143 research outputs found

    Image-guided fluorescence tomography in head & neck surgical models

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    Clinical indications for fluorescence-guided surgery continue to expand, and are being spurred by the rapid development of new agents that improve biological targeting.1 There is a corresponding need to develop imaging systems that quantify fluorescence - not only at the tissue surface, but at depth. We have recently described an image-guided fluorescence tomography system that leverages geometric data from intraoperative cone-beam CT and surgical navigation,2 and builds on finite-element method software (NIRFAST) for diffuse optical tomography (DOT).3 DOT systems have most commonly been used for sub-surface inclusions buried within tissue (e.g., breast and neurological tumors). Here, we focus on inclusion models relevant to tumors infiltrating from the mucosal surface (an “iceberg” model), as is most often the case in head and neck cancer, where over 85% of tumors are squamous cell carcinoma.4 This work presents results from simulations, tissue-simulating anatomical phantoms, and animal studies involving infiltrative tumor models. The objective is to characterize system performance across a range of inclusion diameters, depths, and optical properties. For example, Fig. 1 shows a fluorescence reconstruction of a simulated tonsil tumor in an oral cavity phantom. Future clinical studies are necessary to assess in vivo performance and intraoperative workflow. Please click Additional Files below to see the full abstract

    Predictors of Radiotherapy Induced Bone Injury (RIBI) after stereotactic lung radiotherapy

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    <p>Abstract</p> <p>Background</p> <p>The purpose of this study was to identify clinical and dosimetric factors associated with radiotherapy induced bone injury (RIBI) following stereotactic lung radiotherapy.</p> <p>Methods</p> <p>Inoperable patients with early stage non-small cell lung cancer, treated with SBRT, who received 54 or 60 Gy in 3 fractions, and had a minimum of 6 months follow up were reviewed. Archived treatment plans were retrieved, ribs delineated individually and treatment plans re-computed using heterogeneity correction. Clinical and dosimetric factors were evaluated for their association with rib fracture using logistic regression analysis; a dose-event curve and nomogram were created.</p> <p>Results</p> <p>46 consecutive patients treated between Oct 2004 and Dec 2008 with median follow-up 25 months (m) (range 6 – 51 m) were eligible. 41 fractured ribs were detected in 17 patients; median time to fracture was 21 m (range 7 – 40 m). The mean maximum point dose in non-fractured ribs (n = 1054) was 10.5 Gy ± 10.2 Gy, this was higher in fractured ribs (n = 41) 48.5 Gy ± 24.3 Gy (p < 0.0001). On univariate analysis, age, dose to 0.5 cc of the ribs (D<sub>0.5</sub>), and the volume of the rib receiving at least 25 Gy (V<sub>25</sub>), were significantly associated with RIBI. As D<sub>0.5</sub> and V<sub>25</sub> were cross-correlated (Spearman correlation coefficient: 0.57, p < 0.001), we selected D<sub>0.5</sub> as a representative dose parameter. On multivariate analysis, age (odds ratio: 1.121, 95% CI: 1.04 – 1.21, p = 0.003), female gender (odds ratio: 4.43, 95% CI: 1.68 – 11.68, p = 0.003), and rib D<sub>0.5</sub> (odds ratio: 1.0009, 95% CI: 1.0007 – 1.001, p < 0.0001) were significantly associated with rib fracture.</p> <p>Using D<sub>0.5,</sub> a dose-event curve was constructed estimating risk of fracture from dose at the median follow up of 25 months after treatment. In our cohort, a 50% risk of rib fracture was associated with a D<sub>0.5</sub> of 60 Gy.</p> <p>Conclusions</p> <p>Dosimetric and clinical factors contribute to risk of RIBI and both should be included when modeling risk of toxicity. A nomogram is presented using D<sub>0.5</sub>, age, and female gender to estimate risk of RIBI following SBRT. This requires validation.</p

    Duhemian Themes in Expected Utility Theory

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    This monographic chapter explains how expected utility (EU) theory arose in von Neumann and Morgenstern, how it was called into question by Allais and others, and how it gave way to non-EU theories, at least among the specialized quarters of decion theory. I organize the narrative around the idea that the successive theoretical moves amounted to resolving Duhem-Quine underdetermination problems, so they can be assessed in terms of the philosophical recommendations made to overcome these problems. I actually follow Duhem's recommendation, which was essentially to rely on the passing of time to make many experiments and arguments available, and evebntually strike a balance between competing theories on the basis of this improved knowledge. Although Duhem's solution seems disappointingly vague, relying as it does on "bon sens" to bring an end to the temporal process, I do not think there is any better one in the philosophical literature, and I apply it here for what it is worth. In this perspective, EU theorists were justified in resisting the first attempts at refuting their theory, including Allais's in the 50s, but they would have lacked "bon sens" in not acknowledging their defeat in the 80s, after the long process of pros and cons had sufficiently matured. This primary Duhemian theme is actually combined with a secondary theme - normativity. I suggest that EU theory was normative at its very beginning and has remained so all along, and I express dissatisfaction with the orthodox view that it could be treated as a straightforward descriptive theory for purposes of prediction and scientific test. This view is usually accompanied with a faulty historical reconstruction, according to which EU theorists initially formulated the VNM axioms descriptively and retreated to a normative construal once they fell threatened by empirical refutation. From my historical study, things did not evolve in this way, and the theory was both proposed and rebutted on the basis of normative arguments already in the 1950s. The ensuing, major problem was to make choice experiments compatible with this inherently normative feature of theory. Compability was obtained in some experiments, but implicitly and somewhat confusingly, for instance by excluding overtly incoherent subjects or by creating strong incentives for the subjects to reflect on the questions and provide answers they would be able to defend. I also claim that Allais had an intuition of how to combine testability and normativity, unlike most later experimenters, and that it would have been more fruitful to work from his intuition than to make choice experiments of the naively empirical style that flourished after him. In sum, it can be said that the underdetermination process accompanying EUT was resolved in a Duhemian way, but this was not without major inefficiencies. To embody explicit rationality considerations into experimental schemes right from the beginning would have limited the scope of empirical research, avoided wasting resources to get only minor findings, and speeded up the Duhemian process of groping towards a choice among competing theories

    Expanding global access to radiotherapy

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    Radiotherapy is a critical and inseparable component of comprehensive cancer treatment and care. For many of the most common cancers in low-income and middle-income countries, radiotherapy is essential for effective treatment. In high-income countries, radiotherapy is used in more than half of all cases of cancer to cure localised disease, palliate symptoms, and control disease in incurable cancers. Yet, in planning and building treatment capacity for cancer, radiotherapy is frequently the last resource to be considered. Consequently, worldwide access to radiotherapy is unacceptably low. We present a new body of evidence that quantifies the worldwide coverage of radiotherapy services by country. We show the shortfall in access to radiotherapy by country and globally for 2015-35 based on current and projected need, and show substantial health and economic benefits to investing in radiotherapy. The cost of scaling up radiotherapy in the nominal model in 2015-35 is US266billioninlowincomecountries,26·6 billion in low-income countries, 62·6 billion in lower-middle-income countries, and 948billioninuppermiddleincomecountries,whichamountsto94·8 billion in upper-middle-income countries, which amounts to 184·0 billion across all low-income and middle-income countries. In the efficiency model the costs were lower: 141billioninlowincome,14·1 billion in low-income, 33·3 billion in lower-middle-income, and 494billioninuppermiddleincomecountriesatotalof49·4 billion in upper-middle-income countries-a total of 96·8 billion. Scale-up of radiotherapy capacity in 2015-35 from current levels could lead to saving of 26·9 million life-years in low-income and middle-income countries over the lifetime of the patients who received treatment. The economic benefits of investment in radiotherapy are very substantial. Using the nominal cost model could produce a net benefit of 2781billionin201535(278·1 billion in 2015-35 (265·2 million in low-income countries, 385billioninlowermiddleincomecountries,and38·5 billion in lower-middle-income countries, and 239·3 billion in upper-middle-income countries). Investment in the efficiency model would produce in the same period an even greater total benefit of 3654billion(365·4 billion (12·8 billion in low-income countries, 677billioninlowermiddleincomecountries,and67·7 billion in lower-middle-income countries, and 284·7 billion in upper-middle-income countries). The returns, by the human-capital approach, are projected to be less with the nominal cost model, amounting to 169billionin201535(16·9 billion in 2015-35 (-14·9 billion in low-income countries; -187billioninlowermiddleincomecountries,and18·7 billion in lower-middle-income countries, and 50·5 billion in upper-middle-income countries). The returns with the efficiency model were projected to be greater, however, amounting to 1042billion(104·2 billion (-2·4 billion in low-income countries, 107billioninlowermiddleincomecountries,and10·7 billion in lower-middle-income countries, and 95·9 billion in upper-middle-income countries). Our results provide compelling evidence that investment in radiotherapy not only enables treatment of large numbers of cancer cases to save lives, but also brings positive economic benefits
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