DNA-Doppelstrangbrüche nach interventionsradiologischen Eingriffen

Ionisierende Strahlung kann zu einer Reihe von schädigenden Effekten beim Menschen führen, der wichtigste darunter ist die Induktion eines malignen Zellwachstums (Krebs). DNA-Doppelstrangbrüche gehören dabei zu den bedeutendsten Schäden und können die Karzinogenese initiieren. Es wurde in der letzten Zeit in mehreren Studien gezeigt, dass die Immunfluoreszenzdarstellung von γ‐H2AX‐Foci in vivo bei Lymphozyten zur Quantifizierung von DNA‐Doppelstrangbrüchen anwendbar ist und der Verlust von γ‐H2AX-Foci mit Reparatur der DNA‐Doppelstrangbrüche korreliert. Eine bedeutende Quelle ionisierender Strahlung in der Medizin ist die interventionelle Radiologie, deren kumulative Dosis sich laut der RAD‐IR Studie für verschiedene interventionsradiologische Maßnahmen im Bereich von 1.284 mGy bei einer perkutanen transluminalen Angioplastie (PTA) bewegt. Bei einem interventionsradiologischen Eingriff wird der Patient im Allgemeinen über einen deutlich längeren Zeitraum (bis zu einer Stunde) ionisierender Strahlung ausgesetzt als bei konventionellen Röntgenaufnahmen oder während einer Computertomographie. Als Vergleichsgruppe wurde bei 5 Patienten (2 Frauen, 3 Männer) im Alter von durchschnittlich 64,6 Jahren die Rate an DNA‐Doppelstrangbrüchen nach einer Computertomographie (CT) zu folgenden Zeitpunkten untersucht: vor der CT sowie 5 min, 1 h, 6 h und 24 h nach der CT. Bei 20 Patienten (6 Frauen, 14 Männer) im Alter von durchschnittlich 68,5 Jahren wurde die Rate an DNA‐Doppelstrangbrüchen nach einer perkutanen transluminalen Angioplastie (PTA) der unteren Extremität zu folgenden Zeitpunkten untersucht: vor der PTA sowie 5 min, 1 h, 6 h und 24 h nach der PTA. Bei 3 Patienten erfolgte zusätzliche eine Blutentnahme direkt aus der bestrahlten Extremität. Bei der Computertomographie betrug die Dosiszunahme in der Blutprobe 5 min nach CT im Vergleich zur Blutprobe vor CT hochgerechnet pro 1.000 mGy∙cm durchschnittlich 7,78 ± 0,37 (Mittelwert ± Standardfehler des Mittelwertes [SEM]). Der Korrelationskoeffizient zwischen DLP und Focizunahme nach Bravais‐Pearson (r) betrug 0,997. Nach 24 h zeigt sich eine vollständige Reparatur der Doppelstrangbrüche. Diese Ergebnisse liegen im Bereich der Ergebnisse anderer Arbeitsgruppen, ebenso die Reparaturkinetik. Bei der perkutanen transluminalen Angioplastie zeigten sind deutliche Unterschiede im Vergleich zur Computertomographie. Die Dosiszunahme in der Blutprobe 5 min nach PTA im Vergleich zu unmittelbar vor der PTA betrug hochgerechnet pro 10 Gy∙cm2 durchschnittlich6,56 ± 0,48 (Mittelwert ± SEM). Das Dosisflächenprodukt (DFP) korrelierte gut mit der Dosiszunahme, r betrug 0,993. Im Gegensatz zu den Beobachtungen nach CT beobachtete man hierbei eine unvollständige Reparatur der DNA‐Doppelstrangbrüche nach 24 h. Das durchschnittliche Verhältnis der γ‐H2AX‐Foci pro Zelle 24 h nach PTA im Vergleich zu unmittelbar vor PTA entspricht einem Niveau von 149 % ± 37 % des Ausgangswertes (P einseitig = 0,0091). Die Kinetik der Abnahme der Foci war dabei bei allen 20 Patienten vergleichbar. Es konnte weiterhin nachgewiesen werden, dass der maximale Wert der Dosiszunahme in den Lymphozyten, die direkt aus dem Blutabfluss der behandelten Extremität entnommen wurden, im Vergleich zu den Lymphozyten aus dem systemischen Kreislauf durchschnittlich um den Faktor 1,46 ± 0,20 höher war. Die Immunfluoreszenzdarstellung von γ‐H2AX‐Foci eignet sich zur Darstellung der Formierung und der Reparatur von DNA‐Doppelstrangbrüchen nach perkutaner transluminaler Angioplastie. Zur Interpretation der Ergebnisse müssen aber möglicherweise noch andere Effekte berücksichtigt werden, als die bloße Kumulation der Strahlendosis. Beispielsweise sollen hier der Bystander‐Effekt (Shao et al. 2004; Sedelnikova et al. 2007) oder die höhere Radiosensitivität gegenüber geringen Dosen ionisierender Strahlung und die unvollständige Reparatur von DNA‐Doppelstrangbrüchen nach Strahlendosis im Bereich von 1 mGy angeführt werden

Impact of quantitative pulmonary emphysema score on the rate of pneumothorax and chest tube insertion in CT-guided lung biopsies

The aim of this study was to evaluate the risk of pneumothorax and need for chest tube insertion in CT-guided lung biopsies and identify predictors focusing on pulmonary emphysema determined with quantitative computed tomography. To that end, we retrospectively analysed the incidence of pneumothorax and chest tube insertion in 371 CT-guided lung biopsies with respect to the quantitative emphysema score determined with the density mask technique. Other possible impact factors considered were lesion diameter, length of biopsy pathway within the lung parenchyma, lung lobe, needle size, puncture technique, patient positioning and interventionalist’s level of experience. Quantitative emphysema scores of the lung were significantly higher in patients who developed instant pneumothorax (27%, p < 0.0001), overall pneumothorax (38%, p = 0.001) and had chest tube insertion (9%, p = 0.006) compared to those who did not when analysed with the Mann–Whitney U-test. In logistic regression analysis with inclusion of the other possible impact factors, the quantitative emphysema score remained a statistically significant predictor for all three output parameters. This was confirmed with least absolute shrinkage and selection operator (Lasso) regression analysis. In conclusion, quantitatively determined pulmonary emphysema is a positive predictor of the pneumothorax rate in CT-guided lung biopsy and likelihood of chest tube insertion

Impact of interventionalist’s experience and gender on radiation dose and procedural time in CT-guided interventions—a retrospective analysis of 4380 cases over 10 years

Objectives: To investigate the impact of the interventionalist's experience and gender on radiation dose and procedural time in CT-guided interventions. Methods: We retrospectively analyzed 4380 CT-guided interventions performed at our institution with the same CT scanner from 2009 until 2018, 1287 (29%) by female and 3093 (71%) by male interventionalists. Radiation dose, number of CT fluoroscopy images taken per intervention, total procedural time, type of intervention, and degree of difficulty were derived from the saved dose reports and images. All 16 interventionalists included in this analysis performed their first CT-guided interventions during the study period, and interventions performed by each interventionalist were counted to assess the level of experience for each intervention in terms of the number of prior interventions performed by her or him. The Mann-Whitney U test (MWU test), multivariate regression, and linear mixed model analysis were performed. Results: Assessment of the impact of gender with the MWU test revealed that female interventionalists took a significantly smaller number of images (p < 0.0001) and achieved a lower dose-length product per intervention (p < 0.0001) while taking more time per intervention (p = 0.0001). This finding was confirmed for most types of interventions when additionally accounting for other possible impact factors in multivariate regression analysis. In linear mixed model analysis, we found that radiation dose, number of images taken per intervention, and procedural time decreased statistically significantly with interventionalist's experience. Conclusions: Radiation doses of CT-guided interventions are reduced by interventionalist's experience and, for most types of interventions, when performed by female interventionalists. Key points: • Radiation doses in CT-guided interventions are lower when performed by female interventionalists. • Procedural times of CT-guided interventions are longer when performed by female interventionalists. • Radiation doses of CT-guided interventions decrease with the interventionalist's experience

A radiomics-based model to classify the etiology of liver cirrhosis using gadoxetic acid-enhanced MRI

The implementation of radiomics in radiology is gaining interest due to its wide range of applications. To develop a radiomics-based model for classifying the etiology of liver cirrhosis using gadoxetic acid-enhanced MRI, 248 patients with a known etiology of liver cirrhosis who underwent 306 gadoxetic acid-enhanced MRI examinations were included in the analysis. MRI examinations were classified into 6 groups according to the etiology of liver cirrhosis: alcoholic cirrhosis, viral hepatitis, cholestatic liver disease, nonalcoholic steatohepatitis (NASH), autoimmune hepatitis, and other. MRI examinations were randomized into training and testing subsets. Radiomics features were extracted from regions of interest segmented in the hepatobiliary phase images. The fivefold cross-validated models (2-dimensional-(2D) and 3-dimensional-(3D) based) differentiating cholestatic cirrhosis from noncholestatic etiologies had the best accuracy (87.5%, 85.6%), sensitivity (97.6%, 95.6%), predictive value (0.883, 0.877), and area under curve (AUC) (0.960, 0.910). The AUC was larger in the 2D-model for viral hepatitis, cholestatic cirrhosis, and NASH-associated cirrhosis (P-value of 0.05, 0.05, 0.87, respectively). In alcoholic cirrhosis, the AUC for the 3D model was larger (P=0.01). The overall intra-class correlation coefficient (ICC) estimates and their 95% confident intervals (CI) for all features combined was 0.68 (CI 0.56-0.87) for 2D and 0.71 (CI 0.61-0.93) for 3D measurements suggesting moderate reliability. Radiomics-based analysis of hepatobiliary phase images of gadoxetic acid-enhanced MRI may be a promising noninvasive method for identifying the etiology of liver cirrhosis with better performance of the 2D- compared with the 3D-generated models

Artificial intelligence‐based analysis of body composition in Marfan: skeletal muscle density and psoas muscle index predict aortic enlargement

Background: Patients with Marfan syndrome are at risk for aortic enlargement and are routinely monitored by computed tomography (CT) imaging. The purpose of this study is to analyse body composition using artificial intelligence (AI)-based tissue segmentation in patients with Marfan syndrome in order to identify possible predictors of progressive aortic enlargement. Methods: In this study, the body composition of 25 patients aged <= 50 years with Marfan syndrome and no prior aortic repair was analysed at the third lumbar vertebra (L3) level from a retrospective dataset using an AI-based software tool (Visage Imaging). All patients underwent electrocardiography-triggered CT of the aorta twice within 2 years for suspected progression of aortic disease, suspected dissection, and/or pre-operative evaluation. Progression of aortic enlargement was defined as an increase in diameter at the aortic sinus or the ascending aorta of at least 2 mm. Patients meeting this definition were assigned to the 'progressive aortic enlargement' group (proAE group) and patients with stable diameters to the 'stable aortic enlargement' group (staAE group). Statistical analysis was performed using the Mann-Whitney U test. Two possible body composition predictors of aortic enlargement-skeletal muscle density (SMD) and psoas muscle index (PMI)-were analysed further using multivariant logistic regression analysis. Aortic enlargement was defined as the dependent variant, whereas PMI, SMD, age, sex, body mass index (BMI), beta blocker medication, and time interval between CT scans were defined as independent variants. Results: There were 13 patients in the proAE group and 12 patients in the staAE group. AI-based automated analysis of body composition at L3 revealed a significantly increased SMD measured in Hounsfield units (HUs) in patients with aortic enlargement (proAE group: 50.0 +/- 8.6 HU vs. staAE group: 39.0 +/- 15.0 HU; P = 0.03). PMI also trended towards higher values in the proAE group (proAE group: 6.8 +/- 2.3 vs. staAE group: 5.6 +/- 1.3; P = 0.19). Multivariate logistic regression revealed significant prediction of aortic enlargement for SMD (P = 0.05) and PMI (P = 0.04). Conclusions: Artificial intelligence-based analysis of body composition at L3 in Marfan patients is feasible and easily available from CT angiography. Analysis of body composition at L3 revealed significantly higher SMD in patients with progressive aortic enlargement. PMI and SMD significantly predicted aortic enlargement in these patients. Using body composition as a predictor of progressive aortic enlargement may contribute information for risk stratification regarding follow-up intervals and the need for aortic repair

Added Value of Tomoelastography for Characterization of Pancreatic Neuroendocrine Tumor Aggressiveness Based on Stiffness

Simple Summary: The prediction of pancreatic neuroendocrine tumor (PNET) aggressiveness is important for treatment planning. The aim of this study was to evaluate the diagnostic performance of magnetic resonance elastography (MRE) with tomoelastography postprocessing (tomoelastography) in differentiating PNET from healthy pancreatic tissue and to correlate PNET stiffness with aggressiveness using asphericity derived from positron emission tomography (PET) as reference. In this prospective study we showed in a group of 13 patients with PNET that tomoelastography detected PNET by increased stiffness (p < 0.01) with a high diagnostic performance (AUC = 0.96). PNET was positively correlated with PET derived asphericity (r = 0.81). Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness. Abstract: Purpose: To evaluate the diagnostic performance of tomoelastography in differentiating pancreatic neuroendocrine tumors (PNETs) from healthy pancreatic tissue and to assess the prediction of tumor aggressiveness by correlating PNET stiffness with PET derived asphericity. Methods: 13 patients with PNET were prospectively compared to 13 age-/sex-matched heathy volunteers (CTR). Multifrequency MR elastography was combined with tomoelastography-postprocessing to provide high-resolution maps of shear wave speed (SWS in m/s). SWS of pancreatic neuroendocrine tumor (PNET-T) were compared with nontumorous pancreatic tissue in patients with PNET (PNET-NT) and heathy pancreatic tissue (CTR). The diagnostic performance of tomoelastography was evaluated by ROC-AUC analysis. PNET-SWS correlations were calculated with Pearson’s r. Results: SWS was higher in PNET-T (2.02 ± 0.61 m/s) compared to PNET-NT (1.31 ± 0.18 m/s, p < 0.01) and CTR (1.26 ± 0.09 m/s, p < 0.01). An SWS-cutoff of 1.46 m/s distinguished PNET-T from PNET-NT (AUC = 0.89; sensitivity = 0.85; specificity = 0.92) and a cutoff of 1.49 m/s differentiated pancreatic tissue of CTR from PNET-T (AUC = 0.96; sensitivity = 0.92; specificity = 1.00). The SWS of PNET-T was positively correlated with PET derived asphericity (r = 0.81; p = 0.01). Conclusions: Tomoelastography provides quantitative imaging markers for the detection of PNET and the prediction of greater tumor aggressiveness by increased stiffness

Postoperative single-sequence (PoSSe) MRI: imaging work-up for CT-guided or endoscopic drainage indication of collections after hepatopancreaticobiliary surgery

Purpose: Fluid collections due to anastomotic leakage are a common complication after hepatopancreaticobiliary (HPB) surgery and are usually treated with drainage. We conducted a study to evaluate imaging work-up with a postoperative single-sequence (PoSSe) MRI for the detection of collections and indication of drainage. Material and methods: Forty-six patients who developed signs of leakage (fever, pain, laboratory findings) after HPB surgery were prospectively enrolled. Each patient was examined by abdominal sonography and our PoSSe MRI protocol (axial T2-weighted HASTE only). PoSSe MRI examination time (from entering to leaving the MR scanner room) was measured. Sonography and MRI were evaluated regarding the detection and localization of fluid collections. Each examination was classified for diagnostic sufficiency and an imaging-based recommendation if CT-guided or endoscopic drainage is reasonable or not was proposed. Imaging work-up was evaluated in terms of feasibility and the possibility of drainage indication. Results: Sonography, as first-line modality, detected 21 focal fluid collections and allowed to decide about the need for drainage in 41% of patients. The average time in the scanning room for PoSSe MRI was 9:23 min [7:50-13:32 min]. PoSSe MRI detected 46 focal collections and allowed therapeutic decisions in all patients. Drainage was suggested based on PoSSe MRI in 25 patients (54%) and subsequently indicated and performed in 21 patients (100% sensitivity and 84% specificity). No patient needed further imaging to optimize the treatment. Conclusions: The PoSSe MRI approach is feasible in the early and intermediate postoperative setting after HPB surgery and shows a higher detection rate than sonography. Imaging work-up regarding drainage of collections was successful in all patients and our proposed PoSSe MRI algorithm provides an alternative to the standard work-up

Does Hepatic Steatosis Influence the Detection Rate of Metastases in the Hepatobiliary Phase of Gadoxetic Acid-Enhanced MRI?

The aim of this exploratory study was to evaluate the influence of hepatic steatosis on the detection rate of metastases in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI). A total of 50 patients who underwent gadoxetic acid-enhanced MRI (unenhanced T1w in- and opposed-phase, T2w fat sat, unenhanced 3D-T1w fat sat and 3-phase dynamic contrast-enhanced (uDP), 3D-T1w fat sat hepatobiliary phase (HP)) were retrospectively included. Two blinded observers (O1/O2) independently assessed the images to determine the detection rate in uDP and HP. The hepatic signal fat fraction (HSFF) was determined as the relative signal intensity reduction in liver parenchyma from in- to opposed-phase images. A total of 451 liver metastases were detected (O1/O2, n = 447/411). O1/O2 detected 10.9%/9.3% of lesions exclusively in uDP and 20.2%/15.5% exclusively in HP. Lesions detected exclusively in uDP were significantly associated with a larger HSFF (area under curve (AUC) of receiver operating characteristic (ROC) analysis, 0.93; p 30%) is a potential pitfall for the detection of metastases in HP

Hepatocellular adenomas: is there additional value in using Gd-EOB-enhanced MRI for subtype differentiation?

Purpose: To differentiate subtypes of hepatocellular adenoma (HCA) based on enhancement characteristics in gadoxetic acid (Gd-EOB) magnetic resonance imaging (MRI). Materials and methods: Forty-eight patients with 79 histopathologically proven HCAs who underwent Gd-EOB-enhanced MRI were enrolled (standard of reference: surgical resection). Two blinded radiologists performed quantitative measurements (lesion-to-liver enhancement) and evaluated qualitative imaging features. Inter-reader variability was tested. Advanced texture analysis was used to evaluate lesion heterogeneity three-dimensionally. Results: Overall, there were 19 (24%) hepatocyte nuclear factor (HNF)-1a-mutated (HHCAs), 37 (47%) inflammatory (IHCAs), 5 (6.5%) b-catenin-activated (bHCA), and 18 (22.5%) unclassified (UHCAs) adenomas. In the hepatobiliary phase (HBP), 49.5% (39/79) of all adenomas were rated as hypointense and 50.5% (40/79) as significantly enhancing (defined as > 25% intralesional GD-EOB uptake). 82.5% (33/40) of significantly enhancing adenomas were IHCAs, while only 4% (1/40) were in the HHCA subgroup (p < 0.001). When Gd-EOB uptake behavior was considered in conjunction with established MRI features (binary regression model), the area under the curve (AUC) increased from 0.785 to 0.953 for differentiation of IHCA (atoll sign + hyperintensity), from 0.859 to 0.903 for bHCA (scar + hyperintensity), and from 0.899 to 0.957 for HHCA (steatosis + hypointensity). Three-dimensional region of interest (3D ROI) analysis showed significantly increased voxel heterogeneity for IHCAs (p = 0.038). Conclusion: Gd-EOB MRI is of added value for subtype differentiation of HCAs and reliably identifies the typical heterogeneous HBP uptake of IHCAs. Diagnostic accuracy can be improved significantly by the combined analysis of established morphologic MR appearances and intralesional Gd-EOB uptake. Key points: •Gd-EOB-enhanced MRI is of added value for subtype differentiation of HCA. •IHCA and HHCA can be identified reliably based on their typical Gd-EOB uptake patterns, and accuracy increases significantly when additionally taking established MR appearances into account. •The small numbers of bHCAs and UHCAs remain the source of diagnostic uncertainty

Effects of Artificial Intelligence-Derived Body Composition on Kidney Graft and Patient Survival in the Eurotransplant Senior Program

The Eurotransplant Senior Program allocates kidneys to elderly transplant patients. The aim of this retrospective study is to investigate the use of computed tomography (CT) body composition using artificial intelligence (AI)-based tissue segmentation to predict patient and kidney transplant survival. Body composition at the third lumbar vertebra level was analyzed in 42 kidney transplant recipients. Cox regression analysis of 1-year, 3-year and 5-year patient survival, 1-year, 3-year and 5-year censored kidney transplant survival, and 1-year, 3-year and 5-year uncensored kidney transplant survival was performed. First, the body mass index (BMI), psoas muscle index (PMI), skeletal muscle index (SMI), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) served as independent variates. Second, the cut-off values for sarcopenia and obesity served as independent variates. The 1-year uncensored and censored kidney transplant survival was influenced by reduced PMI (p = 0.02 and p = 0.03, respectively) and reduced SMI (p = 0.01 and p = 0.03, respectively); 3-year uncensored kidney transplant survival was influenced by increased VAT (p = 0.04); and 3-year censored kidney transplant survival was influenced by reduced SMI (p = 0.05). Additionally, sarcopenia influenced 1-year uncensored kidney transplant survival (p = 0.05), whereas obesity influenced 3-year and 5-year uncensored kidney transplant survival. In summary, AI-based body composition analysis may aid in predicting short- and long-term kidney transplant survival