Improving spatial resolution and diagnostic confidence with thinner slice and deep learning image reconstruction in contrast-enhanced abdominal CT.

OBJECTIVE: To evaluate image quality and diagnostic confidence improvement using a thin slice and a deep learning image reconstruction (DLIR) in contrast-enhanced abdominal CT. METHODS: Forty patients with hepatic lesions in enhanced abdominal CT were retrospectively analyzed. Images in the portal phase were reconstructed at 5 mm and 1.25 mm slice thickness using the 50% adaptive statistical iterative reconstruction (ASIR-V) (ASIR-V50%) and at 1.25 mm using DLIR at medium (DLIR-M) and high (DLIR-H) settings. CT number and standard deviation of the hepatic parenchyma, spleen, portal vein, and subcutaneous fat were measured, and contrast-to-noise ratio (CNR) was calculated. Edge-rise-slope (ERS) was measured on the portal vein to reflect spatial resolution and the CT number skewness on liver parenchyma was calculated to reflect image texture. Two radiologists blindly assessed the overall image quality including subjective noise, image contrast, visibility of small structures using a 5-point scale, and object sharpness and lesion contour using a 4-point scale. RESULTS: For the 1.25-mm images, DLIR significantly reduced image noise, improved CNR and overall subjective image quality compared to ASIR-V50%. Compared to the 5-mm ASIR-V50% images, DLIR images had significantly higher scores in the visibility and contour for small structures and lesions; as well as significantly higher ERS and lower CT number skewness. At a quarter of the signal strength, the 1.25-mm DLIR-H images had a similar subjective noise score as the 5-mm ASIR-V50% images. CONCLUSION: DLIR significantly reduces image noise and maintains a more natural image texture; image spatial resolution and diagnostic confidence can be improved using thin slice images and DLIR in abdominal CT. KEY POINTS: • DLIR further reduces image noise compared with ASIR-V while maintaining favorable image texture. • In abdominal CT, thinner slice images improve image spatial resolution and small object visualization but suffer from higher image noise. • Thinner slice images combined with DLIR in abdominal CT significantly suppress image noise for detecting low-density lesions while significantly improving image spatial resolution and overall image quality.

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.

Associations of gestational age and birth anthropometric indicators with brain white matter maturation in full-term neonates.

Newborn assessments, including gestational age (GA) and anthropometric measurements (birth weight, crown-heel length, head circumference) are routinely performed in pediatric settings, being used as important indicators in assessing neonatal development. Close associations of these birth indicators with later cognitive abilities were also reported. However, specific associations of these indicators with white matter (WM) development during the neonatal period remain unclear, as well as the extent to which they influence WM maturation. To address this issue, 51 full-term neonates (GA range, 37-42 weeks) with no abnormalities on MRI were retrospectively recruited. Specific correlations between birth indicators and WM maturation, quantified by diffusion tensor imaging (DTI)-metrics (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity), were identified by using DTI tract-based spatial statistics and automated fiber-tract quantification. Our findings suggest that (a) higher GA, birth weight, and crown-heel length may indicate greater WM maturation in full-term neonates, while head circumference presented weak correlation with WM maturation during early newborn period; (b) among the four indicators examined, GA was the one most associated with WM maturation. We believe that this study advances our knowledge of specific correlations between birth indicators and neonatal brain development and provides a valuable reference for future neonatal studies.

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.

Room-temperature ligand-free Pd/C-catalyzed C-S bond formation: synthesis of 2-substituted benzothiazoles.

The synthesis of 2-substituted benzothiazoles has been achieved via cyclization of o-iodothiobenzanilide derivatives using Pd/C as the catalyst at room temperature. The protocol is ligand-free, additive-free, and high-yielding and involves very mild conditions.

Pleiotropic effects of nitric oxide sustained-release system for peripheral nerve repair.

The regenerative microenvironment after peripheral nerve injury is imbalanced and difficult to rebalance, which is mainly affected by inflammation, oxidative stress, and inadequate blood supply. The difficulty in remodeling the nerve regeneration microenvironment is the main reason for slow nerve regeneration. Traditional drug treatments have certain limitations, such as difficulty in penetrating the blood-nerve barrier and lack of pleiotropic effects. Therefore, there is an urgent need to build multifunctional nerve grafts that can effectively regulate the regenerative microenvironment and promote nerve regeneration. Nitric oxide (NO), a highly effective gas transmitter with diatomic radicals, is an important regulator of axonal growth and migration, synaptic plasticity, proliferation of neural precursor cells, and neuronal survival. Moreover, NO provides potential anti-inflammation, anti-oxidation, and blood vessel promotion applications. However, excess NO may cause cell death and neuroinflammatory cell damage. The prerequisite for NO treatment of peripheral nerve injury is that it is gradually released over time. In this study, we constructed an injectable NO slow-release system with two main components, including macromolecular NO donor nanoparticles (mPEG-P(MSNO-EG) nanoparticles, NO-NPs) and a carrier for the nanoparticles, mPEG-PA-PP injectable temperature-sensitive hydrogel. Due to the multiple physiological regulation of NO and better physiological barrier penetration, the conduit effectively regulates the inflammatory response and oxidative stress of damaged peripheral nerves, promotes nerve vascularization, and nerve regeneration and docking, accelerating the nerve regeneration process. STATEMENT OF SIGNIFICANCE: The slow regeneration speed of peripheral nerves is mainly due to the destruction of the regeneration microenvironment. Neural conduits with drug delivery capabilities have the potential to improve the microenvironment of nerve regeneration. However, traditional drugs are hindered by the blood nerve barrier and cannot effectively target the injured area. NO, an endogenous gas signaling molecule, can freely cross the blood nerve barrier and act on target cells. However, excessive NO can lead to cell apoptosis. In this study, a NO sustained-release system was constructed to regulate the microenvironment of nerve regeneration through various pathways and promote nerve regeneration.

Relationship between pericoronary adipose tissue attenuation value and image reconstruction parameters.

Rationale and objectives: To investigate the relationship between the pericoronary adipose tissue CT mean attenuation (PCATMA) measurement and image reconstruction parameters (adaptive statistical iterative reconstruction-veo (ASIR-V) percentage, kernel, and slice thickness). Materials and methods: One hundred and ninety-eight consecutive patients underwent CT coronary angiography at 100 kilovoltage peak (kVp) (n = 102) and 120 kVp (n = 96) were included. All scans were reconstructed by three means: 1. with 11 different ASIR-V percentages, standard kernel and 0.625 mm; 2. with soft, standard, detail, and bone kernels, 60 % ASIR-V, and 0.625 mm; 3. at 0.625 mm and 1.25 mm slice thickness, standard kernel and 60 % ASIR-V. PCATMA of the three main coronary arteries was calculated using a dedicated software. Linear regression, analysis of variance (ANOVA), Friedman test, and paired t-test were used for statistical analysis. Results: Linear regression of pooled average data showed that the PCATMA was positively and linearly correlated with the ASIR-V percentage (all R squared >0.99). Regression analysis of individual data showed that most R squared were greater than 0.8 or 0.9, but their slope consisted of a relatively wide range. The difference of PCATMA among different kernels for each coronary artery reached statistically significant levels (P < 0.001), particularly for the difference between standard and bone kernel. Most of the differences between 0.625 mm and 1.25 mm for LAD, LCX, and RCA at 100 kVp and 120 kVp reached statistical significance (P < 0.001). Conclusions: PCATMA correlates linearly with the strength of ASIR-V. Reconstruction kernel and slice thickness also affect PCATMA, especially for the sharp kernels.

A photothermal responsive system accelerating nitric oxide release to enhance bone repair by promoting osteogenesis and angiogenesis.

Managing bone defects remains a formidable clinical hurdle, primarily attributed to the inadequate orchestration of vascular reconstruction and osteogenic differentiation in both spatial and temporal dimensions. This challenge persists due to the constrained availability of autogenous grafts and the limited regenerative capacity of allogeneic or synthetic bone substitutes, thus necessitating continual exploration and innovation in the realm of functional and bioactive bone graft materials. While synthetic scaffolds have emerged as promising carriers for bone grafts, their efficacy is curtailed by deficiencies in vascularization and osteoinductive potential. Nitric oxide (NO) plays a key role in revascularization and bone tissue regeneration, yet studies related to the use of NO for the treatment of bone defects remain scarce. Herein, we present a pioneering approach leveraging a photothermal-responsive system to augment NO release. This system comprises macromolecular mPEG-P nanoparticles encapsulating indocyanine green (ICG) (NO-NPs@ICG) and a mPEG-PA-PP injectable thermosensitive hydrogel carrier. By harnessing the synergistic photothermal effects of near-infrared radiation and ICG, the system achieves sustained NO release, thereby activating the soluble guanylate cyclase (SGC)-cyclic guanosine monophosphate (cGMP) signaling pathway both in vitro and in vivo. This orchestrated cascade culminates in the facilitation of angiogenesis and osteogenesis, thus expediting the reparative processes in bone defects. In a nutshell, the NO release-responsive system elucidated in this study presents a pioneering avenue for refining the bone tissue microenvironment and fostering enhanced bone regeneration.

Improving image quality consistency and diagnostic accuracy in lower extremity CT angiography using a split-bolus contrast injection protocol.

OBJECTIVES: To evaluate the clinical value of using a split-bolus contrast injection protocol in improving image quality consistency and diagnostic accuracy in lower extremity CT angiography (CTA). METHODS: Fifty (mean age, 66 ± 12 years) and 39 (mean age, 66 ± 11 years) patients underwent CTA in the lower extremity arteries using split-bolus and fixed-bolus injection schemes, respectively. The objective and subjective image quality of the 2 groups were compared and the diagnostic efficacy for the degree of vessel stenosis was compared using digital subtraction angiography as the gold standard. A P < .05 was considered statistically significant. RESULTS: In comparison with the fixed-bolus scheme, the split-bolus scheme greatly improved the consistency of image quality of the low extremities by significantly increasing the arterial enhancement (337.87 ± 64.67HU vs. 254.74 ± 71.58HU, P < .001), signal-to-noise ratio (22.58 ± 11.64 vs. 7.14 ± 1.98, P < .001), and contrast-to-noise ratio (37.21 ± 10.46 vs. 31.10 ± 15.40, P = .041) in the infrapopliteal segment. The subjective image quality was better (P < .001) and the diagnostic accuracy was higher in the split-bolus group than in the fixed-bolus group (96.00% vs. 91.67%, P < .05, for diagnosing >50% stenosis, and 97.00% vs. 89.10%, P < .05, for diagnosing occlusion) for the infrapopliteal segment arteries. CONCLUSIONS: Compared with the fixed-bolus injection scheme, the split-bolus injection scheme improves the image quality consistency and diagnostic accuracy especially for the infrapopliteal segment arteries in lower extremity CTA. ADVANCES IN KNOWLEDGE: (1) The split-bolus injection scheme of CTA of the lower extremity arteries improves the overall image quality, uniformity of contrast enhancement. (2) Compared with the fixed-bolus injection scheme, the split-bolus injection scheme especially improves the infrapopliteal segment arteries image quality and diagnostic efficacy.

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.

Detection and characterization of urinary stones using material-specific images derived from contrast-enhanced dual-energy CT urography.

OBJECTIVE: To determine the accuracy of material-specific images derived from contrast-enhanced dual-energy CT urography (DECTU) in detecting and measuring urinary stones in comparison with that of unenhanced images and its utility in calcified stone differentiation. METHODS: 105 patients with 202 urinary stones (121 had confirmed composition by infrared spectroscopy) underwent triphasic (unenhanced, portal venous (VP) and excretory phase (EP)) DECTU. Material-specific images were derived in VP and EP with calcium-water, calcium-iodine and CaOxalate_Dihydrate (COD)-Hydroxyapatite (HAP) as basis material pairs. Stone number and size were recorded on unenhanced images and VP and EP material-specific images, where stone densities were also measured. Material densities of calcified stones (pure calcium oxalate [pCaO, n = 34], mixed calcium oxalate [mCaO, n = 14], mixed carbonate phosphate [mCaP, n = 70]) were compared and thresholds for differentiating these stones were determined using receiver operating characteristic analysis. RESULTS: All 202 urinary stones were detected on the unenhanced, calcium (water) and calcium (iodine) images in VP. While the detection rate was significantly decreased to 58 and 64% using calcium (water) and calcium (iodine) images in EP, respectively (all p < 0.001). Stone sizes measured on calcium (iodine) images in VP was similar to that of unenhanced images (10.6 vs 10.7 mm, p > 0.05). Significant differences in material densities were found among pCaO, mCaO and mCaP on COD(HAP) images with AUC of 0.72-0.74 for differentiating these stones. CONCLUSION: Material-specific images in VP derived from DECTU allow reliably detecting and measuring urinary tract stones in comparison with unenhanced images and can identify calcified stones with moderate diagnostic performance to provide potential 33% dose reduction. ADVANCES IN KNOWLEDGE: Material-specific images, especially the calcium (iodine) images in VP allow for reliable detection of urinary stones.Stone size measurement should be performed on the calcium (iodine) images in VP.Material density measurements on COD-HAP (VP) material decomposition images can be used to differentiate among pure calcium oxalate, mixed calcium oxalate and mixed carbonate phosphate stones with AUC of 0.72-0.74.

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.

The Added Value of Virtual Unenhanced Images Obtained From Dual-energy CT Urography in the Detection and Measurement of Urinary Stone.

OBJECTIVE: To evaluate the detection and quantification of urinary stones using virtual unenhanced images (VUE) at different phases and slice thickness in contrast-enhanced dual-energy CT Urography (DECTU) in comparison with true unenhanced images (TUE). METHODS: One hundred and twelve urinary stone patients who required triphasic DECTU were analyzed. Data were reconstructed as the followings: TUE images with 1.25 mm thickness (TUE portal venous phase VUE images with 1.25 and 5-mm thickness (VUE(VP)_1.25 mm and VUE(VP)_5 mm) and excretory phase VUE images with 1.25 and 5-mm thickness (VUE(EP)_1.25mm and VUE(EP)_5mm). The. The stones were divided into large (≥5 mm) and small stones. The detection rate, size and CT value of stones were assessed by 2 radiologists and statistically compared among the above groups. RESULTS: Two hundred and thirty urinary stones (163 large and 67 small stones) were detected on TUE_1.25 mm images. For large stones, the detection rate on VUE(VP)_1.25 mm, VUE(VP)_5 mm, VUE(EP)_1.25 mm and VUE(EP)_5 mm was 100%, 96.9%, 85.9%, and 80.4%; while for small stones, the rate was 77.6%, 37.3%, 46.3%, and 23.9%, respectively. VUE(VP) images significantly improved the stone detection rate compared with VUE(EP) images at both slice thicknesses. In general, VUE images identified stones with smaller sizes and lower Hounsfield units, but thinner slice thickness images reduced the inaccuracy. Inter-reader agreement of the stone detection revealed a k value range from 0.85 to 0.94 for TUE and VUE images. CONCLUSION: Large stones (≥5 mm) can reliably be detected on thin section VUE(VP) images with 33% radiation dose reduction. However, for small stones TUE remains superior. Stone size is underestimated on VUE images.

Low-dose CT urography using deep learning image reconstruction: a prospective study for comparison with conventional CT urography.

OBJECTIVES: To compare the image quality of low-dose CT urography (LD-CTU) using deep learning image reconstruction (DLIR) with conventional CTU (C-CTU) using adaptive statistical iterative reconstruction (ASIR-V). METHODS: This was a prospective, single-institutional study using the excretory phase CTU images for analysis. Patients were assigned to the LD-DLIR group (100kV and automatic mA modulation for noise index (NI) of 23) and C-ASIR-V group (100kV and NI of 10) according to the scan protocols in the excretory phase. Two radiologists independently assessed the overall image quality, artifacts, noise and sharpness of urinary tracts. Additionally, the mean CT attenuation, signal-to-noise ratio (SNR) and contrast-to-noise (CNR) in the urinary tracts were evaluated. RESULTS: 26 patients each were included in the LD-DLIR group (10 males and 16 females; mean age: 57.23 years, range: 33-76 years) and C-ASIR-V group (14 males and 12 females; mean age: 60 years, range: 33-77 years). LD-DLIR group used a significantly lower effective radiation dose compared with the C-ASIR-V group (2.01 ± 0.44 mSv vs 6.9 ± 1.46 mSv, p < 0.001). LD-DLIR group showed good overall image quality with average score >4 and was similar to that of the C-ASIR-V group. Both groups had adequate and similar attenuation value, SNR and CNR in most segments of urinary tracts. CONCLUSION: It is feasibility to provide comparable image quality while reducing 71% radiation dose in low-dose CTU with a deep learning image reconstruction algorithm compared to the conventional CTU with ASIR-V. ADVANCES IN KNOWLEDGE: (1) CT urography with deep learning reconstruction algorithm can reduce the radiation dose by 71% while still maintaining image quality.

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.

Exploring Variances of White Matter Integrity and the Glymphatic System in Simple Febrile Seizures and Epilepsy.

Background: Simple febrile seizures (SFS) and epilepsy are common seizures in childhood. However, the mechanism underlying SFS is uncertain, and the presence of obvious variances in white matter (WM) integrity and glymphatic function between SFS and epilepsy remain unclear. Therefore, this study aimed to investigate the differences in WM integrity and glymphatic function between SFS and epilepsy. Material and Methods: We retrospectively included 26 children with SFS, 33 children with epilepsy, and 28 controls aged 6-60 months who underwent magnetic resonance imaging (MRI). Tract-based spatial statistics (TBSS) were used to compare the diffusion tensor imaging (DTI) metrics of WM among the above-mentioned groups. T2-weighted imaging (T2WI) was used to segment the visible Virchow-Robin space (VRS) through a custom-designed automated method. VRS counts and volume were quantified and compared among the SFS, epilepsy, and control groups. Correlations of the VRS metrics and seizure duration and VRS metrics and the time interval between seizure onset and MRI scan were also investigated. Results: In comparison with controls, children with SFS showed no significant changes in fractional anisotropy (FA), axial diffusivity (AD), or radial diffusivity (RD) in the WM (P > 0.05). Decreased FA, unchanged AD, and increased RD were observed in the epilepsy group in comparison with the SFS and control groups (P < 0.05). Meanwhile, VRS counts were higher in the SFS and epilepsy groups than in the control group (VRS_SFS, 442.42 ± 74.58, VRS_epilepsy, 629.94 ± 106.55, VRS_control, 354.14 ± 106.58; P < 0.001), and similar results were found for VRS volume (VRS_SFS, 6,228.18 ± 570.74 mm3, VRS_epilepsy, 9,684.84 ± 7,292.66mm3, VRS_control, 4,007.22 ± 118.86 mm3; P < 0.001). However, VRS metrics were lower in the SFS group than in the epilepsy group (P < 0.001). In both SFS and epilepsy, VRS metrics positively correlated with seizure duration and negatively correlated with the course after seizure onset. Conclusion: SFS may not be associated with WM microstructural disruption; however, epilepsy is related to WM alterations. Seizures are associated with glymphatic dysfunction in either SFS or epilepsy.

A multi-view pyramid network for skull stripping on neonatal T1-weighted MRI.

Skull stripping or brain extraction on magnetic resonance imaging is a crucial step for structure analyses. In spite of good performances of conventional methods on adult brains, the skull stripping for T1-weighted imaging (T1WI) images on the neonatal brain remains a challenge because of the low image contrast. Therefore, this paper proposes a multi-view pyramid skull stripping network (PSSNet) for neonatal T1WI. To achieve superior skull stripping performance, the conventional pyramid scene parsing network was modified through (1) adding the spatial information of raw feature maps by squeezing the channel information during the feature extraction; (2) increasing the receptive field and adding boundary repair block instead of direct up-sampling; (3) obtaining the final mask through a fusion module on multi-view 2D slices. The 3D skull stripping problem was decomposed into multi-view 2D segmentation tasks to improve the efficiency. We enrolled T1WI images of 70 neonates from the local hospital and 7 infants from the publicly available dataset NeuroBrainS12 (MICCAI 2012). Images of 51 and 26 subjects were used for model training and validation. We compared the proposed method with 7 commonly used methods by using the Dice ratio, sensitivity, specificity, and efficiency. The proposed multi-view PSSNet with the highest Dice ratio (95.44-97.33%) was superior to other methods. Meanwhile, the sensitivity (93.19-97.02%), specificity (97.52-99.68%), and efficiency (8.59-9.30 s per subject) of the proposed method were comparable with the state-of-the-art method. In conclusion, the proposed skull stripping network was robust on neonatal T1WI datasets and feasible in clinical applications.

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.

Abnormal Gray Matter Structural Covariance Networks in Children With Bilateral Cerebral Palsy.

Bilateral cerebral palsy (BCP) is a common movement disorder in children, which often results in lifelong motor disability. One main symptom of BCP is the limitation of hand function in everyday activities. However, the neuroanatomical basis of this prominent hand impairment is yet to discover. Recent advances mainly focus on the lesions of BCP, but the views on the atypical development of cortical parcellations are extremely lacking. Here, in our study, neuroimaging with network analysis was employed to evaluate the changes of structural covariance networks (SCNs) in BCP children. We aimed to elucidate the alteration of SCNs based on cortical thickness (CT), and to reveal the relationship of CT and hand function in the participants with BCP. SCNs were constructed using covariance between regional CT, which was acquired from T1-weighted images of 19 children with BCP and 19 demographically matched healthy controls (HCs). Compared with HCs, BCP children showed increased CT in several regions involving the bilateral areas (lateral occipital, lingual, and fusiform) and right areas (cuneus, pericalcarine, inferior temporal, middle temporal, superior temporal, and insula). Decreased CT was found in the left superior temporal and right superior parietal cortices. Global network analyses revealed significantly decreased normalized clustering and small-worldness in the BCP network. The area under the curve (AUC) of global network measures varied slightly between the BCP and HC networks. The resistance of the both SCNs to the target and random attack showed no significant difference. Also, the BCP foci (right superior temporal and subtemporal cortex) showed a significantly negative correlation between the CT and manual ability. In this work, we identified the CT-based SCNs changes in children with BCP. The abnormal topological organization of SCNs was revealed, indicating abnormal CT, incongruous development of structural wiring, destructive nodal profiles of betweenness, and moved hub distribution in BCP children. This may provide a neuroanatomical hallmark of BCP in the developing brain. Therefore, our results may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.