Recurrence of Pulmonary Arteriovenous Malformation after Embolization in Patients with Pulmonary Hypertension.

PURPOSE: To evaluate the correlation between pulmonary hypertension (PH) and recurrence of pulmonary arteriovenous malformation (PAVM) after embolization. MATERIALS AND METHODS: With institutional review board (IRB) approval, the records of 377 patients with PAVMs evaluated at a single hereditary hemorrhagic telangiectasia (HHT) center of excellence between January 1, 2013, and September 10, 2023, were retrospectively reviewed. PAVMs embolized during this time period were evaluated for recurrence. Patients and PAVMs not treated during this time period were excluded. Growth of previously untreated PAVMs was not considered recurrence. Patients without chest computed tomography (CT) follow-up were excluded. General demographics, HHT status as defined by genetic testing or Curacao criteria, presence of PH, history of smoking, anemia, and hepatic arteriovenous malformations (AVMs) were documented. Odds ratio (OR) was calculated and stratified analysis was performed to assay the correlation between PAVM recurrence, PH, and possible confounders. RESULTS: A total of 151 patients with PAVMs were treated during the study period, including 438 PAVMs, for which follow-up was available. This included 106 patients with definite, 31 with doubtful, and 14 with possible HHT. The presence of PH was significantly associated with PAVM recurrence both by patient (OR, 8.13; 95% CI, 3.50-19.67) and by lesion (OR, 4.07; 95% CI, 2.14-7.91). Multivariate analysis demonstrated that this correlation was independent of several variables including HHT status, smoking history, presence of hepatic AVMs, and anemia. CONCLUSIONS: There is a high correlation between PH and PAVM recurrence, suspected to be due to high pulmonary artery pressures causing recanalization. PH may suggest the need for shorter surveillance intervals.

Hepatic Hypertrophy in Normal and Cirrhotic Livers Following Portal Vein Embolization: Comparative Assessment of 2 Different Embolic Regimens in a Large Animal Model.

PURPOSE: To compare the mechanistic effects and hypertrophy outcomes using 2 different portal vein embolization (PVE) regimens in normal and cirrhotic livers in a large animal model. METHODS AND MATERIALS: The Institutional Animal Care and Use Committee approved all experiments conducted in this study. Fourteen female Yorkshire pigs were separated into a cirrhotic group (CG, n = 7) and non-cirrhotic group (NCG, n = 7) and further subgrouped into those using microspheres and coils (MC, n = 3) or n-butyl cyanoacrylate (nBCA, n = 3) and their corresponding controls (each n = 1). A 3:1 ethiodized oil and ethanol mixture was administered intra-arterially in the CG to induce cirrhosis 4 weeks before PVE. Animals underwent baseline computed tomography (CT), PVE including pre-PVE and post-PVE pressure measurements, and CT imaging at 2 and 4 weeks after PVE. Immunofluorescence stainings for CD3, CD16, Ki-67, and caspase 3 were performed to assess immune cell infiltration, hepatocyte proliferation, and apoptosis. Statistical significance was tested using the Student's t test. RESULTS: Four weeks after PVE, the percentage of future liver remnant (FLR%) increased by 18.8% (standard deviation [SD], 3.6%) vs 10.9% (SD, 0.95%; P < .01) in the NCG vs CG. The baseline percentage of standardized future liver remnant (sFLR%) for the controls were 41.6% for CG vs 43.6% for NCG. Based on the embolic agents used, the sFLR% two weeks after PVE was 58.4% (SD, 3.7%) and 52.2% (SD, 0.9%) (P < .01) for MC and 46.0% (SD, 2.2%) and 47.2% (SD, 0.4%) for nBCA in the NCG and CG, respectively. Meanwhile, the sFLR% 4 weeks after PVE was 60.5% (SD, 3.9%) and 54.9% (SD, 0.8%) (P < .01) and 60.4% (SD, 3.5%) and 54.2% (SD, 0.95%) (P < .01), respectively. Ki-67 signal intensity increased in the embolized lobe in both CG and NCG (P < .01). CONCLUSIONS: This preclinical study demonstrated that MC could be the preferred embolic of choice compared to nBCA when a substantial and rapid FLR increase is needed for resection, in both cirrhotic and non-cirrhotic livers.

Large left varicocele in a patient with portal hypertension treated via transjugular intrahepatic portosystemic shunt placement and both variceal and varicocele embolization.

BACKGROUND: Scrotal swelling from varicocele is a common complaint in adult men. Varicocele due to portosystemic collaterals is a rare presentation of portal hypertension. Imaging workup and intervention for varicocele in this case is more complex than varicocele due to absent or incompetent valves in the testicular veins and pampiniform plexus. CASE PRESENTATION: We present the case of a 53-year-old man with alcohol-related cirrhosis presented with persistent left scrotal heaviness, pain, and swelling found to have a large left varicocele. Given his history of cirrhosis, a contrast-enhanced CT of the abdomen and pelvis was obtained showing that the varices were supplied by a vessel arising from the splenic vein and draining into the left renal vein as well as gastric varices. Varicocele embolization alone is not sufficient in this case, and we treated with transjugular intrahepatic portosystemic shunt, variceal and varicocele embolization. CONCLUSION: In patients presenting with a varicocele with a history of cirrhosis/portal hypertension, cross sectional imaging of the abdomen and pelvis should be obtained prior to treatment to evaluate for the presence of varices which may be pressured by varicocele embolization. If present, consideration should be given to referral to an interventional radiologist for possible concurrent variceal embolization and TIPS placement.

Comparison of metabolic and immunologic responses to transarterial chemoembolization with different chemoembolic regimens in a rabbit VX2 liver tumor model.

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 (pHe) 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: pHe mapping revealed that combining cTACE with prior bicarbonate infusion significantly increased tumor pHe 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 pHe 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 pHe 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).

Cryoablation of Venous Malformations: A Systematic Review.

This study aimed to review systematically the efficacy, safety, and technical aspects of cryoablation in the treatment of venous malformations (VMs) and to provide the groundwork for future studies. A literature search for clinical studies utilizing percutaneous cryoablation of VMs was performed. All clinical studies related to primary or secondary treatment of VMs with percutaneous cryoablation were included in this review. These selected studies were evaluated for patient characteristics, cryoablation technique, technical success, lesion size and pain scores before and after cryoablation, and adverse outcomes. Random effects analysis of postprocedural changes in lesion volume and pain scores was performed. There were 54 patients with 55 cases of cryoablation of VMs. Of these cases, 27 recorded changes in lesion volume and 31 recorded changes in pain scores. The weighted mean postprocedural decrease in lesion size was 92.0% (raw average, 71.7%). The weighted mean reduction in pain score was 77% (raw average, 78.2%). Considering all treated cases (55), complete resolution of symptoms was seen in 35 cases (63.6%) and overall (complete or partial) improvement in 52 cases (94.5%). Common postprocedural symptoms included pain, bruising, swelling and numbness lasting less than 2 weeks. There were two major adverse events (3.7%), with both cases due to persistent dysesthesia. Patients with a history of prior sclerotherapy demonstrated lower preprocedural and postprocedural pain scores (4.7 and 1.3) than patients without prior treatments (5.8 and 2.8). Cryoablation of VMs appears to be potentially safe and effective on limited short-interval follow-up.

Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach.

PURPOSE: To show that a deep learning (DL)-based, automated model for Lipiodol (Guerbet Pharmaceuticals, Paris, France) segmentation on cone-beam computed tomography (CT) after conventional transarterial chemoembolization performs closer to the "ground truth segmentation" than a conventional thresholding-based model. MATERIALS AND METHODS: This post hoc analysis included 36 patients with a diagnosis of hepatocellular carcinoma or other solid liver tumors who underwent conventional transarterial chemoembolization with an intraprocedural cone-beam CT. Semiautomatic segmentation of Lipiodol was obtained. Subsequently, a convolutional U-net model was used to output a binary mask that predicted Lipiodol deposition. A threshold value of signal intensity on cone-beam CT was used to obtain a Lipiodol mask for comparison. The dice similarity coefficient (DSC), mean squared error (MSE), center of mass (CM), and fractional volume ratios for both masks were obtained by comparing them to the ground truth (radiologist-segmented Lipiodol deposits) to obtain accuracy metrics for the 2 masks. These results were used to compare the model versus the threshold technique. RESULTS: For all metrics, the U-net outperformed the threshold technique: DSC (0.65 ± 0.17 vs 0.45 ± 0.22, P < .001) and MSE (125.53 ± 107.36 vs 185.98 ± 93.82, P = .005). The difference between the CM predicted and the actual CM was 15.31 mm ± 14.63 versus 31.34 mm ± 30.24 (P < .001), with lesser distance indicating higher accuracy. The fraction of volume present ([predicted Lipiodol volume]/[ground truth Lipiodol volume]) was 1.22 ± 0.84 versus 2.58 ± 3.52 (P = .048) for the current model's prediction and threshold technique, respectively. CONCLUSIONS: This study showed that a DL framework could detect Lipiodol in cone-beam CT imaging and was capable of outperforming the conventionally used thresholding technique over several metrics. Further optimization will allow for more accurate, quantitative predictions of Lipiodol depositions intraprocedurally.

Research Priorities in Percutaneous Image- and Endoscopy-Guided Interventions for Biliary and Gallbladder Diseases: Proceedings from the Society of Interventional Radiology Foundation Multidisciplinary Research Consensus Panel.

Recent technological advancements, including the introduction of disposable endoscopes, have enhanced the role of interventional radiology (IR) in the management of biliary and gallbladder diseases. There are unanswered questions in this growing field. The Society of Interventional Radiology Foundation convened a virtual research consensus panel consisting of a multidisciplinary group of experts to develop a prioritized research agenda regarding percutaneous image- and endoscopy-guided procedures for biliary and gallbladder diseases. The panelists discussed current data, opportunities for IR, and future efforts to maximize IR's ability and scope. A recurring theme throughout the discussions was to find ways to reduce the total duration of percutaneous drains and improve patients' quality of life. After the presentations and discussions, research priorities were ranked on the basis of their clinical relevance and impact. The research ideas ranked top 3 were as follows: (a) percutaneous multimodality management of benign anastomotic biliary strictures (laser vs endobiliary ablation vs cholangioplasty vs drain upsize protocol alone), (b) ablation of intraductal cholangiocarcinoma with and without stent placement, and (c) cholecystoscopy/choledochoscopy and lithotripsy in nonsurgical patients with calculous cholecystitis. Collaborative, retrospective, and prospective research studies are essential to answer these questions and improve the management protocols for patients with biliary and gallbladder diseases.

Impact of Chemoembolic Regimen on Immune Cell Recruitment and Immune Checkpoint Marker Expression following Transcatheter Arterial Chemoembolization in a VX2 Rabbit Liver Tumor Model.

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/µm2 ± 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.

Deep learning-assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver.

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.

Prospective study of Lipiodol distribution as an imaging marker for doxorubicin pharmacokinetics during conventional transarterial chemoembolization of liver malignancies.

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 (Cmax) 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-Cmax increased from 1 segment (DOX-Cmax, 83.94 ± 75.09 ng/mL; DN-DOX-Cmax, 2.67 ± 2.02 ng/mL/mg) to ≥ 2 segments (DOX-Cmax, 139.66 ± 117.73 ng/mL; DN-DOX-Cmax, 3.68 ± 4.20 ng/mL/mg) to lobar distribution (DOX-Cmax, 334.35 ± 215.18 ng/mL; DN-DOX-Cmax, 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-Cmax 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-Cmax 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 (Cmax). • 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 Cmax 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.

Reliable prediction of survival in advanced-stage hepatocellular carcinoma treated with sorafenib: comparing 1D and 3D quantitative tumor response criteria on MRI.

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.

Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of tumor response in hepatocellular carcinoma after DEB-TACE.

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.

Idarubicin-Loaded ONCOZENE Drug-Eluting Bead Chemoembolization in a Rabbit Liver Tumor Model: Investigating Safety, Therapeutic Efficacy, and Effects on Tumor Microenvironment.

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 mm2/s ± 0.18 vs 2.34 × 10-3 mm2/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.

Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features.

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.

Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.

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.

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.

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.

Sensitivity and Reproducibility of Automated Feeding Artery Detection Software during Transarterial Chemoembolization of Hepatocellular Carcinoma.

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.