103 research outputs found
Body Composition of Patients Undergoing Radical Cystectomy for Bladder Cancer: Sarcopenia, Low Psoas Muscle Index, and Myosteatosis Are Independent Risk Factors for Mortality
Abstract:
Background: We assessed a wide array of body composition parameters to identify those
most relevant as prognostic tools for patients undergoing radical cystectomy (RC) due to bladder
cancer (BC). Methods: In this retrospective, single-center study, preoperative computed tomography
(CT) scans of 657 patients were measured at the level of the 3rd lumbar vertebra (L3) to determine
common body composition indices including sarcopenia, myosteatosis, psoas muscle index (PMI),
subcutaneous and visceral fat index (SFI and VFI), visceral-to-subcutaneous fat ratio (VSR), and visceral
obesity. Predictors of overall survival (OS) and cancer-specific survival (CSS) were identified in
univariate and multivariate survival analysis. Results: Sarcopenia and a low PMI were independently
associated with shorter OS (Sarcopenia: HR 1.30; 95% CI 1.02–1.66; p = 0.04 and a low PMI: HR 1.32;
95% CI 1.02–1.70; p = 0.03) and CSS (Sarcopenia: HR 1.64; 95% CI 1.19–2.25; p < 0.01 and a low PMI:
HR 1.41; 95% CI 1.02–1.96; p = 0.04). Myosteatosis, measured as decreasing average Hounsfield units
of skeletal muscle, was an independent risk factor for OS (HR 0.98; 95% CI 0.97–1.00; p = 0.01) and
CSS (HR 0.98; 95% CI 0.96–1.00; p < 0.05). The assessed adipose tissue indices were not significant
predictors for OS and CSS. Conclusions: Sarcopenia, a low PMI, and myosteatosis are independent
predictors for OS and CSS in patients undergoing radical cystectomy for bladder cancer
Guiding principles for the development and application of solid-phase phosphorus adsorbents for freshwater ecosystems
While a diverse array of phosphorus (P)-adsorbent materials is currently available for application to freshwater aquatic systems, selection of the most appropriate P-adsorbents remains problematic. In particular, there has to be a close correspondence between attributes of the P-adsorbent, its field performance, and the management goals for treatment. These management goals may vary from a rapid reduction in dissolved P to address seasonal enrichments from internal loading, targeting external fluxes due to anthropogenic sources, or long term inactivation of internal P inventories contained within bottom sediments. It also remains a challenge to develop new methods and materials that are ecologically benign and cost-effective. We draw on evidence in the literature and the authors’ personal experiences in the field, to summarise the attributes of a range of P-adsorbent materials. We offer 'guiding principles' to support practical use of existing materials and outline key development needs for new materials
Fractional precipitation of rare earth iodates using complexation and hydrolysis of dimethyl sulfate
Contrast agent recognition in small animal CT using the Medipix2 detector
Energy resolving capabilities of X-ray detectors like the Medipix2 and the upcoming Medipix3 offer access to spectral information which is a new domain of information in medical imaging.
In conventional CT of a composite object only the cumulative contribution of all involved materials to the attenuation is measurable, but not how much each material component contributes to this attenuation is measured. Therefore, contrast agent cannot be distinguished from bone or calcifications. The method of material reconstruction exploits the energy information to determine the partial densities of the involved materials using a maximum likelihood approach, i.e. it allows the separation of contrast agent from tissue, bones and calcifications.
We have employed the Medipix All Resolution System (MARS) scanner equipped with a Medipix2 MXR and performed a CT scan of a mouse with iodine contrast agent in stomach and bowel. The method allows to separate the iodine contrast agent from all the other absorbing structures. In the iodine image, only the iodine concentration is visible, while the non-iodine (water) image shows all the other tissue structures and bones. The method of material reconstruction was applied to real CT data of a biological sample for the first time
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