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.

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.

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.

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.

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.

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.

Computed tomography-based radiomics diagnostic approach for differential diagnosis between early-and late-stage pancreatic ductal adenocarcinoma

BACKGROUND One of the primary reasons for the dismal survival rates in pancreatic ductal adenocarcinoma(PDAC)is that most patients are usually diagnosed at late stages.There is an urgent unmet clinical need to identify and develop diagnostic methods that could precisely detect PDAC at its earliest stages.METHODS A total of 71 patients with pathologically proved PDAC based on surgical resection who underwent contrast-enhanced computed tomography(CT)within 30 d prior to surgery were included in the study.Tumor staging was performed in accordance with the 8th edition of the American Joint Committee on Cancer staging system.Radiomics features were extracted from the region of interest(ROI)for each patient using Analysis Kit software.The most important and predictive radiomics features were selected using Mann-Whitney U test,univar-iate logistic regression analysis,and minimum redundancy maximum relevance(MRMR)method.Random forest(RF)method was used to construct the radiomics model,and 10-times leave group out cross-validation(LGOCV)method was used to validate the robustness and reproducibility of the model.RESULTS A total of 792 radiomics features(396 from late arterial phase and 396 from portal venous phase)were extracted from the ROI for each patient using Analysis Kit software.Nine most important and predictive features were selected using Mann-Whitney U test,univariate logistic regression analysis,and MRMR method.RF method was used to construct the radiomics model with the nine most predictive radiomics features,which showed a high discriminative ability with 97.7%accuracy,97.6%sensitivity,97.8%specificity,98.4%positive predictive value,and 96.8%negative predictive value.The radiomics model was proved to be robust and reproducible using 10-times LGOCV method with an average area under the curve of 0.75 by the average performance of the 10 newly built models.CONCLUSION The radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC.

Correlation between abdominal computed tomography signs and postoperative prognosis for patients with colorectal cancer

BACKGROUND Patients with different stages of colorectal cancer(CRC)exhibit different abdominal computed tomography(CT)signs.Therefore,the influence of CT signs on CRC prognosis must be determined.AIM To observe abdominal CT signs in patients with CRC and analyze the correlation between the CT signs and postoperative prognosis.METHODS The clinical history and CT imaging results of 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University were retrospectively analyzed.Univariate and multivariate Cox regression analyses were used to explore the independent risk factors for postoperative death in patients with CRC.The three-year survival rate was analyzed using the Kaplan-Meier curve,and the correlation between postoperative survival time and abdominal CT signs in patients with CRC was analyzed using Spearman correlation analysis.RESULTS For patients with CRC,the three-year survival rate was 73.86%.The death group exhibited more severe characteristics than the survival group.A multivariate Cox regression model analysis showed that body mass index(BMI),degree of periintestinal infiltration,tumor size,and lymph node CT value were independent factors influencing postoperative death(P<0.05 for all).Patients with characteristics typical to the death group had a low three-year survival rate(log-rankχ2=66.487,11.346,12.500,and 27.672,respectively,P<0.05 for all).The survival time of CRC patients was negatively correlated with BMI,degree of periintestinal infiltration,tumor size,lymph node CT value,mean tumor long-axis diameter,and mean tumor short-axis diameter(r=-0.559,0.679,-0.430,-0.585,-0.425,and-0.385,respectively,P<0.05 for all).BMI was positively correlated with the degree of periintestinal invasion,lymph node CT value,and mean tumor short-axis diameter(r=0.303,0.431,and 0.437,respectively,P<0.05 for all).CONCLUSION The degree of periintestinal infiltration,tumor size,and lymph node CT value are crucial for evaluating the prognosis of patients with CRC.

Computed tomography three-dimensional reconstruction in the diagnosis of bleeding small intestinal polyps:A case report

BACKGROUND Computed tomography(CT)small bowel three-dimensional(3D)reconstruction is a powerful tool for the diagnosis of small bowel disease and can clearly show the intestinal lumen and wall as well as the outside structure of the wall.The horizontal axis position can show the best adjacent intestinal tube and the lesion between the intestinal tubes,while the coronal position can show the overall view of the small bowel.The ileal end of the localization of the display of excellent,and easy to quantitative measurement of the affected intestinal segments,the sagittal position for the rectum and the pre-sacral lesions show the best,for the discovery of fistulae is also helpful.Sagittal view can show rectal and presacral lesions and is useful for fistula detection.It is suitable for the assessment of inflammatory bowel disease,such as assessment of disease severity and diagnosis and differential diagnosis of the small bowel and mesenteric space-occupying lesions as well as the judgment of small bowel obstruction points.CASE SUMMARY Bleeding caused by small intestinal polyps is often difficult to diagnose in clinical practice.This study reports a 29-year-old male patient who was admitted to the hospital with black stool and abdominal pain for 3 months.Using the combination of CT-3D reconstruction and capsule endoscopy,the condition was diagnosed correctly,and the polyps were removed using single-balloon enteroscopyendoscopic retrograde cholangiopancreatography without postoperative complications.CONCLUSION The role of CT-3D in gastrointestinal diseases was confirmed.CT-3D can assist in the diagnosis and treatment of gastrointestinal diseases in combination with capsule endoscopy and small intestinal microscopy.

Computed tomography for the prediction of oesophageal variceal bleeding:A surrogate or complementary to the gold standard?

In this editorial we comment on the in-press article in the World Journal of Gastrointestinal endoscopy about the role of computed tomography(CT)for the prediction of esophageal variceal bleeding.The mortality and morbidity are much increased in patients with chronic liver diseases when complicated with variceal bleeding.Predicting the patient at a risk of bleeding is extremely important and receives a great deal of attention,paving the way for primary prophylaxis either using medical treatment including carvedilol or propranolol,or endoscopic band ligation.Endoscopic examination and the hepatic venous pressure gradient are the gold standards in the diagnosis and prediction of variceal bleeding.Several non-invasive laboratory and radiological examinations are used for the prediction of variceal bleeding.The contrast-enhanced multislice CT is a widely used non-invasive,radiological examination that has many advantages.In this editorial we briefly comment on the current research regarding the use of CT as a non-invasive tool in predicting the variceal bleeding.

Effectiveness of magnetic resonance imaging and spiral computed tomography in the staging and treatment prognosis of colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a prevalent cancer type in clinical settings;its early signs can be difficult to detect,which often results in late-stage diagnoses in many patients.The early detection and diagnosis of CRC are crucial for improving treatment success and patient survival rates.Recently,imaging techniques have been hypothesized to be essential in managing CRC,with magnetic resonance imaging(MRI)and spiral computed tomography(SCT)playing a significant role in enhancing diagnostic and treatment approaches.AIM To explore the effectiveness of MRI and SCT in the preoperative staging of CRC and the prognosis of laparoscopic treatment.METHODS Ninety-five individuals admitted to Zhongshan Hospital Xiamen University underwent MRI and SCT and were diagnosed with CRC.The precision of MRI and SCT for the presurgical classification of CRC was assessed,and pathological staging was used as a reference.Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of blood volume,blood flow,time to peak,permeability surface,blood reflux constant,volume transfer constant,and extracellular extravascular space volume fraction on the prognosis of patients with CRC.RESULTS Pathological biopsies confirmed the following CRC stages:23,23,32,and 17 at T1,T2,T3,and T4,respectively.There were 39 cases at the N0 stage,22 at N1,34 at N2,44 at M0 stage,and 51 at M1.Using pathological findings as the benchmark,the combined use of MRI and SCT for preoperative TNM staging in patients with CRC demonstrated superior sensitivity,specificity,and accuracy compared with either modality alone,with a statistically significant difference in accuracy(P<0.05).Receiver operating characteristic curve analysis revealed the predictive values for laparoscopic treatment prognosis,as indicated by the areas under the curve for blood volume,blood flow,time to peak,and permeability surface,blood reflux constant,volume transfer constant,and extracellular extravascular space volume fraction were 0.750,0.683,0.772,0.761,0.709,0.719,and 0.910,respectively.The corresponding sensitivity and specificity values were also obtained(P<0.05).CONCLUSION MRI with SCT is effective in the clinical diagnosis of patients with CRC and is worthy of clinical promotion.

Computed tomography-based nomogram of Siewert type Ⅱ/Ⅲ adenocarcinoma of esophagogastric junction to predict response to docetaxel, oxaliplatin and S-1

BACKGROUND Neoadjuvant chemotherapy(NAC)has become the standard care for advanced adenocarcinoma of esophagogastric junction(AEG),although a part of the patients cannot benefit from NAC.There are no models based on baseline computed tomography(CT)to predict response of Siewert type II or III AEG to NAC with docetaxel,oxaliplatin and S-1(DOS).AIM To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS.METHODS One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS,and were randomly and consecutively assigned to the training cohort(TC)(n=94)and the validation cohort(VC)(n=34).Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors(version 1.1)criteria.Possible prognostic factors associated with responses after DOS treatment including Siewert classification,gross tumor volume(GTV),and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age.Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS.A nomogram was established based on independent factors to predict the response.The predictive performance of the nomogram was evaluated by Concordance index(C-index),calibration and receiver operating characteristics curve in the TC and VC.RESULTS Univariate analysis showed that Siewert type(52/55 vs 29/39,P=0.005),pretherapeutic cT stage(57/62 vs 24/32,P=0.028),GTV(47.3±27.4 vs 73.2±54.3,P=0.040)were significantly associated with response to DOS in the TC.Multivariate analysis of the TC also showed that the pretherapeutic cT stage,GTV and Siewert type were independent predictive factors related to response to DOS(odds ratio=4.631,1.027 and 7.639,respectively;all P<0.05).The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC(C-index:0.838 and 0.824),with area under the receiver operating characteristic curve of 0.838 and 0.824,respectively.The calibration curves showed that the practical and predicted response to DOS effectively coincided.CONCLUSION A novel nomogram developed with pretherapeutic cT stage,GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.

Characterization of tumors of jaw:Additive value of contrast enhancement and dual-energy computed tomography

BACKGROUND Currently,the differentiation of jaw tumors is mainly based on the lesion’s morphology rather than the enhancement characteristics,which are important in the differentiation of neoplasms across the body.There is a paucity of literature on the enhancement characteristics of jaw tumors.This is mainly because,even though computed tomography(CT)is used to evaluate these lesions,they are often imaged without intravenous contrast.This study hypothesised that the enhancement characteristics of the solid component of jaw tumors can aid in the differentiation of these lesions in addition to their morphology by dual-energy CT,therefore improving the ability to differentiate between various pathologies.AIM To evaluate the role of contrast enhancement and dual-energy quantitative parameters in CT in the differentiation of jaw tumors.METHODS Fifty-seven patients with jaw tumors underwent contrast-enhanced dual-energy CT.Morphological analysis of the tumor,including the enhancing solid component,was done,followed by quantitative analysis of iodine concentration(IC),water concentration(WC),HU,and normalized IC.The study population was divided into four subgroups based on histopathological analysis-central giant cell granuloma(CGCG),ameloblastoma,odontogenic keratocyst(OKC),and other jaw tumors.A one-way ANOVA test for parametric variables and the Kruskal-Wallis test for nonparametric variables were used.If significant differences were found,a series of independent t-tests or Mann-Whitney U tests were used.RESULTS Ameloblastoma was the most common pathology(n=20),followed by CGCG(n=11)and OKC.CGCG showed a higher mean concentration of all quantitative parameters than ameloblastomas(P<0.05).An IC threshold of 31.35×100μg/cm^(3) had the maximum sensitivity(81.8%)and specificity(65%).Between ameloblastomas and OKC,the former showed a higher mean concentration of all quantitative parameters(P<0.001),however when comparing unilocular ameloblastomas with OKCs,the latter showed significantly higher WC.Also,ameloblastoma had a higher IC and lower WC compared to“other jaw tumors”group.CONCLUSION Enhancement characteristics of solid components combined with dual-energy parameters offer a more precise way to differentiate between jaw tumors.

Comparison between solid pseudopapillary neoplasms of the pancreas and pancreatic ductal adenocarcinoma with cystic changes using computed tomography

BACKGROUND Solid pseudopapillary neoplasms of the pancreas(SPN)share similar imaging findings with pancreatic ductal adenocarcinoma with cystic changes(PDAC with cystic changes),which may result in unnecessary surgery.AIM To investigate the value of computed tomography(CT)in differentiation of SPN from PDAC with cystic changes.METHODS This study retrospectively analyzed the clinical and imaging findings of 32 patients diagnosed with SPN and 14 patients diagnosed with PDAC exhibiting cystic changes,confirmed through pathological diagnosis.Quantitative and qualitative analysis was performed,including assessment of age,sex,tumor size,shape,margin,density,enhancement pattern,CT values of tumors,CT contrast enhancement ratios,“floating cloud sign,”calcification,main pancreatic duct dilatation,pancreatic atrophy,and peripancreatic invasion or distal metastasis.Multivariate logistic regression analysis was used to identify relevant features to differentiate between SPN and PDAC with cystic changes,and receiver operating characteristic curves were obtained to evaluate the diagnostic performance of each variable and their combination.RESULTS When compared to PDAC with cystic changes,SPN had a lower age(32 years vs 64 years,P<0.05)and a slightly larger size(5.41 cm vs 3.90 cm,P<0.05).SPN had a higher frequency of“floating cloud sign”and peripancreatic invasion or distal metastasis than PDAC with cystic changes(both P<0.05).No significant difference was found with respect to sex,tumor location,shape,margin,density,main pancreatic duct dilatation,calcification,pancreatic atrophy,enhancement pattern,CT values of tumors,or CT contrast enhancement ratios between the two groups(all P>0.05).The area under the receiver operating characteristic curve of the combination was 0.833(95%confidence interval:0.708-0.957)with 78.6%sensitivity,81.3%specificity,and 80.4%accuracy in differentiation of SPN from PDAC with cystic changes.CONCLUSION A larger tumor size,“floating cloud sign,”and peripancreatic invasion or distal metastasis are useful CT imaging features that are more common in SPN and may help discriminate SPN from PDAC with cystic changes.

Future directions of noninvasive prediction of esophageal variceal bleeding:No worry about the present computed tomography inefficiency

In this editorial,we comment on the minireview by Martino A,published in the recent issue of World Journal of Gastrointestinal Endoscopy 2023;15(12):681-689.We focused mainly on the possibility of replacing the hepatic venous pressure gradient(HVPG)and endoscopy with noninvasive methods for predicting esophageal variceal bleeding.The risk factors for bleeding were the size of the varices,the red sign and the Child-Pugh score.The intrinsic core factor that drove these changes was the HVPG.Therefore,the present studies investigating noninvasive methods,including computed tomography,magnetic resonance imaging,elastography,and laboratory tests,are working on correlating imaging or serum marker data with intravenous pressure and clinical outcomes,such as bleeding.A single parameter is usually not enough to construct an efficient model.Therefore,multiple factors were used in most of the studies to construct predictive models.Encouraging results have been obtained,in which bleeding prediction was partly reached.However,these methods are not satisfactory enough to replace invasive methods,due to the many drawbacks of different studies.There is still plenty of room for future improvement.Prediction of the precise timing of bleeding using various models,and extracting the texture of variceal walls using high-definition imaging modalities to predict the red sign are interesting directions to lay investment on.

Extravasated contrast volumetric assessment on computed tomography angiography in gastrointestinal bleeding:A useful predictor of positive angiographic findings

BACKGROUND Gastrointestinal bleeding(GIB)is a severe and potentially life-threatening condition,especially in cases of delayed treatment.Computed tomography angiography(CTA)plays a pivotal role in the early identification of upper and lower GIB and in the prompt treatment of the haemorrhage.AIM To determine whether a volumetric estimation of the extravasated contrast at CTA in GIB may be a predictor of subsequent positive angiographic findings.METHODS In this retrospective single-centre study,35 patients(22 men;median age 69 years;range 16-92 years)admitted to our institution for active GIB detected at CTA and further submitted to catheter angiography between January 2018 and February 2022 were enrolled.Twenty-three(65.7%)patients underwent endoscopy before CTA.Bleeding volumetry was evaluated in both arterial and venous phases via a semi-automated dedicated software.Bleeding rate was obtained from volume change between the two phases and standardised for unit time.Patients were divided into two groups,according to the angiographic signs and their concordance with CTA.RESULTS Upper bleeding accounted for 42.9%and lower GIB for 57.1%.Mean haemoglobin value at the admission was 7.7 g/dL.A concordance between positive CTA and direct angiographic bleeding signs was found in 19(54.3%)cases.Despite no significant differences in terms of bleeding volume in the arterial phase(0.55 mL vs 0.33 mL,P=0.35),a statistically significant volume increase in the venous phase was identified in the group of patients with positive angiography(2.06 mL vs 0.9 mL,P=0.02).In the latter patient group,a significant increase in bleeding rate was also detected(2.18 mL/min vs 0.19 mL/min,P=0.02).CONCLUSION In GIB of any origin,extravasated contrast volumetric analysis at CTA could be a predictor of positive angiography and may help in avoiding further unnecessary procedures.

影像组学联合CT特征鉴别儿童支原体与非支原体肺炎

目的观察影像组学联合CT特征鉴别儿童支原体肺炎(MP)与非MP的价值。方法回顾性收集153例肺炎患儿,根据支原体RNA检测结果分为MP组(n=101)与非MP组(n=52);按7∶3比例分为训练集(n=107,含71例MP、36例非MP)和验证集(n=46,含30例MP、16例非MP)。比较2组CT表现,以F test算法基于训练集数据筛选6个最佳CT征象,以逻辑回归(LR)方法构建CT模型。基于训练集提取及筛选最佳影像组学特征,分别以LR、支持向量机(SVM)、随机森林(RF)、线性判别分析(LDA)及随机梯度下降法(SGD)分类器构建机器学习(ML)模型;基于最佳CT征象及影像组学特征构建CT-ML模型。绘制受试者工作特征曲线,计算曲线下面积(AUC)评估各模型鉴别MP与非MP的效能。结果病变累及右肺上、中、下叶,支气管壁增厚、树芽征及边缘回缩征为最佳CT征象,以之构建的CTLR在验证集的AUC为0.710。验证集中,ML_(LR)、ML_(SVM)、ML_(RF)、ML_(LDA)及ML_(SGD)的AUC分别为0.715、0.663、0.623、0.706及0.494,ML_(LR)为效能最优影像组学模型。CT-ML_(LR)、CT-ML_(SVM)、CT-ML_(RF)、CT-ML_(LDA)及CT-ML_(SGD)在验证集的AUC分别为0.813、0.823、0.649、0.796及0.665,CT-ML_(SVM)为效能最优CT-ML模型。训练集中,CT-ML_(SVM)的AUC(0.840)高于CTLR及ML_(LR)(AUC=0.713、0.740,P均<0.05);验证集中CTLR、ML_(LR)及CT-ML_(SVM)的AUC差异均无统计学意义(AUC=0.710、0.715及0.823,P均>0.05)。结论影像组学联合CT特征能有效鉴别儿童MP与非MP。

基于深度学习的继发性肺结核CT辅助诊断模型构建及验证

目的:评价基于深度学习的继发性肺结核CT辅助诊断模型在临床应用中的价值。方法:回顾性收集2018年12月至2023年4月在重庆市公共卫生医疗救治中心接受胸部CT平扫的2004例患者的病例资料,分为肺部正常组(544例)、普通肺部感染组(526组)和继发性肺结核组(934例)。按照随机分组(通过R语言的sample函数实现训练集和测试集的完全随机分组)的方式,将数据集划分为训练集(1402例,70.0%)和测试集(602例,30.0%)。所有图像采用肺野自动分割算法,获得肺野区域。进一步采用BasicNet和DenseNet算法进行三组间的分类研究。采用曲线下面积(area under curve,AUC)、敏感度、特异度和准确率评价模型的分类性能。最后,在测试数据中,将最优模型与3位不同年资的放射科医生的诊断结果进行比较。结果:602例独立测试集中,DenseNet模型的性能优于BasicNet模型,两种模型的平均AUC、敏感度、特异度和准确率分别为92.1%和89.4%、79.7%和74.0%、89.4%和86.6%、86.2%和83.3%。其中,DenseNet模型的诊断性能优于低年资医生(准确率分别为90.7%和89.1%,Kappa=0.677),与中年资和高年资医生的诊断水平(准确率分别为90.7%、92.2%和95.3%,Kappa值分别为0.746和0.819)保持高度一致性。结论:DenseNet模型能较准确地识别继发性肺结核,与放射科中年资医师的诊断水准相当,可以作为继发性肺结核的辅助诊断工具。

胸部CT图像质量评价与辐射剂量的临床应用研究

目的:归纳和分析影响胸部CT图像质量的因素,进一步对照分析常规剂量组和低剂量组两组图像质量有无差异,以论证胸部CT低剂量检查的可行性。方法:选取150例胸部CT查体的患者,A组为常规剂量组,管电压120kV,管电流自动调节;B组为低剂量组,管电压100kV,管电流自动调节。参照胸部CT的图像质量评价标准对常规剂量组和低剂量组图像质量进一步作出主观评价。对辐射剂量、信噪比等客观数据进行统计学处理,以P<0.05为差异有统计学意义。并与主观评价相比较。结果:主、客观评价两组图像质量均无统计学意义,A组辐射剂量与B组辐射剂量有统计学意义。结论:影响图像质量的因素包括患者的因素、设备的因素以及操作者的因素,胸部CT采用100kV低剂量检查可以作为常规扫描方案,获得的图像可以满足影像诊断的要求,具有可行性。