Anterior cruciate ligament reconstruction with special reference to magnetic resonance imaging of the postoperative outcome

Anterior cruciate ligament (ACL) tear is a common sports injury of the knee. Arthroscopic reconstruction using autogenous graft material is widely used for patients with ACL instability. The grafts most commonly used are the patellar and the hamstring tendons, by various fixation techniques. Although clinical evaluation and conventional radiography are routinely used in follow-up after ACL surgery, magnetic resonance imaging (MRI) plays an important role in the diagnosis of complications after ACL surgery. The aim of this thesis was to study the clinical outcome of patellar and hamstring tendon ACL reconstruction techniques. In addition, the postoperative appearance of the ACL graft was evaluated using several MRI sequences. Of the 175 patients who underwent an arthroscopically assisted ACL reconstruction, 99 patients were randomized into patellar tendon (n=51) or hamstring tendon (n=48) groups. In addition, 62 patients with hamstring graft ACL reconstruction were randomized into either cross-pin (n=31) or interference screw (n=31) fixation groups. Follow-up evaluation determined knee laxity, isokinetic muscle performance and several knee scores. Lateral and anteroposterior view radiographs were obtained. Several MRI sequences were obtained with a 1.5-T imager. The appearance and enhancement pattern of the graft and periligamentous tissue, and the location of bone tunnels were evaluated. After MRI, arthroscopy was performed on 14 symptomatic knees. The results revealed no significant differences in the 2-year outcome between the groups. In the hamstring tendon group, the average femoral and tibial bone tunnel diameter increased during 2 years follow-up by 33% and 23%, respectively. In the asymptomatic knees, the graft showed homogeneous and low signal intensity with periligamentous streaks of intermediate signal intensity on T2-weighted MR images. In the symptomatic knees, arthroscopy revealed 12 abnormal grafts and two meniscal tears, each with an intact graft. Among 3 lax grafts visible on arthroscopy, MRI showed an intact graft and improper bone tunnel placement. For diagnosing graft failure, all MRI findings combined gave a specificity of 90% and a sensitivity of 81%. In conclusion, all techniques appeared to improve patients' performance, and were therefore considered as good choices for ACL reconstruction. In follow-up, MRI permits direct evaluation of the ACL graft, the bone tunnels, and additional disorders of the knee. Bone tunnel enlargement and periligamentous tissue showing contrast enhancement were non-specific MRI findings that did not signify ACL deficiency. With an intact graft and optimal femoral bone tunnel placement, graft deficiency is unlikely, and the MRI examination should be carefully scrutinized for possible other causes for the patients symptoms.

Microvascular reconstruction in extremity soft tissue sarcoma surgery

Soft tissue sarcomas (STS) are rare tumors of soft tissue occurring most frequently in the extremities. Modern treatment of extremity STS is based on limb-sparing surgery combined with radiotherapy. To prevent local recurrence, a healthy tissue margin of 2.5 cm around the resected tumor is required. This results in large defects of soft tissue and bone, necessitating the use of reconstructive surgery to achieve wound closure. When local or pedicled soft tissue flaps are unavailable, reconstruction with free flaps is used. Free flaps are elevated at a distant site, and have their blood flow restored at the recipient site through microvascular anastomosis. When limb-sparing surgery is made impossible, amputation is the only option. Proximal amputation such as forequarter amputation (FQA) causes considerable morbidity, but is nevertheless warranted for carefully selected patients for cure or palliation. 116 patients treated in 1985 - 2006 were included in the study. Of these, 93 patients treated with limb-sparing surgery and microvascular reconstructive surgery after resection of extremity STS. 25 patients who underwent FQA were also included. Patients were identified and their medical records retrospectively reviewed. In all, 105 free flap procedures were performed for 103 patients. A total of 95 curatively treated STS patients were included in survival analysis. The latissimus dorsi, used in 56% of cases, was the most frequently used free flap. Free flap success rate was 96%. There were 9% microvascular anastomosis complications and 15% wound complications. For curatively treated STS patients, local recurrence-free survival at 5 years was 73.1%, metastasis-free survival 58.3%, and overall disease-specific survival 68.9%. Functional results were good, with 75% of patients regaining normal or near-normal function after lower extremity, and 55% after upper extremity STS resection. Among curatively treated forequarter amputees, 5-year disease-free survival was 44%. In the palliatively treated group median time until disease death was 14 months. Microvascular reconstruction after extremity soft tissue sarcoma resection is safe and reliable, and produces well-healing wounds allowing early oncological treatment. Oncological outcome after these procedures is comparable to that of other extremity sarcoma patients. Functional results are generally good. Forequarter amputation is a useful treatment option for soft tissue tumors of the shoulder girdle and proximal upper extremity. When free flap coverage of extended forequarter amputation is required, the preferable flap is a fillet flap from the amputated extremity. Acceptable oncological outcome is achieved for curatively treated FQA patients. In the palliatively treated patient considerable periods of increased quality of life can be achieved.

New approximation algorithms for minimum cycle bases of graphs

We consider the problem of computing an approximate minimum cycle basis of an undirected edge-weighted graph G with m edges and n vertices; the extension to directed graphs is also discussed. In this problem, a {0,1} incidence vector is associated with each cycle and the vector space over F-2 generated by these vectors is the cycle space of G. A set of cycles is called a cycle basis of G if it forms a basis for its cycle space. A cycle basis where the sum of the weights of the cycles is minimum is called a minimum cycle basis of G. Cycle bases of low weight are useful in a number of contexts, e.g. the analysis of electrical networks, structural engineering, chemistry, and surface reconstruction. We present two new algorithms to compute an approximate minimum cycle basis. For any integer k >= 1, we give (2k - 1)-approximation algorithms with expected running time 0(kmn(1+2/k) + mn((1+1/k)(omega-1))) and deterministic running time 0(n(3+2/k)), respectively. Here omega is the best exponent of matrix multiplication. It is presently known that omega < 2.376. Both algorithms are o(m(omega)) for dense graphs. This is the first time that any algorithm which computes sparse cycle bases with a guarantee drops below the Theta(m(omega)) bound. We also present a 2-approximation algorithm with O(m(omega) root n log n) expected running time, a linear time 2-approximation algorithm for planar graphs and an O(n(3)) time 2.42-approximation algorithm for the complete Euclidean graph in the plane.

Single-resolution and multiresolution extended-Kalman-filter-based reconstruction approaches to optical refraction tomography

The problem of reconstruction of a refractive-index distribution (RID) in optical refraction tomography (ORT) with optical path-length difference (OPD) data is solved using two adaptive-estimation-based extended-Kalman-filter (EKF) approaches. First, a basic single-resolution EKF (SR-EKF) is applied to a state variable model describing the tomographic process, to estimate the RID of an optically transparent refracting object from noisy OPD data. The initialization of the biases and covariances corresponding to the state and measurement noise is discussed. The state and measurement noise biases and covariances are adaptively estimated. An EKF is then applied to the wavelet-transformed state variable model to yield a wavelet-based multiresolution EKF (MR-EKF) solution approach. To numerically validate the adaptive EKF approaches, we evaluate them with benchmark studies of standard stationary cases, where comparative results with commonly used efficient deterministic approaches can be obtained. Detailed reconstruction studies for the SR-EKF and two versions of the MR-EKF (with Haar and Daubechies-4 wavelets) compare well with those obtained from a typically used variant of the (deterministic) algebraic reconstruction technique, the average correction per projection method, thus establishing the capability of the EKF for ORT. To the best of our knowledge, the present work contains unique reconstruction studies encompassing the use of EKF for ORT in single-resolution and multiresolution formulations, and also in the use of adaptive estimation of the EKF's noise covariances. (C) 2010 Optical Society of America

Reconstruction of past UV radiation

Solar ultraviolet (UV) radiation has a broad range of effects concerning life on Earth. Soon after the mid-1980s, it was recognized that the stratospheric ozone content was declining over large areas of the globe. Because the stratospheric ozone layer protects life on Earth from harmful UV radiation, this lead to concern about possible changes in the UV radiation due to anthropogenic activity. Initiated by this concern, many stations for monitoring of the surface UV radiation were founded in the late 1980s and early 1990s. As a consequence, there is an apparent lack of information on UV radiation further in the past: measurements cannot tell us how the UV radiation levels have changed on time scales of, for instance, several decades. The aim of this thesis was to improve our understanding of past variations in the surface UV radiation by developing techniques for UV reconstruction. Such techniques utilize commonly available meteorological data together with measurements of the total ozone column for reconstructing, or estimating, the amount of UV radiation reaching Earth's surface in the past. Two different techniques for UV reconstruction were developed. Both are based on first calculating the clear-sky UV radiation using a radiative transfer model. The clear-sky value is then corrected for the effect of clouds based on either (i) sunshine duration or (ii) pyranometer measurements. Both techniques account also for the variations in the surface albedo caused by snow, whereas aerosols are included as a typical climatological aerosol load. Using these methods, long time series of reconstructed UV radiation were produced for five European locations, namely Sodankylä and Jokioinen in Finland, Bergen in Norway, Norrköping in Sweden, and Davos in Switzerland. Both UV reconstruction techniques developed in this thesis account for the greater part of the factors affecting the amount of UV radiation reaching the Earth's surface. Thus, they are considered reliable and trustworthy, as suggested also by the good performance of the methods. The pyranometer-based method shows better performance than the sunshine-based method, especially for daily values. For monthly values, the difference between the performances of the methods is smaller, indicating that the sunshine-based method is roughly as good as the pyranometer-based for assessing long-term changes in the surface UV radiation. The time series of reconstructed UV radiation produced in this thesis provide new insight into the past UV radiation climate and how the UV radiation has varied throughout the years. Especially the sunshine-based UV time series, extending back to 1926 and 1950 at Davos and Sodankylä, respectively, also put the recent changes driven by the ozone decline observed over the last few decades into perspective. At Davos, the reconstructed UV over the period 1926-2003 shows considerable variation throughout the entire period, with high values in the mid-1940s, early 1960s, and in the 1990s. Moreover, the variations prior to 1980 were found to be caused primarily by variations in the cloudiness, while the increase of 4.5 %/decade over the period 1979-1999 was supported by both the decline in the total ozone column and changes in the cloudiness. Of the other stations included in this work, both Sodankylä and Norrköping show a clear increase in the UV radiation since the early 1980s (3-4 %/decade), driven primarily by changes in the cloudiness, and to a lesser extent by the diminution of the total ozone. At Jokioinen, a weak increase was found, while at Bergen there was no considerable overall change in the UV radiation level.

La norme du corps hybride : Une éthique de la reconstruction et de l'amélioration du corps humain en chirurgie

Aujourd'hui, techniques et technologies interagissent avec le corps humain et donnent aux personnes la possibilité de reconstruire leur corps, mais aussi de l'améliorer et de l'augmenter. L'hybridation est un processus technologique visant à compenser les défaillances humaines. L'augmentation de la puissance d'être est exaltée (santé, sexualité, performance, jeunesse), pourtant son accès n'est pas pour tous. Ce livre propose de démêler les différentes représentations du corps hybride et les projets qui les sous-tendent.

Joseph A. Schumpeter's Theory of Social and Economic Evolution : a Reconstruction and Critique

The book presents a reconstruction, interpretation and critical evaluation of the Schumpeterian theoretical approach to socio-economic change. The analysis focuses on the problem of social evolution, on the interpretation of the innovation process and business cycles and, finally, on Schumpeter s optimistic neglect of ecological-environmental conditions as possible factors influencing social-economic change. The author investigates how the Schumpeterian approach describes the process of social and economic evolution, and how the logic of transformations is described, explained and understood in the Schumpeterian theory. The material of the study includes Schumpeter s works written after 1925, a related part of the commentary literature on these works, and a selected part of the related literature on the innovation process, technological transformations and the problem of long waves. Concerning the period after 1925, the Schumpeterian oeuvre is conceived and analysed as a more or less homogenous corpus of texts. The book is divided into 9 chapters. Chapters 1-2 describe the research problems and methods. Chapter 3 is an effort to provide a systematic reconstruction of Schumpeter's ideas concerning social and economic evolution. Chapters 4 and 5 focus their analysis on the innovation process. In Chapters 6 and 7 Schumpeter's theory of business cycles is examined. Chapter 8 evaluates Schumpeter's views concerning his relative neglect of ecological-environmental conditions as possible factors influencing social-economic change. Finally, chapter 9 draws the main conclusions.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.

Dynamic programming based optimum non-uniform samples for speech reconstruction and coding

Non-uniform sampling of a signal is formulated as an optimization problem which minimizes the reconstruction signal error. Dynamic programming (DP) has been used to solve this problem efficiently for a finite duration signal. Further, the optimum samples are quantized to realize a speech coder. The quantizer and the DP based optimum search for non-uniform samples (DP-NUS) can be combined in a closed-loop manner, which provides distinct advantage over the open-loop formulation. The DP-NUS formulation provides a useful control over the trade-off between bitrate and performance (reconstruction error). It is shown that 5-10 dB SNR improvement is possible using DP-NUS compared to extrema sampling approach. In addition, the close-loop DP-NUS gives a 4-5 dB improvement in reconstruction error.

Lessons from the Sparse Sensor Network Deployment in Rural India

We discuss the key issues in the deployment of sparse sensor networks. The network monitors several environment parameters and is deployed in a semi-arid region for the benefit of small and marginal farmers. We begin by discussing the problems of an existing unreliable 1 sq km sparse network deployed in a village. The proposed solutions are implemented in a new cluster. The new cluster is a reliable 5 sq km network. Our contributions are two fold. Firstly, we describe a. novel methodology to deploy a sparse reliable data gathering sensor network and evaluate the ``safe distance'' or ``reliable'' distance between nodes using propagation models. Secondly, we address the problem of transporting data from rural aggregation servers to urban data centres. This paper tracks our steps in deploying a sensor network in a village,in India, trying to provide better diagnosis for better crop management. Keywords - Rural, Agriculture, CTRS, Sparse.

How to deal with sparse macroseismic data

This study discusses the scope of historical earthquake analysis in low-seismicity regions. Examples of non-damaging earthquake reports are given from the Eastern Baltic (Fennoscandian) Shield in north-eastern Europe from the 16th to the 19th centuries. The information available for past earthquakes in the region is typically sparse and cannot be increased through a careful search of the archives. This study applies recommended rigorous methodologies of historical seismology developed using ample data to the sparse reports from the Eastern Baltic Shield. Attention is paid to the context of reporting, the identity and role of the authors, the circumstances of the reporting, and the opportunity to verify the available information by collating the sources. We evaluate the reliability of oral earthquake recollections and develop criteria for cases when a historical earthquake is attested to by a single source. We propose parametric earthquake scenarios as a way to deal with sparse macroseismic reports and as an improvement to existing databases.

Semi-Supervised Classification Using Sparse Gaussian Process Regression

Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

Composite MR image reconstruction and unaliasing for general trajectories using neural networks

In rapid parallel magnetic resonance imaging, the problem of image reconstruction is challenging. Here, a novel image reconstruction technique for data acquired along any general trajectory in neural network framework, called ``Composite Reconstruction And Unaliasing using Neural Networks'' (CRAUNN), is proposed. CRAUNN is based on the observation that the nature of aliasing remains unchanged whether the undersampled acquisition contains only low frequencies or includes high frequencies too. Here, the transformation needed to reconstruct the alias-free image from the aliased coil images is learnt, using acquisitions consisting of densely sampled low frequencies. Neural networks are made use of as machine learning tools to learn the transformation, in order to obtain the desired alias-free image for actual acquisitions containing sparsely sampled low as well as high frequencies. CRAUNN operates in the image domain and does not require explicit coil sensitivity estimation. It is also independent of the sampling trajectory used, and could be applied to arbitrary trajectories as well. As a pilot trial, the technique is first applied to Cartesian trajectory-sampled data. Experiments performed using radial and spiral trajectories on real and synthetic data, illustrate the performance of the method. The reconstruction errors depend on the acceleration factor as well as the sampling trajectory. It is found that higher acceleration factors can be obtained when radial trajectories are used. Comparisons against existing techniques are presented. CRAUNN has been found to perform on par with the state-of-the-art techniques. Acceleration factors of up to 4, 6 and 4 are achieved in Cartesian, radial and spiral cases, respectively. (C) 2010 Elsevier Inc. All rights reserved.