2D-Perfusion Angiography Using Carbon Dioxide (CO2): A Feasible Tool to Monitor Immediate Treatment Response to Endovascular Therapy of Peripheral Arterial Disease?

Purpose!#!Patients with peripheral arterial disease (PAD) or critical limb ischemia (CLI) require revascularization. Traditionally, endovascular therapy (EVT) is performed with iodinated contrast agent (ICM), which can provoke potential deterioration in renal function. CO2 is a safe negative contrast agent to guide vascular procedures, but interpretation of CO2 angiography is challenging. Changes in blood flow following iodine-aided EVT are assessable with 2D-perfusion angiography (2D-PA). The aim of this study was to evaluate 2D-PA as a tool to monitor blood flow changes during CO!##!Material and methods!#!2D-PA was performed before and after ten EVTs (nine stents; one endoprosthesis; 10/2012-02/2020) in nine patients (six men; 65 ± 10y) with Fontaine stage IIb (n = 8) and IV (n = 1). A reference ROI (ROI!##!Results!#!2D-PA was technically feasible in all cases. A significant increase of 82% in PD!##!Conclusion!#!The presented 2D-PA technique facilitates the assessment of arterial flow in CO2-aided EVTs and has the potential to simplify the assessment of immediate treatment response

Percutaneous Hepatic Perfusion (PHP) with Melphalan in Liver-Dominant Metastatic Uveal Melanoma: The German Experience

Percutaneous hepatic perfusion (PHP) delivers high-dose melphalan to the liver while minimizing systemic toxicity via filtration of the venous hepatic blood. This two-center study aimed to examine the safety, response to therapy, and survival of patients with hepatic-dominant metastatic uveal melanoma (UM) treated with PHP. A total of 66 patients with liver-dominant metastasized uveal melanoma, treated with 145 PHP between April 2014 and May 2020, were retrospectively analyzed with regard to adverse events (AEs; CTCAE v5.0), response (overall response rate (ORR)), and disease control rate (DCR) according to RECIST1.1, as well as progression-free and overall survival (PFS and OS). With an ORR of 59% and a DCR of 93.4%, the response was encouraging. After initial PHP, median hepatic PFS was 12.4 (confidence interval (CI) 4–18.4) months and median OS was 18.4 (CI 7–24.6) months. Hematologic toxicity was the most frequent AE (grade 3 or 4 thrombocytopenia after 24.8% of the procedures); less frequent was grade 3 or 4 hepatic toxicity (increased aspartate transaminase (AST) and alanine transaminase (ALT) after 7.6% and 6.9% of the interventions, respectively). Cardiovascular events included four cases of ischemic stroke (2.8%) and one patient with central pulmonary embolism (0.7%). In conclusion, PHP is a safe and effective salvage treatment for liver-dominant metastatic uveal melanoma. Serious AEs—though rare—demand careful patient selection

Evaluation of a Motion Correction Algorithm for C-Arm Computed Tomography Acquired During Transarterial Chemoembolization

Purpose!#!The aim of this retrospective study was to evaluate the feasibility of a motion correction 3D reconstruction prototype technique for C-arm computed tomography (CACT).!##!Material and methods!#!We included 65 consecutive CACTs acquired during transarterial chemoembolization of 54 patients (47 m,7f; 67 ± 11.3 years). All original raw datasets (CACT!##!Results!#!Objective IQ as defined by an image sharpness metric, increased from 273.5 ± 28 (CACT!##!Conclusion!#!The application of a motion correction algorithm was feasible for all data sets and led to an increase in both objective and subjective IQ parameters.!##!Level of evidence!#!3

Transjugular intrahepatic portosystemic shunt placement: portal vein puncture guided by 3D/2D image registration of contrast-enhanced multi-detector computed tomography and fluoroscopy

Background!#!To assess the technical feasibility, success rate, puncture complications and procedural characteristics of transjugular intrahepatic portosystemic shunt (TIPS) placement using a three-dimensional vascular map (3D-VM) overlay based on image registration of pre-procedural contrast-enhanced (CE) multi-detector computed tomography (MDCT) for portal vein puncture guidance.!##!Materials and methods!#!Overall, 27 consecutive patients (59 ± 9 years, 18male) with portal hypertension undergoing elective TIPS procedure were included. TIPS was guided by CE-MDCT overlay after image registration based on fluoroscopic images. A 3D-VM of the hepatic veins and the portal vein was created based on the pre-procedural CE-MDCT and superimposed on fluoroscopy in real-time. Procedural characteristics as well as hepatic vein catheterization time (HVCT), puncture time (PT), overall procedural time (OPT), fluoroscopy time (FT) and the dose area product (DAP) were evaluated. Thereafter, HVCT, PT, OPT and FT using 3D-VM (61 ± 9 years, 14male) were compared to a previous using classical fluoroscopic guidance (53 ± 9 years, 21male) for two interventional radiologist with less than 3 years of experience in TIPS placement.!##!Results!#!All TIPS procedure using of 3D/2D image registered 3D-VM were successful with a significant reduction of the PSG (p < 0.0001). No clinical significant complication occurred. HVCT was 14 ± 11 min, PT was 14 ± 6 min, OPT was 64 ± 29 min, FT was 21 ± 12 min and DAP was 107.48 ± 93.84 Gy cm!##!Conclusion!#!TIPS placement applying registration-based CE-MDCT vessel information for puncture guidance is feasible and safe. It has the potential to improve hepatic vein catherization, portal vein puncture and radiation exposure

Non-occlusive mesenteric ischemia (NOMI): evaluation of 2D-perfusion angiography (2D-PA) for early treatment response assessment

Purpose!#!To evaluate the feasibility of 2D-perfusion angiography (2D-PA) for the analysis of intra-procedural treatment response after intra-arterial prostaglandin E1 therapy in patients with non-occlusive mesenteric ischemia (NOMI).!##!Methods!#!Overall, 20 procedures in 18 NOMI patients were included in this retrospective case-control study. To evaluate intra-procedural splanchnic circulation changes, post-processing of digital subtraction angiography (DSA) series was performed. Regions of interest (ROIs) were placed in the superior mesenteric artery (SMA; reference), the portal vein (PV; ROI!##!Results!#!Vasodilator therapy leads to a significant decrease of the 2D-PA-derived values PD!##!Conclusion!#!2D-PA offers an objective approach to analyze immediate flow and perfusion changes following vasodilatory therapies of NOMI patients and may be a valuable tool for assessing treatment response

Automatisierte Klassifizierung von radiologischen Freitext-Befunden: Analyse verschiedener Feature-Extraction-Methoden zur Identifizierung distaler Fibulafrakturen

Purpose: Radiology reports mostly contain free-text, which makes it challenging to obtain structured data. Natural language processing (NLP) techniques transform free-text reports into machine-readable document vectors that are important for creating reliable, scalable methods for data analysis. The aim of this study is to classify unstructured radiograph reports according to fractures of the distal fibula and to find the best text mining method. Materials & Methods: We established a novel German language report dataset: a designated search engine was used to identify radiographs of the ankle and the reports were manually labeled according to fractures of the distal fibula. This data was used to establish a machine learning pipeline, which implemented the text representation methods bag-of-words (BOW), term frequency-inverse document frequency (TF-IDF), principal component analysis (PCA), non-negative matrix factorization (NMF), latent Dirichlet allocation (LDA), and document embedding (doc2vec). The extracted document vectors were used to train neural networks (NN), support vector machines (SVM), and logistic regression (LR) to recognize distal fibula fractures. The results were compared via cross-tabulations of the accuracy (acc) and area under the curve (AUC). Results: In total, 3268 radiograph reports were included, of which 1076 described a fracture of the distal fibula. Comparison of the text representation methods showed that BOW achieved the best results (AUC = 0.98; acc = 0.97), followed by TF-IDF (AUC = 0.97; acc = 0.96), NMF (AUC = 0.93; acc = 0.92), PCA (AUC = 0.92; acc = 0.9), LDA (AUC = 0.91; acc = 0.89) and doc2vec (AUC = 0.9; acc = 0.88). When comparing the different classifiers, NN (AUC = 0,91) proved to be superior to SVM (AUC = 0,87) and LR (AUC = 0,85). Conclusion: An automated classification of unstructured reports of radiographs of the ankle can reliably detect findings of fractures of the distal fibula. A particularly suitable feature extraction method is the BOW model. Key Points:  - The aim was to classify unstructured radiograph reports according to distal fibula fractures. - Our automated classification system can reliably detect fractures of the distal fibula. - A particularly suitable feature extraction method is the BOW model.Ziel: Radiologische Befundtexte enthalten häufig Freitext, was eine strukturierte Datenauswertung erschwert. Natural language processing (NLP)-Techniken wandeln Freitext in maschinenlesbare Dokumentenvektoren um, die für die Entwicklung zuverlässiger, skalierbarer Methoden zur Datenanalyse wichtig sind. Ziel dieser Studie war es, unstrukturierte Röntgenbefunde nach Frakturen der distalen Fibula zu klassifizieren und die beste Text-Mining-Methode zu finden. Material & Methoden: Zur Erstellung eines eigenen deutschsprachigen Befunddatensatzes wurden mittels einer dedizierten Suchmaschine Sprunggelenks-Röntgenbilder identifiziert und die entsprechenden Befunde manuell nach Frakturen der distalen Fibula sortiert. Anhand der Daten wurde eine Machine-Learning-Pipeline erstellt, die die Textrepräsentationsmethoden Bag-of-Words (BOW), Term Frequency-Inverse Document Frequency (TF-IDF), Principal Component Analysis (PCA), Non-Negative Matrix Factorization (NMF), Latent Dirichlet Allocation (LDA) und Document Embedding (doc2vec) implementierte. Die extrahierten Dokumentvektoren wurden zum Trainieren von neuronalen Netzen (NN), Support Vector Machines (SVM) und logistischer Regression (LR) verwendet, um distale Fibulafrakturen zu erkennen. Die Ergebnisse wurden mittels Kreuztabellen bzgl. der Accuracy (acc) und der area under the curve (AUC) verglichen. Ergebnisse: Insgesamt wurden 3268 Röntgenbefunde inkludiert, von denen 1076 eine distale Fibulafraktur beschrieben. Der Vergleich der Textdarstellungsmethoden zeigte, dass BOW die besten Ergebnisse erzielte (AUC = 0,98; acc = 0,97), gefolgt von TF-IDF (AUC = 0,97; acc = 0,96), NMF (AUC = 0,93; acc = 0,92), PCA (AUC = 0,92; acc = 0,9), LDA (AUC = 0,91; acc = 0,89) und doc2vec (AUC = 0,9; acc = 0,88). Im Vergleich der Klassifikatoren erwiesen sich die NN (AUC = 0,91) gegenüber SVM (AUC = 0,87) und LR (AUC = 0,85) als überlegen. Schlussfolgerung: Durch die automatisierte Klassifikation von unstrukturierten Befunden von Sprunggelenksaufnahmen können Frakturen der distalen Fibula zuverlässig erkannt werden. Eine besonders geeignete Methode zur Feature Extraction ist das BOW-Modell. Kernaussagen:  - Ziel war die automatisierte Klassifizierung unstrukturierter Röntgenbefunde entsprechend distaler Fibulafrakturen. - Eine zuverlässige Detektion von distalen Fibulafrakturen ist durch das automatisierte Klassifizierungssystem gewährleistet. - Eine besonders geeignete Methode zur Feature Extraction ist das BOW-Modell