain atrophy may be a late consequence of the pretransplant disease activity and/or a transient result of the intense immunoablative conditioning procedure

Intracranial aneurysm segmentation in 3D CT angiography: method and quantitative validation with and without prior noise filtering

Item does not contain fulltextIntracranial aneurysm volume and shape are important factors for predicting rupture risk, for pre-surgical planning and for follow-up studies. To obtain these parameters, manual segmentation can be employed; however, this is a tedious procedure, which is prone to inter- and intra-observer variability. Therefore there is a need for an automated method, which is accurate, reproducible and reliable. This study aims to develop and validate an automated method for segmenting intracranial aneurysms in Computed Tomography Angiography (CTA) data. Also, it is investigated whether prior smoothing improves segmentation robustness and accuracy. The proposed segmentation method is implemented in the level set framework, more specifically Geodesic Active Surfaces, in which a surface is evolved to capture the aneurysmal wall via an energy minimization approach. The energy term is composed of three different image features, namely; intensity, gradient magnitude and intensity variance. The method requires minimal user interaction, i.e. a single seed point inside the aneurysm needs to be placed, based on which image intensity statistics of the aneurysm are derived and used in defining the energy term. The method has been evaluated on 15 aneurysms in 11 CTA data sets by comparing the results to manual segmentations performed by two expert radiologists. Evaluation measures were Similarity Index, Average Surface Distance and Volume Difference. The results show that the automated aneurysm segmentation method is reproducible, and performs in the range of inter-observer variability in terms of accuracy. Smoothing by nonlinear diffusion with appropriate parameter settings prior to segmentation, slightly improves segmentation accuracy

Intracranial aneurysm segmentation in 3D CT angiography: Method and quantitative validation

Department of Imaging Science and TechnologyApplied Science

Comparison of 2D (RANO) and volumetric methods for assessment of recurrent glioblastoma treated with bevacizumab-a report from the BELOB trial

Background. The current method for assessing progressive disease (PD) in glioblastoma is according to the Response Assessment in Neuro-Oncology (RANO) criteria. Bevacizumab-treated patients may show pseudoresponse on postcontrast T1-weighted (T1w) MRI, and a more infltrative non-enhancing growth pattern on T2w/?uid attenuated inversion recovery (FLAIR) images. We investigated whether the RANO criteria remain the method of choice for assessing bevacizumab-treated recurrent glioblastoma when compared with various volumetric methods. Methods. Patients with assessable MRI data from the BELOB trial (n = 148) were included. Patients were treated with bevacizumab, lomustine, or both. At frst and second radiological follow-up (6 and 12 wk), PD was determined using the 2D RANO criteria and various volumetric methods based on enhancing tumor only and enhancing plus non-enhancing tumor. Differences in overall survival (OS) between PD and non-PD patients were assessed with the log-rank test and a Cox model. Hazard ratios (HRs) and their 95% CIs were determined. Results. For all patients together, all methods (except subtraction of non-enhancing from enhancing volume at frst follow-up) showed signifcant differences in OS between PD and non-PD patients (P <.001). The largest risk increase for death in case of PD at both frst and second follow-up was found with the RANO criteria: HR = 2.81 (95% CI, 1.92-4.10) and HR = 2.80 (95% CI, 1.75-4.49), respectively. In the bevacizumab-treated patients, all methods assessed showed signifcant differences in OS between PD and non-PD patients. There were no signifcant differences between methods. Conclusions. In the frst 12 weeks, volumetric methods did not provide signifcant improvement over the RANO criteria as a posttreatment prognostic marker