Integrating Overall Survival and Tumor Control Probability Models to Predict Local Progression After Brain Metastasis Radiosurgery.

Purpose: Stereotactic radiosurgery (SRS) for brain metastases is frequently prescribed to the maximum tolerated dose to minimize the probability of local progression. However, many patients die from extracranial disease prior to local progression and may not require maximally aggressive treatment. Recently, improvements in models of SRS tumor control probability (TCP) and overall survival (OS) have been made. We predicted that by combining models of OS and TCP, we could better predict the true risk of local progression after SRS than by using TCP modeling alone. Methods and Materials: Records of patients undergoing SRS at a single institution were reviewed retrospectively. Using established TCP and OS models, for each patient, the probability of 1-year survival [p(OS)] was calculated, as was the probability of 1-year local progression [p(LP)]) for each treated lesion. Joint-probability was used to combine the models [p(LP,OS)=p(LP)*p(OS)]. Analyses were conducted at the individual metastasis and whole-patient levels. Fine-Gray regression was used to model p(LP) or p(LP,OS) on the risk of local progression after SRS, with death as a competing risk. Results: At the patient level, 1-year local progression was 0.08 (95% CI, 0.03-0.15), median p(LP,OS) was 0.13 (95% CI, 0.07-0.2), and median p(LP) was 0.29 (95% CI, 0.22-0.38). At the metastasis level, 1-year local progression was 0.02 (95% CI, 0.01-0.04), median p(LP,OS) was 0.05 (95% CI, 0.02-0.07), and median p(LP) was 0.10 (95% CI, 0.07-0.13). p(LP,OS) was found to be significantly associated with the risk of local progression at the patient level (P = .048) and metastasis level (P = .007); however, p(LP) was not (P = .16 and P = .28, respectively). Conclusions: Simultaneous modeling of OS and TCP more accurately predicted local progression than TCP modeling alone. Better understanding which patients with brain metastases are at risk of local progression after SRS may help personalize treatment to minimize risk without sacrificing efficacy.

Identification of 18ß-glycyrrhetinic acid as an AGT inhibitor against LPS-induced myocardial dysfunction via high throughput screening.

Sepsis induced myocardial dysfunction (SIMD) is a serious complication of sepsis. There is increasing evidence that the renin-angiotensin system (RAS) is activated in SIMD. Angiotensinogen (AGT) is a precursor of the RAS, and the inhibition of AGT may have significant cardiovascular benefits. But until now, there have been no reports of small molecule drugs targeting AGT. In this study, we designed a promoter-luciferase based system to screen for novel AGT inhibitors to alleviate SIMD. As a result of high-throughput screening, a total of 5 compounds from 351 medicinal herb-derived natural compounds were found inhibiting AGT. 18ß-glycyrrhetinic acid (18ßGA) was further identified as a potent suppressor of AGT. In vitro experiments, 18ßGA could inhibit the secretion of AGT by HepG2 cells and alleviate the elevated level of mitochondrial oxidative stress in cardiomyocytes co-cultured with HepG2 supernatants. In vivo, 18ßGA prolonged the survival rate of SIMD mice, enhanced cardiac function, and inhibited the damage of mitochondrial function and inflammation. In addition, the results showed that 18ßGA may reduce AGT transcription by downregulating hepatocyte nuclear factor 4 (HNF4) and that further alleviated SIMD. In conclusion, we provided a more efficient screening strategy for AGT inhibitors and expanded the novel role of 18ßGA as a promising lead compound in rescuing cardiovascular disease associated with RAS overactivation.

A time- and space-saving Monte Carlo simulation method using post-collimation generative adversarial network for dose calculation of an O-ring gantry Linac.

PURPOSE: This study explores the feasibility of employing Generative Adversarial Networks (GANs) to model the RefleXion X1 Linac. The aim is to investigate the accuracy of dose simulation and assess the potential computational benefits. METHODS: The X1 Linac is a new radiotherapy machine with a binary multi-leaf collimation (MLC) system, facilitating innovative biology-guided radiotherapy. A total of 34 GAN generators, each representing a desired MLC aperture, were developed. Each generator was trained using a phase space file generated underneath the corresponding aperture, enabling the generation of particles and serving as a beam source for Monte Carlo simulation. Dose distributions in water were simulated for each aperture using both the GAN and phase space sources. The agreement between dose distributions was evaluated. The computational time reduction from bypassing the collimation simulation and storage space savings were estimated. RESULTS: The percentage depth dose at 10 cm, penumbra, and full-width half maximum of the GAN simulation agree with the phase space simulation, with differences of 0.4 % ± 0.2 %, 0.32 ± 0.66 mm, and 0.26 ± 0.44 mm, respectively. The gamma passing rate (1 %/1mm) for the planar dose exceeded 90 % for all apertures. The estimated time-saving for simulating an plan using 5766 beamlets was 530 CPU hours. The storage usage was reduced by a factor of 102. CONCLUSION: The utilization of the GAN in simulating the X1 Linac demonstrated remarkable accuracy and efficiency. The reductions in both computational time and storage requirements make this approach highly valuable for future dosimetry studies and beam modeling.

First-Year Experience of Stereotactic Body Radiation Therapy/Intensity Modulated Radiation Therapy Treatment Using a Novel Biology-Guided Radiation Therapy Machine.

Purpose: The aim of this study was to present the first-year experience of treating patients using intensity modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT) with a biology-guided radiation therapy machine, the RefleXion X1 system, installed in a clinical setting. Methods and Materials: A total of 78 patients were treated on the X1 system using IMRT and SBRT from May 2021 to May 2022. Clinical and technical data including treatment sites, number of pretreatment kilovoltage computed tomography (kVCT) scans, beam-on time, patient setup time, and imaging time were collected and analyzed. Machine quality assurance (QA) results, machine performance, and user satisfactory survey were also collected and reported. Results: The most commonly treated site was the head and neck (63%), followed by the pelvis (23%), abdomen (8%), and thorax (6%). Except for 5 patients (6%) who received SBRT treatments for bony metastases in the pelvis, all treatments were conventionally fractionated IMRT. The number of kVCT scans per fraction was 1.2 ± 0.5 (mean ± standard deviation). The beam-on time was 9.2 ± 3.5 minutes. The patient setup time and imaging time per kVCT was 4.8 ± 2.6 minutes and 4.6 ± 1.5 minutes, respectively. The daily machine output deviation was 0.4 ± 1.2% from the baseline. The patient QA had a passing rate of 97.4 ± 2.8% at 3%/2 mm gamma criteria. The machine uptime was 92% of the total treatment time. The daily QA and kVCT image quality received the highest level of satisfaction. The treatment workflow for therapists received the lowest level of satisfaction. Conclusions: One year after the installation, 78 patients were successfully treated with the X1 system using IMRT and/or SBRT. With the recent Food and Drug Administration clearance of biology-guided radiation therapy, our department is preparing to treat patients using positron emission tomography-guidance via a new product release, which will address deficiencies in the current image-guided radiation therapy workflow.

RGFP966 exerts neuroprotective effect via HDAC3/Nrf2 pathway after surgical brain injury in rats.

Histone deacetylase 3 (HDAC3) restores chromatin nucleosomes to a transcriptional repression state, thereby inhibiting gene expression. Studies have found that HDAC3 expression is upregulated in a variety of pathological states of the central nervous system and related to its neurotoxicity. However, the role of HDAC3 in surgical brain injury (SBI) has not been thoroughly explored. OBJECTIVE: To observe the role of HDAC3 in SBI and the outcome of SBI after its suppression. METHODS: Rat SBI model was used, and intraperitoneal injection of RGFP966 (HDAC3 specific inhibitor) was used to detect the changes of HDAC3 expression and neuronal apoptosis indexes in the surrounding cortex of SBI rats, and the cerebral edema and neurological outcome of rats were observed. RESULTS: The expression of HDAC3 in the peripheral cortex of SBI rats was increased, and RGFP966 inhibited the upregulation of HDAC3 and saved the nerve cells around the damaged area. In addition, RGFP966 increased the expression of anti-oxidative stress proteins such as heme oxygenase-1 (HO-1) and superoxide dismutase 2 (SOD2). At the same time, the expression of apoptotic marker protein cleaved-caspase-3 (cle-caspase-3) was decreased, while the expression level of apoptotic protective marker protein B-cell lymphoma 2 (Bcl-2) was increased. In addition, this research demonstrated that in the RGFP966 rat SBI model, the expression level of antioxidant modifier nuclear factor-erythroid 2-related factor 2 (Nrf2) was increased. CONCLUSION: RGFP966 might activate HDAC3/Nrf2 signaling pathway by inhibiting HDAC3, regulated oxidative stress and nerve cell apoptosis induced by SBI in rat SBI model, reduced brain edema, and had a protective effect on nerve injury. It might be a potential target of SBI pathology.

Deep learning-based fluorescence image correction for high spatial resolution precise dosimetry.

Objective.While radiation-excited fluorescence imaging has great potential to measure absolute 2D dose distributions with high spatial resolution, the fluorescence images are contaminated by noise or artifacts due to Cherenkov light, scattered light or background noise. This study developed a novel deep learning-based model to correct the fluorescence images for accurate dosimetric application.Approach.181 single-aperture static photon beams were delivered to an acrylic tank containing quinine hemisulfate water solution. The emitted radiation-exited optical signals were detected by a complementary metal-oxide semiconductor camera to acquire fluorescence images with 0.3 × 0.3 mm2pixel size. 2D labels of projected dose distributions were obtained by applying forward projection calculation of the 3D dose distributions calculated by a clinical treatment planning system. To calibrate the projected dose distributions for Cherenkov angular dependency, a novel empirical Cherenkov emission calibration method was performed. Total 400-epoch supervised learning was applied to a convolutional neural network (CNN) model to predict the projected dose distributions from fluorescence images, gantry, and collimator angles. Accuracy of the calculated projected dose distributions was evaluated with that of uncorrected or conventional methods by using a few quantitative evaluation metrics.Main results.The projected dose distributions corrected by the empirical Cherenkov emission calibration represented more accurate noise-free images than the uncalibrated distributions. The proposed CNN model provided accurate projected dose distributions. The mean absolute error of the projected dose distributions was improved from 2.02 to 0.766 mm·Gy by the CNN model correction. Moreover, the CNN correction provided higher gamma index passing rates for three different threshold criteria than the conventional methods.Significance.The deep learning-based method improves the accuracy of dose distribution measurements. This technique will also be applied to optical signal denoising or Cherenkov light discrimination in other imaging modalities. This method will provide an accurate dose verification tool with high spatial resolution.

Discovery of a potent allosteric activator of DGKQ that ameliorates obesity-induced insulin resistance via the sn-1,2-DAG-PKCε signaling axis.

sn-1,2-diacylglycerol (sn-1,2-DAG)-mediated activation of protein kinase Cε (PKCε) is a key pathway that is responsible for obesity-related lipid metabolism disorders, which induces hepatic insulin resistance and type 2 diabetes. No small molecules have been previously reported to ameliorate these diseases through this pathway. Here, we screened and identified the phytochemical atractylenolide II (AT II) that reduces the hepatic sn-1,2-DAG levels, deactivates PKCε activity, and improves obesity-induced hyperlipidemia, hepatosteatosis, and insulin resistance. Furthermore, using the ABPP strategy, the diacylglycerol kinase family member DGKQ was identified as a direct target of AT II. AT II may act on a novel drug-binding pocket in the CRD and PH domains of DGKQ to thereby allosterically regulate its kinase activity. Moreover, AT II also increases weight loss by activating DGKQ-AMPK-PGC1α-UCP-1 signaling in adipose tissue. These findings suggest that AT II is a promising lead compound to improve obesity-induced insulin resistance.

Individual and combined effects of the GSTM1, GSTT1, and GSTP1 polymorphisms on leukemia risk: An updated meta-analysis.

Background: Several meta-analyses have analyzed the association of GSTM1 present/null, GSTT1 present/null, and GSTP1 IIe105Val polymorphisms with leukemia risk. However, the results of these meta-analyses have been conflicting. Moreover, they did not evaluate the combined effects of the three aforementioned gene polymorphisms. Furthermore, they did not appraise the credibility of the positive results. Finally, many new studies have been published. Therefore, an updated meta-analysis was conducted. Objectives: To further explore the relationship of the three aforementioned gene polymorphisms with leukemia risk. Methods: The crude odds ratios (ORs) and 95% confidence intervals (CIs) were applied to evaluate the association of the individual and combined effects of the three aforementioned genes. Moreover, the false-positive report probability (FPRP) and Bayesian false discovery probability (BFDP) were applied to verify the credibility of these statistically significant associations. Results: Overall, the individual GSTM1, GSTT1, and GSTP1 IIe105Val polymorphisms added leukemia risk. On combining GSTM1 and GSTT1, GSTM1 and GSTP1, and GSTT1 and GSTP1 polymorphisms, positive results were also observed. However, no significant association was observed between the combined effects of these three polymorphisms with leukemia risk in the overall analysis. Moreover, when only selecting Hardy-Weinberg equilibrium (HWE) and medium- and high-quality studies, we came to similar results. However, when the FPRP and BFDP values were applied to evaluate the credibility of positive results, the significant association was only observed for the GSTT1 null genotype with leukemia risk in Asians (BFDP = 0.367, FPRP = 0.009). Conclusion: This study strongly suggests a significant increase in the risk of leukemia in Asians for the GSTT1 null genotype.

Functional Characterization of the Lysine-Specific Histone Demethylases Family in Soybean.

Histone modifications, such as methylation and demethylation, have crucial roles in regulating chromatin structure and gene expression. Lysine-specific histone demethylases (LSDs) belong to the amine oxidase family, which is an important family of histone lysine demethylases (KDMs), and functions in maintaining homeostasis of histone methylation. Here, we identified six LSD-like (LDL) genes from the important leguminous soybean. Phylogenetic analyses divided the six GmLDLs into four clusters with two highly conserved SWRIM and amine oxidase domains. Indeed, demethylase activity assay using recombinant GmLDL proteins in vitro demonstrated that GmLDLs have demethylase activity toward mono- and dimethylated Lys4 but not trimethylated histone 3, similar to their orthologs previously reported in animals. Using real-time PCR experiments in combination with public transcriptome data, we found that these six GmLDL genes exhibit comparable expressions in multiple tissues or in response to different abiotic stresses. Moreover, our genetic variation investigation of GmLDL genes among 761 resequenced soybean accessions indicates that GmLDLs are well conserved during soybean domestication and improvement. Taken together, these findings demonstrate that GmFLD, GmLDL1a, and GmLDL1b are bona fide H3K4 demethylases towards H4K4me1/2 and GmLDLs exist in various members with likely conserved and divergent roles in soybeans.

Downregulation of TREM2/NF-кB signaling may damage the blood-brain barrier and aggravate neuronal apoptosis in experimental rats with surgically injured brain.

Surgical brain injury (SBI) is unavoidable in neurosurgery, and could aggravate secondary brain injury. Post-brain injury, multiple inflammatory factors are released, resulting in neuroinflammation and cell apoptosis, with subsequent brain edema and nerve function injury. TREM2, an immune protein mainly expressed in microglia, is an important link for nerve cells to participate in the inflammatory response. TREM2 and nuclear factor кB (NF-кB) are indeed closely associated with the release of inflammatory cytokines following brain injury. This work aimed to determine the inflammatory function of TREM2 in SBI, and to investigate whether TREM2 regulates interleukin-1 beta (IL-1ß), IL-6 and tumor necrosis factor-α (TNF-α) release through the NF-кB p65 signaling pathway. We established a rat model of SBI, and performed Western blotting (WB), immunofluorescence (IF) and enzyme-linked immunosorbent assay (ELISA) for further analysis. Next, brain edema and neurological score analyses were performed. Finally, whether TREM2 regulating NF-кB p65 signaling affects blood-brain barrier (BBB) permeability and nerve cell apoptosis was examined. We found that post-SBI, TREM2 was upregulated, and inflammation and brain injury were aggravated. After TREM2 downregulation, NF-кB p65 production, inflammation and brain injury were enhanced, suggesting that TREM2 may play a protective role by inhibiting NF-кB p65 production after SBI. Overall, these findings suggest that TREM2 in SBI may have protective effects on postoperative nerve and BBB damage, possibly in part via the NF-κB p65 pathway.

Small-field measurement and Monte Carlo model validation of a novel image-guided radiotherapy system.

PURPOSE: The RefleXion™ X1 is a novel radiotherapy system that is designed for image-guided radiotherapy, and eventually, biology-guided radiotherapy (BgRT). BgRT is a treatment paradigm that tracks tumor motion using real-time positron emission signals. This study reports the small-field measurement results and the validation of a Monte Carlo (MC) model of the first clinical RefleXion unit. METHODS: The RefleXion linear accelerator (linac) produces a 6 MV flattening filter free (FFF) photon beam and consists of a binary multileaf collimator (MLC) system with 64 leaves and two pairs of y-jaws. The maximum clinical field size achievable is 400 × 20 mm2 . The y-jaws provide either a 10 or 20 mm opening at source-to-axis distance (SAD) of 850 mm. The width of each MLC leaf at SAD is 6.25 mm. Percentage depth doses (PDDs) and relative beam profiles were acquired using an Edge diode detector in a water tank for field sizes from 12.5 × 10 to 100 × 20 mm2 . Beam profiles were also measured using films. Output factors of fields ranging from 6.25 × 10 to 100 × 20 mm2 were measured using W2 scintillator detector, Edge detector, and films. Output correction factors k of the Edge detector for RefleXion were calculated. An MC model of the linac including pre-MLC beam sources and detailed structures of MLC and lower y-jaws was validated against the measurements. Simulation codes BEAMnrc and GATE were utilized. RESULTS: The diode measured PDD at 10 cm depth (PDD10) increases from 53.6% to 56.9% as the field opens from 12.5 × 10 to 100 × 20 mm2 . The W2-measured output factor increases from 0.706 to 1 as the field opens from 6.25 × 10 to 100 × 20 mm2 (reference field size). The output factors acquired by diode and film differ from the W2 results by 1.65% (std = 1.49%) and 2.09% (std = 1.41%) on average, respectively. The profile penumbra and full-width half-maximum (FWHM) measured by diode agree well with the film results with a deviation of 0.60 mm and 0.73% on average, respectively. The averaged beam profile consistency calculated between the diode- and film-measured profiles among different depths is within 1.72%. By taking the W2 measurements as the ground truth, the output correction factors k for Edge detector ranging from 0.958 to 1 were reported. For the MC model validation, the simulated PDD10 agreed within 0.6% to the diode measurement. The MC-simulated output factor differed from the W2 results by 2.3% on average (std = 3.7%), while the MC simulated beam penumbra differed from the diode results by 0.67 mm on average (std = 0.42 mm). The MC FWHM agreed with the diode results to within 1.40% on average. The averaged beam profile consistency calculated between the diode and MC profiles among different depths is less than 1.29%. CONCLUSIONS: This study represents the first small-field dosimetry of a clinical RefleXion system. A complete and accurate MC model of the RefleXion linac has been validated.

Inhibition of the p­SPAK/p­NKCC1 signaling pathway protects the blood­brain barrier and reduces neuronal apoptosis in a rat model of surgical brain injury.

Surgical brain injury (SBI) can disrupt the function of the blood­brain barrier (BBB), leading to brain edema and neurological dysfunction. Thus, protecting the BBB and mitigating cerebral edema are key factors in improving the neurological function and prognosis of patients with SBI. The inhibition of WNK lysine deficient protein kinase/STE20/SPS1­related proline/alanine­rich kinase (SPAK) signaling ameliorates cerebral edema, and this signaling pathway regulates the phosphorylation of the downstream Na+­K+­Cl­ cotransporter 1 (NKCC1). Therefore, the purpose of the present study was to investigate the role of SPAK in SBI­induced cerebral edema and to determine whether the SPAK/NKCC1 signaling pathway was involved in SBI via regulating phosphorylation. An SBI model was established in male Sprague­Dawley rats, and the effects of SPAK on the regulation of the NKCC1 signaling pathway on BBB permeability and nerve cell apoptosis by western blotting analysis, immunofluorescence staining, TUNEL staining, Fluoro­Jade C staining, and brain edema and nervous system scores. The results demonstrated that, compared with those in the sham group, phosphorylated (p)­SPAK and p­NKCC1 protein expression levels were significantly increased in the SBI model group. After inhibiting p­SPAK, the expression level of p­NKCC1, neuronal apoptosis and BBB permeability were significantly reduced in SBI model rats. Taken together, these findings suggested that SBI­induced increases in p­SPAK and p­NKCC1 expression exacerbated post­traumatic neural and BBB damage, which may be mediated via the ion­transport­induced regulation of cell edema.

Copper(ii) complexes of N-propargyl cyclam ligands reveal a range of coordination modes and colours, and unexpected reactivity.

The coordination chemistry of N-functionalised cyclam ligands has a rich history, yet cyclam derivatives with pendant alkynes are largely unexplored. This is despite the significant potential and burgeoning application of N-propargyl cyclams and related compounds in the creation of diversely functionalised cyclam derivatives via copper-catalysed azide-alkyne 'click' reactions. Herein we describe single crystal X-ray diffraction and spectroscopic investigations of the coordination chemistry of copper(ii) complexes of cyclam derivatives with between 1 and 4 pendant alkynes. The crystal structures of these copper complexes unexpectedly reveal a range of coordination modes, and the surprising occurrence of five unique complexes within a single recrystallisation of the tetra-N-propargyl cyclam ligand. One of these species exhibits weak intramolecular copper-alkyne coordination, and another is formed by a surprising intramolecular copper-mediated hydroalkoxylation reaction with the solvent methanol, transforming one of the pendant alkynes to an enol ether. Multiple functionalisation of the tetra-N-propargyl ligand is demonstrated via a 'tetra-click' reaction with benzyl azide, and the copper-binding behaviour of the resulting tetra-triazole ligand is characterised spectroscopically.

Frequency-dependent optimal weighting approach for megavoltage multilayer imagers.

Multi-layer imaging (MLI) devices improve the detective quantum efficiency (DQE) while maintaining the spatial resolution of conventional mega-voltage (MV) x-ray detectors for applications in radiotherapy. To date, only MLIs with identical detector layers have been explored. However, it may be possible to instead use different scintillation materials in each layer to improve the final image quality. To this end, we developed and validated a method for optimally combining the individual images from each layer of MLI devices that are built with heterogeneous layers. Two configurations were modeled within the GATE Monte Carlo package by stacking different layers of a terbium doped gadolinium oxysulfide Gd2O2S:Tb (GOS) phosphor and a LKH-5 glass scintillator. Detector response was characterized in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE. Spatial frequency-dependent weighting factors were then analytically derived for each layer such that the total DQE of the summed combination image would be maximized across all spatial modes. The final image is obtained as the weighted sum of the sub-images from each layer. Optimal weighting factors that maximize the DQE were found to be the quotient of MTF and NNPS of each layer in the heterogeneous MLI detector. Results validated the improvement of the DQE across the entire frequency domain. For the LKH-5 slab configuration, DQE(0) increases between 2%-3% (absolute), while the corresponding improvement for the LKH-5 pixelated configuration was 7%. The performance of the weighting method was quantitatively evaluated with respect to spatial resolution, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated planar images of phantoms at 2.5 and 6 MV. The line pair phantom acquisition exhibited a twofold increase in CNR and SNR, however MTF was degraded at spatial frequencies greater than 0.2 lp mm-1. For the Las Vegas phantom, the weighting improved the CNR by around 30% depending on the contrast region while the SNR values are higher by a factor of 2.5. These results indicate that the imaging performance of MLI systems can be enhanced using the proposed frequency-dependent weighting scheme. The CNR and SNR of the weighted combined image are improved across all spatial scales independent of the detector combination or photon beam energy.

Abbreviated on-treatment CBCT using roughness penalized mono-energization of kV-MV data and a multi-layer MV imager.

Simultaneous acquisition of cone beam CT (CBCT) projections using both the kV and MV imagers of an image guided radiotherapy system reduces set-up scan times-a benefit to lung cancer radiation oncology patients-but increases noise in the 3D reconstruction. In this article, we present a kV-MV scan time reduction technique that uses two noise-reducing measures to achieve superior performance. The first is a high-DQE multi-layer MV imager prototype. The second is a beam hardening correction algorithm which combines poly-energetic modeling with edge-preserving, regularized smoothing of the projections. Performance was tested in real acquisitions of the Catphan 604 and a thorax phantom. Percent noise was quantified from voxel values in a soft tissue volume of interest (VOI) while edge blur was quantified from a VOI straddling a boundary between air and soft material. Comparisons in noise/resolution performance trade-off were made between our proposed approach, a dose-equivalent kV-only scan, and a kV-MV reconstruction technique previously published by Yinet al(2005Med. Phys.329). The proposed technique demonstrated lower noise as a function of spatial resolution than the baseline kV-MV method, notably a 50% noise reduction at typical edge blur levels. Our proposed method also exhibited fainter non-uniformity artifacts and in some cases superior contrast. Overall, we find that the combination of a multi-layer MV imager, acquiring at a LINAC source energy of 2.5 MV, and a denoised beam hardening correction algorithm enables noise, resolution, and dose performance comparable to standard kV-imager only set-up CBCT, but with nearly half the gantry rotation time.

Roles, molecular mechanisms, and signaling pathways of TMEMs in neurological diseases.

Transmembrane protein family members (TMEMs) span the entire lipid bilayer and act as channels that allow the transport of specific substances through biofilms. The functions of most TMEMs are unexplored. Numerous studies have shown that TMEMs are involved in the pathophysiological processes of various nervous system diseases, but the specific mechanisms of TMEMs in the pathogenesis of diseases remain unclear. In this review, we discuss the expression, physiological functions, and molecular mechanisms of TMEMs in brain tumors, psychiatric disorders, abnormal motor activity, cobblestone lissencephaly, neuropathic pain, traumatic brain injury, and other disorders of the nervous system. Additionally, we propose that TMEMs may be used as prognostic markers and potential therapeutic targets in patients with various neurological diseases.

GPU-accelerated Monte Carlo simulation of MV-CBCT.

Monte Carlo simulation (MCS) is one of the most accurate computation methods for dose calculation and image formation in radiation therapy. However, the high computational complexity and long execution time of MCS limits its broad use. In this paper, we present a novel strategy to accelerate MCS using a graphic processing unit (GPU), and we demonstrate the application in mega-voltage (MV) cone-beam computed tomography (CBCT) simulation. A new framework that generates a series of MV projections from a single simulation run is designed specifically for MV-CBCT acquisition. A Geant4-based GPU code for photon simulation is incorporated into the framework for the simulation of photon transport through a phantom volume. The FastEPID method, which accelerates the simulation of MV images, is modified and integrated into the framework. The proposed GPU-based simulation strategy was tested for its accuracy and efficiency in a Catphan 604 phantom and an anthropomorphic pelvis phantom with beam energies at 2.5 MV, 6 MV, and 6 MV FFF. In all cases, the proposed GPU-based simulation demonstrated great simulation accuracy and excellent agreement with measurement and CPU-based simulation in terms of reconstructed image qualities. The MV-CBCT simulation was accelerated by factors of roughly 900-2300 using an NVIDIA Tesla V100 GPU card against a 2.5 GHz AMD Opteron™ Processor 6380.

A rapid, accurate image simulation strategy for mega-voltage cone-beam computed tomography.

Intensive computation time is required to simulate images of electronic portal imaging device (EPID) using Monte Carlo (MC) technique, limiting the development of applications associated with EPID, such as mega-voltage cone-beam computed tomography (MV-CBCT). In this study, a fast, accurate simulation strategy for MV-CBCT utilizing the FastEPID technique has been developed and validated. During FastEPID simulation, photon detection was determined by pre-calculated photon energy deposition efficiency (η) and particle transport within the EPID was replaced with a pre-calculated optical photon spread function. This method is capable of reducing the time required for EPID image simulation by a factor of 90-140, without compromising image quality. MV-CBCT images reconstructed from the FastEPID simulated projections have been validated against measurement in terms of mean Hounsfield unit (HU), noise, and cupping artifact. These images were obtained with both a Catphan 604 phantom and an anthropomorphic pelvis phantom, under treatment beam energies of 2.5 MV, 6 MV, and 6 MV flattening filter free. The agreement between measurement and simulation was excellent in all cases. This novel strategy was capable of reducing the run time of a full scan simulation of MV-CBCT performed on a CPU cluster to a matter of hours, rather than weeks or months required by a conventional approach. Multiple applications associated with MV-CBCT (e.g. imager design optimization) are anticipated to gain from the implementation of this novel simulation strategy.

Low-dose megavoltage cone-beam computed tomography using a novel multi-layer imager (MLI).

PURPOSE: The feasibility of low-dose megavoltage cone-beam acquisition (MVCBCT) using a novel, high detective quantum efficiency (DQE) multi-layer imager (MLI) was investigated. The aim of this work was to reconstruct MVCBCT images using the MLI at different total dose levels, and assess Hounsfield Unit (HU) accuracy, noise and contrast-to-noise ratio (CNR) for low-dose megavoltage cone-beam acquisition. METHODS: The MLI has four stacked layers; each layer contains a combination of copper filter/converter, gadolinium oxysulfide (GOS) scintillator and a-Si detector array. In total, 720 projections of a CATPHAN® phantom were acquired over 360° at 2.5, 6, and 6 MV flattening filter free (FFF) beam energies on a Varian TrueBeam LINAC. The dose per projection was 0.01, 0.0167, and 0.05 MU for 2.5, 6, and 6 MV FFF, respectively. MVCBCT images were reconstructed with varying numbers of projections to provide a range of doses for evaluation. Hounsfield Unit uniformity, accuracy, noise and CNR were estimated. Improvements were quantified relative to the standard AS1200 single-layer imager. RESULTS: Average HU uniformity for the MLI reconstructions was within a range of 95%-99% for all of the energies studied. Relative electron density estimation from HU values was within 0.4% ± 1.8% from nominal values. The CNR for MVCBCT based on MLI projections was 2-4× greater than from AS1200 projections. The 2.5 MV beam acquisition with the MLI exhibited the lowest noise and the best balance between CNR and dose for low-dose reconstructions. CONCLUSIONS: Megavoltage cone-beam acquisition imaging with a novel MLI prototype mounted on a clinical linear accelerator demonstrated substantial improvement over the standard AS1200 EPID. Further optimization of MVCBCT reconstruction, particularly for 2.5 MV acquisitions, will improve image metrics. Overall, the MLI improves CNR at substantially lower doses than currently required by conventional detectors. This new high DQE detector could provide high-quality MVCBCT at clinically acceptable doses.