Results for “Multivariate sampling” — Page 13

DOE OSTI2019

Advantages of Intraprocedural Unenhanced CT During Adrenal Venous Sampling to Confirm Accurate Catheterization of the Right Adrenal Vein

Purpose: To evaluate the advantages of intraprocedural CT during adrenal venous sampling (AVS) to confirm accurate catheterization of the right adrenal vein (RAV). Materials and Methods: This single-institution study included 106 patients (mean age 52.4 years; range 28–74 years) with primary aldosteronism who performed contrast-enhanced CT (CECT) before AVS following AVS between January 2011 and March 2018. After catheterization of the RAV under fluoroscopic guidance, unenhanced CT images were obtained to confirm catheter position on unified CT angiography system. Catheter repositioning was performed when the catheter was inaccurately positioned. Venography findings were classified into two groups: (1) presumably cannulated in the RAV (presumed RAV group) and (2) obscured visualization of the RAV because of collateral vessels (obscured RAV group). Success rates of AVS were compared using Fisher’s exact test. Results: The overall success of AVS was achieved in 104 patients (98.1%). Catheter was deviated into the IVC during intraprocedural CT in four patients. Fourteen patients (14.0%) required catheter repositioning by intraprocedural CT images, and accurate catheterization in the RAV was eventually accomplished. The success rate of AVS was significantly higher in the presumed RAV group (90.1% [73/81]) than that in the obscured RAV group (68.4% [13/19]) (p = 0.024). If intraprocedural CT was not acquired during AVS, the success rate of AVS would have been significantly lower (84.9% [90/106]) compared with that use of intraprocedural CT (98.1% [104/106]) (p < 0.001). Conclusions: Intraprocedural unenhanced CT by referring to the preprocedural CECT before AVS enables the confirmation of accurate catheterization of the RAV. Level of Evidence: Level 4, case series.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Inorganic characterization of switchgrass biomass using laser-induced breakdown spectroscopy

The inorganic characterization of 74 samples of switchgrass using laser-induced breakdown spectroscopy (LIBS) was undertaken. Determination of ash and inorganic elements content in biomass materials is vital for feedstock screening for bioconversion processes. Hierarchical models using principal component analysis (PCA) and partial least square analysis (PLS) were used to determine the presence of specific elemental micronutrients that are important in determining plant health for robust biomass production. LIBS uses a 532 nm laser with 45 mJ of laser power to excite the samples of switchgrass plant material and the emission of all the elements present in the plant samples were recorded in single spectra with a wide wavelength range of 200–800 nm. The results were compared to the laboratory standard technique, e.g., ICP-OES technique, to determine the true values for major micronutrients such as, silicon (Si), potassium (K), calcium (Ca), magnesium (Mg), phosphorus (P), and sulfur (S). Overall, our objectives were: 1) To determine the spectral features of switchgrass containing different amounts of these elements and 2) To examine the viability of this technique for determining the quality of the feedstock in terms of its inorganic composition. Cross-validation results showed that the broad-based model developed is promising for inorganics prediction in switchgrass. The LIBS validation prediction for the micronutrient elements mentioned here have been obtained. The regression coefficients for Si, were obtained to be 0.995, 0.994 for calibration and validation respectively, in case of Ca the regression coefficients were, 0.994 and 0.992 for calibration and validation. Similarly, in the case of Mg and K these were calculated to be 0.992 and 0.985, and 0.994 and 0.993 respectively. The regression coefficients are not as good as those for the elements mentioned, in case of the two elements S and P. They are 0.957, and 0.878, and 0.952 and 0.894 respectively for calibration, validation for the two elements. This demonstrates that LIBS-based techniques are inherently well suited for diverse environmental applications. Furthermore, LIBS along with PLS model can show capability in determining the viability of switchgrass as a biomass in the production of biofuels and survivability of switchgrass in processes associated with climate change. LIBS can help determining which switchgrass would be appropriate for a specific conversion process that favors low ash content overall or low value of specific inorganics.

59 BASIC BIOLOGICAL SCIENCES↗