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Background & Aims: Spontaneous portosystemic shunts (SPSS) frequently develop in liver cirrhosis. Recent data suggested that the presence of a single large SPSS is associated with complications, especially overt hepatic encephalopathy (oHE). However, the presence of >1 SPSS is common. This study evaluates the impact of total cross-sectional SPSS area (TSA) on outcomes in patients with liver cirrhosis.
Methods: In this retrospective international multicentric study, CT scans of 908 cirrhotic patients with SPSS were evaluated for TSA. Clinical and laboratory data were recorded. Each detected SPSS radius was measured and TSA calculated. One-year survival was the primary endpoint and acute decompensation (oHE, variceal bleeding, ascites) was the secondary endpoint.
Results: A total of 301 patients (169 male) were included in the training cohort. Thirty percent of all patients presented with >1 SPSS. A TSA cut-off of 83 mm2 was used to classify patients with small or large TSA (S-/L-TSA). Patients with L-TSA presented with higher model for end-stage liver disease score (11 vs. 14) and more commonly had a history of oHE (12% vs. 21%, p <0.05). During follow-up, patients with L-TSA experienced more oHE episodes (33% vs. 47%, p <0.05) and had lower 1-year survival than those with S-TSA (84% vs. 69%, p <0.001). Multivariate analysis identified L-TSA (hazard ratio 1.66; 95% CI 1.02–2.70, p <0.05) as an independent predictor of mortality. An independent multicentric validation cohort of 607 patients confirmed that patients with L-TSA had lower 1-year survival (77% vs. 64%, p <0.001) and more oHE development (35% vs. 49%, p <0.001) than those with S-TSA.
Conclusion: This study suggests that TSA >83 mm2 increases the risk for oHE and mortality in patients with cirrhosis. Our results support the clinical use of TSA/SPSS for risk stratification and decision-making in the management of patients with cirrhosis.
Lay summary: The prevalence of spontaneous portosystemic shunts (SPSS) is higher in patients with more advanced chronic liver disease. The presence of more than 1 SPSS is common in advanced chronic liver disease and is associated with the development of hepatic encephalopathy. This study shows that total cross-sectional SPSS area (rather than diameter of the single largest SPSS) predicts survival in patients with advanced chronic liver disease. Our results support the clinical use of total cross-sectional SPSS area for risk stratification and decision-making in the management of SPSS.
Inflammatory nontraumatic atlantoaxial rotatory subluxation (AAS) in children is an often-missed diagnosis, especially in the early stages of disease. Abscess formation and spinal cord compression are serious risks that call for immediate surgical attention. Neither radiographs nor non-enhanced computed tomography (CT) images sufficiently indicate inflammatory processes. Magnetic resonance imaging (MRI) allows a thorough evaluation of paraspinal soft tissues, joints, and ligaments. In addition, it can show evidence of vertebral distraction and spinal cord compression. After conducting a scoping review of the literature, along with scientific and practical considerations, we outlined a standardized pediatric MRI protocol for suspected inflammatory nontraumatic AAS. We recommend contrast-enhanced MRI as the primary diagnostic imaging modality in children with signs of torticollis in combination with nasopharyngeal inflammatory or ear nose and throat (ENT) surgical history.
Simple Summary: Early and accurate diagnosis of breast cancer that has spread to other organs and tissues is crucial, as therapeutic decisions and outcome expectations might change. Computed tomography (CT) is often used to detect breast cancer’s spread, but this method has its weaknesses. The computer-assisted technique “radiomics” extracts grey-level patterns, so-called radiomic features, from medical images, which may reflect underlying biological processes. Our retrospective study therefore evaluated whether breast cancer spread can be predicted by radiomic features derived from iodine maps, an application on a new generation of CT scanners visualizing tissue blood flow. Based on 77 patients with newly diagnosed breast cancer, we found that this approach might indeed predict cancer spread to other organs/tissues. In the future, radiomics may serve as an additional tool for cancer detection and risk assessment.
Abstract: Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differ- ences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.
Background: Computed tomography of the head (HCT) is a widely used diagnostic tool, especially for emergency and trauma patients. However, the diagnostic yield and outcomes of HCT for patients on medical intensive care units (MICUs) are largely unknown.
Methods: We retrospectively evaluated all head CTs from patients admitted to a single-center MICU during a 5-year period for CT indications, diagnostic yield, and therapeutic consequences. Uni- and multivariate analyses for the evaluation of risk factors for positive head CT were conducted.
Results: Six hundred ninety (18.8%) of all patients during a 5-year period underwent HCT; 78.7% had negative CT results, while 21.3% of all patients had at least 1 new pathological finding. The main indication for acquiring CT scan of the head was an altered mental state (AMS) in 23.5%, followed by a new focal neurology in 20.7% and an inadequate wake up after stopping sedation in 14.9% of all patients. The most common new finding was intracerebral bleeding in 6.4%. In 6.7%, the CT scan itself led to a change of therapy of any kind. Admission after resuscitation or a new focal neurology were independent predictors of a positive CT. Psychic alteration and AMS were both independent predictors of a higher chance of a negative head CT. Positive HCT during MICU is an independent predictor of lower survival.
Conclusions: New onset of focal neurologic deficit seems to be a good predictor for a positive CT, while AMS and psychic alterations seem to be very poor predictors. A positive head CT is an independent predictor of death for MICU patients.