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Rationale and Objectives: CT-guided radiofrequency ablation (RFA) is a potentially curative minimally invasive treatment for liver cancer. Local tumor recurrence limits the success of RFA for large or irregular tumors as it is difficult to visualize the tissue destroyed. This study was designed to validate a real-time software-simulated ablation volume for intraprocedural guidance.Materials and Methods: Software that simulated RFA physics calculated ablation volumes in 17 agar-albumin phantoms (7 with a simulated vessel) and in six in-vivo (porcine) ablations. The software-modeled volumes were compared with the actual ablations (physical lesion in agar, contrast CT in the porcine model) and to the volume predicted by the manufacturer's charts. Error was defined as the distance from evenly distributed points on the segmented true ablation volume surfaces to the closest points on the corresponding computer-generated model, and for the porcine model, to the manufacturer-specified ablation volume. Results:The average maximum error of the simulation was 2.8 mm (range to 4.9 mm) in the phantoms. The heat-sink effect from the simulated vessel was well-modeled by the simulation. In the porcine model, the average maximum error of the simulation was 5.2 mm (range to 8.1 mm) vs 7.8 mm (range to 10.0mm) for the manufacturer's model (p = 0.009). Conclusion:A real-time computer-generated RFA model incorporated tine position, energy deposited, and large vessel proximity to predict the ablation volume in agar phantoms with less than 3mm maximum error. Although the in-vivo model had slightly higher maximum error, the software better predicted the achieved ablation volume compared to the manufacturer's ablation maps.

Objective: Ectopic fat deposition within and around organs is a stronger predictor of cardiometabolic disease status than body mass index (BMI). Fat deposition within the lymphatic system is poorly understood. This study examined the association between the prevalence of cardiometabolic disease and ectopic fat deposition within axillary lymph nodes (LNs) visualized on screening mammograms. Methods:A cross-sectional study was conducted on 834 women presenting for fullfield digital screening mammography. The status of fat-infiltrated LNs was assessed based on the size and morphology of axillary LNs from screening mammograms. The prevalence of cardiometabolic disease was retrieved from the electronic medical records, including type 2 diabetes mellitus (T2DM), hypertension, dyslipidemia, high blood glucose, cardiovascular disease, stroke, and non-alcoholic fatty liver disease.Results: Fat-infiltrated axillary LNs were associated with a high prevalence of T2DM among all women (adjusted odds ratio: 3.92, 95% CI: [2.40, 6.60], p-value < 0.001) and in subgroups of women with and without obesity. Utilizing the status of fatty LNs improved the classification of T2DM status in addition to age and BMI (1.4% improvement in the area under the receiver operating characteristic curve). Conclusion: Fat-infiltrated axillary LNs visualized on screening mammograms were associated with the prevalence of T2DM. If further validated, fat-infiltrated axillary LNs may represent a novel imaging biomarker of T2DM in women undergoing screening mammography.

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Anaerobic digestion is extensively used to recover energy from municipal waste and animal manure. The liquid effluent of anaerobic digestion typically contains high concentrations of ammonium, phosphorus, and divalent cations, which can potentially be recovered by precipitation of sparingly soluble phosphate salts [1-5]. The majority of processes focus on struvite (magnesium ammonium phosphate) crystallization, as both nitrogen and phosphorus are removed and struvite is salable as slow-release plant fertilizer. The potential economics of recovering renewable sources of nitrogen and phosphorus have led to development of various phosphate salt crystallization systems [5-7]. Fluidized bed reactors (FBRs) are commonly used for crystallized phosphate recovery because the design creates an abundance of reactive surface area and solution turbulence [8], enhancing nucleation kinetics and agglomeration. Despite generally high nutrient recovery efficiencies in FBRs, the economic favorability of phosphate salt crystallization systems could be significantly enhanced by increasing the operating pH within the FBR to near the minimum solubility point of struvite (pH = 9 [3]) Sodium hydroxide (NaOH) is often used in research-scale investigation of these technologies because it is highly soluble and can rapidly increase the solution pH [4,7,9,10]. However, such chemical addition approaches can drive up phosphorus recovery costs (as high as $3,500/ton-P) significantly beyond the value of nutrients contained in struvite (~$765/ton-P) [3,11]. Recently, microbial electrochemical technologies (METs), such as microbial fuel cells (MFCs) and microbial electrolysis cells (MECs) have garnered interest as a chemical-free and energy efficient method of enhancing struvite precipitation [12-14]. METs consist of an anode, where anaerobic microbes oxidize organic matter and transfer electrons to an external circuit, and a cathode where the electrons and protons catalytically combine by reducing oxygen to water (MFC) or producing hydrogen gas (MEC). This talk will discuss preliminary results from a bench-scale MEC-FBR system (Figure 1) that demonstrate the potential for an MEC to enable economical pH control in an FBR struvite precipitation system. Net alkali generation rates of approximately 2.3 ± 1.5 mmol m- 2 h-1 were observed in both DC and pulsed-potential MEC tests, which are of reasonable magnitude for typical applications. When only the electrical power input is considered, these experimental data translate to a per-mole cost of alkali generated by an MEC (~7¢ mol-1) that is an order of magnitude lower than the cost of purchased NaOH (~87¢ mol-1). A preliminary net present value (NPV) analysis of the entire MEC unit operation, including both capital and operating costs, suggests a reasonable rate of return can likely be achieved. As well, the data provide preliminary indication of the possibility of further cost advantages from the use of pulsed MEC potentials. The authors acknowledge financial support from USEPA Contract No. EP-D-17-006. References [1] Battistoni, P., A. De Angelis, P. Pavan, M. Prisciandaro, F. Cecchi. “Phosphorus removal from a real anaerobic supernatant by struvite crystallization.” Water Research 35(9): 2167 (2001). [2] Snoeyink, V., D. Jenkins. Water Chemistry.John Wiley (1980). [3] Doyle, J., S. Parsons. “Struvite formation, control and recovery.” Water Research 36(16): 3925 (2002). [4] Ohlinger, K., T. Young, E. Schroeder. “Kinetics effects on preferential struvite accumulation in wastewater.” Journal of Environmental Engineering 126: 730 (1999). [5] Ohlinger, K., T. Young, E. Schroeder. “Postdigestion struvite precipitation using a fluidized bed reactor.” Journal of Environmental Engineering 126: 361 (2000). [6] Ohlinger, K., T. Young, E. Schroeder. “Predicting struvite formation in digestion.” Water Research 32(12): 3607 (1998). [7] Bhuiyan, M., D. Mavinic, F. Koch. “Phosphorus recovery from wastewater through struvite formation in fluidized bed reactors: a sustainable approach.” Water Science & Technology 57(2): 175 (2008). [8] Seckler, M., O. Bruinsma, G. Van Rosmalen. “Phosphate removal in a fluidized bed--I. Identification of physical processes.” Water Research 30(7): 1585 (1996). [9] Le Corre, K., E. Valsami-Jones, P. Hobbs, S. Parsons. “Impact of calcium on struvite crystal size, shape and purity.” Journal of Crystal Growth 283(3-4): 514 (2005). [10] Le Corre, K., E. Valsami-Jones, P. Hobbs, B. Jefferson, S. Parsons. “Struvite crystallisation and recovery using a stainless steel structure as a seed material.” Water Research 41(11): 2449 (2007). [11] Dockhorn, T. In “About the economy of phosphorus recovery,” pp. 145-158. IWA (2009). [12] Cusick, R., B. Logan. “Phosphate recovery as struvite within a single chamber microbial electrolysis cell.” Bioresource Technology, 107: 110 (2012). [13] Hirooka, K., O. Ichihashi. “Phosphorus recovery from artificial wastewater by microbial fuel cell and its effect on power generation.” Bioresource Technology 137: 368 (2013). [14] Ichihashi, O., K. Hirooka. “Removal and recovery of phosphorus as struvite from swine wastewater using microbial fuel cell.” Bioresource Technology 114: 303 (2012). Figure 1