Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.

Cardiac Magnetic Resonance Imaging: What Can It Add to Our Knowledge of the Right Ventricle in Pulmonary Arterial Hypertension?

Pulmonary arterial hypertension (PAH) is a disease of the pulmonary vasculature characterized by vasoconstriction and vascular remodeling leading to a progressive increase in pulmonary vascular resistance (PVR). It is becoming increasingly recognized that it is the response of the right ventricle (RV) to the increased afterload resulting from this increase in PVR that is the most important determinant of patient outcome. A range of hemodynamic, structural, and functional measures associated with the RV have been found to have prognostic importance in PAH and, therefore, have potential value as parameters for the evaluation and follow-up of patients. If such measures are to be used clinically, there is a need for simple, reproducible, accurate, easy-to-use, and noninvasive methods to assess them. Cardiac magnetic resonance imaging (CMRI) is regarded as the "gold standard" method for assessment of the RV, the complex structure of which makes accurate assessment by 2-dimensional methods, such as echocardiography, challenging. However, the majority of data concerning the use of CMRI in PAH have come from studies evaluating a variety of different measures and using different techniques and protocols, and there is a clear need for the development of standardized methodology if CMRI is to be established in the routine assessment of patients with PAH. Should such standards be developed, it seems likely that CMRI will become an important method for the noninvasive assessment and monitoring of patients with PAH. (C) 2012 Elsevier Inc. All rights reserved. (Am J Cardiol 2012;110[suppl]:25S-31S)

Pacemakers and magnetic resonance imaging: Current status and survey in Switzerland

Electromagnetic fields arising from magnetic resonance imaging (MRI) can cause various clinically relevant functional disturbances in patients with cardiac pacemakers. Consequently, an implanted pacemaker is generally considered a contraindication for an MRI scan. With approximately 60 million MRI scans performed worldwide per year, MRI may be indicated for an estimated majority of pacemaker patients during the lifetime of their pacemakers. The availability of MR conditional pacemakers with CE labelling is of particular advantage since they allow the safe use of pacemakers in MRI. In this article the current state of knowledge on pacemakers and MR imaging is discussed. We present the results of a survey conducted among Swiss radiologists to assess current practice in patients with pacemakers.

Potential and limitations of diffusion-weighted magnetic resonance imaging in kidney, prostate, and bladder cancer including pelvic lymph node staging: a critical analysis of the literature

Diagnosis, staging, and treatment monitoring are still suboptimal for most genitourinary tumours. Diffusion-weighted magnetic resonance imaging (DW-MRI) has already shown promise as a noninvasive imaging modality in the early detection of microstructural and functional changes in several pathologies of various organs.

Echocardiogram versus cardiac magnetic resonance imaging for assessing systolic function of subaortic right ventricle in adults with complete transposition of great arteries and previous atrial switch operation

In adults with congenital heart disease and a systemic right ventricle, subaortic ventricular systolic dysfunction is common. Echocardiographic assessment of systolic right ventricular (RV) function in these patients is important but challenging. The aim of the present study was to assess the reliability of conventional echocardiographic RV functional parameters to quantify the systolic performance of a subaortic right ventricle. We compared 56 contemporary echocardiograms and cardiac magnetic resonance studies in 37 adults, aged 26.9 ± 7.4 years, with complete transposition and a subaortic right ventricle. The fractional area change (FAC), lateral tricuspid annular plane systolic excursion, lateral RV systolic motion velocities by tissue Doppler, RV myocardial performance index, and the rate of systolic RV pressure increase (dp/dt) measured across the tricuspid regurgitant jet were assessed by echocardiography and correlated with the cardiac magnetic resonance-derived RV ejection fraction (EF). The mean RVEF was 48.0 ± 7.8%. FAC (r(2) = 0.206, p = 0.001) and dp/dt (r(2) = 0.173, p = 0.009) significantly correlated with RVEF, and the other nongeometric echocardiographic parameters failed to show a significant correlation with RVEF by linear regression analysis. FAC <33% and dp/dt <1,000 mm Hg/s identified a RVEF of <50% with a sensitivity of 77% and 69% and a specificity of 58% and 87%, respectively. In conclusion, in patients with a systemic right ventricle, routine nongeometric echocardiographic parameters of RV function correlated weakly with cardiac magnetic resonance-derived EF. RV FAC and the measurement of the rate of systolic RV pressure increase (dp/dt) should be preferentially used to assess systemic systolic function in adult patients with a subaortic right ventricle.

Extracranial applications of diffusion-weighted magnetic resonance imaging

Diffusion-weighted MRI has become more and more popular in the last couple of years. It is already an accepted diagnostic tool for patients with acute stroke, but is more difficult to use for extracranial applications due to technical challenges mostly related to motion sensitivity and susceptibility variations (e.g., respiration and air-tissue boundaries). However, thanks to the newer technical developments, applications of body DW-MRI are starting to emerge. In this review, we aim to provide an overview of the current status of the published data on DW-MRI in extracranial applications. A short introduction to the physical background of this promising technique is provided, followed by the current status, subdivided into three main topics, the functional evaluation, tissue characterization and therapy monitoring.

The amygdala in schizophrenia: a trimodal magnetic resonance imaging study

In schizophrenic psychoses, structural and functional alterations of the amygdala have been demonstrated by several neuroimaging studies. However, postmortem examinations on the brains of schizophrenics did not confirm the volume changes reported by volumetric magnetic resonance imaging (MRI) studies. In order to address these contradictory findings and to further elucidate the possibly underlying pathophysiological process of the amygdala, we employed a trimodal MRI design including high-resolution volumetry, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) in a sample of 14 schizophrenic patients and 14 matched controls. Three-dimensional MRI volumetry revealed a significant reduction of amygdala raw volumes in the patient group, while amygdala volumes normalized for intracranial volume did not differ between the two groups. The regional diffusional anisotropy of the amygdala, expressed as inter-voxel coherence (COH), showed a marked and significant reduction in schizophrenics. Assessment of qMTI parameters yielded significant group differences for the T2 time of the bound proton pool and the T1 time of the free proton pool, while the semi-quantitative magnetization transfer ratio (MTR) did not differ between the groups. The application of multimodal MRI protocols is diagnostically relevant for the differentiation between schizophrenic patients and controls and provides a new strategy for the detection and characterization of subtle structural alterations in defined regions of the living brain.

Advanced morphological and biochemical magnetic resonance imaging of cartilage repair procedures in the knee joint at 3 Tesla

Morphological and biochemical magnetic resonance imaging (MRI) is due to high field MR systems, advanced coil technology, and sophisticated sequence protocols capable of visualizing articular cartilage in vivo with high resolution in clinical applicable scan time. Several conventional two-dimensional (2D) and three-dimensional (3D) approaches show changes in cartilage structure. Furthermore newer isotropic 3D sequences show great promise in improving cartilage imaging and additionally in diagnosing surrounding pathologies within the knee joint. Functional MR approaches are additionally able to provide a specific measure of the composition of cartilage. Cartilage physiology and ultra-structure can be determined, changes in cartilage macromolecules can be detected, and cartilage repair tissue can thus be assessed and potentially differentiated. In cartilage defects and following nonsurgical and surgical cartilage repair, morphological MRI provides the basis for diagnosis and follow-up evaluation, whereas biochemical MRI provides a deeper insight into the composition of cartilage and cartilage repair tissue. A combination of both, together with clinical evaluation, may represent a desirable multimodal approach in the future, also available in routine clinical use.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.

Cardiac magnetic resonance imaging in the diagnosis and determination of outcome of pulmonary hypertension

Pulmonary hypertension (PH) is a rare but serious condition that causes progressive right ventricular (RV) failure and death. PH may be idiopathic, associated with underlying connective-tissue disease or hypoxic lung disease, and is also increasingly being observed in the setting of heart failure with preserved ejection fraction (HFpEF). The management of PH has been revolutionised by the recent development of new disease-targeted therapies which are beneficial in pulmonary arterial hypertension (PAH), but can be potentially harmful in PH due to left heart disease, so accurate diagnosis and classification of patients is essential. These PAH therapies improve exercise capacity and pulmonary haemodynamics, but their overall effect on the right ventricle remains unclear. Current practice in the UK is to assess treatment response with 6-minute walk test and NYHA functional class, neither of which truly reflects RV function. Cardiac magnetic resonance (CMR) imaging has been established as the gold standard for the evaluation of right ventricular structure and function, but it also allows a non-invasive and accurate study of the left heart. The aims of this thesis were to investigate the use of CMR in the diagnosis of PH, in the assessment of treatment response, and in predicting survival in idiopathic and connective-tissue disease associated PAH. In Chapter 3, a left atrial volume (LAV) threshold of 43 ml/m2 measured with CMR was able to distinguish idiopathic PAH from PH due to HFpEF (sensitivity 97%, specificity 100%). In Chapter 4, disease-targeted PAH therapy resulted in significant improvements in RV and left ventricular ejection fraction (p<0.001 and p=0.0007, respectively), RV stroke volume index (p<0.0001), and left ventricular end-diastolic volume index (p=0.0015). These corresponded to observed improvements in functional class and exercise capacity, although correlation coefficients between Δ 6MWD and Δ RVEF or Δ LVEDV were low. Finally, in Chapter 5, one-year and three-year survival was worse in CTD-PAH (75% and 53%) than in IPAH (83% and 74%), despite similar baseline clinical characteristics, lung function, pulmonary haemodynamics and treatment. Baseline right ventricular stroke volume index was an independent predictor of survival in both conditions. The presence of LV systolic dysfunction was of prognostic significance in CTD-PAH but not IPAH, and a higher LAV was observed in CTD-PAH suggesting a potential contribution from LV diastolic dysfunction in this group.

Utility and safety of invasive (fractional flow reserve) and non-invasive (cardiac magnetic resonance imaging) diagnostic tests in patients with NSTEMI

A prospective randomised controlled clinical trial of treatment decisions informed by invasive functional testing of coronary artery disease severity compared with standard angiography-guided management was implemented in 350 patients with a recent non-ST elevation myocardial infarction (NSTEMI) admitted to 6 hospitals in the National Health Service. The main aims of this study were to examine the utility of both invasive fractional flow reserve (FFR) and non-invasive cardiac magnetic resonance imaging (MRI) amongst patients with a recent diagnosis of NSTEMI. In summary, the findings of this thesis are: (1) the use of FFR combined with intravenous adenosine was feasible and safe amongst patients with NSTEMI and has clinical utility; (2) there was discordance between the visual, angiographic estimation of lesion significance and FFR; (3). The use of FFR led to changes in treatment strategy and an increase in prescription of medical therapy in the short term compared with an angiographically guided strategy; (4) in the incidence of major adverse cardiac events (MACE) at 12 months follow up was similar in the two groups. Cardiac MRI was used in a subset of patients enrolled in two hospitals in the West of Scotland. T1 and T2 mapping methods were used to delineate territories of acute myocardial injury. T1 and T2 mapping were superior when compared with conventional T2-weighted dark blood imaging for estimation of the ischaemic area-at-risk (AAR) with less artifact in NSTEMI. There was poor correlation between the angiographic AAR and MRI methods of AAR estimation in patients with NSTEMI. FFR had a high accuracy at predicting inducible perfusion defects demonstrated on stress perfusion MRI. This thesis describes the largest randomized trial published to date specifically looking at the clinical utility of FFR in the NSTEMI population. We have provided evidence of the diagnostic and clinical utility of FFR in this group of patients and provide evidence to inform larger studies. This thesis also describes the largest ever MRI cohort, including with myocardial stress perfusion assessments, specifically looking at the NSTEMI population. We have demonstrated the diagnostic accuracy of FFR to predict reversible ischaemia as referenced to a non-invasive gold standard with MRI. This thesis has also shown the futility of using dark blood oedema imaging amongst all comer NSTEMI patients when compared to novel T1 and T2 mapping methods.

Quantifying the volume fraction and texture of cancellous bone using 3.0 Tesla magnetic resonance imaging

Introduction: 3.0 Tesla MRI offers the potential to quantify the volume fraction and structural texture of cancellous bone, along with quantification of marrow composition, in a single non-invasive examination. This study describes our preliminary investigations to identify parameters which describe cancellous bone structure including the relationships between texture and volume fraction.

3D reconstruction of long bones utilising magnetic resonance imaging (MRI)

The design of pre-contoured fracture fixation implants (plates and nails) that correctly fit the anatomy of a patient utilises 3D models of long bones with accurate geometric representation. 3D data is usually available from computed tomography (CT) scans of human cadavers that generally represent the above 60 year old age group. Thus, despite the fact that half of the seriously injured population comes from the 30 year age group and below, virtually no data exists from these younger age groups to inform the design of implants that optimally fit patients from these groups. Hence, relevant bone data from these age groups is required. The current gold standard for acquiring such data–CT–involves ionising radiation and cannot be used to scan healthy human volunteers. Magnetic resonance imaging (MRI) has been shown to be a potential alternative in the previous studies conducted using small bones (tarsal bones) and parts of the long bones. However, in order to use MRI effectively for 3D reconstruction of human long bones, further validations using long bones and appropriate reference standards are required. Accurate reconstruction of 3D models from CT or MRI data sets requires an accurate image segmentation method. Currently available sophisticated segmentation methods involve complex programming and mathematics that researchers are not trained to perform. Therefore, an accurate but relatively simple segmentation method is required for segmentation of CT and MRI data. Furthermore, some of the limitations of 1.5T MRI such as very long scanning times and poor contrast in articular regions can potentially be reduced by using higher field 3T MRI imaging. However, a quantification of the signal to noise ratio (SNR) gain at the bone - soft tissue interface should be performed; this is not reported in the literature. As MRI scanning of long bones has very long scanning times, the acquired images are more prone to motion artefacts due to random movements of the subject‟s limbs. One of the artefacts observed is the step artefact that is believed to occur from the random movements of the volunteer during a scan. This needs to be corrected before the models can be used for implant design. As the first aim, this study investigated two segmentation methods: intensity thresholding and Canny edge detection as accurate but simple segmentation methods for segmentation of MRI and CT data. The second aim was to investigate the usability of MRI as a radiation free imaging alternative to CT for reconstruction of 3D models of long bones. The third aim was to use 3T MRI to improve the poor contrast in articular regions and long scanning times of current MRI. The fourth and final aim was to minimise the step artefact using 3D modelling techniques. The segmentation methods were investigated using CT scans of five ovine femora. The single level thresholding was performed using a visually selected threshold level to segment the complete femur. For multilevel thresholding, multiple threshold levels calculated from the threshold selection method were used for the proximal, diaphyseal and distal regions of the femur. Canny edge detection was used by delineating the outer and inner contour of 2D images and then combining them to generate the 3D model. Models generated from these methods were compared to the reference standard generated using the mechanical contact scans of the denuded bone. The second aim was achieved using CT and MRI scans of five ovine femora and segmenting them using the multilevel threshold method. A surface geometric comparison was conducted between CT based, MRI based and reference models. To quantitatively compare the 1.5T images to the 3T MRI images, the right lower limbs of five healthy volunteers were scanned using scanners from the same manufacturer. The images obtained using the identical protocols were compared by means of SNR and contrast to noise ratio (CNR) of muscle, bone marrow and bone. In order to correct the step artefact in the final 3D models, the step was simulated in five ovine femora scanned with a 3T MRI scanner. The step was corrected using the iterative closest point (ICP) algorithm based aligning method. The present study demonstrated that the multi-threshold approach in combination with the threshold selection method can generate 3D models from long bones with an average deviation of 0.18 mm. The same was 0.24 mm of the single threshold method. There was a significant statistical difference between the accuracy of models generated by the two methods. In comparison, the Canny edge detection method generated average deviation of 0.20 mm. MRI based models exhibited 0.23 mm average deviation in comparison to the 0.18 mm average deviation of CT based models. The differences were not statistically significant. 3T MRI improved the contrast in the bone–muscle interfaces of most anatomical regions of femora and tibiae, potentially improving the inaccuracies conferred by poor contrast of the articular regions. Using the robust ICP algorithm to align the 3D surfaces, the step artefact that occurred by the volunteer moving the leg was corrected, generating errors of 0.32 ± 0.02 mm when compared with the reference standard. The study concludes that magnetic resonance imaging, together with simple multilevel thresholding segmentation, is able to produce 3D models of long bones with accurate geometric representations. The method is, therefore, a potential alternative to the current gold standard CT imaging.

In vitro estimation of foetal liver volume using ultrasound, x-ray computed tomography and magnetic resonance imaging

Sixteen formalin-fixed foetal livers were scanned in vitro using a new system for estimating volume from a sequence of multiplanar 2D ultrasound images. Three different scan techniques were used (radial, parallel and slanted) and four volume estimation algorithms (ellipsoid, planimetry, tetrahedral and ray tracing). Actual liver volumes were measured by water displacement. Twelve of the sixteen livers also received x-ray computed tomography (CT) and magnetic resonance (MR) scans and the volumes were calculated using voxel counting and planimetry. The percentage accuracy (mean ± SD) was 5.3 ± 4.7%, −3.1 ± 9.6% and −0.03 ± 9.7% for ultrasound (radial scans, ray volumes), MR and CT (voxel counting) respectively. The new system may be useful for accurately estimating foetal liver volume in utero.