Intravascular ultrasound: validation and clinical application

Atherogenesis is a process with an insidious onset and course. Once clinical signs and symptoms have become manifest, the obstructive lesion is usually at an advanced stage. Arteriography is the standard method for evaluation of atherosclerotic disease and has been useful in identifying the location and approximate severity of the stenotic lesion. Although arteriography provides a silhouette of the vessel lumen, it does not provide accurate knowledge on cross-sectional lumen area, vessel area, shape and morphology of the stenotic lesion. Intravascular ultrasound (lVUS) may overcome these limitations by providing a tomographic image of the vessel. The aim of this work is to validate IVUS and to evaluate subsequent clinical application of this imaging technique. The subjects dealt with in this dissertation are categorised into 5 main topics. I) displacement sensing device; 2) validation of IVUS-derived parameters; 3) the spectrum of vascular morphology before and after intervention determined by IVUS; 4) IVUS as a research tool; 5) IVUS as a clinical too

What have we learned from in vitro intravascular ultrasound?

In vitro studies have established that intravascular ultrasound is a reliable technique for accurate assessment of vascular anatomic structure and disease conditions before and after intervention. In addition, quantitative data from intravascular ultrasound studies correspond well with histologic findings, which serve as the gold standard. These in vitro studies permit the understanding and interpretation of ultrasound images obtained in vivo, although differences between the two settings should be taken into account. New ultrasound modalities currently being developed may enhance the diagnostic differentiation of plaque morphologic characteristics and facilitate on-line quantitative assessment of vessel structure

Low-Dose Computed Tomography With Two- and Three-Dimensional Postprocessing as an Alternative to Plain Radiography for Intrathecal Catheter Visualization: A Phantom Pilot Study

Objectives: In intrathecal drug delivery, visualization of the device has been performed with plain radiography. However, the visibility of the related structures can be problematic. In troubleshooting, after the contrast material injection via the cathe

Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data

To evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two anthropomorphic phantoms in three different sizes (thorax and abdomen, QRM GmbH), in combination with a custom-built insert containing cavities filled with water, and water with 15 mg iodine/mL, were scanned on an EID-based scanner (Siemens SOMATOM Force) and on a PCD-based scanner (Siemens, NAEOTOM Alpha). VMI (range 40–100 keV) were reconstructed without an iterative reconstruction (IR) technique and with an IR strength of 60% for the EID technique (ADMIRE) and closest matching IR strengths of 50% and 75% for the PCD technique (QIR). CNR was defined as the difference in mean CT numbers of water, and water with iodine, divided by the root mean square value of the measured noise in water, and water with iodine. A two-sample t-test was performed to evaluate differences in CNR between images. A p-value &lt; 0.05 was considered statistically significant. For VMI without IR and below 60 keV, the CNR of the PCD-based images at 120 and 90 kVp was up to 55% and 75% higher than the CNR of the EID-based images, respectively (p &lt; 0.05). For VMI above 60 keV, CNRs of PCD-based images at both 120 and 90 kVp were up to 20% lower than the CNRs of EID-based images. Similar or improved performance of PCD-based images in comparison with EID-based images were observed for VMIs reconstructed with IR techniques. In conclusion, with PCD-CT, iodine CNR on low energy VMI (&lt;60 keV) is better than with EID-CT.</p

Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks

Intracranial carotid artery calcification (ICAC) is a major risk factor for stroke, and might contribute to dementia and cognitive decline. Reliance on time-consuming manual annotation of ICAC hampers much demanded further research into the relationship between ICAC and neurological diseases. Automation of ICAC segmentation is therefore highly desirable, but difficult due to the proximity of the lesions to bony structures with a similar attenuation coefficient. In this paper, we propose a method for automatic segmentation of ICAC; the first to our knowledge. Our method is based on a 3D fully convolutional neural network that we extend with two regularization techniques. Firstly, we use deep supervision (hidden layers supervision) to encourage discriminative features in the hidden layers. Secondly, we augment the network with skip connections, as in the recently developed ResNet, and dropout layers, inserted in a way that skip connections circumvent them. We investigate the effect of skip connections and dropout. In addition, we propose a simple problem-specific modification of the network objective function that restricts the focus to the most important image regions and simplifies the optimization. We train and validate our model using 882 CT scans and test on 1,000. Our regularization techniques and objective improve the average Dice score by 7.1%, yielding an average Dice of 76.2% and 97.7% correlation between predicted ICAC volumes and manual annotations.Comment: Accepted for MICCAI 201

MRI-based biomechanical parameters for carotid artery plaque vulnerability assessment.

Carotid atherosclerotic plaques are a major cause of ischaemic stroke. The biomechanical environment to which the arterial wall and plaque is subjected to plays an important role in the initiation, progression and rupture of carotid plaques. MRI is frequently used to characterize the morphology of a carotid plaque, but new developments in MRI enable more functional assessment of carotid plaques. In this review, MRI based biomechanical parameters are evaluated on their current status, clinical applicability, and future developments. Blood flow related biomechanical parameters, including endothelial wall shear stress and oscillatory shear index, have been shown to be related to plaque formation. Deriving these parameters directly from MRI flow measurements is feasible and has great potential for future carotid plaque development prediction. Blood pressure induced stresses in a plaque may exceed the tissue strength, potentially leading to plaque rupture. Multi-contrast MRI based stress calculations in combination with tissue strength assessment based on MRI inflammation imaging may provide a plaque stress-strength balance that can be used to assess the plaque rupture risk potential. Direct plaque strain analysis based on dynamic MRI is already able to identify local plaque displacement during the cardiac cycle. However, clinical evidence linking MRI strain to plaque vulnerability is still lacking. MRI based biomechanical parameters may lead to improved assessment of carotid plaque development and rupture risk. However, better MRI systems and faster sequences are required to improve the spatial and temporal resolution, as well as increase the image contrast and signal-to-noise ratio.This is the author accepted manuscript. The final version is available from Schattauer via http://dx.doi.org/10.1160/TH15-09-071