Demonstration of magnetic resonance Z-spectral imaging for fatty acid characterization of bone marrow at 3 T

Magnetic resonance Z-spectral imaging (ZSI) has emerged as a new approach to measure fat fraction (FF). However, its feasibility for fat spectral imaging remains to be elucidated. In this study, a single-slice ZSI sequence dedicated to fat spectral imaging was designed, and its capability for fatty acid characterization was investigated on peanut oil samples, a multiple-vial fat-water phantom with varied oil volumes, and vertebral body marrow in healthy volunteers and osteoporosis patients at 3 T. The peanut oil spectrum was also recorded with a 400-MHz NMR spectrometer. A Gaussian-Lorentzian sum model was used to resolve water and six fat signals of the pure oil sample or four fat signals of the fat-water phantom or vertebral bone marrow from Z spectra. Fat peak amplitudes were normalized to the total peak amplitude of water and all fat signals. Normalized fat peak amplitudes and FF were quantified and compared among vials of the fat-water phantom or between healthy volunteers and osteoporosis patients. An unpaired student's t-test and Pearson's correlation were conducted, with p less than 0.05 considered statistically significant. The results showed that the peanut oil spectra measured with the ZSI technique were in line with respective NMR spectra, with amplitudes of the six fat signal peaks significantly correlated between the two methods (y = x + 0.001, r = 0.996, p < 0.001 under a repetition time of 1.6 s; and y = 1.026x - 0.003, r = 0.996, p < 0.001 under a repetition time of 3.1 s). Moreover, ZSI-measured FF exhibited a significant correlation with prepared oil volumes (y = 0.876x + 1.290, r = 0.996, p < 0.001). The osteoporosis patients showed significantly higher normalized fat peak amplitudes and FF in the L4 vertebral body marrow than the healthy volunteers (all p < 0.01). In summary, the designed ZSI sequence is feasible for fatty acid characterization, and has the potential to facilitate the diagnosis and evaluation of diseases associated with fat alterations at 3 T.

The CT and MRI features of benign calvarium and skull base osteoblastoma

OBJECTIVE

We retrospectively reviewed the CT and MRI features of patients with benign osteoblastoma in the calvarium and skull base (CSBOB).

METHODS

Nine cases of pathologically confirmed benign CSBOB were analysed retrospectively. The patients had undergone CT and/or MRI. Tumour location, size, and imaging features were reviewed and recorded.

RESULTS

The patients included four males and five females with a mean age of 27.0 years (age 14-40 years). The tumours were located in the frontal bone in 3 patients, the occipital bone in 3 patients, and in the parietal bone, sphenoid bone, and skull base in 1 patient each. On CT, the tumours measured 5.1 ± 3.3 (1.8-8.4) cm. Seven tumours were shown to have caused expansile bony destruction with an eggshell appearance and varying degrees of calcification or matrix mineralization. Multiple septa were observed in 5 tumours. Intracranial growth was observed in 5 tumours. On MRI, 7 tumours showed heterogeneous hypo- to isointensity on T1WI. Heterogeneous high signal patterns with low signal rims and septa were observed in 6 tumours on T2WI, and 4 showed a fluid-fluid level. On contrast-enhanced imaging, 6 tumours showed peripheral and septal enhancement, and 2 showed the dural tail sign.

CONCLUSIONS

Benign CSBOB is a rare tumour characterized by expansile bony destruction, septa, a sclerotic rim and calcification or matrix mineralization on CT and MRI.

ADVANCES IN KNOWLEDGE

The findings from this study contribute to a better understanding of benign CSBOB and provide valuable imaging features that can aid in its diagnosis and differentiation from other tumours in the calvarium and skull base.

Correction: MnO2/Ce6 microbubble-mediated hypoxia modulation for enhancing sono-photodynamic therapy against triple negative breast cancer

Correction for 'MnO2/Ce6 microbubble-mediated hypoxia modulation for enhancing sono-photodynamic therapy against triple negative breast cancer' by Ping Li et al., Biomater. Sci., 2024, https://doi.org/10.1039/d3bm00931a.

MnO2/Ce6 microbubble-mediated hypoxia modulation for enhancing sono-photodynamic therapy against triple negative breast cancer

Sono-photodynamic therapy (SPDT) has emerged as a promising treatment modality for triple negative breast cancer (TNBC). However, the hypoxic tumor microenvironment hinders the application of SPDT. Herein, in this study, a multifunctional platform (MnO2/Ce6@MBs) was designed to address this issue. A sono-photosensitizer (Ce6) and a hypoxia modulator (MnO2) were loaded into microbubbles and precisely released within tumor tissues under ultrasound irradiation. MnO2in situ reacted with the excess H2O2 and H+ and produced O2 within the TNBC tumor, which alleviated hypoxia and augmented SPDT by increasing ROS generation. Meanwhile, the reaction product Mn2+ was able to achieve T1-weighted MRI for enhanced tumor imaging. Additionally, Ce6 and microbubbles served as a fluorescence imaging contrast agent and a contrast-enhanced ultrasound imaging agent, respectively. In in vivo anti-tumor studies, under the FL/US/MR imaging guidance, MnO2/Ce6@MBs combined with SPDT significantly reversed tumor hypoxia and inhibited tumor growth in 4T1-tumor bearing mice. This work presents a theragnostic system for reversing tumor hypoxia and enhancing TNBC treatment.

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection

Accurate detection and segmentation of brain tumors is critical for medical diagnosis. However, current supervised learning methods require extensively annotated images and the state-of-the-art generative models used in unsupervised methods often have limitations in covering the whole data distribution. In this paper, we propose a novel framework Two-Stage Generative Model (TSGM) that combines Cycle Generative Adversarial Network (CycleGAN) and Variance Exploding stochastic differential equation using joint probability (VE-JP) to improve brain tumor detection and segmentation. The CycleGAN is trained on unpaired data to generate abnormal images from healthy images as data prior. Then VE-JP is implemented to reconstruct healthy images using synthetic paired abnormal images as a guide, which alters only pathological regions but not regions of healthy. Notably, our method directly learned the joint probability distribution for conditional generation. The residual between input and reconstructed images suggests the abnormalities and a thresholding method is subsequently applied to obtain segmentation results. Furthermore, the multimodal results are weighted with different weights to improve the segmentation accuracy further. We validated our method on three datasets, and compared with other unsupervised methods for anomaly detection and segmentation. The DSC score of 0.8590 in BraTs2020 dataset, 0.6226 in ITCS dataset and 0.7403 in In-house dataset show that our method achieves better segmentation performance and has better generalization.

Application of Spinal Subtraction and Bone Background Fusion CTA in the Accurate Diagnosis and Evaluation of Spinal Vascular Malformations

BACKGROUND AND PURPOSE

Accurate pretreatment diagnosis and assessment of spinal vascular malformations using spinal CTA are crucial for patient prognosis, but the postprocessing reconstruction may not be able to fully depict the lesions due to the complexity inherent in spinal anatomy. Our purpose was to explore the application value of the spinal subtraction and bone background fusion CTA (SSBBF-CTA) technique in precisely depicting and localizing spinal vascular malformation lesions.

MATERIALS AND METHODS

In this retrospective study, patients (between November 2017 and November 2022) with symptoms similar to those of spinal vascular malformations were divided into diseased (group A) and nondiseased (group B) groups. All patients underwent spinal CTA using Siemens dual-source CT. Multiplanar reconstruction; routine bone subtraction, and SSBBF-CTA images were obtained using the snygo.via and ADW4.6 postprocessing reconstruction workstations. Multiple observers researched the following 3 aspects: 1) preliminary screening capability using original images with multiplanar reconstruction CTA, 2) the accuracy and stability of the SSBBF-CTA postprocessing technique, and 3) diagnostic evaluation of spinal vascular malformations using the 3 types of postprocessing images. Diagnostic performance was analyzed using receiver operating characteristic analysis, while reader or image differences were analyzed using the Wilcoxon signed-rank test or the Kruskal-Wallis rank sum test.

RESULTS

Forty-nine patients (groups A and B: 22 and 27 patients; mean ages, 44.0 [SD, 14.3] years and 44.6 [SD,15.2] years; 13 and 16 men) were evaluated. Junior physicians showed lower diagnostic accuracy and sensitivity using multiplanar reconstruction CTA (85.7% and 77.3%) than senior physicians (93.9% and 90.9%, 98% and 95.5%). Short-term trained juniors achieved SSBBF-CTA image accuracy similar to that of experienced physicians (P > .05). In terms of the visualization and localization of spinal vascular malformation lesions (nidus/fistula, feeding artery, and drainage vein), both multiplanar reconstruction and SSBBF-CTA outperformed routine bone subtraction CTA (P = .000). Compared with multiplanar reconstruction, SSBBF-CTA allowed less experienced physicians to achieve superior diagnostic capabilities (comparable with those of experienced radiologists) more rapidly (P < .05).

CONCLUSIONS

The SSBBF-CTA technique exhibited excellent reproducibility and enabled accurate pretreatment diagnosis and assessment of spinal vascular malformations with high diagnostic efficiency, particularly for junior radiologists.

A novel automatic segmentation method directly based on magnetic resonance imaging K-space data for auxiliary diagnosis of glioma

Background

The use of segmentation architectures in medical imaging, particularly for glioma diagnosis, marks a significant advancement in the field. Traditional methods often rely on post-processed images; however, key details can be lost during the fast Fourier transformation (FFT) process. Given the limitations of these techniques, there is a growing interest in exploring more direct approaches. The adaption of segmentation architectures originally designed for road extraction for medical imaging represents an innovative step in this direction. By employing K-space data as the modal input, this method completely eliminates the information loss inherent in FFT, thereby potentially enhancing the precision and effectiveness of glioma diagnosis.

Methods

In the study, a novel architecture based on a deep-residual U-net was developed to accomplish the challenging task of automatically segmenting brain tumors from K-space data. Brain tumors from K-space data with different under-sampling rates were also segmented to verify the clinical application of our method.

Results

Compared to the benchmarks set in the 2018 Brain Tumor Segmentation (BraTS) Challenge, our proposed architecture had superior performance, achieving Dice scores of 0.8573, 0.8789, and 0.7765 for the whole tumor (WT), tumor core (TC), and enhanced tumor (ET) regions, respectively. The corresponding Hausdorff distances were 2.5649, 1.6146, and 2.7187 for the WT, TC, and ET regions, respectively. Notably, compared to traditional image-based approaches, the architecture also exhibited an improvement of approximately 10% in segmentation accuracy on the K-space data at different under-sampling rates.

Conclusions

These results show the superiority of our method compared to previous methods. The direct performance of lesion segmentation based on K-space data eliminates the time-consuming and tedious image reconstruction process, thus enabling the segmentation task to be accomplished more efficiently.

Fast and robust pulsed chemical exchange saturation transfer (CEST) MRI using a quasi-steady-state (QUASS) algorithm at 3 T

Chemical exchange saturation transfer (CEST) has emerged as a powerful technique to image dilute labile protons. However, its measurement depends on the RF saturation duration (Tsat) and relaxation delay (Trec). Although the recently developed quasi-steady-state (QUASS) solution can reconstruct equilibrium CEST effects under continuous-wave RF saturation, it does not apply to pulsed-CEST MRI on clinical scanners with restricted hardware or specific absorption rate limits. This study proposed a QUASS algorithm for pulsed-CEST MRI and evaluated its performance in muscle CEST measurement. An approximated expression of a steady-state pulsed-CEST signal was incorporated in the off-resonance spin-lock model, from which the QUASS pulsed-CEST effect was derived. Numerical simulation, creatine phantom, and healthy volunteer scans were conducted at 3 T. The CEST effect was quantified with asymmetry analysis in the simulation and phantom experiments. CEST effects of creatine, amide proton transfer, phosphocreatine, and combined magnetization transfer and nuclear Overhauser effects were isolated from a multi-pool Lorentzian model in muscles. Apparent and QUASS CEST measurements were compared under different Tsat/Trec and duty cycles. Paired Student's t-test was employed with P < 0.05 as statistically significant. The simulation, phantom, and human studies showed the strong impact of Tsat/Trec on apparent CEST measurements, which were significantly smaller than the corresponding QUASS CEST measures, especially under short Tsat/Trec times. In comparison, the QUASS algorithm mitigates such impact and enables accurate CEST measurements under short Tsat/Trec times. In conclusion, the QUASS algorithm can accelerate robust pulsed-CEST MRI, promising the efficient detection and evaluation of muscle diseases in clinical settings.

Altered dynamic functional network connectivity in drug-naïve Parkinson's disease patients with excessive daytime sleepiness

Background

Excessive daytime sleepiness (EDS) is a frequent nonmotor symptoms of Parkinson's disease (PD), which seriously affects the quality of life of PD patients and exacerbates other nonmotor symptoms. Previous studies have used static analyses of these resting-state functional magnetic resonance imaging (rs-fMRI) data were measured under the assumption that the intrinsic fluctuations during MRI scans are stationary. However, dynamic functional network connectivity (dFNC) analysis captures time-varying connectivity over short time scales and may reveal complex functional tissues in the brain.

Purpose

To identify dynamic functional connectivity characteristics in PD-EDS patients in order to explain the underlying neuropathological mechanisms.

Methods

Based on rs-fMRI data from 16 PD patients with EDS and 41 PD patients without EDS, we applied the sliding window approach, k-means clustering and independent component analysis to estimate the inherent dynamic connectivity states associated with EDS in PD patients and investigated the differences between groups. Furthermore, to assess the correlations between the altered temporal properties and the Epworth sleepiness scale (ESS) scores.

Results

We found four distinct functional connectivity states in PD patients. The patients in the PD-EDS group showed increased fractional time and mean dwell time in state IV, which was characterized by strong connectivity in the sensorimotor (SMN) and visual (VIS) networks, and reduced fractional time in state I, which was characterized by strong positive connectivity intranetwork of the default mode network (DMN) and VIS, while negative connectivity internetwork between the DMN and VIS. Moreover, the ESS scores were positively correlated with fraction time in state IV.

Conclusion

Our results indicated that the strong connectivity within and between the SMN and VIS was characteristic of EDS in PD patients, which may be a potential marker of pathophysiological features related to EDS in PD patients.

Fatty Acids Composition of the Sacroiliac Joint in Axial Spondyloarthritis: Analysis Using 3.0 T Chemical Shift-Encoded MRI

BACKGROUND

Axial spondyloarthritis (axSpA) is a group of inflammatory diseases that may lead to ankylosis of the sacroiliac joint and spine. Fat lesion in the sacroiliac joint is an important feature in diagnosis and disease progression of axSpA. However, whether there is alteration of fatty acids (FAs) composition has not been investigated using MRI.

PURPOSE

To investigate bone marrow FA composition of the sacroiliac joint in patients with axSpA compared to controls.

STUDY TYPE

Prospective.

SUBJECTS

Eighty five participants (mean age, 32.3 ± 6.1 years): 48 axSpA (25 male, 23 female) and 37 non-SpA controls (18 male, 19 female).

FIELD STRENGTH/SEQUENCE

3.0 T/Two multiple gradient-echo chemical shift-encoded (CSE) MRI which differed only in echo times (TEs) were scanned consecutively.

ASSESSMENT

Axial multi-echo CSE MRI was performed in the sacroiliac joints in vivo. Regions of interest (ROIs) were manually placed on subchondral bone with and without fat lesion in axSpA patients, and on subchondral bone without fat lesion in controls. FA composition was computed within the ROIs using a nonlinear least square method from literature.

STATISTICAL TESTS

Intergroup comparisons were performed using t tests.

RESULTS

In axSpA, male patients had significantly higher monounsaturated FA compared to controls in areas with fat lesion in the sacrum (+12%) and in the ilium (+9%), and in areas without fat lesion in the sacrum (+10%). Significantly lower polyunsaturated FAs were found in areas with fat lesion in the sacrum (-10%) and ilium (-11%), and lower saturated FAs were found in areas without fat lesion in the sacrum (-6%). In female, patients with axSpA had significantly higher saturated FAs in areas with fat lesion in the ilium (+7%) in comparison to controls.

DATA CONCLUSION

FA composition of the sacroiliac joint alters in patients with axSpA, and it can be detected using CSE MRI based analysis.

Classification of asymmetry in mammography via the DenseNet convolutional neural network

Purpose

To investigate the effectiveness of a deep learning system based on the DenseNet convolutional neural network in diagnosing benign and malignant asymmetric lesions in mammography.

Methods

Clinical and image data from 460 women aged 23-82 years (47.57 ± 8.73 years) with asymmetric lesions who underwent mammography at Shenzhen People's Hospital, Shenzhen Luohu District People's Hospital, and Shenzhen Hospital of Peking University from December 2019 to December 2020 were retrospectively analyzed. Two senior radiologists, two junior radiologists, and the DL system read the mammographic images of 460 patients, respectively, and finally recorded the BI-RADS classification of asymmetric lesions. We then used the area under the curve (AUC) of the receiver operating characteristic (ROC) to evaluate the diagnostic efficacy and the difference between AUCs by the Delong method.

Results

Specificity (0.909 vs. 0.835, 0.790, χ2=8.21 and 17.22, p＜0.05) and precision (0.872 vs. 0.763, 0.726, χ2=9.23 and 5.22, p＜0.05) of the DL system in the diagnosis of benign and malignant asymmetric lesions were higher than those of junior radiologist A and B, and there was a statistically significant difference between AUCs (0.778 vs. 0.579, 0.564, Z = 4.033 and 4.460, p＜0.05). Furthermore, the AUC (0.778 vs. 0.904, 0.862, Z = 3.191, and 2.167, p＜0.05) of benign and malignant asymmetric lesions diagnosed by the DL system was lower than that of senior radiologist A and senior radiologist B.

Conclusions

The DL system based on the DenseNet convolution neural network has high diagnostic efficiency, which can help junior radiologists evaluate benign and malignant asymmetric lesions more accurately. It can also improve diagnostic accuracy and reduce missed diagnoses caused by inexperienced junior radiologists.

[Analysis of the relationship between PI-RADS scores and the pathological results of targeted biopsy based on MRI]

Objective: To analyze the relationship between Prostate Imaging Reporting and Data System (PI-RADS) scores and the pathological results of transperineal magnetic resonance-ultrasound fusion guided biopsy. Methods: The clinical data, magnetic resonance imaging (MRI) results and prostate puncture biopsies of 517 patients who were assigned to PI-RADS score of 4 or 5 and underwent transperineal magnetic resonance-ultrasound fusion guided biopsy at The First Affiliated Hospital of Nanjing Medical University from June 2019 to March 2022 were retrospectively analyzed. Patients were divided into the PI-RADS 4 and PI-RADS 5 groups according to their PI-RADS scores and were stratified by their prostate specific antigen (PSA) values (PSA<10 ng/ml vs. PSA 10-20 ng/ml). The pathological negative rates from the biopsy, the distribution of the grade groups according to the grading system by World Health Organization/International Society of Urological Pathology (WHO/ISUP), the detection rates of prostate cancer (PCa) and clinically significant prostate cancer (CsPCa)between the groups were compared. Results: 369 patients with a PI-RADS score of 4 and 148 patients with a PI-RADS score of 5 were included in our research. The overall detection rates of PCa and CsPCa were 77.8% (402/517) and 66.7% (345/517), respectively. In the PI-RADS 4 group, patients with prostate negative biopsies or in WHO/ISUP 1, 2, 3, 4, or 5 grade groups accounted for 28.2%, 12.7%, 20.1%, 17.1%, 18.4% and 3.5%, respectively, whereas in the PI-RADS 5 group the rates were 7.4%, 6.8%, 22.3%, 22.3%, 26.4%, and 14.9%, respectively. The difference was statistically significant (P<0.001). The detection rates of PCa and CsPCa in the PI-RADS 4 group [71.8% (265/369) vs. 59.1% (218/369), P<0.001] were lower than those of the PI-RADS 5 group [92.6% (137/148) vs. 85.8% (127/148), P<0.001]. In the PI-RADS 4 group, the proportion of patients classified into WHO/ISUP 4-5 grade groups was lower than that of patients in the PI-RADS 5 group [22.0% (81/369) vs 41.2% (61/148) (P<0.001)]. The detection rates of PCa and CsPCa in the PSA<10 ng/ml stratification were less than that in the PSA 10-20 ng/ml stratification[74.1% (281/379) vs. 87.7% (121/138), P=0.001], and [60.9% (231/379) vs. 82.6% (114/138), P<0.001]. For patients with PSA<10 ng/ml, the detection rates of PCa and CsPCa in the PI-RADS 4 group were less than those in the PI-RADS5 group [70.9% (217/306) vs. 87.7% (64/73), P=0.003], and [56.2% (172/306) vs. 80.8% (59/73), P<0.001]. For those with a PSA value of 10-20 ng/ml, the detection rates of PCa and CsPCa in the PI-RADS 4 group were less than those in the PI-RADS 5 group [76.2% (48/63) vs. 97.3% (73/75), P<0.001], and [73.0% (46/63) vs. 90.7% (68/75), P=0.006]. There were statistically significant differences in the proportions of patients with prostate negative biopsy and those falling into WHO/ISUP grade groups 1, 2, 3, 4, or 5 (P<0.001) between the PI-RADS 4 group and the PI-RADS 5 group in both stratifications. Conclusions: In this study, the detection rates of CsPCa and PCa in the PI-RADS 4 group were less than those in the PI-RADS 5 group. With the increase of PI-RADS scores, the detection rate of high-grade PCa increased. The same results held for patients with PSA<10 ng/ml or with PSA 10-20 ng/ml.

Cost-Effectiveness of Short-Course Radiotherapy Based Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer in China

PURPOSE/OBJECTIVE(S)

The phase III STELLAR (NCT02533271) trial demonstrated that four cycles of chemotherapy after short-course radiotherapy (SCRT-TNT) were not inferior to the standard care of long-course concurrent radiotherapy (LCRT) in patients with locally advanced rectal cancer (LARC). This study assessed the cost-effectiveness of SCRT-TNT versus LCRT in locally advanced rectal cancer in China on the basis of the STELLAR trial.

MATERIALS/METHODS

A Markov model was used to synthesize the healthcare costs and benefits of LARC patients based on results from the STELLAR trial. The model assumes that LARC who meet the inclusion criteria of the STELLAR trial experience four possible states: No Evidence of Disease (NED), locally recurrence, distant metastases, or any death from rectal cancer or other unrelated causes, where local recurrence continues to be classified as resectable and unresectable. The transition status period is 3 month, and 5 years is used to calculate direct medical costs and health benefits. The probabilities of states transition after SCRT-TNT or LCRT were derived from the results of the STELLAR trial and previous published article (Table.1). Costs were evaluated from the Chinese payer's perspective reported in early 2022 US dollars (US$1 = 6.78 Chinese Yuan). Sensitivity analyses were performed for key variables. Cost-effectiveness was evaluated using the incremental cost-effectiveness ratio and net monetary benefits. Effectiveness was defined as quality-adjusted life-years (QALYs). Willingness-to-pay (WTP) threshold was set at $43500/QALY. Data were collected from October 3, 2020, to September 20, 2021, and analyzed from November 15, 2020, to October 25, 2021.

RESULTS

During the 5-year horizon, for the base case scenario, SCRT-TNT incurred a lower total cost and higher QALYs compared with LCCRT. The total cost was $65767 and QALYs were 1.77 for SCRT-TNT; for LCCRT, the total cost was $72802 and QALYs were 1.64. This resulted in an ICER of -$ 55470.69 per QALY. Therefore, SCRT-TNT was a cost-saving and dominating treatment strategy compared with LCRT. Sensitivity analysis showed that ICERs were most sensitive to the parameters of distant metastases risk after treatment.

CONCLUSION

SCRT-TNT in locally advanced rectal cancer can be a cost-effective alternative to LCRT in China, and should be considered in appropriately selected patients.

[Mechanism of piRNA in bisphenol A-promoted invasion and migration of prostate cancer cells]

Objective: To investigate the regulatory mechanisms of piwi-interacting RNA (piRNA) in bisphenol A (BPA)-induced prostate cancer cell invasion and migration. Methods: The Cancer Genome Atlas (TCGA) data was used to analyze and screen for piRNAs with significantly increased expression in prostate cancer tissues. PC-3 cells were treated with different concentrations of BPA for 12, 24, and 48 h, respectively, and the 20% inhibitory concentration (IC20) was measured using a CCK-8 assay. The expression levels of piRNAs before and after BPA treatment were determined by reverse transcription-quantitative PCR. Target genes regulated by BPA and associated with prostate cancer were screened in the Comparative Toxicogenomics Database (CTD). Dual-luciferase reporter gene assay was performed to verify the relationship between piRNA and target genes, and the expression change of the piRNA target gene was detected by Western blotting. Cell migration and invasion assays were used to determine the effects of piRNA on the malignant phenotype of prostate cancer cells. Results: After treatment of PC-3 cells with 160 μmol/L BPA, the expression of piR-sno48 was most significantly increased (P<0.05). Transfection of piR-sno48 antagomir resulted in decreased expression of endogenous piR-sno48 and a significant increase in the expression of its target gene GSTP1 (P<0.05). However, the expression of GSTP1 did not change significantly in BPA-treated PC-3 cells after transfection with piR-sno48 antagomir (P>0.05). The dual-luciferase reporter gene confirmed that piR-sno48 inhibited the expression of GSTP1 by forming an inversely complementary sequence with the 3'-UTR of GSTP1. The Transwell assay results showed that treatment with BPA significantly increased the invasion and migration ability of prostate cancer cells (P<0.01), whereas piR-sno48 antagonists significantly inhibited the effects above (P<0.01). Conclusion: BPA promotes the invasion and migration of prostate cancer cells by upregulating the expression of piR-sno48 and suppressing the expression of GSTP1. Interfering with the expression of endogenous piR-sno48 may inhibit the malignant phenotype of prostate cancer cells caused by BPA.

Gelanxinning capsule improves coronary microvascular dysfunction by inhibiting inflammation and restoring endothelial function

OBJECTIVE

Gelanxinning capsule (GXSC) is a Chinese medicine to cure coronary artery disease (CAD) and a compound of Pueraria lobata, hawthorn extract, and gypenosides. However, whether GXSC could improve coronary microvascular dysfunction (CMD) is unknown. We aimed to demonstrate the therapeutic effect of GXSC on CMD and its underlying mechanisms in CAD patients.

PATIENTS AND METHODS

This was a single-center, randomized control trial. A total of 78 patients diagnosed by selective coronary angiography (CAG) participated in this study. Patients' demographics, medical history, medications, and results of laboratory testing were collected. The index of microcirculatory resistance (IMR) and coronary flow reserve (CFR) were obtained by CAG and single-photon emission computed tomography (SPECT) separately. Fasting blood samples were obtained on the morning following the admission day. Concentrations of several molecules of inflammation, endothelial function, and coronary microvascular function were measured by ELISA. Patients were followed-up two months after discharge and fasting blood samples were also acquired.

RESULTS

All patients were randomly divided into 2 groups: GXSC, 38 (48.7%), and control, 40 (51.3%). The intergroup comparison revealed no significant differences with respect to all baseline variables. As for inflammation biomarkers, proinflammatory NOD-like receptor thermal protein domain associated protein 3 (NLRP3) and interleukin (IL)-1 were significantly decreased in GXSC compared with the control group (0.71±0.08 vs. 1.04±0.07, p<0.01 and 7.16±0.59 vs. 10.93±1.04, p<0.01). Anti-inflammatory adropin was increased in the GXSC group (7.75±0.59 vs. 5.71±0.68, p=0.03). As for indexes of endothelial function, the concentrations of syndecan (SDC) 1, SDC4 and heparan sulphates (HS) were significantly downregulated in 2 months GXSC treatment (3.31±0.28 vs. 4.85±0.43, p<0.01, 3.79±0.56 vs. 5.69±0.68, p=0.03 and 21.31±2.79 vs. 35.18±4.11 p<0.01). In addition, the level of SIRTUIN 1 (SIRT1), which is a vascular protective protein, was upregulated in GXSC group (5.63±0.30 vs. 4.22±0.37, p<0.01). As for molecules of coronary microvascular function, endocan, soluble urokinase plasminogen activator receptor (suPAR), and growth differentiation factor (GDF)-15 were significantly decreased consistently in GXSC compared with the control group (0.09±0.01 vs. 0.19±0.03, p<0.01, 4.44±0.40 vs. 5.73±0.40, p=0.03 and 2.08±0.17 vs. 2.69±0.18, p=0.02).

CONCLUSIONS

In conclusion, GXSC could improve CMD by inhibiting inflammation and restoring endothelial function. GXSC might be an effective drug in CAD patients without obstructive epicardial coronary arteries but suffering from angina.

Risk factors for bloodstream infection in paediatric haematopoietic stem cell transplantation: a systematic review and meta-analysis

BACKGROUND

Haematopoietic stem cell transplantation (HSCT), a standard treatment for paediatric haematological diseases, is highly associated with bloodstream infection (BSI), which may increase mortality.

AIM

To explore the risk factors for BSI in paediatric HSCT recipients.

METHODS

Three English databases and four Chinese databases were searched from inception to March 17th, 2022. Eligible studies included randomized controlled trials, cohort studies, and case-control studies that enrolled HSCT recipients aged ≤18 years and reported BSI risk factors. Two reviewers independently screened studies, extracted data, and assessed the risk of bias. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE), certainty of body of evidence was assessed.

FINDINGS

Fourteen studies involving 4602 persons were included. The incidences of BSI and associated mortality in paediatric HSCT recipients were approximately 10-50% and 5-15%, respectively. Meta-analysis of all studies revealed that previous BSI before HSCT (relative effect (RE): 2.28; 95% confidence interval (CI) 1.19-4.34, moderate certainty) and receiving an umbilical cord blood transplant (RE: 1.55; 95% CI: 1.22-1.97, moderate certainty) were probably associated with an increased risk of BSI. Meta-analysis of studies with low risk of bias reassured that previous BSI before HSCT probably increased the risk of BSI (RE: 2.28; 95% CI: 1.19-4.34, moderate certainty), and revealed that steroid use (RE: 2.72; 95% CI: 1.31-5.64, moderate certainty) was likely a risk factor whereas autologous HSCT was probably a protective factor of BSI (RE: 0.65; 95% CI: 0.45-0.94, moderate certainty).

CONCLUSION

These findings could inform the management of paediatric HSCT recipients, helping identify who may benefit from prophylactic antibiotics.

Improved breast lesion detection in mammogram images using a deep neural network

PURPOSE

This study aimed to investigate the effect of using a deep neural network (DNN) in breast cancer (BC) detection.

METHODS

In this retrospective study, a DNN-based model was constructed from a total of 880 mammograms that 220 patients underwent between April and June 2020. The mammograms were reviewed by two senior and two junior radiologists with and without the aid of the DNN model. The performance of the network was assessed by comparing the area under the curve (AUC) and receiver operating characteristic curves for the detection of four features of malignancy (masses, calcifications, asymmetries, and architectural distortions), with and without the aid of the DNN model and by the senior and junior radiologists. Additionally, the effect of utilizing the DNN on diagnosis time for both the senior and junior radiologists was evaluated.

RESULTS

The AUCs of the model for the detection of mass and calcification were 0.877 and 0.937, respectively. In the senior radiologist group, the AUC values for evaluation of mass, calcification, and asymmetric compaction were significantly higher with the DNN model than those obtained without the model. Similar effects were observed in the junior radiologist group, but the increase in the AUC values was even more dramatic. The median mammogram assessment time of the junior and senior radiologists was 572 (357-951) s, and 273.5 (129-469) s, respectively, with the DNN model, and the corresponding assessment time without the model, was 739 (445-1003) s and 321 (195-491) s, respectively.

CONCLUSION

The DNN model exhibited high accuracy in detecting the four named features of BC and effectively shortened the review time by both senior and junior radiologists.

Synthetic high-energy computed tomography image via a Wasserstein generative adversarial network with the convolutional block attention module

Background

Computed tomography (CT) is now universally applied into clinical practice with its non-invasive quality and reliability for lesion detection, which highly improves the diagnostic accuracy of patients with systemic diseases. Although low-dose CT reduces X-ray radiation dose and harm to the human body, it inevitably produces noise and artifacts that are detrimental to information acquisition and medical diagnosis for CT images.

Methods

This paper proposes a Wasserstein generative adversarial network (WGAN) with a convolutional block attention module (CBAM) to realize a method of directly synthesizing high-energy CT (HECT) images through low-energy scanning, which greatly reduces X-ray radiation from high-energy scanning. Specifically, our proposed generator structure in WGAN consists of Visual Geometry Group Network (Vgg16), 9 residual blocks, upsampling and CBAM, a subsequent attention block. The convolutional block attention module is integrated into the generator for improving the denoising ability of the network as verified by our ablation comparison experiments.

Results

Experimental results of the generator attention module ablation comparison indicate an optimization boost to the overall generator model, obtaining the synthesized high-energy CT with the best metric and denoising effect. In different methods comparison experiments, it can be clearly observed that our proposed method is superior in the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and most of the statistics (average CT value and its standard deviation) compared to other methods. Because P<0.05, the samples are significantly different. The data distribution at the pixel level between the images synthesized by the method in this paper and the high-energy CT images is also most similar.

Conclusions

Experimental results indicate that CBAM is able to suppress the noise and artifacts effectively and suggest that the image synthesized by the proposed method is closest to the high-energy CT image in terms of visual perception and objective evaluation metrics.

Comparative effectiveness and safety of antibiotic prophylaxis during induction chemotherapy in children with acute leukaemia: a systematic review and meta-analysis

BACKGROUND

Bacterial infections are common during induction therapy in children and adolescents with acute leukaemia and may cause infection-related mortality.

AIM

To determine the efficacy and safety of prophylactic antibiotics in paediatric patients with acute leukaemia receiving induction chemotherapy.

METHODS

From three English databases and four Chinese databases, we searched for randomized controlled trials (RCTs) and cohort studies that compared prophylactic antibiotics to placebo, no prophylaxis, or that compared one antibiotic versus another in paediatric patients with acute leukaemia undergoing induction chemotherapy. Two reviewers independently screened the studies, extracted data, and assessed the risk of bias using Cochrane Risk of Bias 2 tool and Newcastle-Ottawa Scale, and the certainty of evidence using Grading of Recommendations Assessment, Development, and Evaluation (GRADE).

FINDINGS

Two RCTs and ten cohort studies were finally included. For children with acute lymphoblastic leukaemia, antibiotic prophylaxis, including levofloxacin, sulfamethoxazole-trimethoprim, or other antibiotics, probably reduced bacteraemia (risk ratio (RR): 0.44; 95% confidence interval (CI): 0.33-0.60; moderate certainty) without significantly increasing Clostridioides difficile infection (CDI) or invasive fungal infection. Levofloxacin reduced the CDI rate (RR: 0.08; 95% CI: 0.01-0.62; high certainty). Ciprofloxacin prophylaxis probably reduced infection-related mortality (RR: 0.12; 95% CI: 0.01-0.97; moderate certainty). In children with acute myeloid leukaemia, ciprofloxacin plus vancomycin may reduce febrile neutropenia (RR: 0.79; 95% CI: 0.66-0.94; low certainty). Individual studies indicated that prophylaxis increased antibiotic exposure but reduced non-preventive antibiotic exposure.

CONCLUSION

In children with acute leukaemia undergoing induction therapy, antibiotic prophylaxis may improve the bacterial infection and mortality.

Development of a 3D ultrafast laser written near-infrared spectro-interferometer

Direct ultrafast laser photoinscription of transparent materials is a powerful technique for the development of embedded 3D photonics. This is particularly adaptable for astrophotonic devices when a number of inputs are required. The process relies essentially on volume fabrication of waveguiding structures in flexible 3D designs and refractive index contrast parameters adjustable for specific spectral ranges. This enables 3D geometry and thus avoids in-plane crossings of waveguides that can induce losses and cross talk in multi-telescope beam combiners. The additional novel capability of the technique allows for the fabrication of high aspect ratio nanostructures nonperturbatively sampling the optical field. Combining ultrafast laser micro- and nanoprocessing with engineered beams, we present here results for the development of chip-sized silica glass integrated robust 3D three-telescope beam combiners in the near-IR range, as well as embedded diffraction gratings, for phase closure analysis and spectro-interferometry applications in astronomy.

Intermediate-weighted MRI with fat suppression (IW-FS): diagnostic performance for bone marrow edema and erosion detection in axial spondyloarthritis

BACKGROUND

Bone marrow edema (BME) and erosion of the sacroiliac joint are both key lesions for diagnosing axial spondyloarthritis (axSpA) on magnetic resonance imaging (MRI).

PURPOSE

To qualitatively and quantitatively compare intermediate-weighted MRI with fat suppression (IW-FS) with T2-weighted short tau inversion recovery (T2-STIR) in assessment of sacroiliac BME and erosion in axSpA.

MATERIAL AND METHODS

Patients aged 18-60 years with axSpA were prospectively enrolled. All patients underwent a 3.0-T MRI examination of the sacroiliac joints. Para-coronal IW-FS, T2-STIR, and T1-weighted (T1W) images were acquired. BME and erosion were scored by two readers in consensus on IW-FS and STIR using a modified Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system. Consensus scores on T1WI were used as the reference for erosion. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured for BME.

RESULTS

In total, 49 patients (mean age=33.4 ± 7.6 years) were included. More patients were scored as having BME on T2-STIR (36 vs. 29, P = 0.016). SPARCC-BME score on IW-FS was lower than that acquired on T2-STIR (mean, 11.5 vs. 14.7, P = 0.002). SNR and CNR of BME were both lower on IW-FS than on T2-STIR (mean SNR, 118 vs. 218, P < 0.001; mean CNR, 44 vs. 137, P < 0.001). The sensitivity of erosion detection was higher on IW-FS (83%) than on T2-STIR (54%, P = 0.006).

CONCLUSION

IW-FS is not sufficient for BME detection using T2-STIR as the reference standard in patients with axSpA. IW-FS has a much higher sensitivity than T2-STIR for erosion detection in the sacroiliac joint.

Deep learning for fully automated segmentation and volumetry of Couinaud liver segments and future liver remnants shown with CT before major hepatectomy: a validation study of a predictive model

Background

Recent reports have shown the potential for deep learning (DL) models to automatically segment of Couinaud liver segments and future liver remnant (FLR) for liver resections. However, these studies have mainly focused on the development of the models. Existing reports lack adequate validation of these models in diverse liver conditions and thorough evaluation using clinical cases. This study thus aimed to develop and perform a spatial external validation of a DL model for the automated segmentation of Couinaud liver segments and FLR using computed tomography (CT) in various liver conditions and to apply the model prior to major hepatectomy.

Methods

This retrospective study developed a 3-dimensional (3D) U-Net model for the automated segmentation of Couinaud liver segments and FLR on contrast-enhanced portovenous phase (PVP) CT scans. Images were obtained from 170 patients from January 2018 to March 2019. First, radiologists annotated the Couinaud segmentations. Then, a 3D U-Net model was trained in Peking University First Hospital (n=170) and tested in Peking University Shenzhen Hospital (n=178) in cases with various liver conditions (n=146) and in candidates for major hepatectomy (n=32). The segmentation accuracy was evaluated using the dice similarity coefficient (DSC). Quantitative volumetry to evaluate the resectability was compared between manual and automated segmentation.

Results

The DSC in the test data sets 1 and 2 for segments I to VIII was 0.93±0.01, 0.94±0.01, 0.93±0.01, 0.93±0.01, 0.94±0.00, 0.95±0.00, 0.95±0.00, and 0.95±0.00, respectively. The mean automated FLR and FLR% assessments were 493.51±284.77 mL and 38.53%±19.38%, respectively. The mean manual FLR and FLR% assessments were 500.92±284.38 mL and 38.35%±19.14%, respectively, in test data sets 1 and 2. For test data set 1, when automated segmentation of the FLR% was used, 106, 23, 146, and 57 cases were categorized as candidates for a virtual major hepatectomy of types 1, 2, 3, and 4, respectively; however, when manual segmentation of the FLR% was used, 107, 23, 146, and 57 cases were categorized as candidates for a virtual major hepatectomy of types 1, 2, 3, and 4, respectively. For test data set 2, all cases were categorized as candidates for major hepatectomy when automated and manual segmentation of the FLR% was used. No significant differences in FLR assessment (P=0.50; U=185,545), FLR% assessment (P=0.82; U=188,337), or the indications for major hepatectomy were noted between automated and manual segmentation (McNemar test statistic 0.00; P>0.99).

Conclusions

The DL model could be used to fully automate the segmentation of Couinaud liver segments and FLR with CT prior to major hepatectomy in an accurate and clinically practicable manner.

Evaluation of atrial anatomical remodeling in atrial fibrillation with machine-learned morphological features

PURPOSE

To elucidate the role of atrial anatomical remodeling in atrial fibrillation (AF), we proposed an automatic method to extract and analyze morphological characteristics in left atrium (LA), left atrial appendage (LAA) and pulmonary veins (PVs) and constructed classifiers to evaluate the importance of identified features.

METHODS

The LA, LAA and PVs were segmented from contrast computed tomography images using either a commercial software or a self-adaptive algorithm proposed by us. From these segments, geometric and fractal features were calculated automatically. To reduce the model complexity, a feature selection procedure is adopted, with the important features identified via univariable analysis and ensemble feature selection. The effectiveness of this approach is well illustrated by the high accuracy of our models.

RESULTS

Morphological features, such as LAA ostium dimensions and LA volume and surface area, statistically distinguished ([Formula: see text]) AF patients or AF with LAA filling defects (AF(def+)) patients among all patients. On the test set, the best model to predict AF among all patients had an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI, 0.8-1) and the best model to predict AF(def+) among all patients had an AUC of 0.92 (95% CI, 0.81-1).

CONCLUSION

This study automatically extracted and analyzed atrial morphology in AF and identified atrial anatomical remodeling that statistically distinguished AF or AF(def+). The importance of identified atrial morphological features in characterizing AF or AF(def+) was validated by corresponding classifiers. This work provides a good foundation for a complete computer-assisted diagnostic workflow of predicting the occurrence of AF or AF(def+).

Nucleos(t)ide analogues altered quasispecies composition of hepatitis B virus (HBV)-resistant mutations in serum HBV DNA and serum HBV RNA

Serum hepatitis B virus (HBV) RNA is a new serological indicator reflecting viral replication with good clinical application prospects. This study aimed to clarify the dynamic changes of serum HBV RNA levels and the quasispecies of HBV RNA virus-like particles in nucleos(t)ide analogues (NAs)-experienced chronic hepatitis B (CHB) patients harboring NAs-resistant mutations and their identifiable effects on NAs resistance. We included CHB patients who were on long-term NAs treatment and with HBV DNA rebound. The longitudinally dynamics of serum HBV RNA levels were quantitatively detected, and the quasispecies differences between serum HBV DNA and serum HBV RNA were compared by high-throughput sequencing. The effect of NAs concentration pressure on altering the resistance mutations quasispecies proportion of HBV DNA and HBV RNA in cell supernatant was analyzed in vitro. A total of 447 serum samples from 36 CHB patients treated with NAs were collected. The median follow-up period was 47 months (about 4 years), and the longest follow-up period was 117 months (about 10 years). Our results showed that HBV RNA could reflect virological breakthrough in 23 (64%, 23/36) patients, and serum HBV RNA rebound earlier than HBV DNA in 12 (52%, 12/23) patients. However, serum HBV RNA remained at a consistently high level and did not fluctuate significantly with the HBV DNA rebound in 6 of 36 patients. In addition, serum HBV RNA was not consistently detectable in 7 of the 36 patients, and their serum HBV RNA was undetectable even after HBV DNA had rebounded. The proportion of drug-resistant mutations in HBV DNA was higher than that of HBV RNA by high-throughput sequencing. The results of in vitro experiments showed that the viral strains with drug-resistant mutation in HBV DNA in cell supernatants gradually become the dominant strains with the increase of NAs concentrations. Serum HBV RNA levels can reflect virological breakthrough in most NAs- treated CHB patients, but there are certain limitations. NAs alter the quasispecies composition of serum HBV DNA and serum HBV RNA, resulting in a higher detection rate of drug-resistant mutations in serum HBV DNA than in serum HBV RNA. This article is protected by copyright. All rights reserved.

Preoperative prediction of mediastinal lymph node metastasis in non-small cell lung cancer based on 18F-FDG PET/CT radiomics

AIM

To establish and verify a 2-[¹⁸F]-fluoro-2-deoxy-d-glucose (FDG) positron-emission tomography (PET)/computed tomography (CT)-based radiomics nomogram to predict mediastinal lymph node metastasis (LNM) in non-small cell lung cancer (NSCLC) patients preoperatively.

MATERIALS AND METHODS

This retrospective study enrolled 155 NSCLC patients (primary cohort, n=93; validation cohort, n=62). For each patient, 2,704 radiomic features were extracted from the primary lung cancer regions. Four procedures including the Mann-Whitney U-test, Spearman's correlation analysis, minimum redundancy-maximum relevance (mRMR), and least absolute shrinkage and selection operator (LASSO) binary logistic regression were utilised for determining essential features and establishing a radiomics signature. After that, a nomogram was established. The nomogram's potential was assessed based on its discrimination, calibration, and clinical usefulness. The radiomics signature and nomogram predictive performances were evaluated with respect to the area under the receiver operating characteristic curve (AUC), specificity, accuracy, and sensitivity.

RESULTS

The radiomics signature composed of eight selected features had good discriminatory performance of LNM versus non-LNM groups an AUC of 0.851 and 0.826 in primary and validation cohorts, respectively. The nomogram also indicated good discrimination with an AUC of 0.869 and 0.847 in the primary and validation cohorts, respectively. Furthermore, good calibration was demonstrated utilising the nomogram.

CONCLUSIONS

An ¹⁸F-FDG PET/CT-based radiomics nomogram that integrates the radiomics signature and age was promoted to predict mediastinal LNM within NSCLC patients, which could potentially facilitate individualised therapy for mediastinal LNM before treatment. The nomogram was beneficial in clinical practice, as illustrated by decision curve analysis.

Ultrasonic-induced reversible blood–brain barrier opening: Safety evaluation into the cellular level

An important function of the blood–brain barrier (BBB) is to protect the central nervous system and maintain its homeostasis, but it is also a major barrier to the intervention and treatment of neurological diseases. Our study aimed at opening the BBB using a noninvasive method, focused ultrasound, screening for 16 different parameter combinations of frequency, peak voltage (Ppeak) and irradiation time. Comparing the results of hematoxylin–eosin staining, serum oxidative damage factor and TUNEL staining under various conditions, we obtained a parameter combination that did not lead to oxidative stress injury and apoptosis: 0.8 mHz + 900 mVpp + 90 s. It will be used as a safety parameter for BBB opening treatment of Parkinson’s disease in our subsequent experiments. In addition, the closing time after the BBB opening was verified in magnetic resonance imaging contrast examination and at the tissue level. It is worth mentioning that, different from previous studies, we focused on damage assessment at cellular and molecular levels.

Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning

Introduction. To propose a novel deep learning-based method called RG-Net (reconstruction and generation network) for highly accelerated MR parametric mapping by undersampling k-space and reducing the acquired contrast number simultaneously. Methods. The proposed framework consists of a reconstruction module and a generative module. The reconstruction module reconstructs MR images from the acquired few undersampled k-space data with the help of a data prior. The generative module then synthesizes the remaining multi-contrast images from the reconstructed images, where the exponential model is implicitly incorporated into the image generation through the supervision of fully sampled labels. The RG-Net was trained and tested on the T1ρ mapping data from 8 volunteers at net acceleration rates of 17, respectively. Regional T1ρ analysis for cartilage and the brain was performed to assess the performance of RG-Net. Results. RG-Net yields a high-quality T1ρ map at a high acceleration rate of 17. Compared with the competing methods that only undersample k-space, our framework achieves better performance in T1ρ value analysis. Conclusion. The proposed RG-Net can achieve a high acceleration rate while maintaining good reconstruction quality by undersampling k-space and reducing the contrast number simultaneously for fast MR parametric mapping. The generative module of our framework can also be used as an insertable module in other fast MR parametric mapping methods.

Waveguide scattering antennas made by direct laser writing in bulk glass for spectrometry applications in the short-wave IR

A buried straight waveguide perturbed periodically by six antennas composed of submicronic cylinder voids is entirely fabricated using ultrafast laser photoinscription. The light scattered from each antenna is oriented vertically and is detected by a short-wave IR camera bonded to the surface of the glass with no relay optics. The response of each antenna is analyzed using a wavelength tunable laser source and compared to simulated responses verifying the behavior of the antenna. These results show the good potential of the direct laser writing technique to realize monolithic embedded detectors by combining complex optical functions within a 3D design. A wavelength meter application with a spectral resolution of 150 pm is proposed to demonstrate this combination.

Protective effect of liriodendrin against liver ischaemia/reperfusion injury in mice via modulating oxidative stress, inflammation and nuclear factor kappa B/toll-like receptor 4 pathway

BACKGROUND

The aim of the present study was to investigate the protective effect and mechanism of liriodendrin (LDN) is a lignan diglucoside in hepatic ischaemia/ /reperfusion (I/R) injury.

MATERIALS AND METHODS

The liver I/R was established in male C57BL/6 mice. The effect of LDN is initially investigated on hepatic I/R injury via estimating histopathology of liver. The level of metabolic enzymes alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP) was studied along with apoptosis of mouse hepatocytes via TUNEL and flow cytometry analysis. The effect of LDN was investigated on oxidative stress biomarkers (glutathione [GSH] content, malondialdehyde [MDA] and superoxide dismutase [SOD] activities) and pro-inflammatory cytokines (tumour necrosis factor alpha [TNF-α], interleukin [IL]-1β and IL-6). Western blot study was also conducted to elucidate the effect of LDN on toll-like receptor 4/nuclear factor kappa B (TLR4/NF-kB).

RESULTS

Liriodendrin alleviates liver I/R injury, as manifested by decreased plasma ALT, AST and ALP with improvement in liver necrotic area. LDN also reduces apoptosis of mouse hepatocytes with reduction of oxidative stress and generation of pro-inflammatory cytokines. It significantly reduces the expression of TLR4 and NF-kB.

CONCLUSIONS

The study demonstrated that LDN reduces liver injury and prevented apoptosis of hepatocytes following I/R injury. In addition, LDN also reduces oxidative stress, inflammation, and TLR4/NF-kB in I/R injured mice.

[Correlation analysis between children and adolescents watching food TV advertising and fast food consumption]

Based on the open data of China Health and Nutrition Survey (CHNS), 249 children, adolescents and 249 heads of families who completed two rounds of surveys in 2011 and 2015 were selected in this study. According to the fast food consumption of children and adolescents, they were divided into fast food consumption group and non-fast food consumption group. Logistic regression model was used to analyze the relationship between children and adolescents watching Food TV advertising and fast food consumption. After adjusting relevant factors, the results showed that children and adolescents requiring their parents to buy food in TV advertisements (OR=3.122, P=0.001), parents buying food for their children in TV advertisements (OR=4.717, P=0.036), children and adolescents buying food in TV advertisements themselves (OR=3.728, P=0.041), children and adolescents' preference for food in TV advertisements (OR=2.946, P=0.044) and the frequency of children and adolescents reported by their parents asking their parents to buy food in TV advertisements (OR=3.113, P=0.002) were associated with children and adolescents' fast food consumption.

Deep learning-based pulmonary tuberculosis automated detection on chest radiography: large-scale independent testing

BACKGROUND

It is critical to have a deep learning-based system validated on an external dataset before it is used to assist clinical prognoses. The aim of this study was to assess the performance of an artificial intelligence (AI) system to detect tuberculosis (TB) in a large-scale external dataset.

METHODS

An artificial, deep convolutional neural network (DCNN) was developed to differentiate TB from other common abnormalities of the lung on large-scale chest X-ray radiographs. An internal dataset with 7,025 images was used to develop the AI system, including images were from five sources in the U.S. and China, after which a 6-year dynamic cohort accumulation dataset with 358,169 images was used to conduct an independent external validation of the trained AI system.

RESULTS

The developed AI system provided a delineation of the boundaries of the lung region with a Dice coefficient of 0.958. It achieved an AUC of 0.99 and an accuracy of 0.948 on the internal data set, and an AUC of 0.95 and an accuracy of 0.931 on the external data set when it was used to detect TB from normal images. The AI system achieved an AUC of more than 0.9 on the internal data set, and an AUC of over 0.8 on the external data set when it was applied to detect TB, non-TB abnormal and normal images.

CONCLUSIONS

We conducted a real-world independent validation, which showed that the trained system can be used as a TB screening tool to flag possible cases for rapid radiologic review and guide further examinations for radiologists.

Magnetic Resonance Image under the Low-Rank Matrix Denoising Algorithm in Evaluating the Efficacy of Neoadjuvant Chemo-Radiotherapy for Rectal Cancer

This study was to explore the application value of magnetic resonance imaging (MRI) images obtained by low-rank matrix recovery algorithm (LRMR algorithm) in evaluating the curative effect of rectal cancer patients receiving the neoadjuvant chemo-radiotherapy (nCRT). In this study, an image denoising model was designed based on the LRMR algorithm, the original low-rank data matrix was recovered from the error, and the low-rank matrix was restored by solving the optimal kernel norm, so as to effectively separate the image data information and the interference noise. In addition, the model was applied to 60 patients with rectal cancer who received nCRT to extract the texture parameters and lesion-related data from the MRI images. The results showed that the MRI images optimized by LRMR algorithm were clearer than the original images, contained less excess noise, and had improved imaging accuracy and image quality. The results of typical cases suggested that the front of the rectal wall membrane of a patient in the T-downstage group was not smooth before treatment, the internal angiography was blurred, and the wall membrane was thickened, but the wall membrane became thinner after treatment, the highest position was reduced from 1.46 cm to 0.38 cm, the average value of the apparent diffusion coefficient (ADC) increased from 0.732 × 10−3 mm2/s to 1.196 × 10−3 mm2/s, and the lesion tissue was thicker. It was found that the height, length, and ADC of the lesion after the nCRT showed statistically great difference in contrast to the values before the treatment $\left(P<0.05\right)$ . Such results indicated that the nCRT showed obvious effects in the clinical treatment of rectal cancer. In short, the LRMR algorithm could remove the interference noise in the MRI image, and from the information about rectal cancer tumor lesions extracted from that, the height value and length value of tumor lesions in patients given neoadjuvant chemo-radiotherapy were reduced compared with those before treatment, and the apparent diffusion coefficient value was increased, indicating that neoadjuvant chemo-radiotherapy has a significant effect in the clinical treatment of rectal cancer.

[Epidemiological research progress on the relationship between children's dietary patterns and health]

As food preferences and eating habits form early in life, the development of healthy eating habits in early childhood is a way to prevent diet-related diseases. The dietary pattern approach examines the effect of an overall diet on health outcomes, instead of individual foods or nutrients, thereby presenting a comprehensive evaluation of children's dietary intake. This article reviews the current literature to summarize the main methods for assessing dietary patterns and explore relationships between children's dietary patterns and obesity, puberty onset, cardiovascular diseases, and neurodevelopment. The purpose of this review is to provide evidence-based support for reducing the risk of diet-related diseases in children and recommendations for future research directions.

[A prospective study on the associations between dietary intakes of energy and macronutrients before menarche and age at menarche among girls]

Based on the data from China Health and Nutrition Survey (CHNS), 840 girls aged 6-15 years who had information about menarche and participated in dietary survey at least once within 1-5 years before onset of menarche between 1989 and 2015 were included in the study. The median age at baseline of the 840 participants was 10 (9, 11) years. The median age at menarche of the participants was 13 (12, 14) years. After adjusting for the age of birth, place of residence, body mass index Z-score, physical activity level and annual household income per capita, the average age of menarche was advanced by 0.036 (95%CI: -0.068, -0.004) years for every 10 g increase in daily fat intake before menarche. The average age at menarche was 0.008 (95%CI: -0.014, -0.001) years earlier for every 1% increase in the daily energy supply ratio of fat before menarche.

Altered Brain Functional Network in Subtypes of Parkinson's Disease: A Dynamic Perspective

Background: Parkinson's disease (PD) is a highly heterogeneous disease, especially in the clinical characteristics and prognosis. The PD is divided into two subgroups: tremor-dominant phenotype and non-tremor-dominant phenotype. Previous studies reported abnormal changes between the two PD phenotypes by using the static functional connectivity analysis. However, the dynamic properties of brain networks between the two PD phenotypes are not yet clear. Therefore, we aimed to uncover the dynamic functional network connectivity (dFNC) between the two PD phenotypes at the subnetwork level, focusing on the temporal properties of dFNC and the variability of network efficiency.

Methods: We investigated the resting-state functional MRI (fMRI) data from 29 tremor-dominant PD patients (PDTD), 25 non-tremor-dominant PD patients (PDNTD), and 20 healthy controls (HCs). Sliding window approach, k-means clustering, independent component analysis (ICA), and graph theory analysis were applied to analyze the dFNC. Furthermore, the relationship between alterations in the dynamic properties and clinical features was assessed.

Results: The dFNC analyses identified four reoccurring states, one of them showing sparse connections (state I). PDTD patients stayed longer time in state I and showed increased FNC between BG and vSMN in state IV. Both PD phenotypes exhibited higher FNC between dSMN and FPN in state II and state III compared with the controls. PDNTD patients showed decreased FNC between BG and FPN but increased FNC in the bilateral FPN compared with both PDTD patients and controls. In addition, PDNTD patients exhibited greater variability in global network efficiency. Tremor scores were positively correlated with dwell time in state I along with increased FNC between BG and vSMN in state IV.

Conclusions: This study explores the dFNC between the PDTD and PDNTD patients, which offers new evidence on the abnormal time-varying brain functional connectivity and their network destruction of the two PD phenotypes, and may help better understand the neural substrates underlying different types of PD.

PWLS-PR: low-dose computed tomography image reconstruction using a patch-based regularization method based on the penalized weighted least squares total variation approach

BACKGROUND

Radiation exposure computed tomography (CT) scans and the associated risk of cancer in patients have been major clinical concerns. Existing research can achieve low-dose CT imaging by reducing the X-ray current and the number of projections per rotation of the human body. However, this method may produce excessive noise and fringe artifacts in the traditional filtered back projection (FBP)-reconstructed image.

METHODS

To solve this problem, iterative image reconstruction is a promising option to obtain high-quality images from low-dose scans. This paper proposes a patch-based regularization method based on penalized weighted least squares total variation (PWLS-PR) for iterative image reconstruction. This method uses neighborhood patches instead of single pixels to calculate the nonquadratic penalty. The proposed regularization method is more robust than the conventional regularization method in identifying random fluctuations caused by sharp edges and noise. Each iteration of the proposed algorithm can be described in the following three steps: image updating via the total variation based on penalized weighted least squares (PWLS-TV), image smoothing, and pixel-by-pixel image fusion.

RESULTS

Simulation and real-world projection experiments show that the proposed PWLS-PR algorithm achieves a higher image reconstruction performance than similar algorithms. Through the qualitative and quantitative evaluation of simulation experiments, the effectiveness of the method is also verified.

CONCLUSIONS

Furthermore, this study shows that the PWLS-PR method reduces the amount of projection data required for repeated CT scans and has the useful potential to reduce the radiation dose in clinical medical applications.

Clinical characteristics and neuroimaging findings of seven patients with Dyke Davidoff Masson syndrome

Background

DDMS is a rare disease diagnosed by clinical and radiological characteristics. But the complexity of radiological and clinical manifestations of DDMS has become a challenge diagnostically. To date, the reported cases with DDMS had highly varied clinical manifestations including seizures, contralateral hemiplegia/hemiparesis, facial asymmetry, mental retardation, etc. In addition to typical clinical findings, some new characteristics have been recently added to the spectrum of DDMS. However, few cases have been reported to be associated with neuropsychiatric symptoms according to the literature. This study aimed to investigate the neuropsychiatric manifestations associated with Dyke-Davidoff-Masson syndrome (DDMS) and related imaging findings.

Methods

This study included 7 patients diagnosed with DDMS between 2014 and 2020. The clinical characteristics, neuropsychiatric manifestations, and radiological results were retrospectively evaluated.

Results

Seven patients (five males and two females) with a mean age of 28.0 ± 9.73 (range 15.0–41.0) years were included. Five patients were admitted to the psychiatric unit due to psychological and behavioral disorders. Two patients were referred to the neurology unit mainly due to epilepsy. Six patients had epileptic seizures, 4 had hemiplegia, 3 had mental retardation, 2 patients had external ear deformities, and 2 had facial asymmetry. Neuropsychiatric symptoms were presented in 6 (85.7 %) cases. Cases 2–6 developed affective disorders. Deficits in verbal communication, impairment of social interaction, lack of insight, adulia and hypobulia appeared in cases 1–4. Schizophrenia with apathy, and epileptic schizoid psychosis were observed in cases 4 and 5 respectively. Case 6 had behavioral disorders, hyperactivity, tic disorder, mental retardation, anxiety, catatonic symptoms and suicidal tendency. Case 7 had seizures and mental retardation, and no psychiatric symptoms were presented. Radiological examinations showed unilateral cerebral atrophy, enlarged lateral ventricles, and various compensatory hypertrophy of the skull in all cases. The midline structure has shifted to the affected side in 5(71.4 %) cases. Atrophy of the basal ganglia or brain stem was observed in 4(57.1 %) cases.

Conclusions

The hallmark imaging manifestations of DDMS facilitated the diagnosis in most cases. This study illustrated that a variety of psychoneurotic disorders and ear abnormalities were correlated with DDMS.

Nanomedicine Directs Neuronal Differentiation of Neural Stem Cells via Silencing Long Noncoding RNA for Stroke Therapy

Transplantation of neural stem cells (NSCs) is a promising treatment paradigm to replace lost neurons and reconstruct the damaged neural circuit after ischemic stroke. However, most transplanted NSCs often differentiate into astrocytes rather than functional neurons, and the poor neuronal differentiation adversely affects the therapeutic outcome of NSCs and limits their clinical translation for stroke therapy. Herein, a theranostic nanomedicine is developed to codeliver superparamagnetic iron oxide nanoparticles (SPIO) and small interfering RNA/antisense oligonucleotides (siRNA/ASO) against Pnky long noncoding RNA (lncRNA) into NSCs. This nanomedicine not only directs neuronal differentiation of NSCs through silencing the Pnky lncRNA but also allows an in vivo tracking of NSCs with magnetic resonance imaging. The enhanced neuronal differentiation of NSCs significantly improved the structural and functional recovery of the damaged brain after a stroke. The results demonstrate the great potential of the multifunctional nanomedicine targeting lncRNA to enhance stem cell-based therapies for a stroke.

An iterative reconstruction method for sparse-projection data for low-dose CT

Reducing X-ray radiation is beneficial for reducing the risk of cancer in patients. There are two main approaches for achieving this goal namely, one is to reduce the X-ray current, and another is to apply sparse-view protocols to do image scanning and projections. However, these techniques usually lead to degradation of the reconstructed image quality, resulting in excessive noise and severe edge artifacts, which seriously affect the diagnosis result. In order to overcome such limitation, this study proposes and tests an algorithm based on guided kernel filtering. The algorithm combines the characteristics of anisotropic edges between adjacent image voxels, expresses the relevant weights with an exponential function, and adjusts the weights adaptively through local gray gradients to better preserve the image structure while suppressing noise information. Experiments show that the proposed method can effectively suppress noise and preserve the image structure. Comparing with similar algorithms, the proposed algorithm greatly improves the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and root mean square error (RMSE) of the reconstructed image. The proposed algorithm has the best effect in quantitative analysis, which verifies the effectiveness of the proposed method and good image reconstruction performance. Overall, this study demonstrates that the proposed method can reduce the number of projections required for repeated CT scans and has potential for medical applications in reducing radiation doses.

Altered Brain Functional Network in Parkinson Disease With Rapid Eye Movement Sleep Behavior Disorder

Background and Objective: Parkinson disease (PD) with rapid eye movement (REM) sleep behavior disorder (PD-RBD) tend to be a distinct phenotype with more severe clinical characteristics and pathological lesion when compared with PD without RBD (PD-nRBD). However, the pathological mechanism underlying PD-RBD remains unclear. We aim to use the resting-state functional magnetic resonance imaging (rs-fMRI) to explore the mechanism of PD-RBD from the perspective of internal connectivity networks.

Materials and Methods: A total of 92 PD patients and 20 age and sex matched normal controls (NC) were included. All participants underwent rs-fMRI scan and clinical assessment. According to the RBD screening questionnaire (RBDSQ), PD patients were divided into two groups: PD with probable RBD (PD-pRBD) and PD without probable RBD (PD-npRBD). The whole brain was divided into 90 regions using automated anatomic labeling atlas. Functional network of each subject was constructed according to the correlation of rs-fMRI blood oxygenation level dependent signals in any two brain regions and network metrics were analyzed using graph theory approaches. Network properties among three groups were compared and correlation analysis was made using distinguishing network metrics and RBDSQ scores.

Results: We found both PD-pRBD and PD-npRBD patients existed small-world characteristics. PD-pRBD showed a wider range of nodal property changes in neocortex and limbic system than PD-npRBD patients when compared with NC. Besides, PD-pRBD showed significant enhanced nodal efficiency in the bilateral thalamus and betweenness centrality in the left insula, but, reduced betweenness centrality in the right dorsolateral superior frontal gyrus when compared with PD-npRBD. Moreover, nodal efficiency in the bilateral thalamus were positively correlated with RBDSQ scores.

Conclusions: Both NC and PD patients displayed small-world properties and indiscriminate global measure but PD-pRBD showed more extensive changes of nodal properties than PD-npRBD. The increased centrality role in the bilateral thalamus and the left insula, and disruption in the right dorsolateral superior frontal gyrus may play as a key role in underlying pathogenesis of PD-RBD.