Surveillance MRI is associated with improved survival in patients with primary sclerosing cholangitis.

BACKGROUND: The benefits of regular surveillance imaging for cholangiocarcinoma in patients with primary sclerosing cholangitis (PSC) are unclear. Hence, we aimed to evaluate the impact of regular magnetic resonance cholangiopancreatography (MRCP) on outcomes of patients with PSC in Australia, where the practice of MRCP surveillance is variable. METHODS: The relationship between MRCP surveillance and survival outcomes was assessed in a multicenter, retrospective cohort of patients with PSC from 9 tertiary liver centers in Australia. An inverse probability of treatment weighting approach was used to balance groups across potentially confounding covariates. RESULTS: A total of 298 patients with PSC with 2117 person-years of follow-up were included. Two hundred and twenty patients (73.8%) had undergone MRCP surveillance. Regular surveillance was associated with a 71% reduced risk of death on multivariate weighted Cox analysis (HR: 0.29, 95% CI: 0.14-0.59, p < 0.001) and increased likelihood of having earlier endoscopic retrograde cholangiopancreatography from the date of PSC diagnosis in patients with a dominant stricture (p < 0.001). However, survival posthepatobiliary cancer diagnosis was not significantly different between both groups (p = 0.74). Patients who had surveillance of less than 1 scan a year (n = 41) had comparable survival (HR: 0.46, 95% CI 0.16-1.35, p = 0.16) compared to patients who had surveillance at least yearly (n = 172). CONCLUSIONS: In this multicenter cohort study that employed inverse probability of treatment weighting to minimize selection bias, regular MRCP was associated with improved overall survival in patients with PSC; however, there was no difference in survival after hepatobiliary cancer diagnosis. Further prospective studies are needed to confirm the benefits of regular MRCP and optimal imaging interval in patients with PSC.

Cholangiocarcinoma identified in perforated choledochal cyst in a 3-year-old boy.

Cholangiocarcinoma in patients with Choledochal cysts is rare in childhood; however, it seriously affects the prognosis of the disease. The key to addressing this situation lies in completely removing the extrahepatic cyst. We herein present a case report of a 3-year-old boy with cholangiocarcinoma associated with a choledochal cyst (CDC). Preoperative 3D simulation, based on CT data, played an important role in the treatment of this patient.

Prognostic Impact of Visceral Adipose Tissue Imaging Parameters in Patients with Cholangiocarcinoma after Surgical Resection.

Visceral adiposity is known to be related to poor prognosis in patients with cholangiocarcinoma; however, the prognostic significance of the qualitative features of adipose tissue in cholangiocarcinoma has yet to be well defined. This study investigated the prognostic impact of adipose tissue imaging parameters reflecting the quantity and qualitative characteristics of subcutaneous (SAT) and visceral (VAT) adipose tissue on recurrence-free survival (RFS) and overall survival (OS) in 94 patients undergoing resection of cholangiocarcinoma. The area, mean computed tomography (CT) attenuation, and mean 2-deoxy-2-[18F]fluoro-D-glucose (FDG) uptake of SAT and VAT on positron emission tomography (PET)/CT for staging work-up were measured, and the relationship of these adipose tissue imaging parameters with clinicopathological factors and survival was assessed. TNM stage, histologic grade, lymphovascular invasion, and the size of cholangiocarcinoma showed positive correlations with adipose tissue imaging parameters. Multivariate survival analysis demonstrated that the visceral-to-subcutaneous adipose tissue area ratio (VSR) (p = 0.024; hazard ratio, 1.718) and mean FDG uptake of VAT (p = 0.033; hazard ratio, 9.781) were significant predictors for RFS, but all of the adipose tissue imaging parameters failed to show statistical significance for predicting OS. In addition to visceral adiposity, FDG uptake of VAT might be a promising prognostic parameter for predicting RFS in patients with cholangiocarcinoma.

Cholangiocarcinoma: Epidemiology and Imaging-Based Review.

Cholangiocarcinoma (CCA) is a rare cancer of the bile duct epithelium, and in the last few decades its incidence rate has been increasing. It is associated with a high mortality rate due to late diagnosis and its aggressive nature. Many risk factors have been identified; some are more common in certain regions than others. CCA can be classified according to its anatomical location or macroscopic growth pattern, the latter being most helpful for imaging interpretation. Clinical features can vary from obstructive-like symptoms to nonspecific symptoms, such as weight loss and malaise. Imaging, specifically MRI/MRCP, is crucial in diagnosing CCA, staging, and treatment planning. Surgery with chemotherapy is the mainstay treatment option, and other palliative treatment options exist for those who have unresectable disease.

68 Ga-FAPI-04 PET/CT for the Evaluation of Cholangiocarcinoma : Comparison With 18 F-FDG PET/CT and Abdominal 68 Ga-FAPI-04 PET/MR.

PURPOSE: In this study, we evaluated and compared the diagnostic performances of 68 Ga-FAPI-04 PET/CT and 18 F-FDG PET/CT for primary and metastatic cholangiocarcinoma (CCA) lesions. We also investigated the performance of PET/MR for visualizing and characterizing CCA and liver metastasis lesions. PATIENTS AND METHODS: Forty-four patients with suspected CCA were recruited and underwent 68 Ga-FAPI-04 and 18 F-FDG PET/CT within 1 week, including 30 patients who underwent simultaneous abdominal 68 Ga-FAPI-04 PET/MR scanning. The findings were confirmed by histopathology or radiographic follow-up. RESULTS: Compared with 18 F-FDG PET/CT, 68 Ga-FAPI-04 PET/CT showed higher sensitivity (94.3% vs 88.6%) and the same accuracy (86.4% vs 86.4%) in evaluating primary tumors. However, its specificity was lower (55.6% vs 77.8%). 68 Ga-FAPI-04 PET was superior to 18 F-FDG PET in both patient-based and lesion-based evaluations except for metastatic lesions in the liver and bone. For intrahepatic CCA, 68 Ga-FAPI-04 PET/CT and 18 F-FDG PET/CT (100% vs 100%) had similar detection rates, with similar uptake levels between tracers ( P > 0.05). However, for extrahepatic CCA, 68 Ga-FAPI-04 PET/CT had a higher detection rate (89.5% vs 78.9%), and 68 Ga-FAPI-04 had a higher uptake ( P < 0.05). PET/MR was more effective than PET/CT in terms of lesion conspicuity and diagnostic confidence for primary tumors and liver metastases. In addition, multisequence MRI identified more liver metastases than 68 Ga-FAPI-04 PET/CT and 18 F-FDG PET/CT. CONCLUSIONS: Compared with 18 F-FDG PET/CT, 68 Ga-FAPI-04 PET/CT showed a higher sensitivity in detecting primary CCA tumors, involved lymph nodes, and peritoneal metastases. Compared with 68 Ga-FAPI-04 PET/CT, PET/MR detected primary and liver metastatic lesions more accurately. For extrahepatic CCA, the combination of 68 Ga-FAPI-04 PET/CT and abdominal PET/MRI may replace 18 F-FDG PET/CT.

Laparoscopic Tracer Technique for Liver Lymphatic Drainage by Injecting Indocyanine Green into the Glisson Pedicle.

BACKGROUND: Currently, an effective tracer technique for lymphatic drainage during laparoscopic surgery has not been established. This study aimed to elucidate a new fluorescence, imaging technique targeting the hepatic lymphatic drainage area, using indocyanine green (ICG). METHODS: A patient diagnosed with intrahepatic cholangiocarcinoma (ICC) located in segment 8 of the liver was injected with ICG into the connective tissue of the Glisson pedicle supplied by the lesion's liver segment, avoiding the bile duct, portal vein, and hepatic artery. This was performed under the guidance of laparoscopic ultrasonographic localization to trace the lymph nodes. RESULTS: The lymphatic drainage area traced intraoperatively by ICG was consistent with the definition of the right regional lymph nodes for ICC. The lymph nodes were dissected, followed by addition of a fluorescence tracer. CONCLUSIONS: Mastering intraoperative ultrasonic puncture technology can enable effective and accurate tracing of the lymph nodes of the liver segment where the lesion is located. However, the technical standards for this methodology need to be established through further studies.

Component prediction in combined hepatocellular carcinoma-cholangiocarcinoma: habitat imaging and its biologic underpinnings.

PURPOSE: To construct an MRI-based habitat imaging model to help predict component percentage in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) preoperatively, and investigate the biologic underpinnings of habitat imaging in cHCC-CCA. METHODS: The study consisted of one retrospective model-building dataset and one prospective validation dataset from two hospitals. All voxels were assigned into different clusters according to the similarity of enhancement pattern by using K-means clustering method, and each habitat's volume fraction in each lesion was calculated. Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to select optimal predictors, and then to establish an MRI-based habitat imaging model. R-squared was calculated to evaluate performance of the prediction models. Model performance was also verified in the prospective dataset with RNA sequencing data, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was then applied to investigate the biologic underpinnings of habitat imaging. RESULTS: A total of 129 patients were enrolled (mean age, 56.1 ± 10.4, 102 man), among which 104 patients were in the retrospective model-building set, while 25 patients in the prospective validation set. Three habitats, habitat1 (HCC-alike habitat), habitat2 (iCCA-alike habitat), and habitat3 (in-between habitat), were identified. Habitat 1's volume fraction, habitat 3's volume fraction, nonrim APHE, nonperipheral washout, and LI-RADS categorization were selected to develop an HCC percentage prediction model with R-squared of 0.611 in the model-building set and 0.541 in the validation set. Habitat 1's volume fraction was correlated with genes involved in regulation of actin cytoskeleton and Rap1 signaling pathway, which regulate cell migration and tumor metastasis. CONCLUSION: Preoperative prediction of HCC percentage in patients with cHCC-CCA was achieved using an MRI-based habitat imaging model, which may correlate with signaling pathways regulating cell migration and tumor metastasis.

Predictive Factor of Tumor Aggressiveness in Patients with Extrahepatic Cholangiocarcinoma Based on Diffusion-weighted MRI.

BACKGROUND: Extrahepatic cholangiocarcinoma (EHCC), an exceedingly malignant neoplasm, often eludes early detection, culminating in a dire prognosis. Accurate cancer staging systems and pathological differentiation are designed to guide adjuvant interventions and predict postoperative prognoses. OBJECTIVE: This study sought to investigate the predictive capacity of DW-MRI in discerning T stages, lymph node metastasis, and pathological differentiation grades in patients with EHCC. METHODS: Eighty-five patients were pathologically diagnosed with EHCC and underwent abdominal MRI within two weeks before surgery at our hospital from Aug 2011 to Aug 2021. Tumor axial maximum area (AMA) and apparent diffusion coefficient (ADC) values for diverse T stages, N stages, and differentiation grades were retrospectively analyzed. RESULTS: The Mann-Whitney U test displayed significantly higher lesion AMA values (P =0.006) and lower tumor ADC values (P = 0.001) in the nodepositive group (median ADC and AMA value: 1.220×10-3 mm2/s, 82.231 mm2) than in the node-negative group (median ADC and AMA value: 1.316×10-3 mm2/s, 51.174 mm2). A tumor ADC value<1.249×10-3 mm2/s from the receiver operating characteristic curve (AUC=0.725, P=0.001) exhibited the capability to predict node-positive EHCC with a sensitivity of 64.29%, and specificity of 73.68%. Furthermore, a progressive decrease in the degree of EHCC differentiation was associated with a reduction in the tumor ADC value (P=0.000). CONCLUSION: The N stage and differentiation of EHCC can be evaluated non-invasively using diffusion-weighted MRI.

A machine-learning model based on dynamic contrast-enhanced MRI for preoperative differentiation between hepatocellular carcinoma and combined hepatocellular-cholangiocarcinoma.

AIM: To establish a machine-learning model based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to differentiate combined hepatocellular-cholangiocarcinoma (cHCC-CC) from hepatocellular carcinoma (HCC) before surgery. MATERIALS AND METHODS: Clinical and MRI data of 194 patients with histopathologically diagnosed cHCC-CC (n=52) or HCC (n=142) were analysed retrospectively. ITK-SNAP software was used to delineate three-dimensional (3D) lesions and extract high-throughput features. Feature selection was carried out based on Pearson's correlation coefficient and least absolute shrinkage and selection operator (LASSO) regression analysis. A radiomics model (radiomics features), a clinical model (i.e., clinical-image features), and a fusion model (i.e., radiomics features + clinical-image features) were established using six machine-learning classifiers. The performance of each model in distinguishing between cHCC-CC and HCC was evaluated with the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), sensitivity, and specificity. RESULTS: Significant differences in liver cirrhosis, tumour number, shape, edge, peritumoural enhancement in the arterial phase, and lipid were identified between cHCC-CC and HCC patients (p<0.05). The AUC of the fusion model based on logistic regression was 0.878 (95% CI: 0.766-0.949) in the arterial phase in the test set, and the sensitivity/specificity was 0.844/0.714; however, the AUC of the clinical and radiomics models was 0.759 (95% CI: 0.663-0.861) and 0.838 (95% CI: 0.719-0.921) in the test set, respectively. CONCLUSION: The fusion model based on DCE-MRI in the arterial phase can significantly improve the diagnostic rate of cHCC-CC and HCC as compared with conventional approaches.

Utility of modified pancreaticoduodenectomy (Hi-cut PD) for middle-third cholangiocarcinoma: an alternative to hepatopancreaticoduodenectomy.

BACKGROUND: The standard procedure for middle-third cholangiocarcinoma (MCC) is pancreaticoduodenectomy (PD); hepatopancreaticoduodenectomy (HPD) is often performed despite its high risk. There is no clear selection guidance for these procedures. METHODS: Patients with MCC who underwent HPD or PD were retrospectively evaluated. The conventional PD was modified (mPD) to transect the bile duct beyond or close to the cranial level of the portal bifurcation. RESULTS: The mPD group (n = 55) was characterized by older age, shorter operation time, less blood loss, and less frequent complications than were observed in the HPD group (n = 34). The median grossly tumor-free margin of the proximal bile duct (GM) was 13 mm vs 20 mm (P = 0.006). Overall survival did not differ significantly between groups (48% vs 53% at 5 years, P = 0.399). Multivariate analysis identified positive surgical margin as a sole independent prognostic factor (hazard ratio, 1.89; P = 0.043), which was statistically associated with GM length. Five-year survival for mPD patients with GM ≥15 mm was significantly better than that for those who had GM <15 mm (69% vs 33%, P = 0.011) and comparable to that of HPD patients (53%, P = 0.450). CONCLUSION: The mPD may be recommended in patients with MCC, provided that GM ≥15 mm is expected from the preoperative radiological imaging. Otherwise, HPD should be considered.

Immunotherapy and targeted therapy for cholangiocarcinoma: Artificial intelligence research in imaging.

Cholangiocarcinoma (CCA) is a highly aggressive hepatobiliary malignancy, second only to hepatocellular carcinoma in prevalence. Despite surgical treatment being the recommended method to achieve a cure, it is not viable for patients with advanced CCA. Gene sequencing and artificial intelligence (AI) have recently opened up new possibilities in CCA diagnosis, treatment, and prognosis assessment. Basic research has furthered our understanding of the tumor-immunity microenvironment and revealed targeted molecular mechanisms, resulting in immunotherapy and targeted therapy being increasingly employed in the clinic. Yet, the application of these remedies in CCA is a challenging endeavor due to the varying pathological mechanisms of different CCA types and the lack of expressed immune proteins and molecular targets in some patients. AI in medical imaging has emerged as a powerful tool in this situation, as machine learning and deep learning are able to extract intricate data from CCA lesion images while assisting clinical decision making, and ultimately improving patient prognosis. This review summarized and discussed the current immunotherapy and targeted therapy related to CCA, and the research progress of AI in this field.

Survival analysis of patients with extrahepatic cholangiocarcinoma: a nomogram for clinical and MRI features.

BACKGROUND: This study aimed to establish a predictive model to estimate the postoperative prognosis of patients with extrahepatic cholangiocarcinoma (ECC) based on preoperative clinical and MRI features. METHODS: A total of 104 patients with ECC confirmed by surgery and pathology were enrolled from January 2013 to July 2021, whose preoperative clinical, laboratory, and MRI data were retrospectively collected and examined, and the effects of clinical and imaging characteristics on overall survival (OS) were analyzed by constructing Cox proportional hazard regression models. A nomogram was constructed to predict OS, and calibration curves and time-dependent receiver operating characteristic (ROC) curves were employed to assess OS accuracy. RESULTS: Multivariate regression analyses revealed that gender, DBIL, ALT, GGT, tumor size, lesion's position, the signal intensity ratio of liver to paraspinal muscle (SIRLiver/Muscle), and the signal intensity ratio of spleen to paraspinal muscle (SIRSpleen/Muscle) on T2WI sequences were significantly associated with OS, and these variables were included in a nomogram. The concordance index of nomogram for predicting OS was 0.766, and the AUC values of the nomogram predicting 1-year and 2-year OS rates were 0.838 and 0.863, respectively. The calibration curve demonstrated good agreement between predicted and observed OS. 5-fold and 10-fold cross-validation show good stability of nomogram predictions. CONCLUSIONS: Our nomogram based on clinical, laboratory, and MRI features well predicted OS of ECC patients, and could be considered as a convenient and personalized prediction tool for clinicians to make decisions.

The value of an MRI-based radiomics model in predicting the survival and prognosis of patients with extrahepatic cholangiocarcinoma.

OBJECTIVES: The study aimed to establish radiomics models based on magnetic resonance imaging (MRI) multiparameter images to predict the survival and prognosis of patients with extrahepatic cholangiocarcinoma (ECC). METHODS: Seventy-eight patients with ECC confirmed by pathology were collected retrospectively. The radiomics model_a/b/c were constructed based on the 1/2/3-year survival of patients with ECC. The best texture features were selected according to postoperative survival time and ECC patient status to calculate the radiomics score (Rad-score). A cutoff value was selected, and patients were divided into high-risk and low-risk groups. RESULTS: Model_a, model_b, and model_c were used to predict 1-, 2-, and 3-year postoperative survival rates, respectively. The area under the curve values in the training and test groups were 1.000 and 0.933 for model_a, 0.909 and 0.907 for model_b, 1.000 and 0.975 for model_c, respectively. The survival prediction model based on the Rad-score showed that the postoperative mortality risk differed significantly between risk groups (p < 0.0001). CONCLUSIONS: The MRI radiomics model could be used to predict the survival and prognosis of patients with ECC.

A multi-parameter intrahepatic cholangiocarcinoma scoring system based on modified contrast-enhanced ultrasound LI-RADS M criteria for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma.

PURPOSE: To develop a multi-parameter intrahepatic cholangiocarcinoma (ICC) scoring system and compare its diagnostic performance with contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system M (LR-M) criteria for differentiating ICC from hepatocellular carcinoma (HCC). METHODS: This retrospective study enrolled 62 high-risk patients with ICCs and 62 high-risk patients with matched HCCs between January 2022 and December 2022 from two institutions. The CEUS LR-M criteria was modified by adjusting the early wash-out onset (within 45 s) and the marked wash-out (within 3 min). Then, a multi-parameter ICC scoring system was established based on clinical features, B-mode ultrasound features, and modified LR-M criteria. RESULT: We found that elevated CA 19-9 (OR=12.647), lesion boundary (OR=11.601), peripheral rim-like arterial phase hyperenhancement (OR=23.654), early wash-out onset (OR=7.211), and marked wash-out (OR=19.605) were positive predictors of ICC, whereas elevated alpha-fetoprotein (OR=0.078) was a negative predictor. Based on these findings, an ICC scoring system was established. Compared with the modified LR-M and LR-M criteria, the ICC scoring system showed the highest area under the curve (0.911 vs. 0.831 and 0.750, both p<0.05) and specificity (0.935 vs. 0.774 and 0.565, both p<0.05). Moreover, the numbers of HCCs categorized as LR-M decreased from 27 (43.5%) to 14 (22.6%) and 4 (6.5%) using the modified LR-M criteria and ICC scoring system, respectively. CONCLUSION: The modified LR-M criteria-based multi-parameter ICC scoring system had the highest specificity for diagnosing ICC and reduced the number of HCC cases diagnosed as LR-M category.