Computational Modeling and Clonogenic Assay for Radioenhancement of Gold Nanoparticles Using 3D Live Cell Images

Dynamic tracking of onion-like carbon nanoparticles in cancer cells using limited-angle holographic tomography with self-supervised learning

This research presents a novel approach for the dynamic monitoring of onion-like carbon nanoparticles inside colorectal cancer cells. Onion-like carbon nanoparticles are widely used in photothermal cancer therapy, and precise 3D tracking of their distribution is crucial. We proposed a limited-angle digital holographic tomography technique with unsupervised learning to achieve rapid and accurate monitoring. A key innovation is our internal learning neural network. This network addresses the information limitations of limited-angle measurements by directly mapping coordinates to measured data and reconstructing phase information at unmeasured angles without external training data. We validated the network using standard SiO2 microspheres. Subsequently, we reconstructed the 3D refractive index of onion-like carbon nanoparticles within cancer cells at various time points. Morphological parameters of the nanoparticles were quantitatively analyzed to understand their temporal evolution, offering initial insights into the underlying mechanisms. This methodology provides a new perspective for efficiently tracking nanoparticles within cancer cells.

Clonogenic assay and computational modeling using real cell images to study physical enhancement and cellular sensitization induced by metal nanoparticles under MV and kV X-ray irradiation

This study was initiated due to the physically unexplainable tumor controls resulting from metal nanoparticle (MNP) experiments even under MV X-ray irradiation. A more accurate explanation of the mechanism of radiosensitization induced by MNP is warranted, considering both its physical dose enhancement and biological sensitization, as related research is lacking. Thus, we aimed to examine the intricate dynamics involved in MNP-induced radiosensitization. We conducted specifically designed clonogenic assays for the A549 lung cancer cell line with MNP irradiated by 6 MV and 300 kVp X-rays. Two types of MNP were employed: one based on iron oxide, promoting ferroptosis, and the other on gold nanoparticles known for inducing a significant dose enhancement, particularly at low-energy X-rays. We introduced the lethality enhancement factor (LEF) as the fraction in the cell killing attributed to biological sensitization. Subsequently, Monte Carlo simulations were conducted to evaluate the radial dose profiles for each MNP, corresponding to the physical enhancement. Finally, the local effect model was applied to the clonogenic assay results on real cell images. The LEF and the dose enhancement in the cytoplasm were incorporated to increase the accuracy in the average lethal events and, consequently, in the survival fraction. The results reveal an increased cell killing for both of the MNP under MV and kV X-ray irradiation. In both types of MNP, the LEF reveals a biological sensitization evident. The sensitizer enhancement ratio, derived from the calculations, exhibited only 3% and 1% relative differences compared to the conventional linear-quadratic model for gold and ferroptosis inducer nanoparticles, respectively. These findings indicate that MNPs sensitize cells via radiation through mechanisms akin to ferroptosis inducers, not exclusively relying on a physical dose enhancement. Their own contributions to survival fractions were successfully integrated into computational modeling.

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration.

Nanoparticle radiosensitization: from extended local effect modeling to a survival modification framework of compound Poisson additive killing and its carbon dots validation

Objective. To construct an analytical model instead of local effect modeling for the prediction of the biological effectiveness of nanoparticle radiosensitization. Approach. An extended local effects model is first proposed with a more comprehensive description of the nanoparticles mediated local killing enhancements, but meanwhile puts forward challenging issues that remain difficult and need to be further studied. As a novel method instead of local effect modeling, a survival modification framework of compound Poisson additive killing is proposed, as the consequence of an independent additive killing by the assumed equivalent uniform doses of individual nanoparticles per cell under the LQ model. A compound Poisson killing (CPK) model based on the framework is thus derived, giving a general expression of nanoparticle mediated LQ parameter modification. For practical use, a simplified form of the model is also derived, as a concentration dependent correction only to the α parameter, with the relative correction (α″/α) dominated by the mean number, and affected by the agglomeration of nanoparticles per cell. For different agglomeration state, a monodispersion model of the dispersity factor η = 1, and an agglomeration model of 2/3 < η < 1, are provided for practical prediction of (α″/α) value respectively. Main results. Initial validation by the radiosensitization of HepG2 cells by carbon dots showed a high accuracy of the CPK model. In a safe range of concentration (0.003–0.03 μg μl−1) of the carbon dots, the prediction errors of the monodispersion and agglomeration models were both within 2%, relative to the clonogenic survival data of the sensitized HepG2 cells. Significance. The compound Poisson killing model provides a novel approach for analytical prediction of the biological effectiveness of nanoparticle radiosensitization, instead of local effect modeling.

Microdosimetric-Kinetic Model for Radio-enhancement of Gold Nanoparticles: Comparison with LEM

Numerous studies have strongly supported the application of gold nanoparticles (GNPs) as radio-enhanced agents. In our previous study, the local effect model (LEM I) was adopted to predict the cell survival for MDA-MB-231 cells exposed to 150 kVp X rays after 500 µg/ml GNPs treatment. However, microdosimetric quantities could not be obtained, which were correlated with biological effects on cells. Thus, we developed microdosimetric kinetic model (MKM) for GNP radio-enhancement (GNP-MKM), which uses the microdosimetric quantities such as dose-mean lineal energy with subcellular domain size. Using the Monte Carlo simulation tool Geant4, we estimated the dose-mean lineal energy with secondary radiations from GNPs and absorbed dose in the nucleus. The variations in MKM parameters for different domain sizes, and GNP concentrations, were calculated to compare the survival fractions predicted by both models. With a domain radius of 500 nm and a threshold dose of 20 Gy, the sensitizer enhancement ratio predicted by GNP-MKM and GNP-LEM was 1.41 and 1.29, respectively. The GNP-MKM predictions were much more strongly dependent on the domain size than were the GNP-LEM on the threshold dose. These findings provide another method to predict survival fraction for the GNP radio-enhancement.

Optical quantification of intracellular mass density and cell mechanics in 3D mechanical confinement

Biophysical properties of cells such as intracellular mass density and cell mechanics are known to be involved in a wide range of homeostatic functions and pathological alterations. An optical readout that can be used to quantify such properties is the refractive index (RI) distribution. It has been recently reported that the nucleus, initially presumed to be the organelle with the highest dry mass density (ρ) within the cell, has in fact a lower RI and ρ than its surrounding cytoplasm. These studies have either been conducted in suspended cells, or cells adhered on 2D substrates, neither of which reflects the situation in vivo where cells are surrounded by the extracellular matrix (ECM). To better approximate the 3D situation, we encapsulated cells in 3D covalently-crosslinked alginate hydrogels with varying stiffness, and imaged the 3D RI distribution of cells, using a combined optical diffraction tomography (ODT)-epifluorescence microscope. Unexpectedly, the nuclei of cells in 3D displayed a higher ρ than the cytoplasm, in contrast to 2D cultures. Using a Brillouin-epifluorescence microscope we subsequently showed that in addition to higher ρ, the nuclei also had a higher longitudinal modulus (M) and viscosity (η) compared to the cytoplasm. Furthermore, increasing the stiffness of the hydrogel resulted in higher M for both the nuclei and cytoplasm of cells in stiff 3D alginate compared to cells in compliant 3D alginate. The ability to quantify intracellular biophysical properties with non-invasive techniques will improve our understanding of biological processes such as dormancy, apoptosis, cell growth or stem cell differentiation.

Radiosensitization by Au-nanofilm at micrometer level using confocal Raman spectroscopy

PURPOSE

To measure the radiosensitization by an Au-nanofilm (GNF) at a micrometer level on a radiochromic film (RCF) using confocal Raman spectroscopy (CRS).

METHODS

Unlaminated radiochromic films were irradiated by 200 kVp x-ray from 0.3 to 50 Gy to obtain a calibration curve. Raman spectra of these films were measured by positioning the postirradiated RCF perpendicular to the CRS monochromatic beam and reading a depth profile of the film along the lateral axis. The Raman peak corresponding to the C ≡ C peak was obtained from a region of interest of 100 × 5 µm² . To investigate the radiosensitization by GNF, two sets of RCF, one attached to a 100-nm thick GNF and the other without GNF were irradiated at 0.5 Gy by 50 and 120 kVp X-rays. The spatial resolution of the CRS on the RCF was quantified by the modulation transfer function method (MTF). Thus, in the spatial resolution determined by MTF, the doses deposited on the films were evaluated. The dose enhancement factor (DEF) was obtained in the measurable micro-size by comparing doses deposited on the RCFs with and without GNF. To verify the experimental results, Monte Carlo simulations following the experimental set up were performed using Geant4. In addition, analytical calculations for the radiosensitization by GNF were carried out.

RESULTS

The confocal Raman spectroscopy on the RCF achieved a spatial resolution of ~6 μm. An experimental DEF within the first 6 μm depth from the surface of RCF was found to be 17.9 for 50 kVp and 14.7 for 120 kVp. The DEF for the same depth obtained by MC and analytical calculations was 13.53 and 9.75 for 50 kVp, and 10.63 and 6.67 for 120 kVp, respectively.

CONCLUSIONS

The experimental DEF as a function of the distance from GNF was consistent with data from previous studies and the MC simulations, supporting that CRS in conjunction with the RCF is a feasible micrometer-resolution dosimeter.

Holotomography: Refractive Index as an Intrinsic Imaging Contrast for 3-D Label-Free Live Cell Imaging

Live cell imaging provides essential information in the investigation of cell biology and related pathophysiology. Refractive index (RI) can serve as intrinsic optical imaging contrast for 3-D label-free and quantitative live cell imaging, and provide invaluable information to understand various dynamics of cells and tissues for the study of numerous fields. Recently significant advances have been made in imaging methods and analysis approaches utilizing RI, which are now being transferred to biological and medical research fields, providing novel approaches to investigate the pathophysiology of cells. To provide insight into how RI can be used as an imaging contrast for imaging of biological specimens, here we provide the basic principle of RI-based imaging techniques and summarize recent progress on applications, ranging from microbiology, hematology, infectious diseases, hematology, and histopathology.

In silico modeling of cellular probabilistic nanoparticle radiosensitization in head and neck cancers

Background: The use of gold nanoparticles (AuNPs) as radiosensitizers may offer a new approach in the treatment of head and neck cancers; minimizing treatment-associated toxicities and improving patient outcomes. AuNPs promote localized dose deposition; permitting improved local control and/or dose reduction. Aim: This work aimed to address the theoretical optimization of radiation doses, fractionation and nanoparticle injection schedules to maximize therapeutic benefits. Materials & methods: Probabilistic nanoparticle sensitization factors were incorporated into the individual cell-based HYP-RT computer model of tumor growth and radiotherapy. Results: Total dose outcomes across all radiation therapy treatment regimens were found to be significantly reduced with the presence of AuNPs, with bi-weekly injections showing the most decrease. Conclusion: Outcomes suggest the need for regular AuNP administration to permit effective radiosensitization.

Roadmap for metal nanoparticles in radiation therapy: current status, translational challenges, and future directions

This roadmap outlines the potential roles of metallic nanoparticles (MNPs) in the field of radiation therapy. MNPs made up of a wide range of materials (from Titanium, Z = 22, to Bismuth, Z = 83) and a similarly wide spectrum of potential clinical applications, including diagnostic, therapeutic (radiation dose enhancers, hyperthermia inducers, drug delivery vehicles, vaccine adjuvants, photosensitizers, enhancers of immunotherapy) and theranostic (combining both diagnostic and therapeutic), are being fabricated and evaluated. This roadmap covers contributions from experts in these topics summarizing their view of the current status and challenges, as well as expected advancements in technology to address these challenges.

Intercomparison of dose enhancement ratio and secondary electron spectra for gold nanoparticles irradiated by X-rays calculated using multiple Monte Carlo simulation codes

PURPOSE

Targeted radiation therapy has seen an increased interest in the past decade. In vitro and in vivo experiments showed enhanced radiation doses due to gold nanoparticles (GNPs) to tumors in mice and demonstrated a high potential for clinical application. However, finding a functionalized molecular formulation for actively targeting GNPs in tumor cells is challenging. Furthermore, the enhanced energy deposition by secondary electrons around GNPs, particularly by short-ranged Auger electrons is difficult to measure. Computational models, such as Monte Carlo (MC) radiation transport codes, have been used to estimate the physical quantities and effects of GNPs. However, as these codes differ from one to another, the reliability of physical and dosimetric quantities needs to be established at cellular and molecular levels, so that the subsequent biological effects can be assessed quantitatively.

METHODS

In this work, irradiation of single GNPs of 50 nm and 100 nm diameter by X-ray spectra generated by 50 and 100 peak kilovoltages was simulated for a defined geometry setup, by applying multiple MC codes in the EURADOS framework.

RESULTS

The mean dose enhancement ratio of the first 10 nm-thick water shell around a 100 nm GNP ranges from 400 for 100 kVp X-rays to 600 for 50 kVp X-rays with large uncertainty factors up to 2.3.

CONCLUSIONS

It is concluded that the absolute dose enhancement effects have large uncertainties and need an inter-code intercomparison for a high quality assurance; relative properties may be a better measure until more experimental data is available to constrain the models.