High-resolution magnetic resonance imaging in the diagnosis and management of vertebral artery dissection:A case report

BACKGROUND Vertebral artery dissection(VAD)is a rare but life-threatening condition characterized by tearing of the intimal layer of the vertebral artery,leading to stenosis,occlusion or rupture.The clinical presentation of VAD can be heterogeneous,with common symptoms including headache,dizziness and balance problems.Timely diagnosis and treatment are crucial for favorable outcomes;however,VAD is often missed due to its variable clinical presentation and lack of robust diagnostic guidelines.High-resolution magnetic resonance imaging(HRMRI)has emerged as a reliable diagnostic tool for VAD,providing detailed visualization of vessel wall abnormalities.CASE SUMMARY A young male patient presented with an acute onset of severe headache,vomiting,and seizures,followed by altered consciousness.Imaging studies revealed bilateral VAD,basilar artery thrombosis,multiple brainstem and cerebellar infarcts,and subarachnoid hemorrhage.Digital subtraction angiography(DSA)revealed vertebral artery stenosis but failed to detect the dissection,potentially because intramural thrombosis obscured the VAD.In contrast,HRMRI confirmed the diagnosis by revealing specific signs of dissection.The patient was managed conservatively with antiplatelet therapy and other supportive measures,such as blood pressure control and pain management.After 5 mo of rehabilitation,the patient showed significant improvement in swallowing and limb strength.CONCLUSION HR-MRI can provide precise evidence for the identification of VAD.

Measurement of Two Phase Flow in Porous Medium Using High-resolution Magnetic Resonance Imaging

Measurement of two phase flow in porous medium for sequestration was carried out using high-resolution magnetic resonance imaging (MRI) technique. The porous medium was a packed bed of glass beads. Spin echo multi sequence was used to measure the distribution of CO2 and water in the porous medium. The intensity images show that the fluid distribution is non-uniform due to its viscosity and pore structure of porous medium. The velocity distribution of fluids is calculated from the saturation of water and porosity of porous medium. The experimental results show that fluid velocities vary with time and position. The capillary dispersion rate donated the effects of capillary, which was largest at water saturations of 0.45. The displacement process is different between in BZ-02 and BZ-2. The final water residual saturation depends on permeability and porosity.

High-resolution direct magnetic resonance imaging fistulography with hydrogen peroxide for diagnosing anorectal fistula: A preliminary retrospective study

BACKGROUND Fistula-in-ano is an abnormal tunnel formation linking the anal canal with the perineum and perianal skin.Multiple imagining methods are available to evaluate it,among which magnetic resonance imaging(MRI)is the most advanced nonin-vasive preoperative method.However,it is limited in its visualization function.AIM To investigate the use of intraluminal MRI for perianal fistulas via a novel direct MRI fistulography method.METHODS We mixed 3%hydrogen peroxide(HP)with gadolinium for HPMRI fistulogra-phy,retrospectively analyzing 60 cases of complex/recurrent fistula-in-ano using physical examination,trans-perineal ultrasonography(TPUS),low-spatial-reso-lution MRI,and high-resolution direct HPMRI fistulography.We assessed detec-tion rates of fistula tracks,internal openings,their relationship with anal sphinc-ters,and perianal abscesses using statistical analyses,including interobserver agreement(Kappa statistic),and compared results with intraoperative findings.RESULTS Surgical confirmation in 60 cases showed that high-resolution direct HPMRI fis-tulography provided superior detection rates for internal openings(153)and fistula tracks(162)compared to physical exams,TPUS,and low-spatial-resolution MRI(Z>5.7,P<0.05).The effectiveness of physical examination and TPUS was also inferior to that of our method for detecting perianal abscesses(54)(Z=6.773,3.694,P<0.05),whereas that of low-spatial-resolution MRI was not significantly different(Z=1.851,P=0.06).High-resolution direct HPMRI fistulography also achieved the highest interobserver agreement(Kappa:0.89,0.85,and 0.80),while low-spatial-resolution MRI showed moderate agreement(Kappa:0.78,0.74,and 0.69).TPUS and physical examination had lower agreement(Kappa range:0.33-0.63).CONCLUSION High-resolution direct HPMRI fistulography enhances the visualization of recurrent and complex fistula-in-ano,including branched fistulas,allowing for precise planning and improved surgical outcomes.

Advancement in utilization of magnetic resonance imaging and biomarkers in the understanding of schizophrenia

Historically,psychiatric diagnoses have been made based on patient’s reported symptoms applying the criteria from diagnostic and statistical manual of mental disorders.The utilization of neuroimaging or biomarkers to make the diagnosis and manage psychiatric disorders remains a distant goal.There have been several studies that examine brain imaging in psychiatric disorders,but more work is needed to elucidate the complexities of the human brain.In this editorial,we examine two articles by Xu et al and Stoyanov et al,that show developments in the direction of using neuroimaging to examine the brains of people with schizo-phrenia and depression.Xu et al used magnetic resonance imaging to examine the brain structure of patients with schizophrenia,in addition to examining neurotransmitter levels as biomarkers.Stoyanov et al used functional magnetic resonance imaging to look at modulation of different neural circuits by diagnostic-specific scales in patients with schizophrenia and depression.These two studies provide crucial evidence in advancing our understanding of the brain in prevalent psychiatric disorders.

Multiparameter magnetic resonance imaging-based radiomics model for the prediction of rectal cancer metachronous liver metastasis

BACKGROUND The liver,as the main target organ for hematogenous metastasis of colorectal cancer,early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of patients.Herein,this study aims to investigate the application value of a combined machine learning(ML)based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis(MLM).AIM To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal cancer.METHODS We retrospectively analyzed 301 patients with rectal cancer confirmed by surgical pathology at Jingzhou Central Hospital from January 2017 to December 2023.All participants were randomly assigned to the training or validation queue in a 7:3 ratio.We first apply generalized linear regression model(GLRM)and random forest model(RFM)algorithm to construct an MLM prediction model in the training queue,and evaluate the discriminative power of the MLM prediction model using area under curve(AUC)and decision curve analysis(DCA).Then,the robustness and generalizability of the MLM prediction model were evaluated based on the internal validation set between the validation queue groups.RESULTS Among the 301 patients included in the study,16.28%were ultimately diagnosed with MLM through pathological examination.Multivariate analysis showed that carcinoembryonic antigen,and magnetic resonance imaging radiomics were independent predictors of MLM.Then,the GLRM prediction model was developed with a comprehensive nomogram to achieve satisfactory differentiation.The prediction performance of GLRM in the training and validation queue was 0.765[95%confidence interval(CI):0.710-0.820]and 0.767(95%CI:0.712-0.822),respectively.Compared with GLRM,RFM achieved superior performance with AUC of 0.919(95%CI:0.868-0.970)and 0.901(95%CI:0.850-0.952)in the training and validation queue,respectively.The DCA indicated that the predictive ability and net profit of clinical RFM were improved.CONCLUSION By combining multiparameter magnetic resonance imaging with the effectiveness and robustness of ML-based predictive models,the proposed clinical RFM can serve as an insight tool for preoperative assessment of MLM risk stratification and provide important information for individual diagnosis and treatment of rectal cancer patients.

Temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries on magnetic resonance imaging

Moderate to severe perinatal hypoxic-ischemic encephalopathy occurs in~1 to 3/1000 live births in high-income countries and is associated with a significant risk of death or neurodevelopmental disability.Detailed assessment is important to help identify highrisk infants,to help families,and to support appropriate interventions.A wide range of monitoring tools is available to assess changes over time,including urine and blood biomarkers,neurological examination,and electroencephalography.At present,magnetic resonance imaging is unique as although it is expensive and not suited to monitoring the early evolution of hypoxic-ischemic encephalopathy by a week of life it can provide direct insight into the anatomical changes in the brain after hypoxic-ischemic encephalopathy and so offers strong prognostic information on the long-term outcome after hypoxic-ischemic encephalopathy.This review investigated the temporal dynamics of neonatal hypoxic-ischemic encephalopathy injuries,with a particular emphasis on exploring the correlation between the prognostic implications of magnetic resonance imaging scans in the first week of life and their relationship to long-term outcome prediction,particularly for infants treated with therapeutic hypothermia.A comprehensive literature search,from 2016 to 2024,identified 20 pertinent articles.This review highlights that while the optimal timing of magnetic resonance imaging scans is not clear,overall,it suggests that magnetic resonance imaging within the first week of life provides strong prognostic accuracy.Many challenges limit the timing consistency,particularly the need for intensive care and clinical monitoring.Conversely,although most reports examined the prognostic value of scans taken between 4 and 10 days after birth,there is evidence from small numbers of cases that,at times,brain injury may continue to evolve for weeks after birth.This suggests that in the future it will be important to explore a wider range of times after hypoxic-ischemic encephalopathy to fully understand the optimal timing for predicting long-term outcomes.

Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people everywhere.Due to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the spine.The semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar diseases.It is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation accuracy.This work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra S1.Pseudo-colour mask images were generated and used as ground truth for training the model.The work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley Data.The proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

Magnetic resonance imaging evaluation and nuclear receptor binding SET domain protein 1 mutation in the Sotos syndrome with attention-deficit/hyperactivity disorder

Sotos syndrome is characterized by overgrowth features and is caused by alterations in the nuclear receptor binding SET domain protein 1 gene.Attentiondeficit/hyperactivity disorder(ADHD)is considered a neurodevelopment and psychiatric disorder in childhood.Genetic characteristics and clinical presentation could play an important role in the diagnosis of Sotos syndrome and ADHD.Magnetic resonance imaging(MRI)has been used to assess medical images in Sotos syndrome and ADHD.The images process is considered to display in MRI while wavelet fusion has been used to integrate distinct images for achieving more complete information in single image in this editorial.In the future,genetic mechanisms and artificial intelligence related to medical images could be used in the clinical diagnosis of Sotos syndrome and ADHD.

High-grade pancreatic intraepithelial neoplasia: A commentary of magnetic resonance cholangiopancreatography findings

Commentary on the role of magnetic resonance cholangiopancreatography fin-dings in diagnosing high grade pancreatic intraepithelial neoplasms.

Predictive value of magnetic resonance imaging parameters combined with tumor markers for rectal cancer recurrence risk after surgery

BACKGROUND An increasing number of studies to date have found preoperative magnetic resonance imaging(MRI)features valuable in predicting the prognosis of rectal cancer(RC).However,research is still lacking on the correlation between preoperative MRI features and the risk of recurrence after radical resection of RC,urgently necessitating further in-depth exploration.AIM To investigate the correlation between preoperative MRI parameters and the risk of recurrence after radical resection of RC to provide an effective tool for predicting postoperative recurrence.METHODS The data of 90 patients who were diagnosed with RC by surgical pathology and underwent radical surgical resection at the Second Affiliated Hospital of Bengbu Medical University between May 2020 and December 2023 were collected through retrospective analysis.General demographic data,MRI data,and tumor markers levels were collected.According to the reviewed data of patients six months after surgery,the clinicians comprehensively assessed the recurrence risk and divided the patients into high recurrence risk(37 cases)and low recurrence risk(53 cases)groups.Independent sample t-test andχ2 test were used to analyze differences between the two groups.A logistic regression model was used to explore the risk factors of the high recurrence risk group,and a clinical prediction model was constructed.The clinical prediction model is presented in the form of a nomogram.The receiver operating characteristic curve,Hosmer-Lemeshow goodness of fit test,calibration curve,and decision curve analysis were used to evaluate the efficacy of the clinical prediction model.RESULTS The detection of positive extramural vascular invasion through preoperative MRI[odds ratio(OR)=4.29,P=0.045],along with elevated carcinoembryonic antigen(OR=1.08,P=0.041),carbohydrate antigen 125(OR=1.19,P=0.034),and carbohydrate antigen 199(OR=1.27,P<0.001)levels,are independent risk factors for increased postoperative recurrence risk in patients with RC.Furthermore,there was a correlation between magnetic resonance based T staging,magnetic resonance based N staging,and circumferential resection margin results determined by MRI and the postoperative recurrence risk.Additionally,when extramural vascular invasion was integrated with tumor markers,the resulting clinical prediction model more effectively identified patients at high risk for postoperative recurrence,thereby providing robust support for clinical decision-making.CONCLUSION The results of this study indicate that preoperative MRI detection is of great importance for predicting the risk of postoperative recurrence in patients with RC.Monitoring these markers helps clinicians identify patients at high risk,allowing for more aggressive treatment and monitoring strategies to improve patient outcomes.

Whole-body magnetic resonance imaging provides accurate staging of diffuse large B-cell lymphoma, but is less preferred by patients

BACKGROUND Whole-body magnetic resonance imaging(wbMRI)allows general assessment of systemic cancers including lymphomas without radiation burden.AIM To evaluate the diagnostic performance of wbMRI in the staging of diffuse large B-cell lymphoma(DLBCL),determine the value of individual MRI sequences,and assess patients’concerns with wbMRI.METHODS In this single-center prospective study,adult patients newly diagnosed with systemic DLBCL underwent wbMRI on a 3T scanner[diffusion weighted images with background suppression(DWIBS),T2,short tau inversion recovery(STIR),contrast-enhanced T1]and fluorodeoxyglucose(18F-FDG)positron emission tomo-graphy/computed tomography(PET/CT)(reference standard).The involvement of 12 nodal regions and extranodal sites was evaluated on wbMRI and PET/CT.The utility of wbMRI sequences was rated on a five-point scale(0=not useful,4=very useful).Patients received a questionnaire regarding wbMRI.RESULTS Of 60 eligible patients,14(23%)were enrolled and completed the study.The sensitivity of wbMRI in the nodal involvement(182 nodal sites)was 0.84,with 0.99 specificity,positive predictive value of 0.96,negative predictive value of 0.97,and 0.97 accuracy.PET/CT and wbMRI were concordant both in extranodal involvement(13 instances)and staging(κ=1.0).The mean scores of the utility of MRI sequences were 3.71±0.73 for DWIBS,2.64±0.84 for T1,2.14±0.77 for STIR,and 1.29±0.73 for T2(P<0.0001).Patients were mostly concerned about the enclosed environment and duration of the MRI examination(27%of patients).CONCLUSION The wbMRI exhibited excellent sensitivity and specificity in staging DLBCL.DWIBS and contrast-enhanced T1 were rated as the most useful sequences.Patients were less willing to undergo wbMRI as a second examination parallel to PET/CT,especially owing to the long duration and the enclosed environment.

Hemispheric asymmetries and network dysfunctions in adolescent depression:A neuroimaging study using resting-state functional magnetic resonance imaging

BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.

Enhancing rectal cancer liver metastasis prediction:Magnetic resonance imaging-based radiomics,bias mitigation,and regulatory considerations

In this article,we comment on the article by Long et al published in the recent issue of the World Journal of Gastrointestinal Oncology.Rectal cancer patients are at risk for developing metachronous liver metastasis(MLM),yet early prediction remains challenging due to variations in tumor heterogeneity and the limitations of traditional diagnostic methods.Therefore,there is an urgent need for noninvasive techniques to improve patient outcomes.Long et al’s study introduces an innovative magnetic resonance imaging(MRI)-based radiomics model that integrates high-throughput imaging data with clinical variables to predict MLM.The study employed a 7:3 split to generate training and validation datasets.The MLM prediction model was constructed using the training set and subsequently validated on the validation set using area under the curve(AUC)and dollar-cost averaging metrics to assess performance,robustness,and generalizability.By employing advanced algorithms,the model provides a non-invasive solution to assess tumor heterogeneity for better metastasis prediction,enabling early intervention and personalized treatment planning.However,variations in MRI parameters,such as differences in scanning resolutions and protocols across facilities,patient heterogeneity(e.g.,age,comorbidities),and external factors like carcinoembryonic antigen levels introduce biases.Additionally,confounding factors such as diagnostic staging methods and patient comorbidities require further validation and adjustment to ensure accuracy and generalizability.With evolving Food and Drug Administration regulations on machine learning models in healthcare,compliance and careful consideration of these regulatory requirements are essential to ensuring safe and effective implementation of this approach in clinical practice.In the future,clinicians may be able to utilize datadriven,patient-centric artificial intelligence(AI)-enhanced imaging tools integrated with clinical data,which would help improve early detection of MLM and optimize personalized treatment strategies.Combining radiomics,genomics,histological data,and demographic information can significantly enhance the accuracy and precision of predictive models.

High-resolution Magnetic Resonance Imaging of Moyamoya Disease

Objective： To introduce the imaging characteristics of moyamoya disease （MMD） using high-resolution magnetic resonance imaging （HR-MRI） and to discuss the role of HR-MRI in differentiating MMD from other intracranial artery diseases, especially intracranial atherosclerotic disease （ICAD）. Data Sources： This review was based on the data in articles published between 2005 and 2015, which were obtained from PubMed. The keywords included HR-MRI, MMD, ICAD, and intracranial artery diseases. Study Selection： Articles related to HR-MRI for MMD or other intracranial artery diseases were selected for review. Results： There are differences between the characteristic patterns of HR-MRI in MMD and ICAD. MMD is associated with inward remodeling, smaller outer diameters, concentric occlusive lesions and homogeneous signal intensity, while ICAD is more likely to be associated with outward remodeling, normal outer diameters, eccentric occlusive lesions, and heterogeneous signal intensity. Other intracranial artery diseases, such as dissection and vasculitis, also have distinctive characteristics in HR-MRI. HR-MRI may become a useful tool for the differential diagnosis of MMD in the future. Conclusions： HR-MRI of MMD provides a more in-depth understanding of MMD, and it is helpful in evaluating pathological changes in the vessel wall and in differentiating MMD from other intracranial artery steno-occlusive diseases, particularly ICAD.以

Non-invasive assessment of intracranial wall shear stress using high-resolution magnetic resonance imaging in combination with computational fluid dynamics technique

In vivo studies on association between wall shear stress(WSS)and intracranial plaque are deficient.Based on the three-dimensional T1-weighted high-resolution magnetic resonance imaging(3DT1 HR-MRI)data of patients with low-grade stenotic(<50%)atherosclerotic middle cerebral artery(MCA)and subjects with normal MCA,we built a three-dimensional reconstructed WSS model by computational fluid dynamics(CFD)technique.Three-dimensional registration of the CFD model to the HR-MRI was performed with projections based on the resolution and thickness of the images.The relationships between the Wss at each side of the vessel wall and plaque location were analyzed.A total of 94 MCA plaques from 43 patients and 50 normal MCAs were analyzed.In the normal MCAs,WSS was lower at the ventral-inferior wall than at the dorsal-superior wall(proximal segment,p<0.001;middle segment,p<0.001)and lower at the inner wall than at the outer wall of the MCA curve(p<0.001).In atherosclerotic MCAs,similar low Wss regions were observed where plaques developed.The WSS ratio of the ventral-inferior wall to the dorsal-superior wall in atherosclerotic MCAs was lower than that in normal MCAs(p=0.002).The WSS_(inmer-outer)ratio in atherosclerotic MCAs was lower than that in normal MCAs(p=0.002).Low WSS was associated with MCA atherosclerosis formation and occurred mainly at the ventral inferior wall,which was anatomically opposite the orifices of penetrating arteries,and at the inner wall of the MCA curve.Overall,the results were well consistent with the low WSS theory in atherosclerosis formation.The reconstructed WSS model is a promising novel method for assessing an individualized vascular profile once validated by further studies.

Multi-objective optimization of gradient coil for benchtop magnetic resonance imaging system with high-resolution

Significant high magnetic gradient field strength is essential to obtaining high-resolution images in a benchtop mag- netic resonance imaging （BT-MRI） system with permanent magnet. Extending minimum wire spacing and maximum wire width of gradient coils is one of the key solutions to minimize the maximum current density so as to reduce the local heating and generate higher magnetic field gradient strength. However, maximum current density is hard to optimize together with field linearity, stored magnetic energy, and power dissipation by the traditional target field method. In this paper, a new multi-objective method is proposed to optimize the maximum current density, field linearity, stored magnetic energy, and power dissipation in MRI gradient coils. The simulation and experimental results show that the minimum wire spacings are improved by 159% and 62% for the transverse and longitudinal gradient coil respectively. The maximum wire width increases from 0.5 mm to 1.5 mm. Maximum gradient field strengths of 157 mT/m and 405 mT/m for transverse and lon- gitudinal coil are achieved, respectively. The experimental results in BT-MRI instrument demonstrate that the MRI images with in-plane resolution of 50 ~tm can be obtained by using the designed coils.

High-resolution,three-dimensional magnetic resonance imaging axial load dynamic study improves diagnostics of the lumbar spine in clinical practice

BACKGROUND The response to axial physiological pressure due to load transfer to the lumbar spine structures is among the various back pain mechanisms.Understanding the spine adaptation to cumulative compressive forces can influence the choice of personalized treatment strategies.AIM To analyze the impact of axial load on the spinal canal’s size,intervertebral foramina,ligamenta flava and lumbosacral alignment.METHODS We assessed 90 patients using three-dimensional isotropic magnetic resonance imaging acquisition in a supine position with or without applying an axial compression load.Anatomical structures were measured in the lumbosacral region from L1 to S1 in lying and axially-loaded magnetic resonance images.A paired t test atα=0.05 was used to calculate the observed differences.RESULTS After axial loading,the dural sac area decreased significantly,by 5.2%on average(4.1%,6.2%,P<0.001).The intervertebral foramina decreased by 3.4%(2.7%,4.1%,P<0.001),except for L5-S1.Ligamenta flava increased by 3.8%(2.5%,5.2%,P<0.001),and the lumbosacral angle increased.CONCLUSION Axial load exacerbates the narrowing of the spinal canal and intervertebral foramina from L1-L2 to L4-L5.Cumulative compressive forces thicken ligamenta flava and exaggerate lumbar lordosis.

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.

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.

Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma:A quantitative review with Radiomics Quality Score

BACKGROUND Radiomics is a promising tool that may increase the value of magnetic resonance imaging(MRI)for different tasks related to the management of patients with hepatocellular carcinoma(HCC).However,its implementation in clinical practice is still far,with many issues related to the methodological quality of radiomic studies.AIM To systematically review the current status of MRI radiomic studies concerning HCC using the Radiomics Quality Score(RQS).METHODS A systematic literature search of PubMed,Google Scholar,and Web of Science databases was performed to identify original articles focusing on the use of MRI radiomics for HCC management published between 2017 and 2023.The methodological quality of radiomic studies was assessed using the RQS tool.Spearman’s correlation(ρ)analysis was performed to explore if RQS was correlated with journal metrics and characteristics of the studies.The level of statistical significance was set at P<0.05.RESULTS One hundred and twenty-seven articles were included,of which 43 focused on HCC prognosis,39 on prediction of pathological findings,16 on prediction of the expression of molecular markers outcomes,18 had a diagnostic purpose,and 11 had multiple purposes.The mean RQS was 8±6.22,and the corresponding percentage was 24.15%±15.25%(ranging from 0.0% to 58.33%).RQS was positively correlated with journal impact factor(IF;ρ=0.36,P=2.98×10^(-5)),5-years IF(ρ=0.33,P=1.56×10^(-4)),number of patients included in the study(ρ=0.51,P<9.37×10^(-10))and number of radiomics features extracted in the study(ρ=0.59,P<4.59×10^(-13)),and time of publication(ρ=-0.23,P<0.0072).CONCLUSION Although MRI radiomics in HCC represents a promising tool to develop adequate personalized treatment as a noninvasive approach in HCC patients,our study revealed that studies in this field still lack the quality required to allow its introduction into clinical practice.