Application value of individualized tube voltage, contrast injection, and adaptive statistical iterative reconstruction V algorithm based on body mass index in renal computed tomography angiography for radiation and iodinated contrast dose reduction.

OBJECTIVES: To explore the application value of body mass index (BMI)-based kilovoltage peak (kVp) selection and contrast injection protocol combined with different adaptive statistical iterative reconstruction V (ASIR-V) strengths in renal computed tomography angiography (CTA) in reducing radiation and contrast medium (CM) doses. METHODS: One-hundred renal CTA patients were prospectively enrolled and were divided into individualized kVp group (group A, n = 50) and conventional 100 kVp group (group B, n = 50), both with automatic tube current modulation and CM of Iohexol at 350 mgI/mL concentration. Group A: 70 kVp, noise index (NI) of 18 and CM dose rate of 17 mgI/kg/s for 10 s for BMI <25 kg/m2 patients; 80 kVp, NI = 17, and CM dose rate of 19 mgI/kg/s for 10 s for 25 kg/m2≤BMI≤30 kg/m2 patients. Group B: 100 kVp, 50 mL of CM at the flow rate of 4.5 mL/s. The objective image quality, effective radiation dose, CM dose, injection rate, and image quality were compared between the 2 groups. RESULTS: There was no significant difference in patient characteristics between the 2 groups (P > .05). Compared to group B, group A significantly reduced effective radiation dose by 28.4%, CM dose by 27.2%, and injection rate by 22.7% (all P < .001). The 2 groups had similar SD values in erector spine (P > .05). Group A had significantly higher CT values, SNR, and CNR values of the renal arteries than group B (all P < .001). The 2 radiologists had excellent agreement (Kappa value > 0.8) in the subjective scores of renal CTA images and showed no statistically significant difference between the 2 groups (4.57 ± 0.42 vs 4.41 ± 0.49) (P > .05). CONCLUSIONS: BMI-based scan and reconstruction protocol in renal CTA significantly reduces radiation and contrast doses while maintaining diagnostic image quality. ADVANCES IN KNOWLEDGE: (i) BMI-based individualized tube voltage selection and contrast injection protocol in renal CTA reduces both radiation and contrast doses over conventional protocol. (ii) The combination of lower kVp and higher weight ASIR-V maybe used to improve image quality in terms of contrast enhancement and image noise under lower radiation and contrast dose conditions. (iii) Renal CTA of normal size (BMI ≤ 30 kg/m2) patients acquired at low radiation dosage and low iodine contrast dose through the combination of low tube voltage and ASIR-V algorithm achieves excellent diagnostic image quality with a good inter-rater agreement.

Exosomal miR-1a-3p derived from glucocorticoid-stimulated M1 macrophages promotes the adipogenic differentiation of BMSCs in glucocorticoid-associated osteonecrosis of the femoral head by targeting Cebpz.

BACKGROUND: By interacting with bone marrow mesenchymal stem cells (BMSCs) and regulating their function through exosomes, bone macrophages play crucial roles in various bone-related diseases. Research has highlighted a notable increase in the number of M1 macrophages in glucocorticoid-associated osteonecrosis of the femoral head (GA-ONFH). Nevertheless, the intricate crosstalk between M1 macrophages and BMSCs in the glucocorticoid-stimulated environment has not been fully elucidated, and the underlying regulatory mechanisms involved in the occurrence of GA-ONFH remain unclear. METHODS: We employed in vivo mouse models and clinical samples from GA-ONFH patients to investigate the interactions between M1 macrophages and BMSCs. Immunofluorescence staining was used to assess the colocalization of M1 macrophages and BMSCs. Flow cytometry and transcriptomic analysis were performed to evaluate the impact of exosomes derived from normal (n-M1) and glucocorticoid-stimulated M1 macrophages (GC-M1) on BMSC differentiation. Additionally, miR-1a-3p expression was altered in vitro and in vivo to assess its role in regulating adipogenic differentiation. RESULTS: In vivo, the colocalization of M1 macrophages and BMSCs was observed, and an increase in M1 macrophage numbers and a decrease in bone repair capabilities were further confirmed in both GA-ONFH patients and mouse models. Both n-M1 and GC-M1 were identified as contributors to the inhibition of osteogenic differentiation in BMSCs to a certain extent via exosome secretion. More importantly, exosomes derived from GC-M1 macrophages exhibited a heightened capacity to regulate the adipogenic differentiation of BMSCs, which was mediated by miR-1a-3p. In vivo and in vitro, miR-1a-3p promoted the adipogenic differentiation of BMSCs by targeting Cebpz and played an important role in the onset and progression of GA-ONFH. CONCLUSION: We demonstrated that exosomes derived from GC-M1 macrophages disrupt the balance between osteogenic and adipogenic differentiation in BMSCs, contributing to the pathogenesis of GA-ONFH. Inhibiting miR-1a-3p expression, both in vitro and in vivo, significantly mitigates the preferential adipogenic differentiation of BMSCs, thus slowing the progression of GA-ONFH. These findings provide new insights into the regulatory mechanisms underlying GA-ONFH and highlight potential therapeutic targets for intervention.

A gelatin methacryloyl (GelMA) treated with gallic acid and coated with specially designed nanoparticles derived from ginseng enhances the healing of wounds in diabetic rats.

Due to persistent inflammation and oxidative stress reactions, achieving drug absorption in diabetic wounds is challenging. To overcome this problem, our article presents a composite hydrogel, GelMA-GA/DMOG@GDNP, which consists of gelatin methacryloyl (GelMA) treated with gallic acid (GA) and encapsulating ginseng-derived nanoparticles (GDNPs) loaded with dimethyloxallyl glycine (DMOG). The composite hydrogel demonstrates excellent biocompatibility. In laboratory settings, the hydrogel inhibits the production of nitric oxide synthase 2 (iNOS) in mouse immune cells (RAW264.7 cells), enhances the growth and migration of mouse connective tissue cells (L929 cells) and human endothelial cells (HUVECs), and promotes tube formation in HUVECs. In a rat model of type 1 diabetes-induced wounds, the composite hydrogel attenuates inflammatory reactions, facilitates the formation of fibres and blood vessels, accelerates wound healing, and elucidates specific pathway mechanisms through transcriptome sequencing. Therefore, the GelMA-GA/DMOG@GDNP hydrogel can serve as a safe and efficient wound dressing to regulate the inflammatory response, promote collagen fiber and blood vessel formation, and accelerate wound healing. These findings suggest that utilizing this multifunctional engineered nanoparticle-loaded hydrogel in a clinical setting may be a promising strategy for diabetic wound healing.

Early depletion of M1 macrophages retards the progression of glucocorticoid-associated osteonecrosis of the femoral head.

Inflammation stands as a pivotal factor in the pathogenesis of glucocorticoid-associated osteonecrosis of the femoral head (GA-ONFH). However, the vital role played by M1 macrophages, the principal constituents of the inflammatory process, remains largely underexplored. In this study, we employed reverse transcription-quantitative polymerase chain Reaction (RT-PCR), western blot, and flow cytometry to assess the impact of M1-conditioned medium on cultures of mouse bone marrow-derived mesenchymal stem cells (BMSCs) and Murine Long bone Osteocyte-Y4 (MLO-Y4) in vitro. Moreover, we quantified the levels of inflammatory cytokines in the M1-conditioned medium through the employment of an enzyme-linked immunosorbent assay (ELISA). For in vivo analysis, we examined M1 macrophages and investigated the NF-kB signaling pathway in specimens obtained from the femoral heads of animals and humans. We found that the number of M1 macrophages in the femoral head of GA-ONFH patients grew significantly, and in the mice remarkably increase, maintaining high levels in the intramedullary. In vitro, the M1 macrophage-conditioned medium elicited apoptosis in BMSCs and MLO-Y4 cells, shedding light on the intricate interplay between macrophages and these cell types. The presence of TNF-α within the M1-conditioned medium activated the NF-κB pathway, providing mechanistic insight into the apoptotic induction. Moreover, employing a robust rat macrophage clearance model and GA-ONFH model, we demonstrated a remarkable attenuation in TNF-α expression and NF-kB signaling subsequent to macrophage clearance. This pronounced reduction engenders diminished cellular apoptosis and engenders a decelerated trajectory of GA-ONFH progression. In conclusion, our study reveals the crucial involvement of M1 macrophages in the pathogenesis of GA-ONFH, highlighting their indispensable role in disease progression. Furthermore, early clearance emerges as a promising strategy for impeding the development of GA-ONFH.

The value of using a deep learning image reconstruction algorithm of thinner slice thickness to balance the image noise and spatial resolution in low-dose abdominal CT.

Background: Traditional reconstruction techniques have certain limitations in balancing image quality and reducing radiation dose. The deep learning image reconstruction (DLIR) algorithm opens the door to a new era of medical image reconstruction. The purpose of the study was to evaluate the DLIR images at 1.25 mm thickness in balancing image noise and spatial resolution in low-dose abdominal computed tomography (CT) in comparison with the conventional adaptive statistical iterative reconstruction-V at 40% strength (ASIR-V40%) at 5 and 1.25 mm. Methods: This retrospective study included 89 patients who underwent low-dose abdominal CT. Five sets of images were generated using ASIR-V40% at a 5 mm slice thickness and 1.25 mm (high-resolution) with DLIR at 1.25 mm using 3 strengths: low (DLIR-L), medium (DLIR-M), and high (DLIR-H). Qualitative evaluation was performed for image noise, artifacts, and visualization of small structures, while quantitative evaluation was performed for standard deviation (SD), signal-to-noise ratio (SNR), and spatial resolution (defined as the edge rising slope). Results: At 1.25 mm, DLIR-M and DLIR-H images had significantly lower noise (SD in fat: 14.29±3.37 and 9.65±3.44 HU, respectively), higher SNR for liver (3.70±0.78 and 5.64±1.20, respectively), and higher overall image quality (4.30±0.44 and 4.67±0.40, respectively) than did the respective values in ASIR-V40% images (20.60±4.04 HU, 2.60±0.63, and 3.77±0.43; all P values <0.05). Compared with the 5 mm ASIR-V40% images, the 1.25 mm DLIR-H images had lower noise (SD: 9.65±3.44 vs. 13.63±10.03 HU), higher SNR (5.64±1.20 vs. 4.69±1.28), and higher overall image quality scores (4.67±0.40 vs. 3.94±0.46) (all P values <0.001). In addition, DLIR-L, DLIR-M, and DLIR-H images had a significantly higher spatial resolution in terms of edge rising slope (59.66±21.46, 58.52±17.48, and 59.26±13.33, respectively, vs. 33.79±9.23) and significantly higher image quality scores in the visualization of fine structures (4.43±0.50, 4.41±0.49, and 4.38±0.49, respectively vs. 2.62±0.49) than did the 5 mm ASIR-V40 images. Conclusions: The 1.25 mm DLIR-M and DLIR-H images had significantly reduced image noise and improved SNR and overall image quality compared to the 1.25 mm ASIR-V40% images, and they had significantly improved the spatial resolution and visualization of fine structures compared to the 5 mm ASIR-V40% images. DLIR-H images had further reduced image noise compared with the 5 mm ASIR-V40% images, and DLIR-H was the most effective technique at balancing the image noise and spatial resolution in low-dose abdominal CT.

Image quality improvement in low-dose chest CT with deep learning image reconstruction.

OBJECTIVES: To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low-dose chest CT in comparison with 40% adaptive statistical iterative reconstruction-Veo (ASiR-V40%) algorithm. METHODS: This retrospective study included 86 patients who underwent low-dose CT for lung cancer screening. Images were reconstructed with ASiR-V40% and DLIR at low (DLIR-L), medium (DLIR-M), and high (DLIR-H) levels. CT value and standard deviation of lung tissue, erector spinae muscles, aorta, and fat were measured and compared across the four reconstructions. Subjective image quality was evaluated by two blind readers from three aspects: image noise, artifact, and visualization of small structures. RESULTS: The effective dose was 1.03 ± 0.36 mSv. There was no significant difference in CT values of erector spinae muscles and aorta, whereas the maximum difference for lung tissue and fat was less than 5 HU among the four reconstructions. Compared with ASiR-V40%, the DLIR-L, DLIR-M, and DLIR-H reconstructions reduced the noise in aorta by 11.44%, 33.03%, and 56.1%, respectively, and had significantly higher subjective quality scores in image artifacts (all p < 0.001). ASiR-V40%, DLIR-L, and DLIR-M had equivalent score in visualizing small structures (all p > 0.05), whereas DLIR-H had slightly lower score. CONCLUSIONS: Compared with ASiR-V40%, DLIR significantly reduces image noise in low-dose chest CT. DLIR strength is important and should be adjusted for different diagnostic needs in clinical application.

A study of using a deep learning image reconstruction to improve the image quality of extremely low-dose contrast-enhanced abdominal CT for patients with hepatic lesions.

OBJECTIVE: To investigate the feasibility of using deep learning image reconstruction (DLIR) to significantly reduce radiation dose and improve image quality in contrast-enhanced abdominal CT. METHODS: This was a prospective study. 40 patients with hepatic lesions underwent abdominal CT using routine dose (120kV, noise index (NI) setting of 11 with automatic tube current modulation) in the arterial-phase (AP) and portal-phase (PP), and low dose (NI = 24) in the delayed-phase (DP). All images were reconstructed at 1.25 mm thickness using ASIR-V at 50% strength. In addition, images in DP were reconstructed using DLIR in high setting (DLIR-H). The CT value and standard deviation (SD) of hepatic parenchyma, spleen, paraspinal muscle and lesion were measured. The overall image quality includes subjective noise, sharpness, artifacts and diagnostic confidence were assessed by two radiologists blindly using a 5-point scale (1, unacceptable and 5, excellent). Dose between AP and DP was compared, and image quality among different reconstructions were compared using SPSS20.0. RESULTS: Compared to AP, DP significantly reduced radiation dose by 76% (0.76 ± 0.09 mSv vs 3.18 ± 0.48 mSv), DLIR-H DP images had lower image noise (14.08 ± 2.89 HU vs 16.67 ± 3.74 HU, p < 0.001) but similar overall image quality score as the ASIR-V50% AP images (3.88 ± 0.34 vs 4.05 ± 0.44, p > 0.05). For the DP images, DLIR-H significantly reduced image noise in hepatic parenchyma, spleen, muscle and lesion to (14.77 ± 2.61 HU, 14.26 ± 2.67 HU, 14.08 ± 2.89 HU and 16.25 ± 4.42 HU) from (24.95 ± 4.32 HU, 25.42 ± 4.99 HU, 23.99 ± 5.26 HU and 27.01 ± 7.11) with ASIR-V50%, respectively (all p < 0.001) and improved image quality score (3.88 ± 0.34 vs 2.87 ± 0.53; p < 0.05). CONCLUSION: DLIR-H significantly reduces image noise and generates images with clinically acceptable quality and diagnostic confidence with 76% dose reduction. ADVANCES IN KNOWLEDGE: (1) DLIR-H yielded a significantly lower image noise, higher CNR and higher overall image quality score and diagnostic confidence than the ASIR-V50% under low signal conditions. (2) Our study demonstrated that at 76% lower radiation dose, the DLIR-H DP images had similar overall image quality to the routine-dose ASIR-V50% AP images.

Treatment response prediction of rehabilitation program in children with cerebral palsy using radiomics strategy: protocol for a multicenter prospective cohort study in west China.

BACKGROUND: Cerebral palsy (CP) is a major cause of chronic childhood disability worldwide, causing activity limitation as well as impairments in sensation, cognition, and communication. Leveraging biomarkers to establish individualized predictions of future treatment responses will be of great value. We aim to develop and validate a model that can be used to predict the individualized treatment response in Children with CP. METHODS: A multicenter prospective cohort study will be conducted in 4 hospitals in west China. One hundred and thirty children with CP will be recruited and undergo clinical assessment using the Peabody Developmental Motor Scales, Manual Ability Classification System (MACS), Hand Assessment for Infants (HAI), Assisting Hand Assessment (AHA), and Gross Motor Function Classification System (GMFCS). The data collected will include MRI image, clinical status, and socioeconomic status. The clinical information and MRI features extracted using radiomics strategy will be combined for exploratory analysis. The accuracy, sensitivity, and specificity of the model will be assessed using multiple modeling methodologies. Internal and external validation will be used to evaluate the performance of the radiomics model. DISCUSSION: We hypothesized that the findings from this study could provide a critical step towards the prediction of treatment response in children with CP, which could also complement other biomarkers in the development of precision medicine approaches for this severe disorder. TRIAL REGISTRATION: The study was registered with clinicaltrials.gov (NCT02979743).

Isolated periventricular pseudocysts do not affect white matter microstructure development in neonatal stage: A retrospective case-control diffusion tensor imaging study.

BACKGROUND AND PURPOSE: Periventricular pseudocysts (PVPCs) are cystic cavities originating from the germinal matrix. The effects of PVPCs on the development of white matter (WM) in neonates remain unclear. This study aimed to characterise WM microstructural variations in neonates with PVPCs with and without additional abnormities on MRI. MATERIALS AND METHODS: Neonates with PVPCs and controls with no MRI abnormalities were retrospectively enrolled. Test subjects were divided into groups 1 (isolated PVPCs) and 2 (PVPCs with additional MRI abnormalities). The PVPC MRI features collected included lateralisation, locularity, anatomic location, and the maximum anteroposterior diameter. Diffusion tensor imaging (DTI)-derived fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were compared between the PVPC and control groups using tract-based spatial statistics. RESULTS: Thirty-eight neonates with PVPCs and 60 controls were enrolled. Groups 1 and 2 contained 15 and 23 subjects, respectively. The additional MRI findings in group 2 included intracranial haemorrhage, punctate WM lesions, hypoxic-ischaemic encephalopathy, and acute cerebral infarction. No significant differences were found in PVPC MRI features between the 2 test groups. Compared to controls, no significant changes in DTI metrics were observed in group 1 neonates; whereas extensive WM regions with decreased FA, increased RD, and unchanged/increased AD were found in group 2. CONCLUSIONS: Isolated PVPCs are not independently correlated with WM microstructural variations in neonates. This result provides further evidence for supporting the benign outcome of fetuses with isolated PVPCs.

Extremely low-frequency electromagnetic fields enhance the proliferation and differentiation of neural progenitor cells cultured from ischemic brains.

In the mammalian brain, neurogenesis persists throughout the embryonic period and adulthood in the subventricular zone of the lateral ventricle and the granular zone (dentate gyrus) of the hippocampus. Newborn neural progenitor cells (NPCs) in the two regions play a critical role in structural and functional plasticity and neural regeneration after brain injury. Previous studies have reported that extremely low-frequency electromagnetic fields (ELF-EMF) could promote osteogenesis, angiogenesis, and cardiac stem cells' differentiation, which indicates that ELF-EMF might be an effective tool for regenerative therapy. The present studies were carried out to examine the effects of ELF-EMF on hippocampal NPCs cultured from embryonic and adult ischemic brains. We found that exposure to ELF-EMF (50 Hz, 0.4 mT) significantly enhanced the proliferation capability both in embryonic NPCs and in ischemic NPCs. Neuronal differentiation was also enhanced after 7 days of cumulative ELF-EMF exposure, whereas glial differentiation was not influenced markedly. The expression of phosphorylated Akt increased during the proliferation process when ischemic NPCs were exposed to ELF-EMF. However, blockage of the Akt pathway abolished the ELF-EMF-induced proliferation of ischemic NPCs. These data show that ELF-EMF promotes neurogenesis of ischemic NPCs and suggest that this effect may occur through the Akt pathway.Video abstract, Supplemental Digital Content 1, http://links.lww.com/WNR/A347.

Recombinant ADAMTS13 reduces tissue plasminogen activator-induced hemorrhage after stroke in mice.

OBJECTIVE: Tissue plasminogen activator (tPA) is approved for treatment of acute ischemic stroke, but it increases the risk of cerebral hemorrhage. Accumulating evidence suggests that von Willebrand factor (VWF) plays a pivotal role in thrombus formation and microcirculatory disturbances after ischemic stroke. By cleaving VWF, ADAMTS13 (a disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13) protects mice from stroke. Therefore, we hypothesized that recombinant ADAMTS13 (rADAMTS13) could increase the safety of tPA thrombolysis in stroke. METHODS: We examined blood-brain barrier (BBB) permeability after intraventricular injection of tPA, VWF, and rADAMTS13 in nonischemic mice. We investigated the role of rADAMTS13 on reducing tPA-induced BBB dysfunction and cerebral hemorrhage in a mouse stroke model. RESULTS: Intraventricular injection of tPA or VWF under nonischemic conditions resulted in a significant increase in BBB permeability. In contrast, rADAMTS13 blocked both tPA- and VWF-induced BBB opening. BBB disruption following stroke was exacerbated by intravenous administration of tPA, but this was attenuated by injection of rADAMTS13. Correspondingly, tPA-associated hemorrhage after stroke was significantly reduced by rADAMTS13. The antihemorrhagic effect of rADAMTS13 was reversed by injection of recombinant VWF. We also showed that rADAMTS13 inhibited tPA-mediated upregulation of vascular endothelial growth factor (VEGF) in vascular endothelium after stroke. The upregulation of VEGF was suppressed by either an Akt inhibitor wortmannin or a Rho kinase inhibitor fasudil. Furthermore, rADAMTS13 downregulated tPA-induced phosphorylation of Akt and activation of RhoA. INTERPRETATION: These findings demonstrate that the VWF-cleaving protease rADAMTS13 reduced tPA-induced hemorrhage by regulating BBB integrity, and suggest that this effect may occur through the Akt/RhoA-mediated VEGF pathways.