The association between brain volumes, delirium duration, and cognitive outcomes in intensive care unit survivors: the VISIONS cohort magnetic resonance imaging study*.

OBJECTIVE: Delirium duration is predictive of long-term cognitive impairment in intensive care unit survivors. Hypothesizing that a neuroanatomical basis may exist for the relationship between delirium and long-term cognitive impairment, we conducted this exploratory investigation of the associations between delirium duration, brain volumes, and long-term cognitive impairment. DESIGN, SETTING, AND PATIENTS: A prospective cohort of medical and surgical intensive care unit survivors with respiratory failure or shock. MEASUREMENTS: Quantitative high resolution 3-Tesla brain magnetic resonance imaging was used to calculate brain volumes at discharge and 3-month follow-up. Delirium was evaluated using the confusion assessment method for the intensive care unit; cognitive outcomes were tested at 3- and 12-month follow-up. Linear regression was used to examine associations between delirium duration and brain volumes, and between brain volumes and cognitive outcomes. RESULTS: A total of 47 patients completed the magnetic resonance imaging protocol. Patients with longer duration of delirium displayed greater brain atrophy as measured by a larger ventricle-to-brain ratio at hospital discharge (0.76, 95% confidence intervals [0.10, 1.41]; p = .03) and at 3-month follow-up (0.62 [0.02, 1.21], p = .05). Longer duration of delirium was associated with smaller superior frontal lobe (-2.11 cm(3) [-3.89, -0.32]; p = .03) and hippocampal volumes at discharge (-0.58 cm(3) [-0.85, -0.31], p < .001)--regions responsible for executive functioning and memory, respectively. Greater brain atrophy (higher ventricle-to-brain ratio) at 3 months was associated with worse cognitive performances at 12 months (lower Repeatable Battery for the Assessment of Neuropsychological Status score -11.17 [-21.12, -1.22], p = .04). Smaller superior frontal lobes, thalamus, and cerebellar volumes at 3 months were associated with worse executive functioning and visual attention at 12 months. CONCLUSIONS: These preliminary data show that longer duration of delirium is associated with smaller brain volumes up to 3 months after discharge, and that smaller brain volumes are associated with long-term cognitive impairment up to 12 months. We cannot, however, rule out that smaller preexisting brain volumes explain these findings.

Neural components of social evaluation.

Evaluative responses appear to involve 2 seemingly distinct sets of processes: those that are automatically activated and others that are more consciously controlled. Using functional magnetic resonance imaging, the authors investigated the brain systems associated with automatic and controlled evaluative processing. Participants made either evaluative (good-bad) or nonevaluative (past-present) judgments about famous names. Greater amygdala activity was observed for names rated as "bad" relative to those rated as "good," regardless of whether the task directly involved an evaluative judgment (good-bad) or not (past-present). Good-bad judgments resulted in greater medial and ventrolateral prefrontal cortex (PFC) activity than past-present judgments. Furthermore, there was greater ventrolateral PFC activity in good-bad judgments marked by greater ambivalence. Together, these findings indicate a neural distinction between processes engaged for automatic and controlled evaluation. Whereas automatic processes are sensitive to simple valence, controlled processes are sensitive to attitudinal complexity.

A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI.

Intensity inhomogeneity often occurs in real-world images, which presents a considerable challenge in image segmentation. The most widely used image segmentation algorithms are region-based and typically rely on the homogeneity of the image intensities in the regions of interest, which often fail to provide accurate segmentation results due to the intensity inhomogeneity. This paper proposes a novel region-based method for image segmentation, which is able to deal with intensity inhomogeneities in the segmentation. First, based on the model of images with intensity inhomogeneities, we derive a local intensity clustering property of the image intensities, and define a local clustering criterion function for the image intensities in a neighborhood of each point. This local clustering criterion function is then integrated with respect to the neighborhood center to give a global criterion of image segmentation. In a level set formulation, this criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, by minimizing this energy, our method is able to simultaneously segment the image and estimate the bias field, and the estimated bias field can be used for intensity inhomogeneity correction (or bias correction). Our method has been validated on synthetic images and real images of various modalities, with desirable performance in the presence of intensity inhomogeneities. Experiments show that our method is more robust to initialization, faster and more accurate than the well-known piecewise smooth model. As an application, our method has been used for segmentation and bias correction of magnetic resonance (MR) images with promising results.