Use of Dynamic Chest Radiography to Assess Treatment of Pulmonary Exacerbations in Cystic Fibrosis.

Background Although spirometry is an important marker in the management of pulmonary exacerbations in cystic fibrosis (CF), it is a forced maneuver and can generate aerosol. Therefore, it may be difficult to perform in some individuals. Dynamic chest radiography (DCR) provides real-time information regarding pulmonary dynamics alongside fluoroscopic-style thoracic imaging. Purpose To assess the effect of pulmonary exacerbation treatment by using both spirometry and DCR and assess the clinical utility of DCR in participants with CF experiencing pulmonary exacerbations. Materials and Methods In this prospective, observational, single-center pilot study, spirometry and DCR were performed before and after treatment of pulmonary exacerbations in participants with CF between December 2019 and August 2020. Spirometry measured forced expiratory volume in 1 second (FEV1) and forced vital capacity. DCR helped to measure projected lung area (PLA), hemidiaphragm midpoint position, and speed during tidal and deep breathing. Data were analyzed by using the paired t test or Wilcoxon signed-rank test. Correlation was assessed by using the Spearman rank correlation coefficient. Results Twenty participants with CF (mean age, 25 years ± 7 [standard deviation]; 14 women) were evaluated. Spirometry showed that percentage predicted FEV1 improved from a median of 44% (interquartile range [IQR], 17%) before treatment to 55% (IQR, 16%) after treatment (P = .004). DCR showed improvement in median deep breathing excursion for left and right hemidiaphragms (from 18 [IQR, 11] to 25 [IQR, 16] mm [P = .03] and from 13 [IQR, 6] to 19 [IQR, 14] mm [P = .03], respectively) and in median expiratory speed following deep breathing for left and right hemidiaphragms (from 7 [IQR, 2] to 11 [IQR, 5] mm/sec [P = .004] and 6 [IQR, 3] to 9 [IQR, 6] mm/sec [P = .004], respectively). PLA rate of change during full expiration and change in PLA during tidal breathing improved (from a mean of 42 cm2/sec ± 16 to 56 cm2/sec ± 24 [P = .03] and from a mean of 29 cm2 ± 14 to 35 cm2 ± 10 [P = .03], respectively). Conclusion Dynamic chest radiography demonstrated improvement in diaphragm speed and range of chest wall movement during respiration aftere treatment for pulmonary exacerbations in cystic fibrosis and showed potential as a tool to investigate the effect of pulmonary exacerbations on lung mechanics. Clinical trials registration no. NCT01234567 Published under a CC BY 4.0 license. Online supplemental material is available for this article.

Dynamic chest radiography: a state-of-the-art review.

Dynamic chest radiography (DCR) is a real-time sequential high-resolution digital X-ray imaging system of the thorax in motion over the respiratory cycle, utilising pulsed image exposure and a larger field of view than fluoroscopy coupled with a low radiation dose, where post-acquisition image processing by computer algorithm automatically characterises the motion of thoracic structures. We conducted a systematic review of the literature and found 29 relevant publications describing its use in humans including the assessment of diaphragm and chest wall motion, measurement of pulmonary ventilation and perfusion, and the assessment of airway narrowing. Work is ongoing in several other areas including assessment of diaphragmatic paralysis. We assess the findings, methodology and limitations of DCR, and we discuss the current and future roles of this promising medical imaging technology.Critical relevance statement Dynamic chest radiography provides a wealth of clinical information, but further research is required to identify its clinical niche.

Feasibility of dynamic chest radiography to calculate lung volumes in adult people with cystic fibrosis: a pilot study.

INTRODUCTION: Dynamic chest radiography (DCR) is a novel, low-dose, real-time digital imaging system where software identifies moving thoracic structures and can automatically calculate lung areas. In an observational, prospective, non-controlled, single-centre pilot study, we compared it with whole-body plethysmography (WBP) in the measurement of lung volume subdivisions in people with cystic fibrosis (pwCF). METHODS: Lung volume subdivisions were estimated by DCR using projected lung area (PLA) during deep inspiration, tidal breathing and full expiration, and compared with same-day WBP in 20 adult pwCF attending routine review. Linear regression models to predict lung volumes from PLA were developed. RESULTS: Total lung area (PLA at maximum inspiration) correlated with total lung capacity (TLC) (r=0.78, p<0.001), functional residual lung area with functional residual capacity (FRC) (r=0.91, p<0.001), residual lung area with residual volume (RV) (r=0.82, p=0.001) and inspiratory lung area with inspiratory capacity (r=0.72, p=0.001). Despite the small sample size, accurate models were developed for predicting TLC, RV and FRC. CONCLUSION: DCR is a promising new technology that can be used to estimate lung volume subdivisions. Plausible correlations between plethysmographic lung volumes and DCR lung areas were identified. Further studies are needed to build on this exploratory work in both pwCF and individuals without CF. TRIAL REGISTRATION NUMBER: ISRCTN64994816.

Bilateral adaptive graph convolutional network on CT based Covid-19 diagnosis with uncertainty-aware consensus-assisted multiple instance learning.

Coronavirus disease (COVID-19) has caused a worldwide pandemic, putting millions of people's health and lives in jeopardy. Detecting infected patients early on chest computed tomography (CT) is critical in combating COVID-19. Harnessing uncertainty-aware consensus-assisted multiple instance learning (UC-MIL), we propose to diagnose COVID-19 using a new bilateral adaptive graph-based (BA-GCN) model that can use both 2D and 3D discriminative information in 3D CT volumes with arbitrary number of slices. Given the importance of lung segmentation for this task, we have created the largest manual annotation dataset so far with 7,768 slices from COVID-19 patients, and have used it to train a 2D segmentation model to segment the lungs from individual slices and mask the lungs as the regions of interest for the subsequent analyses. We then used the UC-MIL model to estimate the uncertainty of each prediction and the consensus between multiple predictions on each CT slice to automatically select a fixed number of CT slices with reliable predictions for the subsequent model reasoning. Finally, we adaptively constructed a BA-GCN with vertices from different granularity levels (2D and 3D) to aggregate multi-level features for the final diagnosis with the benefits of the graph convolution network's superiority to tackle cross-granularity relationships. Experimental results on three largest COVID-19 CT datasets demonstrated that our model can produce reliable and accurate COVID-19 predictions using CT volumes with any number of slices, which outperforms existing approaches in terms of learning and generalisation ability. To promote reproducible research, we have made the datasets, including the manual annotations and cleaned CT dataset, as well as the implementation code, available at https://doi.org/10.5281/zenodo.6361963.

Development and external validation of a mixed-effects deep learning model to diagnose COVID-19 from CT imaging.

Background: The automatic analysis of medical images has the potential improve diagnostic accuracy while reducing the strain on clinicians. Current methods analyzing 3D-like imaging data, such as computerized tomography imaging, often treat each image slice as individual slices. This may not be able to appropriately model the relationship between slices. Methods: Our proposed method utilizes a mixed-effects model within the deep learning framework to model the relationship between slices. We externally validated this method on a data set taken from a different country and compared our results against other proposed methods. We evaluated the discrimination, calibration, and clinical usefulness of our model using a range of measures. Finally, we carried out a sensitivity analysis to demonstrate our methods robustness to noise and missing data. Results: In the external geographic validation set our model showed excellent performance with an AUROC of 0.930 (95%CI: 0.914, 0.947), with a sensitivity and specificity, PPV, and NPV of 0.778 (0.720, 0.828), 0.882 (0.853, 0.908), 0.744 (0.686, 0.797), and 0.900 (0.872, 0.924) at the 0.5 probability cut-off point. Our model also maintained good calibration in the external validation dataset, while other methods showed poor calibration. Conclusion: Deep learning can reduce stress on healthcare systems by automatically screening CT imaging for COVID-19. Our method showed improved generalizability in external validation compared to previous published methods. However, deep learning models must be robustly assessed using various performance measures and externally validated in each setting. In addition, best practice guidelines for developing and reporting predictive models are vital for the safe adoption of such models.

Efficacy and safety of isatuximab plus bortezomib, lenalidomide, and dexamethasone in patients with newly diagnosed multiple myeloma ineligible/with no immediate intent for autologous stem cell transplantation.

Patients with newly diagnosed multiple myeloma (NDMM) ineligible for autologous stem cell transplantation (ASCT) have lower survival rates and may benefit from frontline regimens that include novel agents. This Phase 1b study (NCT02513186) evaluated preliminary efficacy, safety, and pharmacokinetics (PK) of isatuximab, an anti-CD38 monoclonal antibody, combined with bortezomib-lenalidomide-dexamethasone (Isa-VRd) in patients with NDMM ineligible for/with no intent for immediate ASCT. Overall, 73 patients received four 6-week induction cycles of Isa-VRd, then maintenance with Isa-Rd in 4-week cycles. In the efficacy population (n = 71), the overall response rate was 98.6%, with 56.3% achieving a complete response or better (sCR/CR), and 36/71 (50.7%) patients reaching minimal residual disease negativity (10-5 sensitivity). Grade ≥3 treatment-emergent adverse events (TEAEs) occurred in 79.5% (58/73) of patients but TEAEs leading to permanent study treatment discontinuation were reported in 14 (19.2%) patients. Isatuximab PK parameters were within the previously reported range, suggesting that VRd does not alter the PK of isatuximab. These data support additional studies of isatuximab in NDMM, such as the Phase 3 IMROZ study (Isa-VRd vs VRd).

Eruptive melanocytic naevi following initiation of elexacaftor/ivacaftor/tezacaftor for cystic fibrosis.

A 29 year old woman with cystic fibrosis (CF) presented to CF clinic following the sudden development of over 200 pigmented naevi located predominately on the trunk and limbs 3 months after commencing elexacaftor/tezacaftor/ivacaftor, a novel triple-therapy CFTR modulator therapy for CF. Skin biopsy confirmed benign naevi and the clinical presentation was consistent with eruptive melanocytic naevi. Elexacaftor/tezacaftor/ivacaftor received marketing authorisation in August 2020 and this is the first report of associated naevi. The individual described here remains clinically well, and continues on elexacaftor/tezacaftor/ivacaftor with dermatology follow-up.

Characterisation of hemidiaphragm dysfunction using dynamic chest radiography: a pilot study.

OBJECTIVES: Dynamic chest radiography (DCR) is a novel real-time digital fluoroscopic imaging system that produces clear, wide field-of-view diagnostic images of the thorax and diaphragm in motion, alongside novel metrics on moving structures within the thoracic cavity. We describe the use of DCR in the measurement of diaphragm motion in a pilot series of cases of suspected diaphragm dysfunction. METHODS: We studied 21 patients referred for assessment of diaphragm function due to suspicious clinical symptoms or imaging (breathlessness, orthopnoea, reduced exercise tolerance and/or an elevated hemidiaphragm on plain chest radiograph). All underwent DCR with voluntary sniff manoeuvres. RESULTS: Paradoxical motion on sniffing was observed in 14 patients, and confirmed in six who also underwent fluoroscopy or ultrasound. In four patients, DCR showed reduced hemidiaphragm excursion, but no paradoxical motion; in three, normal bilateral diaphragm motion was demonstrated. DCR was quick to perform, and well tolerated in all cases and with no adverse events reported. DCR was achieved in ∼5 min per patient, with images available to view by the clinician immediately within the clinical setting. CONCLUSION: DCR is a rapid, well-tolerated and straightforward chest radiography technique that warrants further investigation in the assessment of diaphragm dysfunction.

Cardiac sarcoidosis in an adult person with cystic fibrosis: a case report.

Cardiac sarcoidosis and cystic fibrosis (CF) are both rare conditions and their co-existence has not previously been noted in adults. For the first time we report a case of isolated cardiac sarcoidosis in a woman with CF, and discuss the possible combined aetiological factors. As the life expectancy of people with CF continues to increase, clinicians should be aware of the emergence of concomitant inflammatory conditions typically diagnosed in adulthood, and the diagnostic challenges this may present.

Measuring the effect of elexacaftor/tezacaftor/ivacaftor combination therapy on the respiratory pump in people with CF using dynamic chest radiography.

BACKGROUND: The CFTR modulator elexacaftor/tezacaftor/ivacaftor (ELX/TEZ/IVA) leads to significant improvement in the symptoms and spirometry of people with cystic fibrosis (pwCF), but little evidence exists to understand its effect on respiratory pump function. Dynamic chest radiography (DCR) is a novel cineradiographic tool that identifies and tracks the chest wall and diaphragm throughout the breathing cycle, alongside fluoroscopic images of the chest of diagnostic quality. METHODS: In this observational work, we examined the spirometry and DCR of 24 pwCF before and after starting ELX/TEZ/IVA. DCR automatically tracked the hemidiaphragm midpoints and projected lung area (PLA) during tidal and deep breathing manoeuvres. RESULTS: ppFEV1 (61±18 to 73±22, P<0.001) and ppFVC (77±16 to 88±15, P<0.001) improved significantly. DCR demonstrated a significant increase in hemidiaphragm excursion on both the right (18±11 to 26±9 mm, P<0.001) and left (21±11 to 31±11 mm, P<0.001) sides, as well as maximum hemidiaphragm speed during inspiration (right 22±14 to 31±11 mm/s, P=0.03; left 28±11 to 37±16 mm/s, P=0.02). PLA at end-expiration was significantly reduced (334±71 to 290±72cm2, P<0.001), with a significant increase in ΔPLA (83±40 to 117±36cm2, P<0.001). CONCLUSIONS: DCR demonstrated significant improvements in hemidiaphragm excursion and ΔPLA in pwCF started on ELX/TEZ/IVA. These changes likely reflect a reduction in air trapping and improved elastic recoil of the chest, and are consistent with improvements seen in spirometry. The changes seen with DCR are physiologically plausible and correlate well with spirometry. DCR warrants further investigation as a tool for assessing the impact of CFTR-modulating therapies.

Elexacaftor/Tezacaftor/Ivacaftor as a Bridge to Lung Retransplant in a Recipient With Cystic Fibrosis.

The triple-combination cystic fibrosis transmembrane conductance regulator modulator elexacaftor/- tezacaftor/ivacaftor is known to improve lung function and have extrapulmonary benefits in people with cystic fibrosis. However, there is limited evidence for its use in patients with cystic fibrosis after lung transplant, where the donor lung expresses normal levels of the cystic fibrosis transmembrane conductance regulator. We describe the use of elexacaftor/tezacaftor/ivacaftor as a bridge to potential lung retransplant in a 37-year-old man with cystic fibrosis and chronic lung allograft dysfunction. Although forced expiratory volume in 1 second did not improve, the patient had decreased sputum volume, no pulmonary exacerbations of cystic fibrosis, and no longer required continuous antibiotic therapy. Pancreatic function, revised Cystic Fibrosis Questionnaire scores, sinus symptoms, weight, and corticosteroid dependence significantly improved. There were no reported side effects attributable to elexacaftor/tezacaftor/ivacaftor. However, the patient exhibited declined renal function, which had been initially attributed to lability in cyclosporin levels but which were corrected after lithotripsy for renal calculi. Triple-combination modulators of the cystic fibrosis transmembrane conductance regulator may offer benefits to carefully selected individuals awaiting retransplant, balanced against the risk of worsened immunosuppressant level control.

Unilateral diaphragm paralysis with COVID-19 infection.

Neurological complications are well described in SARS-CoV-2, but for the first time we report a case of unilateral diaphragm paralysis occurring early in mechanical ventilation for respiratory failure due to such an infection. The patient subsequently required tracheostomy and ventilator support for 37 days, and had increased breathlessness and an elevated diaphragm at clinic review 9 months later. Dynamic chest radiography demonstrated persistent diaphragm paralysis with an accompanying postural change in lung volumes, and he subsequently underwent surgical plication. This case demonstrates that although persistent dyspnoea is a common feature following SARS-CoV-2 infection and is usually due to deconditioning or persistent parenchymal involvement, it can be due to other causes and needs to be investigated appropriately.

Mycobacterium Simiae Infection in a Person With Cystic Fibrosis.

Although non-tuberculous mycobacteria can be found in the airways of people with cystic fibrosis (pwCF), their role as pathogens may be uncertain, and treatment is problematic. We report the first case of Mycobacterium simiae (M. simiae), often associated with asymptomatic disease or colonisation, which caused pulmonary infection requiring treatment in a pwCF. This report shows that M. simiae, rare in pwCF in the United Kingdom, can cause significant illness and highlights the diagnostic difficulty in individuals with positive smear mycobacteria that can be mistaken initially for pulmonary tuberculosis (TB).

Utility and validity of dynamic chest radiography in cystic fibrosis (dynamic CF): an observational, non-controlled, non-randomised, single-centre, prospective study.

INTRODUCTION: Dynamic chest radiography (DCR) uses novel, low-dose radiographic technology to capture images of the thoracic cavity while in motion. Pulmonary function testing is important in cystic fibrosis (CF). The tolerability, rapid acquisition and lower radiation and cost compared with CT imaging may make DCR a useful adjunct to current standards of care. METHODS AND ANALYSIS: This is an observational, non-controlled, non-randomised, single-centre, prospective study. This study is conducted at the Liverpool Heart and Chest Hospital (LHCH) adult CF unit. Participants are adults with CF. This study reviews DCR taken during routine CF Annual Review (n=150), validates DCR-derived lung volumes against whole body plethysmography (n=20) and examines DCR at the start and end of pulmonary exacerbations of CF (n=20). The primary objectives of this study are to examine if DCR provides lung function information that correlates with PFT, and lung volumes that correlate whole body plethysmography. ETHICS AND DISSEMINATION: This study has received the following approvals: HRA REC (11 December 2019) and LHCH R&I (11 October 2019). Results are made available to people with CF, the funders and other researchers. Processed, anonymised data are available from the research team on request. TRIAL REGISTRATION NUMBER: ISRCTN 64994816.

The financial requirements and time commitments of caregivers for autologous stem cell transplant recipients.

This study is a prospective evaluation of the time commitment and financial requirements of caregivers of autologous stem cell recipients during the period of inpatient hospitalization. Eligible patients identified one caregiver, and a one-page survey addressing the necessary time commitment and out-of-pocket expenses was completed by the caregiver at each visit. The caregivers of 40 patients participated (non-Hodgkin's lymphoma [n = 19], multiple myeloma [n = 18], Hodgkin's lymphoma [n = 2], or acute myelogenous leukemia [n = 1]). Caregivers included spouses (n = 35), partners/friends (n = 2), or family members (n = 3). Results were summarized for the patient's total length of stay. Each caregiver traveled a median of 829 miles over 17.8 hours. Out-of-pocket expenses varied greatly depending on whether a caregiver stayed in local accommodations (cohort 1; n = 11) or in the patient's hospital room (cohort 2; n = 29). Total expenses (median) for each caregiver in cohort 1 were dollar 849.35, including accommodations (dollar 560), gasoline (dollar 87.35), and food (dollar 202). Total expenses (median) for each caregiver in cohort 2 were dollar 181.15, including gasoline (dollar 70) and food (dollar 111.15). Each caregiver in cohort 1 lost a median of 43.5 hours of work compared with 8 hours for each caregiver in cohort 2. The results from this prospective study demonstrate that there is a significant financial and time requirement on the part of the caregiver when a family member or significant other is hospitalized for an autologous stem cell transplant.

Surgical systems biology and personalized longitudinal phenotyping in critical care.

Systems-wide molecular analysis of the metabolic, inflammatory and immune response to surgical trauma has yet to be translated into the operating room. Surgical patients are exposed to a large number of heterogeneous environmental insults that cannot only be quantified by genome-orientated 'omics platforms. Furthermore, surgery demands rapid or near real-time analysis. Systems-level metabolic phenotyping provides a novel 'global' perspective of an organism's metabolic response to surgical injury and, therefore, serves as an ideal platform for the development of personalized therapies in surgery. This article reviews current personalized approaches to healthcare in surgery and explores future directions for personalized surgical biomarker discovery and therapeutics. In particular, this article discusses our vision of 'personalized metabolic phenotyping' in surgery, and outlines next-generation technologies that will make this approach a reality.