Modelling heating of liver tumours with heterogeneous magnetic microsphere deposition

First validation of a model-based hepatic percutaneous microwave ablation planning on a clinical dataset

A model-based planning tool, integrated in an imaging system, is envisioned for CT-guided percutaneous microwave ablation. This study aims to evaluate the biophysical model performance, by comparing its prediction retrospectively with the actual ablation ground truth from a clinical dataset in liver. The biophysical model uses a simplified formulation of heat deposition on the applicator and a heat sink related to vasculature to solve the bioheat equation. A performance metric is defined to assess how the planned ablation overlaps the actual ground truth. Results demonstrate superiority of this model prediction compared to manufacturer tabulated data and a significant influence of the vasculature cooling effect. Nevertheless, vasculature shortage due to branches occlusion and applicator misalignment due to registration error between scans affects the thermal prediction. With a more accurate vasculature segmentation, occlusion risk can be estimated, whereas branches can be used as liver landmarks to improve the registration accuracy. Overall, this study emphasizes the benefit of a model-based thermal ablation solution in better planning the ablation procedures. Contrast and registration protocols must be adapted to facilitate its integration into the clinical workflow.

Effective models of microwave antennae for ablation treatment planning

The level of detail of typical numerical models of microwave tumor ablations poses a challenge to the development of generic, model based treatment planning tools aiming at real time performance. The present contribution describes a flexible and accurate approximation of the microwave heat absorption that aims at mitigating these issues.

Correlation and Agreement of Yttrium-90 Positron Emission Tomography/Computed Tomography with Ex Vivo Radioembolization Microsphere Deposition in the Rabbit VX2 Liver Tumor Model

PURPOSE

To demonstrate a stronger correlation and agreement of yttrium-90 (⁹⁰Y) positron emission tomography (PET)/computed tomography (CT) measurements with explant liver tumor dosing compared with the standard model (SM) for radioembolization.

MATERIALS AND METHODS

Hepatic VX2 tumors were implanted into New Zealand white rabbits, with growth confirmed by 7 T magnetic resonance imaging. Seventeen VX2 rabbits provided 33 analyzed tumors. Treatment volumes were calculated from manually drawn volumes of interest (VOI) with three-dimensional surface renderings. Radioembolization was performed with glass ⁹⁰Y microspheres. PET/CT imaging was completed with scatter and attenuation correction. Three-dimensional ellipsoid VOI were drawn to encompass tumors on fused images. Tumors and livers were then explanted for inductively coupled plasma (ICP)-optical emission spectroscopy (OES) analysis of microsphere content. ⁹⁰Y PET/CT and SM measurements were compared with reference standard ICP-OES measurements of tumor dosing with Pearson correlation and Bland-Altman analyses for agreement testing with and without adjustment for tumor necrosis.

RESULTS

The median infused activity was 33.3 MBq (range, 5.9-152.9). Tumor dose was significantly correlated with ⁹⁰Y PET/CT measurements (r = 0.903, P < .001) and SM estimates (r = 0.607, P < .001). Bland-Altman analyses showed that the SM tended to underestimate the tumor dosing by a mean of -8.5 Gy (CI, -26.3-9.3), and the degree of underestimation increased to a mean of -18.3 Gy (CI, -38.5-1.9) after the adjustment for tumor necrosis.

CONCLUSIONS

⁹⁰Y PET/CT estimates were strongly correlated and had better agreement with reference measurements of tumor dosing than SM estimates.

Nanoparticle transport phenomena in confined flows

Nanoparticles submerged in confined flow fields occur in several technological applications involving heat and mass transfer in nanoscale systems. Describing the transport with nanoparticles in confined flows poses additional challenges due to the coupling between the thermal effects and fluid forces. Here, we focus on the relevant literature related to Brownian motion, hydrodynamic interactions and transport associated with nanoparticles in confined flows. We review the literature on the several techniques that are based on the principles of non-equilibrium statistical mechanics and computational fluid dynamics in order to simultaneously preserve the fluctuation-dissipation relationship and the prevailing hydrodynamic correlations. Through a review of select examples, we discuss the treatments of the temporal dynamics from the colloidal scales to the molecular scales pertaining to nanoscale fluid dynamics and heat transfer. As evident from this review, there, indeed has been little progress made in regard to the accurate modeling of heat transport in nanofluids flowing in confined geometries such as tubes. Therefore the associated mechanisms with such processes remain unexplained. This review has revealed that the information available in open literature on the transport properties of nanofluids is often contradictory and confusing. It has been very difficult to draw definitive conclusions. The quality of work reported on this topic is non-uniform. A significant portion of this review pertains to the treatment of the fluid dynamic aspects of the nanoparticle transport problem. By simultaneously treating the energy transport in ways discussed in this review as related to momentum transport, the ultimate goal of understanding nanoscale heat transport in confined flows may be achieved.

Computational reasoning across multiple models

Computational support of clinical decisions frequently requires the integration of data in a variety of formats and from multiple sources and domains. Some impressive multiscale computational models of biological phenomena have been developed as part of the study of disease and healthcare systems. One can now contemplate harnessing these models arising from computational biology and using highly interconnected clinical data to support clinical decision-making. Indeed, understanding how to build computational systems able to reason across heterogeneous models and datasets is one of the major and perhaps foundational challenges of translational biomedical informatics. In this paper, the authors examine the use of multimodels (models composed of several daughter models) and explore three major research challenges to reasoning across multiple models: model selection, model composition, and computer aided model construction.

In vitro heat generation by ferrimagnetic maghemite microspheres for hyperthermic treatment of cancer under an alternating magnetic field

Ferrimagnetic materials can be expected to be useful as thermo seeds for hyperthermic treatment of cancer, especially where the cancer is located in deep parts of body, as they can generate heat by magnetic hysteretic loss when they are placed in an alternating magnetic field. Recently, it was reported that ferrimagnetic maghemite (gamma-Fe2O3) microspheres 20-30 microm in diameter prepared in aqueous solution can show excellent heat generating ability. However, these microspheres have many cracks on their surfaces. In this study, the preparation conditions for the microspheres was further optimized in order to obtain crack-free ferrimagnetic microspheres, and the in vitro heat generation of the obtained microspheres was measured in an agar phantom under an alternating magnetic field. Crack-free gamma-Fe2O3 microspheres 20-30 microm in diameter were obtained successfully. Their saturation magnetization and coercive force were 68 emu g(-1) and 198 Oe, respectively. Their heat generation under an alternating magnetic field of 300 Oe at 100 kHz was estimated to be 42 W g(-1). The microspheres showed in vitro heat generation when they were dispersed in an agar phantom and placed under an alternating magnetic field. It is believed that these microspheres may be useful for the in situ hyperthermic treatment of cancer.

The field representation language

The complexity of quantitative biomedical models, and the rate at which they are published, is increasing to a point where managing the information has become all but impossible without automation. International efforts are underway to standardise representation languages for a number of mathematical entities that represent a wide variety of physiological systems. This paper presents the Field Representation Language (FRL), a portable representation of values that change over space and/or time. FRL is an extensible mark-up language (XML) derivative with support for large numeric data sets in Hierarchical Data Format version 5 (HDF5). Components of FRL can be reused through unified resource identifiers (URI) that point to external resources such as custom basis functions, boundary geometries and numerical data. To demonstrate the use of FRL as an interchange we present three models that study hyperthermia cancer treatment: a fractal model of liver tumour microvasculature; a probabilistic model simulating the deposition of magnetic microspheres throughout it; and a finite element model of hyperthermic treatment. The microsphere distribution field was used to compute the heat generation rate field around the tumour. We used FRL to convey results from the microsphere simulation to the treatment model. FRL facilitated the conversion of the coordinate systems and approximated the integral over regions of the microsphere deposition field.