Analysis of carotid artery plaque and wall boundaries on CT images by using a semi-automatic method based on level set model

Introduction: The purpose of this study was to evaluate the potentialities of a semi-automated technique in the detection and measurement of the carotid artery plaque. <p/>Methods: Twenty-two consecutive patients (18 males, 4 females; mean age 62 years) examined with MDCTA from January 2011 to March 2011 were included in this retrospective study. Carotid arteries are examined with a 16-multi-detector-row CT system, and for each patient, the most diseased carotid was selected. In the first phase, the carotid plaque was identified and one experienced radiologist manually traced the inner and outer boundaries by using polyline and radial distance method (PDM and RDM, respectively). In the second phase, the carotid inner and outer boundaries were traced with an automated algorithm: level-set-method (LSM). Data were compared by using Pearson rho correlation, Bland–Altman, and regression. <p/>Results: A total of 715 slices were analyzed. The mean thickness of the plaque using the reference PDM was 1.86 mm whereas using the LSM-PDM was 1.96 mm; using the reference RDM was 2.06 mm whereas using the LSM-RDM was 2.03 mm. The correlation values between the references, the LSM, the PDM and the RDM were 0.8428, 0.9921, 0.745 and 0.6425. Bland–Altman demonstrated a very good agreement in particular with the RDM method. <p/>Conclusion: Results of our study indicate that LSM method can automatically measure the thickness of the plaque and that the best results are obtained with the RDM. Our results suggest that advanced computer-based algorithms can identify and trace the plaque boundaries like an experienced human reader

The neurobiology of speech perception decline in aging

Speech perception difficulties are common among elderlies; yet the underlying neural mechanisms are still poorly understood. New empirical evidence suggesting that brain senescence may be an important contributor to these difficulties has challenged the traditional view that peripheral hearing loss was the main factor in the etiology of these difficulties. Here, we investigated the relationship between structural and functional brain senescence and speech perception skills in aging. Following audiometric evaluations, participants underwent MRI while performing a speech perception task at different intelligibility levels. As expected, with age speech perception declined, even after controlling for hearing sensitivity using an audiological measure (pure tone averages), and a bioacoustical measure (DPOAEs recordings). Our results reveal that the core speech network, centered on the supratemporal cortex and ventral motor areas bilaterally, decreased in spatial extent in older adults. Importantly, our results also show that speech skills in aging are affected by changes in cortical thickness and in brain functioning. Age-independent intelligibility effects were found in several motor and premotor areas, including the left ventral premotor cortex and the right supplementary motor area (SMA). Age-dependent intelligibility effects were also found, mainly in sensorimotor cortical areas, and in the left dorsal anterior insula. In this region, changes in BOLD signal modulated the relationship between age and speech perception skills suggesting a role for this region in maintaining speech perception in older ages. These results provide important new insights into the neurobiology of speech perception in aging

Structural Imaging Measures of Brain Aging

During the course of normal aging, biological changes occur in the brain that are associated with changes in cognitive ability. This review presents data from neuroimaging studies of primarily “normal” or healthy brain aging. As such, we focus on research in unimpaired or nondemented older adults, but also include findings from lifespan studies that include younger and middle aged individuals as well as from populations with prodromal or clinically symptomatic disease such as cerebrovascular or Alzheimer’s disease. This review predominantly addresses structural MRI biomarkers, such as volumetric or thickness measures from anatomical images, and measures of white matter injury and integrity respectively from FLAIR or DTI, and includes complementary data from PET and cognitive or clinical testing as appropriate. The findings reveal highly consistent age-related differences in brain structure, particularly frontal lobe and medial temporal regions that are also accompanied by age-related differences in frontal and medial temporal lobe mediated cognitive abilities. Newer findings also suggest that degeneration of specific white matter tracts such as those passing through the genu and splenium of the corpus callosum may also be related to age-related differences in cognitive performance. Interpretation of these findings, however, must be tempered by the fact that comorbid diseases such as cerebrovascular and Alzheimer’s disease also increase in prevalence with advancing age. As such, this review discusses challenges related to interpretation of current theories of cognitive aging in light of the common occurrence of these later-life diseases. Understanding the differences between “Normal” and “Healthy” brain aging and identifying potential modifiable risk factors for brain aging is critical to inform potential treatments to stall or reverse the effects of brain aging and possibly extend cognitive health for our aging society