Juan Melchor

Data quality in rare cancers registration: the report of the RARECARE data quality study

Purpose Rare cancers represent 22% of all tumors in Europe; however, the quality of the data of rare cancers may not be as good as the quality of data for common cancer. The project surveillance of rare cancers in Europe (RARECARE) had, among others, the objective of assessing rare cancer data quality in population-based cancer registries (CRs). Eight rare cancers were considered: mesothelioma, liver angiosarcoma, sarcomas, tumors of oral cavity, CNS tumors, germ cell tumors, leukemia, and malignant digestive endocrine tumors. Methods We selected data on 18,000 diagnoses and revised, on the basis of the pathologic and clinical reports (but not on pathologic specimens), unspecified morphology and topography codes originally attributed by CR officers and checked the quality of follow-up of long-term survivors of poor prognosis cancers. Results A total of 38 CRs contributed from 13 European countries. The majority of unspecified morphology and topography cases were confirmed as unspecified. The few unspecified cases that, after the review, changed to a more specific diagnosis increased the incidence of the common cancer histotypes. For example, 11% of the oral cavity epithelial cancers were reclassified from unspecified to more specific diagnoses: 8% were reclassified as squamous cell carcinoma (commoner) and only 1% as adenocarcinoma (rarer). The revision confirmed the majority of long-term survivors revealing a relative high proportion of mesothelioma long-term survivors. The majority of appendix carcinoids changed behavior from malignant to borderline lesions. Conclusions Our study suggests that the problem of poorly specified morphology and topography cases is mainly one of difficulty in reaching a precise diagnosis. The awareness of the importance of data quality for rare cancers should increase among registrars, pathologists, and clinicians.

Dispersive model selection and reconstruction for tissue culture ultrasonic monitoring

The evolution of relevant mechanical parameters during tissue engineering formation processes can provide useful information for their control in real-time, as well as a new dimension in the understanding of internal processes and their final quality. Since ultrasonics are mechanical waves, they are ideally well suited for probing certain mechanical properties. An ultrasound monitoring Petri dish has been designed for this purpose. The readings from the ultrasonic sensors need a detailed analysis, based on numerical models of the ultrasound-tissue interaction, and a stochastic treatment, in order to extract the relevant information and its evolution with sufficient sensitivity. In addition, a stochastic model-class selection formulation is used to rank which one of the proposed interaction models are more plausible. To verify the sensitivity of the system, a gelation process is monitored.

Torsional Ultrasound Sensor Optimization for Soft Tissue Characterization

Torsion mechanical waves have the capability to characterize shear stiffness moduli of soft tissue. Under this hypothesis, a computational methodology is proposed to design and optimize a piezoelectrics-based transmitter and receiver to generate and measure the response of torsional ultrasonic waves. The procedure employed is divided into two steps: (i) a finite element method (FEM) is developed to obtain a transmitted and received waveform as well as a resonance frequency of a previous geometry validated with a semi-analytical simplified model and (ii) a probabilistic optimality criteria of the design based on inverse problem from the estimation of robust probability of detection (RPOD) to maximize the detection of the pathology defined in terms of changes of shear stiffness. This study collects different options of design in two separated models, in transmission and contact, respectively. The main contribution of this work describes a framework to establish such as forward, inverse and optimization procedures to choose a set of appropriate parameters of a transducer. This methodological framework may be generalizable for other different applications.

Poly(ethylmethacrylate-co-diethylaminoethyl acrylate) coating improves endothelial re-population, bio-mechanical and anti-thrombogenic properties of decellularized carotid arteries for blood vessel replacement

Decellularized vascular scaffolds are promising materials for vessel replacements. However, despite the natural origin of decellularized vessels, issues such as biomechanical incompatibility, immunogenicity risks and the hazards of thrombus formation, still need to be addressed. In this study, we coated decellularized vessels obtained from porcine carotid arteries with poly (ethylmethacrylate-co-diethylaminoethylacrylate) (8g7) with the purpose of improving endothelial coverage and minimizing platelet attachment while enhancing the mechanical properties of the decellularized vascular scaffolds. The polymer facilitated binding of endothelial cells (ECs) with high affinity and also induced endothelial cell capillary tube formation. In addition, platelets showed reduced adhesion on the polymer under flow conditions. Moreover, the coating of the decellularized arteries improved biomechanical properties by increasing its tensile strength and load. In addition, after 5 days in culture, ECs seeded on the luminal surface of 8g7-coated decellularized arteries showed good regeneration of the endothelium. Overall, this study shows that polymer coating of decellularized vessels provides a new strategy to improve re-endothelialization of vascular grafts, maintaining or enhancing mechanical properties while reducing the risk of thrombogenesis. These results could have potential applications in improving tissue-engineered vascular grafts for cardiovascular therapies with small caliber vessels.

Torsion ultrasonic sensor for tissue mechanical characterization

A sensor based on torsional waves is proposed, designed and validated to quantify elastic constants of soft tissue. The proposed transducer design is able to deploy a shear wave elastography technique that accurately quantifies the shear viscoelastic moduli of the tissue, which, as opposed to compression waves, are strongly dependent on the stroma architecture, thus serving as a new biomarker.

A STOCHASTIC MODEL FOR TISSUE CONSISTENCE EVOLUTION BASED ON THE INVERSE PROBLEM

An inverse-stochastic framework is proposed to reproduce the pattern evolution and predict the mechanical properties of a tissue-engineered culture from ultrasonic measurements in an in-vitro culture. A Markovian type of evolution is expected in tissue cultures for mechanical properties such us bulk modulus (K) or attenuation coefficient (AC), under the hypothesis that the future of the process depends only upon its present state, and not upon past states. Additionally a spread in the evolution histories for different repetitions of the same process is expected, consequently stochastic models such us Markov chains [Gallager, 1996] seems to be more suitable. The method proposed is predictive in nature and can be applicable to any measurable biomechanical process, under the assumption that the process shows Markovian evolution.

Logical Inference Framework for Experimental Design of Mechanical Characterization Procedures

Optimizing an experimental design is a complex task when a model is required for indirect reconstruction of physical parameters from the sensor readings. In this work, a formulation is proposed to unify the probabilistic reconstruction of mechanical parameters and an optimization problem. An information-theoretic framework combined with a new metric of information density is formulated providing several comparative advantages: (i) a straightforward way to extend the formulation to incorporate additional concurrent models, as well as new unknowns such as experimental design parameters in a probabilistic way; (ii) the model causality required by Bayes’ theorem is overridden, allowing generalization of contingent models; and (iii) a simpler formulation that avoids the characteristic complex denominator of Bayes’ theorem when reconstructing model parameters. The first step allows the solving of multiple-model reconstructions. Further extensions could be easily extracted, such as robust model reconstruction, or adding alternative dimensions to the problem to accommodate future needs.

Mechanical biomarkers by torsional shear ultrasound for medical diagnosis

The WHO estimates that 15 million babies yearly (1 in 10) will be born preterm. Worldwide, complications of preterm births have supplanted pneumonia as the primary cause of child mortality [1]. The biology of cervical ripening that leads to birth is poorly understood, and there is no clinical tool to quantitatively evaluate the cervical biomechanical state, which in words of Feltovich [2]“… likely contributes to the reason the singleton spontaneous preterm birth rate has not changed appreciably in more than 100 years.” Towards this problem, we work on enabling new sensor technologies sentient to soft tissue biomechanics, to endow a new class of biomarkers that quantify the mechanical functionality of the cervix, and indeed any soft tissue, ranging pathologies from tumors, atherosclerosis, liver fibrosis to osteoarticular syndromes. Ultrasonic characterization of soft tissue has been developed as a clinical diagnostic tool [3] and evolved through different technologies including our torsional wave principle [4]. Our recent advances covering (a) torsional waves (shear elastic waves that propagate in quasifluids radially and in depth in a curled geometry), (b) sensors (based on a novel arrangement of concentric sandwiches of elements), (c) propagation models and (d) patient testing, are allowing to quantify the mechanical functionality beyond linear parameters: dispersive and nonlinear. [1] WHO, 2012; [2] Feltovich. AJOG207(2012):345–354 [3] Barr. Ultras Quart28(2012):13–20; [4] Melchor. Ultrasonics, 54(2014):1950–1962.The WHO estimates that 15 million babies yearly (1 in 10) will be born preterm. Worldwide, complications of preterm births have supplanted pneumonia as the primary cause of child mortality [1]. The biology of cervical ripening that leads to birth is poorly understood, and there is no clinical tool to quantitatively evaluate the cervical biomechanical state, which in words of Feltovich [2]“… likely contributes to the reason the singleton spontaneous preterm birth rate has not changed appreciably in more than 100 years.” Towards this problem, we work on enabling new sensor technologies sentient to soft tissue biomechanics, to endow a new class of biomarkers that quantify the mechanical functionality of the cervix, and indeed any soft tissue, ranging pathologies from tumors, atherosclerosis, liver fibrosis to osteoarticular syndromes. Ultrasonic characterization of soft tissue has been developed as a clinical diagnostic tool [3] and evolved through different technologies including our torsional wave principl...

Performance Study of a Torsional Wave Sensor and Cervical Tissue Characterization

A novel torsional wave sensor designed to characterize mechanical properties of soft tissues is presented in this work. Elastography is a widely used technique since the 1990s to map tissue stiffness. Moreover, quantitative elastography uses the velocity of shear waves to achieve the shear stiffness. This technique exhibits significant limitations caused by the difficulty of the separation between longitudinal and shear waves and the pressure applied while measuring. To overcome these drawbacks, the proposed torsional wave sensor can isolate a pure shear wave, avoiding the possibility of multiple wave interference. It comprises a rotational actuator disk and a piezoceramic receiver ring circumferentially aligned. Both allow the transmission of shear waves that interact with the tissue before being received. Experimental tests are performed using tissue mimicking phantoms and cervical tissues. One contribution is a sensor sensitivity study that has been conducted to evaluate the robustness of the new proposed torsional wave elastography (TWE) technique. The variables object of the study are both the applied pressure and the angle of incidence sensor–phantom. The other contribution consists of a cervical tissue characterization. To this end, three rheological models have fit the experimental data and a static independent testing method has been performed. The proposed methodology permits the reconstruction of the mechanical constants from the propagated shear wave, providing a proof of principle and warranting further studies to confirm the validity of the results.

Model-based damage evaluation of layered CFRP structures

An ultrasonic evaluation technique for damage identification of layered CFRP structures is presented. This approach relies on a model-based estimation procedure that combines experimental data and simulation of ultrasonic damage-propagation interactions. The CFPR structure, a [0/90]4s lay-up, has been tested in an immersion through transmission experiment, where a scan has been performed on a damaged specimen. Most ultrasonic techniques in industrial practice consider only a few features of the received signals, namely, time of flight, amplitude, attenuation, frequency contents, and so forth. In this case, once signals are captured, an algorithm is used to reconstruct the complete signal waveform and extract the unknown damage parameters by means of modeling procedures. A linear version of the data processing has been performed, where only Young modulus has been monitored and, in a second nonlinear version, the first order nonlinear coefficient β was incorporated to test the possibility of detection of ea...