Intravascular ultrasound in the coronary arteries

Ultrasound capsule endoscopy: sounding out the future

Video capsule endoscopy (VCE) has been of immense benefit in the diagnosis and management of gastrointestinal (GI) disorders since its introduction in 2001. However, it suffers from a number of well recognized deficiencies. Amongst these is the limited capability of white light imaging, which is restricted to analysis of the mucosal surface. Current capsule endoscopes are dependent on visual manifestation of disease and limited in regards to transmural imaging and detection of deeper pathology. Ultrasound capsule endoscopy (USCE) has the potential to overcome surface only imaging and provide transmural scans of the GI tract. The integration of high frequency microultrasound (µUS) into capsule endoscopy would allow high resolution transmural images and provide a means of both qualitative and quantitative assessment of the bowel wall. Quantitative ultrasound (QUS) can provide data in an objective and measurable manner, potentially reducing lengthy interpretation times by incorporation into an automated diagnostic process. The research described here is focused on the development of USCE and other complementary diagnostic and therapeutic modalities. Presently investigations have entered a preclinical phase with laboratory investigations running concurrently.

Intraosseous ultrasonography to determine the accuracy of drill hole positioning prior to the placement of pedicle screws: an experimental study

Object

Dorsal fixation with rods and pedicle screws (PSs) is the most frequently used surgery to correct traumatic and degenerative instabilities of the human spine. Prior to screw placement, screw holes are drilled along the vertebral pedicles. Despite the use of a variety of techniques, misplacement of screw holes, and consequently of the PSs, is a common problem. The authors investigated the usefulness of an intraspinal, intraosseous ultrasonography technique to determine the accuracy of drill hole positioning.

Methods

An endovascular ultrasound transducer was used for the intraluminal scanning of bore holes in trabecular bovine bone, 12 pedicle drill holes in cadaveric human spine, and 4 pedicle drill holes in a patient undergoing thoracic spondylodesis. Seven of the experimental bore holes in the cadaveric spine were placed optimally (that is, inside the pedicle) and 5 were placed suboptimally (breaching the medial or lateral cortical surface of the pedicle). Computed tomography scans were obtained in the patient and cadaveric specimen after the procedure.

Results

The image quality achieved in examinations of native bovine bone tissue, the formalin-fixed human spine specimen, and human vertebrae in vivo was equal. The authors endosonographically identified correct intrapedicular and intravertebral positions as well as poor (cortex breached) placement of drill holes.

Conclusions

Intraosseous ultrasonography is a promising technique for the investigation of PS holes prior to screw implantation, and may add to the safety of PS placement.

Identification of Inflamed Atherosclerotic Plaque using 123I-Labeled Interleukin-2 Scintigraphy in High-Risk Peritoneal Dialysis Patients: A Pilot Study

Background

Patients with end-stage renal disease (ESRD) suffer from markedly increased cardiovascular morbidity and mortality. Common carotid artery (CCA) intima-media thickness (IMT) assessment and CCA plaque identification using ultrasound are well-recognized tools for identification and monitoring of atherosclerosis. A new method for monitoring the inflammatory status of plaque, namely radiolabeled interleukin-2 (IL-2) scintigraphy, was proposed recently. The aim of this pilot study was to perform 123I-labeled-IL-2 carotid plaque scintigraphy in ESRD patients treated with peritoneal dialysis and to correlate obtained results with ultrasound assessment of CCA and selected inflammatory markers.

Methods

CCA-IMT was measured and CCA plaques were identified by ultrasound in 10 patients (5 women, 5 men; mean age 62.4 ± 10.4 years; median peritoneal dialysis duration 32.5 months, range 12 – 55 months) with advanced cardiovascular comorbidity. Following CCA ultrasound, 123I-labeled IL-2 carotid plaque scintigraphy was performed. Several biomarkers of inflammation and atherosclerosis were also measured in all patients.

Results

Mean target/non-target ratio for focal 123I-IL-2 uptake within the plaque was 3.15 ± 0.54, and mean IMT from the site of the scintigraphy analysis was 0.975 ± 0.337 mm. Highly significant correlation was found between CCA-IMT and a target/non-target ratio for focal 123I-IL-2 uptake in a corresponding artery ( R = 0.92, p = 0.01). However, no significant correlations were found between target/non-target ratio for focal 123I-IL-2 uptake and levels of measured biomarkers.

Conclusions

Our preliminary results suggest potential for identification of an inflamed (vulnerable) plaque using IL-2 scintigraphy in ESRD patients with cardiovascular comorbidities.

Robust principal component analysis and clustering methods for automated classification of tissue response to ARFI excitation

We introduce a new method for automatic classification of acoustic radiation force impulse (ARFI) displacement profiles using what have been termed "robust" methods for principal component analysis (PCA) and clustering. Unlike classical approaches, the robust methods are less sensitive to high variance outlier profiles and require no a priori information regarding expected tissue response to ARFI excitation. We first validate our methods using synthetic data with additive noise and/or outlier curves. Second, the robust techniques are applied to classifying ARFI displacement profiles acquired in an atherosclerotic familial hypercholesterolemic (FH) pig iliac artery in vivo. The in-vivo classification results are compared with parametric ARFI images showing peak induced displacement and time to 67% recovery and to spatially correlated immunohistochemistry. Our results support that robust techniques outperform conventional PCA and clustering approaches to classification when ARFI data are inclusive of low to relatively high noise levels (up to 5 dB average signal-to-noise [SNR] to amplitude) but no outliers: for example, 99.53% correct for robust techniques vs. 97.75% correct for the classical approach. The robust techniques also perform better than conventional approaches when ARFI data are inclusive of moderately high noise levels (10 dB average SNR to amplitude) in addition to a high concentration of outlier displacement profiles (10% outlier content): for example, 99.87% correct for robust techniques vs. 33.33% correct for the classical approach. This work suggests that automatic identification of tissue structures exhibiting similar displacement responses to ARFI excitation is possible, even in the context of outlier profiles. Moreover, this work represents an important first step toward automatic correlation of ARFI data to spatially matched immunohistochemistry.