Automatic volumetric temperature regulation during in vivo MRI-guided laser-induced thermotherapy (MRg-LITT) with multiple laser probes.

Background: Clinical Laser-Induced Thermotherapy (LITT) currently lacks precise control of tissue temperature increase during the procedure. This study presents a new method to automatically regulate the maximum temperature increase in vivo at different positions by adjusting LITT power delivered by multiple laser probes using real-time volumetric MR-thermometry.

Methods: The regulation algorithm was evaluated in vivo on a pig leg muscle.

Real-time automatic temperature regulation during in vivo MRI-guided laser-induced thermotherapy (MR-LITT).

Precise control of tissue temperature during Laser-Induced Thermotherapy (LITT) procedures has the potential to improve the clinical efficiency and safety of such minimally invasive therapies. We present a method to automatically regulate in vivo the temperature increase during LITT using real-time rapid volumetric Magnetic Resonance thermometry (8 slices acquired every second, with an in-plane resolution of 1.4 mmx1.

Hierarchical segmentation using equivalence test (HiSET): Application to DCE image sequences.

Dynamical contrast enhanced (DCE) imaging allows non invasive access to tissue micro-vascularization. It appears as a promising tool to build imaging biomarkers for diagnostic, prognosis or anti-angiogenesis treatment monitoring of cancer. However, quantitative analysis of DCE image sequences suffers from low signal to noise ratio (SNR).

Mean arterial pressure change associated with cerebral blood flow in healthy older adults.

We investigate over a 12-year period the association between regional cerebral blood flow (CBF) and cardiovascular risk factors in a prospective cohort of healthy older adults (81.96 ± 3.82 year-old) from the Cognitive REServe and Clinical ENDOphenotype (CRESCENDO) study.

A Probabilistic Atlas of Diffuse WHO Grade II Glioma Locations in the Brain.

Diffuse WHO grade II gliomas are diffusively infiltrative brain tumors characterized by an unavoidable anaplastic transformation. Their management is strongly dependent on their location in the brain due to interactions with functional regions and potential differences in molecular biology. In this paper, we present the construction of a probabilistic atlas mapping the preferential locations of diffuse WHO grade II gliomas in the brain.

Concurrent tumor segmentation and registration with uncertainty-based sparse non-uniform graphs.

In this paper, we present a graph-based concurrent brain tumor segmentation and atlas to diseased patient registration framework. Both segmentation and registration problems are modeled using a unified pairwise discrete Markov Random Field model on a sparse grid superimposed to the image domain. Segmentation is addressed based on pattern classification techniques, while registration is performed by maximizing the similarity between volumes and is modular with respect to the matching criterion.

Joint tumor segmentation and dense deformable registration of brain MR images.

In this paper we propose a novel graph-based concurrent registration and segmentation framework. Registration is modeled with a pairwise graphical model formulation that is modular with respect to the data and regularization term. Segmentation is addressed by adopting a similar graphical model, using image-based classification techniques while producing a smooth solution.

Graph based spatial position mapping of low-grade gliomas.

Low-grade gliomas (WHO grade II) are diffusively infiltrative brain tumors arising from glial cells. Spatial classification that is usually based on cerebral lobes lacks accuracy and is far from being able to provide some pattern or statistical interpretation of their appearance. In this paper, we propose a novel approach to understand and infer position of low-grade gliomas using a graphical model.

Three-dimensional analysis of the intrinsic anatomy of the metatarsal bones.

Knowledge of the anatomy of the forefoot is important for understanding its mechanical pathology and developing specific surgical procedures. The aim of this study was to quantify 3-dimensional morphological parameters, which were proposed for the characterization of the metatarsal intrinsic anatomy. Thirty-five metatarsal bones prepared from 7 cadaver specimens were analyzed according to a new 3-dimensional computer-aided (CA) methodology.