Prediction of the histopathologic findings of intrahepatic cholangiocarcinoma: qualitative and quantitative assessment of diffusion-weighted imaging

Radiomics nomogram based on optimal VOI of multi-sequence MRI for predicting microvascular invasion in intrahepatic cholangiocarcinoma

OBJECTIVE

Microvascular invasion (MVI) is a significant adverse prognostic indicator of intrahepatic cholangiocarcinoma (ICC) and affects the selection of individualized treatment regimens. This study sought to establish a radiomics nomogram based on the optimal VOI of multi-sequence MRI for predicting MVI in ICC tumors.

METHODS

160 single ICC lesions with MRI scanning confirmed by postoperative pathology were randomly separated into training and validation cohorts (TC and VC). Multivariate analysis identified independent clinical and imaging MVI predictors. Radiomics features were obtained from images of 6 MRI sequences at 4 different VOIs. The least absolute shrinkage and selection operator algorithm was performed to enable the derivation of robust and effective radiomics features. Then, the best three sequences and the optimal VOI were obtained through comparison. The MVI prediction nomogram combined the independent predictors and optimal radiomics features, and its performance was evaluated via the receiver operating characteristics, calibration, and decision curves.

RESULTS

Tumor size and intrahepatic ductal dilatation are independent MVI predictors. Radiomics features extracted from the best three sequences (T1WI-D, T1WI, DWI) with VOI10mm (including tumor and 10 mm peritumoral region) showed the best predictive performance, with AUCTC = 0.987 and AUCVC = 0.859. The MVI prediction nomogram obtained excellent prediction efficacy in both TC (AUC = 0.995, 95%CI 0.987-1.000) and VC (AUC = 0.867, 95%CI 0.798-0.921) and its clinical significance was further confirmed by the decision curves.

CONCLUSION

A nomogram combining tumor size, intrahepatic ductal dilatation, and the radiomics model of MRI multi-sequence fusion at VOI10mm may be a predictor of preoperative MVI status in ICC patients.

Imaging features based on CT and MRI for predicting prognosis of patients with intrahepatic cholangiocarcinoma: a single-center study and meta-analysis

BACKGROUND

To evaluate the prognostic role of imaging features based on CT and MRI in intrahepatic cholangiocarcinoma (ICC).

METHODS

Two hundred and four patients from a single-center database who underwent radical ICC surgery from 2010 to 2019 were enrolled in the study. Cox proportional hazard model was used for survival analysis of imaging features. A meta-analysis was performed to determine imaging features that predict overall survival (OS) and event-free survival (EFS) in ICC.

RESULTS

In the CT group of the retrospective cohort, tumor multiplicity, infiltrative tumor margin, lymph node metastasis, enhancement pattern in hepatic arterial phase and tumor necrosis correlated with poorer EFS and OS; moreover, enhancing capsules, high carcinoembryonic antigen levels contributed to poor OS. In the MRI group, tumor multiplicity and enhancement pattern were prognostic factors for OS; tumor multiplicity and enhancement pattern resulted in poor EFS. A total of 13 articles containing 1822 patients with ICC were enrolled in the adjusted hazard ratios meta-analysis. The results showed that enhancement pattern and infiltrative tumor margin were predictors of OS and EFS, whereas bile duct invasion was a predictor of OS.

CONCLUSIONS

Arterial enhancement patterns and tumor margin status were associated with both OS and EFS of ICC patients following resection.

Update on the Applications of Radiomics in Diagnosis, Staging, and Recurrence of Intrahepatic Cholangiocarcinoma

BACKGROUND

This paper offers an assessment of radiomics tools in the evaluation of intrahepatic cholangiocarcinoma.

METHODS

The PubMed database was searched for papers published in the English language no earlier than October 2022.

RESULTS

We found 236 studies, and 37 satisfied our research criteria. Several studies addressed multidisciplinary topics, especially diagnosis, prognosis, response to therapy, and prediction of staging (TNM) or pathomorphological patterns. In this review, we have covered diagnostic tools developed through machine learning, deep learning, and neural network for the recurrence and prediction of biological characteristics. The majority of the studies were retrospective.

CONCLUSIONS

It is possible to conclude that many performing models have been developed to make differential diagnosis easier for radiologists to predict recurrence and genomic patterns. However, all the studies were retrospective, lacking further external validation in prospective and multicentric cohorts. Furthermore, the radiomics models and the expression of results should be standardized and automatized to be applicable in clinical practice.

Development and validation of combined Ki67 status prediction model for intrahepatic cholangiocarcinoma based on clinicoradiological features and MRI radiomics

PURPOSE

Incidence and mortality of intrahepatic cholangiocarcinoma (ICC) have been increasing over the past few decades, and Ki67 is an adverse prognostic predictor and an attractive therapeutic target for ICC patients. Thus, we aim to develop and validate a combined Ki67 prediction model for ICC patients.

MATERIALS AND METHODS

Preoperative contrast-enhanced MR images were collected from 178 patients with postoperative pathologically confirmed ICC, and randomly divided into training and validation cohorts in a ratio of 7:3 (124:54). A time-independent test cohort of 49 ICC patients was used for validation. Independent clinicoradiological features of Ki67 status were determined by multivariate analysis. Optimal radiomics features were selected by least absolute shrinkage and selection operator logistic regression and linear discriminant analysis was used to construct combined models. The prediction efficacy of combined model was assessed by receiver operating characteristics curve, and verified by its calibration, decision and clinical impact curves.

RESULTS

HBV (p = 0.022), arterial rim enhancement (p = 0.006) and enhancement pattern (p = 0.012) are independent clinicoradiological features. The radiomics model achieves good prediction efficacy in the training cohort (AUC = 0.860) and validation cohort (AUC = 0.843). The combined Ki67 prediction model incorporates clinicoradiological and radiomics features, and it yields desirable predictive efficiency in test cohort (AUC = 0.815). Decision curves and clinical impact curves further validate that the combined Ki67 prediction model can achieve net benefits in clinical work.

CONCLUSION

The combined Ki67 model incorporating HBV, arterial rim enhancement, enhancement pattern and radiomics features is a potential biomarker in Ki67 prediction and stratification.

Utility of diffusion tensor imaging in differentiating benign from malignant hepatic focal lesions

OBJECTIVES

To assess the diagnostic accuracy of diffusion tensor imaging (DTI) in the characterization of hepatic focal lesions (HFLs) and compare it to diffusion-weighted imaging (DWI).

METHODS

Prospective analysis was done for 49 patients (23 male and 26 female) with 74 HFLs who underwent dynamic MRI, DWI, and DTI. Apparent diffusion coefficient (ADC) values from DWI, fractional anisotropy (FA) values, and mean diffusivity (MD) values from DTI were measured by two independent radiologists. HFLs were classified into benign and malignant HFLs; the latter were subdivided into HCC and non-HCC lesions. Binary logistic regression was performed to analyze the associations between the DTI parameters and the distinction of malignant lesions.

RESULTS

The ADC, MD, and FA at cutoff values of ≤ 1.17 × 10^-3 mm²/s, ≤ 1.71 × 10^-3 mm²/s, and > 0.29, respectively, are excellent discriminators for differentiating malignant and benign HFLs. The mean ADC and MD values of hemangiomas were significantly higher than HCC and non-HCC malignant lesions. In contrast, the mean FA values of hemangiomas were significantly lower than those of non-HCC malignant lesions and HCCs. The ADC and MD were very good discriminators at cutoff values of > 1.03 × 10^-3 mm²/s and > 1.12 × 10^-3 mm²/s, respectively. The FA at a cutoff value > 0.38 is an excellent discriminator for HCC versus non-HCC malignant lesions. Only FA value > 0.38 was a statistically significant independent predictor of HCC versus non-HCC lesions among the three parameters. There was an excellent inter-observer agreement with ICC > 0.9.

CONCLUSION

MD and FA of DTI are non-invasive, very good, and excellent discriminators superior to ADC measured by DWI for the differentiation of HFLs.

KEY POINTS

• The ADC, MD, and FA at cutoff values of ≤ 1.17 × 10^-3 mm²/s, ≤ 1.71 × 10^-3 mm²/s, and > 0.29, respectively, are excellent discriminators for differentiating malignant and benign HFLs. • The mean ADC and MD values of hemangiomas were significantly higher than those of HCC and non-HCC malignant lesions. In contrast, the mean FA values of hemangiomas were significantly lower than those of non-HCC malignant lesions and HCCs, respectively. • Multivariate regression analysis revealed that only FA value > 0.38 was a statistically significant independent predictor of HCC vs. non-HCC lesions. A lesion with FA > 0.38 has 34 times higher odds of being HCC rather than non-HCC lesions.

Nomogram based on MRI for preoperative prediction of Ki-67 expression in patients with intrahepatic mass cholangiocarcinoma

OBJECTIVES

To validate a new nomogram based on magnetic resonance imaging (MRI) for pre-operative prediction of Ki-67 expression in patients with intrahepatic mass cholangiocarcinoma (IMCC).

METHODS

A total of 78 patients with clinicopathologically confirmed IMCC who underwent pre-operative gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced MRI between 2016 and 2022 were enrolled in the training and validation group (53 patients and 25 patients, respectively). Images including qualitative, quantitative MRI features and clinical data were evaluated. Univariate analysis and multivariate logistic regression were used to select the independent predictors and establish different predictive models. The predictive performance was validated by operating characteristic curve (ROC) analysis, calibration curve, and decision curve analysis (DCA). The validation cohort was used to test the predictive performance of the optimal model. The nomogram was constructed with the optimal model.

RESULTS

In the training cohort, independent predictors obtained from the combined model were DWI (OR 1822.741; 95% CI 6.189, 536,781.805; P = 0.01) and HBP enhancement pattern (OR 14.270; 95% CI 1.044, 195.039; P = 0.046). The combined model showed the good performance (AUC 0.981; 95% CI 0.952, 1.000) for predicting Ki-67 expression. In the validation cohort, The combined model (AUC 0.909; 95% CI 0.787, 1.000)showed the best performance compared to the clinical model (AUC 0.448; 95% CI 0.196, 0.700) and MRI model (AUC 0.770; 95% CI 0.570, 0.970).

CONCLUSION

This new nomogram has a good performance in predicting Ki-67 expression in patients with IMCC, which could help the decision-making of the patients' therapy strategies.

Apparent Diffusion Coefficient MRI Shows Association With Early Progression of Unresectable Intrahepatic Cholangiocarcinoma With Combined Targeted-Immunotherapy

BACKGROUND

Most intrahepatic cholangiocarcinomas (ICCs) are diagnosed at advanced stage with an extremely poor prognosis. For these patients, combining targeted therapies and immunotherapy may have a promising therapeutic effect, and current Response Evaluation Criteria in Solid Tumors (RECIST) criteria have limited applicability.

PURPOSE

To investigate the associations between pretreatment MRI features and the efficacy of combined targeted-immunotherapy by estimating the risk of early progression (EP) in unresectable ICC, with special emphasis on diffusion-weighted imaging.

STUDY TYPE

Retrospective.

SUBJECTS

A total of 43 unresectable ICC patients (24 with EP [disease progression ≤12 months after treatment] and 19 with nonearly progression [NEP, disease progression >12 months]), who received first-line systemic therapy with lenvatinib plus PD1 antibody combination.

FIELD STRENGTH/SEQUENCE

The 0-T scanner, including T1- and T2-weighted imaging, diffusion-weighted imaging, and dynamic gadopentetate dimeglumine-enhanced imaging.

ASSESSMENT

Clinical characteristics and MR imaging features including apparent diffusion coefficient (ADC), as well as survival analysis of EP were evaluated.

STATISTICAL TESTS

Features between EP and NEP groups were compared by univariate analyses and multivariate logistic regression analysis. Diagnostic performance was analyzed by receiver operating characteristic curve. Univariate and multivariate Cox regression models were applied for survival analysis of EP. The progression-free survival (PFS) rates were estimated using the Kaplan-Meier analysis and compared by the log-rank test. The significance threshold was set at P < 0.05.

RESULTS

Tumor number, tumor margin, arterial peritumoral enhancement, lymphatic metastasis, and apparent diffusion coefficient (ADC) value were significantly different between EP and NEP groups. At multivariate logistic regression analysis, ADC was the only independent variable associated with EP (odds ratio = 0.012), with an area under the curve of 0.774 (optimal cutoff value was 1.028 × 10^-3  mm² /sec). Multivariate Cox regression model proved that ADC value (hazard ratio = 0.140) and ill-defined margin (hazard ratio = 2.784) were independent risk factors. ICCs with low ADC values showed shorter PFS than those with high values (χ²  = 9.368).

DATA CONCLUSION

Pretreatment MRI features were associated with EP for unresectable ICC treated with combined targeted-immunotherapy, and decreased ADC value was an independent variable.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 4.

Clinical relevance of biomarkers in cholangiocarcinoma: critical revision and future directions

Cholangiocarcinoma (CCA) is a malignant tumour arising from the biliary system. In Europe, this tumour frequently presents as a sporadic cancer in patients without defined risk factors and is usually diagnosed at advanced stages with a consequent poor prognosis. Therefore, the identification of biomarkers represents an utmost need for patients with CCA. Numerous studies proposed a wide spectrum of biomarkers at tissue and molecular levels. With the present paper, a multidisciplinary group of experts within the European Network for the Study of Cholangiocarcinoma discusses the clinical role of tissue biomarkers and provides a selection based on their current relevance and potential applications in the framework of CCA. Recent advances are proposed by dividing biomarkers based on their potential role in diagnosis, prognosis and therapy response. Limitations of current biomarkers are also identified, together with specific promising areas (ie, artificial intelligence, patient-derived organoids, targeted therapy) where research should be focused to develop future biomarkers.

Diffusion-weighted imaging as an imaging biomarker for assessing survival of patients with intrahepatic mass-forming cholangiocarcinoma

BACKGROUND

Mass-forming cholangiocarcinoma is the most common form of intrahepatic cholangiocarcinoma and is associated with a worse prognosis. This study aimed to assess the role of diffusion-weighted imaging and other imaging features as prognostic markers to predict the survival of patients with intrahepatic mass-forming cholangiocarcinoma (IMCC).

MATERIALS AND METHODS

The study included patients with pathologically proven IMCC from January 2011 to January 2018. Two radiologists retrospectively reviewed various imaging findings and manually estimated the area of diffusion restriction. Patients were grouped according to their restriction area into (group 1) restriction ≥ 1/3 of the tumor and (group 2) restriction < 1/3 of the tumor. Statistical analysis was performed to assess the relationship between various imaging features and patients' survival.

RESULTS

Seventy-three patients were included in the study. IMCC patients with tumor size ≥ 5 cm had increased intrahepatic- and peritoneal metastases (p = 039 and p = 0.001 for reader 1 and p = 0.048 and p = 0.057 for reader 2). There was no significant relationship between the diffusion restriction area and tumor size, enhancement pattern, vascular involvement, lymph node metastasis, peritoneal- and distant metastasis. The number of deaths was significantly higher in patients with group 2 restriction (63.6% for group 1 vs. 96.6% for group 2; p = 0.001 for reader 1)(68.2% for group 1 vs. 89.7%% for group 2; p = 0.030 for reader 2). Patients with group 2 restriction had shorter 1- and 3-year survival rates and lower median survival time. Multivariable survival analysis showed two independent prognostic factors relating to poor survival outcomes: peritoneal metastasis (p = 0.04 for reader 1 and p = 0.041 for reader 2) and diffusion restriction < 1/3 (p = 0.011 for reader 1 and p = 0.042 for reader 2). Lymph node metastasis and intrahepatic metastasis were associated with shorter survival in the univariate analysis. However, these factors were non-significant in the multivariate analysis.

CONCLUSION

Restriction diffusion of less than 1/3 and peritoneal metastasis were associated with shorter overall survival of IMCC patients. Other features that might correlate with the outcome are suspicious lymph nodes and multifocal lesions.

Values of MRI Imaging Presentations in the Hepatobiliary Phase, DWI and T2WI Sequences in Predicting Pathological Grades of Intrahepatic Mass-Forming Cholangiocarcinoma

Objective

To retrospectively investigate the value of various MRI image menifestations in the hepatobiliary phase (HBP), DWI and T2WI sequences in predicting the pathological grades of intrahepatic mass-forming cholangiocarcinoma (IMCC).

Materials and Methods

Forty-three patients of IMCCs confirmed by pathology were enrolled including 25 cases in well- or moderately-differentiated group and 18 cases in poorly-differentiated group. All patients underwent DWI, T2WI and HBP scan. The Chi square test was used to compare the differences in the general information. Logistic regression analysis was used to analyze the risk factors in predicting the pathological grade of IMCCs.

Results

The maximal diameter of the IMCC lesion was < 3 cm in 11 patients, between 3 cm and 6 cm in 15, and > 6 cm in 17. Sixteen cases had intrahepatic metastasis, including 5 in the well- or moderately-differentiated group and 11 in the poorly-differentiated group. Seventeen (39.5%) patients presented with target signs in the DWI sequence, including 9 in the well- or moderately-differentiated group and 8 in the poorly-differentiated group. Twenty (46.5%) patients presented with target signs in the T2WI sequence, including 8 in the well- or moderately-differentiated group and 12 in the poorly-differentiated group. Nineteen cases (54.3%) had a complete hypointense signal ring, including 13 in the well- or moderately-differentiated group and 6 in the poorly-differentiated group. Sixteen (45.7%) cases had an incomplete hypointense signal ring, including 5 in the well- or moderately-differentiated group and 11 in the poorly-differentiated group. The lesion size, intrahepatic metastasis, T2WI signal, and integrity of a hypointense signal ring in HBP were statistically significantly different between two gourps. T2WI signal, presence or non-presence of intrahepatic metastasis, and integrity of hypointense signal ring were the independent influencing factors for pathological grade of IMCC.

Conclusion

Target sign in T2WI sequence, presence of intrahepatic metastasis and an incomplete hypointense-signal ring in HBP are more likely to be present in poorly-differentiated IMCCs.

A Multi-Parametric Radiomics Nomogram for Preoperative Prediction of Microvascular Invasion Status in Intrahepatic Cholangiocarcinoma

Background

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime.

Purpose

This study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively.

Methods

A total of 163 pathologically confirmed ICC patients (training cohort: n = 130; validation cohort: n = 33) with postoperative Ga-DTPA-enhanced MR examination were enrolled, and a time-independent test cohort (n = 24) was collected for external validation. Univariate and multivariate analyses were used to determine the independent predictors of MVI status, which were then incorporated into the MVI prediction nomogram. Least absolute shrinkage and selection operator logistic regression was performed to select optimal features and construct radiomics models. The prediction performances of models were assessed by receiver operating characteristic (ROC) curve analysis. The performance of the MVI prediction nomogram was evaluated by its calibration, discrimination, and clinical utility.

Results

Larger tumor size (p = 0.003) and intrahepatic duct dilatation (p = 0.002) are independent predictors of MVI. The final radiomics model shows desirable and stable prediction performance in the training cohort (AUC = 0.950), validation cohort (AUC = 0.883), and test cohort (AUC = 0.812). The MVI prediction nomogram incorporates tumor size, intrahepatic duct dilatation, and the final radiomics model and achieves excellent predictive efficacy in training cohort (AUC = 0.953), validation cohort (AUC = 0.861), and test cohort (AUC = 0.819), fitting well in calibration curves (p > 0.05). Decision curve and clinical impact curve further confirm the clinical usefulness of the nomogram.

Conclusion

The nomogram incorporating tumor size, intrahepatic duct dilatation, and the final radiomics model is a potential biomarker for preoperative prediction of the MVI status in ICC patients.

Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics

Purpose

To test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model.

Methods

Histologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous phase computed tomography (CT), by two readers with different experience (R1 and R2). Morphological CT features included: tumor size, hepatic satellite lesions, lymph node and distant metastases. Radiomic features (RF) were compared across CT protocols and readers. Univariate analysis against overall survival (OS) warranted ranking and selection of RF into radiomic signature (RSign), which was dichotomized into high and low-risk strata (RSign*). Models without and with RSign* (Model 1 and 2, respectively) were compared.

Results

Among 78 patients (median follow-up 262 days, IQR 73–957), 62/78 (79%) died during the study period, 46/78 (59%) died within 1 year. Up to 10% RF showed variability across CT protocols; 37/108 (34%) RF showed variability due to manual segmentation. RSign stratified OS (univariate: HR 1.37 for R1, HR 1.28 for R2), RSign* was different between readers (R1 0.39; R2 0.57). Model 1 showed AUC 0.71, which increased in Model 2: AUC 0.81 (p < 0.001) and AIC 89 for R1, AUC 0.81 (p = 0.001) and AIC 90.2 for R2.

Conclusion

The use of RF into a unified RSign score stratified OS in patients with IMCC. Dichotomized RSign* classified survival strata, its inclusion in risk models showed adjunct yield. The cut-off value of RSign* was different between readers, suggesting that the use of reference values is hampered by interobserver variability.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00261-021-03183-9.

Prognostic prediction of resectable colorectal liver metastasis using the apparent diffusion coefficient from diffusion-weighted magnetic resonance imaging

AIM

Diffusion-weighted magnetic resonance imaging (DWI-MRI) is used to predict tumor malignancy. Here we explored the role of apparent diffusion coefficient (ADC) values in the treatment of patients with resectable colorectal liver metastasis (CRLM).

METHODS

Magnetic resonance imaging (MRI) scans were conducted using a Signa HDe or Signa Explorer 1.5-T scanner (GE Healthcare). ADC maps were calculated using DWI with b values of 0, 20, and 800 s/mm2. We enrolled 60 patients who underwent upfront hepatic resection for CRLM and divided them into ADC-high (n = 30) and ADC-low (n = 30) groups. Clinicopathological variables of the groups were compared. Immunohistochemical analysis of HIF-1α expression in tumor tissues was performed, and the relationship between the ADC value and HIF-1α expression was evaluated.

RESULTS

The disease-free survival rate of the ADC-low group was significantly lower than that of the ADC-high group (P < .05). Univariate analysis revealed that tumor number (more than five), synchronous metastasis, and low ADC were prognostic factors. Multivariate analysis identified low ADC as an independent prognostic factor. Furthermore, the ADC-low group more frequently expressed high levels of HIF-1α than the ADC-high group.

CONCLUSION

Low ADC values were an independent prognostic factor of resectable CRLM and correlated with HIF-1α expression.

Radiomics signature on dynamic contrast-enhanced MR images: a potential imaging biomarker for prediction of microvascular invasion in mass-forming intrahepatic cholangiocarcinoma

OBJECTIVE

To develop a radiomics signature based on dynamic contrast-enhanced (DCE) MR images for preoperative prediction of microvascular invasion (MVI) in patients with mass-forming intrahepatic cholangiocarcinoma (IMCC).

METHODS

One hundred twenty-six patients with surgically resected single IMCC (34 MVI-positive and 92 MVI-negative) were enrolled and allocated to training and validation cohorts (7:3 ratio). Findings of clinical characteristics and MR features were analyzed. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator (LASSO) regression algorithm in the training cohort. The prediction performance of radiomics signature was evaluated by receiver operating characteristics curve (ROC) analysis. Internal validation was performed on an independent cohort containing 38 patients.

RESULTS

Larger tumor size and higher radiomics score were positively correlated with MVI in both training cohort (p < 0.001, < 0.001, respectively) and validation cohort (p = 0.008, 0.001, respectively). The radiomics signature, consisting of seven wavelet features, showed optimal prediction performance in both training (AUC = 0.873) and validation cohorts (AUC = 0.850).

CONCLUSION

A radiomics signature derived from DCE-MRI of the liver can be a reliable imaging biomarker for predicting MVI of IMCC, which could aid in tailoring treatment strategies.

KEY POINTS

• The radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging can be a useful tool to preoperatively predict MVI of IMCC. • Larger tumor size is positively correlated with MVI of IMCC.

Inter-observer agreement of computed tomography and magnetic resonance imaging on gross tumor volume delineation of intrahepatic cholangiocarcinoma: an initial study

Background

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor, and local radiotherapy has a positive effect on patients with an unresectable tumor. Accurate delineation of gross tumor volume (GTV) is crucial to improve the efficacy of radiotherapy. The purpose of this article was to evaluate the consistency of CT, diffusion weighted imaging (DWI) and Gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced MRI on GTV delineation of ICC.

Methods

Fourteen patients with ICC underwent CT (Plain and Portal, CT scans before and 70 s after the injection of Omnipaque, respectively), DWI, and Gd-EOB-DTPA-enhanced MRI (EOB 70 s and EOB 15 min, mDIXON scans at 70 s and 15 min after the injection of Gd-EOB-DTPA, respectively) examinations before radiotherapy. Volumes of GTV delineation on CT and MRI images were recorded. Dice similarity coefficient (DSC) was calculated to evaluate the spatial overlap.

Results

Tumor volume on DWI and EOB 15 min were larger than that on EOB 70 s significantly (both P=0.004). DSC of DWI was significantly larger than that of other CT and MRI sequences (all P≤0.002). DSC of EOB 15 min tended to be larger than that of other CT sequences and EOB 70 s, however, without significances (all P>0.005). Significant correlation was found between DSC and tumor volume (R=0.35, P=0.003).

Conclusions

DWI had significantly higher agreement on GTV delineation of ICC. GTV delineations of ICC on Gd-EOB-DTPA-enhanced MRI showed excellent inter-observer agreement. Fusion of CT and MRI images should be considered to improve the accuracy of GTV delineation.

Role of Central Hypo-enhancement in the Hepatic Arterial Phase of Dynamic Computed Tomography in Patients with Mass-Forming Intrahepatic Cholangiocarcinoma

BACKGROUND/PURPOSE

The enhancement pattern in the hepatic arterial phase (HAP) of dynamic computed tomography (CT) is reportedly a prognostic marker in patients with intrahepatic cholangiocarcinoma (IHCC). This study was performed to clarify the significance of central hypo-enhancement in the HAP in patients with mass-forming IHCC.

METHODS

Forty patients who had undergone initial surgical resection for mass-forming IHCC were enrolled. The dynamic CT was scanned 40 s after contrast agent injection as the HAP. A radiologist classified the patients into three groups based on the vascular pattern: the hyper-enhancement group (Hyper group), rim-enhancement group (Rim group), and hypo-enhancement group (Hypo group). The surgical specimens were immunohistochemically stained for hypoxia-inducible factor 1 (HIF-1). The correlation with clinicopathological findings and HIF-1 expression was investigated.

RESULTS

The Hyper, Rim, and Hypo groups comprised 8, 7, and 25 patients, respectively. There were no significant correlations between the groups and clinicopathological factors. Overall survival (OS) was significantly worse in the Hypo than in the Hyper group (p = 0.03). OS was also significantly worse in the Rim + Hypo group (i.e., hypo-enhancement in the central tumor) than in the Hyper group (p = 0.04). Furthermore, inclusion in the Rim + Hypo group was a prognostic factor for OS (hazard ratio 6.68). High HIF-1 expression in the central part of the tumor was correlated with central hypo-enhancement (Hyper group: 25% and Rim + Hypo group: 72%).

CONCLUSIONS

Central hypo-enhancement was a prognostic factor in patients with IHCC. The high malignant potential of tumors with central hypo-enhancement might be associated with HIF-1 upregulation.

Cholangiocarcinoma Evaluation via Imaging and Artificial Intelligence

BACKGROUND

Cholangiocarcinoma (CCA) is a relatively rare malignant biliary system tumor, and yet it represents the second most common primary hepatic neoplasm, following hepatocellular carcinoma. Regardless of the type, location, or etiology, the survival prognosis of these tumors remains poor. The only method of cure for CCA is complete surgical resection, but part of patients with complete resection are still subject to local recurrence or distant metastasis.

SUMMARY

Over the last several decades, our understanding of the molecular biology of CCA has increased tremendously, diagnostic and evaluative techniques have evolved, and novel therapeutic approaches have been established. Key Messages: This review provides an overview of preoperative imaging evaluations of CCA. Furthermore, relevant information about artificial intelligence (AI) in medical imaging is discussed, as well as the development of AI in CCA treatment.

Intrahepatic cholangiocarcinoma: pathogenesis, current staging, and radiological findings

To this date, it is a major oncological challenge to optimally diagnose, stage, and manage intrahepatic cholangiocarcinoma (ICC). Imaging can not only diagnose and stage ICC, but it can also guide management. Hence, imaging is indispensable in the management of ICC. In this article, we review the pathology, epidemiology, genetics, clinical presentation, staging, pathology, radiology, and treatment of ICC.

A Novel Approach to Assessing Differentiation Degree and Lymph Node Metastasis of Extrahepatic Cholangiocarcinoma: Prediction Using a Radiomics-Based Particle Swarm Optimization and Support Vector Machine Model

BACKGROUND

Radiomics can improve the accuracy of traditional image diagnosis to evaluate extrahepatic cholangiocarcinoma (ECC); however, this is limited by variations across radiologists, subjective evaluation, and restricted data. A radiomics-based particle swarm optimization and support vector machine (PSO-SVM) model may provide a more accurate auxiliary diagnosis for assessing differentiation degree (DD) and lymph node metastasis (LNM) of ECC.

OBJECTIVE

The objective of our study is to develop a PSO-SVM radiomics model for predicting DD and LNM of ECC.

METHODS

For this retrospective study, the magnetic resonance imaging (MRI) data of 110 patients with ECC who were diagnosed from January 2011 to October 2019 were used to construct a radiomics prediction model. Radiomics features were extracted from T1-precontrast weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) using MaZda software (version 4.6; Institute of Electronics, Technical University of Lodz). We performed dimension reduction to obtain 30 optimal features of each sequence, respectively. A PSO-SVM radiomics model was developed to predict DD and LNM of ECC by incorporating radiomics features and apparent diffusion coefficient (ADC) values. We randomly divided the 110 cases into a training group (88/110, 80%) and a testing group (22/110, 20%). The performance of the model was evaluated by analyzing the area under the receiver operating characteristic curve (AUC).

RESULTS

A radiomics model based on PSO-SVM was developed by using 110 patients with ECC. This model produced average AUCs of 0.8905 and 0.8461, respectively, for DD in the training and testing groups of patients with ECC. The average AUCs of the LNM in the training and testing groups of patients with ECC were 0.9036 and 0.8889, respectively. For the 110 patients, this model has high predictive performance. The average accuracy values of the training group and testing group for DD of ECC were 82.6% and 80.9%, respectively; the average accuracy values of the training group and testing group for LNM of ECC were 83.6% and 81.2%, respectively.

CONCLUSIONS

The MRI-based PSO-SVM radiomics model might be useful for auxiliary clinical diagnosis and decision-making, which has a good potential for clinical application for DD and LNM of ECC.

Apparent diffusion coefficient value of mass-forming intrahepatic cholangiocarcinoma: a potential imaging biomarker for prediction of lymph node metastasis

PURPOSE

To compare the differences of MR features between mass-forming intrahepatic cholangiocarcinoma (IMCC) with and without lymph node metastasis (LNM) and to search for new imaging biomarkers for predicting LNM.

MATERIALS AND METHODS

The study included 91 patients with histopathologically confirmed single IMCC (20 patients with LNM and 71 patients without LNM). Findings of preoperative MR imaging including diffusion-weighted imaging (DWI) (b value 0, 500 mm²/s) were analyzed and apparent diffusion coefficient (ADC) values (b = 500 mm²/s) were calculated. Logistic regression analysis was performed to identify independent predictors of LNM. The diagnostic performance of independent predictors was assessed by receiver operating characteristic (ROC) and area under the curve (AUC) was compared.

RESULTS

Larger tumor size (p = 0.001), diameter of largest lymph node (LN) > 1 cm (p < 0.001), higher ADC value of primary IMCC lesion (ADC_IMCC value) (p = 0.001), and positive CA19-9 level (p = 0.018) were correlated with LNM. Multivariate logistic regression analysis demonstrated that ADC_IMCC value (odds ratio, 3.347; p = 0.001) and diameter of largest LN > 1 cm (odds ratio, 7.571; p = 0.004) were independent predictors of LNM. The AUCs for ADC_IMCC value, diameter of largest LN > 1 cm,and combined method (the combination of ADC_IMCC value and diameter of largest LN > 1 cm) were 0.782, 0.701,and 0.857, respectively. The AUC for combined method was significantly higher than that of diameter of largest LN > 1 cm (p = 0.033).

CONCLUSION

ADC_IMCC value can be a potential imaging biomarker for predicting LNM of IMCC, especially in combination with diameter of largest LN > 1 cm.

Outcomes assessment in intrahepatic cholangiocarcinoma using qualitative and quantitative imaging features

BACKGROUND

To assess the performance of imaging features, including radiomics texture features, in predicting histopathologic tumor grade, AJCC stage, and outcomes [time to recurrence (TTR) and overall survival (OS)] in patients with intrahepatic cholangiocarcinoma (ICC).

METHODS

Seventy-three patients (26 M/47F, mean age 63y) with pre-operative imaging (CT, n = 37; MRI, n = 21; CT and MRI, n = 15] within 6 months of resection were included in this retrospective study. Qualitative imaging traits were assessed by 2 observers. A 3rd observer measured tumor apparent diffusion coefficient (ADC), enhancement ratios (ERs), and Haralick texture features. Blood biomarkers and imaging features were compared with histopathology (tumor grade and AJCC stage) and outcomes (TTR and OS) using log-rank, generalized Wilcoxon, Cox proportional hazards regression, and Fisher exact tests.

RESULTS

Median TTR and OS were 53.9 and 79.7 months. ICC recurred in 64.4% (47/73) of patients and 46.6% (34/73) of patients died. There was fair accuracy for some qualitative imaging features in the prediction of worse tumor grade (maximal AUC of 0.68 for biliary obstruction on MRI, p = 0.032, observer 1) and higher AJCC stage (maximal AUC of 0.73 for biliary obstruction on CT, p = 0.002, observer 2; and AUC of 0.73 for vascular involvement on MRI, p = 0.01, observer 2). Cox proportional hazards regression analysis showed that CA 19-9 [hazard ratio (HR) 2.44/95% confidence interval (CI) 1.31-4.57/p = 0.005)] and tumor size on imaging (HR 1.13/95% CI 1.04-1.22/p = 0.003) were significant predictors of TTR, while CA 19-9 (HR 4.08/95% CI 1.75-9.56, p = 0.001) and presence of metastatic lymph nodes at histopathology (HR 2.86/95% CI 1.35-6.07/p = 0.006) were significant predictors of OS. On multivariable analysis, satellite lesions on CT (HR 2.79/95%CI 1.01-7.15/p = 0.032, observer 2), vascular involvement on MRI (HR 0.10/95% CI 0.01-0.85/p = 0.032, observer 1), and texture feature MRI variance (HR 0.55/95% CI 0.31-0.97, p = 0.040) predicted TTR once adjusted for the independent predictors CA 19-9 and tumor size on imaging. Several qualitative and quantitative features demonstrated associations with TTR, OS, and AJCC stage at univariable analysis (range: HR 0.35-19; p < 0.001-0.045), however none were predictive of OS at multivariable analysis when adjusted for CA 19-9 and metastatic lymph nodes (p > 0.088).

CONCLUSIONS

There was reasonable accuracy in predicting tumor grade and higher AJCC stage in ICC utilizing certain qualitative and quantitative imaging traits. Serum CA 19-9, tumor size, presence of metastatic lymph nodes, and qualitative imaging traits of satellite lesions and vascular involvement are predictors of patient outcomes, along with a promising predictive ability of certain quantitative texture features.

Prognostic prediction of apparent diffusion coefficient obtained by diffusion-weighted MRI in mass-forming intrahepatic cholangiocarcinoma

BACKGROUND

We evaluated apparent diffusion coefficient (ADC) of diffusion-weighted image MRI as a prognostic factor for mass-forming intrahepatic cholangiocarcinoma (IHCC).

METHODS

We enrolled 26 patients who had undergone hepatic resections for mass-forming-type IHCC in this study, and calculated their mean ADC, using diffusion-weighted image MRI (b: 0, 20, 800 seconds/mm² ; 1.5 T MRI). Patients were divided into the ADC^High and the ADC^Low groups at the median ADC value (n = 13 for both). We also immunohistochemically evaluated hypoxia-inducible factor (HIF)-1α in tumor tissue.

RESULTS

Median age in the ADC^Low was older (P = .03), and showed significant higher rate of scirrhous tumor (P = .02). The 5-year overall survival rate in the ADC^Low group was significantly worse than in the ADC^High group (P = .04). In multivariate analysis, hilar tumor, portal vein invasion and low ADC were independent prognostic factors (P < .05). The ADC^Low group also had a higher rate of high HIF-1α expression than the ADC^High group (P < .05). Representative case of ADC^Low group showed rich stroma and high HIF-1α expression.

CONCLUSIONS

The ADC values in MRIs can predict IHCC prognosis, and correlated with stromal density and HIF-1α expression.

Apparent diffusion coefficient value of mass-forming intrahepatic cholangiocarcinoma: a potential imaging biomarker for prediction of lymph node metastasis

PURPOSE

To compare the differences of MR features between mass-forming intrahepatic cholangiocarcinoma (IMCC) with and without lymph node metastasis (LNM) and to search for new imaging biomarkers for predicting LNM.

MATERIALS AND METHODS

The study included 91 patients with histopathologically confirmed single IMCC (20 patients with LNM and 71 patients without LNM). Findings of preoperative MR imaging including diffusion-weighted imaging (DWI) (b value 0, 500 mm²/s) were analyzed and apparent diffusion coefficient (ADC) values (b = 500 mm²/s) were calculated. Logistic regression analysis was performed to identify independent predictors of LNM. The diagnostic performance of independent predictors was assessed by receiver operating characteristic (ROC) and area under the curve (AUC) was compared.

RESULTS

Larger tumor size (p = 0.001), diameter of largest lymph node (LN) > 1 cm (p < 0.001), higher ADC value of primary IMCC lesion (ADC_IMCC value) (p = 0.001), and positive CA19-9 level (p = 0.018) were correlated with LNM. Multivariate logistic regression analysis demonstrated that ADC_IMCC value (odds ratio, 3.347; p = 0.001) and diameter of largest LN > 1 cm (odds ratio, 7.571; p = 0.004) were independent predictors of LNM. The AUCs for ADC_IMCC value, diameter of largest LN > 1 cm,and combined method (the combination of ADC_IMCC value and diameter of largest LN > 1 cm) were 0.782, 0.701,and 0.857, respectively. The AUC for combined method was significantly higher than that of diameter of largest LN > 1 cm (p = 0.033).

CONCLUSION

ADC_IMCC value can be a potential imaging biomarker for predicting LNM of IMCC, especially in combination with diameter of largest LN > 1 cm.

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Intrahepatic Carcinosarcoma With Cholangiocarcinoma Elements and Prominent Bile Duct Spread

Carcinosarcomas with elements of cholangiocarcinoma and sarcoma are rare and have a poor prognosis. The spreading pattern and radiological findings of these lesions remain unclear. A 74-year-old man presented with a high γ-glutamyl transferase level. Magnetic resonance imaging revealed dilation of the right intrahepatic and common bile ducts, consistent with an intraductal papillary neoplasm of the bile duct (IPNB), and diffusion-weighted imaging (DWI) indicated an area of high signal intensity in the intrahepatic bile duct. Bile duct biopsy yielded a small amount of atypical spindle cells, and the patient underwent a right hepatectomy. Microscopically, the tumor contained cholangiocarcinoma and sarcomatous components, including osteosarcoma and leiomyosarcoma, leading to a diagnosis of intrahepatic carcinosarcoma. The tumor spread primarily through the intrahepatic bile duct. An accurate radiological diagnosis of carcinosarcoma was challenging, given the apparent similarities with IPNB. The findings from DWI and pathology of a bile duct biopsy may assist with preoperative diagnosis.

Improving the Quality of Diffusion-weighted Imaging of the Left Hepatic Lobe Using Weighted Averaging of Signals from Multiple Excitations

Background:

Diffusion-weighted imaging (DWI) is useful for detecting and characterizing liver lesions but is sensitive to organ motion artifact, especially in the left lobe.

Purpose:

To assess the signal intensity (SI) loss in the left hepatic lobe on DWI depending on motion-proving gradient (MPG) pulse direction (preliminary study) and to evaluate the usefulness of modified signal averaging to reduce the SI loss on DWI (application study).

Methods:

About 48 (preliminary) and 35 (application) patients were included. In the preliminary study, DWI with four different MPG directions, only a single MPG pulse direction (x-, y-, or z-axis) and all three directions combined (standard DWI), were reconstructed from the original data. In the application study, we examined the usefulness of the weighted averaging number of excitations (wNEX) method, in which a larger weighting factor is applied to the higher signal in pixel-by-pixel NEX signal averaging by comparing four reconstruction methods. We assumed that true signals would be the same in both lobes. The SI and apparent diffusion coefficient (ADC) ratios for the left versus right lobe were calculated by dividing the SI/ADC of the right lobe by that of the left lobe.

Results:

In the preliminary study, the SI ratio was significantly lower on DWI using only the x-axis but was significantly higher on DWI using only the z-axis (both P < 0.0001) when compared with standard DWI. In the application study, the SI (mean, 1.15–1.17) and ADC (0.90–0.92) ratios on DWI with wNEX were closer to 1.0 than those on standard DWI (SI ratio, 1.32–1.38; ADC ratio 0.80–0.81); the differences were significant (all P < 0.0001).

Conclusion:

The MPG pulse along the z-axis caused signal loss in the left hepatic lobe. The wNEX reconstruction method effectively reduced signal loss in the left lobe on DWI.

DWI of Pancreatic Ductal Adenocarcinoma: A Pilot Study to Estimate the Correlation With Metastatic Disease Potential and Overall Survival

OBJECTIVE

The purpose of this study is to analyze the relationship between the apparent diffusion coefficient (ADC) of pancreatic ductal adenocarcinoma (PDAC) and the presence or development of metastasis and overall survival (OS).

MATERIALS AND METHODS

Of 290 consecutive patients with histopathologically proven PDAC from January 2013 to December 2014, staging DWI was performed for 124 patients. Image quality was adequate in 112 studies. Sixty-five patients were treatment naïve, but 17 of the 65 were excluded because of the presence of other associated pancreatic pathologic abnormalities. Data for the remaining 48 patients (24 men and 24 women; median age, 65.5 years; interquartile range, 56-77 years) were obtained during a 4-year follow-up period (mean [± SD], 397 ± 415.1 days). The correlation between ADC and the presence or development of metastasis was assessed using descriptive statistics. OS was determined and mortality analysis was performed using Pearson correlation and Kaplan-Meier curves.

RESULTS

Of 48 patients, 10 had metastases at staging MRI, and 12 later developed metastatic disease. Among the latter, the mean time from staging MRI to metastasis was 258 ± 274.1 days. Most (86%) metastases were hepatic (n = 19). During the follow-up period, the remaining 26 patients (54%) never developed metastases. Patients with metastatic disease (n = 22) had significantly lower mean ADCs than did those without metastases (1.27 × 10^-3 vs 1.43 × 10^-3 mm²/s; p = 0.047). The ADC of PDAC had a positive correlation with survival: patients with PDAC with lower ADCs (< 1.36 × 10^-3 mm²/s) had significantly worse 4-year OS rates than did patients with higher ADC values (p = 0.036).

CONCLUSION

Pretreatment ADC values of PDAC may be significantly lower in patients who have or will develop metastatic disease and may correlate with worse OS.

Primary intrahepatic cholangiocarcinoma with sarcomatous stroma: case report and review of the literature

Background

Hepatic carcinosarcomas, which include both carcinomatous and sarcomatous elements, are uncommon in adults. Although carcinosarcoma in hepatocellular carcinoma is occasionally reported, carcinosarcoma in intrahepatic cholangiocarcinoma (ICC) is an extremely rare ICC variant. Few such cases have been reported in English and no large study of its clinicopathological features exists.

Case presentation

Here, we report a 60-year-old man with an asymptomatic hepatic B infection who developed hepatic carcinosarcoma from an otherwise normal liver. The 6.0-cm tumor was accidentally discovered by PET-CT in a cancer examination. Serum examinations showed no elevation of tumor markers. He underwent left and caudate lobectomy of the liver. The diagnosis of intrahepatic cholangiocarcinoma with sarcomatous stroma was based on thorough pathologic examination and immunohistochemical staining. The tumor exhibited adenocarcinomatous and sarcomatous components; the adenocarcinomatous element was positive for epithelial markers, the sarcomatous element was positive for mesenchymal markers, but negative for epithelial markers. The patient made an uneventful recovery after surgery. At present, 14 months after surgery, he remains well with no evidence of tumor recurrence.

Conclusions

We report an unusual case of hepatic carcinosarcoma (intrahepatic cholangiocarcinoma with sarcomatous stroma) and discuss the etiology and prognosis of this rare disease.

Mass-forming intrahepatic cholangiocarcinoma: Can diffusion-weighted imaging predict microvascular invasion?

BACKGROUND

Microvascular invasion (MVI) is a risk factor influencing the survival rate of patients with mass-forming intrahepatic cholangiocarcinoma (IMCC).

PURPOSE

To investigate whether diffusion-weighted imaging (DWI) could be useful in predicting MVI of IMCC.

STUDY TYPE

Retrospective.

SUBJECTS

Eighty patients with surgically resected single IMCC (21 MVI-positive lesions and 59 MVI-negative lesions).

FIELD STRENGTH/SEQUENCE

Preoperative hepatic MRI (1.5T), including T₁ - and T₂ -weighted images (T₁ WI, T₂ WI), DWI, and dynamic enhancement imaging.

ASSESSMENT

Morphologic characteristics including contour of the lesion, biliary dilation and hepatic capsule retraction, signal features on T₁ WI, T₂ WI, and DWI, and dynamic enhancement patterns were qualitatively evaluated. The quantitative analysis was performed for the size and apparent diffusion coefficient (ADC) values.

STATISTICAL TESTS

Chi-square test, Fisher's exact test, and the independent t-test were used for univariate analysis to determine the relationships between these radiological parameters and the presence of MVI. Logistic regression analysis was used to identify the independent predictors of MVI among these radiological parameters. Receiver operating characteristic curve analysis was performed to evaluate their diagnostic performance.

RESULTS

Larger tumor size (P = 0.006) and higher ADC values (P < 0.001) were positively correlated with MVI. Multivariate logistic regression analysis demonstrated that the ADC value (odds ratio, 3.099; P = 0.001) was an independent predictor for MVI of IMCC. The ADC value for MVI of IMCC showed an area under the receiver operating characteristic curve of 0.782 (optimal cutoff value was 1.59 × 10^-3 mm² /s).

DATA CONCLUSION

Larger tumor size was associated with MVI and higher ADC values can be a useful predictor of MVI during the preoperative evaluation of IMCC.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:315-324.