A nomogram based on ultrasonographic features and clinical indicators for differentiating mass-forming intrahepatic cholangiocarcinoma and liver metastatic colorectal adenocarcinoma
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PROVIDER: S-EPMC10644673 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo establish a predictive nomogram to distinguish combined hepatocellular-cholangiocarcinoma (CHC) from hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) based on preoperative clinical and ultrasound findings.MethodsA total of 261 patients with pathologically confirmed primary liver cancers (PLCs) were enrolled in this retrospective study, comprising 87 CHCs, 87 HCCs, and 87 ICCs matched by propensity score matching. Patients were randomly assigned to a training cohort and a validation one at the ratio of 7:3. A nomogram integrating ultrasound imaging characteristics and clinical features was established based on the independent risk factors selected by least absolute shrinkage and selection operator (LASSO) regression. The performance of the nomogram was evaluated in the training and validation cohorts in terms of discrimination, calibration, and clinical usefulness.ResultsThe nomogram, consisting of ultrasound imaging features (shape and margin on B-mode ultrasound, enhanced pattern on contrast-enhanced ultrasound) and clinical information [elevated alpha fetoprotein (AFP) level and serum protein electrophoresis (SPE) α1 level], showed promising performance in differentiating CHC from HCC and ICC, with the concordance index (C-index) of 0.8275 and 0.8530 in the training cohort and the validation cohort, respectively. Hosmer-Lemeshow test and the calibration curves suggested good consistency between predictions and observations. High clinical practicability was confirmed by the decision curve analysis.ConclusionsThe nomogram based on clinical and ultrasound imaging characteristics showed good performance in the discrimination of CHC from other subtypes of PLC and would be valuable in clinical decision-making.
| S-EPMC8885729 | biostudies-literature
Project description:ObjectivesTo establish a nomogram based on preoperative laboratory study variables using least absolute shrinkage and selection operator (LASSO) regression for differentiating combined hepatocellular cholangiocarcinoma (cHCC) from intrahepatic cholangiocarcinoma (iCCA).MethodsWe performed a retrospective analysis of iCCA and cHCC patients who underwent liver resection. Blood signatures were established using LASSO regression, and then, the clinical risk factors based on the multivariate logistic regression and blood signatures were combined to establish a nomogram for a differential preoperative diagnosis between iCCA and cHCC. The differential accuracy ability of the nomogram was determined by Harrell's index (C-index) and decision curve analysis, and the results were validated using a validation set. Furthermore, patients were categorized into two groups according to the optimal cut-off values of the nomogram-based scores, and their survival differences were assessed using Kaplan-Meier curves.ResultsA total of 587 patients who underwent curative liver resection for iCCA or cHCC between January 2008 and December 2017 at West China Hospital were enrolled in this study. The cHCC score was based on the personalized levels of the seven laboratory study variables. On multivariate logistic analysis, the independent factors for distinguishing cHCC were age, sex, biliary duct stones, and portal hypertension, all of which were incorporated into the nomogram combined with the cHCC-score. The nomogram had a good discriminating capability, with a C-index of 0.796 (95% CI, 0.752-0.840). The calibration plot for distinguishing cHCC from iCCA showed optimal agreement between the nomogram prediction and actual observation in the training and validation sets. The decision curves indicated significant clinical usefulness.ConclusionThe nomogram showed good accuracy for the differential diagnosis between iCCA and cHCC preoperatively, and therapeutic decisions would improve if it was applied in clinical practice.
| S-EPMC7756117 | biostudies-literature
Project description:Intrahepatic cholangiocarcinoma (ICC) is a highly lethal hepatobiliary neoplasm, which originates from the bile ducts proximal to the second-order division. ICC can be anatomically divided into two subtypes: the large duct type (mucin-production ICC, muc-ICC) and the small duct type (mixed-ICC) origins from hepatic progenitor cells (HPCs). The immunoreactivity of S100P and neural cell adhesion molecule (NCAM) are useful biomarkers to distinguish the two subtypes. In this study, we report a difficult-to-diagnose case of metastatic retroperitoneal tumor of occult hepatolithiasis-associated ICC. Besides, this case was both positive for S100P and NCAM, considered as a rare muc-ICC with the HPCs features. Tumor whole exome sequencing detection results by Genetron (China) revealed that there were 41 gene mutations in this patient. The SMAD4-p.His530ThrfsTer47 and KRAS-p.Gly12Val mutation might promote the occurrence and distant metastasis of the tumor.
| S-EPMC8921981 | biostudies-literature
Project description:BackgroundIntrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are the most prevalent histologic types of primary liver cancer. HCC and ICC differ in treatment and prognosis, warranting an effective differential diagnosis between them. This study aimed to explore the clinical value of mean platelet volume (MPV) to discriminate between HCC and ICC.Material/methodsWe performed a retrospective analysis of ICC and HCC patients who were from the Harbin Medical University Cancer Hospital, China. Logistic regression analysis was used to identify the independent factors for the differentiation of HCC and ICC. A receiver operating characteristic curve was built to evaluate the diagnostic performance of the potential model. An independent validation study was performed to validate the diagnostic ability.ResultsICC patients were detected in 146 out of 348 patients in the primary cohort. MPV levels were decreased in ICC patients compared with those in HCC patients. Logistic regression analysis revealed that MPV was an independent factor in distinguishing HCC from ICC. A combination of sex, hepatitis B surface antigen, MPV, alpha-fetoprotein, and carbohydrate antigen 19-9 demonstrated a good capability to differentiate HCC from ICC. Similar results were achieved in the validation cohort.ConclusionsMPV may be a new marker to help distinguish ICC from HCC. Further validation studies are required.
| S-EPMC9171941 | biostudies-literature
Project description:Introduction: The emerging field of "radiomics" has considerable potential in disease diagnosis, pathologic grading, prognosis evaluation, and prediction of treatment response. We aimed to develop a novel radiomics nomogram based on radiomics features and clinical characteristics that could preoperatively predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy. Methods: A predictive model was developed from a training cohort comprising 139 ICC patients diagnosed between January 2010 and June 2014. Radiomics features were extracted from arterial-phase image of contrast-enhanced magnetic resonance imaging. Feature selection and construction of a "radiomics signature" were through Spearman's rank correlation and least absolute shrinkage and selection operator (LASSO) logistic regression. Combined with clinical characteristics, a radiomics nomogram was developed with multivariable logistic regression. Performance of the nomogram was evaluated with regard to discrimination, calibration, and clinical utility. An independent validation cohort involving 70 patients recruited from July 2014 to March 2016 was used to evaluate the utility of the nomogram developed. Results: The radiomics signature, consisting of nine features, differed significantly between ER patients and non-ER patients in training and validation cohorts. The area under the curve (AUC) of the radiomics signature in training and validation cohorts was 0.82 (confidence interval [CI], 0.74-0.88) and 0.77 (95% CI, 0.65-0.86), respectively. The AUC of the radiomics nomogram combining the radiomics signature and clinical stage in the two cohorts was 0.90 (95%CI, 0.83-0.94) and 0.86 (95% CI, 0.76-0.93), respectively. Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram. Conclusion: The non-invasive radiomics nomogram developed using the radiomics signature and clinical stage could be used to predict ER of ICC after partial hepatectomy.
| S-EPMC6131601 | biostudies-literature
Project description:Intrahepatic cholangiocarcinoma (ICC) is a rare malignancy with a high prevalence in China. This study aimed to characterize the ICC tissues' bacterial metagenomics signature and explore its antitumor potential for cancer. In this study, 16S rRNA sequencing was carried out on 99 tissues to characterize the features of intratumoral microbiota, followed by single-cell RNA sequencing (scRNA-seq) and multilevel validation. The presence of microbial DNA in tissues was determined using staining, fluorescence in situ hybridization (FISH), and transmission electron microscopy (TEM). A Gram-positive aerobic bacterium, identified as Staphylococcus capitis, was cultured from fresh tissues. Meanwhile, scRNA-seq showed that intratumoral bacteria could be present in multiple cell types. Using 16S rRNA sequencing, we identified a total of 2,320,287 high-quality reads corresponding to 4,594 OTU (operational taxonomic units) sequences. The most abundant bacterial orders include Burkholderiales, Pseudomonadales, Xanthomonadales, Bacillales and Clostridiales. Alpha and Beta diversity analysis revealed specific features in different tissues. In addition, the content of Paraburkholderia fungorum was significantly higher in the paracancerous tissues and negatively correlated with CA199 (Carbohydrate antigen199) levels. The results of in vitro and in vivo experiments suggest that P. fungorum possesses an antitumor activity against tumors. Metabolomics and transcriptomics showed that P. fungorum could inhibit tumor growth through alanine, aspartate and glutamate metabolism. We determined the characteristic profile of the intratumoral microbiota and the antitumor effect of P. fungorum in ICC.
| S-EPMC9794006 | biostudies-literature
Project description:Intrahepatic cholangiocarcinoma (iCCA) is the second most common cancer in liver, with a high recurrence rate after surgery. Recently, we identified a CD11b-CD169-based myeloid response score (MRS), which showed remarkable prognostic potential in hepatocellular carcinoma (HCC). Here, we aimed to verify the prognostic value of the MRS in iCCA and establish an MRS-based nomogram to predict the postoperative prognosis of iCCA patients. From April 2005 to March 2017, a total of 84 patients from the Third Affiliated Hospital of Sun Yat-sen University were enrolled. Preoperative clinical information and surgical specimens of enrolled patients were collected. Among these, tissues from 75 patients passed the clinical data quality control and the staining quality control. The protein expression of CD11b and CD169 in iCCA samples were detected by immunohistochemistry (IHC). Kaplan-Meier analysis and receiver operating characteristic (ROC) curves revealed that the MRS had a high discriminatory ability for predicting the time to recurrence (TTR) of iCCA patients after surgery. Three independent risk factors selected by a Cox proportional hazards regression analysis, namely, the MRS, the tumor size and the status of vascular invasion, were included to construct a nomogram to predict the recurrence of iCCA after resection surgery. ROC curves, calibration analysis and decision curve analysis (DCA) suggested that this nomogram had notable discriminatory power, stability and clinical usefulness in predicting the postoperative recurrence. Together, we explored the prognostic value of the MRS in iCCA, and constructed an MRS-based nomogram which may help to predict postoperative recurrence and aid clinical decisions for iCCA patients.
| S-EPMC8548627 | biostudies-literature
Project description: Not available
| S-EPMC10881313 | biostudies-literature
Project description: Not available
| S-EPMC10722063 | biostudies-literature
Project description:ObjectivesTo develop and validate a diagnostic scoring system to differentiate intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM).MethodsA total of 366 patients (263 in the training cohort, 103 in the validation cohort) who underwent MRI examination with pathologically proven either IMCC or CRLM from two centers were included. Twenty-eight MRI features were collected. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors for distinguishing IMCC from solitary CRLM. The independent predictors were weighted over based on regression coefficients to build a scoring system. The overall score distribution was divided into three groups to show the diagnostic probability of CRLM.ResultsSix independent predictors, including hepatic capsular retraction, peripheral hepatic enhancement, vessel penetrating the tumor, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, and rim enhancement at the portal venous phase were included in the system. All predictors were assigned 1 point. At a cutoff of 3 points, AUCs for this score model were 0.948 and 0.903 with sensitivities of 96.5% and 92.0%, specificities of 84.4% and 71.7%, positive predictive values of 87.7% and 75.4%, negative predictive values of 95.4% and 90.5%, and accuracies of 90.9% and 81.6% for the training and validation cohorts, respectively. An increasing trend was shown in the diagnostic probability of CRLM among the three groups based on the score.ConclusionsThe established scoring system is reliable and convenient for distinguishing IMCC from solitary CRLM using six MRI features.Clinical relevance statementA reliable and convenient scoring system was developed to differentiate between intrahepatic mass-forming cholangiocarcinoma from solitary colorectal liver metastasis using six MRI features.Key points• Characteristic MRI features were identified to distinguish intrahepatic mass-forming cholangiocarcinoma (IMCC) from solitary colorectal liver metastasis (CRLM). • A model to distinguish IMCC from solitary CRLM was created based on 6 features, including hepatic capsular retraction, upper abdominal lymphadenopathy, peripheral washout at the portal venous phase, rim enhancement at the portal venous phase, peripheral hepatic enhancement, and vessel penetrating the tumor.
| S-EPMC10667410 | biostudies-literature