Ventilatory capacity in CLAD is driven by dysfunctional airway structure.

BACKGROUND: Chronic lung allograft dysfunction (CLAD) encompasses three main phenotypes: bronchiolitis obliterans syndrome (BOS), restrictive allograft syndrome (RAS) and a Mixed phenotype combining both pathologies. How the airway structure in its entirety is affected in these phenotypes is still poorly understood. METHODS: A detailed analysis of airway morphometry was applied to gain insights on the effects of airway remodelling on the distribution of alveolar ventilation in end-stage CLAD. Ex vivo whole lung µCT and tissue-core µCT scanning of six control, six BOS, three RAS and three Mixed explant lung grafts (9 male, 9 female, 2014-2021, Leuven, Belgium) were used for digital airway reconstruction and calculation of airway dimensions in relation to luminal obstructions. FINDINGS: BOS and Mixed explants demonstrated airway obstructions of proximal bronchioles (starting at generation five), while RAS explants particularly had airway obstructions in the most distal bronchioles (generation >12). In BOS and Mixed explants 76% and 84% of bronchioles were obstructed, respectively, while this was 22% in RAS. Bronchiolar obstructions were mainly caused by lymphocytic inflammation of the airway wall or fibrotic remodelling, i.e. constrictive bronchiolitis. Proximal bronchiolectasis and imbalance in distal lung ventilation were present in all CLAD phenotypes and explain poor lung function and deterioration of specific lung function parameters. INTERPRETATION: Alterations in the structure of conducting bronchioles revealed CLAD to affect alveolar ventilatory distribution in a regional fashion. The significance of various obstructions, particularly those associated with mucus, is highlighted. FUNDING: This research was funded with the National research fund Flanders (G060322N), received by R.V.

Impact of ultra-high-resolution imaging of the lungs on perceived diagnostic image quality using photon-counting CT.

OBJECTIVES: To compare clinical image quality and perceived impact on diagnostic interpretation of chest CT findings between ultra-high-resolution photon-counting CT (UHR-PCCT) and conventional high-resolution energy-integrating-detector CT (HR-EIDCT) using visual grading analysis (VGA) scores. MATERIALS AND METHODS: Fifty patients who underwent a UHR-PCCT (matrix 512 × 512, 768 × 768, or 1024 × 1024; FOV average 275 × 376 mm, 120 × 0.2 mm; focal spot size 0.6 × 0.7 mm) between November 2021 and February 2022 and with a previous HR-EIDCT within the last 14 months were included. Four readers evaluated central and peripheral airways, lung vasculature, nodules, ground glass opacities, inter- and intralobular lines, emphysema, fissures, bullae/cysts, and air trapping on PCCT (0.4 mm) and conventional EIDCT (1 mm) via side-by-side reference scoring using a 5-point diagnostic quality score. The median VGA scores were compared and tested using one-sample Wilcoxon signed rank tests with hypothesized median values of 0 (same visibility) and 2 (better visibility on PCCT with impact on diagnostic interpretation) at a 2.5% significance level. RESULTS: Almost all lung structures had significantly better visibility on PCCT compared to EIDCT (p < 0.025; exception for ground glass nodules (N = 2/50 patients, p = 0.157)), with the highest scores seen for peripheral airways, micronodules, inter- and intralobular lines, and centrilobular emphysema (mean VGA > 1). Although better visibility, a perceived difference in diagnostic interpretation could not be demonstrated, since the median VGA was significantly different from 2. CONCLUSION: UHR-PCCT showed superior visibility compared to HR-EIDCT for central and peripheral airways, lung vasculature, fissures, ground glass opacities, macro- and micronodules, inter- and intralobular lines, paraseptal and centrilobular emphysema, bullae/cysts, and air trapping. CLINICAL RELEVANCE STATEMENT: UHR-PCCT has emerged as a promising technique for thoracic imaging, offering improved spatial resolution and lower radiation dose. Implementing PCCT into daily practice may allow better visibility of multiple lung structures and optimization of scan protocols for specific pathology. KEY POINTS: • The aim of this study was to verify if the higher spatial resolution of UHR-PCCT would improve the visibility and detection of certain lung structures and abnormalities. • UHR-PCCT was judged to have superior clinical image quality compared to conventional HR-EIDCT in the evaluation of the lungs. UHR-PCCT showed better visibility for almost all tested lung structures (except for ground glass nodules). • Despite superior image quality, the readers perceived no significant impact on the diagnostic interpretation of the studied lung structures and abnormalities.

Computed tomography-based machine learning for donor lung screening before transplantation.

BACKGROUND: Assessment and selection of donor lungs remain largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo computed tomography (CT) images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs before transplantation. METHODS: Clinical measures and ex situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner before transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning, which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures. RESULTS: Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) before CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the intensive care unit and were at 19 times higher risk of developing chronic lung allograft dysfunction within 2 years posttransplant. CONCLUSIONS: We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of posttransplant complications.

Prognostic Value of Chest CT Findings at BOS Diagnosis in Lung Transplant Recipients.

BACKGROUND: Bronchiolitis obliterans syndrome (BOS) after lung transplantation is characterized by fibrotic small airway remodeling, recognizable on high-resolution computed tomography (HRCT). We studied the prognostic value of key HRCT features at BOS diagnosis after lung transplantation. METHODS: The presence and severity of bronchiectasis, mucous plugging, peribronchial thickening, parenchymal anomalies, and air trapping, summarized in a total severity score, were assessed using a simplified Brody II scoring system on HRCT at BOS diagnosis, in a cohort of 106 bilateral lung transplant recipients transplanted between January 2004 and January 2016. Obtained scores were subsequently evaluated regarding post-BOS graft survival, spirometric parameters, and preceding airway infections. RESULTS: A high total Brody II severity score at BOS diagnosis (P = 0.046) and high subscores for mucous plugging (P = 0.0018), peribronchial thickening (P = 0.0004), or parenchymal involvement (P = 0.0121) are related to worse graft survival. A high total Brody II score was associated with a shorter time to BOS onset (P = 0.0058), lower forced expiratory volume in 1 s (P = 0.0006) forced vital capacity (0.0418), more preceding airway infections (P = 0.004), specifically with Pseudomonas aeruginosa (P = 0.002), and increased airway inflammation (P = 0.032). CONCLUSIONS: HRCT findings at BOS diagnosis after lung transplantation provide additional information regarding its underlying pathophysiology and for future prognosis of graft survival.

The Reversed Halo Sign in Pulmonary Infarction due to Acute Pulmonary Embolism.

The reversed halo sign, or atoll sign, is a specific sign with ring-shaped consolidation and central lucency, which is historically considered typical for cryptogenic organising pneumonia. The presence of this sign in subpleural, posterior basal parts of the lower lobes, especially when solitary, should however raise suspicion for other causes, such as pulmonary infarction. Here, we present a case of pulmonary embolism with pulmonary infarction that was detected on HRCT without contrast. Teaching Point: The presence of a reversed halo sign, especially when solitary and located in the periphery of the lower lobes, should raise suspicion of a pulmonary infarction.

Multiple Micronodular Pneumocyte Hyperplasia (MMPH): A Less-Known Presentation of Tuberous Sclerosis Complex Related Lung Disease.

Teaching Point: Multiple micronodular pneumocyte hyperplasia (MMPH) is a less-known presentation of tuberous sclerosis complex (TSC) associated lung disease that usually requires no treatment or follow-up imaging.

CT-based Machine Learning for Donor Lung Screening Prior to Transplantation.

Background: Assessment and selection of donor lungs remains largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo CT images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs prior to transplantation. Methods: Clinical measures and ex-situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner prior to transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning , which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures. Results: Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) prior to CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the ICU and were at 19 times higher risk of developing CLAD within 2 years post-transplant. Conclusions: We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of post-transplant complications.

Granulomatous Lymphocytic Interstitial Lung Disease (GLILD) in Common Variable Immunodeficiency (CVID).

Teaching Point: Granulomatous lymphocytic interstitial lung disease is a non-infectious complication of common variable immunodeficiency. Computed tomography (CT) has an important diagnostic value by demonstrating pulmonary nodules, ground glass opacities, bronchiectasis, subpleural reticulations, lymphadenopathy and splenomegaly.

Insidious Onset of Pulmonary Langerhans Cell Histiocytosis During Oncological Follow-Up.

Teaching Point: Pulmonary Langerhans cell histiocytosis (PLCH) has to be included in the differential diagnosis of cystic pulmonary lesions on chest computed tomography (CT). CT has important diagnostic value by demonstrating initial centrilobular nodules that in time cavitate and transform into cysts, typically sparing the costophrenic angles.

Pedunculated Epipericardial Fat Torsion: A Subtle Clinical and Radiological Mimicker.

Teaching Point: Epipericardial fat torsion is a little-known and uncommon condition with sometimes subtle findings making general awareness essential for detection and for confident diagnosis.

Radiological findings in low-dose CT for COVID-19 pneumonia in 182 patients: Correlation of signs and severity with patient outcome.

ABSTRACT: To characterize computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) pneumonia and their value in outcome prediction.Chest CTs of 182 patients with a confirmed diagnosis of COVID-19 infection by real-time reverse transcription polymerase chain reaction were evaluated for the presence of CT-abnormalities and their frequency. Regarding the patient outcome each patient was categorized in 5 progressive stages and the duration of hospitalization was determined. Regression analysis was performed to find which CT findings are predictive for patient outcome and to assess prognostic factors for the hospitalization duration.Multivariate statistical analysis confirmed a higher age (OR = 1.023, P  =  .025), a higher total visual severity score (OR = 1.038, P  =  .002) and the presence of crazy paving (OR = 2.160, P  =  .034) as predictive parameters for patient outcome. A higher total visual severity score (+0.134 days; P  =  .012) and the presence of pleural effusion (+13.985 days, P  =  0.005) were predictive parameters for a longer hospitalization duration. Moreover, a higher sensitivity of chest CT (false negatives 10.4%; true positives 78.6%) in comparison to real-time reverse transcription polymerase chain reaction was obtained.An increasing percentage of lung opacity as well as the presence of crazy paving and a higher age are associated with a worse patient outcome. The presence of a higher total visual severity score and pleural effusion are significant predictors for a longer hospitalization duration. These results are underscoring the value of chest CT as a diagnostic and prognostic tool in the pandemic outbreak of COVID-19, to facilitate fast detection and to preserve the limited (intensive) care capacity only for the most vulnerable patients.

Defining and predicting progression in non-IPF interstitial lung disease.

Randomized placebo-controlled trials demonstrated the efficacy of antifibrotic treatment in non-IPF progressive fibrosing ILD (fILD). Currently, there is no consensus on how progression should be defined and clinical data of non-IPF fILD patients in a real-world setting are scarce. Non-IPF fILD patients presenting at the University Hospitals Leuven between 2012 and 2016 were included. Different definitions of progression according to the selection criteria of the INBUILD, RELIEF and the uILD study were retrospectively evaluated at every hospital visit. Univariate and multivariate analyses were performed to identify predictors of progression and mortality. The study cohort comprised 120 patients; 68.3%, 54.2% and 65.8% had progressive disease based on the INBUILD, RELIEF and uILD study, respectively. A large overlap of progressive fILD patients according to the different clinical trials was observed. Median transplant-free survival time of progressive fILD patients was 3.9, 3.9, 3.8 years and the median time-to-progression after diagnosis was 2.0, 3.1 and 2.3 years according to the INBUILD, RELIEF and uILD study, respectively. We identified several predictors of mortality, but only an underlying diagnosis of HP and uILD was independently associated with progression. Our data show a high prevalence of progressive fibrosis among non-IPF fILD patients and a discrepancy between predictors of mortality and progression. Mortality rate in fILD is high and the identification of progressive disease is only made late during the disease course. Moreover, future treatment decisions will be based upon disease behavior. Therefore, more predictors of progressive disease are needed to guide treatment decisions in the future.

CT-Guided Transthoracic Biopsy of Lung Lesions Using a Non-Coaxial Biopsy Needle Technique: CT Characteristics Predictive for Diagnostic Accuracy and Pneumothorax.

OBJECTIVES: To analyze computed tomography (CT) characteristics predictive for diagnostic accuracy and pneumothorax in CT fluoroscopy-guided transthoracic biopsy (CTF-TTB) of lung lesions using non-coaxial biopsy needle technique. METHODS: Retrospectively 274 lung lesion biopsies with confirmed histology were included in our study. CTF-TTB was done using an 18-gauge non-coaxial cutting needle. Diagnostic accuracy rates were calculated per lesion size and CT and procedural characteristics were evaluated for their predictive value regarding diagnostic accuracy and development of pneumothorax (maximal nodule diameter, distance to pleura, location per lung segment, nodule composition, benign versus malignant histology, and number of specimens). RESULTS: Overall diagnostic accuracy of CTF-TTB was high (93%). Diagnostic accuracy for lesions ≤10 mm was 81%. Maximal nodule diameter was the only predictive CT characteristic for diagnostic success (p = 0.03). Pneumothorax occurred in 27%. Distance of lesion to pleura was the only risk factor for pneumothorax (p < 0.00001). Pneumothorax rates were significantly lower in subpleural lesions (14%) compared to those located 1-10 mm (47%), 10-20 mm (33%), and >20 mm from pleura (29%). CONCLUSIONS: High diagnostic accuracy rates were achieved with CTF-TTB using non-coaxial biopsy technique, even for lesions ≤10 mm. Pneumothorax rates were comparable with other studies. Lesion size was the only predictive CT characteristic for diagnostic accuracy. Distance to pleura was the only risk factor for pneumothorax.

Comparing Visual Scoring of Lung Injury with a Quantifying AI-Based Scoring in Patients with COVID-19.

OBJECTIVES: Fast diagnosis of Coronavirus Disease 2019 (COVID-19), and the detection of high-risk patients are crucial but challenging in the pandemic outbreak. The aim of this study was to evaluate if deep learning-based software correlates well with the generally accepted visual-based scoring for quantification of the lung injury to help radiologist in triage and monitoring of COVID-19 patients. MATERIALS AND METHODS: In this retrospective study, the lobar analysis of lung opacities (% opacities) by means of a prototype deep learning artificial intelligence (AI)-based software was compared to visual scoring. The visual scoring system used five categories (0: 0%, 1: 0-5%, 2: 5-25%, 3: 25-50%, 4: 50-75% and 5: >75% involvement). The total visual lung injury was obtained by the sum of the estimated grade of involvement of each lobe and divided by five. RESULTS: The dataset consisted of 182 consecutive confirmed COVID-19 positive patients with a median age of 65 ± 16 years, including 110 (60%) men and 72 (40%) women. There was a correlation coefficient of 0.89 (p < 0.001) between the visual and the AI-based estimates of the severity of lung injury. CONCLUSION: The study indicates a very good correlation between the visual scoring and AI-based estimates of lung injury in COVID-19.

Performance of Low-Dose Chest CT as a Triage Tool for Suspected COVID-19 Patients.

PURPOSE: To investigate the role of low-dose chest computed tomography (CT) imaging in the triage of patients suspected of coronavirus disease 2019 (COVID-19) in an emergency setting. MATERIALS AND METHODS: Data from 610 patients admitted to our emergency unit from March 20, 2020, until April 11, 2020, with suspicion of COVID-19 were collected. Diagnostic values of low-dose chest CT for COVID-19 were calculated using consecutive reverse-transcription polymerase chain reaction (RT-PCR) tests and bronchoalveolar lavage (BAL) as reference. Comparative analysis of the 199 COVID-19 positive versus 411 COVID-19 negative patients was done with identification of risk factors and predictors of worse outcome. RESULTS: Sensitivity and specificity of low-dose CT for the diagnosis of COVID-19 respectively ranged from 75% (150/199) to 88% (175/199) and 94% (386/411) to 99% (386/389), depending on the inclusion of inconclusive results. On multivariate analysis, a higher body mass index (BMI), fever, and dyspnea on admission were risk factors for COVID-19 (all p-values < 0.05). The mortality rate was 12.6% (25/199). Higher age and high levels of C-reactive protein (CRP) and D-dimers were predictors of worse outcome (all p-values < 0.05). CONCLUSION: Low-dose chest CT has a high specificity and a moderate to high sensitivity in symptomatic patients with suspicion of COVID-19 and could be used as an effective tool in setting of triage in high-prevalence areas.

Distinct Airway Involvement in Subtypes of End-Stage Fibrotic Pulmonary Sarcoidosis.

BACKGROUND: Sarcoidosis is a systemic granulomatous disease that in most patients affects the lung. Pulmonary fibrotic sarcoidosis is clinically, radiologically, and pathologically a heterogeneous condition. Although substantial indirect evidence suggests small airways involvement, direct evidence currently is lacking. RESEARCH QUESTION: What is the role of the (small) airways in fibrotic sarcoidosis? STUDY DESIGN AND METHODS: Airway morphologic features were investigated in seven explant lungs with end-stage fibrotic sarcoidosis using a combination of CT scanning (large airways), micro-CT scanning (small airways), and histologic examination and compared with seven unused donor lungs as controls with specific attention focused on different radiologically defined sarcoidosis subtypes. RESULTS: Patients with central bronchial distortion (n = 3), diffuse bronchiectasis (n = 3), and usual interstitial pneumonia pattern (n = 1) were identified based on CT scan, showing a decrease and narrowing of large airways, a similar airway number and increased airway diameter of more distal airways, or an increase in airway number and airway diameter, respectively, compared with control participants. The number of terminal bronchioles per milliliter and the total number of terminal bronchioles were decreased in all forms of fibrotic sarcoidosis. Interestingly, the number of terminal bronchioles was inversely correlated with the degree of fibrosis. Furthermore, we identified granulomatous remodeling as a cause of small airways loss using serial micro-CT scanning and histologic examination. INTERPRETATION: The large airways are involved differentially in subtypes of sarcoidosis, but the terminal bronchioles universally are lost. This suggests that small airways loss forms an important aspect in the pathophysiologic features of fibrotic pulmonary sarcoidosis.

Hemoptysis after Lung Transplantation Caused by Bronchial Arterial Neovascularization: Angiographic Analysis and Successful Embolization.

This report discusses 3 bilateral lung transplant recipients (2 female, 1 male) who presented with late hemoptysis (10 y, 18 y, and 19 y after transplantation). All patients had a history of pulmonary infections, bronchiectasis, and/or Aspergillus infection. Arteriography, through catherization of the common femoral artery, demonstrated spontaneous bronchial and systemic neovascularization arising from the thyrocervical trunk, internal thoracic artery, intercostal arteries, and dorsal scapular artery. Embolization was performed with microspheres, polyvinyl alcohol microparticles, and/or glue and effectively terminated hemoptysis. One patient died 10 d later as a result of fungal infection, and the 2 others remained in stable condition (18- and 26-mo postembolization follow-up available).

Identification and characterization of chronic lung allograft dysfunction patients with mixed phenotype: A single-center study.

RATIONALE: Patients can change chronic lung allograft dysfunction (CLAD) phenotype, especially from BOS to mixed phenotype. Our aim was to further characterize these patients. METHOD: Mixed CLAD was defined as a restrictive physiology with persistent CT opacities, after initial bronchiolitis obliterans syndrome (BOS) diagnosis. The incidence, prognosis, pulmonary function, radiology, pathology, and airway inflammation were compared between patients with restrictive allograft syndrome (RAS) and mixed CLAD. RESULT: A total of 268 (44%) patients developed CLAD of which 47 (18%) were diagnosed with RAS "ab initio," 215 (80%) with BOS, and 6 (2%) an undefined phenotype. Twenty-five patients developed a mixed CLAD phenotype (24 BOS to mixed and 1 RAS to mixed). Survival after mixed phenotype diagnosis was comparable (P = .39) to RAS. More emphysema patients developed a mixed phenotype (P = .020) compared to RAS ab initio, while mixed CLAD patients had a lower FEV1 (P < .0001) and FEV1 /FVC (P = .0002) at diagnosis compared to RAS ab initio. CT scans in patients with the mixed phenotype demonstrated apical predominance of the opacities (P = .0034) with pleuroparenchymal fibroelastosis on histopathology. CONCLUSION: We further characterized patients with a mixed phenotype of CLAD. Although the survival after diagnosis was comparable to RAS ab initio patients, there was a difference in demography, pulmonary function, radiology, and pathology.

Histopathologic and radiologic assessment of nontransplanted donor lungs.

Donor organ shortage results in significant waiting list mortality. Donor lung assessment is currently based on donors' history, gas exchange, chest X-ray, bronchoscopy findings, and ultimately in situ inspection but remains subjective. We correlated histopathology and radiology in nontransplanted donor lungs with the clinical indications to decline the offered organ. Sixty-two donor lungs, not used for transplantation (2010-2019), were procured, air-inflated, frozen, scanned with computed tomography, systematically sampled, and histologically and radiologically assessed. Thirty-nine (63%) lungs were declined for allograft-related reasons. In 13/39 (33%) lungs, histology could not confirm the reason for decline, in an additional 8/39 (21%) lungs, histologic abnormalities were only considered mild. In 16/39 (41%) lungs, radiology could not confirm the reason for decline. Twenty-three (37%) donor lungs were not transplanted due to extrapulmonary causes, of which three (13%) lungs displayed severe histologic abnormalities (pneumonia, n = 2; emphysema, n = 1), in addition to mild emphysema in 9 (39%) lungs and minor bronchopneumonia in 1 (4%). Radiology revealed ground-glass opacities in 8/23 (35%) and emphysema in 4/23 (17%) lungs. Histopathologic and radiologic assessment of nontransplanted donor lungs revealed substantial discrepancy with the clinical reason for decline. Optimization of donor lung assessment is necessary to improve current organ acceptance rates.