3D registration of MR and X-ray spine images using an articulated model

Présentation: Cet article a été publié dans le journal : Computerised medical imaging and graphics (CMIG). Le but de cet article est de recaler les vertèbres extraites à partir d’images RM avec des vertèbres extraites à partir d’images RX pour des patients scoliotiques, en tenant compte des déformations non-rigides due au changement de posture entre ces deux modalités. À ces fins, une méthode de recalage à l’aide d’un modèle articulé est proposée. Cette méthode a été comparée avec un recalage rigide en calculant l’erreur sur des points de repère, ainsi qu’en calculant la différence entre l’angle de Cobb avant et après recalage. Une validation additionelle de la méthode de recalage présentée ici se trouve dans l’annexe A. Ce travail servira de première étape dans la fusion des images RM, RX et TP du tronc complet. Donc, cet article vérifie l’hypothèse 1 décrite dans la section 3.2.1.Abstract This paper presents a magnetic resonance image (MRI)/X-ray spine registration method that compensates for the change in the curvature of the spine between standing and prone positions for scoliotic patients. MRIs in prone position and X-rays in standing position are acquired for 14 patients with scoliosis. The 3D reconstructions of the spine are then aligned using an articulated model which calculates intervertebral transformations. Results show significant decrease in regis- tration error when the proposed articulated model is compared with rigid registration. The method can be used as a basis for full body MRI/X-ray registration incorporating soft tissues for surgical simulation.Canadian Institute of Health Research (CIHR

Segmentation and Fracture Detection in CT Images for Traumatic Pelvic Injuries

In recent decades, more types and quantities of medical data have been collected due to advanced technology. A large number of significant and critical information is contained in these medical data. High efficient and automated computational methods are urgently needed to process and analyze all available medical data in order to provide the physicians with recommendations and predictions on diagnostic decisions and treatment planning. Traumatic pelvic injury is a severe yet common injury in the United States, often caused by motor vehicle accidents or fall. Information contained in the pelvic Computed Tomography (CT) images is very important for assessing the severity and prognosis of traumatic pelvic injuries. Each pelvic CT scan includes a large number of slices. Meanwhile, each slice contains a large quantity of data that may not be thoroughly and accurately analyzed via simple visual inspection with the desired accuracy and speed. Hence, a computer-assisted pelvic trauma decision-making system is needed to assist physicians in making accurate diagnostic decisions and determining treatment planning in a short period of time. Pelvic bone segmentation is a vital step in analyzing pelvic CT images and assisting physicians with diagnostic decisions in traumatic pelvic injuries. In this study, a new hierarchical segmentation algorithm is proposed to automatically extract multiplelevel bone structures using a combination of anatomical knowledge and computational techniques. First, morphological operations, image enhancement, and edge detection are performed for preliminary bone segmentation. The proposed algorithm then uses a template-based best shape matching method that provides an entirely automated segmentation process. This is followed by the proposed Registered Active Shape Model (RASM) algorithm that extracts pelvic bone tissues using more robust training models than the Standard ASM algorithm. In addition, a novel hierarchical initialization process for RASM is proposed in order to address the shortcoming of the Standard ASM, i.e. high sensitivity to initialization. Two suitable measures are defined to evaluate the segmentation results: Mean Distance and Mis-segmented Area to quantify the segmentation accuracy. Successful segmentation results indicate effectiveness and robustness of the proposed algorithm. Comparison of segmentation performance is also conducted using both the proposed method and the Snake method. A cross-validation process is designed to demonstrate the effectiveness of the training models. 3D pelvic bone models are built after pelvic bone structures are segmented from consecutive 2D CT slices. Automatic and accurate detection of the fractures from segmented bones in traumatic pelvic injuries can help physicians detect the severity of injuries in patients. The extraction of fracture features (such as presence and location of fractures) as well as fracture displacement measurement, are vital for assisting physicians in making faster and more accurate decisions. In this project, after bone segmentation, fracture detection is performed using a hierarchical algorithm based on wavelet transformation, adaptive windowing, boundary tracing and masking. Also, a quantitative measure of fracture severity based on pelvic CT scans is defined and explored. The results are promising, demonstrating that the proposed method not only capable of automatically detecting both major and minor fractures, but also has potentials to be used for clinical applications

Pelvic kinematics as confounding factor for cam hip impingement

The purpose of this thesis was to explore a range of biomechanical factors linked to the development of symptoms and potentially early onset hip OA in people with cam hip impingement. This was achieved through shape analysis on 3D bone models (segmented from medical images), and motion analysis performed during walking and squatting. Following ethical approval, kinematic and morphological variables were obtained from 19 pre-operative hip impingement patients and 18 healthy controls, and these were compared between groups. Patients demonstrated reduced neck-shaft-angles (-6.0°, p<.01) and increased anterior pelvic tilt during gait (+3.2°, p=.04) which are thought to predispose to impingement by decreasing the proximity between the cam and acetabular rim and making abutment more likely. The transverse pelvic plane is used to measure pelvic tilt during motion analysis, it is therefore interesting that the angle between the transverse and anterior pelvic plane is increased (+4.6°, p=.03) in patients, emphasising that the interplay between shape and function is a priority for further research. Avoidance of hip extension (-5.9°, p<.01) was also observed, which could be a compensatory mechanism to prevent further damages to the hip. Furthermore, large cams are thought to act as a mechanical constraint and limit rotation movement allowed within the acetabulum, as demonstrated by reduced peak hip internal rotation (during squat, -8.5°, p=.03). Controls were regrouped based on morphology to allow comparison between asymptomatic (CAM-; n=11) and symptomatic (CAM+, n=16) cams. Symptomatic cams have an increased width (+41.4°, p<.01), and start more superiorly (-29.4°, p<.01). Increased sagittal pelvic mobility (e.g. during a squat; -11.2° for CAM+, p<.01) is thought to be protective against hip impingement symptoms, as during high flexion angles the pelvic tilts backwards reducing the risk of abutment. These findings highlight the need to establish thresholds taking confounding factors into account.Open Acces

Development of ultrasound to measure deformation of functional spinal units in cervical spine

Neck pain is a pervasive problem in the general population, especially in those working in vibrating environments, e.g. military troops and truck drivers. Previous studies showed neck pain was strongly associated with the degeneration of intervertebral disc, which is commonly caused by repetitive loading in the work place. Currently, there is no existing method to measure the in-vivo displacement and loading condition of cervical spine on the site. Therefore, there is little knowledge about the alternation of cervical spine functionality and biomechanics in dynamic environments. In this thesis, a portable ultrasound system was explored as a tool to measure the vertebral motion and functional spinal unit deformation. It is hypothesized that the time sequences of ultrasound imaging signals can be used to characterize the deformation of cervical spine functional spinal units in response to applied displacements and loading. Specifically, a multi-frame tracking algorithm is developed to measure the dynamic movement of vertebrae, which is validated in ex-vivo models. The planar kinematics of the functional spinal units is derived from a dual ultrasound system, which applies two ultrasound systems to image C-spine anteriorly and posteriorly. The kinematics is reconstructed from the results of the multi-frame movement tracking algorithm and a method to co-register ultrasound vertebrae images to MRI scan. Using the dual ultrasound, it is shown that the dynamic deformation of functional spinal unit is affected by the biomechanics properties of intervertebral disc ex-vivo and different applied loading in activities in-vivo. It is concluded that ultrasound is capable of measuring functional spinal units motion, which allows rapid in-vivo evaluation of C-spine in dynamic environments where X-Ray, CT or MRI cannot be used.2020-02-20T00:00:00

Imaging biomarkers as outcome measures for hereditary and acquired neuromuscular diseases

The generic term biomarkers applies to all detection methods used in the life sciences and may be defined as any detectable biologic parameter, whether biochemical, genetic, histologic, anatomic, physical, functional, or metabolic. By logical extension, we define imaging biomarkers as any anatomic, physiologic, biochemical, or molecular parameter detectable with one or more diagnostic imaging tools for establishing the presence and/or severity of disease. The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. During the three-years Phd project, in collaboration with the Radiology Department of Poliliclinico San Martino/ Dipartimento di Scienze della Salute, the Neurology Unit of Policlinico San Martino / Dipartimento di Scienza della Salute and the Anatomy Departement of University of Barcelona/Campus Bellvitge, the clinical applications of new or recently developed imaging biomarkers based on High Resolution Ultrasound (HRUS) a Magnetic Resonance (MR) in the field of neuromuscular diseases have been indagated. The recent advancements in Ultrasound technology enabled a high resolution and Ultra-High resolution imaging of peripheral nerves. In this regard, the fascicular imaging application in the diagnosis of posterior interosseous nerve and the motor branch of median nerve have been subject of two clinical study. The availability of a 7 tesla MR in the Animal facility of Policlinico San Martino allowed an high-tech study on a murin model of Charcot-Marie-Tooth neuropathy 1B, providing new insight into the pathogenesis of this condition. Regarding the myopathies, a specific focus was sarcopenia and the Ultrasound-derived quantitative and semiquantitative parameters to identify this common condition, to stratify the disease severity and to facilitate the patient monitoring overtime