Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Meta-analysis and dose-response metaregression: circulating insulin-like growth factor I (IGF-I) and mortality

Context: IGF-I plays a central role in metabolism and growth regulation. High IGF-I levels are associated with increased cancer risk and low IGF-I levels with increased risk for cardiovascular disease. Objective: Our objective was to determine the relationship between circulating IGF-I levels and mortality in the general population using random-effects meta-analysis and dose-response metaregression. Data Sources: We searched PubMed, EMBASE, Web of Science, and Cochrane Library from 1985 to September 2010 to identify relevant studies. Study Selection: Population-based cohort studies and (nested) case-control studies reporting on the relation between circulating IGF-I and mortality were assessed for eligibility. Data Extraction: Data extraction was performed by two investigators independently, using a standardized data extraction sheet. Data Synthesis: Twelve studies, with 14,906 participants, were included. Overall, risk of bias was limited. Mortality in subjects with low or high IGF-I levels was compared with mid-centile reference categories. All-cause mortality was increased in subjects with low as well as high IGF-I, with a hazard ratio (HR) of 1.27 (95% CI = 1.08–1.49) and HR of 1.18 (95% CI = 1.04–1.34), respectively. Dose-response metaregression showed a U-shaped relation of IGF-I and all-cause mortality (P = 0.003). The predicted HR for the increase in mortality comparing the 10th IGF-I with the 50th percentile was 1.56 (95% CI = 1.31–1.86); the predicted HR comparing the 90th with the 50th percentile was 1.29 (95% CI = 1.06–1.58). A U-shaped relationship was present for both cancer mortality and cardiovascular mortality. Conclusions: Both low and high IGF-I concentrations are associated with increased mortality in the general population.

Adenovirus-mediated transforming growth factor-beta ameliorates ischemic necrosis of epigastric skin flaps in a rat model

BACKGROUND: Gene therapy has been recently introduced as a novel approach to treat ischemic tissues by using the angiogenic potential of certain growth factors. We investigated the effect of adenovirus-mediated gene therapy with transforming growth factor-beta (TGF-beta) delivered into the subdermal space to treat ischemically challenged epigastric skin flaps in a rat model. MATERIAL AND METHODS: A pilot study was conducted in a group of 5 animals pretreated with Ad-GFP and expression of green fluorescent protein in the skin flap sections was demonstrated under fluorescence microscopy at 2, 4, and 7 days after the treatment, indicating a successful transfection of the skin flaps following subdermal gene therapy. Next, 30 male Sprague Dawley rats were divided into 3 groups of 10 rats each. An epigastric skin flap model, based solely on the right inferior epigastric vessels, was used as the model in this study. Rats received subdermal injections of adenovirus encoding TGF-beta (Ad-TGF-beta) or green fluorescent protein (Ad-GFP) as treatment control. The third group (n = 10) received saline and served as a control group. A flap measuring 8 x 8 cm was outlined on the abdominal skin extending from the xiphoid process proximally and the pubic region distally, to the anterior axillary lines bilaterally. Just prior to flap elevation, the injections were given subdermally in the left upper corner of the flap. The flap was then sutured back to its bed. Flap viability was evaluated seven days after the initial operation. Digital images of the epigastric flaps were taken and areas of necrotic zones relative to total flap surface area were measured and expressed as percentages by using a software program. RESULTS: There was a significant increase in mean percent surviving area between the Ad-TGF-beta group and the two other control groups (P < 0.05). (Ad-TGF-beta: 90.3 +/- 4.0% versus Ad-GFP: 82.2 +/- 8.7% and saline group: 82.6 +/- 4.3%.) CONCLUSIONS: In this study, the authors were able to demonstrate that adenovirus-mediated gene therapy using TGF-beta ameliorated ischemic necrosis in an epigastric skin flap model, as confirmed by significant reduction in the necrotic zones of the flap. The results of this study raise the possibility of using adenovirus-mediated TGF-beta gene therapy to promote perfusion in random portion of skin flaps, especially in high-risk patients.