Validity and reproducibility of ultrasonography for the measurement of intra-abdominal adipose tissue.

OBJECTIVE: We studied the validity and reproducibility of a new abdominal ultrasound protocol for the assessment of intra-abdominal adipose tissue. MEASUREMENTS: Intra-abdominal adipose tissue was assessed by CT, MRI, anthropometry and ultrasonography on a single day. By ultrasonography the distance between peritoneum and lumbar spine was measured using a strict protocol, including the location of the measurements, pressure on the transducer and respiration. All measurements were repeated after 3 months. RESULTS: The study population consisted of 19 overweight patients with a body mass index (BMI) of 32.9 kg/m(2) (s.d. 3.7), intra-abdominal adipose tissue on CT 140.1 cm(2) (s.d. 55.9), and a mean ultrasound distance of 9.8 cm (s.d. 2.5). There was a strong association between the CT and ultrasonographic measures: Pearson correlation coefficient was 0.81 (P<0.001). The correlation between ultrasound and waist circumference was 0.74 (P<0.001), the correlation between CT and waist circumference was 0.57 (P=0.01). Ultrasound appeared a good method to diagnose intra-abdominal obesity: the area under the ROC curve was 0.98. During the follow-up period of 3 months, the patients lost on average almost 3 kg of body weight. The correlation coefficient between changes in intra-abdominal adipose tissue assessed by CT and ultrasound was 0.74 (P<0.001). The correlation coefficient of the mean ultrasound distance assessed by two different sonographers at baseline was 0.94 (P<0.001), the mean difference 0.4 cm (s.d. 0.9), and the coefficient of variation 5.4%, indicating good reproducibility of the ultrasound measurements. CONCLUSIONS: The results of this validation study show that abdominal ultrasound, using a strict protocol, is a reliable and reproducible method to assess the amount of intra-abdominal adipose tissue and to diagnose intra-abdominal obesity.

Determination of superabsorbent polyacrylate dust in workplace atmospheres after derivatization with ethanol and using HPLC with pulsed electrochemical detection.

Superabsorbent polyacrylates (SAPs) have been used in the hygiene industry for many years. A derivatization and analytical method was developed for routine analysis of trace levels of SAP dust in workplace atmospheres. In comparison with existing methods, which are based on the sodium content or the ion exchange properties of the polymer, this method is more specific. It has the advantage of not being influenced by any sodium containing contaminants. Air samples are collected on Teflon filters using air monitoring sampling cassettes. The filters are subsequently placed in quartz vials and a reaction mixture containing hydrochloric acid in ethanol is added. The hydrochloric acid-ethanol solution, when heated, converts the carboxylic acid groups on the backbone of the insoluble polyacrylate into ethyl esters. After reaction, the excess of ethanol and hydrochloric acid is completely removed under vacuum. The sample is then treated with aqueous sodium hydroxide at 80 degrees C to release the bound ethanol. The solution is analyzed by HPLC on an anion exclusion stationary phase using dilute perchloric acid as mobile phase. Ethanol is identified and quantified with a pulsed electrochemical detector. Several environmental samples in addition to laboratory spiked samples were successfully analyzed with this technique. Recoveries averaged > 85% for spiked blank filters at levels from 5 to 50 micrograms per filter with relative standard deviations up to 7%. The instrument's limit of detection (LOD) for ethanol was 0.1 mg l-1. The LOD for derivatization and analysis corresponds to 3 micrograms of SAP per filter (assuming an esterification factor of 0.30 microgram of ethanol per microgram of SAP).

Fast delineation and visualization of vessels in 3-D angiographic images.

A method is presented which aids the clinician in obtaining quantitative measures and a three-dimensional (3-D) representation of vessels from 3-D angiographic data with a minimum of user interaction. Based on two user defined starting points, an iterative procedure tracks the central vessel axis. During the tracking process, the minimum diameter and a surface rendering of the vessels are computed, allowing for interactive inspection of the vasculature. Applications of the method to CTA, contrast enhanced (CE)-MRA and phase contrast (PC)-MRA images of the abdomen are shown. In all applications, a long stretch of vessels with varying width is tracked, delineated, and visualized, in less than 10 s on a standard clinical workstation.

The EASI project--improving the effectiveness and quality of image-guided surgery.

In recent years, advances in computer technology and a significant increase in the accuracy of medical imaging have made it possible to develop systems that can assist the clinician in diagnosis, planning, and treatment. This paper deals with an area that is generally referred to as computer-assisted surgery, image-directed surgery, or image-guided surgery. We report the research, development, and clinical validation performed since January 1996 in the European Applications in Surgical Interventions (EASI) project, which is funded by the European Commission in their "4th Framework Telematics Applications for Health" program. The goal of this project is the improvement of the effectiveness and quality of image-guided neurosurgery of the brain and image-guided vascular surgery of abdominal aortic aneurysms, while at the same time reducing patient risks and overall cost. We have developed advanced prototype systems for preoperative surgical planning and intraoperative surgical navigation, and we have extensively clinically validated these systems. The prototype systems and the clinical validation results are described in this paper.

Advances in three-dimensional diagnostic radiology.

The maturity of current 3D rendering software in combination with recent developments in computer vision techniques enable an exciting range of applications for the visualisation, measurement and interactive manipulation of volumetric data, relevant both for diagnostic imaging and for anatomy. This paper reviews recent work in this area from the Image Sciences Institute at Utrecht University. The processes that yield a useful visual presentation are sequential. After acquisition and before any visualisation, an essential step is to prepare the data properly: this field is known as 'image processing' or 'computer vision' in analogy with the processing in human vision. Examples will be discussed of modern image enhancement and denoising techniques, and the complex process of automatically finding the objects or regions of interest, i.e. segmentation. One of the newer and promising methodologies for image analysis is based on a mathematical analysis of the human (cortical) visual processing: multiscale image analysis. After preprocessing the 3D rendering can be acquired by simulating the 'ray casting' in the computer. New possibilities are presented, such as the integrated visualisation in one image of (accurately registered) datasets of the same patient acquired in different modality scanners. Other examples include colour coding of functional data such as SPECT brain perfusion or functional magnetic resonance (MR) data and even metric data such as skull thickness on the rendered 3D anatomy from MR or computed tomography (CT). Optimal use and perception of 3D visualisation in radiology requires fast display and truly interactive manipulation facilities. Modern and increasingly cheaper workstations ( < $10000) allow this to be a reality. It is now possible to manipulate 3D images of 256 at 15 frames per second interactively, placing virtual reality within reach. The possibilities of modern workstations become increasingly more sophisticated and versatile. Examples presented include the automatic detection of the optimal viewing angle of the neck of aneurysms and the simulation of the design and placement procedure of intra-abdominal aortic stents. Such developments, together with the availability of high-resolution datasets of modern scanners and data such as from the NIH Visible Human project, have a dramatic impact on interactive 3D anatomical atlases.