Publications by authors named "Claus P Heussel"

Background: Computed tomography pulmonary angiography (CTPA) is frequently performed in patients with pulmonary hypertension (PH) and may aid non-invasive estimation of pulmonary hemodynamics. We, therefore, investigated automated volumetry of intrapulmonary vasculature on CTPA, separated into core and peel fractions of the lung volume and its potential to differentially reflect pulmonary hemodynamics in patients with pre- and postcapillary PH.

Methods: A retrospective case-control study of 72 consecutive patients with PH according to the 2022 joint guidelines of the European Society of Cardiology and the European Respiratory Society who underwent right heart catheterization (RHC) and CTPA within 7 days between August 2013 and February 2016 at Thoraxklinik at Heidelberg University Hospital (Heidelberg, Germany) was conducted.

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Objectives: We hypothesized that semiquantitative visual scoring of lung MRI is suitable for GOLD-grade specific characterization of parenchymal and airway disease in COPD and that MRI scores correlate with quantitative CT (QCT) and pulmonary function test (PFT) parameters.

Methods: Five hundred ninety-eight subjects from the COSYCONET study (median age = 67 (60-72)) at risk for COPD or with GOLD1-4 underwent PFT, same-day paired inspiratory/expiratory CT, and structural and contrast-enhanced MRI. QCT assessed total lung volume (TLV), emphysema, and air trapping by parametric response mapping (PRM, PRM) and airway disease by wall percentage (WP).

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Background: In COPD patients with severe right-sided emphysema, complete major and incomplete minor fissure, implantation of one-way valves in both the right upper (RUL) and middle lobes (ML) is a possible approach for endoscopic lung volume reduction. The aim of this retrospective analysis was to evaluate the response to therapy and the complication rate at 90 days (90d-FU) after combined RUL-ML valve implantation.

Methods: This retrospective, monocentric study included all patients from the Thoraxklinik Heidelberg who underwent RUL-ML valve treatment between 2012 and 2023 with available follow-up data.

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  • The study evaluates a deep learning model (LCP-CNN) for classifying the risk of incidentally detected pulmonary nodules, comparing its performance to traditional statistical methods like the Brock model and Lung-RADS®.
  • LCP-CNN showed superior diagnostic accuracy and sensitivity across various patient cohorts, making it more effective for identifying malignant nodules compared to the other methods.
  • The findings suggest that integrating deep learning systems can enhance clinical workflows for managing pulmonary nodules, regardless of a patient’s specific risk factors or conditions.
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Objectives: Small lesions are the limiting factor for reducing gadolinium-based contrast agents in brain magnetic resonance imaging (MRI). The purpose of this study was to compare the sensitivity and precision in metastasis detection on true contrast-enhanced T1-weighted (T1w) images and artificial images synthesized by a deep learning method using low-dose images.

Materials And Methods: In this prospective, multicenter study (5 centers, 12 scanners), 917 participants underwent brain MRI between October 2021 and March 2023 including T1w low-dose (0.

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  • - The study aimed to evaluate tracheal collapsibility using low-dose 4D CT, comparing the results with traditional methods like inspiratory-expiratory CT and bronchoscopy in patients suspected of tracheal collapse.
  • - Researchers analyzed 4D CT scans from 52 patients, finding that 48% exhibited significant tracheal collapsibility (50% or greater) and noted differences between visual 4D CT assessments and other diagnostic methods regarding detection rates of collapsibility.
  • - Results showed that 4D CT was superior in identifying patients with severe collapsibility compared to both paired CT and bronchoscopy, with significant differences in collapsibility measurements between the groups assessed.
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Contrast-enhanced computed tomography (CT) is the standard radiologic examination for evaluating the extent of mediastinal tumors. If tumor infiltration into the large central thoracic vessels, the pericardium, or the myocardium is suspected, cine magnetic resonance imaging (cine-MRI) can provide additional valuable information. We conducted a retrospective study of patients with mediastinal tumors who were staged with CT, cine-MRI, and a T1-weighted turbo spin echo (T1TSE) prior to surgical resection.

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Objective: Investigate the feasibility of detecting early treatment-induced tumor tissue changes in patients with advanced lung adenocarcinoma using diffusion-weighted MRI-derived radiomics features.

Methods: This prospective observational study included 144 patients receiving either tyrosine kinase inhibitors (TKI, n = 64) or platinum-based chemotherapy (PBC, n = 80) for the treatment of pulmonary adenocarcinoma. Patients underwent diffusion-weighted MRI the day prior to therapy (baseline, all patients), as well as either + 1 (PBC) or + 7 and + 14 (TKI) days after treatment initiation.

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Introduction: The aim of this study was to apply quantitative computed tomography (QCT) for GOLD-grade specific disease characterization and phenotyping of air-trapping, emphysema, and airway abnormalities in patients with chronic obstructive pulmonary disease (COPD) from a nationwide cohort study.

Methods: As part of the COSYCONET multicenter study, standardized CT in ex- and inspiration, lung function assessment (FEV1/FVC), and clinical scores (BODE index) were prospectively acquired in 525 patients (192 women, 327 men, aged 65.7 ± 8.

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  • The executive summary outlines evidence-based recommendations for diagnosing and treating nosocomial pneumonia, focusing on practical guidelines for healthcare providers in Germany.
  • It was developed through a systematic review process by an interdisciplinary panel, with the help of an independent methodologist, and presents 26 total recommendations, including ones based on strong evidence and expert consensus.
  • Key recommendations include distinguishing patients at risk for multidrug-resistant pathogens, limitations of routine bacterial PCR testing, and guidelines for antibiotic therapy, emphasizing focused treatments and the importance of rapidly de-escalating unnecessary antibiotics when patients stabilize.
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  • The study evaluates how well deep-learning models detect chronic obstructive pulmonary disease (COPD) in different ethnic groups, focusing on non-Hispanic Whites and African Americans.
  • Training on balanced datasets (both ethnic groups) and using self-supervised learning methods significantly improved model performance and reduced biases compared to using population-specific data.
  • The results underscore the need for equitable and effective AI healthcare solutions to ensure accurate COPD diagnosis across diverse populations.
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  • * Results indicated slight improvements in lung function measurements (FEV and RV) and a significant increase in walking distance, with some patients experiencing atelectasis and a manageable risk of complications.
  • * The findings suggest that simultaneous implantation of both valve types leads to meaningful clinical benefits and is a viable treatment option for patients with severe emphysema.
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Background: Patients with COPD are often affected by loss of bone mineral density (BMD) and osteoporotic fractures. Natriuretic peptides (NP) are known as cardiac markers, but have also been linked to fragility-associated fractures in the elderly. As their functions include regulation of fluid and mineral balance, they also might affect bone metabolism, particularly in systemic disorders such as COPD.

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Background: Cystic and nodular lung diseases encompass a broad spectrum of diseases with different etiologies and clinicoradiological presentations. Their differentiation is crucial for patient management but can be complex due to diseases with features of both categories and overlapping radiological patterns.

Objective: This study aims to describe the imaging features of cystic and nodular lung diseases in high-resolution computed tomography (CT) in detail-primarily based on their etiology-in order to allow a more accurate differential diagnosis of these diseases.

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PET using Ga-labeled fibroblast activation protein (FAP) inhibitors (FAPIs) holds high potential for diagnostic imaging of various malignancies, including lung cancer (LC). However, F-FDG PET is still the clinical gold standard for LC imaging. Several subtypes of LC, especially lepidic LC, are frequently F-FDG PET-negative, which markedly hampers the assessment of single pulmonary lesions suggestive of LC.

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  • The study aims to improve the understanding of chronic obstructive pulmonary disease (COPD) by comparing traditional diagnostic methods with a new self-supervised anomaly detection technique on CT scans, focusing on early detection and disease progression.
  • Using data from 1,310 individuals, including COPD patients and never-smokers, researchers applied the anomaly detection approach to identify lung abnormalities and associated these findings with traditional parametric response mapping (PRM) and pulmonary function tests.
  • Analysis revealed clear patterns of lung abnormalities linked to different stages of COPD and identified distinct clusters, highlighting the effectiveness of the new method in distinguishing between healthy and diseased lung regions.
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Objectives: A prospective, multi-centre study to evaluate concordance of morphologic lung MRI and CT in chronic obstructive pulmonary disease (COPD) phenotyping for airway disease and emphysema.

Methods: A total of 601 participants with COPD from 15 sites underwent same-day morpho-functional chest MRI and paired inspiratory-expiratory CT. Two readers systematically scored bronchial wall thickening, bronchiectasis, centrilobular nodules, air trapping and lung parenchyma defects in each lung lobe and determined COPD phenotype.

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Introduction: Due to hypoxic vasoconstriction, perfusion is interesting in the lungs. Magnetic Resonance Imaging (MRI) perfusion imaging based on Dynamic Contrast Enhancement (DCE) has been demonstrated in patients with Chronic Obstructive Pulmonary Diseases (COPD) using visual scores, and quantification methods were recently developed further. Inter-patient correlations of echo time-dependent observed T [T(TE)] have been shown with perfusion scores, pulmonary function testing, and quantitative computed tomography.

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Article Synopsis
  • This study aimed to use deep learning techniques to analyze chest CT scans for detecting abnormalities related to COPD (Chronic Obstructive Pulmonary Disease) and predicting its severity.
  • It utilized data from two major cohort studies, training a model on one dataset and testing its effectiveness on another, demonstrating superior performance compared to traditional methods.
  • Results showed that higher anomaly scores indicated worse lung function and increased symptoms, suggesting this approach could improve the understanding and assessment of COPD manifestations.
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Objectives: The purpose of this study was to determine the influence of dose reduction on a commercially available lung cancer prediction convolutional neuronal network (LCP-CNN).

Methods: CT scans from a cohort provided by the local lung cancer center (n = 218) with confirmed pulmonary malignancies and their corresponding reduced dose simulations (25% and 5% dose) were subjected to the LCP-CNN. The resulting LCP scores (scale 1-10, increasing malignancy risk) and the proportion of correctly classified nodules were compared.

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Pulmonary involvement is doubtless one the most fatal organ manifestations of the autoimmune rheumatic diseases (ARD) and involves the parenchyma, the vessels, the respiratory system itself, but also the muscles and the pleura. Close and regular screening assessments, identification of risk factors, clinical signs associated with the existence of lung disease should alarm the involved physicians treating these patients. The accurate classification is essential, as different treatment options are nowadays available.

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Background: Despite successful response to first line therapy, patients with small-cell lung cancer (SCLC) often suffer from early relapses and disease progression.

Objective: To investigate the relevance of serum tumor markers for estimation of prognosis at several time points during the course of disease.

Methods: In a prospective, single-center study, serial assessments of progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), cytokeratin-19 fragments (CYFRA 21-1) and carcino-embryogenic antigen (CEA) were performed during and after chemotherapy in 232 SCLC patients, and correlated with therapy response and overall survival (OS).

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Background: Serum tumor markers (STM) may complement imaging and provide additional clinical information for patients with non-small cell lung cancer (NSCLC).

Objective: To determine whether STMs can predict outcomes in patients with stable disease (SD) after initial treatment.

Methods: This single-center, prospective, observational trial enrolled 395 patients with stage III/IV treatment-naïve NSCLC; of which 263 patients were included in this analysis.

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Background: Detection of pulmonary perfusion defects is the recommended approach for diagnosing chronic thromboembolic pulmonary hypertension (CTEPH). This is currently achieved in a clinical setting using scintigraphy. Phase-resolved functional lung (PREFUL) magnetic resonance imaging (MRI) is an alternative technique for evaluating regional ventilation and perfusion without the use of ionizing radiation or contrast media.

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