Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.

Vibration as a method for muscular stimulation

Human reactions to vibration have been extensively investigated in the past. Vibration, as well as whole-body vibration (WBV), has been commonly considered as an occupational hazard for its detrimental effects on human condition and comfort. Although long term exposure to vibrations may produce undesirable side-effects, a great part of the literature is dedicated to the positive effects of WBV when used as method for muscular stimulation and as an exercise intervention. Whole body vibration training (WBVT) aims to mechanically activate muscles by eliciting neuromuscular activity (muscle reflexes) via the use of vibrations delivered to the whole body. The most mentioned mechanism to explain the neuromuscular outcomes of vibration is the elicited neuromuscular activation. Local tendon vibrations induce activity of the muscle spindle Ia fibers, mediated by monosynaptic and polysynaptic pathways: a reflex muscle contraction known as the Tonic Vibration Reflex (TVR) arises in response to such vibratory stimulus. In WBVT mechanical vibrations, in a range from 10 to 80 Hz and peak to peak displacements from 1 to 10 mm, are usually transmitted to the patient body by the use of oscillating platforms. Vibrations are then transferred from the platform to a specific muscle group through the subject body. To customize WBV treatments, surface electromyography (SEMG) signals are often used to reveal the best stimulation frequency for each subject. Use of SEMG concise parameters, such as root mean square values of the recordings, is also a common practice; frequently a preliminary session can take place in order to discover the more appropriate stimulation frequency. Soft tissues act as wobbling masses vibrating in a damped manner in response to mechanical excitation; Muscle Tuning hypothesis suggest that neuromuscular system works to damp the soft tissue oscillation that occurs in response to vibrations; muscles alters their activity to dampen the vibrations, preventing any resonance phenomenon. Muscle response to vibration is however a complex phenomenon as it depends on different parameters, like muscle-tension, muscle or segment-stiffness, amplitude and frequency of the mechanical vibration. Additionally, while in the TVR study the applied vibratory stimulus and the muscle conditions are completely characterised (a known vibration source is applied directly to a stretched/shortened muscle or tendon), in WBV study only the stimulus applied to a distal part of the body is known. Moreover, mechanical response changes in relation to the posture. The transmissibility of vibratory stimulus along the body segment strongly depends on the position held by the subject. The aim of this work was the investigation on the effects that the use of vibrations, in particular the effects of whole body vibrations, may have on muscular activity. A new approach to discover the more appropriate stimulus frequency, by the use of accelerometers, was also explored. Different subjects, not affected by any known neurological or musculoskeletal disorders, were voluntarily involved in the study and gave their informed, written consent to participate. The device used to deliver vibration to the subjects was a vibrating platform. Vibrations impressed by the platform were exclusively vertical; platform displacement was sinusoidal with an intensity (peak-to-peak displacement) set to 1.2 mm and with a frequency ranging from 10 to 80 Hz. All the subjects familiarized with the device and the proper positioning. Two different posture were explored in this study: position 1 - hack squat; position 2 - subject standing on toes with heels raised. SEMG signals from the Rectus Femoris (RF), Vastus Lateralis (VL) and Vastus medialis (VM) were recorded. SEMG signals were amplified using a multi-channel, isolated biomedical signal amplifier The gain was set to 1000 V/V and a band pass filter (-3dB frequency 10 - 500 Hz) was applied; no notch filters were used to suppress line interference. Tiny and lightweight (less than 10 g) three-axial MEMS accelerometers (Freescale semiconductors) were used to measure accelerations of onto patient’s skin, at EMG electrodes level. Accelerations signals provided information related to individuals’ RF, Biceps Femoris (BF) and Gastrocnemius Lateralis (GL) muscle belly oscillation; they were pre-processed in order to exclude influence of gravity. As demonstrated by our results, vibrations generate peculiar, not negligible motion artifact on skin electrodes. Artifact amplitude is generally unpredictable; it appeared in all the quadriceps muscles analysed, but in different amounts. Artifact harmonics extend throughout the EMG spectrum, making classic high-pass filters ineffective; however, their contribution was easy to filter out from the raw EMG signal with a series of sharp notch filters centred at the vibration frequency and its superior harmonics (1.5 Hz wide). However, use of these simple filters prevents the revelation of EMG power potential variation in the mentioned filtered bands. Moreover our experience suggests that the possibility of reducing motion artefact, by using particular electrodes and by accurately preparing the subject’s skin, is not easily viable; even though some small improvements were obtained, it was not possible to substantially decrease the artifact. Anyway, getting rid of those artifacts lead to some true EMG signal loss. Nevertheless, our preliminary results suggest that the use of notch filters at vibration frequency and its harmonics is suitable for motion artifacts filtering. In RF SEMG recordings during vibratory stimulation only a little EMG power increment should be contained in the mentioned filtered bands due to synchronous electromyographic activity of the muscle. Moreover, it is better to remove the artifact that, in our experience, was found to be more than 40% of the total signal power. In summary, many variables have to be taken into account: in addition to amplitude, frequency and duration of vibration treatment, other fundamental variables were found to be subject anatomy, individual physiological condition and subject’s positioning on the platform. Studies on WBV treatments that include surface EMG analysis to asses muscular activity during vibratory stimulation should take into account the presence of motion artifacts. Appropriate filtering of artifacts, to reveal the actual effect on muscle contraction elicited by vibration stimulus, is mandatory. However as a result of our preliminary study, a simple multi-band notch filtering may help to reduce randomness of the results. Muscle tuning hypothesis seemed to be confirmed. Our results suggested that the effects of WBV are linked to the actual muscle motion (displacement). The greater was the muscle belly displacement the higher was found the muscle activity. The maximum muscle activity has been found in correspondence with the local mechanical resonance, suggesting a more effective stimulation at the specific system resonance frequency. Holding the hypothesis that muscle activation is proportional to muscle displacement, treatment optimization could be obtained by simply monitoring local acceleration (resonance). However, our study revealed some short term effects of vibratory stimulus; prolonged studies should be assembled in order to consider the long term effectiveness of these results. Since local stimulus depends on the kinematic chain involved, WBV muscle stimulation has to take into account the transmissibility of the stimulus along the body segment in order to ensure that vibratory stimulation effectively reaches the target muscle. Combination of local resonance and muscle response should also be further investigated to prevent hazards to individuals undergoing WBV treatments.

Development of a method for plasma - induced combustion of intermediate to low-level radioactive waste

This work demonstrates that the plasma - induced combustion of intermediate to low-level radioactive waste is a suitable method for volume reduction and stabilization. Weaknesses of existing facilities can be overcome with novel developments. Plasma treatment of LILW has a high economical advantage by volume reduction for storage in final repositories.