Comparison of nuclear imaging techniques and volumetric imaging for the prediction of postoperative mortality and liver failure in patients undergoing localized liver-directed treatments:a systematic review

BACKGROUND/AIMS: Although volumetric imaging by computed tomography (CT) is the gold standard for preoperative assessment of the future liver remnant, nuclear imaging studies have shown promising data. This systematic review summarized the results from trials investigating volumetric and nuclear medicine imaging for the prediction of postoperative mortality and liver failure (LF). METHODS: MEDLINE and Web of Science were searched for papers investigating nuclear imaging methods for the prediction of postoperative clinical outcomes in patients undergoing local, liver-directed treatments. Only papers investigating both preoperative nuclear imaging and CT or magnetic resonance imaging (MR) for the prediction of postoperative mortality and/or LF were included. RESULTS: Twenty-five trials were qualified for this review. All trials but two used technetium-based tracers for the nuclear imaging examination. Four papers used MR imaging and the remaining used CT for the volumetric evaluation. Overall, the studies were heterogeneous both in terms of methodology and imaging technique. Of the thirteen studies reporting on postoperative mortality, most were descriptive without detailed diagnostic data. A few with detailed data found that nuclear imaging had better predictive value than volumetric imaging. Nineteen studies investigated the prediction of postoperative LF of which seven papers investigated the predictive value of both modalities in multivariable regression analysis. Two papers found that only nuclear imaging parameters were predictive of LF, one paper found that the CT parameter was predictive, and four papers found that combined nuclear and CT/MR imaging parameters were predictive of LF. CONCLUSION: Both methodologies were useful in the preoperative assessment of patients scheduled for liver interventions, especially in combination, but nuclear imaging demonstrated better predictive value for postoperative mortality and LF in a few trials. The overall technical and methodological heterogeneity of the included studies complicates the ability to directly compare the clinical utility of the two imaging techniques

A collagen-based layered chronic wound biofilm model for testing antimicrobial wound products

A new in vitro chronic wound biofilm model was recently published, which provided a layered scaffold simulating mammalian tissue composition on which topical wound care products could be tested. In this paper, we updated the model even further to mimic the dynamic influx of nutrients from below as is the case in a chronic wound. The modified in vitro model was created using collagen instead of agar as the main matrix component and contained both Staphylococcus aureus and Pseudomonas aeruginosa. The model was cast in transwell inserts and then placed in wound simulating media, which allowed for an exchange of nutrients and waste products across a filter. Three potential wound care products and chlorhexidine digluconate 2% solution as a positive control were used to evaluate the model. The tested products were composed of hydrogels made from completely biodegradable starch microspheres carrying different active compounds. The compounds were applied topically and left for 2–4 days. Profiles of oxygen concentration and pH were measured to assess the effect of treatments on bacterial activity. Confocal microscope images were obtained of the models to visualise the existence of microcolonies. Results showed that the modified in vitro model maintained a stable number of the two bacterial species over 6 days. In untreated models, steep oxygen gradients developed and pH increased to &gt;8.0. Hydrogels containing active compounds alleviated the high oxygen consumption and decreased pH drastically. Moreover, all three hydrogels reduced the colony forming units significantly and to a larger extent than the chlorhexidine control treatment. Overall, the modified model expressed several characteristics similar to in vivo chronic wounds.</p

Visible Near-Infrared Spectroscopy and Pedotransfer Function Well Predict Soil Sorption Coefficient of Glyphosate

The soil sorption coefficient (K-d) of glyphosate mainly controls its transport and fate in the environment. Laboratory-based analysis of K-d is laborious and expensive. This study aimed to test the feasibility of visible near-infrared spectroscopy (vis-NIRS) as an alternative method for glyphosate K-d estimation at a country scale and compare its accuracy against pedotransfer function (PTF). A total of 439 soils with a wide range of K-d values (37-2409 L kg(-1)) were collected from Denmark (DK) and southwest Greenland (GR). Two modeling scenarios were considered to predict K-d: a combined model developed on DK and GR samples and individual models developed on either DK or GR samples. Partial least squares regression (PLSR) and artificial neural network (ANN) techniques were applied to develop vis-NIRS models. Results from the best technique were validated using a prediction set and compared with PTF for each scenario. The PTFs were built with soil texture, OC, pH, Fe-ox, and P-ox. The ratio of performance to interquartile distance (RPIQ) was 1.88, 1.70, and 1.50 for the combined (ANN), DK (ANN), and GR (PLSR) validation models, respectively. vis-NIRS obtained higher predictive ability for K-d than PTFs for the combined dataset, whereas PTF resulted in slightly better estimations of K-d on the DK and GR samples. However, the differences in prediction accuracy between vis-NIRS and PTF were statistically insignificant. Considering the multiple advantages of vis-NIRS, e.g., being rapid and non-destructive, it can provide a faster and easier alternative to PTF for estimating glyphosate K-d