Pleural and pericardial effusions as prognostic factors in patients with acute pulmonary embolism: a multicenter study.

PURPOSE: The prognostic role of pleural and pericardial effusion in patients with acute pulmonary embolism (PE) is still unclear with a trend for worse clinical outcome. The aim of the present study was to demonstrate the prognostic role of pleural and pericardial effusion in patients with acute PE in a large multicentre setting. METHODS: The investigated patient sampled was retrospectively comprised of 1082 patients (494 female, 45.7%) with a mean age of 63.8 years ± 15.8. In every case, contrast enhanced computed tomography (CT) pulmonalis angiography was analyzed to diagnose and quantify the pleural and pericardial effusion. The 30-day mortality was the primary endpoint of this study. RESULTS: A total of 127 patients (11.7%) died within the 30-day observation period. Pleural effusion was identified in 438 patients (40.5%) and pericardial effusion was identified in 196 patients (18.1%). The presence of pleural effusion was associated with 30-day mortality, HR = 2.78 (95%CI1.89-4.0), p < 0.001 (univariable analysis), and HR = 2.52 (95%CI1.69-3.76), p < 0.001 (multivariable analysis). The pleural effusion width and density were not associated with 30-day mortality. The presence of pericardial effusion was not associated with 30-day mortality in multivariable analysis, HR = 1.28 (95%CI 0.80-2.03), p = 0.29. CONCLUSIONS: Pleural effusion is a common finding in patients with acute pulmonary embolism, occurring in 40.5% of cases, and is a prognostic imaging finding associated with 30-day mortality. The presence of pleural effusion alone, regardless of volume or density, has been shown to be prognostic and should be included in CT reports. The prognostic role of pericardial effusion is limited.

Development and performance evaluation of fully automated deep learning-based models for myocardial segmentation on T1 mapping MRI data.

To develop a deep learning-based model capable of segmenting the left ventricular (LV) myocardium on native T1 maps from cardiac MRI in both long-axis and short-axis orientations. Models were trained on native myocardial T1 maps from 50 healthy volunteers and 75 patients using manual segmentation as the reference standard. Based on a U-Net architecture, we systematically optimized the model design using two different training metrics (Sørensen-Dice coefficient = DSC and Intersection-over-Union = IOU), two different activation functions (ReLU and LeakyReLU) and various numbers of training epochs. Training with DSC metric and a ReLU activation function over 35 epochs achieved the highest overall performance (mean error in T1 10.6 ± 17.9 ms, mean DSC 0.88 ± 0.07). Limits of agreement between model results and ground truth were from -35.5 to + 36.1 ms. This was superior to the agreement between two human raters (-34.7 to + 59.1 ms). Segmentation was as accurate for long-axis views (mean error T1: 6.77 ± 8.3 ms, mean DSC: 0.89 ± 0.03) as for short-axis images (mean error ΔT1: 11.6 ± 19.7 ms, mean DSC: 0.88 ± 0.08). Fully automated segmentation and quantitative analysis of native myocardial T1 maps is possible in both long-axis and short-axis orientations with very high accuracy.

Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19. / Prävalenz und prognostische Rolle der thorakalen Lymphadenopathie bei Covid-19.

PURPOSE: The prevalent coronavirus disease 2019 (COVID-19) pandemic has spread throughout the world and is considered a serious threat to global health. The prognostic role of thoracic lymphadenopathy in COVID-19 is unclear. The aim of the present meta-analysis was to analyze the prognostic role of thoracic lymphadenopathy for the prediction of 30-day mortality in patients with COVID-19. MATERIALS AND METHODS: The MEDLINE library, Cochrane, and SCOPUS databases were screened for associations between CT-defined features and mortality in COVID-19 patients up to June 2021. In total, 21 studies were included in the present analysis. The quality of the included studies was assessed by the Newcastle-Ottawa Scale. The meta-analysis was performed using RevMan 5.3. Heterogeneity was calculated by means of the inconsistency index I2. DerSimonian and Laird random-effect models with inverse variance weights were performed without any further correction. RESULTS: The included studies comprised 4621 patients. The prevalence of thoracic lymphadenopathy varied between 1 % and 73.4 %. The pooled prevalence was 16.7 %, 95 % CI = (15.6 %; 17.8 %). The hospital mortality was higher in patients with thoracic lymphadenopathy (34.7 %) than in patients without (20.0 %). The pooled odds ratio for the influence of thoracic lymphadenopathy on mortality was 2.13 (95 % CI = [1.80-2.52], p < 0.001). CONCLUSION: The prevalence of thoracic lymphadenopathy in COVID-19 is 16.7 %. The presence of thoracic lymphadenopathy is associated with an approximately twofold increase in the risk for hospital mortality in COVID-19. KEY POINTS: · The prevalence of lymphadenopathy in COVID-19 is 16.7 %.. · Patients with lymphadenopathy in COVID-19 have a higher risk of mortality during hospitalization.. · Lymphadenopathy nearly doubles mortality and plays an important prognostic role.. CITATION FORMAT: · Bucher AM, Sieren M, Meinel F et al. Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2293-8132.

Time trend analysis of Injury Severity score of adult trauma patients with emergent CT examination.

PURPOSE: Controversy exists about whole-body computed tomography (CT) as a primary screening modality for suspected multiple trauma patients. Therefore, the aim of this study was to analyze time trends of CT examinations for trauma patients in relation to the Injury Severity Score (ISS). METHODS: We retrospectively analyzed 561 adult trauma patients (mean age = 54 years) who were admitted to the trauma room of our hospital, immediately followed by a CT examination, in 2009, 2013 und 2017. Review of electronic patient charts was performed to determine the cause of injury. ISS was either calculated upon hospital charts and CT imaging reports or documented in the TraumaRegister DGU® for trauma patients with ICU treatment or ISS ≥ 16. RESULTS: An increasing number of CT examinations of acute trauma patients were performed at our hospital with 117 patients in 2009 compared to 192 in 2013 and 252 in 2017. Their mean age increased (50 years in 2009, 54 in 2013 and 55 in 2017;p = 0.046), whereas their mean ISS decreased over time (15.2 in 2009 compared to 12.1 in 2013 and 10.6 in 2017;p = 0.001), especially in women (15.1 in 2009, 11.8 in 2013 and 7.4 in 2017;p = 0.001 both), younger age groups (18 to 24 years:15.6 in 2009, 6.5 in 2013 and 8.9 in 2017; p = 0.033 and 25 to 49 years:15.0 in 2009, 11.2 in 2013 and 8.3 in 2017;p = 0.001) as well as motor vehicle collision (MVC) victims (16.2 in 2009, 11.8 in 2013 and 6.1 in 2017; p < 0.001). Trauma patients with a high ISS were especially more likely of older age (OR 1.02,p < 0.001) and with the type of incident being a fall (< 3 m: OR3.84,p < 0.001;>3 m: OR6.22,p < 0.001) compared to MVC. CONCLUSION: Previous studies suggesting a benefit of primary whole-body CT for trauma patients might not reflect the current patient population with decreasing ISS. Especially females, younger age groups and MVC patients might benefit from stricter selection criteria for receiving whole-body CT. Our results also emphasize the importance of prevention of fall or tumble for elderly people.

[Artificial intelligence in cardiovascular radiology : Image acquisition, image reconstruction and workflow optimization]. / Künstliche Intelligenz in der kardiovaskulären Radiologie : Bildakquisition, Bildrekonstruktion und Workflowoptimierung.

BACKGROUND: Artificial intelligence (AI) has the potential to fundamentally change radiology workflow. OBJECTIVES: This review article provides an overview of AI applications in cardiovascular radiology with a focus on image acquisition, image reconstruction, and workflow optimization. MATERIALS AND METHODS: First, established applications of AI are presented for cardiovascular computed tomography (CT) and magnetic resonance imaging (MRI). Building on this, we describe the range of applications that are currently being developed and evaluated. The practical benefits, opportunities, and potential risks of artificial intelligence in cardiovascular imaging are critically discussed. The presentation is based on the relevant specialist literature and our own clinical and scientific experience. RESULTS: AI-based techniques for image reconstruction are already commercially available and enable dose reduction in cardiovascular CT and accelerated image acquisition in cardiac MRI. Postprocessing of cardiovascular CT and MRI examinations can already be considerably simplified using established AI-based segmentation algorithms. In contrast, the practical benefits of many AI applications aimed at the diagnosis of cardiovascular diseases are less evident. Potential risks such as automation bias and considerations regarding cost efficiency should also be taken into account. CONCLUSIONS: In a market characterized by great expectations and rapid technical development, it is important to realistically assess the practical benefits of AI applications for your own hospital or practice.

Influence of Deep Learning Based Image Reconstruction on Quantitative Results of Coronary Artery Calcium Scoring.

RATIONALE AND OBJECTIVES: To assess the impact of deep learning-based imaging reconstruction (DLIR) on quantitative results of coronary artery calcium scoring (CACS) and to evaluate the potential of DLIR for radiation dose reduction in CACS. METHODS: For a retrospective cohort of 100 consecutive patients (mean age 62 ±10 years, 40% female), CACS scans were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR-V in 30%, 60% and 90% strength) and DLIR in low, medium and high strength. CACS was quantified semi-automatically and compared between image reconstructions. In a phantom study, a cardiac calcification insert was scanned inside an anthropomorphic thorax phantom at standard dose, 50% dose and 25% dose. FBP reconstructions at standard dose served as the reference standard. RESULTS: In the patient study, DLIR led to a mean underestimation of Agatston score by 3.5, 6.4 and 11.6 points at low, medium and high strength, respectively. This underestimation of Agatston score was less pronounced for DLIR than for ASiR-V. In the phantom study, quantitative CACS results increased with reduced radiation dose and decreased with increasing strength of DLIR. Medium strength DLIR reconstruction at 50% dose reduction and high strength DLIR reconstruction at 75% dose reduction resulted in quantitative CACS results that were comparable to FBP reconstructions at standard dose. CONCLUSION: Compared to FBP as the historical reference standard, DLIR leads to an underestimation of CACS but this underestimation is more moderate than with ASiR-V. DLIR can offset the increase in image noise and calcium score at reduced dose and may thus allow for substantial radiation dose reductions in CACS studies.

Standardization of a CT Protocol for Imaging Patients with Suspected COVID-19-A RACOON Project.

CT protocols that diagnose COVID-19 vary in regard to the associated radiation exposure and the desired image quality (IQ). This study aims to evaluate CT protocols of hospitals participating in the RACOON (Radiological Cooperative Network) project, consolidating CT protocols to provide recommendations and strategies for future pandemics. In this retrospective study, CT acquisitions of COVID-19 patients scanned between March 2020 and October 2020 (RACOON phase 1) were included, and all non-contrast protocols were evaluated. For this purpose, CT protocol parameters, IQ ratings, radiation exposure (CTDIvol), and central patient diameters were sampled. Eventually, the data from 14 sites and 534 CT acquisitions were analyzed. IQ was rated good for 81% of the evaluated examinations. Motion, beam-hardening artefacts, or image noise were reasons for a suboptimal IQ. The tube potential ranged between 80 and 140 kVp, with the majority between 100 and 120 kVp. CTDIvol was 3.7 ± 3.4 mGy. Most healthcare facilities included did not have a specific non-contrast CT protocol. Furthermore, CT protocols for chest imaging varied in their settings and radiation exposure. In future, it will be necessary to make recommendations regarding the required IQ and protocol parameters for the majority of CT scanners to enable comparable IQ as well as radiation exposure for different sites but identical diagnostic questions.

Multi-modal assessment of a cardiac stem cell therapy reveals distinct modulation of regional scar properties.

BACKGROUND: The initial idea of functional tissue replacement has shifted to the concept that injected cells positively modulate myocardial healing by a non-specific immune response of the transplanted cells within the target tissue. This alleged local modification of the scar requires assessment of regional properties of the left ventricular wall in addition to commonly applied measures of global morphological and functional parameters. Hence, we aimed at investigating the effect of cardiac cell therapy with cardiovascular progenitor cells, so-called cardiac induced cells, on both global and regional properties of the left ventricle by a multimodal imaging approach in a mouse model. METHODS: Myocardial infarction was induced in mice by ligation of the left anterior descending artery, the therapy group received an intramyocardial injection of 1 × 106 cardiac induced cells suspended in matrigel, the control group received matrigel only. [18F]FDG positron emission tomography imaging was performed after 17 days, to assess regional glucose metabolism. Three weeks after myocardial infarction, cardiac magnetic resonance imaging was performed for morphological and functional assessment of the left ventricle. Following these measurements, hearts were excised for histological examinations. RESULTS: Cell therapy had no significant effect on global morphological parameters. Similarly, there was no difference in scar size and capillary density between therapy and control group. However, there was a significant improvement in contractile function of the left ventricle - left ventricular ejection fraction, stroke volume and cardiac output. Regional analysis of the left ventricle identified changes of wall properties in the scar area as the putative mechanism. Cell therapy reduced the thinning of the scar and significantly improved its radial contractility. Furthermore, the metabolic defect, assessed by [18F]FDG, was significantly reduced by the cell therapy. CONCLUSION: Our data support the relevance of extending the assessment of global left ventricular parameters by a structured regional wall analysis for the evaluation of therapies targeting at modulation of healing myocardium. This approach will enable a deeper understanding of mechanisms underlying the effect of experimental regenerative therapies, thus paving the way for a successful translation into clinical application.

Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction.

We investigated the effect of deep learning-based image reconstruction (DLIR) compared to iterative reconstruction on image quality in CT pulmonary angiography (CTPA) for suspected pulmonary embolism (PE). For 220 patients with suspected PE, CTPA studies were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR-V 30%, 60% and 90%) and DLIR (low, medium and high strength). Contrast-to-noise ratio (CNR) served as the primary parameter of objective image quality. Subgroup analyses were performed for normal weight, overweight and obese individuals. For patients with confirmed PE (n = 40), we further measured PE-specific CNR. Subjective image quality was assessed independently by two experienced radiologists. CNR was lowest for FBP and enhanced with increasing levels of ASiR-V and, even more with increasing strength of DLIR. High strength DLIR resulted in an additional improvement in CNR by 29-67% compared to ASiR-V 90% (p < 0.05). PE-specific CNR increased by 75% compared to ASiR-V 90% (p < 0.05). Subjective image quality was significantly higher for medium and high strength DLIR compared to all other image reconstructions (p < 0.05). In CT pulmonary angiography, DLIR significantly outperforms iterative reconstruction for increasing objective and subjective image quality. This may allow for further reductions in radiation exposure in suspected PE.

Native myocardial T1 mapping: influence of spatial resolution on quantitative results and reproducibility.

Background: Myocardial mapping techniques can be used to quantitatively assess alterations in myocardial tissue properties. This study aims to evaluate the influence of spatial resolution on quantitative results and reproducibility of native myocardial T1 mapping in cardiac magnetic resonance imaging (MRI). Methods: In this cross-sectional study with prospective data collection between October 2019 and February 2020, 50 healthy adults underwent two identical cardiac MRI examinations in the radiology department on the same day. T1 mapping was performed using a MOLLI 5(3)3 sequence with higher (1.4 mm × 1.4 mm) and lower (1.9 mm × 1.9 mm) in-plane spatial resolution. Global quantitative results of T1 mapping were compared between high-resolution and low-resolution acquisitions using paired t-test. Intra-class correlation coefficient (ICC) and Bland-Altman statistics (absolute and percentage differences as means ± SD) were used for assessing test-retest reproducibility. Results: There was no significant difference between global quantitative results acquired with high vs. low-resolution T1 mapping. The reproducibility of global T1 values was good for high-resolution (ICC: 0.88) and excellent for low-resolution T1 mapping (ICC: 0.95, P=0.003). In subgroup analyses, inferior test-retest reproducibility was observed for high spatial resolution in women compared to low spatial resolution (ICC: 0.71 vs. 0.91, P=0.001) and heart rates >77 bpm (ICC: 0.53 vs. 0.88, P=0.004). Apical segments had higher T1 values and variability compared to other segments. Regional T1 values for basal (ICC: 0.81 vs. 0.89, P=0.023) and apical slices (ICC: 0.86 vs. 0.92, P=0.024) showed significantly higher reproducibility in low-resolution compared to high-resolution acquisitions but without differences for midventricular slice (ICC: 0.91 vs. 0.92, P=0.402). Conclusions: Based on our data, we recommend a spatial resolution on the order of 1.9 mm × 1.9 mm for native myocardial T1 mapping using a MOLLI 5(3)3 sequence at 1.5 T particularly in individuals with higher heart rates and women.

Pericardial Effusion Predicts Clinical Outcomes in Patients with COVID-19: A Nationwide Multicenter Study.

RATIONALE AND OBJECTIVES: The prognostic role of pericardial effusion (PE) in Covid 19 is unclear. The aim of the present study was to estimate the prognostic role of PE in patients with Covid 19 in a large multicentre setting. MATERIALS AND METHODS: This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the Covid 19 pandemic). The acquired sample comprises 1197 patients, 363 (30.3%) women and 834 (69.7%) men. In every case, chest computed tomography was analyzed for PE. Data about 30-day mortality, need for mechanical ventilation and need for intensive care unit (ICU) admission were collected. Data were evaluated by means of descriptive statistics. Group differences were calculated with Mann-Whitney test and Fisher exact test. Uni-and multivariable regression analyses were performed. RESULTS: Overall, 46.4% of the patients were admitted to ICU, mechanical lung ventilation was performed in 26.6% and 30-day mortality was 24%. PE was identified in 159 patients (13.3%). The presence of PE was associated with 30-day mortality: HR= 1.54, CI 95% (1.05; 2.23), p = 0.02 (univariable analysis), and HR= 1.60, CI 95% (1.03; 2.48), p = 0.03 (multivariable analysis). Furthermore, density of PE was associated with the need for intubation (OR=1.02, CI 95% (1.003; 1.05), p = 0.03) and the need for ICU admission (OR=1.03, CI 95% (1.005; 1.05), p = 0.01) in univariable regression analysis. The presence of PE was associated with 30-day mortality in male patients, HR= 1.56, CI 95%(1.01-2.43), p = 0.04 (multivariable analysis). In female patients, none of PE values predicted clinical outcomes. CONCLUSION: The prevalence of PE in Covid 19 is 13.3%. PE is an independent predictor of 30-day mortality in male patients with Covid 19. In female patients, PE plays no predictive role.

Dual-Energy Computed Tomography in Cardiac Imaging.

Dual-energy computed tomography (DECT) acquires images using two energy spectra and offers a variation of reconstruction techniques for improved cardiac imaging. Virtual monoenergetic images decrease artifacts improving coronary plaque and stent visualization. Further, contrast attenuation is increased allowing significant reduction of contrast dose. Virtual non-contrast reconstructions enable coronary artery calcium scoring from contrast-enhanced scans. DECT provides advanced plaque imaging with detailed analysis of plaque components, indicating plaque stability. Extracellular volume assessment using DECT offers noninvasive detection of myocardial fibrosis. This review aims to outline the current cardiac applications of DECT, summarize recent literature, and discuss their findings.

ECG-gated MR angiography at 3T for follow-up after surgery involving the ascending aorta.

We aimed to evaluate electrocardiogram (ECG)-gated MR angiography (MRA) in the follow-up after surgery involving the ascending aorta regarding technical feasibility, image quality, spectrum of findings, and their implications for clinical management. We retrospectively analyzed a cohort of 19 patients (median age 59 years, range 38-79 years), who underwent MRA for follow-up imaging after surgery involving the ascending aorta. Our magnetic resonance imaging protocol consisted of a time-resolved, non-ECG-gated MRA and an ECG-gated MRA performed at 3T. Median examination duration was 25 minutes (range 11-41 minutes). All examinations were assessed by 2 readers in consensus for image quality on a 5-point scale ranging from 1 (non-diagnostic) to 5 (excellent). MRA examinations and patient charts were analyzed for diagnostic findings and their consequences for further management. Subjective image quality was rated as "sufficient" (score 3.1 ±â€…1.1) for the aortic root and as "good" to "excellent" for the ascending aorta (score 4.5 ±â€…0.7), aortic arch (4.5 ±â€…0.7), supra-aortic branches (4.5 ±â€…0.6) and descending aorta (4.6 ±â€…0.7). Abnormal findings were seen in 6 patients (32%) including progressive diameter of remaining aneurysm or dissection (3 patients, 16%) and suture aneurysms (3 patients, 16%). In all 6 of these patients, abnormal findings at MRA had consequences for clinical management. ECG-gated MR angiography at 3T yields good image quality for post-operative surveillance after aortic surgery involving the ascending aorta. This technique may serve as an alternative to computed tomography particularly in younger patients with repeated follow-up.

Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group.

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can be improved by choosing the most appropriate imaging modality for diagnosis, treatment and procedural planning. In this Consensus Statement, we provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations and describe the advances in imaging technology. Clinical consensus recommendations on the appropriateness of each imaging technique for direct coronary artery visualization were derived through a three-step, real-time Delphi process that took place before, during and after the Second International Quantitative Cardiovascular Imaging Meeting in September 2022. According to the Delphi survey answers, CT is the method of choice to rule out obstructive stenosis in patients with an intermediate pre-test probability of coronary artery disease and enables quantitative assessment of coronary plaque with respect to dimensions, composition, location and related risk of future cardiovascular events, whereas MRI facilitates the visualization of coronary plaque and can be used in experienced centres as a radiation-free, second-line option for non-invasive coronary angiography. PET has the greatest potential for quantifying inflammation in coronary plaque but SPECT currently has a limited role in clinical coronary artery stenosis and atherosclerosis imaging. Invasive coronary angiography is the reference standard for stenosis assessment but cannot characterize coronary plaques. Finally, intravascular ultrasonography and optical coherence tomography are the most important invasive imaging modalities for the identification of plaques at high risk of rupture. The recommendations made in this Consensus Statement will help clinicians to choose the most appropriate imaging modality on the basis of the specific clinical scenario, individual patient characteristics and the availability of each imaging modality.

Improved image quality in transcatheter aortic valve implantation planning CT using deep learning-based image reconstruction.

Background: This study aims to evaluate the impact of a novel deep learning-based image reconstruction (DLIR) algorithm on the image quality in computed tomographic angiography (CTA) for pre-interventional planning of transcatheter aortic valve implantation (TAVI). Methods: We analyzed 50 consecutive patients (median age 80 years, 25 men) who underwent TAVI planning CT on a 256-dectector-row CT. Images were reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) and DLIR. Intravascular image noise, edge sharpness, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were quantified for ascending aorta, descending aorta, abdominal aorta and iliac arteries. Two readers (one radiologist and one interventional cardiologist) scored task-specific subjective image quality on a five-point scale. Results: DLIR significantly reduced median image noise by 29-57% at all anatomical locations (all P<0.001). Accordingly, median SNR improved by 44-133% (all P<0.001) and median CNR improved by 44-125% (all P<0.001). DLIR significantly improved subjective image quality for all four pre-specified TAVI-specific tasks (measuring the annulus, assessing valve morphology and calcifications, the coronary ostia, and the suitability of the aorto-iliac access route) for both the radiologist and the interventional cardiologist (P≤0.001). Measurements of the aortic annulus circumference, area and diameter did not differ between ASIR-V and DLIR reconstructions (all P>0.05). Conclusions: DLIR significantly improves objective and subjective image quality in TAVI planning CT compared to a state-of-the-art iterative reconstruction without affecting measurements of the aortic annulus. This may provide an opportunity for further reductions in contrast medium volume in this population.

Management of Pulmonary Artery Synovial Sarcoma: The 3-Step Surgical Approach.

Primary pulmonary artery sarcoma is an uncommon neoplasm. Given its clinical and radiographic resemblance to pulmonary embolism, initial diagnostic steps may be complicated, leading to delay in diagnosis. This report presents the case of a 52-year-old-woman who was admitted with pulmonary embolism. She underwent pulmonary embolectomy, and histopathologic examination revealed synovial sarcoma.

Imaging and Clinical Parameters for Distinction between Infected and Non-Infected Fluid Collections in CT: Prospective Study Using Extended Microbiological Approach.

The aim of this investigation was to evaluate predictive CT imaging features and clinical parameters to distinguish infected from sterile fluid collections. Detection of infectious agents by advanced microbiological analysis was used as the reference standard. From April 2018 to October 2019, all patients undergoing CT-guided drainages were prospectively enrolled, if drainage material volume was at least 5 mL. Univariate analysis revealed attenuation (p = 0.001), entrapped gas (p < 0.001), fat stranding (p < 0.001), wall thickness (p < 0.001) and enhancement (p < 0.001) as imaging biomarkers and procalcitonin (p = 0.003) as clinical predictive parameters for infected fluid collections. On multivariate analysis, attenuation > 10 HU (p = 0.038), presence of entrapped gas (p = 0.027) and wall enhancement (p = 0.028) were independent parameters for distinguishing between infected and non-infected fluids. Gas entrapment had high specificity (93%) but low sensitivity (48%), while wall enhancement had high sensitivity (91%) but low specificity (50%). CT attenuation > 10 HU showed intermediate sensitivity (74%) and specificity (70%). Evaluation of the published proposed scoring systems did not improve diagnostic accuracy over independent predictors in our study. In conclusion, this prospective study confirmed that CT attenuation > 10 HU, entrapped gas and wall enhancement are the key imaging features to distinguish infected from sterile fluid collections on CT.

Negative Venous Leg Ultrasound in Acute Pulmonary Embolism: Prevalence, Clinical Characteristics and Predictors.

The purpose of this study was to investigate the prevalence, clinical characteristics, and predictors of negative venous leg ultrasound in acute pulmonary embolism (PE). We retrospectively analyzed a cohort of 168 patients with acute PE (median age 73 years, 44% women) evaluated with complete venous leg ultrasound. A multivariate logistic regression analysis was performed to identify the independent predictors of negative venous ultrasound in acute PE. Venous leg ultrasound was negative for deep venous thrombosis (DVT) in 78 patients (46.4%). Patients with negative venous ultrasound were less likely to have a history of DVT (7.7% vs. 20.0%, p = 0.0273) and had significantly lower D-dimer levels (median 2.5 vs. 6.2 mg/dL p < 0.0001). Negative venous ultrasound was more frequent in PE diagnosed with V/P-SPECT than in PE diagnosed with CT (66.2% vs. 34.0%, p < 0.0001). The prevalence of negative venous ultrasound increased with more peripherally located PE (29.5% for central/lobar, 43.1% for segmental, and 60.6% for subsegmental PE, p = 0.0049). For the multivariate analysis, a diagnosis of PE with V/P-SPECT rather than CT (OR 3.2, p = 0.0056) and lower D-dimer levels (OR 0.94, p = 0.0266) were independent predictors of negative venous ultrasound. In conclusion, venous leg ultrasound was negative for DVT in almost half of patients with acute PE. Negative venous ultrasound was more common in patients with no history of DVT, lower D-dimer levels, PE diagnosed with V/P-SPECT rather than CT, and more peripherally located PE.

Deep Learning-Based Image Reconstruction for CT Angiography of the Aorta.

To evaluate the impact of a novel, deep-learning-based image reconstruction (DLIR) algorithm on image quality in CT angiography of the aorta, we retrospectively analyzed 51 consecutive patients who underwent ECG-gated chest CT angiography and non-gated acquisition for the abdomen on a 256-dectector-row CT. Images were reconstructed with adaptive statistical iterative reconstruction (ASIR-V) and DLIR. Intravascular image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were quantified for the ascending aorta, the descending thoracic aorta, the abdominal aorta and the iliac arteries. Two readers scored subjective image quality on a five-point scale. Compared to ASIR-V, DLIR reduced the median image noise by 51-54% for the ascending aorta and the descending thoracic aorta. Correspondingly, median CNR roughly doubled for the ascending aorta and descending thoracic aorta. There was a 38% reduction in image noise for the abdominal aorta and the iliac arteries, with a corresponding improvement in CNR. Median subjective image quality improved from good to excellent at all anatomical levels. In CT angiography of the aorta, DLIR substantially improved objective and subjective image quality beyond what can be achieved by state-of-the-art iterative reconstruction. This can pave the way for further radiation or contrast dose reductions.

Isolated calf deep venous thrombosis: frequency on venous ultrasound and clinical characteristics.

BACKGROUND: It remains controversial whether to include calf veins in the initial ultrasound evaluation of suspected deep venous thrombosis (DVT). We sought to investigate the frequency and clinical characteristics of isolated calf DVT. MATERIALS AND METHODS: In this retrospective analysis, we investigated a cohort of 596 patients (median age 69 years, 52.3% women) who had been imaged with complete lower extremity venous duplex ultrasound for suspected acute DVT. Radiology reports were analyzed for the presence and localization of DVT. Clinical information was collected from patients' electronic charts. RESULTS: DVT was found in 157 patients (26.3%), of which 74 patients (47.1%) had isolated calf DVT. Isolated calf DVTs were located in the posterior tibial veins (22 patients, 29.7%), peroneal veins (41 patients, 55.4%) and muscle veins (19 patients, 25.7%). There were no differences in age or sex between patients with isolated calf DVT and patients with proximal DVT. Isolated calf DVT was more commonly associated with leg pain (52.7% vs. 33.7%, p = 0.0234) and less commonly associated with subjective leg swelling (35.1% vs. 55.4%, p = 0.0158) and objectively measured difference in leg circumference (23% vs. 39.8%, p = 0.0268). D-Dimers were significantly lower in patients with isolated lower leg DVT (median 2.3 vs. 6.8 mg/L, p < 0.0001) compared to patients with proximal DVT. CONCLUSIONS: Isolated calf DVT represents approximately half of DVT cases and has different clinical characteristics than proximal DVT.