Chronic pancreatitis:Pain and computed tomography/magnetic resonance imaging findings

Chronic pancreatitis(CP)is a fibroinflammatory disease characterized by irreversible destruction of pancreatic tissue.With the development of the disease,it may lead to exocrine and/or endocrine insufficiency.CP is one of the common diseases that cause abdominal pain,which will not get permanent spontaneous relief as the disease evolves.The American College of Gastroenterology clinical guidelines recommend computed tomography or magnetic resonance imaging as the first-line examination for the diagnosis of CP.CP common imaging findings include pancreatic atrophy,irregular dilatation of the pancreatic duct,calcification of pancreatic parenchyma,pancreatic duct stones,etc.In clinical practice,whether any correlations between CP-induced abdominal pain patterns(no pain/constant/intermittent pain)and corresponding imaging findings present are not well known.Therefore,this review aims to comprehensively sort out and analyze the relevant information by collecting lots of literature on this field,so as to construct a cross-bridge between the clinical manifestations and imaging manifestations of CP patients.Also,it provides an imaging basis and foundation for the classification and diagnosis of abdominal pain types in clinical CP patients.

Atlas of Elbow Soft Tissue Pathologies Using Magnetic Resonance Imaging at the Saint Camille Hospital in Ouagadougou and the Polyclinique Notre Dame de la Paix (Burkina Faso)

Introduction: The elbow is a superficial joint, particularly exposed to direct impact, forced movement, and overstrain. Our work aimed to study magnetic resonance imaging (MRI) pathologies of the soft tissues of the elbow through illustrative cases. Methodology: This was a retrospective and prospective cross-sectional study covering a period of one year, from June 2020 to June 2021, at the Saint Camille Hospital in Ouagadougou and the Polyclinique Notre Dame de la Paix. Results: In general, this study found that the pathologies diagnosed on MRI were lateral epicondylitis, subcutaneous type V elbow lipoma and liposarcoma, anteromedial cortical fracture of the radial cup, cortical detachment fracture of the lateral epicondylitis, medial epicondylitis, villonodular articular synovitis, simple dermo-hypodermatitis, sequellar fibrosis of the ulnar nerve, Workman's syndrome (median and ulnar nerves) and osteoarthritis of the elbow. Lateral epicondylitis was the most frequent pathology, and most patients consulted for elbow pain predominantly associated with pressure on the epicondyle, with relative functional impotence and, occasionally, elbow swelling. Conclusion: MRI, as a complement to ultrasound and radiography, remains the most informative examination for exploring soft-tissue pathologies of the elbow.

PAI-1和FV基因多态性与静脉血栓的临床意义

目的 一种新技术检测静脉血栓相关基因纤溶酶原激活物抑制剂-1(PAI-1)和凝血因子V(FV)基因多态性,分析清远地区人群基因频率分布情况,指导静脉血栓临床药物治疗。方法 提取2020年4月至2021年8月在清远市人民医院行静脉血栓基因检测的2 281例患者DNA,应用数字荧光分子杂交法检测PAI-1和FV基因多态性,并进行Sanger测序加以验证,大数据分析清远市人民医院就诊患者基因型分布频率,评估男、女性和心、脑血管疾病、肿瘤患者PAI-1和FV基因是否突变与发生静脉血栓的风险,指导抗血栓药物使用。结果 数字荧光分子杂交与Sanger测序结果完全符合(100%);大数据发现本地区人群PAI-1基因呈多态性分布(19.33%、50.33%、30.34%),而FV基因型突变极少,多为野生纯合型(99.91%);PAI-1和FV基因型频率和等位基因频率在男、女性和心、脑血管疾病、肿瘤患者人群中差异无统计学意义(P均>0.05);PAI-1基因多态性与疾病进程无明显相关性。结论 PAI-1基因检测对静脉血栓药物应用极具临床意义,可实现精准化个体治疗,但PAI-1基因多态性与其他疾病和性别无关。

活血化瘀药对不稳定型心绞痛患者PAI-1、t-PA影响的Meta分析

目的探讨活血化瘀药对不稳定型心绞痛(Unstable angina,UA)患者纤溶酶原激活物抑制物(Plasminogen activator inhibitor-1,PAI-1)、组织型纤溶酶原激活剂(Tissue-type plasminogen activator,t-PA)水平的影响,进而评价活血化瘀药对不稳定型心绞痛患者临床疗效,从而为临床预防治疗不稳定型心绞痛提供依据。方法通过检索PubMed、EMbase、The Cochrane Library、Web of Science、ClinicalTrials.gov、万方数据和中国知网数据库,收集活血化瘀药联合西医常规治疗UA的随机对照试验(RCT)文献,采用RevMan 5.4软件进行Meta分析。结果共纳入22项研究,涉及1998例研究对象。Meta分析结果显示,与西药相比,联用活血化瘀中药可以进一步降低UA患者血清PAI-1水平[SMD=-1.96,95%CI(-2.50,-1.43)],Z=7.18,P<0.00001,升高UA患者t-PA水平[SMD=0.55,95%CI(0.41,0.69)],Z=7.85,P<0.00001。结论与常规西药治疗相比,联用活血化瘀药可进一步降低UA患者体内PAI-1水平、升高t-PA水平,改善患者纤溶活性。

Mito-specific cascade amplifier sniping metabolism homeostasis for multimodal imaging-guided antitumor bioenergetic therapy

Nicotinamide adenine dinucleotide (NAD+/NADH) pools homeostasis is recognized as an Achilles’ Heel in tumor metabolism reprogramming. However, mitochondria can enable cancer cells to overcome NADH exhaustion by providing NAD+ precursors and/or intermediates, thus promoting their survival rate and potentially driving uncontrollable proliferation. Here, a synergistic intervention NAD+/NADH homeostasis and mitochondrial metabolism strategy with magnetic resonance imaging (MRI)/photoacoustic imaging (PAI) are developed to address grand challenge of metabolic reprogramming for antitumor bioenergetic therapy. A mitochondrial-targeted cascade amplification nanoplatform ([β-MQ]TRL), triggered by NAD(P)H: quinone oxidoreductase-1 (NQO1), can enable a continuous depletion of cytosol NADH until cell death. The end-product, hydrogen peroxide (H_(2)O_(2)), can be further catalytically converted to higher toxic ·OH in proximity to mitochondria based on [β-MQ]TRL mediated Fenton-like reaction, hijacking tumorigenic energy sources and leading to mitochondrial dysfunction. Additionally, the mild thermal ablation enabled by [β-MQ]TRL further amplifies this cascade reaction to effectively prevent tumor metastasis and recurrence. This synchronous intervention strategy with MRI/PAI establishes unprecedented efficiency in antitumor bioenergetic therapy in vivo, which shows excellent promise for clinical application.

Microwave-induced thermoacoustic elastic imaging:A simulation study

Microwave-induced thermoacoustic imaging(MTI)has the advantages of high resolution,high contrast,non-ionization,and non-invasive.Recently,MTI was used in the¯eld of breast cancer screening.In this paper,based on the¯nite element method(FEM)and COMSOL Multiphysics software,a three-dimensional breast cancer model suitable for exploring the MTI process is proposed to investigate the in°uence of Young's modulus(YM)of breast cancer tissue on MTI.It is found that the process of electromagnetic heating and initial pressure generation of the entire breast tissue is earlier in time than the thermal expansion process.Besides,compared with normal breast tissue,tumor tissue has a greater temperature rise,displacement,and pressure rise.In particular,YM of the tumor is related to the speed of thermal expansion.In particular,the larger the YM of the tumor is,the higher the heating and contraction frequency is,and the greater the maximum pressure is.Di®erent Young's moduli correspond to di®erent thermoacoustic signal spectra.In MTI,this study can be used to judge di®erent degrees of breast cancer based on elastic imaging.In addition,this study is helpful in exploring the possibility of microwave-induced thermoacoustic elastic imaging(MTAE).

Data-driven polarimetric imaging: a review

This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.

Deep learning-based inpainting of saturation artifacts in optical coherence tomography images

Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.

Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model:A dual-center study

BACKGROUND Perineural invasion(PNI)has been used as an important pathological indicator and independent prognostic factor for patients with rectal cancer(RC).Preoperative prediction of PNI status is helpful for individualized treatment of RC.Recently,several radiomics studies have been used to predict the PNI status in RC,demonstrating a good predictive effect,but the results lacked generalizability.The preoperative prediction of PNI status is still challenging and needs further study.AIM To establish and validate an optimal radiomics model for predicting PNI status preoperatively in RC patients.METHODS This retrospective study enrolled 244 postoperative patients with pathologically confirmed RC from two independent centers.The patients underwent preoperative high-resolution magnetic resonance imaging(MRI)between May 2019 and August 2022.Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging(T2WI)and contrast-enhanced T1WI(T1CE)sequences.The radiomics signatures were constructed using logistic regression analysis and the predictive potential of various sequences was compared(T2WI,T1CE and T2WI+T1CE fusion sequences).A clinical-radiomics(CR)model was established by combining the radiomics features and clinical risk factors.The internal and external validation groups were used to validate the proposed models.The area under the receiver operating characteristic curve(AUC),DeLong test,net reclassification improvement(NRI),integrated discrimination improvement(IDI),calibration curve,and decision curve analysis(DCA)were used to evaluate the model performance.RESULTS Among the radiomics models,the T2WI+T1CE fusion sequences model showed the best predictive performance,in the training and internal validation groups,the AUCs of the fusion sequence model were 0.839[95%confidence interval(CI):0.757-0.921]and 0.787(95%CI:0.650-0.923),which were higher than those of the T2WI and T1CE sequence models.The CR model constructed by combining clinical risk factors had the best predictive performance.In the training and internal and external validation groups,the AUCs of the CR model were 0.889(95%CI:0.824-0.954),0.889(95%CI:0.803-0.976)and 0.894(95%CI:0.814-0.974).Delong test,NRI,and IDI showed that the CR model had significant differences from other models(P<0.05).Calibration curves demonstrated good agreement,and DCA revealed significant benefits of the CR model.CONCLUSION The CR model based on preoperative MRI radiomics features and clinical risk factors can preoperatively predict the PNI status of RC noninvasively,which facilitates individualized treatment of RC patients.

Two-photon live imaging of direct glia-to-neuron conversion in the mouse cortex

Over the past decade,a growing number of studies have reported transcription factor-based in situ reprogramming that can directly conve rt endogenous glial cells into functional neurons as an alternative approach for n euro regeneration in the adult mammalian central ne rvous system.Howeve r,many questions remain regarding how a terminally differentiated glial cell can transform into a delicate neuron that forms part of the intricate brain circuitry.In addition,concerns have recently been raised around the absence of astrocyte-to-neuron conversion in astrocytic lineage-tra cing mice.In this study,we employed repetitive two-photon imaging to continuously capture the in situ astrocyte-to-neuron conversion process following ecto pic expression of the neural transcription factor NeuroD1 in both prolife rating reactive astrocytes and lineage-tra ced astrocytes in the mouse cortex.Time-lapse imaging over several wee ks revealed the ste p-by-step transition from a typical astrocyte with numero us short,tapered branches to a typical neuro n with a few long neurites and dynamic growth cones that actively explored the local environment.In addition,these lineage-converting cells were able to migrate ra dially or to ngentially to relocate to suitable positions.Furthermore,two-photon Ca2+imaging and patch-clamp recordings confirmed that the newly generated neuro ns exhibited synchronous calcium signals,repetitive action potentials,and spontaneous synaptic responses,suggesting that they had made functional synaptic connections within local neural circuits.In conclusion,we directly visualized the step-by-step lineage conversion process from astrocytes to functional neurons in vivo and unambiguously demonstrated that adult mammalian brains are highly plastic with respect to their potential for neuro regeneration and neural circuit reconstruction.

Laser spectroscopy imaging technique coupled withnanomaterials for cancer diagnosis: A review

Laser spectroscopic imaging techniques have received tremendous attention in the-eld of cancer diagnosis due to their high sensitivity,high temporal resolution,and short acquisition time.However,the limited tissue penetration of the laser is still a challenge for the in vivo diagnosis of deep-seated lesions.Nanomaterials have been universally integrated with spectroscopic imaging techniques for deeper cancer diagnosis in vivo.The components,morphology,and sizes of nanomaterials are delicately designed,which could realize cancer diagnosis in vivo or in situ.Considering the enhanced signal emitting from the nanomaterials,we emphasized their combination with spectroscopic imaging techniques for cancer diagnosis,like the surface-enhanced Raman scattering(SERS),photoacoustic,fluorescence,and laser-induced breakdown spectroscopy(LIBS).Applications ofthe above spectroscopic techniques offer new prospectsfor cancer diagnosis.

NIR-II fluorescence imaging in liver tumor surgery: A narrative review

In liver tumor surgery,the recognition of tumor margin and radical resection of microcancer focis have always been the crucial points to reduce postoperative recurrence of tumor.However,naked-eye inspection and palpation have limited effectiveness in identifying tumor boundaries,and traditional imaging techniques cannot consistently locate tumors in real time.As an intraoperative real-time navigation imaging method,NIRfluorescence imaging has been extensively studied for its simplicity,reliable safety,and superior sensitivity,and is expected to improve the accuracy of liver tumor surgery.In recent years,the research focus of NIRfluorescence has gradually shifted from the-rst near-infrared window(NIR-I,700–900 nm)to the second near-infrared window(NIR-II,1000–1700 nm).Fluorescence imaging in NIR-II reduces the scattering effect of deep tissue,providing a preferable detection depth and spatial resolution while signi-cantly eliminating liver autofluorescence background to clarify tumor margin.Developingfluorophores combined with tumor antibodies will further improve the precision offluorescence-guided surgical navigation.With the development of a bunch offluorophores with phototherapy ability,NIR-II can integrate tumor detection and treatment to explore a new therapeutic strategy for liver cancer.Here,we review the recent progress of NIR-IIfluorescence technology in liver tumor surgery and discuss its challenges and potential development direction.

Magnetic resonance imaging of extraocular rectus muscles abnormalities in acute acquired concomitant esotropia

AIM:To investigate the difference of medial rectus(MR)and lateral rectus(LR)between acute acquired concomitant esotropia(AACE)and the healthy controls(HCs)detected by magnetic resonance imaging(MRI).METHODS:A case-control study.Eighteen subjects with AACE and eighteen HCs were enrolled.MRI scanning data were conducted in target-controlled central gaze with a 3-Tesla magnetic resonance scanner.Extraocular muscles(EOMs)were scanned in contiguous image planes 2-mm thick spanning the EOM origins to the globe equator.To form posterior partial volumes(PPVs),the LR and MR cross-sections in the image planes 8,10,12,and 14 mm posterior to the globe were summed and multiplied by the 2-mm slice thickness.The data were classified according to the right eye,left eye,dominant eye,and non-dominant eye,and the differences in mean cross-sectional area,maximum cross-sectional area,and PPVs of the MR and LR muscle in the AACE group and HCs group were compared under the above classifications respectively.RESULTS:There were no significant differences between the two groups of demographic characteristics.The mean cross-sectional area of the LR muscle was significantly greater in the AACE group than that in the HCs group in the non-dominant eyes(P=0.028).The maximum cross-sectional area of the LR muscle both in the dominant and non-dominant eye of the AACE group was significantly greater than the HCs group(P=0.009,P=0.016).For the dominant eye,the PPVs of the LR muscle were significantly greater in the AACE than that in the HCs group(P=0.013),but not in the MR muscle(P=0.698).CONCLUSION:The size and volume of muscles dominant eyes of AACE subjects change significantly to overcome binocular diplopia.The LR muscle become larger to compensate for the enhanced convergence in the AACE.

Potential applications of 7 Tesla magnetic resonance imaging in paediatric neuroimaging:Feasibility and challenges

The integration of 7 Tesla magnetic resonance imaging(7 T MRI)in adult patients has marked a revolutionary stride in radiology.In this article we explore the feasibility of 7 T MRI in paediatric practice,emphasizing its feasibility,applications,challenges,and safety considerations.The heightened resolution and tissue contrast of 7 T MRI offer unprecedented diagnostic accuracy,particularly in neuroimaging.Applications range from neuro-oncology to neonatal brain imaging,showcasing its efficacy in detecting subtle structural abnormalities and providing enhanced insights into neurological conditions.Despite the promise,challenges such as high cost,discomfort,and safety concerns necessitate careful consideration.Research suggests that,with precautions,7 T MRI is feasible in paediatrics,yet ongoing studies and safety assessments are imperative.

Staging liver fibrosis with various diffusion-weighted magnetic resonance imaging models

BACKGROUND Diffusion-weighted imaging(DWI)has been developed to stage liver fibrosis.However,its diagnostic performance is inconsistent among studies.Therefore,it is worth studying the diagnostic value of various diffusion models for liver fibrosis in one cohort.AIM To evaluate the clinical potential of six diffusion-weighted models in liver fibrosis staging and compare their diagnostic performances.METHODS This prospective study enrolled 59 patients suspected of liver disease and scheduled for liver biopsy and 17 healthy participants.All participants underwent multi-b value DWI.The main DWI-derived parameters included Mono-apparent diffusion coefficient(ADC)from mono-exponential DWI,intravoxel incoherent motion model-derived true diffusion coefficient(IVIM-D),diffusion kurtosis imaging-derived apparent diffusivity(DKI-MD),stretched exponential model-derived distributed diffusion coefficient(SEM-DDC),fractional order calculus(FROC)model-derived diffusion coefficient(FROC-D)and FROC model-derived microstructural quantity(FROC-μ),and continuous-time random-walk(CTRW)model-derived anomalous diffusion coefficient(CTRW-D)and CTRW model-derived temporal diffusion heterogeneity index(CTRW-α).The correlations between DWI-derived parameters and fibrosis stages and the parameters’diagnostic efficacy in detecting significant fibrosis(SF)were assessed and compared.RESULTS CTRW-D(r=-0.356),CTRW-α(r=-0.297),DKI-MD(r=-0.297),FROC-D(r=-0.350),FROC-μ(r=-0.321),IVIM-D(r=-0.251),Mono-ADC(r=-0.362),and SEM-DDC(r=-0.263)were significantly correlated with fibrosis stages.The areas under the ROC curves(AUCs)of the combined index of the six models for distinguishing SF(0.697-0.747)were higher than each of the parameters alone(0.524-0.719).The DWI models’ability to detect SF was similar.The combined index of CTRW model parameters had the highest AUC(0.747).CONCLUSION The DWI models were similarly valuable in distinguishing SF in patients with liver disease.The combined index of CTRW parameters had the highest AUC.

Value of multiple models of diffusion-weighted imaging to predict hepatic lymph node metastases in colorectal liver metastases patients

BACKGROUND About 10%-31% of colorectal liver metastases(CRLM)patients would concomitantly show hepatic lymph node metastases(LNM),which was considered as sign of poor biological behavior and a relative contraindication for liver resection.Up to now,there’s still lack of reliable preoperative methods to assess the status of hepatic lymph nodes in patients with CRLM,except for pathology examination of lymph node after resection.AIM To compare the ability of mono-exponential,bi-exponential,and stretchedexponential diffusion-weighted imaging(DWI)models in distinguishing between benign and malignant hepatic lymph nodes in patients with CRLM who received neoadjuvant chemotherapy prior to surgery.METHODS In this retrospective study,97 CRLM patients with pathologically confirmed hepatic lymph node status underwent magnetic resonance imaging,including DWI with ten b values before and after chemotherapy.Various parameters,such as the apparent diffusion coefficient from the mono-exponential model,and the true diffusion coefficient,the pseudo-diffusion coefficient,and the perfusion fraction derived from the intravoxel incoherent motion model,along with distributed diffusion coefficient(DDC)andαfrom the stretched-exponential model(SEM),were measured.The parameters before and after chemotherapy were compared between positive and negative hepatic lymph node groups.A nomogram was constructed to predict the hepatic lymph node status.The reliability and agreement of the measurements were assessed using the coefficient of variation and intraclass correlation coefficient.RESULTS Multivariate analysis revealed that the pre-treatment DDC value and the short diameter of the largest lymph node after treatment were independent predictors of metastatic hepatic lymph nodes.A nomogram combining these two factors demonstrated excellent performance in distinguishing between benign and malignant lymph nodes in CRLM patients,with an area under the curve of 0.873.Furthermore,parameters from SEM showed substantial repeatability.CONCLUSION The developed nomogram,incorporating the pre-treatment DDC and the short axis of the largest lymph node,can be used to predict the presence of hepatic LNM in CRLM patients undergoing chemotherapy before surgery.This nomogram was proven to be more valuable,exhibiting superior diagnostic performance compared to quantitative parameters derived from multiple b values of DWI.The nomogram can serve as a preoperative assessment tool for determining the status of hepatic lymph nodes and aiding in the decision-making process for surgical treatment in CRLM patients.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and 0.676(95%CI:0.525-0.827)in the validation cohort.All three models demonstrated good accuracy.In the training cohort,the AUC of the radiomic-clinical model was significantly greater than that of the clinical model(P=0.005)and the radiomic model(P=0.016).DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process.CONCLUSION In this study,we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC.This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Clinical issues and challenges in imaging of gastrointestinal diseases:A minireview and our experience

Imaging techniques play a crucial role in the modern era of medicine,particularly in gastroenterology.Nowadays,various non-invasive and invasive imaging modalities are being routinely employed to evaluate different gastrointestinal(GI)diseases.However,many instrumental as well as clinical issues are arising in the area of modern GI imaging.This minireview article aims to briefly overview the clinical issues and challenges encountered in imaging GI diseases while highlighting our experience in the field.We also summarize the advances in clinically available diagnostic methods for evaluating different diseases of the GI tract and demonstrate our experience in the area.In conclusion,almost all imaging techniques used in imaging GI diseases can also raise many challenges that necessitate careful consideration and profound expertise in this field.

In vivo imaging reveals a synchronized correlation among neurotransmitter dynamics during propofol and sevoflurane anesthesia

General anesthesia is widely applied in clinical practice.However,the precise mechanism of loss of consciousness induced by general anesthetics remains unknown.Here,we measured the dynamics of five neurotransmitters,includingγ-aminobutyric acid,glutamate,norepinephrine,acetylcholine,and dopamine,in the medial prefrontal cortex and primary visual cortex of C57BL/6 mice through in vivo fiber photometry and genetically encoded neurotransmitter sensors under anesthesia to reveal the mechanism of general anesthesia from a neurotransmitter perspective.Results revealed that the concentrations of γ-aminobutyric acid,glutamate,norepinephrine,and acetylcholine increased in the cortex during propofol-induced loss of consciousness.Dopamine levels did not change following the hypnotic dose of propofol but increased significantly following surgical doses of propofol anesthesia.Notably,the concentrations of the five neurotransmitters generally decreased during sevoflurane-induced loss of consciousness.Furthermore,the neurotransmitter dynamic networks were not synchronized in the non-anesthesia groups but were highly synchronized in the anesthetic groups.These findings suggest that neurotransmitter dynamic network synchronization may cause anesthetic-induced loss of consciousness.

Imaging characteristics and treatment strategies for carotid artery occlusion caused by skull base fracture:Three case reports

BACKGROUND Traumatic internal carotid artery(ICA)occlusion is a rare complication of skull base fractures,characterized by high mortality and disability rates,and poor prognosis.Therefore,timely discovery and correct management are crucial for saving the lives of such patients and improving their prognosis.This article retrospectively analyzed the imaging and clinical data of three patients,to explore the imaging characteristics and treatment strategies for carotid artery occlusion,combined with severe skull base fractures.CASE SUMMARY This case included three patients,all male,aged 21,63,and 16 years.They underwent plain film skull computed tomography(CT)examination at the onset of their illnesses,which revealed fractures at the bases of their skulls.Ultimately,these cases were definitively diagnosed through CT angiography(CTA)examinations.The first patient did not receive surgical treatment,only anticoagulation therapy,and recovered smoothly with no residual limb dysfunction(Case 1).The other two patients both developed intracranial hypertension and underwent decompressive craniectomy.One of these patients had high intracranial pressure and significant brain swelling postoperatively,leading the family to choose to take him home(Case 2).The other patient also underwent decompressive craniectomy and recovered well postoperatively with only mild limb motor dysfunction(Case 3).We retrieved literature from PubMed on skull base fractures causing ICA occlusion to determine the imaging characteristics and treatment strategies for this type of disease.CONCLUSION For patients with cranial trauma combined with skull base fractures,it is essential to complete a CTA examination as soon as possible,to screen for blunt cerebrovascular injury.