MR Angiography at 3 Tesla to Assess Proximal Internal Carotid Artery Stenoses: Contrast-Enhanced or 3D Time-of-Flight MR Angiography?

PURPOSE The aim of this study was to compare the diagnostic accuracy of 3D time-of-flight (TOF-MRA) and contrast-enhanced (CE-MRA) magnetic resonance angiography at 3 T for detection and quantification of proximal high-grade stenosis using multidetector computed tomography angiography (MDCTA) as reference standard. METHODS The institutional ethics committee approved this prospective study. A total of 41 patients suspected of having internal carotid artery (ICA) stenosis underwent both MDCTA and MRA. CE-MRA and TOF-MRA were performed using a 3.0-T imager with a dedicated eight-element cervical coil. ICA stenoses were measured according to the North American Symptomatic Carotid Endarterectomy Trial criteria and categorized as 0-25 % (minimal), 25-50 % (mild), 50-69 % (moderate), 70-99 % (high grade), and 100 % (occlusion). Sensitivity and specificity for the detection of high-grade ICA stenoses (70-99 %) and ICA occlusions were determined. In addition, intermodality agreement was assessed with κ-statistics for detection of high-grade ICA stenoses (70-99 %) and ICA occlusions. RESULTS A total of 80 carotid arteries of 41 patients were reviewed. Two previously stented ICAs were excluded from analysis. On MDCTA, 7 ICAs were occluded, 12 ICAs presented with and 63 without a high-grade ICA stenosis (70-99 %). For detecting 70-99 % stenosis, both 3D TOF-MRA and CE-MRA were 91.7 % sensitive and 98.5 % specific, respectively. Both MRA techniques were highly sensitive (100 %), and specific (CE-MRA, 100 %; TOF-MRA, 98.7 %) for the detection of ICA occlusion. However, TOF-MRA misclassified one high-grade stenosis as occlusion. Intermodality agreement for detection of 70-99 % ICA stenoses was excellent between TOF-MRA and CE-MRA [κ = 0.902, 95 % confidence interval (CI) = 0.769-1.000], TOF-MRA and MDCTA (κ = 0.902, 95 % CI = 0.769-1.000), and CE-MRA and MDCTA (κ = 0.902, 95 % CI = 0.769-1.000). CONCLUSION Both 3D TOF-MRA and CE-MRA at 3 T are reliable tools for detecting high-grade proximal ICA stenoses (70-99 %). 3D TOF-MRA might misclassify pseudo-occlusions as complete occlusions. If there are no contraindications for CE-MRA, CE-MRA is recommended as primary MR imaging modality.

Magnetic resonance imaging features of sinonasal disorders in horses.

Diseases of paranasal sinuses and nasal passages in horses can be a diagnostic challenge because of the complex anatomy of the head and limitations of many diagnostic modalities. Our hypothesis was that magnetic resonance (MR) imaging would provide excellent anatomical detail and soft tissue resolution, and would be accurate in the diagnosis of diseases of the paranasal sinuses and nasal passages in horses. Fourteen horses were imaged. Inclusion criteria were lesions located to the sinuses or nasal passages that underwent MR imaging and subsequent surgical intervention and/or histopathologic examination. A low field, 0.3 tesla open magnet was used. Sequences in the standard protocol were fast spin echo T2 sagittal and transverse, spin echo T1 transverse, short-tau inversion recovery (STIR) dorsal, gradient echo 3D T1 MPR dorsal (plain and contrast enhanced), spin echo T1 fatsat (contrast enhanced). Mean scan time to complete the examination was 53 min (range 39-99 min). Lesions identified were primary or secondary sinusitis (six horses), paranasal sinus cyst (four horses), progressive ethmoid hematoma (two horses), and neoplasia (two horses). The most useful sequences were fast spin echo T2 transverse and sagittal, STIR dorsal and FE3D MPR (survey and contrast enhanced). Fluid accumulation, mucosal thickening, presence of encapsulated contents, bone deformation, and thickening were common findings observed in MR imaging. In selected horses, magnetic resonance imaging is a useful tool in diagnosing lesions of the paranasal sinuses and nasal passages.

Reconstruction of 3D Vertebral Models from a Single 2D Lateral Fluoroscopic Image

Accurate three-dimensional (3D) models of lumbar vertebrae are required for image-based 3D kinematics analysis. MRI or CT datasets are frequently used to derive 3D models but have the disadvantages that they are expensive, time-consuming or involving ionizing radiation (e.g., CT acquisition). In this chapter, we present an alternative technique that can reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image and a statistical shape model. Cadaveric studies are conducted to verify the reconstruction accuracy by comparing the surface models reconstructed from a single lateral fluoroscopic image to the ground truth data from 3D CT segmentation. A mean reconstruction error between 0.7 and 1.4 mm was found.

Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Data Sets

This paper proposed an automated 3D lumbar intervertebral disc (IVD) segmentation strategy from MRI data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based approach. After that, a three-dimensional (3D) variable-radius soft tube model of the lumbar spine column is built to guide the 3D disc segmentation. The disc segmentation is achieved as a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.

Localization and Segmentation of 3D Intervertebral Discs in MR Images by Data Driven Estimation

This paper addresses the problem of fully-automatic localization and segmentation of 3D intervertebral discs (IVDs) from MR images. Our method contains two steps, where we first localize the center of each IVD, and then segment IVDs by classifying image pixels around each disc center as foreground (disc) or background. The disc localization is done by estimating the image displacements from a set of randomly sampled 3D image patches to the disc center. The image displacements are estimated by jointly optimizing the training and test displacement values in a data-driven way, where we take into consideration both the training data and the geometric constraint on the test image. After the disc centers are localized, we segment the discs by classifying image pixels around disc centers as background or foreground. The classification is done in a similar data-driven approach as we used for localization, but in this segmentation case we are aiming to estimate the foreground/background probability of each pixel instead of the image displacements. In addition, an extra neighborhood smooth constraint is introduced to enforce the local smoothness of the label field. Our method is validated on 3D T2-weighted turbo spin echo MR images of 35 patients from two different studies. Experiments show that compared to state of the art, our method achieves better or comparable results. Specifically, we achieve for localization a mean error of 1.6-2.0 mm, and for segmentation a mean Dice metric of 85%-88% and a mean surface distance of 1.3-1.4 mm.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

VIRTOPSY--scientific documentation, reconstruction and animation in forensic: individual and real 3D data based geo-metric approach including optical body/object surface and radiological CT/MRI scanning.

Until today, most of the documentation of forensic relevant medical findings is limited to traditional 2D photography, 2D conventional radiographs, sketches and verbal description. There are still some limitations of the classic documentation in forensic science especially if a 3D documentation is necessary. The goal of this paper is to demonstrate new 3D real data based geo-metric technology approaches. This paper present approaches to a 3D geo-metric documentation of injuries on the body surface and internal injuries in the living and deceased cases. Using modern imaging methods such as photogrammetry, optical surface and radiological CT/MRI scanning in combination it could be demonstrated that a real, full 3D data based individual documentation of the body surface and internal structures is possible in a non-invasive and non-destructive manner. Using the data merging/fusing and animation possibilities, it is possible to answer reconstructive questions of the dynamic development of patterned injuries (morphologic imprints) and to evaluate the possibility, that they are matchable or linkable to suspected injury-causing instruments. For the first time, to our knowledge, the method of optical and radiological 3D scanning was used to document the forensic relevant injuries of human body in combination with vehicle damages. By this complementary documentation approach, individual forensic real data based analysis and animation were possible linking body injuries to vehicle deformations or damages. These data allow conclusions to be drawn for automobile accident research, optimization of vehicle safety (pedestrian and passenger) and for further development of crash dummies. Real 3D data based documentation opens a new horizon for scientific reconstruction and animation by bringing added value and a real quality improvement in forensic science.

Postmortem quantitative 1.5-T MRI for the differentiation and characterization of serous fluids, blood, CSF, and putrefied CSF.

The purpose of the present study was to investigate whether serous fluids, blood, cerebrospinal fluid (CSF), and putrefied CSF can be characterized and differentiated in synthetically calculated magnetic resonance (MR) images based on their quantitative T 1, T 2, and proton density (PD) values. Images from 55 postmortem short axis cardiac and 31 axial brain 1.5-T MR examinations were quantified using a quantification sequence. Serous fluids, fluid blood, sedimented blood, blood clots, CSF, and putrefied CSF were analyzed for their mean T 1, T 2, and PD values. Body core temperature was measured during the MRI scans. The fluid-specific quantitative values were related to the body core temperature. Equations to correct for temperature differences were generated. In a 3D plot as well as in statistical analysis, the quantitative T 1, T 2 and PD values of serous fluids, fluid blood, sedimented blood, blood clots, CSF, and putrefied CSF could be well differentiated from each other. The quantitative T 1 and T 2 values were temperature-dependent. Correction of quantitative values to a temperature of 37 °C resulted in significantly better discrimination between all investigated fluid mediums. We conclude that postmortem 1.5-T MR quantification is feasible to discriminate between blood, serous fluids, CSF, and putrefied CSF. This finding provides a basis for the computer-aided diagnosis and detection of fluids and hemorrhages.

Automated 3D Lumbar Intervertebral Disc Segmentation from MRI Data Sets

This paper proposed an automated three-dimensional (3D) lumbar intervertebral disc (IVD) segmentation strategy from Magnetic Resonance Imaging (MRI) data. Starting from two user supplied landmarks, the geometrical parameters of all lumbar vertebral bodies and intervertebral discs are automatically extracted from a mid-sagittal slice using a graphical model based template matching approach. Based on the estimated two-dimensional (2D) geometrical parameters, a 3D variable-radius soft tube model of the lumbar spine column is built by model fitting to the 3D data volume. Taking the geometrical information from the 3D lumbar spine column as constraints and segmentation initialization, the disc segmentation is achieved by a multi-kernel diffeomorphic registration between a 3D template of the disc and the observed MRI data. Experiments on 15 patient data sets showed the robustness and the accuracy of the proposed algorithm.

Preoperative Planning of Periacetabular Osteotomy (PAO)

Pelvic osteotomies improve containment of the femoral head in cases of developmental dysplasia of the hip or in femoroacetabular impingement due to acetabular retroversion. In the evolution of osteotomies, the Ganz Periacetabular Osteotomy (PAO) is among the complex reorientation osteotomies and allows for complete mobilization of the acetabulum without compromising the integrity of the pelvic ring. For the complex reorientation osteotomies, preoperative planning of the required acetabular correction is an important step, due to the need to comprehend the three-dimensional (3D) relationship between acetabulum and femur. Traditionally, planning was performed using conventional radiographs in different projections, reducing the 3D problem to a two-dimensional one. Known disturbance variables, mainly tilt and rotation of the pelvis make assessment by these means approximate at the most. The advent of modern enhanced computation skills and new imaging techniques gave room for more sophisticated means of preoperative planning. Apart from analysis of acetabular geometry on conventional x-rays by sophisticated software applications, more accurate assessment of coverage and congruency and thus amount of correction necessary can be performed on multiplanar CT images. With further evolution of computer-assisted orthopaedic surgery, especially the ability to generate 3D models from the CT data, examiners were enabled to simulate the in vivo situation in a virtual in vitro setting. Based on this ability, different techniques have been described. They basically all employ virtual definition of an acetabular fragment. Subsequently reorientation can be simulated using either 3D calculation of standard parameters of femoroacetabular morphology, or joint contact pressures, or a combination of both. Other techniques employ patient specific implants, templates or cutting guides to achieve the goal of safe periacetabular osteotomies. This chapter will give an overview of the available techniques for planning of periacetabular osteotomy.

2D-3D Reconstruction-Based Planning of Total Hip Arthroplasty

This chapter proposed a personalized X-ray reconstruction-based planning and post-operative treatment evaluation framework called iJoint for advancing modern Total Hip Arthroplasty (THA). Based on a mobile X-ray image calibration phantom and a unique 2D-3D reconstruction technique, iJoint can generate patient-specific models of hip joint by non-rigidly matching statistical shape models to the X-ray radiographs. Such a reconstruction enables a true 3D planning and treatment evaluation of hip arthroplasty from just 2D X-ray radiographs whose acquisition is part of the standard diagnostic and treatment loop. As part of the system, a 3D model-based planning environment provides surgeons with hip arthroplasty related parameters such as implant type, size, position, offset and leg length equalization. With this newly developed system, we are able to provide true 3D solutions for computer assisted planning of THA using only 2D X-ray radiographs, which is not only innovative but also cost-effective.

Biomechanical validation of computer assisted planning of periacetabular osteotomy: A preliminary study based on finite element analysis

Periacetabular Osteotomy (PAO) is a joint preserving surgical intervention intended to increase femoral head coverage and thereby to improve stability in young patients with hip dysplasia. Previously, we developed a CT-based, computer-assisted program for PAO diagnosis and planning, which allows for quantifying the 3D acetabular morphology with parameters such as acetabular version, inclination, lateral center edge (LCE) angle and femoral head coverage ratio (CO). In order to verify the hypothesis that our morphology-based planning strategy can improve biomechanical characteristics of dysplastic hips, we developed a 3D finite element model based on patient-specific geometry to predict cartilage contact stress change before and after morphology-based planning. Our experimental results demonstrated that the morphology-based planning strategy could reduce cartilage contact pressures and at the same time increase contact areas. In conclusion, our computer-assisted system is an efficient tool for PAO planning.