Applicazioni dei fasci quasi-monocromatici in medicina

I raggi X, a partire dalla loro scoperta, avvenuta nel 1895 ad opera di Wilhelm Conrad Röntgen, si sono rivelati un potentissimo mezzo per lo studio della materia. In particolare in campo medico hanno permesso la nascita della diagnostica per immagini che, parallelamente allo sviluppo delle tecnologie, è diventata un mezzo imprescindibile per lo studio delle patologie. Negli ultimi decenni molti studi sono stati compiuti in particolare sui vantaggi dell’utilizzo nell’imaging di raggi X monocromatici in sostituzione dell’usuale radiazione policromatica. Con il seguente elaborato si ha l’intento di fornire un quadro generale sulla fisica dei raggi X, sulla loro interazione con la materia e sugli attuali metodi di produzione di fasci monocromatici e quasi-monocromatici, con particolare attenzione all'utilizzo su vasta scala. Sono state infine trattate le principali applicazioni della radiazione monocromatica e quasi-monocromatica nelle tecniche di imaging medico.

Age at hip or knee joint replacement surgery predicts likelihood of revision surgery

We compared revision and mortality rates of 4668 patients undergoing primary total hip and knee replacement between 1989 and 2007 at a University Hospital in New Zealand. The mean age at the time of surgery was 69 years (16 to 100). A total of 1175 patients (25%) had died at follow-up at a mean of ten years post-operatively. The mean age of those who died within ten years of surgery was 74.4 years (29 to 97) at time of surgery. No change in comorbidity score or age of the patients receiving joint replacement was noted during the study period. No association of revision or death could be proven with higher comorbidity scoring, grade of surgeon, or patient gender. We found that patients younger than 50 years at the time of surgery have a greater chance of requiring a revision than of dying, those around 58 years of age have a 50:50 chance of needing a revision, and in those older than 62 years the prosthesis will normally outlast the patient. Patients over 77 years old have a greater than 90% chance of dying than requiring a revision whereas those around 47 years are on average twice as likely to require a revision than die. This information can be used to rationalise the need for long-term surveillance and during the informed consent process.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

LIKELIHOOD ESTIMATION OF CONJUGACY RELATIONSHIPS IN LINEAR MODELS WITH APPLICATIONS TO HIGH-THROUGHPUT GENOMICS

In the simultaneous estimation of a large number of related quantities, multilevel models provide a formal mechanism for efficiently making use of the ensemble of information for deriving individual estimates. In this article we investigate the ability of the likelihood to identify the relationship between signal and noise in multilevel linear mixed models. Specifically, we consider the ability of the likelihood to diagnose conjugacy or independence between the signals and noises. Our work was motivated by the analysis of data from high-throughput experiments in genomics. The proposed model leads to a more flexible family. However, we further demonstrate that adequately capitalizing on the benefits of a well fitting fully-specified likelihood in the terms of gene ranking is difficult.

A SURVEY OF THE LIKELIHOOD APPROACH TO BIOEQUIVALENCE TRIALS

Bioequivalence trials are abbreviated clinical trials whereby a generic drug or new formulation is evaluated to determine if it is "equivalent" to a corresponding previously approved brand-name drug or formulation. In this manuscript, we survey the process of testing bioequivalence and advocate the likelihood paradigm for representing the resulting data as evidence. We emphasize the unique conflicts between hypothesis testing and confidence intervals in this area - which we believe are indicative of the existence of the systemic defects in the frequentist approach - that the likelihood paradigm avoids. We suggest the direct use of profile likelihoods for evaluating bioequivalence and examine the main properties of profile likelihoods and estimated likelihoods under simulation. This simulation study shows that profile likelihoods are a reasonable alternative to the (unknown) true likelihood for a range of parameters commensurate with bioequivalence research. Our study also shows that the standard methods in the current practice of bioequivalence trials offers only weak evidence from the evidential point of view.