The role of iliac vein stent placement in pelvic venous disorder management.

Pelvic venous disease (PeVD) has historically been challenging to diagnose and treat. This paper describes a comprehensive approach to the diagnosis of PeVD and reviews the role of iliac vein stent placement in treatment. Patient selection is vital for non-thrombotic iliac vein lesions (NIVLs) as only a small subset of patients with an NIVL will benefit from stent placement. There is limited, inconclusive data on optimal treatment for patients with both primary ovarian vein reflux and an NIVL. Patients with chronic post-thrombotic outflow obstruction typically have a more favorable risk/benefit ratio for intervention but require anticoagulation and close follow-up due to poorer long-term stent patency. Intravascular ultrasound is a useful tool for identifying obstructive lesions, sizing stents, and planning landing zones. More research is needed to characterize underlying pathophysiology, validate thresholds for intervention, develop reliable methods for outcomes assessment, and determine treatment response. Until this data is produced, an individualized treatment approach is warranted.

Conventional vs. Drug-Eluting Beads Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma-A Propensity Score Weighted Comparison of Efficacy and Safety.

This study compared the efficacy and safety of conventional transarterial chemoembolization (cTACE) with drug-eluting beads (DEB)-TACE in patients with unresectable hepatocellular carcinoma (HCC). This retrospective analysis included 370 patients with HCC treated with cTACE (n = 248) or DEB-TACE (n = 122) (January 2000-July 2014). Overall survival (OS) was assessed using uni- and multivariate Cox proportional hazards models and Kaplan-Meier analysis. Additionally, baseline imaging was assessed, and clinical and laboratory toxicities were recorded. Propensity score weighting via a generalized boosted model was applied to account for group heterogeneity. There was no significant difference in OS between cTACE (20 months) and DEB-TACE patients (24.3 months, ratio 1.271, 95% confidence interval 0.876-1.69; p = 0.392). However, in patients with infiltrative disease, cTACE achieved longer OS (25.1 months) compared to DEB-TACE (9.2 months, ratio 0.366, 0.191-0.702; p = 0.003), whereas DEB-TACE proved more effective in nodular disease (39.4 months) than cTACE (18 months, ratio 0.458, 0.308-0681; p = 0.007). Adverse events occurred with similar frequency, except for abdominal pain, which was observed more frequently after DEB-TACE (101/116; 87.1%) than cTACE (119/157; 75.8%; p = 0.02). In conclusion, these findings suggest that tumor morphology and distribution should be used as parameters to inform decisions on the selection of embolic materials for TACE for a more personalized treatment planning in patients with unresectable HCC.

Extrahepatic Applications of Yttrium-90 Radioembolization.

While initially described and now accepted as treatment for primary and secondary malignancies in the liver, radioembolization therapy has expanded to include treatment for other disease pathologies and other organ systems. Advantages and limitations for these treatments exist and must be compared against more traditional treatments for these processes. This article provides an overview of the current applications for radioembolization outside of the liver, for both malignant and nonmalignant disease.

Catheter-directed therapies for pulmonary embolism: considerations for patients with patent foramen ovale.

Pulmonary embolism can be fatal, especially in high-risk patients who have contraindications to systemic thrombolysis or surgical embolectomy. For this population, interventionalists can provide catheter-directed therapies, including catheter-directed thrombolysis and thrombectomy, using a wide array of devices. Endovascular treatment of pulmonary embolism shows great promise through fractionated thrombolytic drug delivery, fragmentation, and aspiration mechanisms with thrombectomy devices. Although successful outcomes have been reported after using these treatments, evidence is especially limited in patients with both a patent foramen ovale (PFO) and acute pulmonary embolism. In patients with PFO, it is important to consider whether catheter-directed therapy is appropriate or whether surgical embolectomy should instead be performed. An increased risk of paradoxical embolus in these patients supports the use of diagnostic echocardiography with possible surgical closure of PFO after one episode of pulmonary embolism. Percutaneous PFO closure, which can be performed at the time of catheter-based therapy, theoretically reduces risk of future paradoxical embolization, although more data are needed before making a recommendation for this specific group of patients.

Automated feature quantification of Lipiodol as imaging biomarker to predict therapeutic efficacy of conventional transarterial chemoembolization of liver cancer.

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.

Supervised Machine Learning in Oncology: A Clinician's Guide.

The widespread adoption of electronic health records has resulted in an abundance of imaging and clinical information. New data-processing technologies have the potential to revolutionize the practice of medicine by deriving clinically meaningful insights from large-volume data. Among those techniques is supervised machine learning, the study of computer algorithms that use self-improving models that learn from labeled data to solve problems. One clinical area of application for supervised machine learning is within oncology, where machine learning has been used for cancer diagnosis, staging, and prognostication. This review describes a framework to aid clinicians in understanding and critically evaluating studies applying supervised machine learning methods. Additionally, we describe current studies applying supervised machine learning techniques to the diagnosis, prognostication, and treatment of cancer, with a focus on gastroenterological cancers and other related pathologies.

Alternatives to Surgery for Early-Stage Non-Small Cell Lung Cancer: Thermal Ablation.

Thermal ablation involves the application of heat or cold energy to the lung under image guidance to eradicate tumors. It is indicated for treatment of early-stage non-small cell lung cancer in nonsurgical patients. Ablation technologies have advanced, such that nearly all small tumors can now be treated safely and effectively. Ablation does not cause a lasting decline in pulmonary function tests and may therefore be used to treat multiple synchronous and metachronous lung tumors, a chief advantage over other treatments. Large series with intermediate- and long-term data have been reported showing favorable overall survival, similar to radiation therapy.

Oligometastatic Disease and Interventional Oncology: Rationale and Research Directions.

Oligometastatic disease (OMD) is generally defined as a stage of clinically or radiographically demonstrated metastatic disease limited in total disease burden and without rapid spread. Interventional oncology performs local therapies for primary and metastatic cancers, including OMD. Interventional oncology treatments can be pursued both as definitive therapy and for palliative purposes. Applied to OMD, these interventions can offer patients a decreasing overall tumor burden, minimizing cancer morbidity, and early evidence suggests a survival benefit. Here, we discuss the range of interventional oncology treatments, including ablation, chemoembolization, radioembolization, and irreversible electroporation. We describe the rationale for their application to OMD and discuss future directions for research.

Simultaneous proximal embolic protection and inferior vena cava mechanical thrombectomy using the FlowTriever system.

Interventional radiologists have the unique ability to apply their imaging knowledge, wide scope of technical skills, and use of innovative technologies to comprehensively address the percutaneous management of the thromboembolic disease processes. This report illustrates successful management of a thrombosed IVC, while protecting against possible pulmonary embolism. Here, we present a 49-year-old female with stage IIIB ovarian cancer who presented with severe bilateral lower extremity edema and anasarca in setting of occlusive thrombus of IVC. The thrombus was the result of compressionfrom a large hepatic hematoma which gradually developed after radical hysterectomy. A new mechanical thrombectomy device approved for use in pulmonary embolism, Inari FlowTriever catheter, was used off-label to remove the clot. The self-expanding mesh discs in the Inari FlowTriever catheter were utilized to protect against pulmonary embolism while percutaneously draining the hepatic hematoma and alleviating the IVC compression. The IVC was largely patent at the end of the procedure, and the patient experienced complete resolution of her symptoms. This case report demonstrates the successful and safe off-label use of a new mechanical thrombectomy device approved for pulmonary embolism thrombectomy in the IVC and illustrates a novel application of the nitinol mesh discs in the device as proximal embolic protection.

Right Atrial and Massive Pulmonary Artery Mechanical Thrombectomy Under Echocardiography Guidance Using the FlowTriever System.

INTRODUCTION: Management of clot in transit in patients with pulmonary embolism, who are candidates for percutaneous intervention, can be challenging. This is a case report of simultaneous right atrial mechanical thrombectomy under echocardiography guidance and pulmonary artery embolectomy under fluoroscopy guidance, using the recently introduced FlowTriever system (Inari Medical Inc., Irvine, CA, USA). REPORT: An 88 year old female, resuscitated from cardiopulmonary arrest near the end of a total right hip arthroplasty, presented for management of suspected massive pulmonary embolism. Her right atrial thrombus was removed under transthoracic echocardiography guidance, and her pulmonary arterial thrombus was subsequently successfully treated under fluoroscopy. DISCUSSION: The FlowTriever system can be safely and effectively used under real time transthoracic echocardiography guidance to retrieve clot in transit from the cardiac chambers, in addition to its standard application for the pulmonary artery under fluoroscopy guidance.

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.

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.

Science to Practice: Decrypting the Enigma of Ablation-induced Off-Target Effects-Is Network Pathway Analysis the Final Piece of the Puzzle?

As part of the ongoing effort to better understand and mitigate pro-oncogenic off-target effects of imaging-guided radiofrequency ablation (RFA), Kumar et al ( 1 ) used gene expression and network pathway analysis to examine the gene activation profiles in the peri-ablational zone after RFA in a breast adenocarcinoma liver metastasis animal model. Their analysis identified STAT3 (signal transducer and activator of transcription 3) as a key transcription factor upregulated in many signaling pathways in the peri-ablational zone after RFA. Consequently, the authors successfully used two STAT3 inhibitors to reduce distant tumor growth after treatment with RFA. By demonstrating that judicious and appropriate adjuvant therapy helped contain distant tumor growth caused by ablation, Kumar et al have managed to pave the road ahead for the definitive success of ablation.

Science to Practice: Molecular-targeted Drug Delivery in Combination with Radiofrequency Ablation of Liver Cancer: A Magic Bullet?

In an effort to improve the technical success rates and clinical outcomes of radiofrequency (RF) ablation, Yan et al validated the use of a tumor-penetrating peptide and thermosensitive doxorubicin (DOX)-loaded nanoparticles in combination with RF ablation in a hepatocellular carcinoma mouse model. By achieving higher chemotherapeutic drug concentrations in target lesions, fewer toxic effects, and improved survival end points in an animal tumor model, the authors conclude that superior tumor treatment with RF ablation is possible when combined with molecular-targeted drug delivery systems.