Lung Density Analysis Using Quantitative Chest CT for Early Prediction of Chronic Lung Allograft Dysfunction

Percentage of low attenuation area on computed tomography detects chronic lung allograft dysfunction, especially bronchiolitis obliterans syndrome, after bilateral lung transplantation

INTRODUCTION

The percentage of low attenuation area (%LAA) on computed tomography (CT) is useful for evaluating lung emphysema, and higher %LAA was observed in patients with chronic lung allograft dysfunction (CLAD). This study investigated the relationship between the %LAA and the development of CLAD after bilateral lung transplantation (LT).

METHODS

We conducted a single-center retrospective study of 75 recipients who underwent bilateral LT; the recipients were divided into a CLAD group (n = 30) and a non-CLAD group (n = 45). The %LAA was calculated using CT and compared between the two groups from 4 years before to 4 years after the diagnosis of CLAD. The relationships between the %LAA and the percent baseline values of the pulmonary function test parameters were also calculated.

RESULTS

The %LAA was significantly higher in the CLAD group than in the non-CLAD group from 2 years before to 2 years after the diagnosis of CLAD (P < .05). In particular, patients with bronchiolitis obliterans syndrome (BOS) exhibited significant differences even from 4 years before to 4 years after diagnosis (P < .05). Significant negative correlations between the %LAA and the percent baseline values of the forced expiratory volume in 1 s (r = -.36, P = .0031), the forced vital capacity (r = -.27, P = .027), and the total lung capacity (r = -.40, P < .001) were seen at the time of CLAD diagnosis.

CONCLUSION

The %LAA on CT was associated with the development of CLAD and appears to have the potential to predict CLAD, especially BOS, after bilateral LT.

[Chronic lung allograft dysfunction in 2022, past and updates]

INTRODUCTION

While short-term results of lung transplantation have improved considerably, long-term survival remains below that achieved for other solid organ transplants.

CURRENT KNOWLEDGE

The main cause of late mortality is chronic lung allograft dysfunction (CLAD), which affects nearly half of the recipients 5 years after transplantation. Immunological and non-immune risk factors have been identified. These factors activate the innate and adaptive immune system, leading to lesional and altered wound-healing processes, which result in fibrosis affecting the small airways or interstitial tissue. Several phenotypes of CLAD have been identified based on respiratory function and imaging pattern. Aside from retransplantation, which is possible for only small number of patients, no treatment can reverse the CLAD process.

PERSPECTIVES

Current therapeutic research is focused on anti-fibrotic treatments and photopheresis. Basic research has identified numerous biomarkers that could prove to be relevant as therapeutic targets.

CONCLUSION

While the pathophysiological mechanisms of CLAD are better understood than before, a major therapeutic challenge remains.

Biomarkers for Chronic Lung Allograft Dysfunction: Ready for Prime Time?

Chronic lung allograft dysfunction (CLAD) remains a major hurdle impairing lung transplant outcome. Parallel to the better clinical identification and characterization of CLAD and CLAD phenotypes, there is an increasing urge to find adequate biomarkers that could assist in the earlier detection and differential diagnosis of CLAD phenotypes, as well as disease prognostication. The current status and state-of-the-art of biomarker research in CLAD will be discussed with a particular focus on radiological biomarkers or biomarkers found in peripheral tissue, bronchoalveolar lavage' and circulating blood' in which significant progress has been made over the last years. Ultimately, although a growing number of biomarkers are currently being embedded in the follow-up of lung transplant patients, it is clear that one size does not fit all. The future of biomarker research probably lies in the rigorous combination of clinical information with findings in tissue, bronchoalveolar lavage' or blood. Only by doing so, the ultimate goal of biomarker research can be achieved, which is the earlier identification of CLAD before its clinical manifestation. This is desperately needed to improve the prognosis of patients with CLAD after lung transplantation.

Transition from BOS to RAS impairs prognosis after lung transplantation-CLAD subtype analysis by CT volumetry

Background

Chronic lung allograft dysfunction (CLAD), subclassified into bronchiolitis obliterans syndrome (BOS) or restrictive allograft syndrome (RAS), limits survival after lung transplantation. Information concerning transition from BOS to RAS is limited. We aimed to characterize the lung volume change after BOS diagnosis by computed tomography (CT) volumetry and to determine the incidence, risk factors and clinical significance of BOS to RAS transition.

Methods

CT volumetry measurements were performed from 63 patients with CLAD initially classified as BOS by CT volumetry. BOS patients with lung volume remaining >85% of baseline were classified as persistent BOS, whereas BOS patients whose lung volume permanently decreased to ≤85% of baseline were classified as BOS to RAS transition.

Results

During follow-up (median 9.8 years) eight patients (12.7%) were classified as BOS to RAS transition, which decreased recipient (p = 0.004) and graft survival (p = 0.020) in comparison to patients with persistent BOS. Opacities on chest imaging preceded BOS to RAS transition in 88% of patients. Opacities on chest imaging at BOS diagnosis and early CLAD diagnosis after transplantation were risk factors for transition.

Conclusion

Based on lung volume decrease measured by CT volumetry, a small proportion of BOS patients transitioned to RAS which had an adverse effect on recipient and graft survival.

Predefined and data driven CT densitometric features predict critical illness and hospital length of stay in COVID-19 patients

The aim of this study was to compare whole lung CT density histograms to predict critical illness outcome and hospital length of stay in a cohort of 80 COVID-19 patients. CT chest images on segmented lungs were retrospectively analyzed. Functional Principal Component Analysis (FPCA) was used to find the main modes of variations on CT density histograms. CT density features, the CT severity score, the COVID-GRAM score and the patient clinical data were assessed for predicting the patient outcome using logistic regression models and survival analysis. ROC analysis predictors of critically ill status: 87.5th percentile CT density (Q875)—AUC 0.88 95% CI (0.79 0.94), F1-CT—AUC 0.87 (0.77 0.93) Standard Deviation (SD-CT)—AUC 0.86 (0.73, 0.93). Multivariate models combining CT-density predictors and Neutrophil–Lymphocyte Ratio showed the highest accuracy. SD-CT, Q875 and F1 score were significant predictors of hospital length of stay (LOS) while controlling for hospital death using competing risks models. Moreover, two multivariate Fine-Gray regression models combining the clinical variables: age, NLR, Contrast CT factor with either Q875 or F1 CT-density predictors revealed significant effects for the prediction of LOS incidence in presence of a competing risk (death) and acceptable predictive performances (Bootstrapped C-index 0.74 [0.70 0.78]).

Novel biomarkers of chronic lung allograft dysfunction: is there anything reliable?

PURPOSE OF REVIEW

Chronic lung allograft dysfunction (CLAD) remains a major barrier preventing long-term survival following lung transplantation. As our clinical knowledge regarding its definition and presentation has significantly improved over the last years, adequate biomarkers to predict development of CLAD, phenotype of CLAD or prognosis post-CLAD diagnosis are definitely needed.

RECENT FINDINGS

Radiological and physiological markers are gradually entering routine clinical practice. In-depth investigation of biological samples including broncho-alveolar lavage, biopsy and serum has generated potential biomarkers involved in fibrogenesis, airway injury and inflammation but none of these are universally accepted or implemented although progress has been made, specifically regarding donor-derived cell-free DNA and donor-specific antibodies.

SUMMARY

Although a lot of promising biomarkers have been put forward, a very limited number has made it to routine clinical practice. Nevertheless, a biomarker that leads to earlier detection or more adequate disease phenotyping would advance the field enormously.

Chronic lung allograft dysfunction phenotype and prognosis by machine learning CT analysis

BACKGROUND

Chronic lung allograft dysfunction (CLAD) is the principal cause of graft failure in lung transplant recipients and prognosis depends on CLAD phenotype. We used machine learning computed tomography (CT) lung texture analysis tool at CLAD diagnosis for phenotyping and prognostication compared to radiologists' scoring.

METHODS

This retrospective study included all adult first double-lung transplant patients (01/2010-12/2015) with CLAD (censored 12/2019) and inspiratory CT near CLAD diagnosis. The machine learning tool quantified ground-glass opacity, reticulation, hyperlucent lung, and pulmonary vessel volume (PVV). Two radiologists scored for ground-glass opacity, reticulation, consolidation, pleural effusion, air trapping and bronchiectasis. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of machine learning and radiologist for CLAD phenotype. Multivariable Cox proportional-hazards regression analysis for allograft survival controlled for age, sex, native lung disease, cytomegalovirus serostatus, and CLAD phenotype (bronchiolitis obliterans syndrome [BOS] and restrictive allograft syndrome [RAS]/mixed).

RESULTS

88 patients were included (57 BOS, 20 RAS/mixed, and 11 unclassified/undefined) with CT a median 9.5 days from CLAD onset. Radiologist and machine learning parameters phenotyped RAS/mixed with PVV as the strongest indicator (AUC 0.85). Machine learning hyperlucent lung phenotyped BOS using only inspiratory CT (AUC=0.76). Radiologist and machine learning parameters predicted graft failure in the multivariable analysis, best with PVV (HR=1.23, 95%CI 1.05-1.44, p=0.01).

CONCLUSIONS

Machine learning discriminated between CLAD phenotypes on CT. Both radiologist and machine learning scoring were associated with graft failure, independent of CLAD phenotype. PVV, unique to machine learning, was the strongest in phenotyping and prognostication.

Chronic lung allograft dysfunction subtype analysis by computed tomography volumetry

BACKGROUND

Chronic lung allograft dysfunction (CLAD) limits long-term survival after lung transplantation. Of the two subtypes, restrictive allograft syndrome (RAS) is characterized by a larger lung volume decrease and worse prognosis than bronchiolitis obliterans syndrome (BOS). We used computed tomography (CT) volumetry to classify CLAD subtypes and determined their clinical impact.

METHODS

Adult primary lung transplants performed 2003-2015 (n = 167) were retrospectively evaluated for CLAD and subclassified with CT volumetry. Lung volume decrease of < 15% from baseline resulted in BOS_CT-vol and ≥15% resulted in RAS_CT-vol diagnosis. Clinical impact of CLAD subtypes was defined, and the prognostic value of different lung function, radiological, and lung volume parameters present at the time of CLAD diagnosis were compared.

RESULTS

CLAD affected 43% of patients and was classified with CT volumetry as BOS_CT-vol in 89% and RAS_CT-vol in 11%. Median graft survival estimate in RAS_CT-vol was significantly decreased compared to BOS_CT-vol (1.6 vs. 9.7 years, P = .038). At CLAD onset, RAS_CT-vol diagnosis (P = .05), increased lung density (P = .007), and more severe FEV1 (P = .004) decline from baseline, increased graft loss risk in multivariate analysis.

CONCLUSIONS

CT volumetry serves to identify lung transplant patients with a poor clinical outcome but should be validated in prospective trials.

Radiographic Graft Surveillance in Lung Transplantation: Prognostic Role of Parametric Response Mapping

RATIONALE

Chronic lung allograft dysfunction (CLAD) results in significant morbidity following lung transplantation. Potential CLAD occurs when lung function declines to 80-90% of baseline. Better non-invasive tools to prognosticate at potential CLAD are needed.

OBJECTIVES

To determine if parametric response mapping (PRM), a CT voxel-wise methodology, applied to high resolution CT scans can identify patients at risk of progression to CLAD or death.

METHODS

Radiographic features and PRM-based CT metrics quantifying functional small airways disease (PRMfSAD) and parenchymal disease (PRMPD) were studied at potential CLAD (n=61). High PRMfSAD and high PRMPD were defined as ≥ 30%. Restricted mean modeling was performed to compare CLAD-free survival among groups.

MEASUREMENTS AND MAIN RESULTS

PRM metrics identified 3 unique signatures: high PRMfSAD (11.5%), high PRMPD (41%) and neither (PRMNormal; 47.5%). Patients with high PRMfSAD or PRMPD had shorter CLAD-free median survival times (0.46 years and 0.50 years) compared to patients with predominantly PRMNormal (2.03 years; p=0.004 and 0.007 compared to PRMfSAD and PRMPD groups, respectively). In multivariate modeling adjusting for single versus double lung transplant, age at transplant, BMI at potential CLAD, and time from transplant to CT, PRMfSAD or PRMPD ≥ 30% continue to be statistically significant predictors of shorter CLAD-free survival. Air trapping by radiologist interpretation was common (66%), similar across PRM groups, and was not predictive of CLAD-free survival. Ground glass opacities by radiologist read occurred in 16% of cases and was associated with decreased CLAD-free survival (p<0.001).

CONCLUSIONS

PRM analysis offers valuable prognostic information at potential CLAD, identifying patients most at risk of developing CLAD or death.

Chronic Lung Allograft Dysfunction: Evolving Concepts and Therapies

The primary factor that limits long-term survival after lung transplantation is chronic lung allograft dysfunction (CLAD). CLAD also impairs quality of life and increases the costs of medical care. Our understanding of CLAD continues to evolve. Consensus definitions of CLAD and the major CLAD phenotypes were recently updated and clarified, but it remains to be seen whether the current definitions will lead to advances in management or impact care. Understanding the potential differences in pathogenesis for each CLAD phenotype may lead to novel therapeutic strategies, including precision medicine. Recognition of CLAD risk factors may lead to earlier interventions to mitigate risk, or to avoid risk factors all together, to prevent the development of CLAD. Unfortunately, currently available therapies for CLAD are usually not effective. However, novel therapeutics aimed at both prevention and treatment are currently under investigation. We provide an overview of the updates to CLAD-related terminology, clinical phenotypes and their diagnosis, natural history, pathogenesis, and potential strategies to treat and prevent CLAD.

Lung Transplantation: CT Assessment of Chronic Lung Allograft Dysfunction (CLAD)

Chronic lung allograft rejection remains one of the major causes of morbi-mortality after lung transplantation. The term Chronic Lung Allograft Dysfunction (CLAD) has been proposed to describe the different processes that lead to a significant and persistent deterioration in lung function without identifiable causes. The two main phenotypes of CLAD are Bronchiolitis Obliterans Syndrome (BOS) and Restrictive Allograft Syndrome (RAS), each of them characterized by particular functional and imaging features. These entities can be associated (mixed phenotype) or switched from one to the other. If CLAD remains a clinical diagnosis based on spirometry, computed tomography (CT) scan plays an important role in the diagnosis and follow-up of CLAD patients, to exclude identifiable causes of functional decline when CLAD is first suspected, to detect early abnormalities that can precede the diagnosis of CLAD (particularly RAS), to differentiate between the obstructive and restrictive phenotypes, and to detect exacerbations and evolution from one phenotype to the other. Recognition of early signs of rejection is crucial for better understanding of physiopathologic pathways and optimal management of patients.

Chronic Lung Allograft Dysfunction Post Lung Transplantation: A Review of Computed Tomography Quantitative Methods for Detection and Follow-Up

Chronic lung allograft dysfunction (CLAD) remains the leading cause of morbidity and mortality after lung transplantation. The term encompasses both obstructive and restrictive phenotypes, as well as mixed and undefined phenotypes. Imaging, in addition to pulmonary function tests, plays a major role in identifying the CLAD phenotype and is essential for follow-up after lung transplantation. Quantitative imaging allows for the performing of reader-independent precise evaluation of CT examinations. In this review article, we will discuss the role of quantitative imaging methods for evaluating the airways and the lung parenchyma on computed tomography (CT) images, for an early identification of CLAD and for prognostic estimation. We will also discuss their limits and the need for novel approaches to predict, understand, and identify CLAD in its early stages.

Differentiation of usual vertebral compression fractures using CT histogram analysis as quantitative biomarkers: A proof-of-principle study

PURPOSE

To investigate the utility of CT histogram analysis (CTHA) for discrimination of traumatic, osteoporotic and malignant fractures in patients with vertebral compression fractures (VCFs). To evaluate the feasibility and accuracy of CTHA in differentiating non-malignant (traumatic and osteoporotic) from malignant VCFs.

MATERIALS AND METHODS

Totally, 235 patients with VCFs were enrolled in the current experimental study. There were 132 patients with traumatic VCFs, 51 with osteoporotic VCFs and 52 with malignant VCFs, with MRI and histology as the standard references. All the patients underwent unenhanced CT scans. Nineteen histogram-based parameters were derived using Omni-Kinetics software (Omni-Kinetics, GE Healthcare). The reproducibility of those parameters was evaluated using two independent delineations conducted by two observers. These histogram parameters were compared among the three different VCFs using Kruskal-Wallis H test. Traumatic VCFs and osteoporotic VCFs were combined as non-malignant VCFs and compared with malignant VCFs using Mann-Whitney U test Multivariable logistic regression analysis was performed on the significantly different features and built a diagnosis model. Receiver operating characteristic (ROC) curve was carried out to observe the difference of diagnostic performance between the single positive parameter and the combination of parameters.

RESULTS

All the 19 parameters presented excellent reproducibility, with intraclass correlation coefficient values from 0.789 to 0.997. At quantitative evaluation, the best predictive histogram parameters in discrimination of the three different types of VCFs were relative min intensity (p = 0.022), relative entropy (p = 0.043), and relative frequency size (p < 0.001). Relative frequency size (p < 0.001) and relative quantile5 (p = 0.012) resulted in statistically significant difference between non-malignant and malignant VCFs. The area under ROC curve indicated that relative frequency size combined with relative quantile5 (0.754; 95 % confidence intervals: 0.661∼0.829; p < 0.001) was of best performance in differentiating malignant from non-malignant VCFs.

CONCLUSIONS

Our results are encouraging and suggest that histogram parameters derived from unenhanced CT could be reliable quantitative biomarkers for diff ;erential diagnosis of usual VCFs.

Shorter telomere length following lung transplantation is associated with clinically significant leukopenia and decreased chronic lung allograft dysfunction-free survival

Patients with short telomeres and interstitial lung disease may have decreased chronic lung allograft dysfunction (CLAD)-free survival following lung transplantation. The relationship between post-transplant telomere length and outcomes following lung transplantation has not been characterised among all recipients, regardless of native lung disease.

This was a single-centre prospective cohort study. Consenting transplant recipients had their telomere length measured using quantitative real-time PCR assays on peripheral blood collected at the time of surveillance bronchoscopy. We assessed the association between early post-transplant telomere length (as measured in the first 100 days) and CLAD-free survival, time to clinically significant leukopenia, cytomegalovirus (CMV) viraemia, chronic kidney disease, and acute cellular rejection. We also assessed the association between rate of telomere shortening and CLAD-free survival.

Telomere lengths were available for 98 out of 215 (45.6%) recipients who underwent lung transplant during the study period (median measurement per patient=2 (interquartile range, 1–3)). Shorter telomere length was associated with decreased CLAD-free survival (hazard ratio (HR)=1.24; 95% CI=1.03–1.48; p=0.02), leukopenia requiring granulocyte colony-stimulating factor (HR=1.17, 95% CI=1.01–1.35, p=0.03), and CMV viraemia among CMV-mismatch recipients (HR=4.04, 95% CI=1.05–15.5, p=0.04). Telomere length was not associated with acute cellular rejection or chronic kidney disease. Recipients with more rapid loss in telomere length (defined as the highest tertile of telomere shortening) did not have worse subsequent CLAD-free survival than those without rapid loss (HR=1.38, 95% CI=0.27–7.01, p=0.70).

Shorter early post-transplant telomere length is associated with decreased CLAD-free survival and clinically significant leukopenia in lung transplant recipients, regardless of native lung disease.

Shorter recipient telomere length following lung transplantation is associated with clinically significant leukopenia and decreased chronic lung allograft dysfunction-free survivalhttps://bit.ly/2ytymXc

An update on chronic lung allograft dysfunction

Chronic lung allograft dysfunction (CLAD) remains a significant challenge and the major determinant of morbidity and mortality post lung transplantation (LTx). The definition of CLAD has evolved significantly over the last ten years, reflecting better understanding of pathophysiology and different phenotypes. While there is an agreed consensus approach to CLAD, questions remain regarding the limitations of lung function parameters as well as the role of imaging and histopathology. Here we present a current snapshot of the definition of CLAD, its evolution and future directions.