PixelPrint 4D : A 3D printing method of fabricating patient-specific deformable CT phantoms for respiratory motion applications.

All in-vivo medical imaging is impacted by patient motion, especially respiratory motion, which has a significant influence on clinical workflows in diagnostic imaging and radiation therapy. Many technologies such as motion artifact reduction and tumor tracking algorithms have been developed to compensate for respiratory motion during imaging. To assess these technologies, respiratory motion phantoms (RMPs) are required as preclinical testing environments, for instance, in computed tomography (CT). However, current RMPs are highly simplified and do not exhibit realistic tissue structures or deformation patterns. With the rise of more complex motion compensation technologies such as deep learning-based algorithms, there is a need for more realistic RMPs. This work introduces PixelPrint 4D , a 3D printing method designed to fabricate lifelike, patient-specific deformable lung phantoms for CT imaging. The phantom demonstrated accurate replication of patient lung structures, textures, and attenuation profiles. Furthermore, it exhibited accurate nonrigid deformations, volume changes, and attenuation changes under compression. PixelPrint 4D enables the production of highly realistic RMPs, surpassing existing models to offer more robust testing environments for a diverse array of novel CT technologies.

Matrix Protein of Vesicular Stomatitis Virus Targets the Mitochondria, Reprograms Glucose Metabolism, and Sensitizes to 2-Deoxyglucose in Glioblastoma.

A potential therapeutic approach for cancer treatment is target oxidative phosphorylation and glycolysis simultaneously. The matrix protein of vesicular stomatitis virus (VSV MP) can target the surface of mitochondria, causing morphological changes that may be associated with mitochondrial dysfunction and oxidative phosphorylation inhibition. Previous research has shown that mitochondrial abnormalities can direct glucose metabolism toward glycolysis. Thus, after treatment with VSV MP, glycolysis inhibition is necessary to completely block glucose metabolism and eradicate cancer. Here, to inhibit glycolysis, the 2-deoxy-D-glucose (2-DG), a synthetic glucose analog was used to combine with VSV MP to treat cancer. This study aims to determine how VSV MP affects the glucose bioenergetic metabolism of cancer cells and to evaluate the synergistic effect of 2-DG when combined with VSV. Our results indicated that in U87 and C6 glioblastoma cell lines, VSV MP caused mitochondrial membrane potential loss, cytochrome c release, and glucose bioenergetics metabolism reprogramming. When combined with 2-DG, VSV MP synergistically aggravated cell viability, apoptosis, and G2/M phase arrest. Meanwhile, the combination therapy exacerbated ATP depletion, activated AMPK, and inhibited mammalian target of rapamycin signaling pathways. In addition, 2-DG treatment alone induced autophagy in glioblastoma cells; however, VSV MP inhibited the autophagy induced by 2-DG in combined treatment and finally contributed to the enhanced cytotoxic effect of the combination strategy in U87 and C6 cancer cells. In the orthotopic U87 glioblastoma model and subcutaneous C6 glioblastoma model, the combined treatment led to significant tumor regression and prolonged survival. A potent therapeutic approach for treating glioblastoma may be found in the combination of VSV MP and glycolytic inhibitors.

PixelPrint: Generating Patient-Specific Phantoms for Spectral CT using Dual Filament 3D Printing.

In recent years, the importance of spectral CT scanners in clinical settings has significantly increased, necessitating the development of phantoms with spectral capabilities. This study introduces a dual-filament 3D printing technique for the fabrication of multi-material phantoms suitable for spectral CT, focusing particularly on creating realistic phantoms with orthopedic implants to mimic metal artifacts. Previously, we developed PixelPrint for creating patient-specific lung phantoms that accurately replicate lung properties through precise attenuation profiles and textures. This research extends PixelPrint's utility by incorporating a dual-filament printing approach, which merges materials such as calcium-doped Polylactic Acid (PLA) and metal-doped PLA, to emulate both soft tissue and bone, as well as orthopedic implants. The PixelPrint dual-filament technique utilizes an interleaved approach for material usage, whereby alternating lines of calcium-doped and metal-doped PLA are laid down. The development of specialized filament extruders and deposition mechanisms in this study allows for controlled layering of materials. The effectiveness of this technique was evaluated using various phantom types, including one with a dual filament orthopedic implant and another based on a human knee CT scan with a medical implant. Spectral CT scanner results demonstrated a high degree of similarity between the phantoms and the original patient scans in terms of texture, density, and the creation of realistic metal artifacts. The PixelPrint technology's ability to produce multi-material, lifelike phantoms present new opportunities for evaluating and developing metal artifact reduction (MAR) algorithms and strategies.

Lifelike PixelPrint phantoms for assessing clinical image quality and dose reduction capabilities of a deep learning CT reconstruction algorithm.

Deep learning CT reconstruction (DLR) has become increasingly popular as a method for improving image quality and reducing radiation exposure. Due to their nonlinear nature, these algorithms result in resolution and noise performance which are object-dependent. Therefore, traditional CT phantoms, which lack realistic tissue morphology, have become inadequate for assessing clinical imaging performance. We propose to utilize 3D-printed PixelPrint phantoms, which exhibit lifelike attenuation profiles, textures, and structures, as a better tool for evaluating DLR performance. In this study, we evaluate a DLR algorithm (Precise Image (PI), Philips Healthcare) using a custom PixelPrint lung phantom and perform head-to-head comparisons between DLR, iterative reconstruction, and filtered back projection (FBP) with scans acquired at a broad range of radiation exposures (CTDIvol: 0.5, 1, 2, 4, 6, 9, 12, 15, 19, and 20 mGy). We compared the performance of each resultant image using noise, peak signal to noise ratio (PSNR), structural similarity index (SSIM), feature-based similarity index (FSIM), information theoretic-based statistic similarity measure (ISSM) and universal image quality index (UIQ). Iterative reconstruction at 9 mGy matches the image quality of FBP at 12 mGy (diagnostic reference level) for all metrics, demonstrating a dose reduction capability of 25%. Meanwhile, DLR matches the image quality of diagnostic reference level FBP images at doses between 4 - 9 mGy, demonstrating dose reduction capabilities between 25% and 67%. This study shows that DLR allows for reduced radiation dose compared to both FBP and iterative reconstruction without compromising image quality. Furthermore, PixelPrint phantoms offer more realistic testing conditions compared to traditional phantoms in the evaluation of novel CT technologies. This, in turn, promotes the translation of new technologies, such as DLR, into clinical practice.

Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm.

Objective. Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels.Method. The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology. The phantom was placed inside two different size extension rings to mimic a small- and medium-sized patient and was scanned on a conventional CT scanner at exposures between 0.5 and 20 mGy. Each scan was reconstructed using filtered back projection (FBP), iterative reconstruction, and DLR at five levels of denoising. Image noise, contrast to noise ratio (CNR), root mean squared error, structural similarity index (SSIM), and multi-scale SSIM (MS SSIM) were calculated for each image.Results.DLR demonstrated superior performance compared to FBP and iterative reconstruction for all measured metrics in both phantom sizes, with better performance for more aggressive denoising levels. DLR was estimated to reduce dose by 25%-83% in the small phantom and by 50%-83% in the medium phantom without decreasing image quality for any of the metrics measured in this study. These dose reduction estimates are more conservative compared to the estimates obtained when only considering noise and CNR.Conclusion. DLR has the capability of producing diagnostic image quality at up to 83% lower radiation dose, which can improve the clinical utility and viability of lower dose CT scans. Furthermore, the PixelPrint phantom used in this study offers an improved testing environment with more realistic tissue structures compared to traditional CT phantoms, allowing for structure-based image quality evaluation beyond noise and contrast-based assessments.

3D printed phantom with 12 000 submillimeter lesions to improve efficiency in CT detectability assessment.

BACKGROUND: The detectability performance of a CT scanner is difficult to precisely quantify when nonlinearities are present in reconstruction. An efficient detectability assessment method that is sensitive to small effects of dose and scanner settings is desirable. We previously proposed a method using a search challenge instrument: a phantom is embedded with hundreds of lesions at random locations, and a model observer is used to detect lesions. Preliminary tests in simulation and a prototype showed promising results. PURPOSE: In this work, we fabricated a full-size search challenge phantom with design updates, including changes to lesion size, contrast, and number, and studied our implementation by comparing the lesion detectability from a nonprewhitening (NPW) model observer between different reconstructions at different exposure levels, and by estimating the instrument sensitivity to detect changes in dose. METHODS: Designed to fit into QRM anthropomorphic phantoms, our search challenge phantom is a cylindrical insert 10 cm wide and 4 cm thick, embedded with 12 000 lesions (nominal width of 0.6 mm, height of 0.8 mm, and contrast of -350 HU), and was fabricated using PixelPrint, a 3D printing technique. The insert was scanned alone at a high dose to assess printing accuracy. To evaluate lesion detectability, the insert was placed in a QRM thorax phantom and scanned from 50 to 625 mAs with increments of 25 mAs, once per exposure level, and the average of all exposure levels was used as high-dose reference. Scans were reconstructed with three different settings: filtered-backprojection (FBP) with Br40 and Br59, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) with strength level 5 and Br59 kernel. An NPW model observer was used to search for lesions, and detection performance of different settings were compared using area under the exponential transform of free response ROC curve (AUC). Using propagation of uncertainty, the sensitivity to changes in dose was estimated by the percent change in exposure due to one standard deviation of AUC, measured from 5 repeat scans at 100, 200, 300, and 400 mAs. RESULTS: The printed insert lesions had an average position error of 0.20 mm compared to printing reference. As the exposure level increases from 50 mAs to 625 mAs, the lesion detectability AUCs increase from 0.38 to 0.92, 0.42 to 0.98, and 0.41 to 0.97 for FBP Br40, FBP Br59, and SAFIRE Br59, respectively, with a lower rate of increase at higher exposure level. FBP Br59 performed best with AUC 0.01 higher than SAFIRE Br59 on average and 0.07 higher than FBP Br40 (all P < 0.001). The standard deviation of AUC was less than 0.006, and the sensitivity to detect changes in mAs was within 2% for FBP Br59. CONCLUSIONS: Our 3D-printed search challenge phantom with 12 000 submillimeter lesions, together with an NPW model observer, provide an efficient CT detectability assessment method that is sensitive to subtle effects in reconstruction and is sensitive to small changes in dose.

Circ_0044235 regulates the development of osteoarthritis by the modulation of miR-375/PIK3R3 axis.

BACKGROUND: Circular RNAs (circRNAs) play an important role in osteoarthritis (OA). However, the role of circRNA in OA is still unclear. Here, we explored the role and mechanism of circ_0044235 in OA. METHODS: CHON-001 cells were treated with IL-1ß to establish OA model in vitro. The levels of circ_0044235, miR-375 and phosphoinositide 3-kinase (PI3K) regulatory subunit 3 (PIK3R3) were detected by quantitative real-time PCR. Cell count kit-8 assay and flow cytometry assay were used to detect cell viability and apoptosis. The concentrations of inflammation factors were determined by enzyme-linked immunosorbent assay. Western blot was used to detect protein levels. The interaction between miR-375 and circ_0044235 or PIK3R3 was analyzed by dual-luciferase reporter assay and RNA immunoprecipitation assay. RESULTS: Circ_0044235 was significantly decreased in OA cartilage tissue and IL-1ß-treated CHON-001 cells. Overexpression of circ_0044235 promoted IL-1ß-stimulated CHON-001 cell viability and inhibited apoptosis, inflammation, and extracellular matrix (ECM) degradation. In mechanism analysis, circ_0044235 could act as a sponge for miR-375 and positively regulate PIK3R3 expression. In addition, miR-375 ameliorated the effect of circ_0044235 overexpression on IL-1ß-mediated CHON-001 cells injury. In addition, miR-375 inhibition mitigated IL-1ß-induced CHON-001 cell injury, while PIK3R3 silencing restored the effect. CONCLUSION: Circ_0044235 knockdown alleviated IL-1ß-induced chondrocytes injury by regulating miR-375/PIK3R3 axis, confirming that circ_0044235 might be a potential target for OA treatment.

Clozapine-Induced Severe Toxicity: Exploring the Pharmacokinetic Profile of Clozapine and Its Significance in Hemodynamic Instability - A Case Report.

Hemodynamic instability in patients with clozapine intoxication can indirectly reflect the serum concentration of clozapine.We have described a case of a 32-year-old pregnant woman who developed life-threatening clozapine toxicity at 28 weeks of gestation. The levels of clozapine and norclozapine in the serum were high. We initiated hemoperfusion(HP) and other detoxification therapies to remove the drug. The patient had severely dilated peripheral blood vessels, which led to cardiac symptoms such as fatal hypotension and uncontrollable tachycardia, resulting in very high cardiac output and elevated Central venous oxygen saturation (ScvO2). Pharmacological intervention significantly improved the hemodynamics.In light of our observations in the ongoing case, we posit that evaluating hemodynamic parameters before and after blood detoxification could serve as a valuable means to gauge effectiveness and provide guidance for treatment.

Patient-derived PixelPrint phantoms for evaluating clinical imaging performance of a deep learning CT reconstruction algorithm.

Objective: Deep learning reconstruction (DLR) algorithms exhibit object-dependent resolution and noise performance. Thus, traditional geometric CT phantoms cannot fully capture the clinical imaging performance of DLR. This study uses a patient-derived 3D-printed PixelPrint lung phantom to evaluate a commercial DLR algorithm across a wide range of radiation dose levels. Approach: The lung phantom used in this study is based on a patient chest CT scan containing ground glass opacities and was fabricated using PixelPrint 3D-printing technology. The phantom was placed inside two different sized extension rings to mimic a small and medium sized patient and was scanned on a conventional CT scanner at exposures between 0.5 and 20 mGy. Each scan was reconstructed using filtered back projection (FBP), iterative reconstruction, and DLR at five levels of denoising. Image noise, contrast to noise ratio (CNR), root mean squared error (RMSE), structural similarity index (SSIM), and multi-scale SSIM (MS SSIM) were calculated for each image. Main Results: DLR demonstrated superior performance compared to FBP and iterative reconstruction for all measured metrics in both phantom sizes, with better performance for more aggressive denoising levels. DLR was estimated to reduce dose by 25-83% in the small phantom and by 50-83% in the medium phantom without decreasing image quality for any of the metrics measured in this study. These dose reduction estimates are more conservative compared to the estimates obtained when only considering noise and CNR with a non-anatomical physics phantom. Significance: DLR has the capability of producing diagnostic image quality at up to 83% lower radiation dose which can improve the clinical utility and viability of lower dose CT scans. Furthermore, the PixelPrint phantom used in this study offers an improved testing environment with more realistic tissue structures compared to traditional CT phantoms, allowing for structure-based image quality evaluation beyond noise and contrast-based assessments.

Development of a 3 MV coaxial peaking capacitor for large-scale electromagnetic pulse simulator.

Coaxial peaking capacitor is a key component in high-altitude electromagnetic pulse (EMP) simulators with fast front pulse output. It poses significant technical and engineering challenges in limiting radiation field amplitude and test space. This paper presents the design and testing of a 180 pF, 3 MV coaxial peaking capacitor with improved insulation performance. In the insulation design, the length of the dielectric film is extended to reduce the background electric field on the flashover path. The electric field threshold obtained from image diagnosis is used as a reference. During capacitor testing, the insulation characteristics are diagnosed using both direct and indirect methods. The voltage measured by a D-dot probe, the output waveform of the Marx generator in the primary source, and the radiation field waveform are analyzed to understand the flashover characteristics of the capacitor and to improve the reliability of the test results. The experimental results demonstrate that the peaking capacitor can operate stably at 3.0 MV. If flashover occurring on the dropping edge of the pulse is permitted, the operating voltage can be greater than 3.7 MV without significantly affecting the radiation field waveform. The analysis on the surface flashover morphology of the peaking capacitor reveals that the flashover mainly occurs at the dropping edge of the capacitor's waveform, indicating that the damage to the film is not serious. This research significantly increases the working voltage of coaxial peaking capacitors and contributes to the development of high-altitude EMP simulation technology.