Publications by authors named "Claus-Peter HeuSSel"

Article Synopsis
  • 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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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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Article Synopsis
  • 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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Article Synopsis
  • * 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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  • - Histological confirmation through either CT-guided needle biopsy (CTGNB) or bronchoscopy is crucial for planning lung cancer treatment, with concerns raised about CTGNB potentially increasing pleural recurrence risk, especially considering tumor proximity to the pleura.
  • - A study of 844 lung cancer patients revealed a low pleural recurrence rate (3.2%), and while CTGNB resulted in tumors being closer to the pleura, the biopsy method itself did not significantly impact the recurrence risk.
  • - The analysis concluded that CTGNB is safe and does not increase the risk of pleural recurrence, but this finding needs to be corroborated with data from larger, multicenter studies.
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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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Background: Chronic obstructive pulmonary disease (COPD) poses a substantial global health burden, demanding advanced diagnostic tools for early detection and accurate phenotyping. In this line, this study seeks to enhance COPD characterization on chest computed tomography (CT) by comparing the spatial and quantitative relationships between traditional parametric response mapping (PRM) and a novel self-supervised anomaly detection approach, and to unveil potential additional insights into the dynamic transitional stages of COPD.

Methods: Non-contrast inspiratory and expiratory CT of 1,310 never-smoker and GOLD 0 individuals and COPD patients (GOLD 1-4) from the COPDGene dataset were retrospectively evaluated.

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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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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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Background The latest large language models (LLMs) solve unseen problems via user-defined text prompts without the need for retraining, offering potentially more efficient information extraction from free-text medical records than manual annotation. Purpose To compare the performance of the LLMs ChatGPT and GPT-4 in data mining and labeling oncologic phenotypes from free-text CT reports on lung cancer by using user-defined prompts. Materials and Methods This retrospective study included patients who underwent lung cancer follow-up CT between September 2021 and March 2023.

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Objectives: Molecular diagnosis for targeted therapies has been improved significantly in non-small-cell lung cancer (NSCLC) patients in recent years. Here we report on the prevalence of rare fusions in NSCLC and dissect their genomic architecture and potential clinical implications.

Materials And Methods: Overall, n = 5554 NSCLC patients underwent next-generation sequencing (NGS) for combined detection of oncogenic mutations and fusions either at primary diagnosis (n = 5246) or after therapy resistance (n = 308).

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Background: In chronic obstructive pulmonary disease (COPD) abnormal lung function is related to emphysema and airway obstruction, but their relative contribution in each GOLD-stage is not fully understood. In this study, we used quantitative computed tomography (QCT) parameters for phenotyping of emphysema and airway abnormalities, and to investigate the relative contribution of QCT emphysema and airway parameters to airflow limitation specifically in each GOLD stage.

Methods: Non-contrast computed tomography (CT) of 492 patients with COPD former GOLD 0 COPD and COPD stages GOLD 1-4 were evaluated using fully automated software for quantitative CT.

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Objective: First-line pembrolizumab alone, as approved for PD-L1 ≥50%, or with chemotherapy was analyzed in older non-small-cell lung cancer (NSCLC) patients, for whom evidence is scarce.

Materials And Methods: A total of 156 consecutive ≥70 year-old patients treated between January 2016 and May 2021 were retrospectively analyzed. Tumor progression was verified through radiologic review, while toxicity was captured from records.

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Objective: Intratumoral heterogeneity was found to be a significant factor causing resistance to lung cancer therapies, including immune checkpoint blockade. Lesser is known about spatial heterogeneity of the tumor microenvironment (TME) and its association with genetic properties of the tumor, which is of particular interest in the therapy-naïve setting.

Materials And Methods: We performed multi-region sampling (2-4 samples per tumor; total of 55 samples) from a cohort of 19 untreated stage IA-IIIB lung adenocarcinomas (n = 11 KRAS mutant, n = 1 ERBB2 mutant, n = 7 KRAS wildtype).

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The evaluation of a patient with interstitial lung disease (ILD) includes assessment of clinical, radiological, and often histopathological data. As there were no specific recommendations to guide the evaluation of patients under the suspicion of an ILD within the German practice landscape, this position statement from an interdisciplinary panel of ILD experts provides guidance related to the diagnostic modalities which should be used in the evaluation of ILD. This includes clinical assessment rheumatological evaluation, radiological examinations, histopathologic sampling and the need for a final discussion in a multidisciplinary team.

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