In the treatment of Non-Hodgkin lymphoma (NHL), multiple therapeutic options are available. Improving outcome predictions are essential to optimize treatment. The metabolic active tumor volume (MATV) has shown to be a prognostic factor in NHL. It is usually retrieved using semi-automated thresholding methods based on standardized uptake values (SUV), calculated from 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) images. However, there is currently no consensus method for NHL. The aim of this study was to review literature on different segmentation methods used, and to evaluate selected methods by using an in house created software tool. A software tool, MUltiple SUV Threshold (MUST)-segmenter was developed where tumor locations are identified by placing seed-points on the PET images, followed by subsequent region growing. Based on a literature review, 9 SUV thresholding methods were selected and MATVs were extracted. The MUST-segmenter was utilized in a cohort of 68 patients with NHL. Differences in MATVs were assessed with paired t-tests, and correlations and distributions figures. High variability and significant differences between the MATVs based on different segmentation methods (p < 0.05) were observed in the NHL patients. Median MATVs ranged from 35 to 211 cc. No consensus for determining MATV is available based on the literature. Using the MUST-segmenter with 9 selected SUV thresholding methods, we demonstrated a large and significant variation in MATVs. Identifying the most optimal segmentation method for patients with NHL is essential to further improve predictions of toxicity, response, and treatment outcomes, which can be facilitated by the MUST-segmenter.

UNASSIGNED: To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases.
UNASSIGNED: In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models.
UNASSIGNED: Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong < 0.001).
UNASSIGNED: Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Translation of imaging into 3-dimensional (3D) printed patient-specific phantoms (3DPSPs) can help visualize complex cardiovascular anatomy and enable tailoring of therapy. The aim of this paper is to review the entire process of phantom production, including imaging, materials, 3D printing technologies, and the validation of 3DPSPs. A systematic review of published research was conducted using Embase and MEDLINE, including studies that investigated 3DPSPs in cardiovascular medicine. Among 2,534 screened papers, 212 fulfilled inclusion criteria and described 3DPSPs as a valuable adjunct for planning and guiding interventions (n = 108 [51%]), simulation of physiological or pathological conditions (n = 19 [9%]), teaching of health care professionals (n = 23 [11%]), patient education (n = 3 [1.4%]), outcome prediction (n = 6 [2.8%]), or other purposes (n = 53 [25%]). The most common imaging modalities to enable 3D printing were cardiac computed tomography (n = 131 [61.8%]) and cardiac magnetic resonance (n = 26 [12.3%]). The printing process was conducted mostly by material jetting (n = 54 [25.5%]) or stereolithography (n = 43 [20.3%]). The 10 largest studies that evaluated the geometric accuracy of 3DPSPs described a mean bias <±1 mm; however, the validation process was very heterogeneous among the studies. Three-dimensional printed patient-specific phantoms are highly accurate, used for teaching, and applied to guide cardiovascular therapy. Systematic comparison of imaging and printing modalities following a standardized validation process is warranted to allow conclusions on the optimal production process of 3DPSPs in the field of cardiovascular medicine.

UNASSIGNED: Non-alcoholic fatty liver disease (NAFLD) is widespread chronic disease of the live in humans with the prevalence of 30% of the United States population.1,2 The goal of the study is to validate the performance of quantitative ultrasound algorithms in the assessment of hepatic steatosis in patients with suspected NAFLD.
UNASSIGNED: This prospective study enrolled a total of 31 patients with clinical suspicion of NAFLD to receive liver fat measurements by quantitative ultrasound and reference MRI measurements (proton density fat-fraction, PDFF). The following ultrasound (US) parameters based on both raw ultrasound RF (Radio Frequency) data and 2D B-mode images of the liver were analyzed with subsequent correlation with MRI-PDFF: hepatorenal index, acoustic attenuation coefficient, Nakagami coefficient parameter, shear wave viscosity, shear wave dispersion and shear wave elasticity. Ultrasound parameters were also correlated with the presence of hypertension and diabetes.
UNASSIGNED: The mean (± SD) age and body mass index of the patients were 49.03 (± 12.49) and 30.12 (± 6.15), respectively. Of the aforementioned ultrasound parameters, the hepatorenal index and acoustic attenuation coefficient showed a strong correlation with MRI-PDFF derivations of hepatic steatosis, with r-values of 0.829 and 0.765, respectively. None of the remaining US parameters showed strong correlations with PDFF. Significant differences in Nakagami parameters and acoustic attenuation coefficients were found in those patients with and without hypertension.
UNASSIGNED: Hepatorenal index and acoustic attenuation coefficient correlate well with MRI-PDFF-derived measurements of hepatic steatosis. Quantitative ultrasound is a promising tool for the diagnosis and assessment of patients with NAFLD.

UNASSIGNED: We aimed to evaluate long-term outcome of patients with chronic non-cirrhotic extrahepatic portal vein obstruction (CNC-EHPVO) who underwent portal vein recanalisation (PVR) without transjugular intrahepatic portosystemic shunt (TIPS) insertion and to determine factors predicting PVR failure and stent occlusion.
UNASSIGNED: This retrospective monocentric study included all patients who underwent PVR without TIPS insertion in the context of CNC-EHPVO between the years 2000 and 2019. Primary patency was defined by the absence of a complete stent occlusion on follow-up imaging.
UNASSIGNED: A total of 31 patients underwent PVR with a median follow-up of 52 months (24-82 months). Indications were gastrointestinal bleeding (n = 13), abdominal pain attributed to CNC-EHPVO (n = 7), prior to abdominal surgery (n = 4), and others (n = 7). Technical success was obtained in 27 patients. PVR failure was associated with extension within the intrahepatic portal veins (p = 0.005) and recanalisation for abdominal pain (p = 0.02). Adverse events occurred in 6 patients with no mortality. Anticoagulation was administered in 21 patients after technical success of PVR. In patients with technical success, 5-year primary patency was 73% and was associated with improved muscle mass (p = 0.007) and decreased spleen volume (p = 0.01) at 1 year. Furthermore, 21 (78%) patients with PVR technical success were free of portal hypertension complication at 5 years.
UNASSIGNED: PVR without TIPS insertion was feasible and safe in selected patients with CNC-EHPVO and portal hypertension with past or expected complications. Primary patency at 5 years was obtained in 3 of 4 patients with technical success of PVR and was associated with a control of complications of CNC-EHPVO. PVR was associated with improvement of sarcopenia and decreased spleen volume at 1 year.
UNASSIGNED: Patients with chronic obstruction of the portal vein and without cirrhosis or malignancy can develop complications related to the high pressure in the venous system. The present study reports long-term favourable outcome of patients in whom the obstruction was treated with stents.

Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative and quantitative information from multiple data sources to make a diagnosis, prognosticate the disease course, and recommend a treatment. In the last 5 years, advances in artificial intelligence (AI), particularly in deep learning, have made it possible to extract clinically relevant information from complex and diverse clinical datasets. In particular, histopathology and radiology image data contain diagnostic, prognostic and predictive information which AI can extract. Ultimately, such AI systems could be implemented in clinical routine as decision support tools. However, in the context of hepatology, this requires further large-scale clinical validation and regulatory approval. Herein, we summarise the state of the art in AI in hepatology with a particular focus on histopathology and radiology data. We present a roadmap for the further development of novel biomarkers in hepatology and outline critical obstacles which need to be overcome.

Thermal drift of optical systems employed for surface guided radiation therapy (SGRT) adds uncertainty to patient setup and monitoring. This work describes methods to measure the drift of individual camera pods as well as the drift of the combined clinical signal. It presents results for four clinical C-Rad Catalyst+ HD systems. Based on the measured clinical drift, recipes are provided on how to calculate relevant uncertainties in patient setup and patient position monitoring with SGRT. Strategies to reduce the impact of drift are explained. While the results are specific to the systems investigated, the methodology is transferable and the clinical recipes are universally applicable.

This study aimed to assess the impact of the margin applied to the clinical target volume, to create the planning target volume, on plan quality of a novel dysphagia-optimised intensity modulated radiotherapy technique developed within a head and neck cancer multicentre randomised controlled trial. Protocol compliant plans were used for a single benchmark planning case. Larger margins were associated with higher doses to adjacent organs at risk, particularly the inferior pharyngeal constrictor muscle, but coincided with some improved low dose target coverage. A 3 mm margin is recommended for this technique if local practices allow.

UNASSIGNED: To investigate the potential of texture analysis and machine learning to predict treatment response to transarterial radioembolization (TARE) on pre-interventional cone-beam computed tomography (CBCT) images in patients with liver metastases.
UNASSIGNED: In this IRB-approved retrospective single-center study 36 patients with a total of 104 liver metastases (56 % male, mean age 61.1 ± 13 years) underwent CBCT prior to TARE and follow-up imaging 6 months after therapy. Treatment response was evaluated according to RECIST version 1.1 and dichotomized into disease control (partial response/stable disease) versus disease progression (progressive disease). After target lesion segmentation, 104 radiomics features corresponding to seven different feature classes were extracted with the pyRadiomics package. After dimension reduction machine learning classifications were performed on a custom artificial neural network (ANN). Ten-fold cross validation on a previously unseen test data set was performed.
UNASSIGNED: The average administered cumulative activity from TARE was 1.6 Gbq (± 0.5 Gbq). At a mean follow-up of 5.9 ± 0.8 months disease control was achieved in 82 % of metastases. After dimension reduction, 15 of 104 (15 %) texture analysis features remained for further analysis. On a previously unseen set of liver metastases the Multilayer Perceptron ANN yielded a sensitivity of 94.2 %, specificity of 67.7 % and an area-under-the receiver operating characteristics curve of 0.85.
UNASSIGNED: Our study indicates that texture analysis-based machine learning may has potential to predict treatment response to TARE using pre-treatment CBCT images of patients with liver metastases with high accuracy.

Echocardiographic imaging is crucial for patient management during cardiotoxic cancer therapy. Left ventricular ejection fraction is the most commonly used parameter for identifying left ventricular dysfunction. However, it lacks sensitivity to detect subclinical changes in cardiac function due to cardiotoxic treatment. Global longitudinal strain (GLS) is the best studied strain parameter with established diagnostic and prognostic value. Multiple studies have demonstrated changes in GLS as an early marker of cardiotoxicity. This document serves as a primer to help clinicians in the acquisition and interpretation of strain in cardio-oncology. Cases with embedded videos illustrate a step-by-step approach to obtaining GLS measurements and common pitfalls to avoid. The document includes a concise summary of the indications of GLS in cardio-oncology and its role in guiding oncological therapy. Practical approaches on how to implement strain in the echo laboratory with guidance on training and quality assurance are also discussed.