Nanoscale gold nanoparticle (GNP)-laden tumor cell model and its use for estimation of intracellular dose from GNP-induced secondary electrons.

BACKGROUND: Gold nanoparticles (GNPs) accumulated within tumor cells have been shown to sensitize tumors to radiotherapy. From a physics point of view, the observed GNP-mediated radiosensitization is due to various downstream effects of the secondary electron (SE) production from internalized GNPs such as GNP-mediated dose enhancement. Over the years, numerous computational investigations on GNP-mediated dose enhancement/radiosensitization have been conducted. However, such investigations have relied mostly on simple cellular geometry models and/or artificial GNP distributions. Thus, it is at least desirable, if not necessary, to conduct further investigations using cellular geometry models that properly reflect realistic cell morphology as well as internalized GNP distributions at the nanoscale. PURPOSE: The primary aim of this study was to develop a nanometer-resolution geometry model of a GNP-laden tumor cell for computational investigations of GNP-mediated dose enhancement/radiosensitization. The secondary aim was to demonstrate the utility of this model by quantifying GNP-induced SE tracks/dose distribution at sub-cellular levels for further validation of a nanoscopic dose point kernel (nDPK) method against full-fledged Geant4 Monte Carlo (MC) simulation. METHODS: A transmission electron microscopy (TEM) image of a single cell showing cytoplasm, cellular nucleus, and internalized GNPs in the cellular endosome was segmented into sub-cellular levels based on pixel value thresholding. A corresponding material density was allocated to each pixel, and, by adding a thickness, each pixel was transformed to a geometric voxel and imported as a Geant4-acceptable input geometry file. In Geant4-Penelope MC simulation, a clinical 6 MV photon beam was applied, vertically or horizontally to the cell surface, and energy deposition to the cellular nucleus and cytoplasm, due to SEs emitted by internalized GNPs, was scored. Next, nDPK calculations were performed by generating virtual electron tracks from each GNP voxel to all nucleus and cytoplasm voxels. Subsequently, another set of Geant4 simulation was performed with both Penelope and DNA physics models under the geometry closely mimicking in vitro cell irradiation with a clinical 6 MV photon beam, allowing for derivation of nDPK specific to this geometry and further comparison between Gean4 simulation and nDPK method. RESULTS: The Geant4-calculated SE tracks and associated energy depositions showed significant dependence on photon incidence angle. For perpendicular incidence, nDPK results showed good agreement (average percentage pixel-to-pixel difference of 0.4% for cytoplasm and 0.5% for nucleus) with Geant4 results, while, for parallel incidence, the agreement became worse (-1.7%-0.7% for cytoplasm and -5.5%-0.8% for nucleus). Under the 6 MV cell irradiation geometry, nDPK results showed reasonable agreement (pixel-to-pixel Pearson's product moment correlation coefficient of 0.91 for cytoplasm and 0.98 for nucleus) with Geant4 results. CONCLUSIONS: The currently developed TEM-based model of a GNP-laden cell offers unprecedented details of realistic intracellular GNP distributions for nanoscopic computational investigations of GNP-mediated dose enhancement/radiosensitization. A benchmarking study performed with this model showed reasonable agreement between Geant4- and nDPK-calculated intracellular dose deposition by SEs emitted from internalized GNPs, especially under perpendicular incidence - a popular cell irradiation geometry and when the Geant4-Penelope physics model was used.

Dosimetric impact of applicator displacement on three-dimensional image-guided high-dose-rate brachytherapy treatments for cervical cancer.

Purpose: To determine the dosimetric impact of brachytherapy applicator displacement during intracavitary (IC) and combined intracavitary/interstitial (IC/IS) high-dose-rate brachytherapy in the treatment of cervical cancer. Material and methods: Data from 27 consecutively treated patients undergoing IC or IC/IS high-dose-rate brachytherapy with tandem and ovoid-based applicators at a single academic medical center were analyzed. Virtual applicator displacements (a single shift of whole applicator with tandem/ovoid/associated needles) of 0 (clinical position), 2, 5, 7, and 10 mm in the inferior direction were modeled on treatment planning CT or MRI scans, with maintaining the same dwell times. Radiation dose to target volumes (D90 of high-risk clinical target volume) and organs at risk (OARs) (D0.1cc, D1cc, and D2cc of bladder, rectum, and sigmoid) were calculated for each virtual applicator shift, and significance of displacements was assessed using general linear model and Kruskal-Wallis test. Results: Mean dose to high-risk clinical target volume (HR-CTV) D90 was 95.7%, 88.9%, 84.6%, and 77.1% of the prescribed dose in clinical position with displacements of 2, 5, 7, and 10 mm, respectively. Rectal D2cc significantly increased by 28% and 44% at displacement of 7 mm and 10 mm, respectively. IC/IS cases showed relatively greater dosimetric differences than IC cases, with HR-CTV D90 doses of 94.4%, 85.8%, 80.4%, and 72.4% at virtual displacements of 2, 5, 7, and 10 mm, respectively. Conclusions: Applicator displacements of 5 mm or greater result in statistically significant and clinically meaningful decreases in radiation dose to HR-CTV during 3-dimensional high-dose-rate brachytherapy treatment planning, with corresponding increase in radiation dose to the rectum. IC/IS applicator displacements lead to relatively greater differences than those of IC applicators.

Deep Learning-Based TEM Image Analysis for Fully Automated Detection of Gold Nanoparticles Internalized Within Tumor Cell.

Transmission electron microscopy (TEM) imaging can be used for detection/localization of gold nanoparticles (GNPs) within tumor cells. However, quantitative analysis of GNP-containing cellular TEM images typically relies on conventional/thresholding-based methods, which are manual, time-consuming, and prone to human errors. In this study, therefore, deep learning (DL)-based methods were developed for fully automated detection of GNPs from cellular TEM images. Several models of "you only look once (YOLO)" v5 were implemented, with a few adjustments to enhance the model's performance by applying the transfer learning approach, adjusting the size of the input image, and choosing the best optimization algorithm. Seventy-eight original (12,040 augmented) TEM images of GNP-laden tumor cells were used for model implementation and validation. A maximum F1 score (harmonic mean of the precision and recall) of 0.982 was achieved by the best-trained models, while mean average precision was 0.989 and 0.843 at 0.50 and 0.50-0.95 intersection over union threshold, respectively. These results suggested the developed DL-based approach was capable of precisely estimating the number/position of internalized GNPs from cellular TEM images. A novel DL-based TEM image analysis tool from this study will benefit research/development efforts on GNP-based cancer therapeutics, for example, by enabling the modeling of GNP-laden tumor cells using nanometer-resolution TEM images.

The effect of integrating knowledge-based planning with multicriteria optimization in treatment planning for prostate SBRT.

Knowledge-based planning (KBP) and multicriteria optimization (MCO) are two powerful tools to assist treatment planners in achieving optimal target coverage and organ-at-risk (OAR) sparing. The purpose of this work is to investigate if integrating MCO with conventional KBP can further improve treatment plan quality for prostate cancer stereotactic body radiation therapy (SBRT). A two-phase study was designed to investigate the impact of MCO and KBP in prostate SBRT treatment planning. The first phase involved the creation of a KBP model based on thirty clinical SBRT plans, generated by manual optimization (KBP_M). A ten-patient validation cohort was used to compare manual, MCO, and KBP_M optimization techniques. The next phase involved replanning the original model cohort with additional tradeoff optimization via MCO to create a second model, KBP_MCO. Plans were then generated using linear integration (KBP_M+MCO), non-linear integration (KBP_MCO), and a combination of integration methods (KBP_MCO+MCO). All plans were analyzed for planning target volume (PTV) coverage, OAR constraints, and plan quality metrics. Comparisons were generated to evaluate plan and model quality. Phase 1 highlighted the necessity of KBP and MCO in treatment planning, as both optimization methods improved plan quality metrics (Conformity and Heterogeneity Indices) and reduced mean rectal dose by 2 Gy, as compared to manual planning. Integrating MCO with KBP did not further improve plan quality, as little significance was seen over KBP or MCO alone. Principal component score (PCS) fitting showed KBP_MCO improved bladder and rectum estimated and modeled dose correlation by 5% and 22%, respectively; however, model improvements did not significantly impact plan quality. KBP and MCO have shown to reduce OAR dose while maintaining desired PTV coverage in this study. Further integration of KBP and MCO did not show marked improvements in treatment plan quality while requiring increased time in model generation and optimization time.

Use of the Fully Spectroscopic Pixelated Cadmium Telluride Detector for Benchtop X-Ray Fluorescence Computed Tomography.

In this work, we integrated a commercially-available fully-spectroscopic pixelated cadmium telluride (CdTe) detector system as a two-dimensional (2D) array detector into our existing benchtop cone-beam x-ray fluorescence computed tomography (XFCT) system. After integrating this detector, known as High-Energy X-ray Imaging Technology (HEXITEC), we performed quantitative imaging of gold nanoparticle (GNP) distribution in a small animal-sized phantom using our benchtop XFCT system. Owing to the upgraded detector component within our benchtop XFCT system, we were able to conduct this phantom imaging in an unprecedented manner by volumetric XFCT scans followed by XFCT image reconstruction in 3D. The current results showed that adoption of HEXITEC, in conjunction with a custom-made parallel-hole collimator, drastically reduced the XFCT scan time/dose. Compared with the previous work performed with our original benchtop XFCT system adopting a single crystal CdTe detector, the currently observed reduction was up to a factor of 5, while achieving comparable GNP detection limit under similar experimental conditions. Overall, we demonstrated, for the first time to the best our knowledge, the feasibility of benchtop XFCT imaging of small animal-sized objects containing biologically relevant GNP concentrations (on the order of 0.1 mg Au/cm3 or 100 parts-per-million/ppm), with the scan time (on the order of 1 minute)/x-ray dose (on the order of 10 cGy) that are likely meeting the minimum requirements for routine preclinical imaging applications.

Sensitivity enhancement of an experimental benchtop x-ray fluorescence imaging system by deploying a single crystal cadmium telluride detector system optimized for high flux x-ray operations.

In this work, an energy-resolving thermoelectrically cooled single crystal cadmium telluride (CdTe) detector system upgraded with the latest firmware was optimized for high x-ray flux operations using high bias voltage and fast peaking time. This detector system was deployed into an experimental benchtop x-ray fluorescence (XRF) imaging/computed tomography (XFCT) system developed for quantitative imaging of metal nanoprobes such as gold nanoparticles (GNPs). Using the firmware-upgraded and existing/old CdTe detector systems, the Compton/XRF spectra from small (8 mm diameter) GNP-containing phantoms were acquired. The phantoms were irradiated with 1.8 mm Sn-filtered 125 kVp cone beam x-rays at 24 mA. The firmware-upgraded detector system produced relatively lower dead time under high x-ray flux, compared with the old detector system, and performed well with the spectral resolution of ~0.7 keV (in full width at half maximum) at 69 keV photon energy. Given the same 2 mm aperture detector collimator and irradiation time of 10 s, this detector system managed to score nearly 50% more gold XRF signals than the existing one at all GNP concentrations tested. This improvement resulted in the GNP detection limit of 0.02 wt. % which was lower than that (0.03 wt. %) achievable with the existing detector system. When combined with the detector collimator containing a larger (3 mm) aperture, the firmware-upgraded detector system produced drastically more gold XRF signal at a given GNP concentration (e.g., 9 times more for 1 wt. % GNP solution and irradiation time of 10 s), leading to further reduction in the GNP detection limit (i.e., 0.01 wt. %). The present investigation showed that the firmware upgraded CdTe detector system optimized for high x-ray flux operations allowed for better photon counting efficiency, thus leading to sensitivity enhancement of an experimental benchtop XRF/XFCT imaging system.

Characterization of a Pixelated Cadmium Telluride Detector System Using a Polychromatic X-Ray Source and Gold Nanoparticle-Loaded Phantoms for Benchtop X-Ray Fluorescence Imaging.

Pixelated semi-conductor detectors providing high energy resolution enable parallel acquisition of x-ray fluorescence (XRF) signals, potentially leading to performance enhancement of benchtop XRF imaging or computed tomography (XFCT) systems utilizing ordinary polychromatic x-ray sources. However, little is currently known about the characteristics of such detectors under typical operating conditions of benchtop XRF imaging/XFCT. In this work, a commercially available pixelated cadmium telluride (CdTe) detector system, HEXITEC (High Energy X-ray Imaging Technology), was characterized to address this issue. Specifically, HEXITEC was deployed into our benchtop cone-beam XFCT system, and used to detect gold Kα XRF photons from gold nanoparticle (GNP)-loaded phantoms. To facilitate the detection of XRF photons, various parallel-hole stainless steel collimators were fabricated and coupled with HEXITEC. A pixel-by-pixel spectrum merging algorithm was introduced to obtain well-defined XRF + scatter spectra with parallel-hole collimators. The effect of charge sharing addition (CSA) and discrimination (CSD) algorithms was also investigated for pixel-level CS correction. Finally, the detector energy resolution, in terms of the full-width at half-maximum (FWHM) values at two gold Kα XRF peaks (~68 keV), was also determined. Under the current experimental conditions, CSD provided the best energy resolution of HEXITEC (~1.05 keV FWHM), compared with CSA and no CS correction. This FWHM value was larger (by up to ~0.35 keV) than those reported previously for HEXITEC (at ~60 keV Am-241 peak) and single-crystal CdTe detectors (at two gold Kα XRF peaks). This investigation highlighted characteristics of HEXITEC as well as the necessity for application-specific detector characterization.

Monte Carlo study of x-ray detection configurations for benchtop x-ray fluorescence computed tomography of gold nanoparticle-loaded objects.

Over the last decade, the performance of benchtop x-ray fluorescence computed tomography (XFCT) systems has been significantly enhanced through hardware and software optimizations. Recent studies have indicated the need of energy-resolving pixelated/array detectors in the x-ray detection component to further improve the sensitivity and image resolution of benchtop XFCT systems while meeting the realistic constraints of dose and scan time. Thus, it is of immediate interest in the research community to conduct the following investigations: (a) delineation of strengths/weaknesses of detection configurations that incorporate pixelated/array detectors in combination with two most frequently used (parallel-hole and pinhole) collimators; (b) one-to-one comparison of their performance under identical imaging conditions of benchtop XFCT. In this study, we developed a Geant4-based Monte Carlo model to investigate the effects of the aforementioned detection configurations on the sensitivity and image resolution of a benchtop XFCT system. Using this model, we simulated the detection of x-ray fluorescence and scattered photons from gold nanoparticle-containing phantoms using energy-resolving pixelated detectors coupled with parallel-hole and pinhole collimators. Simulation results demonstrated that the detector consisting of large pixels (1 mm × 1 mm) combined with a parallel-hole collimator had better sensitivity (i.e. lower detection limit) than the detector made of smaller pixels (0.25 mm × 0.25 mm) coupled with a pinhole collimator. In comparison, although slightly less sensitive, the latter detector configuration achieved better image resolution than did the former. Thus, a detection configuration consisting of a pixelated detector with submillimeter pixels and a pinhole collimator is preferable when image resolution is critical for benchtop XFCT applications. On the other hand, the detector with larger pixels coupled with a parallel-hole collimator is better suited for benchtop XFCT applications in which higher sensitivity and shorter scan time are essential.

High-sensitivity imaging and quantification of intratumoral distributions of gold nanoparticles using a benchtop x-ray fluorescence imaging system.

A high-sensitivity benchtop x-ray fluorescence (XRF) imaging system, based on a high-power x-ray source and silicon drift detector, has been developed. This system allows gold L-shell XRF-based quantitative imaging of gold nanoparticles (GNPs) at concentrations as low as 0.007 mg/cm3 (7 ppm) in biological tissues/water. Its capability for biomedical applications was demonstrated by imaging the GNP distribution within a small (∼12×11×2 mm3) ex vivo sample (extracted from a murine tumor after intravenous GNP administration). The results suggest direct translatability for routine preclinical ex vivo imaging tasks involving GNPs, as well as the possibility for in vivo imaging of small/superficial animal tumors.

A detector's eye view (DEV)-based OSEM algorithm for benchtop x-ray fluorescence computed tomography (XFCT) image reconstruction.

In this study, we developed a detector's eye view (DEV)-based ordered subsets expectation maximization (OSEM) algorithm for more accurate reconstruction of benchtop x-ray fluorescence computed tomography (XFCT) images. The proposed approach was tested using two sets of benchtop XFCT imaging data derived from a newly performed gold nanoparticle (GNP)-containing phantom imaging study and a previously published postmortem benchtop XFCT imaging study of a tumor-bearing mouse injected with GNPs. DEV-based OSEM resulted in higher spatial resolution (up to ~20% decrease in the full width at half maximum values of the regions of interest), compared with filtered back-projection (FBP) and traditional OSEM. It also resulted in up to an order of magnitude smaller background noise in the reconstructed images than FBP, while producing consistently less background noise than traditional OSEM.

Investigation of transmission computed tomography (CT) image quality and x-ray dose achievable from an experimental dual-mode benchtop x-ray fluorescence CT and transmission CT system.

OBJECTIVE: To investigate the image quality and x-ray dose associated with a transmission computed tomography (CT) component implemented within the same platform of an experimental benchtop x-ray fluorescence CT (XFCT) system for multimodal preclinical imaging applications. METHODS: Cone-beam CT scans were performed using an experimental benchtop CT + XFCT system and a cylindrically-shaped 3D-printed polymethyl methacrylate phantom (3 cm in diameter, 7 cm in height) loaded with various concentrations (0.05-1 wt. %) of gold nanoparticles (GNPs). Two commercial CT quality assurance phantoms containing 3D line-pair (LP) targets and contrast targets were also scanned. The x-ray beams of 40 and 62 kVp, both filtered by 0.08 mm Cu and 0.4 mm Al, were used with 17 ms of exposure time per projection at three current settings (2.5, 5, and 10 mA). The ordered-subset simultaneous algebraic reconstruction and total variation-minimization methods were used to reconstruct images. Sparse projection and short scan were considered to reduce the x-ray dose. The contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were calculated. RESULTS: The lowest detectable concentration of GNPs (CNR > 5) and the highest spatial resolution (per MTF50%) were 0.10 wt. % and 9.5 LP/CM, respectively, based on the images reconstructed from 360 projections of the 40 kVp beam (or x-ray dose of 3.44 cGy). The background noise for the image resulting in the lowest GNP detection limit was 25 Hounsfield units. CONCLUSION: The transmission CT component within the current experimental benchtop CT + XFCT system produced images deemed acceptable for multimodal (CT + XFCT) imaging purposes, with less than 4 cGy of x-ray dose.

Evaluation of dose point kernel rescaling methods for nanoscale dose estimation around gold nanoparticles using Geant4 Monte Carlo simulations.

The absence of proper nanoscale experimental techniques to investigate the dose-enhancing properties of gold nanoparticles (GNPs) interacting with radiation has prompted the development of various Monte Carlo (MC)-based nanodosimetry techniques that generally require considerable computational knowledge, time and specific tools/platforms. Thus, this study investigated a hybrid computational framework, based on the electron dose point kernel (DPK) method, by combining Geant4 MC simulations with an analytical approach. This hybrid framework was applied to estimate the dose distributions around GNPs due to the secondary electrons emitted from GNPs irradiated by various photon sources. Specifically, the equivalent path length approximation was used to rescale the homogeneous DPKs for heterogeneous GNPs embedded in water/tissue. Compared with Geant4 simulations, the hybrid framework halved calculation time while utilizing fewer computer resources, and also resulted in mean discrepancies less than 20 and 5% for Yb-169 and 6 MV photon irradiation, respectively. Its appropriateness and computational efficiency in handling more complex cases were also demonstrated using an example derived from a transmission electron microscopy image of a cancer cell containing internalized GNPs. Overall, the currently proposed hybrid computational framework can be a practical alternative to full-fledged MC simulations, benefiting a wide range of GNP- and radiation-related applications.