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

Construction Strategy of Functionalized Liposomes and Multidimensional Application

Liposomes are widely used in the biological field due to their good biocompatibility and surface modification properties. With the development of biochemistry and material science, many liposome structures and their surface functional components have been modified and optimized one by one, pushing the liposome platform from traditional to functionalized and intelligent, which will better satisfy and expand the needs of scientific research. However, a main limiting factor effecting the efficiency of liposomes is the complicated environmental conditions in the living body. Currently, in order to overcome the above problem, functionalized liposomes have become a very promising strategy. In this paper, binding strategies of liposomes with four main functional elements, namely nucleic acids, antibodies, peptides, and stimuli-responsive motif have been summarized for the first time. In addition, based on the construction characteristics of functionalized liposomes, such as drug-carrying, targeting, long-circulating, and stimulus-responsive properties, a comprehensive overview of their features and respective research progress are presented. Finally, the paper critically presents the limitations of these functionalized liposomes in the current applications and also prospectively suggests the future development directions, aiming to accelerate realization of their industrialization.

A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model

Active surveillance (AS) is a suitable management option for newly diagnosed prostate cancer, which usually presents low to intermediate clinical risk. Patients enrolled in AS have their tumor monitored via longitudinal multiparametric MRI (mpMRI), PSA tests, and biopsies. Hence, treatment is prescribed when these tests identify progression to higher-risk prostate cancer. However, current AS protocols rely on detecting tumor progression through direct observation according to population-based monitoring strategies. This approach limits the design of patient-specific AS plans and may delay the detection of tumor progression. Here, we present a pilot study to address these issues by leveraging personalized computational predictions of prostate cancer growth. Our forecasts are obtained with a spatiotemporal biomechanistic model informed by patient-specific longitudinal mpMRI data (T2-weighted MRI and apparent diffusion coefficient maps from diffusion-weighted MRI). Our results show that our technology can represent and forecast the global tumor burden for individual patients, achieving concordance correlation coefficients from 0.93 to 0.99 across our cohort (n = 7). In addition, we identify a model-based biomarker of higher-risk prostate cancer: the mean proliferation activity of the tumor (P = 0.041). Using logistic regression, we construct a prostate cancer risk classifier based on this biomarker that achieves an area under the ROC curve of 0.83. We further show that coupling our tumor forecasts with this prostate cancer risk classifier enables the early identification of prostate cancer progression to higher-risk disease by more than 1 year. Thus, we posit that our predictive technology constitutes a promising clinical decision-making tool to design personalized AS plans for patients with prostate cancer.

SIGNIFICANCE

Personalization of a biomechanistic model of prostate cancer with mpMRI data enables the prediction of tumor progression, thereby showing promise to guide clinical decision-making during AS for each individual patient.

Development of a Treatment Planning Framework for Laser Interstitial Thermal Therapy (LITT)

PURPOSE

Develop a treatment planning framework for neurosurgeons treating high-grade gliomas with LITT to minimize the learning curve and improve tumor thermal dose coverage.

METHODS

Deidentified patient images were segmented using the image segmentation software Materialize MIMICS©. Segmented images were imported into the commercial finite element analysis (FEA) software COMSOL Multiphysics© to perform bioheat transfer simulations. The laser probe was modeled as a cylindrical object with radius 0.7 mm and length 100 mm, with a constant beam diameter. A modeled laser probe was placed in the tumor in accordance with patient specific patient magnetic resonance temperature imaging (MRTi) data. The laser energy was modeled as a deposited beam heat source in the FEA software. Penne's bioheat equation was used to model heat transfer in brain tissue. The cerebrospinal fluid (CSF) was modeled as a solid with convectively enhanced conductivity to capture heat sink effects. In this study, thermal damage-dependent blood perfusion was assessed. Pulsed laser heating was modeled based on patient treatment logs. The stationary heat source and pullback heat source techniques were modeled to compare the calculated tissue damage. The developed bioheat transfer model was compared to MRTi data obtained from a laser log during LITT procedures. The application builder module in COMSOL Multiphysics© was utilized to create a Graphical User Interface (GUI) for the treatment planning framework.

RESULTS

Simulations predicted increased thermal damage (10-15%) in the tumor for the pullback heat source approach compared with the stationary heat source. The model-predicted temperature profiles followed trends similar to those of the MRTi data. Simulations predicted partial tissue ablation in tumors proximal to the CSF ventricle.

CONCLUSION

A mobile platform-based GUI for bioheat transfer simulation was developed to aid neurosurgeons in conveniently varying the simulation parameters according to a patient-specific treatment plan. The convective effects of the CSF should be modeled with heat sink effects for accurate LITT treatment planning.

Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning

Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser ablation (LA) is one of the least invasive approaches, especially for tumors in high-risk locations. Precise control of the LA effect is required to safely destroy the tumor. Although temperature imaging techniques provide an indirect measurement of the thermal damage, a degree of uncertainty remains about the treatment effect. Optical techniques are currently emerging as tools to directly assess tissue thermal damage. Among them, hyperspectral imaging (HSI) has shown promising results in image-guided surgery and in the thermal ablation field. The highly informative data provided by HSI, associated with deep learning, enable the implementation of non-invasive prediction models to be used intraoperatively. Here we show a novel paradigm “peak temperature prediction model” (PTPM), convolutional neural network (CNN)-based, trained with HSI and infrared imaging to predict LA-induced damage in the liver. The PTPM demonstrated an optimal agreement with tissue damage classification providing a consistent threshold (50.6 ± 1.5 °C) for the damage margins with high accuracy (~0.90). The high correlation with the histology score (r = 0.9085) and the comparison with the measured peak temperature confirmed that PTPM preserves temperature information accordingly with the histopathological assessment.

Predictive modeling of brain tumor laser ablation dynamics

INTRODUCTION

Laser interstitial thermal therapy (LITT) is a novel MR thermometry-guided thermoablative tool revolutionizing the clinical management of brain tumors. A limitation of LITT is our inability to estimate a priori how tissues will respond to thermal energy, which hinders treatment planning and delivery. The aim of this study was to determine whether brain tumor LITT ablation dynamics may be predicted by features of the preoperative MRI and the relevance of these data, if any, to the recurrence of metastases after LITT.

METHODS

Intraoperative thermal damage estimate (TDE) map pixels representative of irreversible damage were retrospectively quantified relative to ablation onset for 101 LITT procedures. Raw TDE pixel counts and TDE pixel counts modelled with first order dynamics were related to eleven independent variables derived from the preoperative MRI, demographics, laser settings, and tumor pathology. Stepwise regression analysis generated predictive models of LITT dynamics, and leave-one-out cross validation evaluated the accuracy of these models at predicting TDE pixel counts solely from the independent variables. Using a deformable atlas, TDE maps were co-registered to the immediate post-ablation MRI, allowing comparison of predicted and actual ablation sizes.

RESULTS

Brain tumor TDE pixel counts modelled with first order dynamics, but not raw pixel counts, are correlated with the independent variables. Independent variables showing strong relations to the TDE pixel measures include T1 gadolinium and T2 signal, perfusion, and laser power. Associations with tissue histopathology are minimal. Leave-one-out analysis demonstrates that predictive models using these independent variables account for 77% of the variance observed in TDE pixel counts. Analysis of metastases treated revealed a trend towards the over-estimation of LITT effects by TDE maps during rapid ablations, which was associated with tumor recurrence.

CONCLUSIONS

Features of the preoperative MRI are predictive of LITT ablation dynamics and could eventually be used to improve the clinical efficacy with which LITT is delivered to brain tumors.

Moxibustion-Simulating Bipolar Radiofrequency Suppresses Weight Gain and Induces Adipose Tissue Browning via Activation of UCP1 and FGF21 in a Mouse Model of Diet-Induced Obesity

Background

Obesity is a pathological condition associated with various diseases including diabetes, stroke, arthritis, infertility, and heart disease. Moxibustion is widely used to prevent and manage obesity in traditional Asian medicine. We tested our hypothesis that moxibustion-simulating bipolar radiofrequency (M-RF) can suppress total body and white adipose tissue (WAT) weight gain via induction of WAT browning in a mouse model of diet-induced obesity (DIO).

Methods

We designed an M-RF device that could accurately adjust the depth and temperature at which heat stimulation was administered into the abdomen of DIO mice. High-fat-fed male C57BL/6 mice were treated with the M-RF device every two or three days for three weeks. We then harvested WAT and serum from the mice and measured total body and WAT weight, size of adipocytes, mitochondrial contents, features of the dead adipocyte environment, and levels of uncoupling protein 1 (UCP1) and fibroblast growth factor 21 (FGF21).

Results

Heat stimulation by M-RF in DIO mice resulted in precise temperature adjustment in the mice abdomen, with variance less than 1°C. Additionally, M-RF stimulation inhibited body and WAT weight gain, resulting in increased formation of beige adipocytes, increased mitochondrial content, and decreased formation of dead adipocytes in WAT. Moreover, treatment of M-RF induced expression of UCP1 and FGF21 in serum and/or epididymal WATs in DIO mice.

Conclusion

Heat stimulation by M-RF treatment induced upregulation of UCP1 and FGF21 expression in serum and/or WATs, which was correlated with reduced total body and WAT weight gain in DIO mice.

Stimulus-responsive liposomes as smart nanoplatforms for drug delivery applications

Liposomes are known to be promising nanoparticles (NPs) for drug delivery applications. Among different types of self-assembled NPs, liposomes stand out for their non-toxic nature, and their possession of dual hydrophilic-hydrophobic domains. Advantages of liposomes include the ability to solubilize hydrophobic drugs, the ability to incorporate different hydrophilic and lipophilic drugs at the same time, lessening the exposure of host organs to potentially toxic drugs and allowing modification of the surface by a variety of different chemical groups. This modification of the surface, or of the individual constituents, may be used to achieve two important goals. Firstly, ligands for active targeting can be attached that are recognized by cognate receptors over-expressed on the target cells of tissues. Secondly, modification can be used to impart a stimulus-responsive or "smart" character to the liposomes, whereby the cargo is released on demand only when certain internal stimuli (pH, reducing agents, specific enzymes) or external stimuli (light, magnetic field or ultrasound) are present. Here, we review the field of smart liposomes for drug delivery applications.

Temperature feedback-controlled photothermal treatment with diffusing applicator: theoretical and experimental evaluations

To minimize thermal injury, the current study evaluated the real-time temperature monitoring with a proportional-integrative-derivative (PID) controller during 980-nm photothermal treatment with a radially-diffusing applicator. Both simulations and experiments demonstrated comparable thermal behaviors in temperature distribution and the degree of irreversible tissue denaturation. The PID-controlled application constantly maintained the pre-determined temperature of 353 K (steady-state error = < 1 K). Due to constant energy delivery, coagulation volumes linearly increased up to 1.04 ± 0.02 cm(3) with irradiation time. Integration of temperature feedback with diffuser-assisted photothermal treatments can provide a feasible therapeutic modality to treat pancreatic tumors in an effective manner.

Comprehensive analytical model for CW laser induced heat in turbid media

In this work, we present a new analytical approach to model continuous wave laser induced temperature in highly homogeneous turbid media. First, the diffusion equation is used to model light transport and a comprehensive solution is derived analytically by obtaining a special Greens' function. Next, the time-dependent bio-heat equation is used to describe the induced heat increase and propagation within the medium. The bio-heat equation is solved analytically utilizing the separation of variables technique. Our theoretical model is successfully validated using numerical simulations and experimental studies with agarose phantoms and ex-vivo chicken breast samples. The encouraging results show that our method can be implemented as a simulation tool to determine important laser parameters that govern the magnitude of temperature rise within homogenous biological tissue or organs.

Model development and experimental validation for analyzing initial transients of irradiation of tissues during thermal therapy using short pulse lasers

BACKGROUND AND OBJECTIVES

Short pulse lasers with pulse durations in the range of nanoseconds and shorter are effective in the targeted delivery of heat energy for precise tissue heating and ablation. This photothermal therapy is useful where the removal of cancerous tissue sections is required. The objective of this paper is to use finite element modeling to demonstrate the differences in the thermal response of skin tissue to short-pulse and continuous wave laser irradiation in the initial stages of the irradiation. Models have been developed to validate the temperature distribution and heat affected zone during laser irradiation of excised rat skin samples and live anesthetized mouse tissue.

STUDY DESIGN/MATERIALS AND METHODS

Excised rat skin samples and live anesthetized mice were subjected to Nd:YAG pulsed laser (1,064 nm, 500 ns) irradiation of varying powers. A thermal camera was used to measure the rise in surface temperature as a result of the laser irradiation. Histological analyses of the heat affected zone created in the tissue samples due to the temperature rise were performed. The thermal interaction of the laser with the tissue was quantified by measuring the thermal dose delivered by the laser. Finite element geometries of three-dimensional tissue sections for continuum and vascular models were developed using COMSOL Multiphysics. Blood flow was incorporated into the vascular model to mimic the presence of discrete blood vessels and contrasted with the continuum model without blood perfusion.

RESULTS

The temperature rises predicted by the continuum and the vascular models agreed with the temperature rises observed at the surface of the excised rat tissue samples and live anesthetized mice due to laser irradiation respectively. The vascular model developed was able to predict the cooling produced by the blood vessels in the region where the vessels were present. The temperature rise in the continuum model due to pulsed laser irradiation was higher than that due to continuous wave (CW) laser irradiation in the initial stages of the irradiation. The temperature rise due to pulsed and CW laser irradiation converged as the time of irradiation increased. A similar trend was observed when comparing the thermal dose for pulsed and CW laser irradiation in the vascular model.

CONCLUSION

Finite element models (continuum and vascular) were developed that can be used to predict temperature rise and quantify the thermal dose resulting from laser irradiation of excised rat skin samples and live anesthetized mouse tissue. The vascular model incorporating blood perfusion effects predicted temperature rise better in the live animal tissue. The models developed demonstrated that pulsed lasers caused greater temperature rise and delivered a greater thermal dose than CW lasers of equal average power, especially during the initial transients of irradiation. This analysis will be beneficial for thermal therapy applications where maximum delivery of thermal dose over a short period of time is important.

Interstitial ultrasound ablation of vertebral and paraspinal tumours: parametric and patient-specific simulations

PURPOSE

Theoretical parametric and patient-specific models are applied to assess the feasibility of interstitial ultrasound ablation of tumours in and near the spine and to identify potential treatment delivery strategies.

METHODS

3D patient-specific finite element models (n = 11) of interstitial ultrasound ablation of tumours associated with the spine were generated. Gaseous nerve insulation and various applicator configurations, frequencies (3 and 7 MHz), placement trajectories, and tumour locations were simulated. Parametric studies with multilayered models investigated the impacts of tumour attenuation, tumour dimension, and the thickness of bone insulating critical structures. Temperature and thermal dose were calculated to define ablation (>240 equivalent minutes at 43 °C (EM43 °C)) and safety margins (<45 °C and <6 EM43 °C), and to determine performance and required delivery parameters.

RESULTS

Osteolytic tumours (≤44 mm) encapsulated by bone could be successfully ablated with 7 MHz interstitial ultrasound (8.1-16.6 W/cm(2), 120-5900 J, 0.4-15 min). Ablation of tumours (94.6-100% volumetric) 0-14.5 mm from the spinal canal was achieved within 3-15 min without damaging critical nerves. 3 MHz devices provided faster ablation (390 versus 930 s) of an 18 mm diameter osteoblastic (high bone content) volume than 7 MHz devices. Critical anatomy in proximity to the tumour could be protected by selection of appropriate applicator configurations, active sectors, and applied power schemas, and through gaseous insulation. Preferential ultrasound absorption at bone surfaces facilitated faster, more effective ablations in osteolytic tumours and provided isolation of ablative energies and temperatures.

CONCLUSIONS

Parametric and patient-specific studies demonstrated the feasibility and potential advantages of interstitial ultrasound ablation treatment of paraspinal and osteolytic vertebral tumours.

Trigger responsive polymeric nanocarriers for cancer therapy

Conventional chemotherapy for the treatment of cancer has limited specificity when administered systemically and is often associated with toxicity issues. Enhanced accumulation of polymeric nanocarriers at a tumor site may be achieved by passive and active targeting. Incorporation of trigger responsiveness into these polymeric nanocarriers improves the anticancer efficacy of such systems by modulating the release of the drug according to the tumor environment. Triggers used for tumor targeting include internal triggers such as pH, redox and enzymes and external triggers such as temperature, magnetic field, ultrasound and light. While internal triggers are specific cues of the tumor microenvironment, external triggers are those which are applied externally to control the release. This review highlights the various strategies employed for the preparation of such trigger responsive polymeric nanocarriers for cancer therapy and provides an overview of the state of the art in this field.

Influence of hyperthermia on efficacy and uptake of carbon nanohorn-cisplatin conjugates

Single-walled carbon nanohorns (SWNHs) have significant potential for use in photothermal therapies due to their capability to absorb near infrared light and deposit heat. Additionally, their extensive relative surface area and volume makes them ideal drug delivery vehicles. Novel multimodal treatments are envisioned in which laser excitation can be utilized in combination with chemotherapeutic-SWNH conjugates to thermally enhance the therapeutic efficacy of the transported drug. Although mild hyperthermia (41-43 °C) has been shown to increase cellular uptake of drugs such as cisplatin (CDDP) leading to thermal enhancement, studies on the effects of hyperthermia on cisplatin loaded nanoparticles are currently limited. After using a carbodiimide chemical reaction to attach CDDP to the exterior surface of SWNHs and nitric acid to incorporate CDDP in the interior volume, we determined the effects of mild hyperthermia on the efficacy of the CDDP-SWNH conjugates. Rat bladder transitional carcinoma cells were exposed to free CDDP or one of two CDDP-SWNH conjugates in vitro at 37 °C and 42 °C with the half maximal inhibitory concentration (IC50) for each treatment. The in vitro results demonstrate that unlike free CDDP, CDDP-SWNH conjugates do not exhibit thermal enhancement at 42 °C. An increase in viability of 16% and 7% was measured when cells were exposed at 42 deg compared to 37 deg for the surface attached and volume loaded CDDP-SWNH conjugates, respectively. Flow cytometry and confocal microscopy showed a decreased uptake of CDDP-SWNH conjugates at 42 °C compared to 37 °C, revealing the importance of nanoparticle uptake on the CDDP-SWNH conjugate's efficacy, particularly when hyperthermia is used as an adjuvant, and demonstrates the effect of particle size on uptake during mild hyperthermia. The uptake and drug release studies elucidated the difference in viability seen in the drug efficacy studies at different temperatures. We speculate that the disparity in thermal enhancement efficacy observed for free drug compared to the drug SWNH conjugates is due to their intrinsic size differences and, therefore, their mode of cellular uptake: diffusion or endocytosis. These experiments indicate the importance of tuning properties of nanoparticle-drug conjugates to maximize cellular uptake to ensure thermal enhancement in nanoparticle mediated photothermal-chemotherapy treatments.

Comparative analysis of mathematical models of cell death and thermal damage processes

The standard method for assessing hyperthermia treatment has been calculation of cumulative equivalent minutes at 43 °C, CEM43 and its variations. This parameter normalises treatment thermal histories rather than predicts treatment results. Arrhenius models have been widely used in analysing higher temperature thermal treatments and successfully employed to predict irreversible thermal alterations in structural proteins. Unfortunately, in many, but not all cases they fail to represent thermally induced damage or cell death at hyperthermic temperatures, 43-50 °C, exhibiting significant over-prediction of the initial 'shoulder' region. The failure arises from the simplifying assumptions used to derive the irreversible reaction format that has been used in thermal damage studies. Several successful multi-parameter fit methods have been employed to model cell survival data. The two-state statistical thermodynamic model was derived from basic thermodynamic principles. The three-state model results from relaxing the assumptions under the Arrhenius formulation that result in an irreversible reaction. In other cell processes studied in vitro the irreversible Arrhenius model holds, and is sufficient to provide an accurate and useful estimate of thermal damage and cell death. It is essential in numerical model work to include multiple thermal damage processes operating in parallel to obtain a clear image of the likely outcome in tissues. Arrhenius and other C(t) models have that capability, while a single value for CEM43, does not.

Estimating nanoparticle optical absorption with magnetic resonance temperature imaging and bioheat transfer simulation

PURPOSE

Optically activated nanoparticle-mediated heating for thermal therapy applications is an area of intense research. The ability to characterise the spatio-temporal heating potential of these particles for use in modelling under various exposure conditions can aid in the exploration of new approaches for therapy as well as more quantitative prospective approaches to treatment planning. The purpose of this research was to investigate an inverse solution to the heat equation using magnetic resonance temperature imaging (MRTI) feedback, for providing optical characterisation of two types of nanoparticles (gold-silica nanoshells and gold nanorods).

METHODS

The optical absorption of homogeneous nanoparticle-agar mixtures was measured during exposure to an 808 nm laser using real-time MRTI. A coupled finite element solution of heat transfer was registered with the data and used to solve the inverse problem. The L2 norm of the difference between the temperature increase in the model and MRTI was minimised using a pattern search algorithm by varying the absorption coefficient of the mixture.

RESULTS

Absorption fractions were within 10% of literature values for similar nanoparticles. Comparison of temporal and spatial profiles demonstrated good qualitative agreement between the model and the MRTI. The weighted root mean square error was <1.5 σMRTI and the average Dice similarity coefficient for ΔT = 5 °C isotherms was >0.9 over the measured time interval.

CONCLUSION

This research demonstrates the feasibility of using an indirect method for making minimally invasive estimates of nanoparticle absorption that might be expanded to analyse a variety of geometries and particles of interest.

Techniques for temperature monitoring during laser-induced thermotherapy: an overview

Laser-induced thermotherapy (LITT) is a hyperthermic procedure recently employed to treat cancer in several organs. The amount of coagulated tissue depends on the temperature distribution around the applicator, which plays a crucial role for an optimal outcome: the removal of the whole neoplastic tissue, whilst preventing damage to the surrounding healthy tissue. Although feedback concerning tissue temperature could be useful to drive the physician in the adjustment of laser settings and treatment duration, LITT is usually performed without real-time monitoring of tissue temperature. During recent decades, many thermometric techniques have been developed to be used during thermal therapies. This paper provides an overview of techniques and sensors employed for temperature measurement during tissue hyperthermia, focusing on LITT, and an investigation of their performances in this application. The paper focuses on the most promising and widespread temperature monitoring techniques, splitting them into two groups: the former includes invasive techniques based on the use of thermocouples and fibre-optic sensors; the second analyses non-invasive methods, i.e. magnetic resonance imaging-, computerised tomography- and ultrasound-based thermometry. Background information on measuring principle, medical applications, advantages and weaknesses of each method are provided and discussed.

Generalised polynomial chaos-based uncertainty quantification for planning MRgLITT procedures

PURPOSE

A generalised polynomial chaos (gPC) method is used to incorporate constitutive parameter uncertainties within the Pennes representation of bioheat transfer phenomena. The stochastic temperature predictions of the mathematical model are critically evaluated against MR thermometry data for planning MR-guided laser-induced thermal therapies (MRgLITT).

METHODS

The Pennes bioheat transfer model coupled with a diffusion theory approximation of laser tissue interaction was implemented as the underlying deterministic kernel. A probabilistic sensitivity study was used to identify parameters that provide the most variance in temperature output. Confidence intervals of the temperature predictions are compared to MR temperature imaging (MRTI) obtained during phantom and in vivo canine (n = 4) MRgLITT experiments. The gPC predictions were quantitatively compared to MRTI data using probabilistic linear and temporal profiles as well as 2-D 60 °C isotherms.

RESULTS

Optical parameters provided the highest variance in the model output (peak standard deviation: anisotropy 3.51 °C, absorption 2.94 °C, scattering 1.84 °C, conductivity 1.43 °C, and perfusion 0.94 °C). Further, within the statistical sense considered, a non-linear model of the temperature and damage-dependent perfusion, absorption, and scattering is captured within the confidence intervals of the linear gPC method. Multivariate stochastic model predictions using parameters with the dominant sensitivities show good agreement with experimental MRTI data.

CONCLUSIONS

Given parameter uncertainties and mathematical modelling approximations of the Pennes bioheat model, the statistical framework demonstrates conservative estimates of the therapeutic heating and has potential for use as a computational prediction tool for thermal therapy planning.