Gold Nanoparticle-Optimized Computed Tomography Imaging Combined with Transcranial Magnetic Stimulation on Rehabilitation Training of Children with Cerebral Palsy

Traditional computed tomography (CT) contrast agents, such as iodine-containing small molecules (omnipaque), have limitations in some applications. The development of nanotechnology has made it possible to develop CT contrast agents based on this technology. In this study, a large number of surface functional groups of the fifth-generation polyamide-amine dendrimer (P5-NH2) were applied to functionally modify polyethylene glycol (PEG), targeting molecules, or drugs, which were used as the carrier of CT contrast agents. With the help of sodium borohydride (NaBH4), there was a rapid reduction. The fluorescein thiocyanate (FT) and PEG modified with lactobionic acid (PEG-LA) weres connected before gold coating to obtain gold nanoparticles coated with targeted dendrimer (Au(P5-LA)DENPs). In the experiment, the gold nanoparticles were characterized, and the liver cancer nude mouse model was established, so as to analyze the CT imaging performance of the material. Besides, the above was applied in the motor function of children with cerebral palsy, and the improvement effect of CT imaging combined with transcranial magnetic stimulation based on the preparation of nanomaterials on the movement function of children was analyzed and demonstrated with the help of graph theory. The results showed that the average particle size of gold nanoparticles was 1.88 nm. Within the range of 5 °C–50 °C and pH = 4–7, the physical properties of the aqueous solution of this material were stable. What’s more, the cell activity still exceeded 80% when the material concentration reached 2000 nm. The nude mouse model of liver cancer indicated that the CT imaging based on this material enhanced the image contrast effect of the tumor part, and the material had no obvious toxic and side effects. CT imaging based on the preparation of nanomaterials can promote transcranial magnetic stimulation to accelerate the efficiency of brain movement, accelerate the global and local information exchange and integration speed of brain network, thereby improving the movement function of children.

Negative effects of iodine-based contrast agent on renal function in patients with moderate reduced renal function hospitalized for COVID-19

Background Kidney disease and renal failure are associated with hospital deaths in patients with COVID − 19. We aimed to test if contrast enhancement affects short-term renal function in hospitalized COVID − 19 patients. Methods Plasma creatinine (P-creatinine) was measured on the day of computed tomography (CT) and 24 h, 48 h, and 4–10 days after CT. Contrast-enhanced (n = 142) and unenhanced (n = 24) groups were subdivided, based on estimated glomerular filtration rates (eGFR), > 60 and ≤ 60 ml/min/1.73 m2. Contrast-induced acute renal failure (CI-AKI) was defined as ≥27 μmol/L increase or a > 50% rise in P-creatinine from CT or initiation of renal replacement therapy during follow-up. Patients with renal replacement therapy were studied separately. We evaluated factors associated with a > 50% rise in P-creatinine at 48 h and at 4–10 days after contrast-enhanced CT. Results Median P-creatinine at 24–48 h and days 4–10 post-CT in patients with eGFR> 60 and eGFR≥30–60 in contrast-enhanced and unenhanced groups did not differ from basal values. CI-AKI was observed at 48 h and at 4–10 days post contrast administration in 24 and 36% (n = 5/14) of patients with eGFR≥30–60. Corresponding figures in the eGFR> 60 contrast-enhanced CT group were 5 and 5% respectively, (p < 0.037 and p < 0.001, Pearson χ2 test). In the former group, four of the five patients died within 30 days. Odds ratio analysis showed that an eGFR≥30–60 and 30-day mortality were associated with CK-AKI both at 48 h and 4–10 days after contrast-enhanced CT. Conclusion Patients with COVID − 19 and eGFR≥30–60 had a high frequency of CK-AKI at 48 h and at 4–10 days after contrast administration, which was associated with increased 30-day mortality. For patients with eGFR≥30–60, we recommend strict indications are practiced for contrast-enhanced CT. Contrast-enhanced CT had a modest effect in patients with eGFR> 60.

Facile Fabrication of BiF3: Ln (Ln = Gd, Yb, Er)@PVP Nanoparticles for High-Efficiency Computed Tomography Imaging

X-ray computed tomography (CT) has been widely used in clinical practice, and contrast agents such as Iohexol are often used to enhance the contrast of CT imaging between normal and diseased tissue. However, such contrast agents can have some toxicity. Thus, new CT contrast agents are urgently needed. Owing to the high atomic number (Z = 83), low cost, good biological safety, and great X-ray attenuation property (5.74 cm2 kg−1 at 100 keV), bismuth has gained great interest from researchers in the field of nano-sized CT contrast agents. Here, we synthesized BiF3: Ln@PVP nanoparticles (NPs) with an average particle size of about 380 nm. After coating them with polyvinylpyrrolidone (PVP), the BiF3: Ln@PVP NPs possessed good stability and great biocompatibility. Meanwhile, compared with the clinical contrast agent Iohexol, BiF3: Ln@PVP NPs showed superior in vitro CT imaging contrast. Subsequently, after in situ injection with BiF3: Ln@PVP NPs, the CT value of the tumor site after the injection was significantly higher than that before the injection (the CT value of the pre-injection and post-injection was 48.9 HU and 194.58 HU, respectively). The morphology of the gastrointestinal (GI) tract can be clearly observed over time after oral administration of BiF3: Ln@PVP NPs. Finally, the BiF3: Ln@PVP NPs were completely discharged from the GI tract of mice within 48 h of oral administration with no obvious damage to the GI tract. In summary, our easily synthesized BiF3: Ln@PVP NPs can be used as a potential clinical contrast agent and may have broad application prospects in CT imaging.

Purpura fulminans, Toxic Epidermal Necrolysis, and disseminated herpes simplex. A rare combination.

A 52-year-old, previously healthy woman, developed SJS, potentially due to a reaction to CT contrast, although still unknown. This developed into Toxic epidermal necrolysis, later unexpected multiorgan failure and Purpura fulminans. Autopsy demonstrates herpes simplex virus in the bladder and lungs on immunohistological staining.

Investigation of a Novel Deep Learning-Based Computed Tomography Perfusion Mapping Framework for Functional Lung Avoidance Radiotherapy

Functional lung avoidance radiation therapy aims to minimize dose delivery to the normal lung tissue while favoring dose deposition in the defective lung tissue based on the regional function information. However, the clinical acquisition of pulmonary functional images is resource-demanding, inconvenient, and technically challenging. This study aims to investigate the deep learning-based lung functional image synthesis from the CT domain. Forty-two pulmonary macro-aggregated albumin SPECT/CT perfusion scans were retrospectively collected from the hospital. A deep learning-based framework (including image preparation, image processing, and proposed convolutional neural network) was adopted to extract features from 3D CT images and synthesize perfusion as estimations of regional lung function. Ablation experiments were performed to assess the effects of each framework component by removing each element of the framework and analyzing the testing performances. Major results showed that the removal of the CT contrast enhancement component in the image processing resulted in the largest drop in framework performance, compared to the optimal performance (~12%). In the CNN part, all the three components (residual module, ROI attention, and skip attention) were approximately equally important to the framework performance; removing one of them resulted in a 3–5% decline in performance. The proposed CNN improved ~4% overall performance and ~350% computational efficiency, compared to the U-Net model. The deep convolutional neural network, in conjunction with image processing for feature enhancement, is capable of feature extraction from CT images for pulmonary perfusion synthesis. In the proposed framework, image processing, especially CT contrast enhancement, plays a crucial role in the perfusion synthesis. This CTPM framework provides insights for relevant research studies in the future and enables other researchers to leverage for the development of optimized CNN models for functional lung avoidance radiation therapy.