Todd Schlachter

Human bile contains MicroRNA‐laden extracellular vesicles that can be used for cholangiocarcinoma diagnosis

Cholangiocarcinoma (CCA) presents significant diagnostic challenges, resulting in late patient diagnosis and poor survival rates. Primary sclerosing cholangitis (PSC) patients pose a particularly difficult clinical dilemma because they harbor chronic biliary strictures that are difficult to distinguish from CCA. MicroRNAs (miRs) have recently emerged as a valuable class of diagnostic markers; however, thus far, neither extracellular vesicles (EVs) nor miRs within EVs have been investigated in human bile. We aimed to comprehensively characterize human biliary EVs, including their miR content. We have established the presence of extracellular vesicles in human bile. In addition, we have demonstrated that human biliary EVs contain abundant miR species, which are stable and therefore amenable to the development of disease marker panels. Furthermore, we have characterized the protein content, size, numbers, and size distribution of human biliary EVs. Utilizing multivariate organization of combinatorial alterations (MOCA), we defined a novel biliary vesicle miR‐based panel for CCA diagnosis that demonstrated a sensitivity of 67% and specificity of 96%. Importantly, our control group contained 13 PSC patients, 16 with biliary obstruction of varying etiologies (including benign biliary stricture, papillary stenosis, choledocholithiasis, extrinsic compression from pancreatic cysts, and cholangitis), and 3 with bile leak syndromes. Clinically, these types of patients present with a biliary obstructive clinical picture that could be confused with CCA. Conclusion: These findings establish the importance of using extracellular vesicles, rather than whole bile, for developing miR‐based disease markers in bile. Finally, we report on the development of a novel bile‐based CCA diagnostic panel that is stable, reproducible, and has potential clinical utility. (Hepatology 2014;60:896–907)

A Novel Inherently Radiopaque Bead for Transarterial Embolization to Treat Liver Cancer - A Pre-clinical Study

Purpose: Embolotherapy using microshperes is currently performed with soluble contrast to aid in visualization. However, administered payload visibility dimishes soon after delivery due to soluble contrast washout, leaving the radiolucent beads location unknown. The objective of our study was to characterize inherently radiopaque beads (RO Beads) in terms of physicomechanical properties, deliverability and imaging visibility in a rabbit VX2 liver tumor model. Materials and Methods: RO Beads, which are based on LC Bead® platform, were compared to LC Bead. Bead size (light microscopy), equilibrium water content (EWC), density, X-ray attenuation and iodine distribution (micro-CT), suspension (settling times), deliverability and in vitro penetration were investigated. Fifteen rabbits were embolized with either LC Bead or RO Beads + soluble contrast (iodixanol-320), or RO Beads+dextrose. Appearance was evaluated with fluoroscopy, X-ray single shot, cone-beam CT (CBCT). Results: Both bead types had a similar size distribution. RO Beads had lower EWC (60-72%) and higher density (1.21-1.36 g/cc) with a homogeneous iodine distribution within the beads interior. RO Beads suspension time was shorter than LC Bead, with durable suspension (>5 min) in 100% iodixanol. RO Beads ≤300 µm were deliverable through a 2.3-Fr microcatheter. Both bead types showed similar penetration. Soluble contrast could identify target and non-target embolization on fluoroscopy during administration. However, the imaging appearance vanished quickly for LC Bead as contrast washed-out. RO Beads+contrast significantly increased visibility on X-ray single shot compared to LC Bead+contrast in target and non-target arteries (P=0.0043). Similarly, RO beads demonstrated better visibility on CBCT in target arteries (P=0.0238) with a trend in non-target arteries (P=0.0519). RO Beads+dextrose were not sufficiently visible to monitor embolization using fluoroscopy. Conclusion: RO Beads provide better conspicuity to determine target and non-target embolization compared to LC Bead which may improve intra-procedural monitoring and post-procedural evaluation of transarterial embolization.

Uveal Melanoma Metastatic to the Liver: The Role of Quantitative Volumetric Contrast-Enhanced MR Imaging in the Assessment of Early Tumor Response after Transarterial Chemoembolization

PURPOSE To determine whether volumetric changes of enhancement as seen on contrast-enhanced magnetic resonance (MR) imaging can help assess early tumor response and predict survival in patients with metastatic uveal melanoma after one session of transarterial chemoembolization (TACE). MATERIALS AND METHODS Fifteen patients with 59 lesions who underwent MR imaging before and 3 to 4 weeks after the first TACE were retrospectively included. MR analysis evaluated signal intensities, World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), European Association for the Study of the Liver (EASL), modified RECIST (mRECIST), tumor volume [volumetric RECIST (vRECIST)], and volumetric tumor enhancement [quantitative EASL (qEASL)]. qEASL was expressed in cubic centimeters [qEASL (cm3)] and as a percentage of the tumor volume [qEASL (%)]. Paired t test with its exact permutation distribution was used to compare measurements before and after TACE. The Kaplan-Meier method with the log-rank test was used to calculate overall survival for responders and non-responders. RESULTS In target lesions, mean qEASL (%) decreased from 63.9% to 42.6% (P = .016). No significant changes were observed using the other response criteria. In non-target lesions, mean WHO, RECIST, EASL, mRECIST, vRECIST, and qEASL (cm3) were significantly increased compared to baseline. qEASL (%) remained stable (P = .214). Median overall survival was 5.6 months. qEASL (cm3) was the only parameter that could predict survival based on target lesions (3.6 vs 40.5 months, P < .001) or overall (target and non-target lesions) response (4.4 vs 40.9 months, P = .001). CONCLUSION Volumetric tumor enhancement may be used as a surrogate biomarker for survival prediction in patients with uveal melanoma after the first TACE.

Transarterial chemoembolization in soft-tissue sarcoma metastases to the liver – The use of imaging biomarkers as predictors of patient survival

BACKGROUND The clinical management of patients with metastatic soft-tissue sarcoma of the liver is complicated by the paucity of reliable clinical data. This study evaluated the safety profile, survival outcome as well as the role of imaging biomarkers of tumor response in metastatic soft-tissue sarcoma (mSTS) of the liver treated with conventional transarterial chemoembolization (cTACE). MATERIALS/METHODS This retrospective analysis included 30 patients with mSTS of the liver treated with cTACE. The safety profile, overall survival (OS) and progression-free survival (PFS) after the procedure were evaluated. Tumor response in each patient was assessed using RECIST, modified (m) RECIST and EASL guidelines. In addition, a 3D quantification of the enhancing tumor volume (quantitative [q] EASL) was performed. For each method, patients were classified as responders (R) and non-responders (NR), and evaluated using Kaplan-Meier and multivariate Cox proportional hazard ratio (HR) analysis. RESULTS No Grade III or IV toxicities were reported in a total of 77 procedures (mean, 2.6/patient). Median OS was 21.2 months (95% CI, 13.4-28.9) and PFS was 6.3 months (95% CI, 4.4-8.2). The enhancement-based techniques identified 11 (44%), 12 (48%) and 12 (48%) patients as R according to EASL, mRECIST and qEASL, respectively. No stratification was achieved with RECIST. Multivariate analysis identified tumor response according to mRECIST and qEASL as reliable predictors of improved patient survival (P=0.019; HR 0.3 [0.1-0.8] and P=0.006; HR 0.2 [0.1-0.6], respectively). CONCLUSION This study confirmed the role of cTACE as a safe salvage therapy option in patients with mSTS of the liver. The demonstrated advantages of enhancement-based tumor response assessment techniques over size-based criteria validate mRECIST and qEASL as preferable methods after intraarterial therapy.

Percutaneous Transhepatic Cholangioscopy

The role of the interventional radiologist continues to expand in the treatment of biliary disease. Percutaneous transhepatic cholangioscopy (PTCS) provides direct visualization of the biliary system for diagnostic and therapeutic interventions, especially in cases where anatomical considerations prohibit a peroral approach. Visual inspection and endoscopically guided biopsy allow differentiation between benign and malignant lesions, as well as accurate assessment of the tumor extent for surgical planning. Studies have demonstrated greater than 95% accuracy with PTCS in diagnosing biliary malignancies. Cholangioscopy is also used to treat obstructive stones in the biliary system, which may require laser lithotripsy. PTCS-guided removal of biliary stones is highly successful, with complete stone removal from the bile ducts occurring in approximately 90% of cases. Overall, PTCS is a safe and effective procedure, with severe complications occurring in less than 8% of patients. The purpose of this review is to familiarize its reader with common indications for PTCS, techniques for procedural success, expected outcomes, and management of potential complications.

Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning—An Artificial Intelligence Concept

PURPOSE To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques. MATERIALS AND METHODS This study included 36 patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization. The cohort (age 62 ± 8.9 years; 31 men; 13 white; 24 Eastern Cooperative Oncology Group performance status 0, 10 status 1, 2 status 2; 31 Child-Pugh stage A, 4 stage B, 1 stage C; 1 Barcelona Clinic Liver Cancer stage 0, 12 stage A, 10 stage B, 13 stage C; tumor size 5.2 ± 3.0 cm; number of tumors 2.6 ± 1.1; and 30 conventional transarterial chemoembolization, 6 with drug-eluting embolic agents). MR imaging was obtained before and 1 month after transarterial chemoembolization. Image-based tumor response to transarterial chemoembolization was assessed with the use of the 3D quantitative European Association for the Study of the Liver (qEASL) criterion. Clinical information, baseline imaging, and therapeutic features were used to train logistic regression (LR) and random forest (RF) models to predict patients as treatment responders or nonresponders under the qEASL response criterion. The performance of each model was validated using leave-one-out cross-validation. RESULTS Both LR and RF models predicted transarterial chemoembolization treatment response with an overall accuracy of 78% (sensitivity 62.5%, specificity 82.1%, positive predictive value 50.0%, negative predictive value 88.5%). The strongest predictors of treatment response included a clinical variable (presence of cirrhosis) and an imaging variable (relative tumor signal intensity >27.0). CONCLUSIONS Transarterial chemoembolization outcomes in patients with HCC may be predicted before procedures by combining clinical patient data and baseline MR imaging with the use of AI and ML techniques.

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. The objective of this study was to develop a method to predict response to intra-arterial treatment prior to intervention. The method provides a general framework for predicting outcomes prior to intra-arterial therapy. It involves pooling clinical, demographic and imaging data across a cohort of patients and using these data to train a machine learning model. The trained model is applied to new patients in order to predict their likelihood of response to intra-arterial therapy. The method entails the acquisition and parsing of clinical, demographic and imaging data from N patients who have already undergone trans-arterial therapies. These data are parsed into discrete features (age, sex, cirrhosis, degree of tumor enhancement, etc.) and binarized into true/false values (e.g., age over 60, male gender, tumor enhancement beyond a set threshold, etc.). Low-variance features and features with low univariate associations with the outcome are removed. Each treated patient is labeled according to whether they responded or did not respond to treatment. Each training patient is thus represented by a set of binary features and an outcome label. Machine learning models are trained using N - 1 patients with testing on the left-out patient. This process is repeated for each of the N patients. The N models are averaged to arrive at a final model. The technique is extensible and enables inclusion of additional features in the future. It is also a generalizable process that may be applied to clinical research questions outside of interventional radiology. The main limitation is the need to derive features manually from each patient. A popular modern form of machine learning called deep learning does not suffer from this limitation, but requires larger datasets.

Irinotecan-Eluting 75–150-μm Embolics Lobar Chemoembolization in Patients with Colorectal Cancer Liver Metastases: A Prospective Single-Center Phase I Study

PURPOSE The primary end point of this trial was to determine the feasibility and safety of transarterial chemoembolization with the use of 75-150-μm drug-eluting embolics loaded with irinotecan (DEE-IRI) for the treatment of metastatic colorectal cancer (CRC) refractory to systemic chemotherapy. MATERIALS AND METHODS Fourteen patients (mean age 57.9 years) with liver-dominant metastatic disease (14.3% unilobar, 85.7% bilobar), who had failed at least 1 line of chemotherapy, were enrolled and received up to 4 (mean 2.3) cycles of DEE-IRI lobar transarterial chemoembolization. Technical complications and adverse events were recorded, and response was assessed by means of imaging-based criteria. Levels of irinotecan and angiogenesis biomarkers in the serum were measured at multiple time points. RESULTS Thirty-two DEE-IRI transarterial chemoembolizations were successfully performed, and the full dose (100 mg) was delivered in all cases. The only grade 3-4 toxicity was abdominal pain (29%). One patient had objective response according to the Response Evaluation Criteria in Solid Tumors and World Health Organization, and 3 patients had objective response according to the European Association for the Study of the Liver. The median overall survival was 18.14 months, and the 1-year survival was 65%. The average plasma Cmax of the active metabolite was 41.5 ± 26.1 ng/mL, with average Tmax of 1.3 ± 0.5 hours. The treatment significantly reduced levels of vascular endothelial growth factor receptor 1 (VEGFR1) at 24 hours. CONCLUSIONS Lobar transarterial chemoembolization with the use of DEE-IRI is a technically feasible and well tolerated palliative treatment for patients with refractory liver-predominant CRC metastatic disease and has acceptable pharmacokinetics. VEGFR1 is a potential biomarker for predicting treatment efficacy and risk of adverse events.