Postoperative Spinal Cord Ischemia Monitoring: A Review of Techniques Available after Endovascular Aortic Repair.

BACKGROUND: Spinal cord ischemia is one of the complications that can occur after open and endovascular thoracoabdominal aortic repair. This occurs despite various perioperative approaches, including distal aortic perfusion, hybrid procedures with extra anatomical bypasses, motor-evoked potential, and cerebrospinal fluid drainage. The inability to recognize spinal ischemia in a timely manner remains a devastating complication after thoracoabdominal aortic repair.This review aims to look at novel technologies that are designed for continuous monitoring to detect early changes that signal the development of spinal cord ischemia and to discuss their benefits and limitations. METHODS: We conducted a systematic review of the technologies available for continuous monitoring in the intensive care unit for early detection of spinal cord ischemia. Studies were eligible for inclusion if they used different technologies for monitoring spinal ischemia during the postoperative period. All articles that were not available in English were excluded. To ensure that all relevant articles were included, no other significant restrictions were imposed. RESULTS: We identified 59 studies from the outset to December 2022 to be included in our study. New techniques have been studied as potentially useful monitoring tools that could provide simple and effective monitoring of the spinal cord. These include near-infrared spectroscopy, contrast-enhanced ultrasound, magnetic resonance imaging, fiber optic monitoring of the spinal cord, and cerebrospinal fluid biomarkers. CONCLUSIONS: Despite the development of new techniques to monitor for postoperative spinal cord ischemia, their use remains limited. We recommend more future research to ensure rapid intervention for our patients.

Brownian Diffusion of Hexagonal Boron Nitride Nanosheets and Graphene in Two Dimensions.

Two-dimensional (2D) nanomaterials have numerous interesting chemical and physical properties that make them desirable building blocks for the manufacture of macroscopic materials. Liquid-phase processing is a common method for forming macroscopic materials from these building blocks including wet-spinning and vacuum filtration. As such, assembling 2D nanomaterials into ordered functional materials requires an understanding of their solution dynamics. Yet, there are few experimental studies investigating the hydrodynamics of disk-like materials. Herein, we report the lateral diffusion of hexagonal boron nitride nanosheets (h-BN and graphene) in aqueous solution when confined in 2-dimensions. This was done by imaging fluorescent surfactant-tagged nanosheets and visualizing them by using fluorescence microscopy. Spectroscopic studies were conducted to characterize the interactions between h-BN and the fluorescent surfactant, and atomic force microscopy (AFM) was conducted to characterize the quality of the dispersion. The diffusion data under different gap sizes and viscosities displayed a good correlation with Kramers' theory. We propose that the yielded activation energies by Kramers' equation express the magnitude of the interaction between fluorescent surfactant tagged h-BN and glass because the energies remain constant with changing viscosity and decrease with increasing confinement size. The diffusion of graphene presented a similar trend with similar activation energy as the h-BN. This relationship suggests that Kramers' theory can also be applied to simulate the diffusion of other 2D nanomaterials.

Cadaveric aortic aneurysm creation: A life-like model for training endovascular repair.

The recent decline in RAAA incidence and the fast paced scenario with associated challenges regarding training calls for initiative for a better training environment to maximize learning. This led us to the creation of a pulsatile human cadaveric RAAA model. Fresh frozen cadaver was used to create RAAA with BioTissue in hybrid suite with ability to perform CBCTA for sizing. As a proof of concept, the model was used to perform REVAR with proximal CODA balloon control. The model proved to be feasible and we believe it is a better environment to train and gain adequate proficiency in RAAA management.

HS-GC-FID method for quantification of HFA-152a in cell culture media, and plasma from a range of species and regulatory compliant validations.

INTRODUCTION: 1,1-Difluoroethane (HFA-152a) is being developed as an alternative propellant in pressurized metered dose inhalers (pMDIs). As a part of the regulatory development pathway, pharmacology, toxicology and clinical studies have been conducted with inhaled HFA-152a. These studies require fit for purpose regulatory compliant (GxP validated) methods for quantification of HFA-152a from blood. METHODS: As HFA-152a is a gas at standard temperature and pressure, novel methods were developed to support the analysis across the wide range of species and concentrations required for regulatory filing. RESULTS: The developed methods utilized a headspace auto sampler coupled to a gas chromatograph (GC) with flame ionization detection. Key factors in the successful method included bringing together fit for purpose approaches to the head space vials, volume of matrix (blood), detection range required for species/study objective, handling / transfer of blood into head space vials and the stability/storage required for the analysis of the samples. The species-specific assays were fully validated under regulatory (GLP) conditions for mouse, rat, rabbit, canine and human and non-regulatory (non GLP) validations for guinea pig and cell culture media. DISCUSSION: Overall the novel approach of head space analysis of whole blood allowed for the development and validation of assays used to generate the toxicokinetic data that supported clinical testing of HFA-152a as a new pMDI propellant.

The utility of machine learning for predicting donor discard in abdominal transplantation.

BACKGROUND: Increasing access and better allocation of organs in the field of transplantation is a critical problem in clinical care. Limitations exist in accurately predicting allograft discard. Potential exists for machine learning to provide a balanced assessment of the potential for an organ to be used in a transplantation procedure. METHODS: We accessed and utilized all available deceased donor United Network for Organ Sharing data from 1987 to 2020. With these data, we evaluated the performance of multiple machine learning methods for predicting organ use. The machine learning methods trialed included XGBoost, random forest, Naïve Bayes (NB), logistic regression, and fully connected feedforward neural network classifier methods. The top two methods, XGBoost and random forest, were fully developed using 10-fold cross-validation and Bayesian optimization of hyperparameters. RESULTS: The top performing model at predicting liver organ use was an XGBoost model which achieved an AUC-ROC of .925, an AUC-PR of .868, and an F1 statistic of .756. The top performing model for predicting kidney organ use classification was an XGBoost model which achieved an AUC-ROC of .952, and AUC-PR of .883, and an F1 statistic of .786. CONCLUSIONS: The XGBoost method demonstrated a significant improvement in predicting donor allograft discard for both kidney and livers in solid organ transplantation procedures. Machine learning methods are well suited to be incorporated into the clinical workflow; they can provide robust quantitative predictions and meaningful data insights for clinician consideration and transplantation decision-making.

Houston Methodist Ruptured Abdominal Aortic Aneurysm Guidelines.

Ruptured abdominal aortic aneurysm (RAAA) is an acute aortic condition that requires emergent intervention and appropriate continuity of care to optimize patient outcomes. We describe the standardized RAAA protocol at the Houston Methodist Hospital Acute Aortic Treatment Center, developed to navigate critical patient transfer periods safely and efficiently, make crucial decisions about surgical intervention, and clearly communicate these plans with other care team providers. Our workflow is organized into five phases: prehospital, preoperative, intraoperative, postoperative, and post-discharge. We identify the transfer center, anesthesia, operating room nursing staff, surgeons, and intensive care unit as key entities of our acute aortic pathology care team. This systematic protocol for the management of acute aortic emergencies such as RAAA identifies critical decision points, potential complications at each stage, and recommendations for best practice.

nnU-Net Deep Learning Method for Segmenting Parenchyma and Determining Liver Volume From Computed Tomography Images.

Background: Recipient donor matching in liver transplantation can require precise estimations of liver volume. Currently utilized demographic-based organ volume estimates are imprecise and nonspecific. Manual image organ annotation from medical imaging is effective; however, this process is cumbersome, often taking an undesirable length of time to complete. Additionally, manual organ segmentation and volume measurement incurs additional direct costs to payers for either a clinician or trained technician to complete. Deep learning-based image automatic segmentation tools are well positioned to address this clinical need. Objectives: To build a deep learning model that could accurately estimate liver volumes and create 3D organ renderings from computed tomography (CT) medical images. Methods: We trained a nnU-Net deep learning model to identify liver borders in images of the abdominal cavity. We used 151 publicly available CT scans. For each CT scan, a board-certified radiologist annotated the liver margins (ground truth annotations). We split our image dataset into training, validation, and test sets. We trained our nnU-Net model on these data to identify liver borders in 3D voxels and integrated these to reconstruct a total organ volume estimate. Results: The nnU-Net model accurately identified the border of the liver with a mean overlap accuracy of 97.5% compared with ground truth annotations. Our calculated volume estimates achieved a mean percent error of 1.92% + 1.54% on the test set. Conclusions: Precise volume estimation of livers from CT scans is accurate using a nnU-Net deep learning architecture. Appropriately deployed, a nnU-Net algorithm is accurate and quick, making it suitable for incorporation into the pretransplant clinical decision-making workflow.

Evaluation of a Novel System for RFID Intraoperative Cardiovascular Analytics.

Objective: To evaluate a novel technology for real time tracking of RF-Identified (RFID) surgical tools (Biotic System), providing intraoperative data analytics during simulated cardiovascular procedures. Ineffective asset management in the Operating Room (OR) leads to inefficient utilization of resources and contributes to prolonged operative times and increased costs. Analysis of captured data can assist in quantifying instrument utilization, procedure flow, performance and prevention of retained instruments. Methods & Results: Five surgeons performed thirteen simulated surgical cases on three human cadavers. Procedures included (i) two abdominal aortic aneurysm (AAA) repairs, (ii) three carotid endarterectomies (CE), (iii) two femoropopliteal (fem-pop) bypasses, (iv) thoracic aortic aneurysm repair, (v) coronary artery bypass graft, (vi) aortic valve replacement, (vii) ascending aortic aneurysm repair, (viii) heart transplants, and (ix) mitral valve replacement. For each case an average of 139 surgical instruments were RFID-tagged and tracked intraoperatively. Data was captured and analyzed retrospectively. Of the 139 instruments tracked across each of the 13 cases, 55 instruments (39.5%) were actually used, demonstrating a high level of redundancy. For repeat cases (i.e. CE/AAA/fem-pop): (i) average instrument usage was 41 ± 3.6 (8.8% variation) for CE (n=3); (ii) average instrument usage was 69 ± 4.0 (5.8% variation) for AAA (n=2); and (iii) average instrument usage was 48 ± 2.5 (5.3% variation) for fem- pop (n=2). Results also showed a reduction in end-of-procedure instrument counting times of 58-87%. Conclusions: We report on a method for collecting intraoperative data analytics regarding instrument usage via RFID technology. This system will help refine instrument selection, quantitate instrument utilization and prevent inadvertent retention in a patient. This should help increase efficiency in packaging and sterilization and let surgeons make objective decisions in the composition of surgical trays. Clinical and Translational Impact Statement-Intraoperative analytics of surgical tools and associated equipment may ultimately lead to safer more efficient surgeries that increase patient outcomes while decreasing the cost of care.

Machine Learning to Predict Outcomes and Cost by Phase of Care After Coronary Artery Bypass Grafting.

BACKGROUND: Machine learning may enhance prediction of outcomes after coronary artery bypass grafting (CABG). We sought to develop and validate a dynamic machine learning model to predict CABG outcomes at clinically relevant pre- and postoperative time points. METHODS: The Society of Thoracic Surgeons (STS) registry data elements from 2086 isolated CABG patients were divided into training and testing datasets and input into Extreme Gradient Boosting decision-tree machine learning algorithms. Two prediction models were developed based on data from preoperative (80 parameters) and postoperative (125 parameters) phases of care. Outcomes included operative mortality, major morbidity or mortality, high cost, and 30-day readmission. Machine learning and STS model performance were assessed using accuracy and the area under the precision-recall curve (AUC-PR). RESULTS: Preoperative machine learning models predicted mortality (accuracy, 98%; AUC-PR = 0.16; F1 = 0.24), major morbidity or mortality (accuracy, 75%; AUC-PR = 0.33; F1 = 0.42), high cost (accuracy, 83%; AUC-PR = 0.51; F1 = 0.52), and 30-day readmission (accuracy, 70%; AUC-PR = 0.47; F1 = 0.49) with high accuracy. Preoperative machine learning models performed similarly to the STS for prediction of mortality (STS AUC-PR = 0.11; P = .409) and outperformed STS for prediction of mortality or major morbidity (STS AUC-PR = 0.28; P < .001). Addition of intraoperative parameters further improved machine learning model performance for major morbidity or mortality (AUC-PR = 0.39; P < .01) and high cost (AUC-PR = 0.64; P < .01), with cross-clamp and bypass times emerging as important additive predictive parameters. CONCLUSIONS: Machine learning can predict mortality, major morbidity, high cost, and readmission after isolated CABG. Prediction based on the phase of care allows for dynamic risk assessment through the hospital course, which may benefit quality assessment and clinical decision-making.

On the Use of Carbon Cables from Plastic Solvent Combinations of Polystyrene and Toluene in Carbon Nanotube Synthesis.

For every three people on the planet, there are approximately two Tonnes (Te) of plastic waste. We show that carbon recovery from polystyrene (PS) plastic is enhanced by the coaddition of solvents to grow carbon nanotubes (CNTs) by liquid injection chemical vapour deposition. Polystyrene was loaded up to 4 wt% in toluene and heated to 780 °C in the presence of a ferrocene catalyst and a hydrogen/argon carrier gas at a 1:19 ratio. High resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Raman spectroscopy were used to identify multiwalled carbon nanotubes (MWCNTs). The PS addition in the range from 0 to 4 wt% showed improved quality and CNT homogeneity; Raman "Graphitic/Defective" (G/D) values increased from 1.9 to 2.3; mean CNT diameters increased from 43.0 to 49.2 nm; and maximum CNT yield increased from 11.37% to 14.31%. Since both the CNT diameters and the percentage yield increased following the addition of polystyrene, we conclude that carbon from PS contributes to the carbon within the MWCNTs. The electrical contact resistance of acid-washed Bucky papers produced from each loading ranged from 2.2 to 4.4 Ohm, with no direct correlation to PS loading. Due to this narrow range, materials with different loadings were mixed to create the six wires of an Ethernet cable and tested using iPerf3; the cable achieved up- and down- link speeds of ~99.5 Mbps, i.e., comparable to Cu wire with the same dimensions (~99.5 Mbps). The lifecycle assessment (LCA) of CNT wire production was compared to copper wire production for a use case in a Boeing 747-400 over the lifespan of the aircraft. Due to their lightweight nature, the CNT wires decreased the CO2 footprint by 21 kTonnes (kTe) over the aircraft's lifespan.

Sensing Temperature in Vitro and in Cells Using a BODIPY Molecular Probe.

Boron dipyrromethene (BODIPY) molecular rotors have shown sensitivity toward viscosity, polarity, and temperature. Here, we report a 1,3,5,7-tetramethyl-8-phenyl-BODIPY modified with a polyethylene glycol (PEG) chain, for temperature sensing and live cell imaging. This new PEG-BODIPY dye presents an increase in nonradiative decay as temperature increases, which directly influences its lifetime. This change in lifetime is dependent on changes in both temperature and viscosity at low viscosity values, but is only dependent on temperature at high viscosity values. The dependence of fluorescence lifetime with temperature allows for temperature monitoring in vitro and in cells, with sub degree resolution. When in contact with cells, the PEG-BODIPY spontaneously penetrates and stains the cell but not the nucleus. Furthermore, no significant cell toxicity was found even at 100 µM concentration. Using fluorescence lifetime imaging microscopy (FLIM), we were able to observe the changes in the lifetime of PEG-BODIPY within the cell at different temperatures. The use of FLIM and molecular probes such as PEG-BODIPY can provide important information about cellular temperature and heat dissipation upon medically relevant stimuli, such as radiofrequency ablation and photodynamic therapy.

Development of photoactive Sweet-C60 for pancreatic cancer stellate cell therapy.

AIM: Glycoconjugated C60 derivatives are of particular interest as potential cancer targeting agents due to an upregulated metabolic glucose demand, especially in the case of pancreatic adenocarcinoma and its dense stroma, which is known to be driven by a subset of pancreatic stellate cells. MATERIALS & METHODS: Herein, we describe the synthesis and biological characterization of a hexakis-glucosamine C60 derivative (termed 'Sweet-C60'). RESULTS: Synthesized fullerene derivative predominantly accumulates in the nucleus of pancreatic stellate cells; is inherently nontoxic up to concentrations of 1 mg/ml; and is photoactive when illuminated with blue and green light, allowing its use as a photodynamic therapy agent. CONCLUSION: Obtained glycoconjugated nanoplatform is a promising nanotherapeutic for pancreatic cancer.

Improved, Shorter-Latency Carcinogen-Induced Hepatocellular Carcinoma Model in Pigs.

Large animal models are important tools for hepatocellular carcinoma (HCC) research, especially in studies of hepatic vasculature, interventional techniques, and radiofrequency or microwave hyperthermia. Currently, diethylnitrosamine (DENA)-induced HCC in pigs is the only large animal model for in situ HCC with a tumor latency of 10-26 months. While phenobarbital (PB) is often used to accelerate DENA-induced HCC in rodents, it has not been previously studied in the porcine model. Therefore, we hypothesize that the addition of PB in the DENA-induced HCC porcine model will accelerate tumor latency compared to DENA alone. HCC and benign lesions were seen on serial MRI and confirmed on histopathology. Liver and tumors were further characterized by CT angiography, vascular corrosion casting, and permittivity measurements.

Ultrasound Doppler as an Imaging Modality for Selection of Murine 4T1 Breast Tumors for Combination Radiofrequency Hyperthermia and Chemotherapy.

Noninvasive radiofrequency-induced (RF) hyperthermia has been shown to increase the perfusion of chemotherapeutics and nanomaterials through cancer tissue in ectopic and orthotopic murine tumor models. Additionally, mild hyperthermia (37°C-45°C) has previously shown a synergistic anticancer effect when used with standard-of-care chemotherapeutics such as gemcitabine and Abraxane. However, RF hyperthermia treatment schedules remain unoptimized, and the mechanisms of action of hyperthermia and how they change when treating various tumor phenotypes are poorly understood. Therefore, pretreatment screening of tumor phenotypes to identify key tumors that are predicted to respond more favorably to hyperthermia will provide useful mechanistic data and may improve therapeutic outcomes. Herein, we identify key biophysical tumor characteristics in order to predict the outcome of combinational RF and chemotherapy treatment. We demonstrate that ultrasound imaging using Doppler mode can be utilized to predict the response of combinational RF and chemotherapeutic therapy in a murine 4T1 breast cancer model.

Chemotherapy and Radiofrequency-Induced Mild Hyperthermia Combined Treatment of Orthotopic Pancreatic Ductal Adenocarcinoma Xenografts.

Patients with pancreatic ductal adenocarcinomas (PDAC) have one of the poorest survival rates of all cancers. The main reason for this is related to the unique tumor stroma and poor vascularization of PDAC. As a consequence, chemotherapeutic drugs, such as nab-paclitaxel and gemcitabine, cannot efficiently penetrate into the tumor tissue. Non-invasive radiofrequency (RF) mild hyperthermia treatment was proposed as a synergistic therapy to enhance drug uptake into the tumor by increasing tumor vascular inflow and perfusion, thus, increasing the effect of chemotherapy. RF-induced hyperthermia is a safer and non-invasive technique of tumor heating compared to conventional contact heating procedures. In this study, we investigated the short- and long-term effects (~20 days and 65 days, respectively) of combination chemotherapy and RF hyperthermia in an orthotopic PDAC model in mice. The benefit of nab-paclitaxel and gemcitabine treatment was confirmed in mice; however, the effect of treatment was statistically insignificant in comparison to saline treated mice during long-term observation. The benefit of RF was minimal in the short-term and completely insignificant during long-term observation.

Non-Invasive Radiofrequency Field Treatment of 4T1 Breast Tumors Induces T-cell Dependent Inflammatory Response.

Previous work using non-invasive radiofrequency field treatment (RFT) in cancer has demonstrated its therapeutic potential as it can increase intratumoral blood perfusion, localization of intravenously delivered drugs, and promote a hyperthermic intratumoral state. Despite the well-known immunologic benefits that febrile hyperthermia can induce, an investigation of how RFT could modulate the intra-tumoral immune microenvironment had not been studied. Thus, using an established 4T1 breast cancer model in immune competent mice, we demonstrate that RFT induces a transient, localized, and T-cell dependent intratumoral inflammatory response. More specifically we show that multi- and singlet-dose RFT promote an increase in tumor volume in immune competent Balb/c mice, which does not occur in athymic nude models. Further leukocyte subset analysis at 24, 48, and 120 hours after a single RFT show a rapid increase in tumoral trafficking of CD4+ and CD8+ T-cells 24 hours post-treatment. Additional serum cytokine analysis reveals an increase in numerous pro-inflammatory cytokines and chemokines associated with enhanced T-cell trafficking. Overall, these data demonstrate that non-invasive RFT could be an effective immunomodulatory strategy in solid tumors, especially for enhancing the tumoral trafficking of lymphocytes, which is currently a major hindrance of numerous cancer immunotherapeutic strategies.

A new mild hyperthermia device to treat vascular involvement in cancer surgery.

Surgical margin status in cancer surgery represents an important oncologic parameter affecting overall prognosis. The risk of disease recurrence is minimized and survival often prolonged if margin-negative resection can be accomplished during cancer surgery. Unfortunately, negative margins are not always surgically achievable due to tumor invasion into adjacent tissues or involvement of critical vasculature. Herein, we present a novel intra-operative device created to facilitate a uniform and mild heating profile to cause hyperthermic destruction of vessel-encasing tumors while safeguarding the encased vessel. We use pancreatic ductal adenocarcinoma as an in vitro and an in vivo cancer model for these studies as it is a representative model of a tumor that commonly involves major mesenteric vessels. In vitro data suggests that mild hyperthermia (41-46 °C for ten minutes) is an optimal thermal dose to induce high levels of cancer cell death, alter cancer cell's proteomic profiles and eliminate cancer stem cells while preserving non-malignant cells. In vivo and in silico data supports the well-known phenomena of a vascular heat sink effect that causes high temperature differentials through tissues undergoing hyperthermia, however temperatures can be predicted and used as a tool for the surgeon to adjust thermal doses delivered for various tumor margins.

Pancreatic adenocarcinoma response to chemotherapy enhanced with non-invasive radio frequency evaluated via an integrated experimental/computational approach.

Although chemotherapy combined with radiofrequency exposure has shown promise in cancer treatment by coupling drug cytotoxicity with thermal ablation or thermally-induced cytotoxicity, limited access of the drug to tumor loci in hypo-vascularized lesions has hampered clinical application. We recently showed that high-intensity short-wave capacitively coupled radiofrequency (RF) electric-fields may reach inaccessible targets in vivo. This non-invasive RF combined with gemcitabine (Gem) chemotherapy enhanced drug uptake and effect in pancreatic adenocarcinoma (PDAC), notorious for having poor response and limited therapeutic options, but without inducing thermal injury. We hypothesize that the enhanced cytotoxicity derives from RF-facilitated drug transport in the tumor microenvironment. We propose an integrated experimental/computational approach to evaluate chemotherapeutic response combined with RF-induced phenotypic changes in tissue with impaired transport. Results show that RF facilitates diffusive transport in 3D cell cultures representing hypo-vascularized lesions, enhancing drug uptake and effect. Computational modeling evaluates drug vascular extravasation and diffusive transport as key RF-modulated parameters, with transport being dominant. Assessment of hypothetical schedules following current clinical protocol for Stage-IV PDAC suggests that unresponsive lesions may be growth-restrained when exposed to Gem plus RF. Comparison of these projections to experiments in vivo indicates that synergy may result from RF-induced cell phenotypic changes enhancing drug transport and cytotoxicity, thus providing a potential baseline for clinically-focused evaluation.

Non-Invasive Radiofrequency Field Treatment to Produce Hepatic Hyperthermia: Efficacy and Safety in Swine.

The Kanzius non-invasive radio-frequency hyperthermia system (KNiRFH) has been investigated as a treatment option for hepatic hyperthermia cancer therapy. The treatment involves exposing the patient to an external high-power RF (13.56 MHz) electric field, whereby the propagating waves penetrate deep into the tumor causing targeted heating based on differential tissue dielectric properties. However, a comprehensive examination of the Kanzius system alongside any associated toxicities and its ability to induce hepatic hyperthermia in larger animal models, such as swine, are the subjects of the work herein. Ten Yucatan female mini-swine were treated with the KNiRFH system. Two of the pigs were treated a total of 17 times over a five-week period to evaluate short- and long-term KNiRFH-associated toxicities. The remaining eight pigs were subjected to single exposure sessions to evaluate heating efficacy in liver tissue. Our goal was to achieve a liver target temperature of 43°C and to evaluate toxicities and burns post-treatment. Potential toxicities were evaluated by contrast-enhanced MRI of the upper abdomen and blood work, including complete metabolic panel, complete blood count, and liver enzymes. The permittivities of subcutaneous fat and liver were also measured, which were used to calculate tissue specific absorption rates (SAR). Our results indicate negligible KNiRFH-associated toxicities; however, due to fat overheating, liver tissue temperature did not exceed 38.5°C. This experimental limitation was corroborated by tissue permittivity and SAR calculations of subcutaneous fat and liver. Significant steps must be taken to either reduce subcutaneous fat heating or increase localized heating, potentially through the use of KNiRFH-active nanomaterials, such as gold nanoparticles or single-walled carbon nanotubes, which have previously shown promising results in murine cancer models.

The effects of non-invasive radiofrequency electric field hyperthermia on biotransport and biodistribution of fluorescent [60]fullerene derivative in a murine orthotopic model of breast adenocarcinoma.

The aim of this study is to understand the combined and differential biokinetic effects of radiofrequency (RF) electric-field hyperthermia as an adjunctive therapy to [60]fullerene nanoparticle-based drug delivery systems in targeting the micro-vasculature and micro-environments of breast cancer tumors. Intravital microscopy (IVM) is an ideal tool to provide the spatial and temporal resolution needed for quantification in this investigation. The water-soluble and fluorescent [60]fullerene derivative (C60-serPF) was designed to be an amphiphilic nanostructure, which is able to cross several biological membranes and accumulate in tumor tissues by passing through abnormally leaky tumor blood vessels. To elucidate the coupled effects of the highly permeable, but heterogeneous tumor vasculature, with the permeabilizing effects of mild (40-42°C) hyperthermia produced by a local RF field, we controlled variables across tumor and non-tumor mammary gland microvasculature with and without application of RF hyperthermia in each condition. We notice that tumor tissue is characterized by more intense drug extravasation than in contralateral mammary fat pad tissue, which is consistent with enhanced permeability and retention (EPR) effects. The analysis of a permeability parameter (Papp), C60-serPF velocity, and the time of compound influx into the intra- and extra-vascular space suggest that mild RF hyperthermia can improve nanoparticle delivery into tumor tissue.