Vesselness-based 2D–3D registration of the coronary arteries

Purpose  Robust and accurate automated co-registration of the coronary arteries in 3D CTA and 2D X-ray angiography during percutaneous coronary interventions (PCI), in order to present a fused visualization. Methods  A novel vesselness-based similarity measure was developed, that avoids an explicit segmentation of the X-ray image. A stochastic optimizer searches the optimal registration using the similarity measure. Results  Both simulated data and clinical data were used to investigate the accuracy and capture range of the proposed method. The experiments show that the proposed method outperforms the iterative closest point method in terms of accuracy (average residual error of 0.42 mm vs. 1.44 mm) and capture range (average 71.1 mm/20.3° vs. 14.1 mm/5.2°). Conclusion  The proposed method has proven to be accurate and the capture range is ample for usage in PCI. Especially the absence of an explicit segmentation of the interventionally acquired X-ray images considerably aids the robustness of the method.     

Computer assisted determination of acetabular cup orientation using 2D–3D image registration

Background  

2D–3D image-based registration methods have been developed to measure acetabular cup orientation after total hip arthroplasty (THA). These methods require registration of both the prosthesis and the CT images to 2D radiographs and compute implant position with respect to a reference. The application of these methods is limited in clinical practice due to two limitations: (1) the requirement of a computer-aided design (CAD) model of the prosthesis, which may be unavailable due to the proprietary concerns of the manufacturer, and (2) the requirement of either multiple radiographs or radiograph-specific calibration, usually unavailable for retrospective studies. In this paper, we propose a new method to address these limitations.     

Fast and robust 3D ultrasound registration – Block and game theoretic matching

Real-time 3D US has potential for image guidance in minimally invasive liver interventions. However, motion caused by patient breathing makes it hard to visualize a localized area, and to maintain alignment with pre-operative information. In this work we develop a fast affine registration framework to compensate in real-time for liver motion/displacement due to breathing. The affine registration of two consecutive ultrasound volumes in time is performed using block-matching. For a set of evenly distributed points in one volume and their correspondences in the other volume, we propose a robust outlier rejection method to reject false matches. The inliers are then used to determine the affine transformation. The approach is evaluated on 13 4D ultrasound sequences acquired from 8 subjects. For 91 pairs of 3D ultrasound volumes selected from these sequences, a mean registration error of 1.8 mm is achieved. A graphics processing unit (GPU) implementation runs the 3D US registration at 8 Hz.     

A framework for automatic creation of gold-standard rigid 3D–2D registration datasets

Purpose

Advanced image-guided medical procedures incorporate 2D intra-interventional information into pre-interventional 3D image and plan of the procedure through 3D/2D image registration (32R). To enter clinical use, and even for publication purposes, novel and existing 32R methods have to be rigorously validated. The performance of a 32R method can be estimated by comparing it to an accurate reference or gold standard method (usually based on fiducial markers) on the same set of images (gold standard dataset). Objective validation and comparison of methods are possible only if evaluation methodology is standardized, and the gold standard  dataset is made publicly available. Currently, very few such datasets exist and only one contains images of multiple patients acquired during a procedure. To encourage the creation of gold standard 32R datasets, we propose an automatic framework.

Methods

The framework is based on rigid registration of fiducial markers. The main novelty is spatial grouping of fiducial markers on the carrier device, which enables automatic marker localization and identification across the 3D and 2D images.

Results

The proposed framework was demonstrated on clinical angiograms of 20 patients. Rigid 32R computed by the framework was more accurate than that obtained manually, with the respective target registration error below 0.027 mm compared to 0.040 mm.

Conclusion

The framework is applicable for gold standard setup on any rigid anatomy, provided that the acquired images contain spatially grouped fiducial markers. The gold standard datasets and software will be made publicly available.

     

Assessment of spline‐based 2D–3D registration for image‐guided spine surgery

2D–3D registration of pre‐operative 3D volumetric data with a series of calibrated and undistorted intra‐operative 2D projection images has shown great potential in CT‐based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline‐based multi‐resolution 2D–3D image registration algorithm has been adapted together with a novel least‐squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D–3D registration algorithm to achieve sub‐millimeter accuracy in a realistic setup in less than one minute.     

Organ-focused mutual information for nonrigid multimodal registration of liver CT and Gd–EOB–DTPA-enhanced MRI

Accurate detection of liver lesions is of great importance in hepatic surgery planning. Recent studies have shown that the detection rate of liver lesions is significantly higher in gadoxetic acid-enhanced magnetic resonance imaging (Gd–EOB–DTPA-enhanced MRI) than in contrast-enhanced portal-phase computed tomography (CT); however, the latter remains essential because of its high specificity, good performance in estimating liver volumes and better vessel visibility. To characterize liver lesions using both the above image modalities, we propose a multimodal nonrigid registration framework using organ-focused mutual information (OF-MI). This proposal tries to improve mutual information (MI) based registration by adding spatial information, benefiting from the availability of expert liver segmentation in clinical protocols. The incorporation of an additional information channel containing liver segmentation information was studied. A dataset of real clinical images and simulated images was used in the validation process. A Gd–EOB–DTPA-enhanced MRI simulation framework is presented. To evaluate results, warping index errors were calculated for the simulated data, and landmark-based and surface-based errors were calculated for the real data. An improvement of the registration accuracy for OF-MI as compared with MI was found for both simulated and real datasets. Statistical significance of the difference was tested and confirmed in the simulated dataset (p < 0.01).     

A novel approach to 2D/3D registration of X-ray images using Grangeat’s relation

Fast and accurate 2D/3D registration plays an important role in many applications, ranging from scientific and engineering domains all the way to medical care. Today’s predominant methods are based on computationally expensive approaches, such as virtual forward or back projections, that limit the real-time applicability of the routines. Here, we present a novel concept that makes use of Grangeat’s relation to intertwine information from the 3D volume and the 2D projection space in a way that allows pre-computation of all time-intensive steps. The main effort within actual registration tasks is reduced to simple resampling of the pre-calculated values, which can be executed rapidly on modern GPU hardware. We analyze the applicability of the proposed method on simulated data under various conditions and evaluate the findings on real data from a C-arm CT scanner. Our results show high registration quality in both simulated as well as real data scenarios and demonstrate a reduction in computation time for the crucial computation step by a factor of six to eight when compared to state-of-the-art routines. With minor trade-offs in accuracy, this speed-up can even be increased up to a factor of 100 in particular settings. To our knowledge, this is the first application of Grangeat’s relation to the topic of 2D/3D registration. Due to its high computational efficiency and broad range of potential applications, we believe it constitutes a highly relevant approach for various problems dealing with cone beam transmission images.     

Preoperative liver registration for augmented monocular laparoscopy using backward–forward biomechanical simulation

Purpose

Augmented reality for monocular laparoscopy from a preoperative volume such as CT is achieved in two steps. The first step is to segment the organ in the preoperative volume and reconstruct its 3D model. The second step is to register the preoperative 3D model to an initial intraoperative laparoscopy image. To date, there does not exist an automatic initial registration method to solve the second step for the liver in the de facto operating room conditions of monocular laparoscopy. Existing methods attempt to solve for both deformation and pose simultaneously, leading to nonconvex problems with no optimal solution algorithms.

Methods

We propose in contrast to break the problem down into two parts, solving for (i) deformation and (ii) pose. Part (i) simulates biomechanical deformations from the preoperative to the intraoperative state to predict the liver’s unknown intraoperative shape by modeling gravity, the abdominopelvic cavity’s pressure and boundary conditions. Part (ii) rigidly registers the simulated shape to the laparoscopy image using contour cues.

Results

Our formulation leads to a well-posed problem, contrary to existing methods. This is because it exploits strong environment priors to complement the weak laparoscopic visual cues.

Conclusion

Quantitative results with in silico and phantom experiments and qualitative results with laparosurgery images for two patients show that our method outperforms the state-of-the-art in accuracy and registration time.

     

3D–2D registration in endovascular image-guided surgery: evaluation of state-of-the-art methods on cerebral angiograms

Purpose

Image guidance for minimally invasive surgery is based on spatial co-registration and fusion of 3D pre-interventional images and treatment plans with the 2D live intra-interventional images. The spatial co-registration or 3D–2D registration is the key enabling technology; however, the performance of state-of-the-art automated methods is rather unclear as they have not been assessed under the same test conditions. Herein we perform a quantitative and comparative evaluation of ten state-of-the-art methods for 3D–2D registration on a public dataset of clinical angiograms.

Methods

Image database consisted of 3D and 2D angiograms of 25 patients undergoing treatment for cerebral aneurysms or arteriovenous malformations. On each of the datasets, highly accurate “gold-standard” registrations of 3D and 2D images were established based on patient-attached fiducial markers. The database was used to rigorously evaluate ten state-of-the-art 3D–2D registration methods, namely two intensity-, two gradient-, three feature-based and three hybrid methods, both for registration of 3D pre-interventional image to monoplane or biplane 2D images.

Results

Intensity-based methods were most accurate in all tests (0.3 mm). One of the hybrid methods was most robust with 98.75% of successful registrations (SR) and capture range of 18 mm for registrations of 3D to biplane 2D angiograms. In general, registration accuracy was similar whether registration of 3D image was performed onto mono- or biplanar 2D images; however, the SR was substantially lower in case of 3D to monoplane 2D registration. Two feature-based and two hybrid methods had clinically feasible execution times in the order of a second.

Conclusions

Performance of methods seems to fall below expectations in terms of robustness in case of registration of 3D to monoplane 2D images, while translation into clinical image guidance systems seems readily feasible for methods that perform registration of the 3D pre-interventional image onto biplanar intra-interventional 2D images.

     

What is the ideal approach for emergent pericardiocentesis using point-of-care ultrasound guidance?

BACKGROUND: Traditionally performed using a subxiphoid approach, the increasing use of point-of-care ultrasound in the emergency department has made other approaches (parasternal and apical) for pericardiocentesis viable. The aim of this study is to identify the ideal approach for emergency-physician-performed ultrasound-guided pericardiocentesis as determined by ultrasound image quality, distance from surface to pericardial fluid, and likely obstructions or complications.     

Deproteination of whole blood for LC–MS/MS using paramagnetic micro-particles

Objectives

Liquid chromatography tandem mass spectrometry has become increasingly popular in clinical laboratories over the last decade due to the inherent sensitivity and specificity of the technology. Nevertheless, full automation and hence application in routine laboratories is still hampered by laborious and difficult-to-automate sample pre-treatment protocols. Functionalized paramagnetic micro-particles could simplify sample pre-treatment and ease automation. We evaluated the applicability of a pre-commercial, straightforward paramagnetic micro-particle based kit for the lysis and deproteination of whole blood for the LC–MS/MS analysis of everolimus and compared the performance to our routine protein precipitation method.

Design and methods

Samples were prepared for LC–MS/MS everolimus analysis on an Acquity UPLC chromatographic system coupled to a TQD mass spectrometer (both Waters Ltd.) using a pre-commercial MagSi-TDMprep kit and a routine protein precipitation respectively. Both pre-treatment methods were validated for imprecision, accuracy, linearity, limit of quantification, matrix effect, recovery and process efficiency. A method comparison (n = 63) between both pre-treatment methods was performed.

Results

Imprecision and bias were within pre-defined criteria (15%) for both pre-treatment methods. Both methods were linear from 1.2 to 14.8 μg/L with a limit of quantification of 0.6 μg/L. Process efficiency was on average 65% for protein precipitation pre-treatment and was substantially higher for the MagSi-TDMprep method (85%). A Passing–Bablok regression showed no significant difference between the two pre-treatment methods.

Conclusion

For everolimus in whole blood, the MagSi-TDMprep sample pre-treatment was applicable and comparable to protein precipitation for LC–MS/MS with the possible advantage of easier automation.     

High-throughput liquid–liquid extraction and LCMSMS assay for determination of circulating 25(OH) vitamin D3 and D2 in the routine clinical laboratory

BackgroundIncreasing focus on vitamin D as essential to health has underscored the need for accurate and precise high-throughput measurement of serum 25(OH)D.MethodsSerum was denatured in acetonitrile containing hexadeuterated 25(OH)D3 as internal standard (IS) and automatically applied to filter plates packed with inert diatomous earth material for subsequent heptane extraction. Extracts were chromatographed on a C12 HPLC column, and detected on a triple quadropole mass spectrometer.ResultsThe inter-assay precision was 9.4% and 8.8% respectively at 32.0 and 59.7 nmol/l for 25(OH)D3 and 8.6% and 8.0% at 23.4 and 64.4 nmol/l for 25(OH)D2. The detection limit was 10 nmol/l for both metabolites. Three percent of samples contained > 50 nmol/l 25(OH)D2. Total run time was 4 min. We have performed more than 200,000 routine samples and the method performs well in external control schemes.ConclusionWe describe a robust, high-throughput, LLE-LCMSMS method for accurate and precise quantitation of 25(OH)D3 and 25(OH)D2 in serum. The use of diatomaceous earth material for extraction of vitamin D in 96-well format enables fast, simple and efficient sample preparation. The method offers a cost-effective alternative to immunological methods for use in the routine clinical biochemical laboratory.     

TRUS–MRI image registration: a paradigm shift in the diagnosis of significant prostate cancer

Accuracy of multiparametric MRI has greatly improved the ability of localizing tumor foci of prostate cancer. This property can be used to perform a TRUS–MR image registration, new technological advance, which allows for an overlay of an MRI onto a TRUS image to target a prostate biopsy toward a suspicious area Three types of registration have been developed: cognitive-based, sensor-based, and organ-based registration. Cognitive registration consists of aiming a suspicious area during biopsy with the knowledge of the lesion location identified on multiparametric MRI. Sensor-based registration consists of tracking in real time the TRUS probe with a magnetic device, achieving a global positioning system which overlays in real-time prostate image on both modalities. Its main limitation is that it does not take into account prostate and patient motion during biopsy. Two systems (Artemis and Uronav) have been developed to partially circumvent this drawback. Organ-based registration (Koelis) does not aim to track the TRUS probe, but the prostate itself to compute in a 3D acquisition the TRUS prostate shape, allowing for a registration with the corresponding 3D MRI shape. This system is not limited by prostate/patient motion and allows for a deformation of the organ during registration. Pros and cons of each technique and the rationale for a targeted biopsy only policy are discussed.