Publications by authors named "Cornelia M Schaefer-Prokop"

Members of the Fleischner Society have compiled a glossary of terms for thoracic imaging that replaces previous glossaries published in 1984, 1996, and 2008, respectively. The impetus to update the previous version arose from multiple considerations. These include an awareness that new terms and concepts have emerged, others have become obsolete, and the usage of some terms has either changed or become inconsistent to a degree that warranted a new definition.

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Article Synopsis
  • This study aimed to independently validate commercial AI products for predicting bone age using hand radiographs and detecting lung nodules on chest radiographs.
  • Two AI algorithms for bone age prediction demonstrated a strong correlation with expert readers, while no significant differences in performance were found between AI and human readers.
  • Four AI algorithms for lung nodule detection outperformed human readers, indicating potential advantages of using AI in this area, while others did not show a notable difference in performance.
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PFI Pulmonary Functional Imaging (PFI) refers to visualization and measurement of ventilation, perfusion, gas flow and exchange as well as biomechanics. In this review, we will highlight the historical development of PFI, describing recent advances and listing the various techniques for PFI offered per modality. Challenges PFI is facing and requirements for PFI from a clinical point of view will be pointed out.

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Background: A baseline computed tomography (CT) scan for lung cancer (LC) screening may reveal information indicating that certain LC screening participants can be screened less, and instead require dedicated early cardiac and respiratory clinical input. We aimed to develop and validate competing death (CD) risk models using CT information to identify participants with a low LC risk and a high CD risk.

Methods: Participant demographics and quantitative CT measures of LC, cardiovascular disease and chronic obstructive pulmonary disease were considered for deriving a logistic regression model for predicting 5-year CD risk using a sample from the National Lung Screening Trial (n=15 000).

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The purpose of this case-cohort study was to investigate whether the frequency and computed tomography (CT) features of pulmonary nodules posed a risk for the future development of lung cancer (LC) at a different location. Patients scanned between 2004 and 2012 at two Dutch academic hospitals were cross-linked with the Dutch Cancer Registry. All patients who were diagnosed with LC by 2014 and a random selection of LC-free patients were considered.

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Purpose: To microsimulate the effects of three additional annual CT screening rounds on lung cancer (LC) survival in the National Lung Screening Trial (NLST).

Methods: We used multiple imputation to model the effect of additional screening in the full NLST cohort on the time to LC diagnosis and on LC death in those participants who were diagnosed with LC by the end of NLST. Nodule growth models were derived from a Dutch in-vivo study.

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Article Synopsis
  • Several studies have found that intrapulmonary lymph nodes (IPLNs) are benign lesions on CT scans that don't need follow-up after they're initially detected.
  • IPLNs are often misidentified as pulmonary nodules, and being able to accurately recognize them could help reduce unnecessary follow-up CT scans.
  • The review highlights the variability in defining and classifying these nodules and introduces a decision tree to assist clinicians in properly categorizing them.
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Objectives: Combined assessment of cardiovascular disease (CVD), COPD and lung cancer may improve the effectiveness of lung cancer screening in smokers. The aims were to derive and assess risk models for predicting lung cancer incidence, CVD mortality and COPD mortality by combining quantitative computed tomography (CT) measures from each disease, and to quantify the added predictive benefit of self-reported patient characteristics given the availability of a CT scan.

Methods: A survey model (patient characteristics only), CT model (CT information only) and final model (all variables) were derived for each outcome using parsimonious Cox regression on a sample from the National Lung Screening Trial (n=15 000).

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  • The use of molecular targeting agents and immune checkpoint inhibitors in cancer treatment has led to an increase in lung toxicity, particularly drug-related pneumonitis (DRP).
  • Diagnosing DRP involves ruling out other causes, with symptoms varying from mild to potentially fatal, and the assessment of lung imaging can reveal different radiologic patterns indicative of DRP severity.
  • Treatment typically includes stopping the offending drug, administering immunosuppressive therapy, and providing supportive care, with recommendations for diagnosis and management aimed at various healthcare professionals.
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  • The use of molecular targeting agents and immune checkpoint inhibitors (ICIs) in cancer treatment has led to increased lung toxicity, specifically drug-related pneumonitis (DRP), highlighting the importance of recognizing its incidence and risk factors.
  • Diagnosis of DRP typically involves ruling out other causes, and symptoms can vary significantly, from mild to potentially life-threatening.
  • Imaging features of DRP can include various radiological patterns, and treatment usually involves stopping the offending drug, administering immunosuppressive therapy, and providing supportive care, including oxygen if needed.
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Background: Improved imaging techniques have increased the incidence of subsegmental pulmonary embolism (ssPE). Indirect evidence is suggesting that ssPE may represent a more benign presentation of venous thromboembolism not necessarily requiring anticoagulant treatment. However, correctly diagnosing ssPE is challenging with reported low interobserver agreement, partly due to the lack of widely accepted diagnostic criteria.

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Objective: To compare nodule enhancement on subtraction CT iodine maps to that on dual-energy CT iodine maps using CT datasets acquired simultaneously.

Methods: A previously-acquired set of lung subtraction and dual-energy CT maps consisting of thirty patients with 95 solid pulmonary nodules (≥4 mm diameter) was used. Nodules were annotated and segmented on CT angiography, and mean nodule enhancement in the iodine maps calculated.

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Background The prognosis of hospitalized patients with severe coronavirus disease 2019 (COVID-19) is difficult to predict, and the capacity of intensive care units was a limiting factor during the peak of the pandemic and is generally dependent on a country's clinical resources. Purpose To determine the value of chest radiographic findings together with patient history and laboratory markers at admission to predict critical illness in hospitalized patients with COVID-19. Materials and Methods In this retrospective study, which included patients from March 7, 2020, to April 24, 2020, a consecutive cohort of hospitalized patients with real-time reverse transcription polymerase chain reaction-confirmed COVID-19 from two large Dutch community hospitals was identified.

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Purpose: One of the main pathophysiological mechanisms of chronic obstructive pulmonary disease is inflammation, which has been associated with lymphadenopathy. Intrapulmonary lymph nodes can be identified on CT as perifissural nodules (PFN). We investigated the association between the number and size of PFNs and measures of COPD severity.

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  • Chest radiography can aid in COVID-19 triage, especially in resource-limited areas.
  • An AI system, CAD4COVID-XRay, analyzed over 24,000 chest radiographs and was found to effectively detect COVID-19 pneumonia.
  • The AI system showed diagnostic performance comparable to six experienced readers, outperforming them at higher sensitivity levels.
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With more than 900,000 confirmed cases worldwide and nearly 50,000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment.

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With more than 900 000 confirmed cases worldwide and nearly 50 000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment.

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Background Dual-energy CT iodine maps are used to detect pulmonary embolism (PE) with CT angiography but require dedicated hardware. Subtraction CT, a software-only solution, results in iodine maps with high contrast-to-noise ratios. Purpose To compare the use of subtraction CT versus dual-energy CT iodine maps to CT angiography for PE detection.

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The objective of this study was to compare the image quality of iodine maps derived from subtraction CT and from dual-energy CT (DECT) in patients with suspected pulmonary embolism (PE). In this prospective study conducted between July 2016 and April 2017, consecutive patients with suspected PE underwent unenhanced CT at 100 kV and dual-energy pulmonary CT angiography at 100 and 140 kV on a dual-source scanner. The scanner was set to generate subtraction and DECT iodine maps at similar radiation doses.

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Purpose: Normalized emphysema score is a protocol-robust CT biomarker of mortality. We aimed to improve mortality prediction by including the emphysema score progression rate-its change over time-into the models.

Method And Materials: CT scans from 6000 National Lung Screening Trial CT arm participants were included.

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It is well known that lung cancer can manifest itself in imaging as solid and subsolid nodules or masses. However, in this era of increased computed tomography use another morphological computed tomography appearance of lung cancer is increasingly being recognised, presenting as a malignancy in relation to cystic airspaces. Despite the fact that it seems to be a relatively common finding in daily practice, literature on this entity is scarce and presumably the overall awareness is limited.

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Overall survival of patients with cancer continues to increase and so they receive more frequent CT imaging, making oncological patients a growing population that effectively receives lung cancer screening in the course of daily practice. However, it is currently uncertain how early lung cancer detection in this subgroup of patients should be optimally managed. We describe the relationship between primary lung cancer and prior malignancies in a nationwide cohort, in an attempt to identify possible areas of improvement in nodule management.

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