Assessment of Intracardiac and Extracardiac Deformities in Patients with Various Types of Pulmonary Atresia by Dual-Source Computed Tomography

Background:Pulmonary atresia(PA)is a group of heterogeneous complex congenital heart disease.Only one study modality might not get a correct diagnosis.This study aims to investigate the diagnostic power of dualsource computed tomography(DSCT)for all intracardiac and extracardiac deformities in patients with PA compared with transthoracic echocardiography(TTE).Materials and Methods:This retrospective study enrolled 79 patients and divided them into three groups according to their main diagnosis.All associated malformations and clinical information,including treatments,were recorded and compared among the three groups.The diagnostic power of DSCT and TTE on all associated malformations were compared.The surgical index(McGoon ratio,pulmonary arterials index(PAI),and total neopulmonary arterial index)and radiation dose were calculated on the basis of DSCT.Results:Of the patients,32,30,and 17 were divided into the groups of PA with ventricular septal defect(VSD),PA with VSD and major aortopulmonary collateral arteries,and PA with other major malformations,respectively.Consequently,182,162,and 13 intracardiac,extracardiac,and other major malformations were diagnosed,respectively.Moreover,DSCT showed a better diagnostic performance in extracardiac deformities(154 vs.117,p<0.001),whereas TTE could diagnose intracardiac deformities better(159 vs.139,p=0.001).The McGoon ratio,PAI,and treatment methods were significantly different among the three groups(p=0.014,p=0.008,and p=0.018,respectively).Conclusion:More than one imaging modality should be used to make a correct diagnosis when clinically suspecting PA.DSCT is superior to TTE in diagnosing extracardiac deformities and could be used to roughly calculate surgical indices to optimize treatment strategy.

Truncus arteriosus:Diagnosis with dual-source computed tomography angiography and low radiation dose

Truncus arteriosus is an uncommon congenital cardiac abnormality which is characterized by a single arterial trunk origin from the heart that supplies both the systemic,pulmonary and coronary circulation.We present a preterm newborn female patient with type 2 truncusarteriosus,left superior vena cava and aberrant subclavian artery diagnosed with low dose dual-source cardiac computed tomography(CT).We discuss that low dose dual-source cardiac CT has more advantages than other imaging methods and it is an important modality for assessment of patients with conotruncal anomalies such as truncusarteriosus.

Non-enhanced Low-tube-voltage High-pitch Dual-source Computed Tomography with Sinogram Affirmed Iterative Reconstruction Algorithm of the Abdomen and Pelvis

Objective To investigate the image quality, radiation dose and diagnostic value of the low-tube-voltage high-pitch dual-source computed tomography(DSCT) with sinogram affirmed iterative reconstruction(SAFIRE) for non-enhanced abdominal and pelvic scans. Methods This institutional review board-approved prospective study included 64 patients who gave written informed consent for additional abdominal and pelvic scan with DSCT in the period from November to December 2012. The patients underwent standard non-enhanced CT scans(protocol 1) [tube voltage of 120 k Vp/pitch of 0.9/filtered back-projection(FBP) reconstruction] followed by high-pitch non-enhanced CT scans(protocol 2)(100 k Vp/3.0/SAFIRE). The total scan time, mean CT number, signal-to-noise ratio(SNR), image quality, lesion detectability and radiation dose were compared between the two protocols. Results The total scan time of protocol 2 was significantly shorter than that of protocol 1(1.4±0.1 seconds vs. 7.6±0.6 seconds, P<0.001). There was no significant difference between protocol 1 and protocol 2 in mean CT number of all organs(liver, 55.4±6.3 HU vs. 56.1±6.8 HU, P=0.214; pancreas, 43.6±5.9 HU vs. 43.7±5.8 HU, P=0.785; spleen, 47.9±3.9 HU vs. 49.4±4.3 HU, P=0.128; kidney, 32.2±2.3 HU vs. 33.1±2.3 HU, P=0.367; abdominal aorta, 44.8±5.6 HU vs. 45.0±5.5 HU, P=0.499; psoas muscle, 50.7±4.1 HU vs. 50.3±4.5 HU, P=0.279). SNR on images of protocol 2 was higher than that of protocol 1(liver, 5.0±1.2 vs. 4.5±1.1, P<0.001; pancreas, 4.0±1.0 vs. 3.6±0.8, P<0.001; spleen, 4.7±1.0 vs. 4.1±0.9, P<0.001; kidney, 3.1±0.6 vs. 2.8±0.6, P<0.001; abdominal aorta, 4.1±1.0 vs. 3.8±1.0, P<0.001; psoas muscle, 4.5±1.1 vs. 4.3±1.2, P=0.012). The overall image noise of protocol 2 was lower than that of protocol1(9.8±3.1 HU vs. 11.1±3.0 HU, P<0.001). Image quality of protocol 2 was good but lower than that of protocol 1(4.1±0.7 vs. 4.6±0.5, P<0.001). Protocol 2 perceived 229 of 234 lesions(97.9%) that were detected in protocol 1 in the abdomen and pelvis. Radiation dose of protocol 2 was lower than that of protocol 1(4.4±0.4 m Sv vs. 7.3±2.4 m Sv, P<0.001) and the mean dose reduction was 41.4%. Conclusion The high-pitch DSCT with SAFIRE can shorten scan time and reduce radiation dose while preserving image quality in non-enhanced abdominal and pelvic scans.

128-slice Dual-source Computed Tomography Coronary Angiography in Patients with Atrial Fibrillation: Image Quality and Radiation Dose of Prospectively Electrocardiogram-triggered Sequential Scan Compared with Retrospectively Electrocardiogram-gated Spiral

Objective To evaluate the image quality （IQ） and radiation dose of 128-slice dual-source computed tomography （DSCT） coronary angiography using prospectively electrocardiogram （ECG）-triggered sequen- tial scan mode compared with ECG-gated spiral scan mode in a population with atrial fibrillation. Methods Thirty-two patients with suspected coronary artery disease and permanent atrial fibrilla- tion referred for a second-generation 128-slice DSCT coronary angiography were included in the prospec- tive study. Of them, 17 patients （sequential group） were randomly selected to use a prospectively ECG.~triggered sequential scan, while the other 15 patients （spiral group） used a retrospectively ECG-gated spiral scan. The IQ was assessed by two readers independently, using a four-point grading scale from excel- lent （grade 1） to non-assessable （grade 4）, based on the American Heart Association 15-segment model. IQ of each segment and effective dose of each natient were comDared between the two groups. Results The mean heart rate （HR） of the sequential group was 96±27 beats per minute （bpm） with a variation range of 73±25 bpm, while the mean HR of the spiral group was 86±22 bpm with a variationrange of 65±24 bpm. Both of the mean FIR （t= 1.91, P=0.243） and HR variation range （t=0.950, P=0.350） had no significant difference between the two groups. In per-segment analysis, IQ of the sequential group vs. spiral group was rated as excellent （grade 1） in 190/244 （78%） vs. 177/217 （82%） by readerl and 197/245 （80%） vs. 174/214 （81%） by reader2, as non-assessable （grade 4） in 4/244 （2%） vs. 2/217 （1%） by readerl and 6/245 （2%） vs. 4/214 （2%） by reader2. Overall averaged IQ per-patient in the sequential and spiral group showed equally good （1.27＋0.19 vs. 1.25＋0.22, Z=-0.834, P=0.404）. The effective radiation dose of the sequential group reduced significantly compared with the spiral group （4.88±1.77 mSv vs. 10.20±3.64 mSv; t=-5.372, P=0.000）. Conclusion Compared with retrospectively ECG-gated spiral scan, prospectively ECG-triggered sequential DSCT coronary angiography provides similarly diagnostically valuable images in patients with atrial fibrillation and significantly reduces radiation dose.

Comparison of Intracardiac and Extracardiac Malformations Associated with Single Atrium,Single Ventricle and Single Atrium-Single Ventricle Using Dual-Source Computed Tomography

Background:To evaluate the qualitative and quantitative differences between intracardiac and extracardiac vascular malformations in patients with a single atrium(SA),single ventricle(SV)and single atrium-single ventricle(SA-SV)using dual-source CT(DSCT),and to compare the diagnostic performances of DSCT and transthoracic echocardiography(TTE).Methods:This retrospective study included 24 SA,75 SV and 24 SA-SV patients who underwent both DSCT and TTE before surgery.The diagnostic values of DSCT and TTE for intracardiac and extracardiac malformations were compared according to the surgical results.The diameters of the major artery and vein were measured and calculated based on DSCT and compared among the three groups.Results:The most common malformation was pulmonary artery disease in SA(50.0%)and SA-SV(45.8%)groups and patent ductus arteriosus(33.3%)in SV group.Although there was no statistical difference,arterial development was relatively poor in the SA group.All groups showed the trend of pulmonary artery stenosis(SA vs.SV vs.SA-SV:50.0%vs.30.7%vs.33.3%).There was a significant difference in mean pulmonary vein index among the groups(p=0.017).The diagnostic sensitivity of DSCT was superior to that of TTE for extracardiac malformations.Conclusions:The most common malformation in SA and SA-SV patients is pulmonary artery stenosis.SV patients are most likely to be complicated with patent ductus arteriosus.DSCT is more advantageous than TTE for diagnosing combined extracardiac malformations and can accurately measure the diameter of arteriovenous vessels.

Double contrast-enhanced ultrasonography improves diagnostic accuracy of T staging compared with multi-detector computed tomography in gastric cancer patients

BACKGROUND Gastric cancer(GC)is the most common malignant tumor and ranks third for cancer-related deaths among the worldwide.The disease poses a serious public health problem in China,ranking fifth for incidence and third for mortality.Knowledge of the invasive depth of the tumor is vital to treatment decisions.AIM To evaluate the diagnostic performance of double contrast-enhanced ultrasonography(DCEUS)for preoperative T staging in patients with GC by comparing with multi-detector computed tomography(MDCT).METHODS This single prospective study enrolled patients with GC confirmed by preoperative gastroscopy from July 2021 to March 2023.Patients underwent DCEUS,including ultrasonography(US)and intravenous contrast-enhanced ultrasonography(CEUS),and MDCT examinations for the assessment of preoperative T staging.Features of GC were identified on DCEUS and criteria developed to evaluate T staging according to the 8th edition of AJCC cancer staging manual.The diagnostic performance of DCEUS was evaluated by comparing it with that of MDCT and surgical-pathological findings were considered as the gold standard.RESULTS A total of 229 patients with GC(80 T1,33 T2,59 T3 and 57 T4)were included.Overall accuracies were 86.9%for DCEUS and 61.1%for MDCT(P<0.001).DCEUS was superior to MDCT for T1(92.5%vs 70.0%,P<0.001),T2(72.7%vs 51.5%,P=0.041),T3(86.4%vs 45.8%,P<0.001)and T4(87.7%vs 70.2%,P=0.022)staging of GC.CONCLUSION DCEUS improved the diagnostic accuracy of preoperative T staging in patients with GC compared with MDCT,and constitutes a promising imaging modality for preoperative evaluation of GC to aid individualized treatment decision-making.

Lymphatic plastic bronchitis and primary chylothorax: A study based on computed tomography lymphangiography

BACKGROUND This study presents an evaluation of the computed tomography lymphangio-graphy(CTL)features of lymphatic plastic bronchitis(PB)and primary chylotho-rax to improve the diagnostic accuracy for these two diseases.AIM To improve the diagnosis of lymphatic PB or primary chylothorax,a retrospective analysis of the clinical features and CTL characteristics of 71 patients diagnosed with lymphatic PB or primary chylothorax was performed.METHODS The clinical and CTL data of 71 patients(20 with lymphatic PB,41 with primary chylothorax,and 10 with lymphatic PB with primary chylothorax)were collected retrospectively.CTL was performed in all patients.The clinical manifestations,CTL findings,and conventional chest CT findings of the three groups of patients were compared.The chi-square test or Fisher's exact test was used to compare the differences among the three groups.A difference was considered to be statistically significant when P<0.05.RESULTS(1)The percentages of abnormal contrast medium deposits on CTL in the three groups were as follows:Thoracic duct outlet in 14(70.0%),33(80.5%)and 8(80.0%)patients;peritracheal region in 18(90.0%),15(36.6%)and 8(80.0%)patients;pleura in 6(30.0%),33(80.5%)and 9(90.0%)patients;pericardium in 6(30.0%),6(14.6%)and 4(40.0%)patients;and hilum in 16(80.0%),11(26.8%)and 7(70.0%)patients;and(2)the abnormalities on conven-tional chest CT in the three groups were as follows:Ground-glass opacity in 19(95.0%),18(43.9%)and 8(80.0%)patients;atelectasis in 4(20.0%),26(63.4%)and 7(70.0%)patients;interlobular septal thickening in 12(60.0%),11(26.8%)and 3(30.0%)patients;bronchovascular bundle thickening in 14(70.0%),6(14.6%)and 4(40.0%)patients;localized mediastinal changes in 14(70.0%),14(34.1%),and 7(70.0%)patients;diffuse mediastinal changes in 6(30.0%),5(12.2%),and 3(30.0%)patients;cystic lesions in the axilla in 2(10.0%),6(14.6%),and 2(20.0%)patients;and cystic lesions in the chest wall in 0(0%),2(4.9%),and 2(4.9%)patients.CONCLUSION CTL is well suited to clarify the characteristics of lymphatic PB and primary chylothorax.This method is an excellent tool for diagnosing these two diseases.

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma

Background:Gallbladder carcinoma(GBC)is highly malignant,and its early diagnosis remains difficult.This study aimed to develop a deep learning model based on contrast-enhanced computed tomography(CT)images to assist radiologists in identifying GBC.Methods:We retrospectively enrolled 278 patients with gallbladder lesions(>10 mm)who underwent contrast-enhanced CT and cholecystectomy and divided them into the training(n=194)and validation(n=84)datasets.The deep learning model was developed based on ResNet50 network.Radiomics and clinical models were built based on support vector machine(SVM)method.We comprehensively compared the performance of deep learning,radiomics,clinical models,and three radiologists.Results:Three radiomics features including LoG_3.0 gray-level size zone matrix zone variance,HHL firstorder kurtosis,and LHL gray-level co-occurrence matrix dependence variance were significantly different between benign gallbladder lesions and GBC,and were selected for developing radiomics model.Multivariate regression analysis revealed that age≥65 years[odds ratios(OR)=4.4,95%confidence interval(CI):2.1-9.1,P<0.001],lesion size(OR=2.6,95%CI:1.6-4.1,P<0.001),and CA-19-9>37 U/mL(OR=4.0,95%CI:1.6-10.0,P=0.003)were significant clinical risk factors of GBC.The deep learning model achieved the area under the receiver operating characteristic curve(AUC)values of 0.864(95%CI:0.814-0.915)and 0.857(95%CI:0.773-0.942)in the training and validation datasets,which were comparable with radiomics,clinical models and three radiologists.The sensitivity of deep learning model was the highest both in the training[90%(95%CI:82%-96%)]and validation[85%(95%CI:68%-95%)]datasets.Conclusions:The deep learning model may be a useful tool for radiologists to distinguish between GBC and benign gallbladder lesions.

The diagnostic yield for computed tomography pulmonary angiography in patients with anticoagulation

BACKGROUND:Patients who present to the emergency department(ED)for suspected pulmonary embolism(PE)are often on active oral anticoagulation(AC).However,the diagnostic yield of computed tomography pulmonary angiography(CTPA)in screening for PE in patients who present on AC has not been well characterized.We aim to investigate the diagnostic yield of CTPA in diagnosing PE depending on AC status.METHODS:We reviewed and analyzed the electronic medical records of patients who underwent CTPA for PE at a university hospital ED from June 1,2019,to March 25,2022.Primary outcome was the incidence of PE on CTPA depending on baseline AC status and indication for AC.RESULTS:Of 2,846 patients,242 were on AC for a history of venous thromboembolism(VTE),210 were on AC for other indications,and 2,394 were not on AC.The incidence of PE on CTPA was significantly lower in patients on AC for other indications(5.7%)when compared to patients on AC for prior VTE(24.3%)and patients not on AC at presentation(9.8%)(P<0.001).In multivariable analysis among the whole cohort,AC was associated with a positive CTPA(odds ratio[OR]0.26,95%confidence interval[CI]:0.15-0.45,P<0.001).CONCLUSION:The incidence of PE among patients undergoing CTPA in the ED is lower in patients previously on AC for indications other than VTE when compared to those not on AC or those on AC for history of VTE.AC status and indication for AC may affect pre-test probability of a positive CTPA,and AC status therefore warrants consideration as part of future diagnostic algorithms among patients with suspected PE.

Whole-volume histogram analysis of spectral-computed tomography iodine maps characterizes HER2 expression in gastric cancer

BACKGROUND Although surgery remains the primary treatment for gastric cancer(GC),the identification of effective alternative treatments for individuals for whom surgery is unsuitable holds significance.HER2 overexpression occurs in approximately 15%-20%of advanced GC cases,directly affecting treatment-related decisions.Spectral-computed tomography(sCT)enables the quantification of material compositions,and sCT iodine concentration parameters have been demonstrated to be useful for the diagnosis of GC and prediction of its invasion depth,angioge-nesis,and response to systemic chemotherapy.No existing report describes the prediction of GC HER2 status through histogram analysis based on sCT iodine maps(IMs).AIM To investigate whether whole-volume histogram analysis of sCT IMs enables the prediction of the GC HER2 status.METHODS This study was performed with data from 101 patients with pathologically confirmed GC who underwent preoperative sCT examinations.Nineteen parameters were extracted via sCT IM histogram analysis:The minimum,maximum,mean,standard deviation,variance,coefficient of variation,skewness,kurtosis,entropy,percentiles(1st,5th,10th,25th,50th,75th,90th,95th,and 99th),and lesion volume.Spearman correlations of the parameters with the HER2 status and clinicopathological parameters were assessed.Receiver operating characteristic curves were used to evaluate the parameters’diagnostic performance.RESULTS Values for the histogram parameters of the maximum,mean,standard deviation,variance,entropy,and percentiles were significantly lower in the HER2+group than in the HER2–group(all P<0.05).The GC differentiation and Lauren classification correlated significantly with the HER2 status of tumor tissue(P=0.001 and 0.023,respectively).The 99th percentile had the largest area under the curve for GC HER2 status identification(0.740),with 76.2%,sensitivity,65.0%specificity,and 67.3%accuracy.All sCT IM histogram parameters correlated positively with the GC HER2 status(r=0.237-0.337,P=0.001-0.017).CONCLUSION Whole-lesion histogram parameters derived from sCT IM analysis,and especially the 99th percentile,can serve as imaging biomarkers of HER2 overexpression in GC.

Preoperative prediction of lymphovascular and perineural invasion in gastric cancer using spectral computed tomography imaging and machine learning

BACKGROUND Lymphovascular invasion(LVI)and perineural invasion(PNI)are important prognostic factors for gastric cancer(GC)that indicate an increased risk of metastasis and poor outcomes.Accurate preoperative prediction of LVI/PNI status could help clinicians identify high-risk patients and guide treatment deci-sions.However,prior models using conventional computed tomography(CT)images to predict LVI or PNI separately have had limited accuracy.Spectral CT provides quantitative enhancement parameters that may better capture tumor invasion.We hypothesized that a predictive model combining clinical and spectral CT parameters would accurately preoperatively predict LVI/PNI status in GC patients.AIM To develop and test a machine learning model that fuses spectral CT parameters and clinical indicators to predict LVI/PNI status accurately.METHODS This study used a retrospective dataset involving 257 GC patients(training cohort,n=172;validation cohort,n=85).First,several clinical indicators,including serum tumor markers,CT-TN stages and CT-detected extramural vein invasion(CT-EMVI),were extracted,as were quantitative spectral CT parameters from the delineated tumor regions.Next,a two-step feature selection approach using correlation-based methods and information gain ranking inside a 10-fold cross-validation loop was utilized to select informative clinical and spectral CT parameters.A logistic regression(LR)-based nomogram model was subsequently constructed to predict LVI/PNI status,and its performance was evaluated using the area under the receiver operating characteristic curve(AUC).RESULTS In both the training and validation cohorts,CT T3-4 stage,CT-N positive status,and CT-EMVI positive status are more prevalent in the LVI/PNI-positive group and these differences are statistically significant(P<0.05).LR analysis of the training group showed preoperative CT-T stage,CT-EMVI,single-energy CT values of 70 keV of venous phase(VP-70 keV),and the ratio of standardized iodine concentration of equilibrium phase(EP-NIC)were independent influencing factors.The AUCs of VP-70 keV and EP-NIC were 0.888 and 0.824,respectively,which were slightly greater than those of CT-T and CT-EMVI(AUC=0.793,0.762).The nomogram combining CT-T stage,CT-EMVI,VP-70 keV and EP-NIC yielded AUCs of 0.918(0.866-0.954)and 0.874(0.784-0.936)in the training and validation cohorts,which are significantly higher than using each of single independent factors(P<0.05).CONCLUSION The study found that using portal venous and EP spectral CT parameters allows effective preoperative detection of LVI/PNI in GC,with accuracy boosted by integrating clinical markers.

Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors

BACKGROUND The colon cancer prognosis is influenced by multiple factors,including clinical,pathological,and non-biological factors.However,only a few studies have focused on computed tomography(CT)imaging features.Therefore,this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics,and establishes a nomogram to provide critical guidance for the individualized treatment.AIM To establish and validate a nomogram to predict the overall survival(OS)of patients with colon cancer.METHODS A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021.The patients were randomly divided into training and testing groups at a 1:1 ratio.Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS,and a nomogram model was constructed for the training group.Survival curves were calculated using the Kaplan–Meier method.The concordance index(C-index)and calibration curve were used to evaluate the nomogram model in the training and testing groups.RESULTS Multivariate logistic regression analysis revealed that lymph node metastasis on CT,perineural invasion,and tumor classification were independent prognostic factors.A nomogram incorporating these variables was constructed,and the C-index of the training and testing groups was 0.804 and 0.692,respectively.The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS.CONCLUSION A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability.It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.

Review on article of preoperative prediction in chronic hepatitis B virus patients using spectral computed tomography and machine learning

This letter comments on the article that developed and tested a machine learning model that predicts lymphovascular invasion/perineural invasion status by combining clinical indications and spectral computed tomography characteristics accurately.We review the research content,methodology,conclusions,strengths and weaknesses of the study,and introduce follow-up research to this work.

Computed tomography-based radiomic model for the prediction of neoadjuvant immunochemotherapy response in patients with advanced gastric cancer

BACKGROUND Neoadjuvant immunochemotherapy(nICT)has emerged as a popular treatment approach for advanced gastric cancer(AGC)in clinical practice worldwide.However,the response of AGC patients to nICT displays significant heterogeneity,and no existing radiomic model utilizes baseline computed tomography to predict treatment outcomes.AIM To establish a radiomic model to predict the response of AGC patients to nICT.METHODS Patients with AGC who received nICT(n=60)were randomly assigned to a training cohort(n=42)or a test cohort(n=18).Various machine learning models were developed using selected radiomic features and clinical risk factors to predict the response of AGC patients to nICT.An individual radiomic nomogram was established based on the chosen radiomic signature and clinical signature.The performance of all the models was assessed through receiver operating characteristic curve analysis,decision curve analysis(DCA)and the Hosmer Lemeshow goodness-of-fit test.RESULTS The radiomic nomogram could accurately predict the response of AGC patients to nICT.In the test cohort,the area under curve was 0.893,with a 95%confidence interval of 0.803-0.991.DCA indicated that the clinical application of the radiomic nomogram yielded greater net benefit than alternative models.CONCLUSION A nomogram combining a radiomic signature and a clinical signature was designed to predict the efficacy of nICT in patients with AGC.This tool can assist clinicians in treatment-related decision-making.

Computed tomography radiogenomics:A potential tool for prediction of molecular subtypes in gastric stromal tumor

BACKGROUND Preoperative knowledge of mutational status of gastrointestinal stromal tumors(GISTs)is essential to guide the individualized precision therapy.AIM To develop a combined model that integrates clinical and contrast-enhanced computed tomography(CE-CT)features to predict gastric GISTs with specific genetic mutations,namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions.METHODS A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio.The models were constructed using selected clinical features,conventional CT features,and radiomics features extracted from abdominal CE-CT images.Three models were developed:ModelCT sign,modelCT sign+rad,and model CTsign+rad+clinic.The diagnostic performance of these models was evaluated using receiver operating characteristic(ROC)curve analysis and the Delong test.RESULTS The ROC analyses revealed that in the training cohort,the area under the curve(AUC)values for model_(CT sign),model_(CT sign+rad),and modelCT_(sign+rad+clinic)for predicting KIT exon 11 mutation were 0.743,0.818,and 0.915,respectively.In the validation cohort,the AUC values for the same models were 0.670,0.781,and 0.811,respectively.For predicting KIT exon 11 codons 557-558 deletions,the AUC values in the training cohort were 0.667,0.842,and 0.720 for model_(CT sign),model_(CT sign+rad),and modelCT_(sign+rad+clinic),respectively.In the validation cohort,the AUC values for the same models were 0.610,0.782,and 0.795,respectively.Based on the decision curve analysis,it was determined that the model_(CT sign+rad+clinic)had clinical significance and utility.CONCLUSION Our findings demonstrate that the combined modelCT_(sign+rad+clinic)effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions.This combined model has the potential to be valuable in assessing the genotype of GISTs.

Computed tomography imaging and clinical significance of bacterium-positive pulmonary tuberculosis complicated with diabetes

BACKGROUND The increasing prevalence of tuberculosis(TB)and diabetes on a global scale poses a significant health challenge,particularly due to their co-occurrence,which amplifies the severity,recurrence and mortality rates associated with both conditions.This highlights the need for further investigation into their interrelationship.AIM To explore the computed tomography(CT)imaging and clinical significance of bacterium-positive pulmonary TB(PTB)combined with diabetes.METHODS There were 50 patients with bacterium-positive PTB and diabetes,and 50 with only bacterium-positive PTB.The latter were designated as the control group.The CT imaging of the two groups of patients was compared,including lesion range,shape,density and calcification.RESULTS No significant differences were observed in age,gender,smoking and drinking history,high blood pressure,hyperlipidemia and family genetic factors between the groups.However,compared to the patients diagnosed solely with simple bacterium-positive PTB,those with concurrent diabetes showed a wider range of lesions and more complex and diverse morphology on CT images.Among them,intrapulmonary tuberculosis lesions were often accompanied by manifestations of pulmonary infection,such as cavity formation and bronchiectasis.At the same time,diabetes-related signs were often seen on CT images,such as pulmonary infection combined with diabetic pulmonary lesions.Logistic regression analysis identified age and medical history as significant factors influencing the degree of pulmonary infection and CT imaging outcomes in patients with both TB and diabetes.This suggests that older age and specific medical histories may increase the risk or severity of pulmonary damage in these patients.CONCLUSION CT imaging reveals more complex lesions in PTB patients with diabetes,emphasizing the need for careful evaluation and comprehensive analysis to enhance diagnostic accuracy.

A machine learning-based strategy for predicting the mechanical strength of coral reef limestone using X-ray computed tomography

Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL samples were utilized for training the support vector machine(SVM)-,random forest(RF)-,and back propagation neural network(BPNN)-based models,respectively.Simultaneously,the machine learning model was embedded into genetic algorithm(GA)for parameter optimization to effectively predict uniaxial compressive strength(UCS)of CRL.Results indicate that the BPNN model with five hidden layers presents the best training effect in the data set of CRL.The SVM-based model shows a tendency to overfitting in the training set and poor generalization ability in the testing set.The RF-based model is suitable for training CRL samples with large data.Analysis of Pearson correlation coefficient matrix and the percentage increment method of performance metrics shows that the dry density,pore structure,and porosity of CRL are strongly correlated to UCS.However,the P-wave velocity is almost uncorrelated to the UCS,which is significantly distinct from the law for homogenous geomaterials.In addition,the pore tensor proposed in this paper can effectively reflect the pore structure of coral framework limestone(CFL)and coral boulder limestone(CBL),realizing the quantitative characterization of the heterogeneity and anisotropy of pore.The pore tensor provides a feasible idea to establish the relationship between pore structure and mechanical behavior of CRL.

Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis

BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.

Energy spectrum computed tomography multi-parameter imaging in preoperative assessment of vascular and neuroinvasive status in gastric cancer

BACKGROUND Vascular and nerve infiltration are important indicators for the progression and prognosis of gastric cancer(GC),but traditional imaging methods have some limitations in preoperative evaluation.In recent years,energy spectrum computed tomography(CT)multiparameter imaging technology has been gradually applied in clinical practice because of its advantages in tissue contrast and lesion detail display.AIM To explore and analyze the value of multiparameter energy spectrum CT imaging in the preoperative assessment of vascular invasion(LVI)and nerve invasion(PNI)in GC patients.METHODS Data from 62 patients with GC confirmed by pathology and accompanied by energy spectrum CT scanning at our hospital between September 2022 and September 2023,including 46 males and 16 females aged 36-71(57.5±9.1)years,were retrospectively collected.The patients were divided into a positive group(42 patients)and a negative group(20 patients)according to the presence of LVI/PNI.The CT values(CT40 keV,CT70 keV),iodine concentration(IC),and normalized IC(NIC)of lesions in the upper energy spectrum CT images of the arterial phase,venous phase,and delayed phase 40 and 70 keV were measured,and the slopes of the energy spectrum curves[K(40-70)]from 40 to 70 keV were calculated.Arterial Core Tip:To investigate the application value of multiparameter energy spectrum computed tomography(CT)imaging in the preoperative assessment of vascular and nerve infiltration in patients with gastric cancer(GC).The imaging data of GC patients were retrospectively analyzed to evaluate the accuracy and sensitivity of CT for identifying and quantifying vascular and nerve infiltration and for comparison with postoperative pathological results.The purpose of this study was to verify the clinical feasibility and potential advantages of multiparameter energy spectrum CT imaging in guiding preoperative diagnosis and treatment decision-making and to provide a new imaging basis for improving the diagnostic accuracy and prognosis of GC patients.

Computed tomography for prediction of esophageal variceal bleeding

This letter to the editor relates to the study entitled“The role of computed tomography for the prediction of esophageal variceal bleeding:Current status and future perspectives”.Esophageal variceal bleeding(EVB)is one of the most common and severe complications related to portal hypertension(PH).Despite marked advances in its management during the last three decades,EVB is still associated with significant morbidity and mortality.The risk of first EVB is related to the severity of both PH and liver disease,and to the size and endoscopic appearance of esophageal varices.Indeed,hepatic venous pressure gradient(HVPG)and esophagogastroduodenoscopy(EGD)are currently recognized as the“gold standard”and the diagnostic reference standard for the prediction of EVB,respectively.However,HVPG is an invasive,expensive,and technically complex procedure,not widely available in clinical practice,whereas EGD is mainly limited by its invasive nature.In this scenario,computed tomography(CT)has been recently proposed as a promising modality for the non-invasive prediction of EVB.While CT serves solely as a diagnostic tool and cannot replace EGD or HVPG for delivering therapeutic and physiological information,it has the potential to enhance the prediction of EVB more effectively when combined with liver disease scores,HVPG,and EGD.However,to date,evidence concerning the role of CT in this setting is still lacking,therefore we aim to summarize and discuss the current evidence concerning the role of CT in predicting the risk of EVB.