Longitudinal studies indicate that declines in cognition and memory accelerate after age 70 years. The neuroanatomic and neurophysiologic underpinnings of cognitive change are unclear, as there is little information on longitudinal brain changes. We are conducting a longitudinal neuroimaging study of nondemented older participants in the Baltimore Longitudinal Study of Aging. This report focuses on age and sex differences in brain structure measured by magnetic resonance imaging during the first two annual evaluations. Cross-sectional results from 116 participants aged 59-85 years reveal significantly larger ventricular volumes and smaller gray and white matter volumes in older compared with younger participants and in men compared with women. Regional brain volumes show that the effects of age and sex are not uniform across brain regions. Age differences are greatest for the parietal region. Sex differences tend to be larger for frontal and temporal than parietal and occipital regions. Longitudinal analysis demonstrates an increase of 1526 mm(3) in ventricular volume over 1 year, but no detectable change in total or regional brain volumes. Definition of the pattern and rate of longitudinal brain changes will facilitate the detection of pathological brain changes, which may be predictors of dementia.

In this work, we developed, implemented, and validated an image-processing system for qualitative and quantitative volumetric analysis of brain images. This system allows the visualization and quantitation of global and regional brain volumes. Global volumes were obtained via an automated adaptive Bayesian segmentation technique that labels the brain into white matter, gray matter, and cerebrospinal fluid. Absolute volumetric errors for these compartments ranged between 1 and 3% as indicated by phantom studies. Quantitation of regional brain volumes was performed through normalization and tessellation of segmented brain images into the Talairach space with a 3D elastic warping model. Retest reliability of regional volumes measured in Talairach space indicated errors of < 1.5% for the frontal, parietal, temporal, and occipital brain regions. Additional regional analysis was performed with an automated hybrid method combining a region-of-interest approach and voxel-based analysis, named Regional Analysis of Volumes Examined in Normalized Space (RAVENS). RAVENS analysis for several subcortical structures showed good agreement with operator-defined volumes. This system has sufficient accuracy for longitudinal imaging data and is currently being used in the analysis of neuroimaging data of the Baltimore Longitudinal Study of Aging.

Ultrasound (US) is a valuable imaging modality used to detect primary breast malignancy. However, radiologists have a limited ability to distinguish between benign and malignant lesions on US, leading to false-positive and false-negative results, which limit the positive predictive value of lesions sent for biopsy (PPV3) and specificity. A recent study demonstrated that incorporating an AI-based decision support (DS) system into US image analysis could help improve US diagnostic performance. While the DS system is promising, its efficacy in terms of its impact also needs to be measured when integrated into existing clinical workflows. The current study evaluates workflow schemas for DS integration and its impact on diagnostic accuracy. The impact on two different reading methodologies, sequential and independent, was assessed. This study demonstrates significant accuracy differences between the two workflow schemas as measured by area under the receiver operating curve (AUC), as well as inter-operator variability differences as measured by Kendall’s tau-b. This evaluation has practical implications on the utilization of such technologies in diagnostic environments as compared to previous studies.

MRI estimates of CA are dependent on both the type of PS and SA; therefore, the choice of SA technique and PS should be consistent during an MS treatment trial. The progression of CA in MS should only be used as a secondary or tertiary outcome measure in treatment trials until a better understanding of how this measurement is affected by the disease, the image acquisition and analysis techniques.

No abstract

The purpose of this research was to develop queries that quantify the utilization of comparison imaging in free-text radiology reports. The queries searched for common phrases that indicate whether comparison imaging was utilized, not available, or not mentioned. The queries were iteratively refined and tested on random samples of 100 reports with human review as a reference standard until the precision and recall of the queries did not improve significantly between iterations. Then, query accuracy was assessed on a new random sample of 200 reports. Overall accuracy of the queries was 95.6%. The queries were then applied to a database of 1.8 million reports. Comparisons were made to prior images in 38.69% of the reports (693,955/1,793,754), were unavailable in 18.79% (337,028/1,793,754), and were not mentioned in 42.52% (762,771/1,793,754). The results show that queries of text reports can achieve greater than 95% accuracy in determining the utilization of prior images.

No abstract

In this work, we developed and implemented a multimodality multidimensional imaging system which is capable of generating and displaying anatomical and functional images of selected structures and processes within a vertebrate's central nervous system (CNS). The functional images are generated from [14C]-2-deoxy-D-glucose (2DG) autoradiography whereas the anatomic images are derived from cytochrome oxidase (CO) histochemistry. This multi-modality imaging system has been used to study mechanisms underlying information processing in the rat brain. We have applied this technique to visualize and measure the plasticity (deformation) observed in the rat's whisker system due to neonatal lesioning of selected peripheral sensory organs. Application of this imaging system revealed detailed information about the shape, size, and directionality of selected cortical and subcortical structures. Previous 2-D imaging techniques were unable to deliver such holistic information. Another important issue addressed in this work is related to image registration problems. We developed an image registration technique which employs extrinsic fiduciary marks for alignment and is capable of registering images with subpixel accuracy. It uses the information from all available fiduciary marks to promote alignment of the sections and to avoid propagation of errors across a serial data set.