Biaxial stretching of polytetrafluoroethylene in industrial scale to fabricate medical ePTFE membrane with node-fibril microstructure.

Expanded polytetrafluoroethylene (ePTFE) is promising in biomedical fields such as covered stents and plastic surgery owing to its excellent biocompatibility and mechanical properties. However, ePTFE material prepared by the traditional biaxial stretching process is with thicker middle and thinner sides due to the bowing effect, which poses a major problem in industrial-scale fabrication. To solve this problem, we design an olive-shaped winding roller to provide the middle part of the ePTFE tape with a greater longitudinal stretching amplitude than the two sides, so as to make up for the excessive longitudinal retraction tendency of the middle part when it is transversely stretched. The as-fabricated ePTFE membrane has, as designed, uniform thickness and node-fibril microstructure. In addition, we examine the effects of mass ratio of lubricant to PTFE powder, biaxial stretching ratio and sintering temperature on the performance of the resultant ePTFE membranes. Particularly, the relation between the internal microstructure of the ePTFE membrane and its mechanical properties is revealed. Besides stable mechanical properties, the sintered ePTFE membrane exhibits satisfactory biological properties. We make a series of biological assessments including in vitro hemolysis, coagulation, bacterial reverse mutation and in vivo thrombosis, intracutaneous reactivity test, pyrogen test and subchronic systemic toxicity test; all of the results meet the relevant international standards. The muscle implantation of the sintered ePTFE membrane into rabbits indicates acceptable inflammatory reactions of our sintered ePTFE membrane fabricated on industrial scale. Such a medical-grade raw material with the unique physical form and condensed-state microstructure is expected to afford an inert biomaterial potentially for stent-graft membrane.

Mitochondria-Targeted Thymidylate Synthase Inhibitor Based on Fluorescent Molecularly Imprinted Polymers for Tumor Antimetabolic Therapy.

Antimetabolites targeting thymidylate synthase (TS), such as 5-fluorouracil and capecitabine, have been widely used in tumor therapy in the past decades. Here, we present a strategy to construct mitochondria-targeted antimetabolic therapeutic nanomedicines based on fluorescent molecularly imprinted polymers (FMIP), and the nanomedicine was denoted as Mito-FMIP. Mito-FMIP, synthesized using fluorescent dye-doped silica as the carrier and amino acid sequence containing the active center of TS as the template peptide, could specifically recognize and bind to the active site of TS, thus inhibiting the catalytic activity of TS, and therefore hindering subsequent DNA biosynthesis, ultimately inhibiting tumor growth. The imprinting factor of FMIP reached 2.9, and the modification of CTPB endowed Mito-FMIP with the ability to target mitochondria. In vitro experiments demonstrated that Mito-FMIP was able to efficiently aggregate in mitochondria and inhibit CT26 cell proliferation by 59.9%. The results of flow cytometric analysis showed that the relative mean fluorescence intensity of Mito-FMIP accumulated in the mitochondria was 3.4-fold that of FMIP. In vivo experiments showed that the tumor volume of the Mito-FMIP-treated group was only one third of that of the untreated group. In addition, Mito-FMIP exibited the maximum emission wavelength at 682 nm, which allowed it to be used for fluorescence imaging of tumors. Taken together, this study provides a new strategy for the construction of nanomedicines with antimetabolic functions based on molecularly imprinted polymers.

A Novel Hexokinases Inhibitor Based on Molecularly Imprinted Polymer for Combined Starvation and Enhanced Photothermal Therapy of Malignant Tumors.

The heat tolerance of tumor cells induced by heat shock proteins (HSPs) is the major factor that seriously hinders further application of PTT, as it can lead to tumor inflammation, invasion, and even recurrence. Therefore, new strategies to inhibit HSPs expression are essential to improve the antitumor efficacy of PTT. Here, we prepared a novel nanoparticle inhibitor by synthesizing molecularly imprinted polymers with a high imprinting factor (3.1) on the Prussian Blue surface (PB@MIP) for combined tumor starvation and photothermal therapy. Owing to using hexokinase (HK) epitopes as the template, the imprinted polymers could inhibit the catalytic activity of HK to interfere with glucose metabolism by specifically recognizing its active sites and then achieve starvation therapy by restricting ATP supply. Meanwhile, MIP-mediated starvation downregulated the ATP-dependent expression of HSPs and then sensitized tumors to hyperthermia, ultimately improving the therapeutic effect of PTT. As the inhibitory effect of PB@MIP on HK activity, more than 99% of the mice tumors were eliminated by starvation therapy and enhanced PTT.

Intestinal stents: Structure, functionalization and advanced engineering innovation.

Intestinal stents are a palliative treatment option that solves many shortcomings of traditional surgeries for cancer-induced intestinal obstructions. The present review provides an overview of the incidence, clinical manifestations and limitations in the treatment of intestinal cancers. The paper also discusses material property requirements, indications, complications and the future of stent-assisted therapy. The advantages and disadvantages of different materials and processing techniques for intestinal stents are reviewed along with new stent treatment combinations for colorectal cancer. Challenges that require further cooperative studies are also detailed. The future development of intestinal stents will depend on innovation in material designs as well as the utilization of multi-functional strategies and innovative engineering solutions.

Characterization of thermal and optical properties in porcine pancreas tissue.

BACKGROUND: Photothermal therapies have shown promise for treating pancreatic ductal adenocarcinoma when they can be applied selectively, but off-target heating can frustrate treatment outcomes. Improved strategies leveraging selective binding and localized heating are possible with precision medical approaches such as functionalized gold nanoparticles, but careful control of optical dosage and thermal generation would be imperative. However, the literature review revealed many groups assume liver properties for pancreas tissue or rely on insufficiently rigorous characterization studies. OBJECTIVE: The objective of this study was to determine the thermal conductivity and optical properties at 808/1064 nm wavelengths in healthy samples of fresh and frozen porcine pancreas ex vivo. METHODS: Thermal conductivity of the porcine pancreas tissue was measured by utilizing a hot plate and two K-type thermocouples. Experimental variables such as tissue sample thickness, hot plate temperature, and heat convection coefficient were estimated through the control experiments utilizing specimens with known thermal conductivity. Optical evaluations assessed light attenuation at the 808 and 1064 nm wavelengths (continuous wave, collimated beam) by measuring the light transmittance and reflectance of different tissue thicknesses. In turn, these measurements were input into an inverse adding-doubling program to estimate the optical absorption and reduced scattering coefficients. RESULTS: Interestingly, pancreas tissue thermal conductivity was demonstrated to have no significant difference (p > 0.5) between samples that were fresh, frozen for 7 days, or frozen for 14 days. Conversely, optical property assessment exhibited a significant difference (p < 0.001) between fresh and frozen tissue samples, with increased absorbance and reflectance within the frozen group. However, the optical attenuation values measured were substantially less than that of the liver or reported in previous pancreas studies, suggesting a wide overestimation of these properties. CONCLUSIONS: These thermal and optical properties are critical to the development of novel therapeutic strategies like plasmonic photothermal therapy, but perhaps more importantly, are invaluable towards informing better surgical planning and operative technique among the existing thermal approaches for treating pancreas tissue.

Bimetallic molecularly imprinted nanozyme: Dual-mode detection platform.

Molecularly imprinted polymer nanozyme (MIL-101(Co,Fe)@MIP) with bimetallic active sites and high-efficiency peroxidase-like (POD-like) activity were synthesized for the ratiometric fluorescence and colorimetric dual-mode detection of vanillin with high selectivity and sensitivity. Compared with the monometallic nanozyme, the POD-like activity of bimetallic nanozyme was greatly enhanced by changing the electronic structure and surface structure. Ratiometric fluorescence and colorimetric dual-mode detection of vanillin in aqueous solution was realized by vanillin entering specific imprinted cavities and blocking the molecular channels on the surface of MIL-101(Co,Fe)@MIP and the dual-mode visual detection was also realized. The limits of detection were as low as 104 nM and 198 nM, respectively. The method proposed in this paper was applied to the real samples of ice cream and candy. And the recoveries were between 93.3% and 105.5%, which also reached a satisfactory degree. The further detection of dexamethasone and prednisone, two drugs belonging to glucocorticoid, proved that the nanozyme analysis method based on MIL-101(Co,Fe)@MIP could be developed into a sensing platform.

Assessment and Modeling of Plasmonic Photothermal Therapy Delivered via a Fiberoptic Microneedle Device Ex Vivo.

Plasmonic photothermal therapy (PPTT) has potential as a superior treatment method for pancreatic cancer, a disease with high mortality partially attributable to the currently non-selective treatment options. PPTT utilizes gold nanoparticles infused into a targeted tissue volume and exposed to a specific light wavelength to induce selective hyperthermia. The current study focuses on developing this approach within an ex vivo porcine pancreas model via an innovative fiberoptic microneedle device (FMD) for co-delivering light and gold nanoparticles. The effects of laser wavelengths (808 vs. 1064 nm), irradiances (20-50 mW·mm-2), and gold nanorod (GNR) concentrations (0.1-3 nM) on tissue temperature profiles were evaluated to assess and control hyperthermic generation. The GNRs had a peak absorbance at ~800 nm. Results showed that, at 808 nm, photon absorption and subsequent heat generation within tissue without GNRs was 65% less than 1064 nm. The combination of GNRs and 808 nm resulted in a 200% higher temperature rise than the 1064 nm under similar conditions. A computational model was developed to predict the temperature shift and was validated against experimental results with a deviation of <5%. These results show promise for both a predictive model and spatially selective, tunable treatment modality for pancreatic cancer.

Phosphate-Degradable Nanoparticles Based on Metal-Organic Frameworks for Chemo-Starvation-Chemodynamic Synergistic Antitumor Therapy.

Chemodynamic therapy (CDT) was regarded as a promising approach for tumor treatment. However, owing to the insufficient amount of endogenous hydrogen peroxide (H2O2) in tumor cells, the efficacy of CDT was limited. In this study, we designed phosphate-responsive nanoparticles (denoted as MGDFT NPs) based on metal-organic frameworks, which were simultaneously loaded with drug doxorubicin (DOX) and glucose oxidases (GOx). The decorated GOx could act as a catalytic nanomedicine for the response to the abundant glucose in the tumor microenvironment, generating a great deal of H2O2, which would enhance the Fenton reaction and produce toxic hydroxyl radicals (·OH). Meanwhile, the growth of tumors would also be inhibited by overconsuming the intratumoral glucose, which was the "fuel" for cell proliferation. When the nanoparticles entered into tumor cells, a high concentration of phosphate induced structure collapse, releasing the loaded DOX for chemotherapy. Furthermore, the decoration of target agents endowed the nanoparticles with favorable target ability to specific tumor cells and mitochondria. Consequently, the designed MGDFT NPs displayed desirable synergistic therapeutic effects via combining chemotherapy, starvation therapy, and enhanced Fenton reaction, facilitating the development of multimodal precise antitumor therapy.

Targeted Mitochondrial Fluorescence Imaging-Guided Tumor Antimetabolic Therapy with the Imprinted Polymer Nanomedicine Capable of Specifically Recognizing Dihydrofolate Reductase.

As we all know, inhibiting the activity of dihydrofolate reductase (DHFR) has always been an effective strategy for folate antimetabolites to treat tumors. In the past, it mainly relied on chemical drugs. Here, we propose a new strategy, (3-propanecarboxyl)triphenylphosphonium bromide (CTPB)-modified molecularly imprinted polymer nanomedicine (MIP-CTPB). MIP-CTPB prepared by imprinting the active center of DHFR can specifically bind to the active center to block the catalytic activity of DHFR, thereby inhibiting the synthesis of DNA and ultimately inhibiting the tumor growth. The modification of CTPB allows the nanomedicine to be targeted and enriched in mitochondria, where DHFR is abundant. The confocal laser imaging results show that MIP-CTPB can target mitochondria. Cytotoxicity experiments show that MIP-CTPB inhibits HeLa cell proliferation by 42.2%. In vivo experiments show that the tumor volume of the MIP-CTPB-treated group is only one-sixth of that of the untreated group. The fluorescent and paramagnetic properties of the nanomedicine enable targeted fluorescence imaging of mitochondria and T2-weighted magnetic resonance imaging of tumors. This research not only opens up a new direction for the application of molecular imprinting, but also provides a new idea for tumor antimetabolic therapy guided by targeted mitochondrial imaging.

Novel expandable architected breathing tube for improving airway securement in emergency care.

Life-saving interventions utilize endotracheal intubation to secure a patient's airway, but performance of the clinical standard of care endotracheal tube (ETT) is inadequate. For instance, in the current COVID-19 crisis, patients can expect prolonged intubation. This protracted intubation may produce health complications such as tracheal stenosis, pneumonia, and necrosis of tracheal tissue, as current ETTs are not designed for extended use. In this work, we propose an improved ETT design that seeks to overcome these limitations by utilizing unique geometries which enable a novel expanding cylinder. The mechanism provides a better distribution of the contact forces between the ETT and the trachea, which should enhance patient tolerability. Results show that at full expansion, our new ETT exerts pressures in a silicone tracheal phantom well within the recommended standard of care. Also, preliminary manikin tests demonstrated that the new ETT can deliver similar performance in terms of air pressure and air volume when compared with the current gold standard ETT. The potential benefits of this new architected ETT are threefold, by limiting exposure of healthcare providers to patient pathogens through streamlining the intubation process, reducing downstream complications, and eliminating the need of multiple size ETT as one architected ETT fits all.

Tumor-Sensitive Biodegradable Nanoparticles of Molecularly Imprinted Polymer-Stabilized Fluorescent Zeolitic Imidazolate Framework-8 for Targeted Imaging and Drug Delivery.

Targeting enrichment of nanocarriers at tumor sites and effective drug release are critical in cancer treatment. Accordingly, we used fluorescent zeolitic imidazolate framework-8 nanoparticles loaded with doxorubicin (FZIF-8/DOX) as the core and a molecularly imprinted polymer (MIP) as the shell to synthesize tumor-sensitive biodegradable FZIF-8/DOX-MIP nanoparticles (FZIF-8/DOX-MIPs). The MIP prepared with the epitope of CD59 cell membrane glycoprotein as the template allowed FZIF-8/DOX-MIPs to be enriched to tumor sites by actively targeting recognition of MCF-7 cancer cells (CD59-positive). Moreover, using N,N'-diacrylylcystamine as the cross-linker and dimethylaminoethyl methacrylate as the main monomer, the MIP's framework will be broken under the stimulation of a tumor microenvironment (high-concentration glutathione and weakly acidic), so that the internal FZIF-8/DOX is exposed to a microacidic environment to release DOX through further degradation. More importantly, the ability of FZIF-8/DOX-MIPs in targeted fluorescence imaging and effective drug release has been validated both in vitro and in vivo. Compared to other cells and nanoparticles, FZIF-8/DOX-MIPs were more capable of being phagocytosed by MCF-7 cells and were more lethal to MCF-7 cells. In the comparative experiments carried out on tumor-bearing mice, FZIF-8/DOX-MIPs had the best inhibitory effect on the growth of MCF-7 tumors. Furthermore, the FZIF-8/DOX-MIPs can serve as a diagnostic agent because of the active targeting of MCF-7 cells and the stronger red fluorescence of the embedded carbon quantum dots. Because of the active targeting ability, good biocompatibility, tumor-sensitive biodegradability, and effective drug release performance, FZIF-8/DOX-MIPs can be widely used in tumor imaging and treatment.

Multiphysics Modeling of Plasmonic Photothermal Heating Effects in Gold Nanoparticles and Nanoparticle Arrays.

Induced hyperthermia has been demonstrated as an effective oncological treatment due to the reduced heat tolerance of most malignant tissues; however, most techniques for heat generation within a target volume are insufficiently selective, inducing heating and unintended damage to surrounding healthy tissues. Plasmonic photothermal therapy (PPTT) utilizes light in the near-infrared (NIR) region to induce highly localized heating in gold nanoparticles, acting as exogenous chromophores, while minimizing heat generation in nearby tissues. However, optimization of treatment parameters requires extensive in vitro and in vivo studies for each new type of pathology and tissue targeted for treatment, a process that can be substantially reduced by implementing computational modeling. Herein, we describe the development of an innovative model based on the finite element method (FEM) that unites photothermal heating physics at the nanoscale with the micron scale to predict the heat generation of both single and arrays of gold nanoparticles. Plasmonic heating from laser illumination is computed for gold nanoparticles with three different morphologies: nanobipyramids, nanorods, and nanospheres. Model predictions based on laser illumination of nanorods at a visible wavelength (655 nm) are validated through experiments, which demonstrate a temperature increase of 5 °C in the viscinity of the nanorod array when illuminated by a 150 mW red laser. We also present a predictive model of the heating effect induced at 810 nm, wherein the heating efficiencies of the various morphologies sharing this excitation peak are compared. Our model shows that the nanorod is the most effective at heat generation in the isolated scenario, and arrays of 91 nm long nanorods reached hyperthermic levels (an increase of at least 5 °C) within a volume of over 20 µm3.

The Impact of a Location-Sensing Electronic Health Record on Clinician Efficiency and Accuracy: A Pilot Simulation Study.

BACKGROUND: Through the Health Information Technology for Economic and Clinical Health Act of 2009, the federal government invested $26 billion in electronic health records (EHRs) to improve physician performance and patient safety; however, these systems have not met expectations. One of the cited issues with EHRs is the human-computer interaction, as exhibited by the excessive number of interactions with the interface, which reduces clinician efficiency. In contrast, real-time location systems (RTLS)-technologies that can track the location of people and objects-have been shown to increase clinician efficiency. RTLS can improve patient flow in part through the optimization of patient verification activities. However, the data collected by RTLS have not been effectively applied to optimize interaction with EHR systems. OBJECTIVES: We conducted a pilot study with the intention of improving the human-computer interaction of EHR systems by incorporating a RTLS. The aim of this study is to determine the impact of RTLS on process metrics (i.e., provider time, number of rooms searched to find a patient, and the number of interactions with the computer interface), and the outcome metric of patient identification accuracy METHODS: A pilot study was conducted in a simulated emergency department using a locally developed camera-based RTLS-equipped EHR that detected the proximity of subjects to simulated patients and displayed patient information when subjects entered the exam rooms. Ten volunteers participated in 10 patient encounters with the RTLS activated (RTLS-A) and then deactivated (RTLS-D). Each volunteer was monitored and actions recorded by trained observers. We sought a 50% improvement in time to locate patients, number of rooms searched to locate patients, and the number of mouse clicks necessary to perform those tasks. RESULTS: The time required to locate patients (RTLS-A = 11.9 ± 2.0 seconds vs. RTLS-D = 36.0 ± 5.7 seconds, p < 0.001), rooms searched to find patient (RTLS-A = 1.0 ± 1.06 vs. RTLS-D = 3.8 ± 0.5, p < 0.001), and number of clicks to access patient data (RTLS-A = 1.0 ± 0.06 vs. RTLS-D = 4.1 ± 0.13, p < 0.001) were significantly reduced with RTLS-A relative to RTLS-D. There was no significant difference between RTLS-A and RTLS-D for patient identification accuracy. CONCLUSION: This pilot demonstrated in simulation that an EHR equipped with real-time location services improved performance in locating patients and reduced error compared with an EHR without RTLS. Furthermore, RTLS decreased the number of mouse clicks required to access information. This study suggests EHRs equipped with real-time location services that automates patient location and other repetitive tasks may improve physician efficiency, and ultimately, patient safety.

A fully coupled space-time multiscale modeling framework for predicting tumor growth.

Most biological systems encountered in living organisms involve highly complex heterogeneous multi-component structures that exhibit different physical, chemical, and biological behavior at different spatial and temporal scales. The development of predictive mathematical and computational models of multiscale events in such systems is a major challenge in contemporary computational biomechanics, particularly the development of models of growing tumors in humans. The aim of this study is to develop a general framework for tumor growth prediction by considering major biological events at tissue, cellular, and subcellular scales. The key to developing such multiscale models is how to bridge spatial and temporal scales that range from 10-3 to 103 mm in space and from 10-6 to 107 s in time. In this paper, a fully coupled space-time multiscale framework for modeling tumor growth is developed. The framework consists of a tissue scale model, a model of cellular activities, and a subcellular transduction signaling pathway model. The tissue, cellular, and subcellular models in this framework are solved using partial differential equations for tissue growth, agent-based model for cellular events, and ordinary differential equations for signaling transduction pathway as a network at subcellular scale. The model is calibrated using experimental observations. Moreover, this model is biologically-driven from a signaling pathway, volumetrically-consistent between cellular and tissue scale in terms of tumor volume evolution in time, and a biophysically-sound tissue model that satisfies all conservation laws. The results show that the model is capable of predicting major characteristics of tumor growth such as the morphological instability, growth patterns of different cell phenotypes, compact regions of the higher cell density at the tumor region, and the reduction of growth rate due to drug delivery. The predicted treatment outcomes show a reduction in proliferation at different rates in response to different drug dosages. Moreover, the results of several 3D applications to tumor growth and the evolution of cellular and subcellular events are presented.

CrossLink: a novel method for cross-condition classification of cancer subtypes.

BACKGROUND: We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. METHODS: To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. RESULTS: We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. CONCLUSIONS: A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

Simulation of temperature field for temperature-controlled radio frequency ablation using a hyperbolic bioheat equation and temperature-varied voltage calibration: a liver-mimicking phantom study.

This study aims at improving the accuracy of temperature simulation for temperature-controlled radio frequency ablation (RFA). We proposed a new voltage-calibration method in the simulation and investigated the feasibility of a hyperbolic bioheat equation (HBE) in the RFA simulation with longer durations and higher power. A total of 40 RFA experiments was conducted in a liver-mimicking phantom. Four mathematical models with multipolar electrodes were developed by the finite element method in COMSOL software: HBE with/without voltage calibration, and the Pennes bioheat equation (PBE) with/without voltage calibration. The temperature-varied voltage calibration used in the simulation was calculated from an experimental power output and temperature-dependent resistance of liver tissue. We employed the HBE in simulation by considering the delay time τ of 16 s. First, for simulations by each kind of bioheat equation (PBE or HBE), we compared the differences between the temperature-varied voltage-calibration and the fixed-voltage values used in the simulations. Then, the comparisons were conducted between the PBE and the HBE in the simulations with temperature-varied voltage calibration. We verified the simulation results by experimental temperature measurements on nine specific points of the tissue phantom. The results showed that: (1) the proposed voltage-calibration method improved the simulation accuracy of temperature-controlled RFA for both the PBE and the HBE, and (2) for temperature-controlled RFA simulation with the temperature-varied voltage calibration, the HBE method was 0.55 °C more accurate than the PBE method. The proposed temperature-varied voltage calibration may be useful in temperature field simulations of temperature-controlled RFA. Besides, the HBE may be used as an alternative in the simulation of long-duration high-power RFA.

The design and fabrication of two portal vein flow phantoms by different methods.

PURPOSE: This study outlines the design and fabrication techniques for two portal vein flow phantoms. METHODS: A materials study was performed as a precursor to this phantom fabrication effort and the desired material properties are restated for continuity. A three-dimensional portal vein pattern was created from the Visual Human database. The portal vein pattern was used to fabricate two flow phantoms by different methods with identical interior surface geometry using computer aided design software tools and rapid prototyping techniques. One portal flow phantom was fabricated within a solid block of clear silicone for use on a table with Ultrasound or within medical imaging systems such as MRI, CT, PET, or SPECT. The other portal flow phantom was fabricated as a thin walled tubular latex structure for use in water tanks with Ultrasound imaging. Both phantoms were evaluated for usability and durability. RESULTS: Both phantoms were fabricated successfully and passed durability criteria for flow testing in the next project phase. CONCLUSIONS: The fabrication methods and materials employed for the study yielded durable portal vein phantoms.

An investigation of industrial molding compounds for use in 3D ultrasound, MRI, and CT imaging phantoms.

PURPOSE: This study investigated the ultrasound, MRI, and CT imaging characteristics of several industrial casting and molding compounds as a precursor to the future development of durable and anatomically correct flow phantoms. METHODS: A set of usability and performance criteria was established for a proposed phantom design capable of supporting liquid flow during imaging. A literature search was conducted to identify the materials and methods previously used in phantom fabrication. A database of human tissue and casting material properties was compiled to facilitate the selection of appropriate materials for testing. Several industrial casting materials were selected, procured, and used to fabricate test samples that were imaged with ultrasound, MRI, and CT. RESULTS: Five silicones and one polyurethane were selected for testing. Samples of all materials were successfully fabricated. All imaging modalities were able to discriminate between the materials tested. Ultrasound testing showed that three of the silicones could be imaged to a depth of at least 2.5 cm (1 in.). The RP-6400 polyurethane exhibited excellent contrast and edge detail for MRI phantoms and appears to be an excellent water reference for CT applications. The 10T and 27T silicones appear to be usable water references for MRI imaging. CONCLUSIONS: Based on study data and the stated selection criteria, the P-4 silicone provided sufficient material contrast to water and edge detail for use across all imaging modalities with the benefits of availability, low cost, dimensional stability, nontoxic, nonflammable, durable, cleanable, and optical clarity. The physical and imaging differences of the materials documented in this study may be useful for other applications.

Model-based planning and real-time predictive control for laser-induced thermal therapy.

In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity.