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.

Role of new molecular approaches for the early diagnosis of bladder cancer in clinical practice

There is an urgent need to improve the performance of urine cytology for the diagnosis of bladder cancer. In preliminary studies, telomerase activity evaluated by telomeric repeat amplification protocol (TRAP) assay and chromosomal aneuploidy detected by fluorescence in situ hybridization (FISH) in the diagnosis of bladder cancer have produced important results. Urine cell-free (UCF) DNA has also been proposed as a potential marker for early bladder cancer diagnosis. In the first study the diagnostic performance of TRAP assay and FISH analysis was assessed, while the second study evaluated the potential role of UCF DNA integrity in early bladder cancer diagnosis. In the first cross-sectional study, 289 consecutive patients who presented with urinary symptoms underwent cystoscopy and cytology evaluation. In the second study, UCF DNA was isolated from 51 bladder cancer patients, 46 symptomatic patients, and 32 healthy volunteers. c-Myc, BCAS1 and HER2 gene sequences longer than 250 bp were quantified by real time PCR to verify UCF DNA integrity. In the first study, sensitivity and specificity were 0.39 and 0.83, respectively, for cytology; 0.66 and 0.72 for TRAP; 0.78 and 0.60 for the cytology and TRAP combination; 0.78 and 0.78 for the cytology, TRAP and FISH combination; and 0.65 and 0.93 for the TRAP and FISH combination. In the second study, at the best cutoff of 0.1 ng/µl, UCF DNA integrity analysis showed a sensitivity of 0.73 and a specificity of 0.84 in healthy individuals and 0.83 in symptomatic patients. The preliminary results suggest that these biomarkers could potentially be used for the early diagnosis of bladder cancer, especially in high-risk populations (e.g, symptomatic individuals exposed to occupational risk) who may benefit from the use of noninvasive diagnostic tests in terms of cost-benefit.