Artificial intelligence(AI)is revolutionizing medical imaging,particularly in chronic liver diseases assessment.AI technologies,including machine learning and deep learning,are increasingly integrated with multiparame...Artificial intelligence(AI)is revolutionizing medical imaging,particularly in chronic liver diseases assessment.AI technologies,including machine learning and deep learning,are increasingly integrated with multiparametric ultrasound(US)techniques to provide more accurate,objective,and non-invasive evaluations of liver fibrosis and steatosis.Analyzing large datasets from US images,AI enhances diagnostic precision,enabling better quantification of liver stiffness and fat content,which are essential for diagnosing and staging liver fibrosis and steatosis.Combining advanced US modalities,such as elastography and doppler imaging with AI,has demonstrated improved sensitivity in identifying different stages of liver disease and distinguishing various degrees of steatotic liver.These advancements also contribute to greater reproducibility and reduced operator dependency,addressing some of the limitations of traditional methods.The clinical implications of AI in liver disease are vast,ranging from early detection to predicting disease progression and evaluating treatment response.Despite these promising developments,challenges such as the need for large-scale datasets,algorithm transparency,and clinical validation remain.The aim of this review is to explore the current applications and future potential of AI in liver fibrosis and steatosis assessment using multiparametric US,highlighting the technological advances and clinical relevance of this emerging field.展开更多
BACKGROUND Endoscopic variceal band ligation(EVBL)represents a pivotal treatment in the prophylaxis of esophageal varices bleeding in patients with cirrhosis,but in some cases a single session of EVBL is unable to era...BACKGROUND Endoscopic variceal band ligation(EVBL)represents a pivotal treatment in the prophylaxis of esophageal varices bleeding in patients with cirrhosis,but in some cases a single session of EVBL is unable to eradicate esophageal varices completely,and a control endoscopy after 2-4 weeks is required to assess eradication and/or the need for another band ligation.Liver stiffness measurement(LSM)is being increasingly used as a screening non-invasive tool to predict varices according to Baveno VII criteria.However,to date,there are no instruments able to non-invasively predict the outcome of EVBL.AIM To identify non-invasive predictors of varices eradication(VE)after EVBL through multiparametric ultrasound(US).Secondary aim was to develop a prediction model of successful variceal eradication based on non-invasive parameters.METHODS We prospectively enrolled consecutive cirrhotic patients intolerant or with contraindications to beta-blockers undergoing EVBL for bleeding prophylaxis.Patients underwent multiparametric US with LSM,spleen stiffness measurement(SSM)and dynamic contrastenhanced US(DCE-US)on liver parenchyma and portal vein,at baseline(T0)and one month(T1)after EVBL.Each US parameter and their variations from baseline were correlated with VE evaluated by control endoscopy performed at T1.RESULTS We enrolled 41 patients(median age 64 years,75.6%males).At T128 patients(68.3%)reached VE,whereas 13(31.7%)required a second EVBL.Patients who achieved VE showed a significant decrease in SSM(P=0.018),and a significant increase in peak enhancement,area under the curve and wash-in rate of both liver parenchyma and portal vein after treatment(P<0.001).Statistically significant differences between the two groups of patients were incorporated in a multivariate analysis and used to develop three prediction models.CONCLUSION A multimodal US approach based on DCE-US parameters,LSM and SSM might become a reliable predictor of VE and a useful non-invasive alternative to endoscopy.展开更多
BACKGROUND Patients harboring gene mutations like KRAS,NRAS,and BRAF demonstrate highly variable responses to chemotherapy,posing challenges for treatment optimization.Multiparametric magnetic resonance imaging(MRI),w...BACKGROUND Patients harboring gene mutations like KRAS,NRAS,and BRAF demonstrate highly variable responses to chemotherapy,posing challenges for treatment optimization.Multiparametric magnetic resonance imaging(MRI),with its noninvasive capability to assess tumor characteristics in detail,has shown promise in evaluating treatment response and predicting therapeutic outcomes.This technology holds potential for guiding personalized treatment strategies tailored to individual patient profiles,enhancing the precision and effectiveness of colorectal cancer care.AIM To create a multiparametric MRI-based predictive model for assessing chemotherapy efficacy in colorectal cancer patients with gene mutations.METHODS This retrospective study was conducted in a tertiary hospital,analyzing 157 colorectal cancer patients with gene mutations treated between August 2022 and December 2023.Based on chemotherapy outcomes,the patients were categorized into favorable(n=60)and unfavorable(n=50)response groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of chemotherapy efficacy.A predictive nomogram was constructed using significant variables,and its performance was assessed using the area under the receiver operating characteristic curve(AUC)in both training and validation sets.RESULTS Univariate analysis identified that tumor differentiation,T2 signal intensity ratio,tumor-to-anal margin distance,and MRI-detected lymph node metastasis as significantly associated with chemotherapy response(P<0.05).Multivariate Logistics regression confirmed these four parameters as independent predictors.The predictive model demonstrated strong discrimination,with an AUC of 0.938(sensitivity:86%;specificity:92%)in the training set,and 0.942(sensitivity:100%;specificity:83%)in the validation set.CONCLUSION We established and validated a multiparametric MRI-based model for predicting chemotherapy response in colorectal cancer patients with gene mutations.This model holds promise for guiding individualized treatment strategies.展开更多
BACKGROUND In metabolic dysfunction-associated steatotic liver disease(MASLD)the identi-fication of patients at high risk of evolution to metabolic dysfunction-associated steatohepatitis(MASH)is challenging.AIM To inv...BACKGROUND In metabolic dysfunction-associated steatotic liver disease(MASLD)the identi-fication of patients at high risk of evolution to metabolic dysfunction-associated steatohepatitis(MASH)is challenging.AIM To investigate the performance of different ultrasound(US)-based techniques for the non-invasive assessment of liver fibrosis,steatosis,and inflammation in these patients.METHODS We collected data from consecutive patients who underwent liver biopsy for suspected MASLD between January 2019 and December 2021.Two-dimensional shear-wave elastography,sound speed plane-wave US,attenuation plane-wave US,viscosity plane-wave US(Vi.PLUS)using Aixplorer MACH 30 system,and transient elastography and controlled attenuation parameter from FibroScan were measured before biopsy.RESULTS A total of 120 participants were enrolled.Both transient elastography and two-dimensional shear-wave elasto-graphy showed good performance for the diagnosis of advanced fibrosis[area under the receiver operating charac-teristic curve(AUROC)=0.93 and 0.90,respectively].The diagnostic performance of Vi.PLUS for the presence of both ballooning grade≥1 and lobular inflammation≥1 was good with an AUROC of 0.72.A score based on Vi.PLUS,aspartate aminotransferase,and sound speed plane-wave US[viscosity-aspartate aminotransferase-speed of sound MASH ultrasound score(VAS-MASH-US score)]had a good accuracy for the diagnosis of MASH(AUROC=0.75).VAS-MASH-US score>0.6 showed a good sensitivity for MASH diagnosis(79.0%).According to decision curve analysis,the application of the VAS-MASH-US score would lead to a more accurate selection of patients who are candidates to undergo liver biopsy and would reduce the need for invasive procedures for patients at low risk of MASH.CONCLUSION Multiparametric US allows the non-invasive assessment of steatosis,inflammation,and fibrosis in patients with MASLD.Liver viscosity improved the capability of non-invasively identifying patients with MASH.展开更多
Colorectal cancer(CRC) is a heterogeneous disease, with a diverse and plastic immune cell infiltrate. These immune cells play an important role in regulating tumour growth-progression or elimination. Some populations ...Colorectal cancer(CRC) is a heterogeneous disease, with a diverse and plastic immune cell infiltrate. These immune cells play an important role in regulating tumour growth-progression or elimination. Some populations of cells have a strong correlation with disease-free survival, making them useful prognostic markers. In particular, the infiltrate of CD3^+ and CD8^+ T cells into CRC tumours has been validated worldwide as a valuable indicator of patient prognosis. However, the heterogeneity of the immune response, both between patients with tumours of different molecular subtypes, and within the tumour itself, necessitates the use of multiparametric analysis in the investigation of tumour-specific immune responses. This review will outline the multiparametric analysis techniques that have been developed and applied to studying the role of immune cells in the tumour, with a focus on colorectal cancer. Because much of the data in this disease relates to T cell subsets and heterogeneity, we have used T cell populations as examples throughout. Flow and mass cytometry give a detailed representation of the cells within the tumour in a single-cell suspension on a per-cell basis. Imaging technologies, such as imaging mass cytometry, are used to investigate increasing numbers of markers whilst retaining the spatial and structural information of the tumour section and the infiltrating immune cells. Together, the analyses of multiple immune parameters can provide valuable information to guide clinical decision-making in CRC.展开更多
BACKGROUND Non-invasive assessment of non-alcoholic steatohepatitis(NASH)is increasing in desirability due to the invasive nature and costs associated with the current form of assessment;liver biopsy.Quantitative mult...BACKGROUND Non-invasive assessment of non-alcoholic steatohepatitis(NASH)is increasing in desirability due to the invasive nature and costs associated with the current form of assessment;liver biopsy.Quantitative multiparametric magnetic resonance imaging(mpMRI)to measure liver fat(proton density fat fraction)and fibroinflammatory disease[iron-corrected T1(cT1)],as well as elastography techniques[vibration-controlled transient elastography(VCTE)liver stiffness measure],magnetic resonance elastography(MRE)and 2D Shear-Wave elastography(SWE)to measure stiffness and fat(controlled attenuated parameter,CAP)are emerging alternatives which could be utilised as safe surrogates to liver biopsy.AIM To evaluate the agreement of non-invasive imaging modalities with liver biopsy,and their subsequent diagnostic accuracy for identifying NASH patients.METHODS From January 2019 to February 2020,Japanese patients suspected of NASH were recruited onto a prospective,observational study and were screened using noninvasive imaging techniques;mpMRI with LiverMultiScan®,VCTE,MRE and 2DSWE.Patients were subsequently biopsied,and samples were scored by three independent pathologists.The diagnostic performances of the non-invasive imaging modalities were assessed using area under receiver operating characteristic curve(AUC)with the median of the histology scores as the gold standard diagnoses.Concordance between all three independent pathologists was further explored using Krippendorff’s alpha(a)from weighted kappa statistics.RESULTS N=145 patients with mean age of 60(SD:13 years.),39%females,and 40%with body mass index≥30 kg/m2 were included in the analysis.For identifying patients with NASH,MR liver fat and cT1 were the strongest performing individual measures(AUC:0.80 and 0.75 respectively),and the mpMRI metrics combined(cT1 and MR liver fat)were the overall best non-invasive test(AUC:0.83).For identifying fibrosis≥1,MRE performed best(AUC:0.97),compared to VCTE-liver stiffness measure(AUC:0.94)and 2D-SWE(AUC:0.94).For assessment of steatosis≥1,MR liver fat was the best performing non-invasive test(AUC:0.92),compared to controlled attenuated parameter(AUC:0.75).Assessment of the agreement between pathologists showed that concordance was best for steatosis(a=0.58),moderate for ballooning(a=0.40)and fibrosis(a=0.40),and worst for lobular inflammation(a=0.11).CONCLUSION Quantitative mpMRI is an effective alternative to liver biopsy for diagnosing NASH and non-alcoholic fatty liver,and thus may offer clinical utility in patient management.展开更多
We attempted to perform risk categories based on the free/total prostate-specific antigen ratio (%fPSA), prostate-specific antigen(PSA) density (PSAD, in ng ml^(−2)), and multiparametric magnetic resonance imaging (mp...We attempted to perform risk categories based on the free/total prostate-specific antigen ratio (%fPSA), prostate-specific antigen(PSA) density (PSAD, in ng ml^(−2)), and multiparametric magnetic resonance imaging (mpMRI) step by step, with the goal ofdetermining the best clinical diagnostic strategy to avoid unnecessary tests and prostate biopsy (PBx) in biopsy-naïve men with PSAlevels ranging from 4 ng ml^(−1) to 10 ng ml^(−1). We included 439 patients who had mpMRI and PBx between August 2018 and July2021 (West China Hospital, Chengdu, China). To detect clinically significant prostate cancer (csPCa) on PBx, receiver-operatingcharacteristic (ROC) curves and their respective area under the curve were calculated. Based on %fPSA, PSAD, and ProstateImaging-Reporting and Data System (PI-RADS) scores, the negative predictive value (NPV) and positive predictive value (PPV) werecalculated sequentially. The optimal %fPSA threshold was determined to be 0.16, and the optimal PSAD threshold was 0.12 for%fPSA ≥0.16 and 0.23 for %fPSA <0.16, respectively. When PSAD <0.12 was combined with patients with %fPSA ≥0.16, the NPVof csPCa increased from 0.832 (95% confidence interval [CI]: 0.766–0.887) to 0.931 (95% CI: 0.833–0.981);the detection rateof csPCa was similar when further stratified by PI-RADS scores (P = 0.552). Combining %fPSA <0.16 with PSAD ≥0.23 ng ml^(−2)predicted significantly more csPCa patients than those with PSAD <0.23 ng ml^(−2) (58.4% vs 26.7%, P < 0.001). Using PI-RADSscores 4 and 5, the PPV was 0.739 (95% CI: 0.634–0.827) when further stratified by mpMRI results. In biopsy-naïve patientswith PSA level of 4–10 ng ml^(−1), stratification of %fPSA and PSAD combined with PI-RADS scores may be useful in the decisionmaking process prior to undergoing PBx.展开更多
The purpose of this study was to explore transrectal ultrasound(TRUS)findings of prostate cancer(PCa)guided by multiparametric magnetic resonance imaging(mpMRI)and to improve the Prostate Imaging Reporting and Data Sy...The purpose of this study was to explore transrectal ultrasound(TRUS)findings of prostate cancer(PCa)guided by multiparametric magnetic resonance imaging(mpMRI)and to improve the Prostate Imaging Reporting and Data System(PI-RADS)system for avoiding unnecessary mpMRI-guided targeted biopsy(TB).From January 2018 to October 2019,fusion mpMRI and TRUS-guided biopsies were performed in 162 consecutive patients.The study included 188 suspicious lesions on mpMRI in 156 patients,all of whom underwent mpMRI-TRUS fusion imaging-guided TB and 12-core transperineal systematic biopsy(SB).Univariate analyses were performed to investigate the relationship between TRUS features and PCa.Then,logistic regression analysis with generalized estimating equations was performed to determine the independent predictors of PCa and obtain the fitted probability of PCa.The detection rates of PCa based on TB alone,SB alone,and combined SB and TB were 55.9%(105 of 188),52.6%(82 of 156),and 62.8%(98 of 156),respectively.The significant predictors of PCa on TRUS were hypoechogenicity(odds ratio[OR]:9.595,P=0.002),taller-than-wide shape(OR:3.539,P=0.022),asymmetric vascular structures(OR:3.728,P=0.031),close proximity to capsule(OR:3.473,P=0.040),and irregular margins(OR:3.843,P=0.041).We propose subgrouping PI-RADS score 3 into categories 3a,3b,3c,and 3d based on different numbers of TRUS predictors,as the creation of PI-RADS 3a(no suspicious ultrasound features)could avoid 16.7%of mpMRI-guided TBs.Risk stratification of PCa with mpMRI-TRUS fusion imaging-directed ultrasound features could avoid unnecessary mpMRI-TBs.展开更多
Liver disease accounts for approximately 2 million deaths per year worldwide.All chronic liver diseases(CLDs),whether of toxic,genetic,autoimmune,or infectious origin,undergo typical histological changes in the struct...Liver disease accounts for approximately 2 million deaths per year worldwide.All chronic liver diseases(CLDs),whether of toxic,genetic,autoimmune,or infectious origin,undergo typical histological changes in the structure of the tissue.These changes may include the accumulation of extracellular matrix material,fats,triglycerides,or tissue scarring.Noninvasive methods for diagnosing CLD,such as conventional B-mode ultrasound(US),play a significant role in diagnosis.Doppler US,when coupled with B-mode US,can be helpful in evaluating the hemodynamics of hepatic vessels and detecting US findings associated with hepatic decompensation.US elastography can assess liver stiffness,serving as a surrogate marker for liver fibrosis.It is important to note that interpreting these values should not rely solely on a histological classification.Contrast-enhanced US(CEUS)provides valuable information on tissue perfusion and enables excellent differentiation between benign and malignant focal liver lesions.Clinical evaluation,the etiology of liver disease,and the patient current comorbidities all influence the interpretation of liver stiffness measurements.These measurements are most clinically relevant when interpreted as a probability of compensated advanced CLD.B-mode US offers a subjective estimation of fatty infiltration and has limited sensitivity for mild steatosis.The controlled attenuation parameter requires a dedicated device,and cutoff values are not clearly defined.Quan-titative US parameters for liver fat estimation include the attenuation coefficient,backscatter coefficient,and speed of sound.These parameters offer the advantage of providing fat quantification alongside B-mode evaluation and other US parameters.Multiparametric US(MPUS)of the liver introduces a new concept for complete noninvasive diagnosis.It encourages examiners to utilize the latest features of an US machine,including conventional B-mode,liver stiffness evaluation,fat quantification,dispersion imaging,Doppler US,and CEUS for focal liver lesion characterization.This comprehensive approach allows for diagnosis in a single examination,providing clinicians worldwide with a broader perspective and becoming a cornerstone in their diagnostic arsenal.MPUS,in the hands of skilled clinicians,becomes an invaluable predictive tool for diagnosing,staging,and monitoring CLD.展开更多
Portal hypertension,the most common complication in liver cirrhosis,is characterized by a pathologic increase in portal venous pressure.Portal hypertension is defined as a pressure gradient greater than 5 mmHg between...Portal hypertension,the most common complication in liver cirrhosis,is characterized by a pathologic increase in portal venous pressure.Portal hypertension is defined as a pressure gradient greater than 5 mmHg between the portal vein and the inferior caval vein.Clinically significant portal hypertension is determined by a hepatic venous pressure gradient(HVPG)exceeding 10 mmHg.Complications are likely to occur if the pressure exceeds this threshold.The gold standard for assessing portal hypertension is the measurement of HVPG,which is an invasive procedure.This review discusses the various multiparametric capabilities of ultrasound,including B-mode,color Doppler imaging,Doppler measurement,contrast-enhanced ultrasound,endoscopic ultrasound,and elastography to diagnose portal hypertension and assess its severity.展开更多
To the Editor,Hepatic venous pressure gradient(HVPG)measurement is the gold standard measurement for diagnosing portal hypertension(PH),a critical complication of liver cirrhosis.However,HVPG is an invasive and highly...To the Editor,Hepatic venous pressure gradient(HVPG)measurement is the gold standard measurement for diagnosing portal hypertension(PH),a critical complication of liver cirrhosis.However,HVPG is an invasive and highly specialized technique.Noninvasive measurements would be extremely valuable to assess portal venous pressure[1].It is therefore with interest that Möller et al.[2]report noninvasive multiparametric ultrasound-based criteria and measurements for evaluating PH comprehensively.展开更多
Background:The predictive value of different MRI sequences for axillary lymph node metastasis(ALNM)in patients with invasive breast cancer remains unclear.This study compared the performance of radiomics models based ...Background:The predictive value of different MRI sequences for axillary lymph node metastasis(ALNM)in patients with invasive breast cancer remains unclear.This study compared the performance of radiomics models based on individual and combined MRI sequences for the preoperative prediction of ALNM and evaluated the clinical application value of the optimal model.Methods:This retrospective study included 454 patients(mean±SD age 50.9±10.7 years)diagnosed with invasive breast cancer from two centers,with 382 patients from Center 1(training cohort)and 72 patients from Center 2(external test cohort).Tumor segmentation and radiomics feature extraction were performed on T2‐weighted imaging(T2WI),diffusion‐weighted imaging(DWI),and dynamic contrast‐enhanced(DCE)images.The least absolute shrinkage and selection operator with 10‐fold cross‐validation was used for feature selection and radiomics score construction.Three single‐sequence models and one multisequence radiomics model were developed,and the optimal model was combined with conventional MRI features to create a combined MRI model.The combined model's performance was compared to radiologists'diagnoses.A nomogram was developed based on the optimal model and correlated with prognosis using the Kaplan–Meier curve and Cox proportional hazard regression.Model performance was evaluated using area under the curve(AUC);DeLong's test was used for comparison.Results:In the external test cohort,the DCE model showed the highest performance(AUC=0.76)but was not significantly different from T2WI(AUC=0.72)and DWI(AUC=0.70)(all p>0.05).The combined radiomics model achieved an AUC of 0.82,outperforming DWI and T2WI(p<0.05),but was not significantly different from the DCE model(p>0.05).The combined MRI model demonstrated the highest AUC of 0.84 and notably improved radiologist diagnostic accuracy.A nomogram based on the combined MRI model was developed to assist clinical decision‐making by providing individualized risk predictions.The higher‐risk group based on the model's predictive probability showed a significantly worse prognosis(p<0.001).Conclusion:The combined radiomics model outperformed single‐sequence models in predicting ALNM.The combined MRI model demonstrated the highest performance,improving diagnostic accuracy and showing potential for prognostic prediction.展开更多
Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American C...Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American College of Radiology revised the PI-RADS to address the limitations of version 1 in December 2014.This study aimed to determine whether the PI-RADS version 2 （PI-RADS v2） scoring system improves the diagnostic accuracy of mp-MRI of the prostate compared with PI-RADS v1.Methods：This retrospective study was approved by the institutional review board.A total of 401 consecutive patients,with clinically suspicious Pca undergoing 3.0 T mp-MRI （T2-weighted imaging ＋ diffusion-weighted imaging ＋ DCE） before transrectal ultrasound-guided biopsy between June 2013 and July 2015,were included in the study.All patients were scored using the 5-point PI-RADS scoring system based on either PI-RADS v1 or v2.Receiver operating characteristics were calculated for statistical analysis.Sensitivity,specificity,and diagnostic accuracy were compared using McNemar＇s test.Results：Pca was present in 150 of 401 （37.41%） patients.When we pooled data from both peripheral zone （PZ） and transition zone （TZ）,the areas under the curve were 0.889 for PI-RADS v1 and 0.942 for v2 （P =0.0001）.Maximal accuracy was achieved with a score threshold of 4.At this threshold,in the PZ,similar sensitivity,specificity,and accuracy were achieved with v 1 and v2 （all P 〉 0.05）.In the TZ,sensitivity was higher for v2 than for v1 （96.36% vs.76.36%,P =0.003）,specificity was similar for v2 and v1 （90.24% vs.84.15%,P =0.227）,and accuracy was higher for v2 than for v1 （92.70% vs.81.02%,P =0.002）.Conclusions：Both v1 and v2 showed good diagnostic performance for the detection of Pca.However,in the TZ,the performance was better with v2 than with v1.展开更多
Phenomics explores the complex interactions among genes,epigenetics,symbiotic microorganisms,diet,and environmental exposure based on the physical,chemical,and biological characteristics of individuals and groups.Incr...Phenomics explores the complex interactions among genes,epigenetics,symbiotic microorganisms,diet,and environmental exposure based on the physical,chemical,and biological characteristics of individuals and groups.Increasingly efficient and comprehensive phenotyping techniques have been integrated into modern phenomics-related research.Multicolor flow cytometry technology provides more measurement parameters than conventional flow cytometry.Based on detailed descriptions of cell phenotypes,rare cell populations and cell subsets can be distinguished,new cell phenotypes can be discovered,and cell apoptosis characteristics can be detected,which will expand the potential of cell phenomics research.Based on the enhancements in multicolor flow cytometry hardware,software,reagents,and method design,the present review summarizes the recent advances and applications of multicolor flow cytometry in cell phenomics,illuminating the potential of applying phenomics in future studies.展开更多
Objectives:To assess the role of multiparametric magnetic resonance imaging(mp-MRI)in the diagnosis and staging of urinary bladder cancer(BC).Materials and methods:Fifty patients diagnosed with bladder masses underwen...Objectives:To assess the role of multiparametric magnetic resonance imaging(mp-MRI)in the diagnosis and staging of urinary bladder cancer(BC).Materials and methods:Fifty patients diagnosed with bladder masses underwent mp-MRI study.The results of 3 image sets were analyzed and compared with the histopathological results as a reference standard:T2-weighted image(T2WI)plus dynamic contrast-enhanced(DCE),T2WI plus diffusion-weighted images(DWI),and mp-MRI,including T2WI plus DWI and DCE.The diagnostic accuracy of mp-MRI was evaluated using receiver operating characteristic curve analysis.Results:The accuracy of T2WI plus DCE for detecting muscle invasion of BC was 79.5%with a fair agreement with histopathological examination(κ=0.59);this percentage increased up to 88.6%using T2WI plus DWI,with good agreement with histopathological examination(κ=0.74),whereas mp-MRI had the highest overall accuracy(95.4%)and excellent agreement with histopathological data(κ=0.83).Multiparametric MRI can differentiate between low-and high-grade bladder tumors with a high sensitivity and specificity of 93.3%and 98.3%,respectively.Conclusions:Multiparametric MRI is an acceptable method for the preoperative detection and accurate staging of BC,with reasonable accuracy in differentiating between low-and high-grade BC.展开更多
Background:To evaluate the predictive values of Prostate Imaging Reporting and Data System version 2(PI-RADS v2),prostate-specific antigen(PSA)level,PSA density(PSAD),digital rectal examination findings,and prostate v...Background:To evaluate the predictive values of Prostate Imaging Reporting and Data System version 2(PI-RADS v2),prostate-specific antigen(PSA)level,PSA density(PSAD),digital rectal examination findings,and prostate volume,individually and in combination,for the detection of prostate cancer(Pca)in biopsy-naïve patients.Methods:We retrospectively analyzed 630 patients who underwent transrectal systematic prostate biopsy following prostate multiparametric magnetic resonance imaging.A standard 12-core biopsy procedure was performed.Univariate and multivariate analyses were performed to determine the significant predictors of clinically significant cancer but not Pca.Results:The median age,PSA level,and PSAD were 70 years,8.6 ng/mL,and 0.18 ng/mL/mL,respectively.A total of 374(59.4%)of 630 patients were biopsy-positive for Pca,and 241(64.4%)of 374 were diagnosed with clinically significant Pca(csPCa).The PI-RADS v2 score and PSAD were independent predictors of Pca and csPCa.The PI-RADS v2 score of 5 regardless of the PSAD value,or PI-RADS v2 score of 4 plus a PSAD of<0.3 ng/mL/mL,was associated with the highest csPCa detection rate(36.1%-82.1%).Instead,the PI-RADS v2 score of<3 and PSAD of<0.3 ng/mL/mL yielded the lowest risk of csPCa.Conclusion:The combination of the PI-RADS v2 score and PSAD could prove to be a helpful and reliable diagnostic tool before performing prostate biopsies.Patients with a PI-RADS v2 score of<3 and PSAD of<0.3 ng/mL/mL could potentially avoid a prostate biopsy.展开更多
In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal s...In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).展开更多
Type 2 diabetes mellitus (T2DM) and obesity are growing global pandemics thatshares the common characteristic of insulin resistance (IR). IR leads to progressive β-cell failure, worsening T2DM and its cardiovascular ...Type 2 diabetes mellitus (T2DM) and obesity are growing global pandemics thatshares the common characteristic of insulin resistance (IR). IR leads to progressive β-cell failure, worsening T2DM and its cardiovascular complications. Thus, earlydiagnosis of IR is important to prevent and reverse β-cell dedifferentiation.However, there is a lack of accessible, non-invasive and affordable tools to earlydiagnose and stratify IR. The gold standard method used in the research setting isthe hyperinsulinemic-euglycemic clamp, however it is invasive, laborious,expensive and difficult to apply at a large scale. Hou et al presents a potentialnovel surrogate biomarker for diagnosing IR in T2DM. Magnetic resonanceimaging derived biomarkers can potentially become the accessible and noninvasivealternative to the hyperinsulinemic-euglycemic clamp, enabling thetimely diagnosis of IR with potential clinical applications in T2DM treatments andpreventative care.展开更多
Objective This study aimed to assess the local staging of bladder tumors in patients utilizing preoperative multiparametric MRI(mpMRI)and to demonstrate the clinical efficacy of this method through a comparative analy...Objective This study aimed to assess the local staging of bladder tumors in patients utilizing preoperative multiparametric MRI(mpMRI)and to demonstrate the clinical efficacy of this method through a comparative analysis with corresponding histopathological findings.Methods Between November 2020 and April 2022,63 patients with a planned cystoscopy and a preliminary or previous diagnosis of bladder tumor were included.All participants underwent mpMRI,and Vesical Imaging Reporting and Data System(VI-RADS)criteria were applied to assess the recorded images.Subsequently,obtained biopsies were histopathologically examined and compared with radiological findings.Results Of the 63 participants,60 were male,and three were female.Categorizing tumors with a VI-RADS score of>3 as muscle invasive,84%were radiologically classified as having an invasive bladder tumor.However,histopathological results indicated invasive bladder tumors in 52%of cases.Sensitivity of the VI-RADS score was 100%;specificity was 23%;the negative predictive value was 100%;and the positive predictive value was 62%.Conclusion The scoring system obtained through mpMRI,VI-RADS,proves to be a successful method,particularly in determining the absence of muscle invasion in bladder cancer.Its efficacy in detecting muscle invasion in bladder tumors could be further enhanced with additional studies,suggesting potential for increased diagnostic efficiency through ongoing research.The VI-RADS could enhance the selection of patients eligible for accurate diagnosis and treatment.展开更多
Background:Multiparametric magnetic resonance imaging(mpMRI)has significantly advanced prostate cancer(PCa)detection,yet decisions on invasive biopsy with moderate prostate imaging reporting and data system(PI-RADS)sc...Background:Multiparametric magnetic resonance imaging(mpMRI)has significantly advanced prostate cancer(PCa)detection,yet decisions on invasive biopsy with moderate prostate imaging reporting and data system(PI-RADS)scores remain ambiguous.Methods:To explore the decision-making capacity of Generative Pretrained Transformer-4(GPT-4)for automated prostate biopsy recommendations,we included 2299 individuals who underwent prostate biopsy from 2018 to 2023 in 3 large medical centers,with available mpMRI before biopsy and documented clinical-histopathological records.GPT-4 generated structured reports with given prompts.The performance of GPT-4 was quantified using confusion matrices,and sensitivity,specificity,as well as area under the curve were calculated.Multiple artificial evaluation procedures were conducted.Wilcoxon’s rank sum test,Fisher’s exact test,and Kruskal-Wallis tests were used for comparisons.Results:Utilizing the largest sample size in the Chinese population,patients with moderate PI-RADS scores(scores 3 and 4)accounted for 39.7%(912/2299),defined as the subset-of-interest(SOI).The detection rates of clinically significant PCa corresponding to PI-RADS scores 2-5 were 9.4%,27.3%,49.2%,and 80.1%,respectively.Nearly 47.5%(433/912)of SOI patients were histopathologically proven to have undergone unnecessary prostate biopsies.With the assistance of GPT-4,20.8%(190/912)of the SOI population could avoid unnecessary biopsies,and it performed even better[28.8%(118/410)]in the most heterogeneous subgroup of PI-RADS score 3.More than 90.0%of GPT-4-generated reports were comprehensive and easy to understand,but less satisfied with the accuracy(82.8%).GPT-4 also demonstrated cognitive potential for handling complex problems.Additionally,the Chain of Thought method enabled us to better understand the decision-making logic behind GPT-4.Eventually,we developed a ProstAIGuide platform to facilitate accessibility for both doctors and patients.Conclusions:This multi-center study highlights the clinical utility of GPT-4 for prostate biopsy decision-making and advances our understanding of the latest artificial intelligence implementation in various medical scenarios.展开更多
文摘Artificial intelligence(AI)is revolutionizing medical imaging,particularly in chronic liver diseases assessment.AI technologies,including machine learning and deep learning,are increasingly integrated with multiparametric ultrasound(US)techniques to provide more accurate,objective,and non-invasive evaluations of liver fibrosis and steatosis.Analyzing large datasets from US images,AI enhances diagnostic precision,enabling better quantification of liver stiffness and fat content,which are essential for diagnosing and staging liver fibrosis and steatosis.Combining advanced US modalities,such as elastography and doppler imaging with AI,has demonstrated improved sensitivity in identifying different stages of liver disease and distinguishing various degrees of steatotic liver.These advancements also contribute to greater reproducibility and reduced operator dependency,addressing some of the limitations of traditional methods.The clinical implications of AI in liver disease are vast,ranging from early detection to predicting disease progression and evaluating treatment response.Despite these promising developments,challenges such as the need for large-scale datasets,algorithm transparency,and clinical validation remain.The aim of this review is to explore the current applications and future potential of AI in liver fibrosis and steatosis assessment using multiparametric US,highlighting the technological advances and clinical relevance of this emerging field.
文摘BACKGROUND Endoscopic variceal band ligation(EVBL)represents a pivotal treatment in the prophylaxis of esophageal varices bleeding in patients with cirrhosis,but in some cases a single session of EVBL is unable to eradicate esophageal varices completely,and a control endoscopy after 2-4 weeks is required to assess eradication and/or the need for another band ligation.Liver stiffness measurement(LSM)is being increasingly used as a screening non-invasive tool to predict varices according to Baveno VII criteria.However,to date,there are no instruments able to non-invasively predict the outcome of EVBL.AIM To identify non-invasive predictors of varices eradication(VE)after EVBL through multiparametric ultrasound(US).Secondary aim was to develop a prediction model of successful variceal eradication based on non-invasive parameters.METHODS We prospectively enrolled consecutive cirrhotic patients intolerant or with contraindications to beta-blockers undergoing EVBL for bleeding prophylaxis.Patients underwent multiparametric US with LSM,spleen stiffness measurement(SSM)and dynamic contrastenhanced US(DCE-US)on liver parenchyma and portal vein,at baseline(T0)and one month(T1)after EVBL.Each US parameter and their variations from baseline were correlated with VE evaluated by control endoscopy performed at T1.RESULTS We enrolled 41 patients(median age 64 years,75.6%males).At T128 patients(68.3%)reached VE,whereas 13(31.7%)required a second EVBL.Patients who achieved VE showed a significant decrease in SSM(P=0.018),and a significant increase in peak enhancement,area under the curve and wash-in rate of both liver parenchyma and portal vein after treatment(P<0.001).Statistically significant differences between the two groups of patients were incorporated in a multivariate analysis and used to develop three prediction models.CONCLUSION A multimodal US approach based on DCE-US parameters,LSM and SSM might become a reliable predictor of VE and a useful non-invasive alternative to endoscopy.
基金Supported by Shenzhen High-level Hospital Construction Fund.
文摘BACKGROUND Patients harboring gene mutations like KRAS,NRAS,and BRAF demonstrate highly variable responses to chemotherapy,posing challenges for treatment optimization.Multiparametric magnetic resonance imaging(MRI),with its noninvasive capability to assess tumor characteristics in detail,has shown promise in evaluating treatment response and predicting therapeutic outcomes.This technology holds potential for guiding personalized treatment strategies tailored to individual patient profiles,enhancing the precision and effectiveness of colorectal cancer care.AIM To create a multiparametric MRI-based predictive model for assessing chemotherapy efficacy in colorectal cancer patients with gene mutations.METHODS This retrospective study was conducted in a tertiary hospital,analyzing 157 colorectal cancer patients with gene mutations treated between August 2022 and December 2023.Based on chemotherapy outcomes,the patients were categorized into favorable(n=60)and unfavorable(n=50)response groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of chemotherapy efficacy.A predictive nomogram was constructed using significant variables,and its performance was assessed using the area under the receiver operating characteristic curve(AUC)in both training and validation sets.RESULTS Univariate analysis identified that tumor differentiation,T2 signal intensity ratio,tumor-to-anal margin distance,and MRI-detected lymph node metastasis as significantly associated with chemotherapy response(P<0.05).Multivariate Logistics regression confirmed these four parameters as independent predictors.The predictive model demonstrated strong discrimination,with an AUC of 0.938(sensitivity:86%;specificity:92%)in the training set,and 0.942(sensitivity:100%;specificity:83%)in the validation set.CONCLUSION We established and validated a multiparametric MRI-based model for predicting chemotherapy response in colorectal cancer patients with gene mutations.This model holds promise for guiding individualized treatment strategies.
文摘BACKGROUND In metabolic dysfunction-associated steatotic liver disease(MASLD)the identi-fication of patients at high risk of evolution to metabolic dysfunction-associated steatohepatitis(MASH)is challenging.AIM To investigate the performance of different ultrasound(US)-based techniques for the non-invasive assessment of liver fibrosis,steatosis,and inflammation in these patients.METHODS We collected data from consecutive patients who underwent liver biopsy for suspected MASLD between January 2019 and December 2021.Two-dimensional shear-wave elastography,sound speed plane-wave US,attenuation plane-wave US,viscosity plane-wave US(Vi.PLUS)using Aixplorer MACH 30 system,and transient elastography and controlled attenuation parameter from FibroScan were measured before biopsy.RESULTS A total of 120 participants were enrolled.Both transient elastography and two-dimensional shear-wave elasto-graphy showed good performance for the diagnosis of advanced fibrosis[area under the receiver operating charac-teristic curve(AUROC)=0.93 and 0.90,respectively].The diagnostic performance of Vi.PLUS for the presence of both ballooning grade≥1 and lobular inflammation≥1 was good with an AUROC of 0.72.A score based on Vi.PLUS,aspartate aminotransferase,and sound speed plane-wave US[viscosity-aspartate aminotransferase-speed of sound MASH ultrasound score(VAS-MASH-US score)]had a good accuracy for the diagnosis of MASH(AUROC=0.75).VAS-MASH-US score>0.6 showed a good sensitivity for MASH diagnosis(79.0%).According to decision curve analysis,the application of the VAS-MASH-US score would lead to a more accurate selection of patients who are candidates to undergo liver biopsy and would reduce the need for invasive procedures for patients at low risk of MASH.CONCLUSION Multiparametric US allows the non-invasive assessment of steatosis,inflammation,and fibrosis in patients with MASLD.Liver viscosity improved the capability of non-invasively identifying patients with MASH.
文摘Colorectal cancer(CRC) is a heterogeneous disease, with a diverse and plastic immune cell infiltrate. These immune cells play an important role in regulating tumour growth-progression or elimination. Some populations of cells have a strong correlation with disease-free survival, making them useful prognostic markers. In particular, the infiltrate of CD3^+ and CD8^+ T cells into CRC tumours has been validated worldwide as a valuable indicator of patient prognosis. However, the heterogeneity of the immune response, both between patients with tumours of different molecular subtypes, and within the tumour itself, necessitates the use of multiparametric analysis in the investigation of tumour-specific immune responses. This review will outline the multiparametric analysis techniques that have been developed and applied to studying the role of immune cells in the tumour, with a focus on colorectal cancer. Because much of the data in this disease relates to T cell subsets and heterogeneity, we have used T cell populations as examples throughout. Flow and mass cytometry give a detailed representation of the cells within the tumour in a single-cell suspension on a per-cell basis. Imaging technologies, such as imaging mass cytometry, are used to investigate increasing numbers of markers whilst retaining the spatial and structural information of the tumour section and the infiltrating immune cells. Together, the analyses of multiple immune parameters can provide valuable information to guide clinical decision-making in CRC.
文摘BACKGROUND Non-invasive assessment of non-alcoholic steatohepatitis(NASH)is increasing in desirability due to the invasive nature and costs associated with the current form of assessment;liver biopsy.Quantitative multiparametric magnetic resonance imaging(mpMRI)to measure liver fat(proton density fat fraction)and fibroinflammatory disease[iron-corrected T1(cT1)],as well as elastography techniques[vibration-controlled transient elastography(VCTE)liver stiffness measure],magnetic resonance elastography(MRE)and 2D Shear-Wave elastography(SWE)to measure stiffness and fat(controlled attenuated parameter,CAP)are emerging alternatives which could be utilised as safe surrogates to liver biopsy.AIM To evaluate the agreement of non-invasive imaging modalities with liver biopsy,and their subsequent diagnostic accuracy for identifying NASH patients.METHODS From January 2019 to February 2020,Japanese patients suspected of NASH were recruited onto a prospective,observational study and were screened using noninvasive imaging techniques;mpMRI with LiverMultiScan®,VCTE,MRE and 2DSWE.Patients were subsequently biopsied,and samples were scored by three independent pathologists.The diagnostic performances of the non-invasive imaging modalities were assessed using area under receiver operating characteristic curve(AUC)with the median of the histology scores as the gold standard diagnoses.Concordance between all three independent pathologists was further explored using Krippendorff’s alpha(a)from weighted kappa statistics.RESULTS N=145 patients with mean age of 60(SD:13 years.),39%females,and 40%with body mass index≥30 kg/m2 were included in the analysis.For identifying patients with NASH,MR liver fat and cT1 were the strongest performing individual measures(AUC:0.80 and 0.75 respectively),and the mpMRI metrics combined(cT1 and MR liver fat)were the overall best non-invasive test(AUC:0.83).For identifying fibrosis≥1,MRE performed best(AUC:0.97),compared to VCTE-liver stiffness measure(AUC:0.94)and 2D-SWE(AUC:0.94).For assessment of steatosis≥1,MR liver fat was the best performing non-invasive test(AUC:0.92),compared to controlled attenuated parameter(AUC:0.75).Assessment of the agreement between pathologists showed that concordance was best for steatosis(a=0.58),moderate for ballooning(a=0.40)and fibrosis(a=0.40),and worst for lobular inflammation(a=0.11).CONCLUSION Quantitative mpMRI is an effective alternative to liver biopsy for diagnosing NASH and non-alcoholic fatty liver,and thus may offer clinical utility in patient management.
基金supported by the National Natural Science Foundation of China(grant No.81902578,81974098,and 81974099)the National Key Research and Development Program of China(grant No.SQ2017YFSF090096).
文摘We attempted to perform risk categories based on the free/total prostate-specific antigen ratio (%fPSA), prostate-specific antigen(PSA) density (PSAD, in ng ml^(−2)), and multiparametric magnetic resonance imaging (mpMRI) step by step, with the goal ofdetermining the best clinical diagnostic strategy to avoid unnecessary tests and prostate biopsy (PBx) in biopsy-naïve men with PSAlevels ranging from 4 ng ml^(−1) to 10 ng ml^(−1). We included 439 patients who had mpMRI and PBx between August 2018 and July2021 (West China Hospital, Chengdu, China). To detect clinically significant prostate cancer (csPCa) on PBx, receiver-operatingcharacteristic (ROC) curves and their respective area under the curve were calculated. Based on %fPSA, PSAD, and ProstateImaging-Reporting and Data System (PI-RADS) scores, the negative predictive value (NPV) and positive predictive value (PPV) werecalculated sequentially. The optimal %fPSA threshold was determined to be 0.16, and the optimal PSAD threshold was 0.12 for%fPSA ≥0.16 and 0.23 for %fPSA <0.16, respectively. When PSAD <0.12 was combined with patients with %fPSA ≥0.16, the NPVof csPCa increased from 0.832 (95% confidence interval [CI]: 0.766–0.887) to 0.931 (95% CI: 0.833–0.981);the detection rateof csPCa was similar when further stratified by PI-RADS scores (P = 0.552). Combining %fPSA <0.16 with PSAD ≥0.23 ng ml^(−2)predicted significantly more csPCa patients than those with PSAD <0.23 ng ml^(−2) (58.4% vs 26.7%, P < 0.001). Using PI-RADSscores 4 and 5, the PPV was 0.739 (95% CI: 0.634–0.827) when further stratified by mpMRI results. In biopsy-naïve patientswith PSA level of 4–10 ng ml^(−1), stratification of %fPSA and PSAD combined with PI-RADS scores may be useful in the decisionmaking process prior to undergoing PBx.
基金This work was supported in part by the National Natural Science Foundation of China(No.81671695,81725008,81801700 and 81927801)Fundamental Research Funds for the Central Universities(No.22120190213)+1 种基金Shanghai Municipal Health Commission(No.2019LJ21 and SHSLCZDZK03502)the Science and Technology Commission of Shanghai Municipality(No.19DZ2251100 and 19441903200).
文摘The purpose of this study was to explore transrectal ultrasound(TRUS)findings of prostate cancer(PCa)guided by multiparametric magnetic resonance imaging(mpMRI)and to improve the Prostate Imaging Reporting and Data System(PI-RADS)system for avoiding unnecessary mpMRI-guided targeted biopsy(TB).From January 2018 to October 2019,fusion mpMRI and TRUS-guided biopsies were performed in 162 consecutive patients.The study included 188 suspicious lesions on mpMRI in 156 patients,all of whom underwent mpMRI-TRUS fusion imaging-guided TB and 12-core transperineal systematic biopsy(SB).Univariate analyses were performed to investigate the relationship between TRUS features and PCa.Then,logistic regression analysis with generalized estimating equations was performed to determine the independent predictors of PCa and obtain the fitted probability of PCa.The detection rates of PCa based on TB alone,SB alone,and combined SB and TB were 55.9%(105 of 188),52.6%(82 of 156),and 62.8%(98 of 156),respectively.The significant predictors of PCa on TRUS were hypoechogenicity(odds ratio[OR]:9.595,P=0.002),taller-than-wide shape(OR:3.539,P=0.022),asymmetric vascular structures(OR:3.728,P=0.031),close proximity to capsule(OR:3.473,P=0.040),and irregular margins(OR:3.843,P=0.041).We propose subgrouping PI-RADS score 3 into categories 3a,3b,3c,and 3d based on different numbers of TRUS predictors,as the creation of PI-RADS 3a(no suspicious ultrasound features)could avoid 16.7%of mpMRI-guided TBs.Risk stratification of PCa with mpMRI-TRUS fusion imaging-directed ultrasound features could avoid unnecessary mpMRI-TBs.
文摘Liver disease accounts for approximately 2 million deaths per year worldwide.All chronic liver diseases(CLDs),whether of toxic,genetic,autoimmune,or infectious origin,undergo typical histological changes in the structure of the tissue.These changes may include the accumulation of extracellular matrix material,fats,triglycerides,or tissue scarring.Noninvasive methods for diagnosing CLD,such as conventional B-mode ultrasound(US),play a significant role in diagnosis.Doppler US,when coupled with B-mode US,can be helpful in evaluating the hemodynamics of hepatic vessels and detecting US findings associated with hepatic decompensation.US elastography can assess liver stiffness,serving as a surrogate marker for liver fibrosis.It is important to note that interpreting these values should not rely solely on a histological classification.Contrast-enhanced US(CEUS)provides valuable information on tissue perfusion and enables excellent differentiation between benign and malignant focal liver lesions.Clinical evaluation,the etiology of liver disease,and the patient current comorbidities all influence the interpretation of liver stiffness measurements.These measurements are most clinically relevant when interpreted as a probability of compensated advanced CLD.B-mode US offers a subjective estimation of fatty infiltration and has limited sensitivity for mild steatosis.The controlled attenuation parameter requires a dedicated device,and cutoff values are not clearly defined.Quan-titative US parameters for liver fat estimation include the attenuation coefficient,backscatter coefficient,and speed of sound.These parameters offer the advantage of providing fat quantification alongside B-mode evaluation and other US parameters.Multiparametric US(MPUS)of the liver introduces a new concept for complete noninvasive diagnosis.It encourages examiners to utilize the latest features of an US machine,including conventional B-mode,liver stiffness evaluation,fat quantification,dispersion imaging,Doppler US,and CEUS for focal liver lesion characterization.This comprehensive approach allows for diagnosis in a single examination,providing clinicians worldwide with a broader perspective and becoming a cornerstone in their diagnostic arsenal.MPUS,in the hands of skilled clinicians,becomes an invaluable predictive tool for diagnosing,staging,and monitoring CLD.
文摘Portal hypertension,the most common complication in liver cirrhosis,is characterized by a pathologic increase in portal venous pressure.Portal hypertension is defined as a pressure gradient greater than 5 mmHg between the portal vein and the inferior caval vein.Clinically significant portal hypertension is determined by a hepatic venous pressure gradient(HVPG)exceeding 10 mmHg.Complications are likely to occur if the pressure exceeds this threshold.The gold standard for assessing portal hypertension is the measurement of HVPG,which is an invasive procedure.This review discusses the various multiparametric capabilities of ultrasound,including B-mode,color Doppler imaging,Doppler measurement,contrast-enhanced ultrasound,endoscopic ultrasound,and elastography to diagnose portal hypertension and assess its severity.
文摘To the Editor,Hepatic venous pressure gradient(HVPG)measurement is the gold standard measurement for diagnosing portal hypertension(PH),a critical complication of liver cirrhosis.However,HVPG is an invasive and highly specialized technique.Noninvasive measurements would be extremely valuable to assess portal venous pressure[1].It is therefore with interest that Möller et al.[2]report noninvasive multiparametric ultrasound-based criteria and measurements for evaluating PH comprehensively.
基金supported by National Natural Science Foundation of China,(Nos.82302314,81901711)Guangdong Basic and Applied Basic Research Foundation,(Nos.2022A1515110792,2023A1515220097,2024A1515010653)+2 种基金Medical Scientific Research Foundation of Guangdong Province(No.A2023073)Science and technology Projects in Guangzhou,(Nos.2023A04J1275,2024A03J1030)Guangzhou First People's Hospital Frontier Medical Technology Project(QY‐C04).
文摘Background:The predictive value of different MRI sequences for axillary lymph node metastasis(ALNM)in patients with invasive breast cancer remains unclear.This study compared the performance of radiomics models based on individual and combined MRI sequences for the preoperative prediction of ALNM and evaluated the clinical application value of the optimal model.Methods:This retrospective study included 454 patients(mean±SD age 50.9±10.7 years)diagnosed with invasive breast cancer from two centers,with 382 patients from Center 1(training cohort)and 72 patients from Center 2(external test cohort).Tumor segmentation and radiomics feature extraction were performed on T2‐weighted imaging(T2WI),diffusion‐weighted imaging(DWI),and dynamic contrast‐enhanced(DCE)images.The least absolute shrinkage and selection operator with 10‐fold cross‐validation was used for feature selection and radiomics score construction.Three single‐sequence models and one multisequence radiomics model were developed,and the optimal model was combined with conventional MRI features to create a combined MRI model.The combined model's performance was compared to radiologists'diagnoses.A nomogram was developed based on the optimal model and correlated with prognosis using the Kaplan–Meier curve and Cox proportional hazard regression.Model performance was evaluated using area under the curve(AUC);DeLong's test was used for comparison.Results:In the external test cohort,the DCE model showed the highest performance(AUC=0.76)but was not significantly different from T2WI(AUC=0.72)and DWI(AUC=0.70)(all p>0.05).The combined radiomics model achieved an AUC of 0.82,outperforming DWI and T2WI(p<0.05),but was not significantly different from the DCE model(p>0.05).The combined MRI model demonstrated the highest AUC of 0.84 and notably improved radiologist diagnostic accuracy.A nomogram based on the combined MRI model was developed to assist clinical decision‐making by providing individualized risk predictions.The higher‐risk group based on the model's predictive probability showed a significantly worse prognosis(p<0.001).Conclusion:The combined radiomics model outperformed single‐sequence models in predicting ALNM.The combined MRI model demonstrated the highest performance,improving diagnostic accuracy and showing potential for prognostic prediction.
基金This study was supported by a grant of National Natural Science Foundation of China （No. 81171307）.
文摘Background：Prostate Imaging Reporting and Data System （PI-RADS） is a globally acceptable standardization for multiparametric magnetic resonance imaging （mp-MRI） in prostate cancer （PCa） diagnosis.The American College of Radiology revised the PI-RADS to address the limitations of version 1 in December 2014.This study aimed to determine whether the PI-RADS version 2 （PI-RADS v2） scoring system improves the diagnostic accuracy of mp-MRI of the prostate compared with PI-RADS v1.Methods：This retrospective study was approved by the institutional review board.A total of 401 consecutive patients,with clinically suspicious Pca undergoing 3.0 T mp-MRI （T2-weighted imaging ＋ diffusion-weighted imaging ＋ DCE） before transrectal ultrasound-guided biopsy between June 2013 and July 2015,were included in the study.All patients were scored using the 5-point PI-RADS scoring system based on either PI-RADS v1 or v2.Receiver operating characteristics were calculated for statistical analysis.Sensitivity,specificity,and diagnostic accuracy were compared using McNemar＇s test.Results：Pca was present in 150 of 401 （37.41%） patients.When we pooled data from both peripheral zone （PZ） and transition zone （TZ）,the areas under the curve were 0.889 for PI-RADS v1 and 0.942 for v2 （P =0.0001）.Maximal accuracy was achieved with a score threshold of 4.At this threshold,in the PZ,similar sensitivity,specificity,and accuracy were achieved with v 1 and v2 （all P 〉 0.05）.In the TZ,sensitivity was higher for v2 than for v1 （96.36% vs.76.36%,P =0.003）,specificity was similar for v2 and v1 （90.24% vs.84.15%,P =0.227）,and accuracy was higher for v2 than for v1 （92.70% vs.81.02%,P =0.002）.Conclusions：Both v1 and v2 showed good diagnostic performance for the detection of Pca.However,in the TZ,the performance was better with v2 than with v1.
基金This work was supported by National Key Project of China(2016YFA0502201 and 2017YFA0700404)Standard Technology Management Project(2013811)+1 种基金the State Administration for Market Regulation,National Science and Technology Basic Condition Platform project(APT2001)Natural Science Foundation of Shenzhen(JCYJ20190808150009605).
文摘Phenomics explores the complex interactions among genes,epigenetics,symbiotic microorganisms,diet,and environmental exposure based on the physical,chemical,and biological characteristics of individuals and groups.Increasingly efficient and comprehensive phenotyping techniques have been integrated into modern phenomics-related research.Multicolor flow cytometry technology provides more measurement parameters than conventional flow cytometry.Based on detailed descriptions of cell phenotypes,rare cell populations and cell subsets can be distinguished,new cell phenotypes can be discovered,and cell apoptosis characteristics can be detected,which will expand the potential of cell phenomics research.Based on the enhancements in multicolor flow cytometry hardware,software,reagents,and method design,the present review summarizes the recent advances and applications of multicolor flow cytometry in cell phenomics,illuminating the potential of applying phenomics in future studies.
文摘Objectives:To assess the role of multiparametric magnetic resonance imaging(mp-MRI)in the diagnosis and staging of urinary bladder cancer(BC).Materials and methods:Fifty patients diagnosed with bladder masses underwent mp-MRI study.The results of 3 image sets were analyzed and compared with the histopathological results as a reference standard:T2-weighted image(T2WI)plus dynamic contrast-enhanced(DCE),T2WI plus diffusion-weighted images(DWI),and mp-MRI,including T2WI plus DWI and DCE.The diagnostic accuracy of mp-MRI was evaluated using receiver operating characteristic curve analysis.Results:The accuracy of T2WI plus DCE for detecting muscle invasion of BC was 79.5%with a fair agreement with histopathological examination(κ=0.59);this percentage increased up to 88.6%using T2WI plus DWI,with good agreement with histopathological examination(κ=0.74),whereas mp-MRI had the highest overall accuracy(95.4%)and excellent agreement with histopathological data(κ=0.83).Multiparametric MRI can differentiate between low-and high-grade bladder tumors with a high sensitivity and specificity of 93.3%and 98.3%,respectively.Conclusions:Multiparametric MRI is an acceptable method for the preoperative detection and accurate staging of BC,with reasonable accuracy in differentiating between low-and high-grade BC.
文摘Background:To evaluate the predictive values of Prostate Imaging Reporting and Data System version 2(PI-RADS v2),prostate-specific antigen(PSA)level,PSA density(PSAD),digital rectal examination findings,and prostate volume,individually and in combination,for the detection of prostate cancer(Pca)in biopsy-naïve patients.Methods:We retrospectively analyzed 630 patients who underwent transrectal systematic prostate biopsy following prostate multiparametric magnetic resonance imaging.A standard 12-core biopsy procedure was performed.Univariate and multivariate analyses were performed to determine the significant predictors of clinically significant cancer but not Pca.Results:The median age,PSA level,and PSAD were 70 years,8.6 ng/mL,and 0.18 ng/mL/mL,respectively.A total of 374(59.4%)of 630 patients were biopsy-positive for Pca,and 241(64.4%)of 374 were diagnosed with clinically significant Pca(csPCa).The PI-RADS v2 score and PSAD were independent predictors of Pca and csPCa.The PI-RADS v2 score of 5 regardless of the PSAD value,or PI-RADS v2 score of 4 plus a PSAD of<0.3 ng/mL/mL,was associated with the highest csPCa detection rate(36.1%-82.1%).Instead,the PI-RADS v2 score of<3 and PSAD of<0.3 ng/mL/mL yielded the lowest risk of csPCa.Conclusion:The combination of the PI-RADS v2 score and PSAD could prove to be a helpful and reliable diagnostic tool before performing prostate biopsies.Patients with a PI-RADS v2 score of<3 and PSAD of<0.3 ng/mL/mL could potentially avoid a prostate biopsy.
文摘In the context of climate change,countries in West Africa are faced with recurrent flooding with catastrophic consequences,that makes it imperative to have access to rainfall information on fine spatial and temporal scales for better monitoring and prediction of these phenomena,as could be provided by weather radars.Based on an extensive archive of data from the X-band polarimetric radar and rain gauges observations gathered during the intensive AMMA campaigns in 2006–2007 and the Megha-Tropiques satellite measurement validation programme in 2010 in West Africa,we(i)simulated jointly realistic data for polarimetric radar variables and rain intensity using copula,and(ii)assessed rain rate estimation methods based on neural network(NN)inversion techniques and non-linearly calibrated parametric algorithms.The assessment of rainfall rate retrieval by these estimators is carried out using the part of the observations database not employed for calibration steps.The multiparametric algorithms R(ZH,K_(DP))and R(Z_(DR),K_(DP))perform better than R(ZH,Z_(DR))and R(ZH,Z_(DR),K_(DP)),especially since they are calibrated using copulas with upper tail dependencies,with KGE ranging in 0.68–0.75 and 0.79–0.82,respectively versus ranges of 0.40–0.64 and 0.20–0.51,for the two latter estimators.The neural network-based estimators RNN(Z_(DR),K_(DP))and RNN(ZH,K_(DP)),show KGE score characteristics comparable to those obtained from the best parametric relations,specifically optimized for the synthetic copula-based dataset.However,the neural network-based estimators were shown to be more robust when applied to a specific rainfall event.More specifically,neural network-based estimators trained on synthetic data are sensitive to the copulas’ability to capture the dependence between the variables of interest over the entire distribution of joint values.This leads to a near-cancellation of sensitivity to variability in the raindrop size distribution,as shown the coefficients of correlation near 1,especially for RNN(Z_(DR),K_(DP)),and for less extent RNN(Z_(H),K_(DP)).
文摘Type 2 diabetes mellitus (T2DM) and obesity are growing global pandemics thatshares the common characteristic of insulin resistance (IR). IR leads to progressive β-cell failure, worsening T2DM and its cardiovascular complications. Thus, earlydiagnosis of IR is important to prevent and reverse β-cell dedifferentiation.However, there is a lack of accessible, non-invasive and affordable tools to earlydiagnose and stratify IR. The gold standard method used in the research setting isthe hyperinsulinemic-euglycemic clamp, however it is invasive, laborious,expensive and difficult to apply at a large scale. Hou et al presents a potentialnovel surrogate biomarker for diagnosing IR in T2DM. Magnetic resonanceimaging derived biomarkers can potentially become the accessible and noninvasivealternative to the hyperinsulinemic-euglycemic clamp, enabling thetimely diagnosis of IR with potential clinical applications in T2DM treatments andpreventative care.
文摘Objective This study aimed to assess the local staging of bladder tumors in patients utilizing preoperative multiparametric MRI(mpMRI)and to demonstrate the clinical efficacy of this method through a comparative analysis with corresponding histopathological findings.Methods Between November 2020 and April 2022,63 patients with a planned cystoscopy and a preliminary or previous diagnosis of bladder tumor were included.All participants underwent mpMRI,and Vesical Imaging Reporting and Data System(VI-RADS)criteria were applied to assess the recorded images.Subsequently,obtained biopsies were histopathologically examined and compared with radiological findings.Results Of the 63 participants,60 were male,and three were female.Categorizing tumors with a VI-RADS score of>3 as muscle invasive,84%were radiologically classified as having an invasive bladder tumor.However,histopathological results indicated invasive bladder tumors in 52%of cases.Sensitivity of the VI-RADS score was 100%;specificity was 23%;the negative predictive value was 100%;and the positive predictive value was 62%.Conclusion The scoring system obtained through mpMRI,VI-RADS,proves to be a successful method,particularly in determining the absence of muscle invasion in bladder cancer.Its efficacy in detecting muscle invasion in bladder tumors could be further enhanced with additional studies,suggesting potential for increased diagnostic efficiency through ongoing research.The VI-RADS could enhance the selection of patients eligible for accurate diagnosis and treatment.
基金supported by the Beijing Key Clinical Specialty Project(20240930)the National Natural Science Foundation of China(NSFC 82373436)+7 种基金the Beijing Hospitals Authority’Youth Program(BHAYP,QML20230114)the Beijing Natural Science Foundation(BNSF Z200027)the Beijing Chaoyang Hospital Multi-disciplinary Team Program(CYDXK202204),the NSFC(62331001)the BNSF(Z200027)the NSFC(82202097)the BHAYP(QML20230113)the Training Fund for Open Projects at Clinical Institutes and Departments of Capital Medical University(CCMU2022ZKYXY010)the Beijing Scholars Program(No.[2015]160).
文摘Background:Multiparametric magnetic resonance imaging(mpMRI)has significantly advanced prostate cancer(PCa)detection,yet decisions on invasive biopsy with moderate prostate imaging reporting and data system(PI-RADS)scores remain ambiguous.Methods:To explore the decision-making capacity of Generative Pretrained Transformer-4(GPT-4)for automated prostate biopsy recommendations,we included 2299 individuals who underwent prostate biopsy from 2018 to 2023 in 3 large medical centers,with available mpMRI before biopsy and documented clinical-histopathological records.GPT-4 generated structured reports with given prompts.The performance of GPT-4 was quantified using confusion matrices,and sensitivity,specificity,as well as area under the curve were calculated.Multiple artificial evaluation procedures were conducted.Wilcoxon’s rank sum test,Fisher’s exact test,and Kruskal-Wallis tests were used for comparisons.Results:Utilizing the largest sample size in the Chinese population,patients with moderate PI-RADS scores(scores 3 and 4)accounted for 39.7%(912/2299),defined as the subset-of-interest(SOI).The detection rates of clinically significant PCa corresponding to PI-RADS scores 2-5 were 9.4%,27.3%,49.2%,and 80.1%,respectively.Nearly 47.5%(433/912)of SOI patients were histopathologically proven to have undergone unnecessary prostate biopsies.With the assistance of GPT-4,20.8%(190/912)of the SOI population could avoid unnecessary biopsies,and it performed even better[28.8%(118/410)]in the most heterogeneous subgroup of PI-RADS score 3.More than 90.0%of GPT-4-generated reports were comprehensive and easy to understand,but less satisfied with the accuracy(82.8%).GPT-4 also demonstrated cognitive potential for handling complex problems.Additionally,the Chain of Thought method enabled us to better understand the decision-making logic behind GPT-4.Eventually,we developed a ProstAIGuide platform to facilitate accessibility for both doctors and patients.Conclusions:This multi-center study highlights the clinical utility of GPT-4 for prostate biopsy decision-making and advances our understanding of the latest artificial intelligence implementation in various medical scenarios.
