Midregional Proatrial Natriuretic Peptide (MRproANP) is associated with vertebral fractures and low bone density in patients with chronic obstructive pulmonary disease (COPD).

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. RESEARCH QUESTION: We investigated the association between NP serum levels, vertebral fractures and BMD assessed by chest computed tomography (CT) in patients with COPD. METHODS: Participants of the COSYCONET cohort with CT scans were included. Mean vertebral bone density on CT (BMD-CT) as a risk factor for osteoporosis was assessed at the level of TH12 (AI-Rad Companion), and vertebral compression fractures were visually quantified by two readers. Their relationship with N-terminal pro-B-type natriuretic peptide (NT-proBNP), Mid-regional pro-atrial natriuretic peptide (MRproANP) and Midregional pro-adrenomedullin (MRproADM) was determined using group comparisons and multivariable analyses. RESULTS: Among 418 participants (58% male, median age 64 years, FEV1 59.6% predicted), vertebral fractures in TH12 were found in 76 patients (18.1%). Compared to patients without fractures, these had elevated serum levels (p ≤ 0.005) of MRproANP and MRproADM. Using optimal cut-off values in multiple logistic regression analyses, MRproANP levels ≥ 65 nmol/l (OR 2.34; p = 0.011) and age (p = 0.009) were the only significant predictors of fractures after adjustment for sex, BMI, smoking status, FEV1% predicted, SGRQ Activity score, daily physical activity, oral corticosteroids, the diagnosis of cardiac disease, and renal impairment. Correspondingly, MRproANP (p < 0.001), age (p = 0.055), SGRQ Activity score (p = 0.061) and active smoking (p = 0.025) were associated with TH12 vertebral density. INTERPRETATION: MRproANP was a marker for osteoporotic vertebral fractures in our COPD patients from the COSYCONET cohort. Its association with reduced vertebral BMD on CT and its known modulating effects on fluid and ion balance are suggestive of direct effects on bone mineralization. TRIAL REGISTRATION: ClinicalTrials.gov NCT01245933, Date of registration: 18 November 2010.

Phenotyping of COPD with MRI in comparison to same-day CT in a multi-centre trial.

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. A third reader acted as adjudicator to establish consensus. Inter-modality and inter-reader agreement were assessed using Cohen's kappa (im-κ and ir-κ). RESULTS: The mean combined MRI score for bronchiectasis/bronchial wall thickening was 4.5/12 (CT scores, 2.2/12 for bronchiectasis and 6/12 for bronchial wall thickening; im-κ, 0.04-0.3). Expiratory right/left bronchial collapse was observed in 51 and 47/583 on MRI (62 and 57/599 on CT; im-κ, 0.49-0.52). Markers of small airways disease on MRI were 0.15/12 for centrilobular nodules (CT, 0.34/12), 0.94/12 for air trapping (CT, 0.9/12) and 7.6/12 for perfusion deficits (CT, 0.37/12 for mosaic attenuation; im-κ, 0.1-0.41). The mean lung defect score on MRI was 1.3/12 (CT emphysema score, 5.8/24; im-κ, 0.18-0.26). Airway-/emphysema/mixed COPD phenotypes were assigned in 370, 218 and 10 of 583 cases on MRI (347, 218 and 34 of 599 cases on CT; im-κ, 0.63). For all examined features, inter-reader agreement on MRI was lower than on CT. CONCLUSION: Concordance of MRI and CT for phenotyping of COPD in a multi-centre setting was substantial with variable inter-modality and inter-reader concordance for single diagnostic key features. CLINICAL RELEVANCE STATEMENT: MRI of lung morphology may well serve as a radiation-free imaging modality for COPD in scientific and clinical settings, given that its potential and limitations as shown here are carefully considered. KEY POINTS: • In a multi-centre setting, MRI and CT showed substantial concordance for phenotyping of COPD (airway-/emphysema-/mixed-type). • Individual features of COPD demonstrated variable inter-modality concordance with features of pulmonary hypertension showing the highest and bronchiectasis showing the lowest concordance. • For all single features of COPD, inter-reader agreement was lower on MRI than on CT.

Prediction of disease severity in COPD: a deep learning approach for anomaly-based quantitative assessment of chest CT.

OBJECTIVES: To quantify regional manifestations related to COPD as anomalies from a modeled distribution of normal-appearing lung on chest CT using a deep learning (DL) approach, and to assess its potential to predict disease severity. MATERIALS AND METHODS: Paired inspiratory/expiratory CT and clinical data from COPDGene and COSYCONET cohort studies were included. COPDGene data served as training/validation/test data sets (N = 3144/786/1310) and COSYCONET as external test set (N = 446). To differentiate low-risk (healthy/minimal disease, [GOLD 0]) from COPD patients (GOLD 1-4), the self-supervised DL model learned semantic information from 50 × 50 × 50 voxel samples from segmented intact lungs. An anomaly detection approach was trained to quantify lung abnormalities related to COPD, as regional deviations. Four supervised DL models were run for comparison. The clinical and radiological predictive power of the proposed anomaly score was assessed using linear mixed effects models (LMM). RESULTS: The proposed approach achieved an area under the curve of 84.3 ± 0.3 (p < 0.001) for COPDGene and 76.3 ± 0.6 (p < 0.001) for COSYCONET, outperforming supervised models even when including only inspiratory CT. Anomaly scores significantly improved fitting of LMM for predicting lung function, health status, and quantitative CT features (emphysema/air trapping; p < 0.001). Higher anomaly scores were significantly associated with exacerbations for both cohorts (p < 0.001) and greater dyspnea scores for COPDGene (p < 0.001). CONCLUSION: Quantifying heterogeneous COPD manifestations as anomaly offers advantages over supervised methods and was found to be predictive for lung function impairment and morphology deterioration. CLINICAL RELEVANCE STATEMENT: Using deep learning, lung manifestations of COPD can be identified as deviations from normal-appearing chest CT and attributed an anomaly score which is consistent with decreased pulmonary function, emphysema, and air trapping. KEY POINTS: • A self-supervised DL anomaly detection method discriminated low-risk individuals and COPD subjects, outperforming classic DL methods on two datasets (COPDGene AUC = 84.3%, COSYCONET AUC = 76.3%). • Our contrastive task exhibits robust performance even without the inclusion of expiratory images, while voxel-based methods demonstrate significant performance enhancement when incorporating expiratory images, in the COPDGene dataset. • Anomaly scores improved the fitting of linear mixed effects models in predicting clinical parameters and imaging alterations (p < 0.001) and were directly associated with clinical outcomes (p < 0.001).

GOLD-Grade Specific Disease Characterization and Phenotyping of COPD Using Quantitative Computed Tomography in the Nationwide COSYCONET Multicenter Trial in Germany.

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 ± 8.5 years) at risk for COPD and at GOLD1-4. QCT parameters such as total lung volume (TLV), emphysema index (EI), parametric response mapping (PRM) for emphysema (PRMEmph) and functional small airway disease (PRMfSAD), total airway volume (TAV), wall percentage (WP), and total diameter (TD) were computed using automated software. RESULTS: TLV, EI, PRMfSAD, and PRMEmph increased incrementally with each GOLD grade (p < 0.001). Aggregated WP5-10 of subsegmental airways was higher from GOLD1 to GOLD3 and lower again at GOLD4 (p < 0.001), whereas TD5-10 was significantly dilated only in GOLD4 (p < 0.001). Fifty-eight patients were phenotyped as "non-airway non-emphysema type," 202 as "airway type," 96 as "emphysema type," and 169 as "mixed type." FEV1/FVC was best in "non-airway non-emphysema type" compared to other phenotypes, while "mixed type" had worst FEV1/FVC (p < 0.001). BODE index was 0.56 ± 0.72 in the "non-airway non-emphysema type" and highest with 2.55 ± 1.77 in "mixed type" (p < 0.001). CONCLUSION: QCT demonstrates increasing hyperinflation and emphysema depending on the GOLD grade, while airway wall thickening increases until GOLD3 and airway dilatation occur in GOLD4. QCT identifies four disease phenotypes with implications for lung function and prognosis.

ERS/ESTS/ESTRO/ESR/ESTI/EFOMP statement on management of incidental findings from low dose CT screening for lung cancer.

BACKGROUND: Screening for lung cancer with low radiation dose computed tomography has a strong evidence base, is being introduced in several European countries and is recommended as a new targeted cancer screening programme. The imperative now is to ensure that implementation follows an evidence-based process that will ensure clinical and cost effectiveness. This European Respiratory Society (ERS) task force was formed to provide an expert consensus for the management of incidental findings which can be adapted and followed during implementation. METHODS: A multi-European society collaborative group was convened. 23 topics were identified, primarily from an ERS statement on lung cancer screening, and a systematic review of the literature was conducted according to ERS standards. Initial review of abstracts was completed and full text was provided to members of the group for each topic. Sections were edited and the final document approved by all members and the ERS Science Council. RESULTS: Nine topics considered most important and frequent were reviewed as standalone topics (interstitial lung abnormalities, emphysema, bronchiectasis, consolidation, coronary calcification, aortic valve disease, mediastinal mass, mediastinal lymph nodes and thyroid abnormalities). Other topics considered of lower importance or infrequent were grouped into generic categories, suitable for general statements. CONCLUSIONS: This European collaborative group has produced an incidental findings statement that can be followed during lung cancer screening. It will ensure that an evidence-based approach is used for reporting and managing incidental findings, which will mean that harms are minimised and any programme is as cost-effective as possible.

Implementation of artificial intelligence in thoracic imaging-a what, how, and why guide from the European Society of Thoracic Imaging (ESTI).

This statement from the European Society of Thoracic imaging (ESTI) explains and summarises the essentials for understanding and implementing Artificial intelligence (AI) in clinical practice in thoracic radiology departments. This document discusses the current AI scientific evidence in thoracic imaging, its potential clinical utility, implementation and costs, training requirements and validation, its' effect on the training of new radiologists, post-implementation issues, and medico-legal and ethical issues. All these issues have to be addressed and overcome, for AI to become implemented clinically in thoracic radiology. KEY POINTS: • Assessing the datasets used for training and validation of the AI system is essential. • A departmental strategy and business plan which includes continuing quality assurance of AI system and a sustainable financial plan is important for successful implementation. • Awareness of the negative effect on training of new radiologists is vital.

Quantification of pulmonary perfusion abnormalities using DCE-MRI in COPD: comparison with quantitative CT and pulmonary function.

OBJECTIVES: Pulmonary perfusion abnormalities are prevalent in patients with chronic obstructive pulmonary disease (COPD), are potentially reversible, and may be associated with emphysema development. Therefore, we aimed to evaluate the clinical meaningfulness of perfusion defects in percent (QDP) using DCE-MRI. METHODS: We investigated a subset of baseline DCE-MRIs, paired inspiratory/expiratory CTs, and pulmonary function testing (PFT) of 83 subjects (age = 65.7 ± 9.0 years, patients-at-risk, and all GOLD groups) from one center of the "COSYCONET" COPD cohort. QDP was computed from DCE-MRI using an in-house developed quantification pipeline, including four different approaches: Otsu's method, k-means clustering, texture analysis, and 80th percentile threshold. QDP was compared with visual MRI perfusion scoring, CT parametric response mapping (PRM) indices of emphysema (PRMEmph) and functional small airway disease (PRMfSAD), and FEV1/FVC from PFT. RESULTS: All QDP approaches showed high correlations with the MRI perfusion score (r = 0.67 to 0.72, p < 0.001), with the highest association based on Otsu's method (r = 0.72, p < 0.001). QDP correlated significantly with all PRM indices (p < 0.001), with the strongest correlations with PRMEmph (r = 0.70 to 0.75, p < 0.001). QDP was distinctly higher than PRMEmph (mean difference = 35.85 to 40.40) and PRMfSAD (mean difference = 15.12 to 19.68), but in close agreement when combining both PRM indices (mean difference = 1.47 to 6.03) for all QDP approaches. QDP correlated moderately with FEV1/FVC (r = - 0.54 to - 0.41, p < 0.001). CONCLUSION: QDP is associated with established markers of disease severity and the extent corresponds to the CT-derived combined extent of PRMEmph and PRMfSAD. We propose to use QDP based on Otsu's method for future clinical studies in COPD. KEY POINTS: • QDP quantified from DCE-MRI is associated with visual MRI perfusion score, CT PRM indices, and PFT. • The extent of QDP from DCE-MRI corresponds to the combined extent of PRMEmph and PRMfSAD from CT. • Assessing pulmonary perfusion abnormalities using DCE-MRI with QDP improved the correlations with CT PRM indices and PFT compared to the quantification of pulmonary blood flow and volume.

[Chest X-ray: implementation and indication : Recommendations of the thoracic imaging working group of the German Radiological Society]. / Röntgen-Thorax: Durchführung und Indikationen : Empfehlungen der AG Thoraxdiagnostik der Deutschen Röntgengesellschaft.

BACKGROUND: Even after more than 100 years, the chest X­ray is still an important technique to detect important pathological changes of lungs, heart and vessels in a fast and low-dose manner. For the German-speaking regions, there are only recommendations available published by the "Ständigen Strahlenschutzkommission (SSK)" regarding the indication. These recommendations are not updated on a regular basis and more recent developments are only integrated with delayed. METHODS: The chest division of the German Radiological Society has summarized their expertise for the usage and indication of the chest X­ray. Especially within the field of oncology the usage of chest X­ray is evaluated differently to the aforementioned recommendations; here chest computed tomography (CT) is much more sensitive for evaluation of metastasis and local invasion of tumors. Also, within the area of infectious diseases in non-immunocompetent patients, CT is the method of choice. Based on the structure of the current recommendations, many current guidelines and indications are summarized and presented within the context of the usage of chest X­ray.

Prediction of lung emphysema in COPD by spirometry and clinical symptoms: results from COSYCONET.

BACKGROUND: Lung emphysema is an important phenotype of chronic obstructive pulmonary disease (COPD), and CT scanning is strongly recommended to establish the diagnosis. This study aimed to identify criteria by which physicians with limited technical resources can improve the diagnosis of emphysema. METHODS: We studied 436 COPD patients with prospective CT scans from the COSYCONET cohort. All items of the COPD Assessment Test (CAT) and the St George's Respiratory Questionnaire (SGRQ), the modified Medical Research Council (mMRC) scale, as well as data from spirometry and CO diffusing capacity, were used to construct binary decision trees. The importance of parameters was checked by the Random Forest and AdaBoost machine learning algorithms. RESULTS: When relying on questionnaires only, items CAT 1 & 7 and SGRQ 8 & 12 sub-item 3 were most important for the emphysema- versus airway-dominated phenotype, and among the spirometric measures FEV1/FVC. The combination of CAT item 1 (≤ 2) with mMRC (> 1) and FEV1/FVC, could raise the odds for emphysema by factor 7.7. About 50% of patients showed combinations of values that did not markedly alter the likelihood for the phenotypes, and these could be easily identified in the trees. Inclusion of CO diffusing capacity revealed the transfer coefficient as dominant measure. The results of machine learning were consistent with those of the single trees. CONCLUSIONS: Selected items (cough, sleep, breathlessness, chest condition, slow walking) from comprehensive COPD questionnaires in combination with FEV1/FVC could raise or lower the likelihood for lung emphysema in patients with COPD. The simple, parsimonious approach proposed by us might help if diagnostic resources regarding respiratory diseases are limited. Trial registration ClinicalTrials.gov, Identifier: NCT01245933, registered 18 November 2010, https://clinicaltrials.gov/ct2/show/record/NCT01245933 .

Echo Time-Dependent Observed Lung T1 in Patients With Chronic Obstructive Pulmonary Disease in Correlation With Quantitative Imaging and Clinical Indices.

BACKGROUND: There is a clinical need for imaging-derived biomarkers for the management of chronic obstructive pulmonary disease (COPD). Observed pulmonary T1 (T1 (TE)) depends on the echo-time (TE) and reflects regional pulmonary function. PURPOSE: To investigate the potential diagnostic value of T1 (TE) for the assessment of lung disease in COPD patients by determining correlations with clinical parameters and quantitative CT. STUDY TYPE: Prospective non-randomized diagnostic study. POPULATION: Thirty COPD patients (67.7 ± 6.6 years). Data from a previous study (15 healthy volunteers [26.2 ± 3.9 years) were used as reference. FIELD STRENGTH/SEQUENCE: Study participants were examined at 1.5 T using dynamic contrast-enhanced three-dimensional gradient echo keyhole perfusion sequence and a multi-echo inversion recovery two-dimensional UTE (ultra-short TE) sequence for T1 (TE) mapping at TE1-5  = 70 µsec, 500 µsec, 1200 µsec, 1650 µsec, and 2300 µsec. ASSESSMENT: Perfusion images were scored by three radiologists. T1 (TE) was automatically quantified. Computed tomography (CT) images were quantified in software (qCT). Clinical parameters including pulmonary function testing were also acquired. STATISTICAL TESTS: Spearman rank correlation coefficients (ρ) were calculated between T1 (TE) and perfusion scores, clinical parameters and qCT. A P-value <0.05 was considered statistically significant. RESULTS: Median values were T1 (TE1-5 ) = 644 ± 78 msec, 835 ± 92 msec, 835 ± 87 msec, 831 ± 131 msec, 893 ± 220 msec, all significantly shorter than previously reported in healthy subjects. A significant increase of T1 was observed from TE1 to TE2 , with no changes from TE2 to TE3 (P = 0.48), TE3 to TE4 (P = 0.94) or TE4 to TE5 (P = 0.02) which demonstrates an increase at shorter TEs than in healthy subjects. Moderate to strong Spearman's correlations between T1 and parameters including the predicted diffusing capacity for carbon monoxide (DLCO, ρ < 0.70), mean lung density (MLD, ρ < 0.72) and the perfusion score (ρ > -0.69) were found. Overall, correlations were strongest at TE2 , weaker at TE1 and rarely significant at TE4 -TE5 . DATA CONCLUSION: In COPD patients, the increase of T1 (TE) with TE occurred at shorter TEs than previously found in healthy subjects. Together with the lack of correlation between T1 and clinical parameters of disease at longer TEs, this suggests that T1 (TE) quantification in COPD patients requires shorter TEs. The TE-dependence of correlations implies that T1 (TE) mapping might be developed further to provide diagnostic information beyond T1 at a single TE. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Ten years of chest MRI for patients with cystic fibrosis : Translation from the bench to clinical routine.

BACKGROUND: Despite recent advances in our knowledge about the pathophysiology and treatment of cystic fibrosis (CF), pulmonary involvement remains the most important determinant of morbidity and mortality in patients with CF. Since lung function testing may not be sensitive enough for subclinical disease progression, and because young children may have normal spirometry results over a longer period of time, imaging today plays an increasingly important role in clinical routine and research for the monitoring of CF lung disease. In this regard, chest magnetic resonance imaging (MRI) could serve as a radiation-free modality for structural and functional lung imaging. METHODS: Our research agenda encompassed the entire process of development, implementation, and validation of appropriate chest MRI protocols for use with infant and adult CF patients alike. RESULTS: After establishing a general MRI protocol for state-of-the-art clinical 1.5-T scanners based on the available sequence technology, a semiquantitative scoring system was developed followed by cross-validation of the method against the established modalities of computed tomography, radiography, and lung function testing. Cross-sectional studies were then set up to determine the sensitivity of the method for the interindividual variation of the disease and for changes in disease severity after treatment. Finally, the MRI protocol was implemented at multiple sites to be validated in a multicenter setting. CONCLUSION: After more than a decade, lung MRI has become a valuable tool for monitoring CF in clinical routine application and as an endpoint for clinical studies.

Relationship of spirometric, body plethysmographic, and diffusing capacity parameters to emphysema scores derived from CT scans.

Phenotyping of chronic obstructive pulmonary disease (COPD) with computed tomography (CT) is used to distinguish between emphysema- and airway-dominated type. The phenotype is reflected in correlations with lung function measures. Among these, the relative value of body plethysmography has not been quantified. We addressed this question using CT scans retrospectively collected from clinical routine in a large COPD cohort. Three hundred and thirty five patients with baseline data of the German COPD cohort COPD and Systemic Consequences-Comorbidities Network were included. CT scans were primarily evaluated using a qualitative binary emphysema score. The binary score was positive for emphysema in 52.5% of patients, and there were significant differences between the positive/negative groups regarding forced expiratory volume in 1 second (FEV1), FEV1/forced vital capacity (FVC), intrathoracic gas volume (ITGV), residual volume (RV), specific airway resistance (sRaw), transfer coefficient (KCO), transfer factor for carbon monoxide (TLCO), age, pack-years, and body mass index (BMI). Stepwise discriminant analyses revealed the combination of FEV1/FVC, RV, sRaw, and KCO to be significantly related to the binary emphysema score. The additional positive predictive value of body plethysmography, however, was only slightly higher than that of the conventional combination of spirometry and diffusing capacity, which if taken alone also achieved high predictive values, in contrast to body plethysmography. The additional information on the presence of CT-diagnosed emphysema as conferred by body plethysmography appeared to be minor compared to the well-known combination of spirometry and CO diffusing capacity.

Towards synchrotron phase-contrast lung imaging in patients - a proof-of-concept study on porcine lungs in a human-scale chest phantom.

In-line free propagation phase-contrast synchrotron tomography of the lungs has been shown to provide superior image quality compared with attenuation-based computed tomography (CT) in small-animal studies. The present study was performed to prove the applicability on a human-patient scale using a chest phantom with ventilated fresh porcine lungs. Local areas of interest were imaged with a pixel size of 100 µm, yielding a high-resolution depiction of anatomical hallmarks of healthy lungs and artificial lung nodules. Details like fine spiculations into surrounding alveolar spaces were shown on a micrometre scale. Minor differences in artificial lung nodule density were detected by phase retrieval. Since we only applied a fraction of the X-ray dose used for clinical high-resolution CT scans, it is believed that this approach may become applicable to the detailed assessment of focal lung lesions in patients in the future.

Echo time dependence of observed T1 in the human lung.

BACKGROUND: This work is intended to demonstrate that T1 measured in the lungs depends on the echo time (TE) used. Measuring lung T1 can be used to gain quantitative morphological and functional information. It is also shown that this dependence is particularly visible when using an ultra-short TE (UTE) sequence with TE well below 1 ms for T1 quantification in lung tissue, rather than techniques with TE on the order of 1-2 ms. METHODS: The lungs of 12 healthy volunteers (aged 22 to 33 years) were examined at 1.5 Tesla. A segmented inversion recovery Look-Locker multi-echo sequence based on two-dimensional UTE was used for independent T1 quantification at five TEs between TE1 = 70 µs and TE5 = 2.3 ms. RESULTS: The measured T1 was found to increase gradually with TE from 1060 ± 40 ms at TE1 to 1389 ± 53 ms at TE5 (P < 0.001). CONCLUSION: Measuring T1 at ultra-short echo times reveals a significant dependence of observed T1 on the echo time. Thus, any comparison of T1 values should also consider the TEs used. However, this dependence on TE could also be exploited to gain additional diagnostic information on the tissue compartments in the lung.

Free breathing 1H MRI of the human lung with an improved radial turbo spin-echo.

OBJECTIVE: To optimize a radial turbo spin-echo sequence for motion-robust morphological lung magnetic resonance imaging (MRI) in free respiration. MATERIALS AND METHODS: A versatile multi-shot radial turbo spin-echo (rTSE) sequence is presented, using a modified golden ratio-based reordering designed to prevent coherent streaking due to data inconsistencies from physiological motion and the decaying signal. The point spread function for a moving object was simulated using a model for joint respiratory and cardiac motion with a concomitant T2 signal decay and with rTSE acquisition using four different reordering techniques. The reordering strategies were compared in vivo using healthy volunteers and the sequence was tested for feasibility in two patients with lung cancer and pneumonia. RESULTS: Simulations and in vivo measurements showed very weak artifacts, aside from motion blur, using the proposed reordering. Due to the opportunity for longer scan times in free respiration, a high signal-to-noise ratio (SNR) was achieved, facilitating identification of the disease as compared to standard half-Fourier-acquisition single-shot turbo spin-echo (HASTE) scans. Additionally, post-processing allowed modifying the T2 contrast retrospectively, further improving the diagnostic fidelity. CONCLUSION: The proposed radial TSE sequence allowed for high-resolution imaging with limited obscuring artifacts. The radial k-space traversal allowed for versatile post-processing that may help to improve the diagnosis of subtle diseases.

Magnetic resonance imaging detects changes in structure and perfusion, and response to therapy in early cystic fibrosis lung disease.

RATIONALE: Studies demonstrating early structural lung damage in infants and preschool children with cystic fibrosis (CF) suggest that noninvasive monitoring will be important to identify patients who may benefit from early therapeutic intervention. Previous studies demonstrated that magnetic resonance imaging (MRI) detects structural and functional abnormalities in lungs from older patients with CF without radiation exposure. OBJECTIVES: To evaluate the potential of MRI to detect abnormal lung structure and perfusion in infants and preschool children with CF, and to monitor the response to therapy for pulmonary exacerbation. METHODS: MRI studies were performed in 50 children with CF (age, 3.1 ± 2.1 yr; range, 0-6 yr) in stable clinical condition (n = 40) or pulmonary exacerbation before and after antibiotic treatment (n = 10), and in 26 non-CF control subjects (age, 2.9 ± 1.9 yr). T1- and T2-weighted sequences before and after intravenous contrast and first-pass perfusion imaging were acquired, and assessed on the basis of a dedicated morphofunctional score. MEASUREMENTS AND MAIN RESULTS: MRI demonstrated bronchial wall thickening/bronchiectasis, mucus plugging, and perfusion deficits from the first year of life in most stable patients with CF (global score, 10.0 ± 4.0), but not in non-CF control subjects (score, 0.0 ± 0.0; P < 0.001). In patients with exacerbations, the global MRI score was increased to 18.0 ± 2.0 (P < 0.001), and was significantly reduced to 12.0 ± 3.0 (P < 0.05) after antibiotic therapy. CONCLUSIONS: MRI detected abnormalities in lung structure and perfusion, and response to therapy for exacerbations in infants and preschool children with CF. These results support the development of MRI for noninvasive monitoring and as an end point in interventional trials for early CF lung disease. Clinical trial registered with www.clinicaltrials.gov (NCT00760071).

Thoracic MRI in pleural infection - a feasibility study from patients' and radiographers' perspectives.

BACKGROUND: Pleural infections present significant clinical challenges, particularly in elderly or immunosuppressed patients, leading to prolonged hospital stay, high morbidity and high mortality. While CT and X-ray are standard imaging modalities, MRI's potential remain unexplored due to historical limitations in scan duration and patient discomfort. Advances in MRI technology, however, may enable its broader use in thoracic imaging. The study aimed to explore the feasibility of thoracic MRI from the radiographers' and patients' perspectives. METHODS: A prospective feasibility study was conducted involving thirteen patients with pleural infections who underwent thoracic MRI as an add-on within 48 h of the conventional contrast-enhanced chest CT. Feasibility was assessed on technical success, and scan duration. Patients and radiographers experiences were evaluated through questionnaires and qualitative comments. RESULTS: Technical success was high as all thirteen patients completed the scans. The mean in-room time was 30.7±5.5 minutes and the mean scan time was 23 ± 5.4 minutes. Radiographers reported the MRI scans as feasible with few patients requiring breaks or assistance. Most patients found the MRI experience manageable though two reported difficulties with breath-hold instructions. No patients were challenged by lying in supine position and no patients felt very anxious. No significant movement- or breathing artefacts were identified on MRI. CONCLUSION: Thoracic MRI is feasible with high technical success, acceptable scan time, and good patient experience in patients with pleural infections offering potential as a radiation-free imaging modality. Furthermore, compared to CT, the use of MRI showed potential advantages in identifying pleural effusion septations.

How do deep-learning models generalize across populations? Cross-ethnicity generalization of COPD detection.

OBJECTIVES: To evaluate the performance and potential biases of deep-learning models in detecting chronic obstructive pulmonary disease (COPD) on chest CT scans across different ethnic groups, specifically non-Hispanic White (NHW) and African American (AA) populations. MATERIALS AND METHODS: Inspiratory chest CT and clinical data from 7549 Genetic epidemiology of COPD individuals (mean age 62 years old, 56-69 interquartile range), including 5240 NHW and 2309 AA individuals, were retrospectively analyzed. Several factors influencing COPD binary classification performance on different ethnic populations were examined: (1) effects of training population: NHW-only, AA-only, balanced set (half NHW, half AA) and the entire set (NHW + AA all); (2) learning strategy: three supervised learning (SL) vs. three self-supervised learning (SSL) methods. Distribution shifts across ethnicity were further assessed for the top-performing methods. RESULTS: The learning strategy significantly influenced model performance, with SSL methods achieving higher performances compared to SL methods (p < 0.001), across all training configurations. Training on balanced datasets containing NHW and AA individuals resulted in improved model performance compared to population-specific datasets. Distribution shifts were found between ethnicities for the same health status, particularly when models were trained on nearest-neighbor contrastive SSL. Training on a balanced dataset resulted in fewer distribution shifts across ethnicity and health status, highlighting its efficacy in reducing biases. CONCLUSION: Our findings demonstrate that utilizing SSL methods and training on large and balanced datasets can enhance COPD detection model performance and reduce biases across diverse ethnic populations. These findings emphasize the importance of equitable AI-driven healthcare solutions for COPD diagnosis. CRITICAL RELEVANCE STATEMENT: Self-supervised learning coupled with balanced datasets significantly improves COPD detection model performance, addressing biases across diverse ethnic populations and emphasizing the crucial role of equitable AI-driven healthcare solutions. KEY POINTS: Self-supervised learning methods outperform supervised learning methods, showing higher AUC values (p < 0.001). Balanced datasets with non-Hispanic White and African American individuals improve model performance. Training on diverse datasets enhances COPD detection accuracy. Ethnically diverse datasets reduce bias in COPD detection models. SimCLR models mitigate biases in COPD detection across ethnicities.

Capturing COPD heterogeneity: anomaly detection and parametric response mapping comparison for phenotyping on chest computed tomography.

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. A novel self-supervised anomaly detection approach was applied to quantify lung abnormalities associated with COPD, as regional deviations. These regional anomaly scores were qualitatively and quantitatively compared, per GOLD class, to PRM volumes (emphysema: PRMEmph, functional small-airway disease: PRMfSAD) and to a Principal Component Analysis (PCA) and Clustering, applied on the self-supervised latent space. Its relationships to pulmonary function tests (PFTs) were also evaluated. Results: Initial t-Distributed Stochastic Neighbor Embedding (t-SNE) visualization of the self-supervised latent space highlighted distinct spatial patterns, revealing clear separations between regions with and without emphysema and air trapping. Four stable clusters were identified among this latent space by the PCA and Cluster Analysis. As the GOLD stage increased, PRMEmph, PRMfSAD, anomaly score, and Cluster 3 volumes exhibited escalating trends, contrasting with a decline in Cluster 2. The patient-wise anomaly scores significantly differed across GOLD stages (p < 0.01), except for never-smokers and GOLD 0 patients. In contrast, PRMEmph, PRMfSAD, and cluster classes showed fewer significant differences. Pearson correlation coefficients revealed moderate anomaly score correlations to PFTs (0.41-0.68), except for the functional residual capacity and smoking duration. The anomaly score was correlated with PRMEmph (r = 0.66, p < 0.01) and PRMfSAD (r = 0.61, p < 0.01). Anomaly scores significantly improved fitting of PRM-adjusted multivariate models for predicting clinical parameters (p < 0.001). Bland-Altman plots revealed that volume agreement between PRM-derived volumes and clusters was not constant across the range of measurements. Conclusion: Our study highlights the synergistic utility of the anomaly detection approach and traditional PRM in capturing the nuanced heterogeneity of COPD. The observed disparities in spatial patterns, cluster dynamics, and correlations with PFTs underscore the distinct - yet complementary - strengths of these methods. Integrating anomaly detection and PRM offers a promising avenue for understanding of COPD pathophysiology, potentially informing more tailored diagnostic and intervention approaches to improve patient outcomes.

Expiratory Venous Volume and Arterial Tortuosity are Associated with Disease Severity and Mortality Risk in Patients with COPD: Results from COSYCONET.

Purpose: The aim of this study was to evaluate the association between computed tomography (CT) quantitative pulmonary vessel morphology and lung function, disease severity, and mortality risk in patients with chronic obstructive pulmonary disease (COPD). Patients and Methods: Participants of the prospective nationwide COSYCONET cohort study with paired inspiratory-expiratory CT were included. Fully automatic software, developed in-house, segmented arterial and venous pulmonary vessels and quantified volume and tortuosity on inspiratory and expiratory scans. The association between vessel volume normalised to lung volume and tortuosity versus lung function (forced expiratory volume in 1 sec [FEV1]), air trapping (residual volume to total lung capacity ratio [RV/TLC]), transfer factor for carbon monoxide (TLCO), disease severity in terms of Global Initiative for Chronic Obstructive Lung Disease (GOLD) group D, and mortality were analysed by linear, logistic or Cox proportional hazard regression. Results: Complete data were available from 138 patients (39% female, mean age 65 years). FEV1, RV/TLC and TLCO, all as % predicted, were significantly (p < 0.05 each) associated with expiratory vessel characteristics, predominantly venous volume and arterial tortuosity. Associations with inspiratory vessel characteristics were absent or negligible. The patterns were similar for relationships between GOLD D and mortality with vessel characteristics. Expiratory venous volume was an independent predictor of mortality, in addition to FEV1. Conclusion: By using automated software in patients with COPD, clinically relevant information on pulmonary vasculature can be extracted from expiratory CT scans (although not inspiratory scans); in particular, expiratory pulmonary venous volume predicted mortality. Trial Registration: NCT01245933.