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Purpose: To characterize the effects of commonly used transcatheter arterial chemoembolization (TACE) regimens on the immune response and immune checkpoint marker expression using a VX2 rabbit liver tumor model., Materials and Methods: Twenty-four VX2 liver tumor-bearing New Zealand white rabbits were assigned to 7 groups (n = 3 per group) undergoing locoregional therapy as follows: (a) bicarbonate infusion without embolization, (b) conventional TACE (cTACE) using a water-in-oil emulsion containing doxorubicin mixed 1:2 with Lipiodol, drug-eluting embolic-TACE with either (c) idarubicin-eluting Oncozene microspheres (40 μm) or (d) doxorubicin-eluting Lumi beads (40-90 μm). For each therapy arm (b-d), a tandem set of 3 animals with additional bicarbonate infusion before TACE was added, to evaluate the effect of pH modification on the immune response. Three untreated rabbits served as controls. Tissue was harvested 24 hours after treatment, followed by digital immunohistochemistry quantification (counts/μm 2 ± SEM) of tumor-infiltrating cluster of differentiation 3 + T-lymphocytes, human leukocyte antigen DR type antigen-presenting cells (APCs), cytotoxic T-lymphocyte-associated protein-4 (CTLA-4), and programmed cell death protein-1 (PD-1)/PD-1 ligand (PD-L1) pathway axis expression., Results: Lumi-bead TACE induced significantly more intratumoral T-cell and APC infiltration than cTACE and Oncozene-microsphere TACE. Additionally, tumors treated with Lumi-bead TACE expressed significantly higher intratumoral immune checkpoint markers compared with cTACE and Oncozene-microsphere TACE. Neoadjuvant bicarbonate demonstrated the most pronounced effect on cTACE and resulted in a significant increase in intratumoral cluster of differentiation 3 + T-cell infiltration compared with cTACE alone., Conclusions: This preclinical study revealed significant differences in evoked tumor immunogenicity depending on the choice of chemoembolic regimen for TACE., (Copyright © 2022 SIR. Published by Elsevier Inc. All rights reserved.)

PURPOSE Patients with acute calculus cholecystitis and contraindications to cholecystectomy receive cholecystostomy drainage catheters, many of which remain in place until end of life. This study aims to assess safety, feasibility, and early clinical outcomes of percutaneous cholecystoscopy using the LithoVue endoscope, laser/mechanical cholelithotripsy, and mechanical cholelithotomy for management of symptomatic cholelithiasis. METHODS This was a single-institute retrospective analysis of 17 patients with acute calculus cholecystitis who had contraindications to cholecystectomy, underwent cholecystostomy catheter placement between 2015 and 2017, and stone removal between 2017 and 2018. The LithoVue 7.7- 9.5 F endoscope was used in combination with laser/mechanical cholelithotripsy, mechanical retrograde, and balloon-assisted anterograde cholelithotomy to remove gallstones and common bile duct stones. Surgical contraindications ranged from cardiopulmonary disease to morbid obesity to neoplastic processes. Timing and number of interventions, as well as technical and clinical successes, were assessed. RESULTS The median time interval from cholecystostomy catheter placement to cholelithotripsy was 58 days, after an average of 2 tube exchange procedures. Technical and clinical success were achieved in all patients (stone-free gallbladder and cholecystostomy tube removal). On average, three sessions of cholecystoscopy and laser and mechanical cholelithotripsy were required for complete gallstone extraction. The mean interval time between the first cholelithotripsy session and removal of cholecystostomy was 71.8±60.8 days. There were neither major nor minor procedure-related complications. CONCLUSION Percutaneous cholecystoscopy using the LithoVue endoscope, in combination with laser/ mechanical cholelithotripsy and mechanical cholelithotomy, is feasible, safe, well-tolerated, and was able to remove the cholecystostomy tube in the patients with contraindication to cholecystectomy.

Objectives: The goal of this study was to investigate the effects of TACE using Lipiodol, Oncozene™ drug-eluting embolics (DEEs), or LUMI™-DEEs alone, or combined with bicarbonate on the metabolic and immunological tumor microenvironment in a rabbit VX2 tumor model., Methods: VX2 liver tumor-bearing rabbits were assigned to five groups. MRI and extracellular pH (pH e ) mapping using Biosensor Imaging of Redundant Deviation in Shifts (BIRDS) were performed before and after intra-arterial therapy with conventional TACE (cTACE), DEE-TACE with Idarubicin-eluting Oncozene™-DEEs, or Doxorubicin-eluting LUMI™-DEEs, each with or without prior bicarbonate infusion, and in untreated rabbits or treated with intra-arterial bicarbonate only. Imaging results were validated with immunohistochemistry (IHC) staining of cell viability (PCNA, TUNEL) and immune response (HLA-DR, CD3). Statistical analysis was performed using Mann-Whitney U test., Results: pH e mapping revealed that combining cTACE with prior bicarbonate infusion significantly increased tumor pH e compared to control (p = 0.0175) and cTACE alone (p = 0.0025). IHC staining revealed peritumoral accumulation of HLA-DR + antigen-presenting cells and CD3 + T-lymphocytes in controls. cTACE-treated tumors showed reduced immune infiltration, which was restored through combination with bicarbonate. DEE-TACE with Oncozene™-DEEs induced moderate intratumoral and marked peritumoral infiltration, which was slightly reduced with bicarbonate. Addition of bicarbonate prior to LUMI™-beads enhanced peritumoral immune cell infiltration compared to LUMI™-beads alone and resulted in the strongest intratumoral immune cell infiltration across all treated groups., Conclusions: The choice of chemoembolic regimen for TACE strongly affects post-treatment TME pH e and the ability of immune cells to accumulate and infiltrate the tumor tissue., Key Points: • Combining conventional transarterial chemotherapy with prior bicarbonate infusion increases the pH e towards a more physiological value (p = 0.0025). • Peritumoral infiltration and intratumoral accumulation patterns of antigen-presenting cells and T-lymphocytes after transarterial chemotherapy were dependent on the choice of the chemoembolic regimen. • Combination of intra-arterial treatment with Doxorubicin-eluting LUMI™-beads and bicarbonate infusion resulted in the strongest intratumoral presence of immune cells (positivity index of 0.47 for HLADR + -cells and 0.62 for CD3 + -cells)., (© 2021. European Society of Radiology.)

The spontaneous rupture of pulmonary AVMs, resulting in pulmonary hemorrhage and hydrothorax, is a life-threatening complication. While this phenomenon has been previously reported, the true incidence is not yet known. This study retrospectively reviewed records of 801 HHT patients with pulmonary AVMs to identify a single lifetime episode of hemothorax or pulmonary hemorrhage secondary to pulmonary AVM rupture. The lifetime prevalence and incidence of pulmonary AVM rupture in HHT patients was 2.7% and 0.16% respectively. In these patients, AVM rupture represented the initial presentation of HHT in nine (40.9%) cases and was life-threatening in nine (40.9%) cases. All cases occurred in virgin lesions, and subsequent embolization was curative. While a feared complication, pulmonary AVM rupture is rare and is likely effectively prevented by existing embolization techniques and indications.

Purpose: Thermal ablation (TA) and transarterial chemoembolization (TACE) may be used alone or in combination (TACE+TA) for the treatment of hepatocellular carcinoma (HCC). The aim of our study was to compare the time to tumor progression (TTP) and overall survival (OS) for patients who received TA alone or TACE+TA for HCC tumors under 3 cm., Materials and Methods: This HIPAA-compliant IRB-approved retrospective analysis included 85 therapy-naïve patients from 2010 to 2018 (63 males, 22 females, mean age 62.4 ± 8.5 years) who underwent either TA alone (n = 64) or TA in combination with drug-eluting beads (DEB)-TACE (n = 18) or Lipiodol-TACE (n = 3) for locoregional therapy of early stage HCC with maximum tumor diameter under 3 cm. Kaplan-Meier analysis was performed using the log-rank test to assess TTP and OS., Results: All TA and TACE+TA treatments included were technically successful. TTP was 23.0 months in the TA group and 22.0 months in the TACE+TA group. There was no statistically significant difference in TTP (p = 0.64). Median OS was 69.7 months in the TA group and 64.6 months in the TACE+TA group. There was no statistically significant difference in OS (p = 0.14). The treatment cohorts had differences in AFP levels (p = 0.03) and BCLC stage (p = 0.047). Complication rates between patient groups were similar (p = 0.61)., Conclusion: For patients with HCC under 3 cm, TA alone and TACE+TA have similar outcomes in terms of TTP and OS, suggesting that TACE+TA may not be needed for these tumors unless warranted by tumor location or other technical consideration., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Objectives: To train a deep learning model to differentiate between pathologically proven hepatocellular carcinoma (HCC) and non-HCC lesions including lesions with atypical imaging features on MRI., Methods: This IRB-approved retrospective study included 118 patients with 150 lesions (93 (62%) HCC and 57 (38%) non-HCC) pathologically confirmed through biopsies (n = 72), resections (n = 29), liver transplants (n = 46), and autopsies (n = 3). Forty-seven percent of HCC lesions showed atypical imaging features (not meeting Liver Imaging Reporting and Data System [LI-RADS] criteria for definitive HCC/LR5). A 3D convolutional neural network (CNN) was trained on 140 lesions and tested for its ability to classify the 10 remaining lesions (5 HCC/5 non-HCC). Performance of the model was averaged over 150 runs with random sub-sampling to provide class-balanced test sets. A lesion grading system was developed to demonstrate the similarity between atypical HCC and non-HCC lesions prone to misclassification by the CNN., Results: The CNN demonstrated an overall accuracy of 87.3%. Sensitivities/specificities for HCC and non-HCC lesions were 92.7%/82.0% and 82.0%/92.7%, respectively. The area under the receiver operating curve was 0.912. CNN's performance was correlated with the lesion grading system, becoming less accurate the more atypical imaging features the lesions showed., Conclusion: This study provides proof-of-concept for CNN-based classification of both typical- and atypical-appearing HCC lesions on multi-phasic MRI, utilizing pathologically confirmed lesions as "ground truth.", Key Points: • A CNN trained on atypical appearing pathologically proven HCC lesions not meeting LI-RADS criteria for definitive HCC (LR5) can correctly differentiate HCC lesions from other liver malignancies, potentially expanding the role of image-based diagnosis in primary liver cancer with atypical features. • The trained CNN demonstrated an overall accuracy of 87.3% and a computational time of < 3 ms which paves the way for clinical application as a decision support instrument.

Objectives: To compare 1D and 3D quantitative tumor response criteria applied to DCE-MRI in patients with advanced-stage HCC undergoing sorafenib therapy to predict overall survival (OS) early during treatment., Methods: This retrospective analysis included 29 patients with advanced-stage HCC who received sorafenib for at least 60 days. All patients underwent baseline and follow-up DCE-MRI at 81.5 ± 29.3 days (range 35-140 days). Response to sorafenib was assessed in 46 target lesions using 1D criteria RECIST1.1 and mRECIST. In addition, a segmentation-based 3D quantification of absolute enhancing lesion volume (vqEASL) was performed on the arterial phase MRI, and the enhancement fraction of total tumor volume (%qEASL) was calculated. Accordingly, patients were stratified into groups of disease control (DC) and disease progression (DP). OS was evaluated using Kaplan-Meier curves with log-rank test and Cox proportional hazards regression model., Results: The Kaplan-Meier analysis revealed that stratification of patients in DC vs. DP according to mRECIST (p = 0.0371) and vqEASL (p = 0.0118) successfully captured response and stratified OS, while stratification according to RECIST and %qEASL did not correlate with OS (p = 0.6273 and p = 0.7474, respectively). Multivariable Cox regression identified tumor progression according to mRECIST and qEASL as independent risk factors of decreased OS (p = 0.039 and p = 0.006, respectively)., Conclusions: The study identified enhancement-based vqEASL and mRECIST as reliable predictors of patient survival early after initiation of treatment with sorafenib. This data provides evidence for potential advantages 3D quantitative, enhancement-based tumor response analysis over conventional techniques regarding early identification of treatment success or failure., Key Points: • Tumor response criteria on MRI can be used to predict survival benefit of sorafenib therapy in patients with advanced HCC. • Stratification into DC and DP using mRECIST and vqEASL significantly correlates with OS (p = 0.0371 and p = 0.0118, respectively) early after initiation of sorafenib, while stratification according to RECIST and %qEASL did not correlate with OS (p = 0.6273 and p = 0.7474, respectively). • mRECIST (HR = 0.325, p = 0.039. 95%CI 0.112-0.946) and qEASL (HR = 0.183, p = 0.006, 95%CI 0.055-0.613) are independent prognostic factors of survival in HCC patients undergoing sorafenib therapy.

Objectives: To evaluate the prognostic potential of Lipiodol distribution for the pharmacokinetic (PK) profiles of doxorubicin (DOX) and doxorubicinol (DOXOL) after conventional transarterial chemoembolization (cTACE)., Methods: This prospective clinical trial ( ClinicalTrials.gov : NCT02753881) included 30 consecutive participants with liver malignancies treated with cTACE (5/2016-10/2018) using 50 mg DOX/10 mg mitomycin C emulsified 1:2 with ethiodized oil (Lipiodol). Peripheral blood was sampled at 10 timepoints for standard non-compartmental analysis of peak concentrations (C max ) and area under the curve (AUC) with dose normalization (DN). Imaging markers included Lipiodol distribution on post-cTACE CT for patient stratification into 1 segment (n = 10), ≥ 2 segments (n = 10), and lobar cTACE (n = 10), and baseline enhancing tumor volume (ETV). Adverse events (AEs) and tumor response on MRI were recorded 3-4 weeks post-cTACE. Statistics included repeated measurement ANOVA (RM-ANOVA), Mann-Whitney, Kruskal-Wallis, Fisher's exact test, and Pearson correlation., Results: Hepatocellular (n = 26), cholangiocarcinoma (n = 1), and neuroendocrine metastases (n = 3) were included. Stratified according to Lipiodol distribution, DOX-C max increased from 1 segment (DOX-C max , 83.94 ± 75.09 ng/mL; DN-DOX-C max , 2.67 ± 2.02 ng/mL/mg) to ≥ 2 segments (DOX-C max , 139.66 ± 117.73 ng/mL; DN-DOX-C max , 3.68 ± 4.20 ng/mL/mg) to lobar distribution (DOX-C max , 334.35 ± 215.18 ng/mL; DN-DOX-C max , 7.11 ± 4.24 ng/mL/mg; p = 0.036). While differences in DN-DOX-AUC remained insignificant, RM-ANOVA revealed significant separation of time concentration curves for DOX (p = 0.023) and DOXOL (p = 0.041) comparing 1, ≥ 2 segments, and lobar cTACE. Additional indicators of higher DN-DOX-C max were high ETV (p = 0.047) and Child-Pugh B (p = 0.009). High ETV and tumoral Lipiodol coverage also correlated with tumor response. AE occurred less frequently after segmental cTACE., Conclusions: This prospective clinical trial provides updated PK data revealing Lipiodol distribution as an imaging marker predictive of DOX-C max and tumor response after cTACE in liver cancer., Key Points: • Prospective pharmacokinetic analysis after conventional TACE revealed Lipiodol distribution (1 vs. ≥ 2 segments vs. lobar) as an imaging marker predictive of doxorubicin peak concentrations (C max ). • Child-Pugh B class and tumor hypervascularization, measurable as enhancing tumor volume (ETV) at baseline, were identified as additional predictors for higher dose-normalized doxorubicin C max after conventional TACE. • ETV at baseline and tumoral Lipiodol coverage can serve as predictors of volumetric tumor response after conventional TACE according to quantitative European Association for the Study of the Liver (qEASL) criteria.

Purpose: Liver Imaging Reporting and Data System (LI-RADS) uses multiphasic contrast-enhanced imaging for hepatocellular carcinoma (HCC) diagnosis. The goal of this feasibility study was to establish a proof-of-principle concept towards automating the application of LI-RADS, using a deep learning algorithm trained to segment the liver and delineate HCCs on MRI automatically., Methods: In this retrospective single-center study, multiphasic contrast-enhanced MRIs using T1-weighted breath-hold sequences acquired from 2010 to 2018 were used to train a deep convolutional neural network (DCNN) with a U-Net architecture. The U-Net was trained (using 70% of all data), validated (15%) and tested (15%) on 174 patients with 231 lesions. Manual 3D segmentations of the liver and HCC were ground truth. The dice similarity coefficient (DSC) was measured between manual and DCNN methods. Postprocessing using a random forest (RF) classifier employing radiomic features and thresholding (TR) of the mean neural activation was used to reduce the average false positive rate (AFPR)., Results: 73 and 75% of HCCs were detected on validation and test sets, respectively, using > 0.2 DSC criterion between individual lesions and their corresponding segmentations. Validation set AFPRs were 2.81, 0.77, 0.85 for U-Net, U-Net + RF, and U-Net + TR, respectively. Combining both RF and TR with the U-Net improved the AFPR to 0.62 and 0.75 for the validation and test sets, respectively. Mean DSC between automatically detected lesions using the DCNN + RF + TR and corresponding manual segmentations was 0.64/0.68 (validation/test), and 0.91/0.91 for liver segmentations., Conclusion: Our DCNN approach can segment the liver and HCCs automatically. This could enable a more workflow efficient and clinically realistic implementation of LI-RADS.

Conventional transarterial chemoembolization (cTACE) is a guideline-approved image-guided therapy option for liver cancer using the radiopaque drug-carrier and micro-embolic agent Lipiodol, which has been previously established as an imaging biomarker for tumor response. To establish automated quantitative and pattern-based image analysis techniques of Lipiodol deposition on 24 h post-cTACE CT as biomarker for treatment response. The density of Lipiodol deposits in 65 liver lesions was automatically quantified using Hounsfield Unit thresholds. Lipiodol deposition within the tumor was automatically assessed for patterns including homogeneity, sparsity, rim, and peripheral deposition. Lipiodol deposition was correlated with enhancing tumor volume (ETV) on baseline and follow-up MRI. ETV on baseline MRI strongly correlated with Lipiodol deposition on 24 h CT (p < 0.0001), with 8.22% ± 14.59 more Lipiodol in viable than necrotic tumor areas. On follow-up, tumor regions with Lipiodol showed higher rates of ETV reduction than areas without Lipiodol (p = 0.0475) and increasing densities of Lipiodol enhanced this effect. Also, homogeneous (p = 0.0006), non-sparse (p < 0.0001), rim deposition within sparse tumors (p = 0.045), and peripheral deposition (p < 0.0001) of Lipiodol showed improved response. This technical innovation study showed that an automated threshold-based volumetric feature characterization of Lipiodol deposits is feasible and enables practical use of Lipiodol as imaging biomarker for therapeutic efficacy after cTACE.

Purpose: To investigate toxicity, efficacy, and microenvironmental effects of idarubicin-loaded 40-μm and 100-μm drug-eluting embolic (DEE) transarterial chemoembolization in a rabbit liver tumor model., Materials and Methods: Twelve male New Zealand White rabbits with orthotopically implanted VX2 liver tumors were assigned to DEE chemoembolization with 40-μm (n = 5) or 100-μm (n = 4) ONCOZENE microspheres or no treatment (control; n = 3). At 24-72 hours postprocedurally, multiparametric magnetic resonance (MR) imaging including dynamic contrast-enhanced (DCE), diffusion-weighted imaging (DWI), and biosensor imaging of redundant deviation in shifts (BIRDS) was performed to assess extracellular pH (pHe), followed by immediate euthanasia. Laboratory parameters and histopathologic ex vivo analysis included fluorescence confocal microscopy and immunohistochemistry., Results: DCE MR imaging demonstrated a similar degree of devascularization of embolized tumors for both microsphere sizes (mean arterial enhancement, 8% ± 12 vs 36% ± 51 in controls; P = .07). Similarly, DWI showed postprocedural increases in diffusion across the entire lesion (apparent diffusion coefficient, 1.89 × 10 -3 mm 2 /s ± 0.18 vs 2.34 × 10 -3 mm 2 /s ± 0.18 in liver; P = .002). BIRDS demonstrated profound tumor acidosis at baseline (mean pHe, 6.79 ± 0.08 in tumor vs 7.13 ± 0.08 in liver; P = .02) and after chemoembolization (6.8 ± 0.06 in tumor vs 7.1 ± 0.04 in liver; P = .007). Laboratory and ex vivo analyses showed central tumor core penetration and greater increase in liver enzymes for 40-μm vs 100-μm microspheres. Inhibition of cell proliferation, intratumoral hypoxia, and limited idarubicin elution were equally observed with both sphere sizes., Conclusions: Noninvasive multiparametric MR imaging visualized chemoembolic effects in tumor and tumor microenvironment following DEE chemoembolization. Devascularization, increased hypoxia, coagulative necrosis, tumor acidosis, and limited idarubicin elution suggest ischemia as the predominant therapeutic mechanism. Substantial size-dependent differences indicate greater toxicity with the smaller microsphere diameter., (Copyright © 2020 SIR. Published by Elsevier Inc. All rights reserved.)

Objectives: To investigate the predictive value of quantifiable imaging and inflammatory biomarkers in patients with hepatocellular carcinoma (HCC) for the clinical outcome after drug-eluting bead transarterial chemoembolization (DEB-TACE) measured as volumetric tumor response and progression-free survival (PFS)., Methods: This retrospective study included 46 patients with treatment-naïve HCC who received DEB-TACE. Laboratory work-up prior to treatment included complete and differential blood count, liver function, and alpha-fetoprotein levels. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were correlated with radiomic features extracted from pretreatment contrast-enhanced magnetic resonance imaging (MRI) and with tumor response according to quantitative European Association for the Study of the Liver (qEASL) criteria and progression-free survival (PFS) after DEB-TACE. Radiomic features included single nodular tumor growth measured as sphericity, dynamic contrast uptake behavior, arterial hyperenhancement, and homogeneity of contrast uptake. Statistics included univariate and multivariate linear regression, Cox regression, and Kaplan-Meier analysis., Results: Accounting for laboratory and clinical parameters, high baseline NLR and PLR were predictive of poorer tumor response (p = 0.014 and p = 0.004) and shorter PFS (p = 0.002 and p < 0.001). When compared to baseline imaging, high NLR and PLR correlated with non-spherical tumor growth (p = 0.001 and p < 0.001)., Conclusions: This study establishes the prognostic value of quantitative inflammatory biomarkers associated with aggressive non-spherical tumor growth and predictive of poorer tumor response and shorter PFS after DEB-TACE., Key Points: • In treatment-naïve hepatocellular carcinoma (HCC), high baseline platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) are associated with non-nodular tumor growth measured as low tumor sphericity. • High PLR and NLR are predictive of poorer volumetric enhancement-based tumor response and PFS after DEB-TACE in HCC. • This set of readily available, quantitative immunologic biomarkers can easily be implemented in clinical guidelines providing a paradigm to guide and monitor the personalized application of loco-regional therapies in HCC.

Purpose: To establish magnetic resonance (MR)-based molecular imaging paradigms for the noninvasive monitoring of extracellular pH (pH e ) as a functional surrogate biomarker for metabolic changes induced by locoregional therapy of liver cancer., Experimental Design: Thirty-two VX2 tumor-bearing New Zealand white rabbits underwent longitudinal imaging on clinical 3T-MRI and CT scanners before and up to 2 weeks after complete conventional transarterial chemoembolization (cTACE) using ethiodized oil (lipiodol) and doxorubicin. MR-spectroscopic imaging (MRSI) was employed for pH e mapping. Multiparametric MRI and CT were performed to quantify tumor enhancement, diffusion, and lipiodol coverage of the tumor posttherapy. In addition, incomplete cTACE with reduced chemoembolic doses was applied to mimic undertreatment and exploit pH e mapping to detect viable tumor residuals. Imaging findings were correlated with histopathologic markers indicative of metabolic state (HIF-1α, GLUT-1, and LAMP-2) and viability (proliferating cell nuclear antigen and terminal deoxynucleotidyl-transferase dUTP nick-end labeling)., Results: Untreated VX2 tumors demonstrated a significantly lower pH e (6.80 ± 0.09) than liver parenchyma (7.19 ± 0.03, P < 0.001). Upregulation of HIF-1α, GLUT-1, and LAMP-2 confirmed a hyperglycolytic tumor phenotype and acidosis. A gradual tumor pH e increase toward normalization similar to parenchyma was revealed within 2 weeks after complete cTACE, which correlated with decreasing detectability of metabolic markers. In contrast, pH e mapping after incomplete cTACE indicated both acidic viable residuals and increased tumor pH e of treated regions. Multimodal imaging revealed durable tumor devascularization immediately after complete cTACE, gradually increasing necrosis, and sustained lipiodol coverage of the tumor., Conclusions: MRSI-based pH e mapping can serve as a longitudinal monitoring tool for viable tumors. As most liver tumors are hyperglycolytic creating microenvironmental acidosis, therapy-induced normalization of tumor pH e may be used as a functional biomarker for positive therapeutic outcome., (©2019 American Association for Cancer Research.)

Our purpose was to identify baseline imaging features in patients with liver cancer that correlate with 90 Y distribution on postprocedural SPECT and predict tumor response to transarterial radioembolization (TARE). Methods: This retrospective study was approved by the institutional review board and included 38 patients with hepatocellular carcinoma (HCC) ( n = 23; 18/23 men; mean age, 62.39 ± 8.62 y; 34 dominant tumors) and non-HCC hepatic malignancies ( n = 15; 9/15 men; mean age, 61.13 ± 11.51 y; 24 dominant tumors) who underwent 40 resin-based TARE treatments (August 2012 to January 2018). Multiphasic contrast-enhanced MRI or CT was obtained before and Bremsstrahlung SPECT within 2 h after TARE. Total tumor volume (cm 3 ) and enhancing tumor volume (ETV [cm 3 ] and % of total tumor volume), and total and enhancing tumor burden (%), were volumetrically assessed on baseline imaging. Up to 2 dominant tumors per treated lobe were analyzed. After multimodal image registration of baseline imaging and SPECT/CT, 90 Y distribution was quantified on SPECT as tumor-to-normal-liver ratio (TNR). Response was assessed according to RECIST1.1 and quantitative European Association for the Study of the Liver criteria. Clinical parameters were also assessed. Statistical tests included Mann-Whitney U, Pearson correlation, and linear regression. Results: In HCC patients, high baseline ETV% significantly correlated with high TNR on SPECT, demonstrating greater 90 Y uptake in the tumor relative to the liver parenchyma ( P < 0.001). In non-HCC patients, a correlation between ETV% and TNR was observed as well ( P = 0.039). Follow-up imaging for response assessments within 1-4 mo after TARE was available for 23 patients with 25 treatments. The change of ETV% significantly correlated with TNR in HCC ( P = 0.039) but not in non-HCC patients ( P = 0.886). Additionally, Child-Pugh class B patients demonstrated significantly more 90 Y deposition in nontumorous liver than Child-Pugh A patients ( P = 0.021). Conclusion: This study identified ETV% as a quantifiable imaging biomarker on preprocedural MRI and CT to predict 90 Y distribution on postprocedural SPECT in HCC and non-HCC. However, the relationship between the preferential uptake of 90 Y to the tumor and tumor response after radioembolization could be validated only for HCC., (© 2019 by the Society of Nuclear Medicine and Molecular Imaging.)

Objectives: To develop and validate a proof-of-concept convolutional neural network (CNN)-based deep learning system (DLS) that classifies common hepatic lesions on multi-phasic MRI., Methods: A custom CNN was engineered by iteratively optimizing the network architecture and training cases, finally consisting of three convolutional layers with associated rectified linear units, two maximum pooling layers, and two fully connected layers. Four hundred ninety-four hepatic lesions with typical imaging features from six categories were utilized, divided into training (n = 434) and test (n = 60) sets. Established augmentation techniques were used to generate 43,400 training samples. An Adam optimizer was used for training. Monte Carlo cross-validation was performed. After model engineering was finalized, classification accuracy for the final CNN was compared with two board-certified radiologists on an identical unseen test set., Results: The DLS demonstrated a 92% accuracy, a 92% sensitivity (Sn), and a 98% specificity (Sp). Test set performance in a single run of random unseen cases showed an average 90% Sn and 98% Sp. The average Sn/Sp on these same cases for radiologists was 82.5%/96.5%. Results showed a 90% Sn for classifying hepatocellular carcinoma (HCC) compared to 60%/70% for radiologists. For HCC classification, the true positive and false positive rates were 93.5% and 1.6%, respectively, with a receiver operating characteristic area under the curve of 0.992. Computation time per lesion was 5.6 ms., Conclusion: This preliminary deep learning study demonstrated feasibility for classifying lesions with typical imaging features from six common hepatic lesion types, motivating future studies with larger multi-institutional datasets and more complex imaging appearances., Key Points: • Deep learning demonstrates high performance in the classification of liver lesions on volumetric multi-phasic MRI, showing potential as an eventual decision-support tool for radiologists. • Demonstrating a classification runtime of a few milliseconds per lesion, a deep learning system could be incorporated into the clinical workflow in a time-efficient manner.

Objectives: To develop a proof-of-concept "interpretable" deep learning prototype that justifies aspects of its predictions from a pre-trained hepatic lesion classifier., Methods: A convolutional neural network (CNN) was engineered and trained to classify six hepatic tumor entities using 494 lesions on multi-phasic MRI, described in Part 1. A subset of each lesion class was labeled with up to four key imaging features per lesion. A post hoc algorithm inferred the presence of these features in a test set of 60 lesions by analyzing activation patterns of the pre-trained CNN model. Feature maps were generated that highlight regions in the original image that correspond to particular features. Additionally, relevance scores were assigned to each identified feature, denoting the relative contribution of a feature to the predicted lesion classification., Results: The interpretable deep learning system achieved 76.5% positive predictive value and 82.9% sensitivity in identifying the correct radiological features present in each test lesion. The model misclassified 12% of lesions. Incorrect features were found more often in misclassified lesions than correctly identified lesions (60.4% vs. 85.6%). Feature maps were consistent with original image voxels contributing to each imaging feature. Feature relevance scores tended to reflect the most prominent imaging criteria for each class., Conclusions: This interpretable deep learning system demonstrates proof of principle for illuminating portions of a pre-trained deep neural network's decision-making, by analyzing inner layers and automatically describing features contributing to predictions., Key Points: • An interpretable deep learning system prototype can explain aspects of its decision-making by identifying relevant imaging features and showing where these features are found on an image, facilitating clinical translation. • By providing feedback on the importance of various radiological features in performing differential diagnosis, interpretable deep learning systems have the potential to interface with standardized reporting systems such as LI-RADS, validating ancillary features and improving clinical practicality. • An interpretable deep learning system could potentially add quantitative data to radiologic reports and serve radiologists with evidence-based decision support.

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 C max of the active metabolite was 41.5 ± 26.1 ng/mL, with average T max 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., (Copyright © 2018 SIR. Published by Elsevier Inc. All rights reserved.)

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.

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., (Copyright © 2018 SIR. Published by Elsevier Inc. All rights reserved.)

Purpose: To evaluate the performance of automated feeder detection (AFD) software (EmboGuide; Philips Healthcare, Best, The Netherlands) on hepatocellular carcinoma (HCC) tumors during transarterial chemoembolization., Materials and Methods: Forty-four first-time transarterial chemoembolization patients (37 men; mean age, 62 ± 11 years) were enrolled between May 2012 and July 2013. A total of 86 HCC lesions were treated (2.0 ± 1.4 lesions per patient; 27.6 ± 15.9 mm maximum diameter). One hundred forty-seven feeding arteries were found with digital subtraction angiography (DSA), cone-beam computed tomography (CT), and AFD software with the option of manual adjustment (MA). Three independent interventional radiologists analyzed the cone-beam CT images retrospectively with and without AFD and MA. Compared with the number of treated vessels, the number of true positives, false positives, false negatives, sensitivity, and interreader agreement were determined using clustered binary data analysis., Results: Cone-beam CT enabled detection of 100 ± 3.5 feeding arteries (70% sensitivity) with 68.6% agreement among readers. AFD software significantly improved detection to 127±0.6 feeding arteries (86% sensitivity, P = .008) with 99.7% reader agreement and reduced the number of false negatives from an average of 47 ± 3.5 to 20 ± 0.6 (P = .008). MA of the AFD results produced similar feeding artery detection rates (127 ± 5.1, 86% sensitivity, P = .8), with lower interreader agreement (91.6%) and slightly fewer false positives (16 ± 0.0 to 14 ± 2.5, P = .4)., Conclusions: AFD software significantly improved feeding artery detection rates during transarterial chemoembolization of HCC lesions with better user reproducibility compared with cone-beam CT alone. In conjunction with DSA, AFD enables maximum feeding artery detection in this setting., (Copyright © 2017 SIR. Published by Elsevier Inc. All rights reserved.)

Objectives: To compare efficacy, survival outcome and prognostic factors of conventional transarterial chemoembolisation (cTACE), drug-eluting beads TACE (DEB-TACE) and yttrium-90 radioembolisation (Y90) for the treatment of liver metastases from gastroenteropancreatic (GEP) neuroendocrine tumours (NELM)., Methods: This retrospective analysis included 192 patients (58.6 years mean age, 56% men) with NELM treated with cTACE (N = 122), DEB-TACE (N = 26) or Y90 (N = 44) between 2000 and 2014. Radiologic response to therapy was assessed according to Response Evaluation Criteria in Solid Tumours (RECIST) and World Health Organization (WHO) criteria using periprocedural MR imaging. Survival analysis included propensity score analysis (PSA), median overall survival (MOS), hepatic progression-free survival, Kaplan-Meier using log-rank test and the uni- and multivariate Cox proportional hazards model (MVA)., Results: MOS of the entire study population was 28.8 months. As for cTACE, DEB-TACE and Y90, MOS was 33.8 months, 21.7 months and 23.6 months, respectively. According to the MVA, cTACE demonstrated a significantly longer MOS as compared to DEB-TACE (p <.01) or Y90 (p = .02). The 5-year survival rate after initial cTACE, DEB-TACE and Y90 was 28.2%, 10.3% and 18.5%, respectively., Conclusions: Upon PSA, our study suggests significant survival benefits for patients treated with cTACE as compared to DEB-TACE and Y90. This data supports the therapeutic decision for cTACE as the primary intra-arterial therapy option in patients with unresectable NELM until proven otherwise., Key Points: • cTACE achieved a significantly longer overall survival in patients with unresectable NELM. • Patients treated with cTACE showed a prolonged hepatic progression-free survival. • cTACE, DEB-TACE and Y90 radioembolisation demonstrated comparable safety and toxicity profiles. • Age >70 years, extrahepatic metastases and tumour burden >50% were identified as negative predictors. • Propensity score analysis suggests the superiority of cTACE over DEB-TACE and Y90.

Objectives: Our study sought to compare the overall survival in patients with hepatocellular carcinoma (HCC) and portal venous thrombosis (PVT), treated with either conventional trans-arterial chemoembolization (cTACE) or drug-eluting beads (DEB) TACE., Methods: This retrospective analysis included a total of 133 patients, treated without cross-over and compared head-to-head by means or propensity score weighting. Mortality was compared using survival analysis upon propensity score weighting. Adverse events and liver toxicity grade ≥3 were recorded and reported for each TACE. In order to compare with historical sorafenib studies, a sub-group analysis was performed and included patients who fulfilled the SHARP inclusion criteria., Results: The median overall survival (MOS) of the entire cohort was 4.53 months (95 % CI, 3.63-6.03). MOS was similar across treatment arms, no significant difference between cTACE (N = 95) and DEB-TACE (N = 38) was observed (MOS of 5.0 vs. 3.33 months, respectively; p = 0.157). The most common adverse events after cTACE and DEB- TACE, respectively, were as follows: post-embolization syndrome [N = 57 (30.0 %) and N = 38 (61.3 %)], diarrhea [N = 3 (1.6 %) and N = 3 (4.8 %)], and encephalopathy [N = 11 (5.8 %) and N = 2 (3.2 %)]., Conclusion: Our retrospective study could not reveal a difference in toxicity and efficiency between cTACE and DEB-TACE for treatment of advanced stage HCC with PVT., Key Points: • Conventional TACE (cTACE) and drug-eluting-beads TACE (DEB-TACE) demonstrated equal safety profiles. • Survival rates after TACE are similar to patients treated with sorafenib. • Child-Pugh class and tumor burden are reliable predictors of 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., (Copyright © 2015. Published by Elsevier Ireland Ltd.)

Unlabelled: 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., (© 2014 by the American Association for the Study of Liver Diseases.)