3D-Volumetric Shunt Measurement for Detection of High-Risk Esophageal Varices in Liver Cirrhosis.

Background and Objectives: Esophageal varices (EV) and variceal hemorrhages are major causes of mortality in liver cirrhosis patients. Detecting EVs early is crucial for effective management. Computed tomography (CT) scans, commonly performed for various liver-related indications, provide an opportunity for non-invasive EV assessment. However, previous CT studies focused on variceal diameter, neglecting the three-dimensional (3D) nature of varices and shunt vessels. This study aims to evaluate the potential of 3D volumetric shunt-vessel measurements from routine CT scans for detecting high-risk esophageal varices in portal hypertension. Methods: 3D volumetric measurements of esophageal varices were conducted using routine CT scans and compared to endoscopic variceal grading. Receiver operating characteristic (ROC) analyses were performed to determine the optimal cutoff value for identifying high-risk varices based on shunt volume. The study included 142 patients who underwent both esophagogastroduodenoscopy (EGD) and contrast-enhanced CT within six months. Results: The study established a cutoff value for identifying high-risk varices. The CT measurements exhibited a significant correlation with endoscopic EV grading (correlation coefficient r = 0.417, p < 0.001). A CT cutoff value of 2060 mm3 for variceal volume showed a sensitivity of 72.1% and a specificity of 65.5% for detecting high-risk varices during endoscopy. Conclusions: This study demonstrates the feasibility of opportunistically measuring variceal volumes from routine CT scans. CT volumetry for assessing EVs may have prognostic value, especially in cirrhosis patients who are not suitable candidates for endoscopy.

Fetal Cardiac MRI Using Doppler US Gating: Emerging Technology and Clinical Implications.

Fetal cardiac MRI using Doppler US gating is an emerging technique to support prenatal diagnosis of congenital heart disease and other cardiovascular abnormalities. Analogous to postnatal electrocardiographically gated cardiac MRI, this technique enables directly gated MRI of the fetal heart throughout the cardiac cycle, allowing for immediate data reconstruction and review of image quality. This review outlines the technical principles and challenges of cardiac MRI with Doppler US gating, such as loss of gating signal due to fetal movement. A practical workflow of patient preparation for the use of Doppler US-gated fetal cardiac MRI in clinical routine is provided. Currently applied MRI sequences (ie, cine or four-dimensional flow imaging), with special consideration of technical adaptations to the fetal heart, are summarized. The authors provide a literature review on the clinical benefits of Doppler US-gated fetal cardiac MRI for gaining additional diagnostic information on cardiovascular malformations and fetal hemodynamics. Finally, future perspectives of Doppler US-gated fetal cardiac MRI and further technical developments to reduce acquisition times and eliminate sources of artifacts are discussed. Keywords: MR Fetal, Ultrasound Doppler, Cardiac, Heart, Congenital, Obstetrics, Fetus Supplemental material is available for this article. © RSNA, 2024.

[Screening, risk stratification and CT imaging for assessment of coronary artery disease]. / Screening, Risikostratifizierung und CT-Bildgebung zur Abklärung der koronaren Herzkrankheit.

BACKGROUND: Early treatment of cardiovascular risk factors and characterization of coronary plaques is essential to collect prognostic information about coronary artery disease (CAD) and prevent cardiovascular events. OBJECTIVES: Discussion of the most important risk factors of CAD, basic diagnostic of CAD, prevention, and prognostic factors of CAD with focus on cardiac computed tomography (CT). MATERIALS AND METHODS: Prevalence and prognostic impact of CAD risk factors; description of specific assessment of risk profiles; estimation of pretest probability; conventional prevention of CAD; prognostic assessment of CAD using the Calcium Scoring and coronary CT angiography. RESULTS: Assessment of risk profiles and estimation of pretest probability for obstructive coronary stenosis necessitates a thorough evaluation of medical history and laboratory values. The composition and extent of calcified and noncalcified plaques in CT exams based on the criteria of the Coronary Artery Disease-Reporting and Data System give important prognostic information about the risk of cardiovascular events, which increases with high plaque burden and vice versa. Initial imaging with CT for evaluation of CAD leads to a reduction of invasive coronary angiographies and catheter-associated complications. CONCLUSIONS: Besides early detection of cardiovascular risk factors, the additional assessment of plaque burden and significant stenosis in CT gives further prognostic information to facilitate effective therapies to prevent cardiovascular events and in the case of low plaque burden avoid invasive coronary angiography. However, systmatic screening using Calcium Scoring is not established yet due to insufficient data, although it could potentially be used for an early risk stratification in patients with multiple risk factors.

Generative Pre-trained Transformer 4 makes cardiovascular magnetic resonance reports easy to understand.

BACKGROUND: Patients are increasingly using Generative Pre-trained Transformer 4 (GPT-4) to better understand their own radiology findings. PURPOSE: To evaluate the performance of GPT-4 in transforming cardiovascular magnetic resonance (CMR) reports into text that is comprehensible to medical laypersons. METHODS: ChatGPT with GPT-4 architecture was used to generate three different explained versions of 20 various CMR reports (n = 60) using the same prompt: "Explain the radiology report in a language understandable to a medical layperson". Two cardiovascular radiologists evaluated understandability, factual correctness, completeness of relevant findings, and lack of potential harm, while 13 medical laypersons evaluated the understandability of the original and the GPT-4 reports on a Likert scale (1 "strongly disagree", 5 "strongly agree"). Readability was measured using the Automated Readability Index (ARI). Linear mixed-effects models (values given as median [interquartile range]) and intraclass correlation coefficient (ICC) were used for statistical analysis. RESULTS: GPT-4 reports were generated on average in 52 s ± 13. GPT-4 reports achieved a lower ARI score (10 [9-12] vs 5 [4-6]; p < 0.001) and were subjectively easier to understand for laypersons than original reports (1 [1] vs 4 [4,5]; p < 0.001). Eighteen out of 20 (90%) standard CMR reports and 2/60 (3%) GPT-generated reports had an ARI score corresponding to the 8th grade level or higher. Radiologists' ratings of the GPT-4 reports reached high levels for correctness (5 [4, 5]), completeness (5 [5]), and lack of potential harm (5 [5]); with "strong agreement" for factual correctness in 94% (113/120) and completeness of relevant findings in 81% (97/120) of reports. Test-retest agreement for layperson understandability ratings between the three simplified reports generated from the same original report was substantial (ICC: 0.62; p < 0.001). Interrater agreement between radiologists was almost perfect for lack of potential harm (ICC: 0.93, p < 0.001) and moderate to substantial for completeness (ICC: 0.76, p < 0.001) and factual correctness (ICC: 0.55, p < 0.001). CONCLUSION: GPT-4 can reliably transform complex CMR reports into more understandable, layperson-friendly language while largely maintaining factual correctness and completeness, and can thus help convey patient-relevant radiology information in an easy-to-understand manner.

Image quality of abdominal photon-counting CT with reduced contrast media dose: Evaluation of reduced contrast media protocols during the COVID19 pandemic supply shortage.

Rationale and objectives: Aim of this study was to assess the impact of contrast media dose (CMD) reduction on diagnostic quality of photon-counting detector CT (PCD-CT) and energy-integrating detector CT (EID-CT). Methods: CT scans of the abdominal region with differing CMD acquired in portal venous phase on a PCD-CT were included and compared to EID-CT scans. Diagnostic quality and contrast intensity were rated. Additionally, readers had to assign the scans to reduced or regular CMD. Regions-of-interest (ROIs) were placed in defined segments of portal vein, inferior vena cava, liver, spleen, kidneys, abdominal aorta and muscular tissue. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Results: Overall 158 CT scans performed on a PCD-CT and 68 examinations on an EID-CT were analyzed. Overall diagnostic quality showed no significant differences for PCD-CT with standard CMD which scored a median 5 (IQR:5-5) and PCD-CT with 70% CMD scoring 5 (4-5). (For PCD-CT, 71.69% of the examinations with reduced CMD were assigned to regular CMD by the readers, for EID-CT 9.09%. Averaged for all measurements SNR for 50% CMD was reduced by 19% in PCD-CT (EID-CT 34%) and CNR by 48% (EID-CT 56%). Virtual monoenergetic images (VMI)50keV for PCD-CT images acquired with 50% CMD showed an increase in SNR by 72% and CNR by 153%. Conclusions: Diagnostic interpretability of PCD-CT examinations with reduction of up to 50% CMD is maintained. PCD-CT deducted scans especially with 70% CMD were often not recognized as CMD reduced scans. Compared to EID-CT less decline in SNR and CNR is observed for CMD reduced PCD-CT images. Employing VMI50keV for CMD-reduced PCD-CT images compensated for the effects.

CT-derived Epicardial Adipose Tissue Inflammation Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement.

PURPOSE: Inflammatory changes in epicardial (EAT) and pericardial adipose tissue (PAT) are associated with increased overall cardiovascular risk. Using routine, preinterventional cardiac CT data, we examined the predictive value of quantity and quality of EAT and PAT for outcome after transcatheter aortic valve replacement (TAVR). MATERIALS AND METHODS: Cardiac CT data of 1197 patients who underwent TAVR at the in-house heart center between 2011 and 2020 were retrospectively analyzed. The amount and density of EAT and PAT were quantified from single-slice CT images at the level of the aortic valve. Using established risk scores and known independent risk factors, a clinical benchmark model (BMI, Chronic kidney disease stage, EuroSCORE 2, STS Prom, year of intervention) for outcome prediction (2-year mortality) after TAVR was established. Subsequently, we tested whether the additional inclusion of area and density values of EAT and PAT in the clinical benchmark model improved prediction. For this purpose, the cohort was divided into a training (n=798) and a test cohort (n=399). RESULTS: Within the 2-year follow-up, 264 patients died. In the training cohort, particularly the addition of EAT density to the clinical benchmark model showed a significant association with outcome (hazard ratio 1.04, 95% CI: 1.01-1.07; P =0.013). In the test cohort, the outcome prediction of the clinical benchmark model was also significantly improved with the inclusion of EAT density (c-statistic: 0.589 vs. 0.628; P =0.026). CONCLUSIONS: EAT density as a surrogate marker of EAT inflammation was associated with 2-year mortality after TAVR and may improve outcome prediction independent of established risk parameters.

Radiologists' perspectives on the workflow integration of an artificial intelligence-based computer-aided detection system: A qualitative study.

In healthcare, artificial intelligence (AI) is expected to improve work processes, yet most research focuses on the technical features of AI rather than its real-world clinical implementation. To evaluate the implementation process of an AI-based computer-aided detection system (AI-CAD) for prostate MRI readings, we interviewed German radiologists in a pre-post design. We embedded our findings in the Model of Workflow Integration and the Technology Acceptance Model to analyze workflow effects, facilitators, and barriers. The most prominent barriers were: (i) a time delay in the work process, (ii) additional work steps to be taken, and (iii) an unstable performance of the AI-CAD. Most frequently named facilitators were (i) good self-organization, and (ii) good usability of the software. Our results underline the importance of a holistic approach to AI implementation considering the sociotechnical work system and provide valuable insights into key factors of the successful adoption of AI technologies in work systems.

Deep learning denoising reconstruction for improved image quality in fetal cardiac cine MRI.

Purpose: This study aims to evaluate deep learning (DL) denoising reconstructions for image quality improvement of Doppler ultrasound (DUS)-gated fetal cardiac MRI in congenital heart disease (CHD). Methods: Twenty-five fetuses with CHD (mean gestational age: 35 ± 1 weeks) underwent fetal cardiac MRI at 3T. Cine imaging was acquired using a balanced steady-state free precession (bSSFP) sequence with Doppler ultrasound gating. Images were reconstructed using both compressed sensing (bSSFP CS) and a pre-trained convolutional neural network trained for DL denoising (bSSFP DL). Images were compared qualitatively based on a 5-point Likert scale (from 1 = non-diagnostic to 5 = excellent) and quantitatively by calculating the apparent signal-to-noise ratio (aSNR) and contrast-to-noise ratio (aCNR). Diagnostic confidence was assessed for the atria, ventricles, foramen ovale, valves, great vessels, aortic arch, and pulmonary veins. Results: Fetal cardiac cine MRI was successful in 23 fetuses (92%), with two studies excluded due to extensive fetal motion. The image quality of bSSFP DL cine reconstructions was rated superior to standard bSSFP CS cine images in terms of contrast [3 (interquartile range: 2-4) vs. 5 (4-5), P < 0.001] and endocardial edge definition [3 (2-4) vs. 4 (4-5), P < 0.001], while the extent of artifacts was found to be comparable [4 (3-4.75) vs. 4 (3-4), P = 0.40]. bSSFP DL images had higher aSNR and aCNR compared with the bSSFP CS images (aSNR: 13.4 ± 6.9 vs. 8.3 ± 3.6, P < 0.001; aCNR: 26.6 ± 15.8 vs. 14.4 ± 6.8, P < 0.001). Diagnostic confidence of the bSSFP DL images was superior for the evaluation of cardiovascular structures (e.g., atria and ventricles: P = 0.003). Conclusion: DL image denoising provides superior quality for DUS-gated fetal cardiac cine imaging of CHD compared to standard CS image reconstruction.

Use of virtual monoenergetic images for reduction of extensive dental implant associated artifacts in photon-counting detector CT.

Aim of this study was to assess the impact of virtual monoenergetic images (VMI) on dental implant artifacts in photon-counting detector computed tomography (PCD-CT) compared to standard reconstructed polychromatic images (PI). 30 scans with extensive (≥ 5 dental implants) dental implant-associated artifacts were retrospectively analyzed. Scans were acquired during clinical routine on a PCD-CT. VMI were reconstructed for 100-190 keV (10 keV steps) and compared to PI. Artifact extent and assessment of adjacent soft tissue were rated using a 5-point Likert grading scale for qualitative assessment. Quantitative assessment was performed using ROIs in most pronounced hypodense and hyperdense artifacts, artifact-impaired soft tissue, artifact-free fat and muscle tissue. A corrected attenuation was calculated as difference between artifact-impaired tissue and tissue without artifacts. Qualitative assessment of soft palate and cheeks improved for all VMI compared to PI (Median PI: 1 (Range: 1-3) and 1 (1-3); e.g. VMI130 keV 2 (1-5); p < 0.0001 and 2 (1-4); p < 0.0001). In quantitative assessment, VMI130 keV showed best results with a corrected attenuation closest to 0 (PI: 30.48 ± 98.16; VMI130 keV: - 0.55 ± 73.38; p = 0.0026). Overall, photon-counting deducted VMI reduce the extent of dental implant-associated artifacts. VMI of 130 keV showed best results and are recommended to support head and neck CT scans.

SCMR expert consensus statement for cardiovascular magnetic resonance of patients with a cardiac implantable electronic device.

Cardiovascular magnetic resonance (CMR) is a proven imaging modality for informing diagnosis and prognosis, guiding therapeutic decisions, and risk stratifying surgical intervention. Patients with a cardiac implantable electronic device (CIED) would be expected to derive particular benefit from CMR given high prevalence of cardiomyopathy and arrhythmia. While several guidelines have been published over the last 16 years, it is important to recognize that both the CIED and CMR technologies, as well as our knowledge in MR safety, have evolved rapidly during that period. Given increasing utilization of CIED over the past decades, there is an unmet need to establish a consensus statement that integrates latest evidence concerning MR safety and CIED and CMR technologies. While experienced centers currently perform CMR in CIED patients, broad availability of CMR in this population is lacking, partially due to limited availability of resources for programming devices and appropriate monitoring, but also related to knowledge gaps regarding the risk-benefit ratio of CMR in this growing population. To address the knowledge gaps, this SCMR Expert Consensus Statement integrates consensus guidelines, primary data, and opinions from experts across disparate fields towards the shared goal of informing evidenced-based decision-making regarding the risk-benefit ratio of CMR for patients with CIEDs.

Optical Flow-Guided Cine MRI Segmentation With Learned Corrections.

In cardiac cine magnetic resonance imaging (MRI), the heart is repeatedly imaged at numerous time points during the cardiac cycle. Frequently, the temporal evolution of a certain region of interest such as the ventricles or the atria is highly relevant for clinical diagnosis. In this paper, we devise a novel approach that allows for an automatized propagation of an arbitrary region of interest (ROI) along the cardiac cycle from respective annotated ROIs provided by medical experts at two different points in time, most frequently at the end-systolic (ES) and the end-diastolic (ED) cardiac phases. At its core, a 3D TV- L1 -based optical flow algorithm computes the apparent motion of consecutive MRI images in forward and backward directions. Subsequently, the given terminal annotated masks are propagated by this bidirectional optical flow in 3D, which results, however, in improper initial estimates of the segmentation masks due to numerical inaccuracies. These initially propagated segmentation masks are then refined by a 3D U-Net-based convolutional neural network (CNN), which was trained to enforce consistency with the forward and backward warped masks using a novel loss function. Moreover, a penalization term in the loss function controls large deviations from the initial segmentation masks. This method is benchmarked both on a new dataset with annotated single ventricles containing patients with severe heart diseases and on a publicly available dataset with different annotated ROIs. We emphasize that our novel loss function enables fine-tuning the CNN on a single patient, thereby yielding state-of-the-art results along the complete cardiac cycle.

Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-intensity focused ultrasound treatment.

OBJECTIVES: To evaluate the prognostic value of CT-based markers of sarcopenia and myosteatosis in comparison to the Eastern Cooperative Oncology Group (ECOG) score for survival of patients with advanced pancreatic cancer treated with high-intensity focused ultrasound (HIFU). MATERIALS AND METHODS: For 142 retrospective patients, the skeletal muscle index (SMI), skeletal muscle radiodensity (SMRD), fatty muscle fraction (FMF), and intermuscular fat fraction (IMFF) were determined on superior mesenteric artery level in pre-interventional CT. Each marker was tested for associations with sex, age, body mass index (BMI), and ECOG. The prognostic value of the markers was examined in Kaplan-Meier analyses with the log-rank test and in uni- and multivariable Cox proportional hazards (CPH) models. RESULTS: The following significant associations were observed: Male patients had higher BMI and SMI. Patients with lower ECOG had lower BMI and SMI. Patients with BMI lower than 21.8 kg/m2 (median) also showed lower SMI and IMFF. Patients younger than 63.3 years (median) were found to have higher SMRD, lower FMF, and lower IMFF. In the Kaplan-Meier analysis, significantly lower survival times were observed in patients with higher ECOG or lower SMI. Increased patient risk was observed for higher ECOG, lower BMI, and lower SMI in univariable CPH analyses for 1-, 2-, and 3-year survival. Multivariable CPH analysis for 1-year survival revealed increased patient risk for higher ECOG, lower SMI, lower IMFF, and higher FMF. In multivariable analysis for 2- and 3-year survival, only ECOG and FMF remained significant. CONCLUSION: CT-based markers of sarcopenia and myosteatosis show a prognostic value for assessment of survival in advanced pancreatic cancer patients undergoing HIFU therapy. CLINICAL RELEVANCE STATEMENT: The results indicate a greater role of myosteatosis for additional risk assessment beyond clinical scores, as only FMF was associated with long-term survival in multivariable CPH analyses along ECOG and also showed independence to ECOG in group analysis. KEY POINTS: • This study investigates the prognostic value of CT-based markers of sarcopenia and myosteatosis for patients with pancreatic cancer treated with high-intensity focused ultrasound. • Markers for sarcopenia and myosteatosis showed a prognostic value besides clinical assessment of the physical status by the Eastern Cooperative Oncology Group score. In contrast to muscle size measurements, the myosteatosis marker fatty muscle fraction demonstrated independence to the clinical score. • The results indicate that myosteatosis might play a greater role for additional patient risk assessments beyond clinical assessments of physical status.

Prospective effects of an artificial intelligence-based computer-aided detection system for prostate imaging on routine workflow and radiologists' outcomes.

OBJECTIVES: Artificial intelligence (AI) is expected to alleviate the negative consequences of rising case numbers for radiologists. Currently, systematic evaluations of the impact of AI solutions in real-world radiological practice are missing. Our study addresses this gap by investigating the impact of the clinical implementation of an AI-based computer-aided detection system (CAD) for prostate MRI reading on clinicians' workflow, workflow throughput times, workload, and stress. MATERIALS AND METHODS: CAD was newly implemented into radiology workflow and accompanied by a prospective pre-post study design. We assessed prostate MRI case readings using standardized work observations and questionnaires. The observation period was three months each in a single department. Workflow throughput times, PI-RADS score, CAD usage and radiologists' self-reported workload and stress were recorded. Linear mixed models were employed for effect identification. RESULTS: In data analyses, 91 observed case readings (pre: 50, post: 41) were included. Variation of routine workflow was observed following CAD implementation. A non-significant increase in overall workflow throughput time was associated with CAD implementation (mean 16.99 ± 6.21 vs 18.77 ± 9.69 min, p = .51), along with an increase in diagnostic reading time for high suspicion cases (mean 15.73 ± 4.99 vs 23.07 ± 8.75 min, p = .02). Changes in radiologists' self-reported workload or stress were not found. CONCLUSION: Implementation of an AI-based detection aid was associated with lower standardization and no effects over time on radiologists' workload or stress. Expectations of AI decreasing the workload of radiologists were not confirmed by our real-world study. PRE-REGISTRATION: German register for clinical trials https://drks.de/; DRKS00027391.

Opportunistic CT-derived analysis of fat and muscle tissue composition predicts mortality in patients with cardiogenic shock.

Prognosis estimation in patients with cardiogenic shock (CS) is important to guide clinical decision making. Aim of this study was to investigate the predictive value of opportunistic CT-derived body composition analysis in CS patients. Amount and density of fat and muscle tissue of 152 CS patients were quantified from single-slice CT images at the level of the intervertebral disc space L3/L4. Multivariable Cox regression and Kaplan-Meier survival analyses were performed to evaluate the predictive value of opportunistically CT-derived body composition parameters on the primary endpoint of 30-day mortality. Within the 30-day follow-up, 90/152 (59.2%) patients died. On multivariable analyses, lactate (Hazard Ratio 1.10 [95% Confidence Interval 1.04-1.17]; p = 0.002) and patient age (HR 1.04 [95% CI 1.01-1.07], p = 0.017) as clinical prognosticators, as well as visceral adipose tissue (VAT) area (HR 1.004 [95% CI 1.002-1.007]; p = 0.001) and skeletal muscle (SM) area (HR 0.987 [95% CI 0.975-0.999]; p = 0.043) as imaging biomarkers remained as independent predictors of 30-day mortality. Kaplan-Meier survival analyses showed significantly increased 30-day mortality in patients with higher VAT area (p = 0.015) and lower SM area (p = 0.035). CT-derived VAT and SM area are independent predictors of dismal outcomes in CS patients and have the potential to emerge as new imaging biomarkers available from routine diagnostic CT.

Prevention of cerebral thromboembolism by oral anticoagulation with dabigatran after pulmonary vein isolation for atrial fibrillation: the ODIn-AF trial.

BACKGROUND AND OBJECTIVES: Long-term oral anticoagulation (OAC) following successful catheter ablation of atrial fibrillation (AF) remains controversial. Prospective data are missing. The ODIn-AF study aimed to evaluate the effect of OAC on the incidence of silent cerebral embolic events and clinically relevant cardioembolic events in patients at intermediate to high risk for embolic events, free from AF after pulmonary vein isolation (PVI). METHODS: This prospective, randomized, multicenter, open-label, blinded endpoint interventional trial enrolled patients who were scheduled for PVI to treat paroxysmal or persistent AF. Six months after PVI, AF-free patients were randomized to receive either continued OAC with dabigatran or no OAC. The primary endpoint was the incidence of new silent micro- and macro-embolic lesions detected on brain MRI at 12 months of follow-up compared to baseline. Safety analysis included bleedings, clinically evident cardioembolic, and serious adverse events (SAE). RESULTS: Between 2015 and 2021, 200 patients were randomized into 2 study arms (on OAC: n = 99, off OAC: n = 101). There was no significant difference in the occurrence of new cerebral microlesions between the on OAC and off OAC arm [2 (2%) versus 0 (0%); P = 0.1517] after 12 months. MRI showed no new macro-embolic lesion, no clinical apparent strokes were present in both groups. SAE were more frequent in the OAC arm [on OAC n = 34 (31.8%), off OAC n = 18 (19.4%); P = 0.0460]; bleedings did not differ. CONCLUSION: Discontinuation of OAC after successful PVI was not found to be associated with an elevated risk of cerebral embolic events compared with continued OAC after a follow-up of 12 months.

Post-interventional infectious complications in percutaneous transabdominal lymphatic interventions: an observational study.

The purpose of this retrospective study was to evaluate the occurrence of infectious complications and inflammatory reactions after transabdominal lymphatic-interventions. 63 lymphatic-interventions were performed in 60 patients (male/female: 35/25; mean age 56 [9-85] years) [chylothorax n = 48, chylous ascites n = 7, combined chylothorax/chylous ascites n = 5]. Post-interventional clinical course and laboratory findings were analyzed in the whole cohort as well as subgroups without (group A; n = 35) and with peri-interventional antibiotics (group B; n = 25) (pneumonia n = 16, drainage-catheter inflammation n = 5, colitis n = 1, cystitis n = 1, transcolonic-access n = 2). No septic complications associated with the intervention occurred. Leucocytes increased significantly, peaking on post-interventional day-1 (8.6 ± 3.9 × 106 cells/mL vs. 9.8 ± 4.7 × 106 cells/mL; p = 0.009) and decreased thereafter (day-10: 7.3 ± 2.7 × 106 cells/mL, p = 0.005). CRP-values were pathological in 89.5% of patients already at baseline (40.1 ± 63.9 mg/L) and increased significant on day-3 (77.0 ± 78.8 mg/L, p < 0.001). Values decreased thereafter (day-15: 25.3 ± 34.4 mg/L, p = 0.04). In subgroup B, 13/25 patients had febrile episodes post-interventionally (pneumonia n = 11, cystitis n = 1, drainage-catheter inflammation n = 1). One patient developed biliary peritonitis despite continued antibiotics and underwent cholecystectomy. Baseline leucocytes and CRP-levels were higher in group B than A, but with comparable post-interventional profiles. Clinically relevant infectious complications associated with transabdominal lymphatic-interventions are rare irrespective of peri-interventional antibiotic use. Post-interventional elevation of leucocytes and CRP are observed with normalization over 10-15 days.

Direct deep learning-based survival prediction from pre-interventional CT prior to transcatheter aortic valve replacement.

PURPOSE: To investigate survival prediction in patients undergoing transcatheter aortic valve replacement (TAVR) using deep learning (DL) methods applied directly to pre-interventional CT images and to compare performance with survival models based on scalar markers of body composition. METHOD: This retrospective single-center study included 760 patients undergoing TAVR (mean age 81 ± 6 years; 389 female). As a baseline, a Cox proportional hazards model (CPHM) was trained to predict survival on sex, age, and the CT body composition markers fatty muscle fraction (FMF), skeletal muscle radiodensity (SMRD), and skeletal muscle area (SMA) derived from paraspinal muscle segmentation of a single slice at L3/L4 level. The convolutional neural network (CNN) encoder of the DL model for survival prediction was pre-trained in an autoencoder setting with and without a focus on paraspinal muscles. Finally, a combination of DL and CPHM was evaluated. Performance was assessed by C-index and area under the receiver operating curve (AUC) for 1-year and 2-year survival. All methods were trained with five-fold cross-validation and were evaluated on 152 hold-out test cases. RESULTS: The CNN for direct image-based survival prediction, pre-trained in a focussed autoencoder scenario, outperformed the baseline CPHM (CPHM: C-index = 0.608, 1Y-AUC = 0.606, 2Y-AUC = 0.594 vs. DL: C-index = 0.645, 1Y-AUC = 0.687, 2Y-AUC = 0.692). Combining DL and CPHM led to further improvement (C-index = 0.668, 1Y-AUC = 0.713, 2Y-AUC = 0.696). CONCLUSIONS: Direct DL-based survival prediction shows potential to improve image feature extraction compared to segmentation-based scalar markers of body composition for risk assessment in TAVR patients.

Long-Term Clinical Outcome of Abdomino-Thoracic Lymphatic Interventions of Traumatic and Non-Traumatic Lymphatic Leakage in Adults.

The aim of this study was to retrospectively evaluate the long-term results of lymphatic interventions in adults with abdomino-thoracic lymphatic pathologies. Management of abdomino-thoracic chylous effusions in adults undergoing X-ray-lymphangiography with or without lymph-vessel embolization (LVE) from 2010-2018 was reviewed. Patients underwent lymphangiography alone when imaging showed normal findings or lymphatic obstruction without leakage or reflux; otherwise, LVE was performed (leakage, reflux, obstruction with leakage or reflux, lymphatic masses). Technical and clinical success, complications, and long-term outcomes were assessed. 78 patients (47 male, median age 56.3 years) were treated for chylous effusions (60.3% traumatic, 39.7% non-traumatic). Lymphangiography showed leakage (48.7%), reflux (14.1%), obstruction (28.2%), lymphatic masses (5.1%), and normal findings (3.8%). Embolization was performed in 49/78 (62.8%) cases. Overall, treatment was clinically successful in 74.4% (mean follow-up of 28 months), with significant differences between LVE and lymphangiography (91.8% vs. 44.8%; p < 0.001), traumatic and non-traumatic etiologies (89.4% vs. 51.6%; p < 0.001), and leakage locations (p = 0.003). The clinical success of LVE did not differ between leakage etiologies or locations. Complications occurred in 5 patients (2/5 needed treatment). Patients survived significantly longer after successful treatment (2679 vs. 927 days; p = 0.044) and without malignancy (3214 vs. 1550 days; p = 0.043). Lymphatic interventions are safe and effective. LVE should be attempted whenever feasible, as success is high (>90%). Successful intervention has a positive effect on patient survival.