Gold nanoparticles spectral CT imaging and limit of detectability in a new materials contrast-detail phantom.

This study involves the synthesis, characterization, and spectral photon counting CT (SPCCT) imaging of gold nanoparticles tailored for enhancing the contrast of small cancer lesions. We used the modified Turkevich method to produce thiol-capped gold nanoparticles (AuNPs) at different concentrations (20, 15, 10, 5, 2.5, 1.25, 0.6 mg/ml). We thoroughly characterized the AuNPs using Transmission Electron Microscopy (TEM), X-ray diffraction spectroscopy (XRD), Dynamic Light Scattering (DLS), and UV-visible absorption spectroscopy. To assess the AuNPs contrast enhancing performance, we designed and built a new material contrast detail phantom for CT imaging and determined the minimum detectable concentrations of AuNPs in simulated lesions of small diameters (1, 2, 3, and 5 mm). The synthesized AuNPs are spherical with an average size of approximately 20 ± 4 nm, with maximum UV absorption occurring at 527 nm wavelength, and exhibit a face-centered cubic structure of gold according to XRD analysis. The synthesized gold nanoparticles demonstrated high contrast in SPCCT, suggesting their potential as contrast agents for imaging cancer tissues. The AuNPs image contrast was directly proportional to the AuNPs concentration. We are the first to determine that the lowest visually distinguishable contrast was achieved at a gold concentration of 5 mg/ml for a 2 mm simulated lesion. For 1 mm size lesion the smallest visible concentration was 10 mg/ml. This newly developed phantom can be used for determining the minimal concentration required for various high-Z nanoparticles to produce detectable contrast in X-ray imaging for small-size simulated lesions.

Applications of machine and deep learning to patient-specific IMRT/VMAT quality assurance.

In order to deliver accurate and safe treatment to cancer patients in radiation therapy using advanced techniques such as intensity modulated radiation therapy (IMRT) and volumetric-arc radiation therapy (VMAT), patient specific quality assurance (QA) should be performed before treatment. IMRT/VMAT dose measurements in a phantom using various devices have been clinically adopted as standard method for QA. This approach allows the verification of the accuracy of the dose calculation, data transfer, and the delivery system. However, patient-specific QA procedures are expensive and require significant time and effort by the physicists. Over the past 5 years, machine learning (ML) and deep learning (DL) algorithms for predictions of IMRT/VMAT QA outcome have been investigated. Various ML and DL models have shown promising prediction accuracy and a high potential as time-efficient virtual QA tool. In this paper, we review the ML and DL based models that were developed for patient specific IMRT and VMAT QA outcome predictions from algorithmic and clinical applicability perspectives. We focus on comparing the algorithms, the dataset sizes, the input parameters and features, the QA outcome prediction approaches, the validation, the performance, the clinical applicability, and the potential clinical impact. In addition, we discuss the present challenges as well as the future directions in the implementation of these models. To the best of our knowledge, this is the first review on the application of ML and DL based models in IMRT/VMAT QA predictions.

Green emitting rare earth Gd2O3:Tb3+ nanoparticles for rapid imaging of latent fingerprint.

A series of green emitting Gd2O3:Tb3+ (Tb: 0%-10% mol) nanoparticles (NP) were synthesized using the hydrothermal method, then characterized and evaluated for latent fingerprint visualization. X-ray diffraction study (XRD) revealed a cubic structure of the nanoparticles and the total incorporation of the terbium in the Gd2O3 matrix. Field Emission-Scanning Electron Microscopy (FESEM), Energy Dispersive x-ray Spectrometry (EDX) and Transmission Electron Microscopy (TEM) were used to study the morphology and the elementary composition of the NP. Photoluminescence (PL) studies showed strong green emission around 540 nm due to the transition 5D4 â†’ 7F5. The luminescence color of the synthesized NP was characterized by the CIE 1931 chromaticity diagram. The potential use of the NP powders for the visualization of latent fingerprint under UV irradiation was assessed on various substrates. The latent fingerprint images revealed by the Gd2O3:Tb3+ NP powders are clear enough to extract and analyze reliable fingerprint features. The fingerprint quality was evaluated using three fingerprint quality assessment metrics and by extracting and measuring the visibility of the minutiae. The experimental results show very good quality images of the latent fingerprint acquired using the Gd2O3:Tb3+ NP and yield good minutiae extraction.

Prediction of the individual multileaf collimator positional deviations during dynamic IMRT delivery priori with artificial neural network.

PURPOSES: Multileaf collimator (MLC) positional accuracy during dynamic intensity modulation radiotherapy (IMRT) delivery is crucial for safe and accurate patient treatment. The deviations of individual leaf positions from its intended positions can lead to errors in the dose delivered to the patient and hence may adversely affect the treatment outcome. In this study, we propose a state-of-the-art machine learning (ML) method based on an artificial neural network (ANN) for accurately predicting the MLC leaf positional deviations during the dynamic IMRT treatment delivery priori using log file data. METHODS: Data of ten patients treated with sliding window dynamic IMRT delivery were retrospectively retrieved from a single-institution database. The patients' plans were redelivered with no patient on the couch using a Varian linear accelerator equipped with a Millennium 120 HD MLC system. Then the machine recorded log files data, a total of over 400 files containing 360 800 control points, were collected. A total of 14 parameters were extracted from the planning data in the log files such as leaf planned positions, dose fraction, leaf velocity, leaf moving status, leaf gap, and others. Next, we developed a feed-forward ANN architecture mapping the input parameters with the output to predict the MLC leaf positional deviations during the delivery priori. The proposed model was trained on 70% of the total data using the delivered leaf positional data as a target response. The trained model was then validated and tested on 30% of the available data. The model accuracy was evaluated using the mean squared error (MSE), regression plot, and error histogram. RESULTS: The deviations between the individual MLC planned and delivered positions can reach up to a few millimeters, with a maximum deviation of 1.2 mm. The predicted leaf positions at control points closely matched the delivered positions for all MLC leaves during the treatment delivery. The ANN model achieved a maximum MSE of 0.0001 mm2 (root MSE of 0.0097 mm) in predicting the leaf positions at control points of test data for each leaf. The correlation coefficient, that measures the goodness of fit, was perfect (R = 0.999) in all plots indicating an excellent agreement between the predicted and delivered MLC positions for the training, validation, and test data. CONCLUSIONS: We successfully demonstrated a proposed ANN-based method capable of accurately predicting the individual MLC leaf positional deviations during the dynamic IMRT delivery priori. Our ML model based on ANN outperformed the reported accuracy in the literature of various ML models. The results of this study could be extended to actual application in the dose calculation/optimization, hence enhancing the gamma passing rate for patient-specific IMRT quality assurance.

Heterogeneity and scatter effects on Ir-192 brachytherapy dose distribution.

We studied the effects of the presence of an air cavity and scatter due to patient size on dose distribution near an Iriduim-192 brachytherapy source (Ir-192). The source was modeled using Monte Carlo (MC) code MCNP5. The Radial dose, gL(r), and the anisotropy function, F(r,θ) specified by the AAPM TG-43 have been determined and compared with the consensus data (AAPM report No. 229). We compared our MC results to the measured dose distribution using an EBT3 Gafchromic® film measurement. The dose was determined in the presence of an air cavity of 3, 5, and 7mm diameters located at 2mm distance from Ir-192. The dose was also determined for Ir-192 centered in 30×30×30cm3 and 80×80×80cm3 water phantoms. The MC results of gL(r) and F(r,θ) agreed with the consensus data to within 2% and 3%, respectively. The MC and the measured dose distributions agreed well with a maximum difference of 8.2% at the periphery of the film. The dose at 10cm from the Ir-192 source with a full scattering medium (80×80×80cm3) was 7% higher compared to the dose in (30×30×30cm3) water phantom. The dose to water in the presence of a 3, 5, and 7mm diameter air cavity increased by an average of 3%, 6%, and 9%, respectively, compared to the dose with no air cavity. Ignoring scatter effects and the heterogeneity correction in the presence of an air cavity can lead to significant errors in dose delivered to patients.

Synthesis of Gd2O3:Eu nanoplatelets for MRI and fluorescence imaging.

We synthesized Gd2O3 and Gd2O3 doped by europium (Eu) (2% to 10%) nanoplatelets using the polyol chemical method. The synthesized nanoplatelets were characterized by X-ray diffraction (XRD), FESEM, TEM, and EDX techniques. The optical properties of the synthesized nanoplatelets were investigated by photoluminescence spectroscopy. We also studied the magnetic resonance imaging (MRI) contrast enhancement of T1 relaxivity using 3 T MRI. The XRD for Gd2O3 revealed a cubic crystalline structure. The XRD of Gd2O3:Eu(3+) nanoplatelets were highly consistent with Gd2O3 indicating the total incorporation of the Eu(3+) ions in the Gd2O3 matrix. The Eu doping of Gd2O3 produced red luminescence around 612 nm corresponding to the radiative transitions from the Eu-excited state (5)D0 to the (7)F2. The photoluminescence was maximal at 5% Eu doping concentration. The stimulated CIE chromaticity coordinates were also calculated. Judd-Ofelt analysis was used to obtain the radiative properties of the sample from the emission spectra. The MRI contrast enhancement due to Gd2O3 was compared to DOTAREM commercial contrast agent at similar concentration of gadolinium oxide and provided similar contrast enhancement. The incorporation of Eu, however, decreased the MRI contrast due to replacement of gadolinium by Eu.

Polymer nanoparticles containing 2,4,6-triiodophenol: a potential contrast medium for medical imaging.

Contrast agents have been utilized for x-ray imaging to visualize blood vessels. Triiodobenzene derivatives are known contrast agents yet have not been formulated in a nanoparticle form for the purpose of enhancing the contrast of cancer tissues. In this study, experiments to encapsulate 2,4,6-triiodophenol in a polymer matrix were designed. Spherical NPs made of PLA, PLGA, PLA-TPGS, PLGA-TPGS and TPGS-FOL, were synthesized and characterized. Using the oil-in-water single-emulsion technique, the effect of several experimental parameters such as sonication power, ratio of 2,4,6-triiodophenol/polymer, type and concentration of emulsifier, and polymer type has been studied. A good morphology of polymer NPs with entrapped 2,4,6-triiodophenol was successfully obtained however the encapsulated iodine was in the range of 5 to 26%.

Skin dose measurements using radiochromic films, TLDS and ionisation chamber and comparison with Monte Carlo simulation.

Estimation of the surface dose is very important for patients undergoing radiation therapy. The purpose of this study is to investigate the dose at the surface of a water phantom at a depth of 0.007 cm as recommended by the International Commission on Radiological Protection and International Commission on Radiation Units and Measurement with radiochromic films (RFs), thermoluminescent dosemeters and an ionisation chamber in a 6-MV photon beam. The results were compared with the theoretical calculation using Monte Carlo (MC) simulation software (MCNP5, BEAMnrc and DOSXYZnrc). The RF was calibrated by placing the films at a depth of maximum dose (d(max)) in a solid water phantom and exposing it to doses from 0 to 500 cGy. The films were scanned using a transmission high-resolution HP scanner. The optical density of the film was obtained from the red component of the RGB images using ImageJ software. The per cent surface dose (PSD) and percentage depth dose (PDD) curve were obtained by placing film pieces at the surface and at different depths in the solid water phantom. TLDs were placed at a depth of 10 cm in a solid water phantom for calibration. Then the TLDs were placed at different depths in the water phantom and were exposed to obtain the PDD. The obtained PSD and PDD values were compared with those obtained using a cylindrical ionisation chamber. The PSD was also determined using Monte Carlo simulation of a LINAC 6-MV photon beam. The extrapolation method was used to determine the PSD for all measurements. The PSD was 15.0±3.6% for RF. The TLD measurement of the PSD was 16.0±5.0%. The (0.6 cm(3)) cylindrical ionisation chamber measurement of the PSD was 50.0±3.0%. The theoretical calculation using MCNP5 and DOSXYZnrc yielded a PSD of 15.0±2.0% and 15.7±2.2%. In this study, good agreement between PSD measurements was observed using RF and TLDs with the Monte Carlo calculation. However, the cylindrical chamber measurement yielded an overestimate of the PSD. This is probably due to the ionisation chamber calibration factor that is only valid in charged particle equilibrium condition, which is not achieved at the surface in the build-up region.

Antithrombotic properties of the thromboxane A2/prostaglandin H2 receptor antagonist S18886 on prevention of platelet-dependent cyclic flow reductions in dogs.

A potent thromboxane A2/PGH2 (TP)-receptor antagonist, S18886, was evaluated for its antithrombotic property in a dog model of acute periodic platelet-mediated thrombosis in stenosed coronary arteries with endothelial damage. After thrombosis had been obtained in 11 dogs, S18886 (300 microg/kg bolus) was administered IV. Heart rate, systemic blood pressure, and coronary blood flow were continuously recorded. Ex vivo whole blood platelet aggregation (PA), blood pH, hematocrit, platelet count, PO2, PCO2, and bleeding times were measured before and 30 minutes after administration of S18886. S18886 completely inhibited thrombosis in all dogs in approximately 5-10 minutes. No change in heart rate, blood pressure, pH, PO2, PCO2, platelet count, or bleeding time and a slight but significant elevation in hematocrit occurred. Infusion of epinephrine IV after complete inhibition of thrombosis by S18886 partially restored thrombosis in 3 of the 11 dogs. PA induced by collagen (4 microg/mL), collagen (0.25 microg/mL) plus epinephrine (1 microg/mL), collagen (1 microg/mL) plus epinephrine (1 microg/mL), ADP (40 microM) plus epinephrine (1 microg/mL), and phorbol 12-myristate 13-acetate (0.5 nM) were attenuated by 90 +/- 8% (P < 0.005), 98 +/- 2% (P < 0.05), 78 +/- 6% (P < 0.005), 70 +/- 10% (P < 0.005), and 28 +/- 8% (P < 0.05), respectively. In conclusion, S18886 is a potent platelet inhibitor that attenuates in vivo platelet-dependent thrombosis in the experimental dog model and reduces ex vivo platelet aggregation.