Frequency and Nature of Genomic Alterations in ERBB2-Altered Urothelial Bladder Cancer.

BACKGROUND: Human epidermal growth factor-2 (HER2) overexpression is an oncogenic driver in many solid tumors, including urothelial bladder cancer (UBC). In addition, activating mutations in the ERBB2 gene have been shown to play an oncogenic role similar to ERBB2 amplification. OBJECTIVE: To describe and compare the frequency and nature of genomic alterations (GA) of ERBB2-altered (mutations, amplification) and ERBB2 wild-type UBC. PATIENTS AND METHODS: Using a hybrid capture-based comprehensive profiling assay, 9518 UBC cases were grouped by ERBB2 alteration and evaluated for all classes of genomic alterations (GA), tumor mutational burden (TMB), microsatellite instability (MSI), genome-wide loss of heterozygosity (gLOH), and genomic mutational signature. PD-L1 expression was measured by immunohistochemistry (Dako 22C3). Categorical statistical comparisons were performed using Fisher's exact tests. RESULTS: A total of 602 (6.3%) UBC cases featured ERBB2 extracellular domain short variant (SV) GA (ECDmut+), 253 (2.7%) cases featured ERBB2 kinase domain SV GA (KDmut+), 866 (9.1%) cases had ERBB2 amplification (amp+), and 7797 (81.9%) cases were ERBB2 wild-type (wt). European genetic ancestry of ECDmut+ was higher than ERBB2wt. Numerous significant associations were observed when comparing GA by group. Notably among these, CDKN2A/MTAP loss were more frequent in ERBB2wt versus ECDmut+ and amp+. ERBB3 GA were more frequent in ECDmut+ and KDmut+ than ERBB2wt. TERT GA were more frequent in ECDmut+, KDmut+, and amp+ versus ERBB2wt. TOP2A amplification was significantly more common in ECDmut+ and amp+ versus ERBB2wt, and TP53 SV GA were significantly higher in ERBB2 amp+ versus ERBB2wt. Mean TMB levels were significantly higher in ECDmut+, KDmut+, and amp+ than in ERBB2wt. Apolipoprotein B mRNA-editing enzyme, catalytic polypeptides (APOBEC) signature was more frequent in ECDmut+, KDmut+, and amp+ versus ERBB2wt. No significant differences were observed in PD-L1 status between groups, while gLOH-high status was more common in amp+ versus ERBB2wt. MSI-high status was more frequent in KDmut+ versus ERBB2wt, and in ERBB2wt than in amp+. CONCLUSIONS: We noted important differences in co-occurring GA in ERBB2-altered (ECDmut+, KDmut+, amp+) versus ERBB2wt UBC, as well as higher mean TMB and higher APOBEC mutational signature in the ERBB2-altered groups. Our results can help refine future clinical trial designs and elucidate possible response and resistance mechanisms for ERBB2-altered UBC.

The effect of dietary interventions or patterns on the cardiometabolic health of individuals treated with androgen deprivation therapy for prostate cancer: A systematic review.

Prostate cancer survivors treated with androgen deprivation therapy may be at increased risk of cardiovascular disease. Dietary recommendations for the prevention and/or management of cardiovascular disease for these individuals are lacking. This review synthesizes the evidence on the effect of dietary interventions on cardiometabolic biomarkers and cardiovascular disease risk in prostate cancer survivors receiving androgen deprivation therapy. A systematic review was conducted across PubMed, CINAHL, Embase, and Cochrane CENTRAL. Intervention or observational cohort studies evaluating diets, nutrients, or nutraceuticals with or without concurrent exercise interventions on cardiovascular disease, cardiovascular events, or cardiovascular disease biomarkers in those treated with androgen deprivation therapy were included. Confidence in the body of evidence was appraised using Grading of Recommendations, Assessment, Development and Evaluations. Twelve studies reported across fifteen papers were included. Interventions were heterogenous, with most studies including an exercise co-intervention (n = 8). Few significant findings for the effects of diet on cardiometabolic markers were likely due to weak methodology and sample sizes. Strongest evidence was for the effect of a healthy Western dietary pattern with exercise on improved blood pressure (Confidence: moderate). The healthy Western dietary pattern with exercise may improve high-density lipoprotein cholesterol (Confidence: Low) and flow-mediated dilation. Soy may improve total cholesterol (Confidence: Very low). A low-carbohydrate diet with physical activity may improve high-density lipoprotein cholesterol, incidence of metabolic syndrome, and Framingham cardiovascular disease risk score. Evidence of the effect of dietary interventions on cardiometabolic biomarkers and cardiovascular disease risk of prostate cancer survivors receiving androgen deprivation therapy is insufficient to inform practice. Well-designed dietary interventions aimed at improving cardiometabolic outcomes of this population are warranted to inform future dietary recommendations.

Expectation maximisation pseudo labels.

In this paper, we study pseudo-labelling. Pseudo-labelling employs raw inferences on unlabelled data as pseudo-labels for self-training. We elucidate the empirical successes of pseudo-labelling by establishing a link between this technique and the Expectation Maximisation algorithm. Through this, we realise that the original pseudo-labelling serves as an empirical estimation of its more comprehensive underlying formulation. Following this insight, we present a full generalisation of pseudo-labels under Bayes' theorem, termed Bayesian Pseudo Labels. Subsequently, we introduce a variational approach to generate these Bayesian Pseudo Labels, involving the learning of a threshold to automatically select high-quality pseudo labels. In the remainder of the paper, we showcase the applications of pseudo-labelling and its generalised form, Bayesian Pseudo-Labelling, in the semi-supervised segmentation of medical images. Specifically, we focus on: (1) 3D binary segmentation of lung vessels from CT volumes; (2) 2D multi-class segmentation of brain tumours from MRI volumes; (3) 3D binary segmentation of whole brain tumours from MRI volumes; and (4) 3D binary segmentation of prostate from MRI volumes. We further demonstrate that pseudo-labels can enhance the robustness of the learned representations. The code is released in the following GitHub repository: https://github.com/moucheng2017/EMSSL.

Adaptive multi-interventional trial platform to improve patient care for fibrotic interstitial lung diseases.

BACKGROUND: Fibrotic interstitial lung diseases (fILDs) are a heterogeneous group of lung diseases associated with significant morbidity and mortality. Despite a large increase in the number of clinical trials in the last 10 years, current regulatory-approved management approaches are limited to two therapies that prevent the progression of fibrosis. The drug development pipeline is long and there is an urgent need to accelerate this process. This manuscript introduces the concept and design of an innovative research approach to drug development in fILD: a global Randomised Embedded Multifactorial Adaptive Platform in fILD (REMAP-ILD). METHODS: Description of the REMAP-ILD concept and design: the specific terminology, design characteristics (multifactorial, adaptive features, statistical approach), target population, interventions, outcomes, mission and values, and organisational structure. RESULTS: The target population will be adult patients with fILD, and the primary outcome will be a disease progression model incorporating forced vital capacity and mortality over 12 months. Responsive adaptive randomisation, prespecified thresholds for success and futility will be used to assess the effectiveness and safety of interventions. REMAP-ILD embraces the core values of diversity, equity, and inclusion for patients and researchers, and prioritises an open-science approach to data sharing and dissemination of results. CONCLUSION: By using an innovative and efficient adaptive multi-interventional trial platform design, we aim to accelerate and improve care for patients with fILD. Through worldwide collaboration, novel analytical methodology and pragmatic trial delivery, REMAP-ILD aims to overcome major limitations associated with conventional randomised controlled trial approaches to rapidly improve the care of people living with fILD.

Multi-task localization of the hemidiaphragms and lung segmentation in portable chest X-ray images of COVID-19 patients.

Background: The COVID-19 can cause long-term symptoms in the patients after they overcome the disease. Given that this disease mainly damages the respiratory system, these symptoms are often related with breathing problems that can be caused by an affected diaphragm. The diaphragmatic function can be assessed with imaging modalities like computerized tomography or chest X-ray. However, this process must be performed by expert clinicians with manual visual inspection. Moreover, during the pandemic, the clinicians were asked to prioritize the use of portable devices, preventing the risk of cross-contamination. Nevertheless, the captures of these devices are of a lower quality. Objectives: The automatic quantification of the diaphragmatic function can determine the damage of COVID-19 on each patient and assess their evolution during the recovery period, a task that could also be complemented with the lung segmentation. Methods: We propose a novel multi-task fully automatic methodology to simultaneously localize the position of the hemidiaphragms and to segment the lung boundaries with a convolutional architecture using portable chest X-ray images of COVID-19 patients. For that aim, the hemidiaphragms' landmarks are located adapting the paradigm of heatmap regression. Results: The methodology is exhaustively validated with four analyses, achieving an 82.31% ± 2.78% of accuracy when localizing the hemidiaphragms' landmarks and a Dice score of 0.9688 ± 0.0012 in lung segmentation. Conclusions: The results demonstrate that the model is able to perform both tasks simultaneously, being a helpful tool for clinicians despite the lower quality of the portable chest X-ray images.

Imaging of pulmonary fibrosis in children: A review, with proposed diagnostic criteria.

Computed tomography (CT) imaging findings of pulmonary fibrosis are well established for adults and have been shown to correlate with prognosis and outcome. Recognition of fibrotic CT findings in children is more limited. With approved treatments for adult pulmonary fibrosis, it has become critical to define CT criteria for fibrosis in children, to identify patients in need of treatment and those eligible for clinical trials. Understanding how pediatric fibrosis compares with idiopathic pulmonary fibrosis and other causes of fibrosis in adults is increasingly important as these patients transition to adult care teams. Here, we review what is known regarding the features of pulmonary fibrosis in children compared with adults. Pulmonary fibrosis in children may be associated with genetic surfactant dysfunction disorders, autoimmune systemic disorders, and complications after radiation, chemotherapy, transplantation, and other exposures. Rather than a basal-predominant usual interstitial pneumonia pattern with honeycombing, pediatric fibrosis is primarily characterized by reticulation, traction bronchiectasis, architectural distortion, or cystic lucencies/abnormalities. Ground-glass opacities are more frequent in children with fibrotic interstitial lung disease than adults, and disease distribution appears more diffuse, without clearly defined axial or craniocaudal predominance. Following discussion and consensus amongst a panel of expert radiologists, pathologists and physicians, distinctive disease features were integrated to develop criteria for the first global Phase III trial in children with pulmonary fibrosis.

Characterizing the Genomic Landscape of the Micropapillary Subtype of Urothelial Carcinoma of the Bladder Harboring Activating Extracellular Mutations of ERBB2.

The micropapillary subtype of urothelial carcinoma (MPUC) of the bladder is a very aggressive histological variant of urothelial bladder cancer (UBC). A high frequency of MPUC contains activating mutations in the extracellular domain (ECD) of ERBB2. We sought to further characterize ERBB2 ECD-mutated MPUC to identify additional genomic alterations that have been associated with tumor progression and therapeutic response. In total, 5,485 cases of archived formalin-fixed, paraffin-embedded UBC underwent comprehensive genomic profiling to identify ERBB2 ECD-mutated MPUC and evaluate the frequencies of genomic co-alterations. We identified 219 cases of UBC with ERBB2 ECD mutations (74% S310F and 26% S310Y), of which 63 (28.8%) were MPUC. Genomic analysis revealed that TERT, TP53, and ARID1A were the most common co-altered genes in ERBB2-mutant MPUC (82.5%, 58.7%, and 39.7%, respectively) and did not differ from ERBB2-mutant non-MPUC (86.5%, 51.9%, and 35.3%). The main differences between ERBB2 ECD-mutated MPUC compared with non-MPUC were KMT2D, RB1, and MTAP alterations. KMT2D and RB1 are tumor-suppressor genes. KMT2D frequency was significantly decreased in ERBB2 ECD-mutated MPUC (6.3%) in contrast to non-MPUC (27.6%; P < .001). RB1 mutations were more frequent in ERBB2 ECD-mutated MPUC (33.3%) than in non-MPUC (17.3%; P = .012). Finally, MTAP loss, an emerging biomarker for new synthetic lethality-based anticancer drugs, was less frequent in ERBB2 ECD-mutated MPUC (11.1%) than in non-MPUC (26.9%; P = .018). Characterizing the genomic landscape of MPUC may not only improve our fundamental knowledge about this aggressive morphological variant of UBC but also has the potential to identify possible prognostic and predictive biomarkers that may drive tumor progression and dictate treatment response to therapeutic approaches.

A formula for predicting emphysema extent in combined idiopathic pulmonary fibrosis and emphysema.

BACKGROUND: No single pulmonary function test captures the functional effect of emphysema in idiopathic pulmonary fibrosis (IPF). Without experienced radiologists, other methods are needed to determine emphysema extent. Here, we report the development and validation of a formula to predict emphysema extent in patients with IPF and emphysema. METHODS: The development cohort included 76 patients with combined IPF and emphysema at the Royal Brompton Hospital, London, United Kingdom. The formula was derived using stepwise regression to generate the weighted combination of pulmonary function data that fitted best with emphysema extent on high-resolution computed tomography. Test cohorts included patients from two clinical trials (n = 455 [n = 174 with emphysema]; NCT00047645, NCT00075998) and a real-world cohort from the Royal Brompton Hospital (n = 191 [n = 110 with emphysema]). The formula is only applicable for patients with IPF and concomitant emphysema and accordingly was not used to detect the presence or absence of emphysema. RESULTS: The formula was: predicted emphysema extent = 12.67 + (0.92 x percent predicted forced vital capacity) - (0.65 x percent predicted forced expiratory volume in 1 second) - (0.52 x percent predicted carbon monoxide diffusing capacity). A significant relationship between the formula and observed emphysema extent was found in both cohorts (R2 = 0.25, P < 0.0001; R2 = 0.47, P < 0.0001, respectively). In both, the formula better predicted observed emphysema extent versus individual pulmonary function tests. A 15% emphysema extent threshold, calculated using the formula, identified a significant difference in absolute changes from baseline in forced vital capacity at Week 48 in patients with baseline-predicted emphysema extent < 15% versus ≥ 15% (P = 0.0105). CONCLUSION: The formula, designed for use in patients with IPF and emphysema, demonstrated enhanced ability to predict emphysema extent versus individual pulmonary function tests. TRIAL REGISTRATION: NCT00047645; NCT00075998.

First analysis of the safety and efficacy of UGN-101 in the treatment of ureteral tumors.

OBJECTIVE: UGN-101 has been approved for the chemoablation of low-grade upper tract urothelial cancer (UTUC) involving the renal pelvis and calyces. Herein is the first reported cohort of patients with ureteral tumors treated with UGN-101. PATIENTS AND METHODS: We performed a retrospective review of patients treated with UGN-101 for UTUC at 15 high-volume academic and community centers focusing on outcomes of patients treated for ureteral disease. Patients received UGN-101 with either adjuvant or chemo-ablative intent. Response rates are reported for patients receiving chemo-ablative intent. Adverse outcomes were characterized with a focus on the rate of ureteral stenosis. RESULTS: In a cohort of 132 patients and 136 renal units, 47 cases had tumor involvement of the ureter, with 12 cases of ureteral tumor only (8.8%) and 35 cases of ureteral plus renal pelvic tumors (25.7%). Of the 23 patients with ureteral involvement who received UGN-101 induction with chemo-ablative intent, the complete response was 47.8%, which did not differ significantly from outcomes in patients without ureteral involvement. Fourteen patients (37.8%) with ureteral tumors had significant ureteral stenosis at first post-treatment evaluation, however, when excluding those with pre-existing hydronephrosis or ureteral stenosis, only 5.4% of patients developed new clinically significant stenosis. CONCLUSIONS: UGN-101 appears to be safe and may have similar efficacy in treating low-grade urothelial carcinoma of the ureter as compared to renal pelvic tumors.

Serum C-reactive protein is associated with earlier mortality across different interstitial lung diseases.

BACKGROUND AND OBJECTIVE: The acute-phase protein C-reactive protein (CRP) is known to be associated with poor outcomes in cancer and cardiovascular disease, but there is limited evidence of its prognostic implications in interstitial lung diseases (ILDs). We therefore set out to test whether baseline serum CRP levels are associated with mortality in four different ILDs. METHODS: In this retrospective study, clinically measured CRP levels, as well as baseline demographics and lung function measures, were collected for ILD patients first presenting to the Royal Brompton Hospital between January 2010 and December 2019. Cox regression analysis was used to determine the relationship with 5-year mortality. RESULTS: Patients included in the study were: idiopathic pulmonary fibrosis (IPF) n = 422, fibrotic hypersensitivity pneumonitis (fHP) n = 233, rheumatoid arthritis associated ILD (RA-ILD) n = 111 and Systemic Sclerosis associated ILD (SSc-ILD) n = 86. Patients with a recent history of infection were excluded. Higher CRP levels were associated with shorter 5-year survival in all four disease groups on both univariable analyses, and after adjusting for age, gender, smoking history, immunosuppressive therapy and baseline disease severity (IPF: HR (95% CI): 1.3 (1.1-1.5), p = 0.003, fHP: 1.5 (1.2-1.9), p = 0.001, RA-ILD: 1.4 (1.1-1.84), p = 0.01 and SSc-ILD: 2.7 (1.6-4.5), p < 0.001). CONCLUSION: Higher CRP levels are independently associated with reduced 5-year survival in IPF, fHP, RA-ILD and SSc-ILD.

CenTime: Event-conditional modelling of censoring in survival analysis.

Survival analysis is a valuable tool for estimating the time until specific events, such as death or cancer recurrence, based on baseline observations. This is particularly useful in healthcare to prognostically predict clinically important events based on patient data. However, existing approaches often have limitations; some focus only on ranking patients by survivability, neglecting to estimate the actual event time, while others treat the problem as a classification task, ignoring the inherent time-ordered structure of the events. Additionally, the effective utilisation of censored samples-data points where the event time is unknown- is essential for enhancing the model's predictive accuracy. In this paper, we introduce CenTime, a novel approach to survival analysis that directly estimates the time to event. Our method features an innovative event-conditional censoring mechanism that performs robustly even when uncensored data is scarce. We demonstrate that our approach forms a consistent estimator for the event model parameters, even in the absence of uncensored data. Furthermore, CenTime is easily integrated with deep learning models with no restrictions on batch size or the number of uncensored samples. We compare our approach to standard survival analysis methods, including the Cox proportional-hazard model and DeepHit. Our results indicate that CenTime offers state-of-the-art performance in predicting time-to-death while maintaining comparable ranking performance. Our implementation is publicly available at https://github.com/ahmedhshahin/CenTime.

Small Airways Disease in Pre-COPD with Emphysema: A Cross-Sectional Study.

RATIONALE: Small airway disease is an important pathophysiological feature of COPD. Recently, pre-COPD has been put forward as potential precursor stage of COPD, defined by abnormal spirometry or significant emphysema on CT in the absence of airflow obstruction. METHODS: We collected whole lungs/lung lobes from patients with emphysematous pre-COPD (n=10), COPD GOLD I (n=6), GOLD II (n=6), GOLD III/IV (n=7) and controls (n=10) which were analyzed using CT and microCT. The degree of emphysema and the number and morphology of small airways was compared between the different groups and further correlations were investigated with physiologic measures. Airway and parenchymal pathology was also validated with histopathology. MEASUREMENTS AND MAIN RESULTS: The number of transitional bronchioles (TrB)/mL and terminal bronchioles (TB)/mL was significantly lower in pre-COPD, GOLD I, GOLD II and GOLD III/IV compared to controls. In addition, the number of alveolar attachments of the TrB and TB was also lower in pre-COPD and all COPD groups compared to controls. We did not find any differences between the pre-COPD and COPD group in either CT or microCT measures. The % of emphysema on CT showed the strongest correlation with the number of small airways, also in patients without airflow obstruction. Histopathology showed an increase in the mean chord length and a decrease in the alveolar surface density in pre-COPD and all GOLD stages compared to control. CONCLUSION: Lungs of patients with emphysematous pre-COPD already show lower small airway number and airway remodeling and in the absence of physiologic airway obstruction.

Genomic Profiles and Clinical Outcomes of Penile Squamous Cell Carcinoma With Elevated Tumor Mutational Burden.

Importance: Tumor mutational burden (TMB) is a putative biomarker of efficacy for immune checkpoint inhibitor (ICI) therapies of solid tumors, but not specifically for penile squamous cell carcinoma (PSCC). Objective: To characterize biomarker features and ICI therapy outcomes associated with high TMB in PSCC in the routine clinical practice setting. Design, Setting, and Participants: In this cohort study, 397 PSCC cases were analyzed to identify genomic alterations in more than 300 cancer-associated genes and genomic signatures, including TMB, using a hybrid capture-based comprehensive genomic profiling assay. Tumor mutational burden was categorized as low (<10 mutations per megabase [mut/Mb]), high (10-19 mut/Mb), or very high (≥20 mut/Mb). Germline status of genetic alterations was predicted using a validated somatic-germline computational method. Clinical outcomes of patients with metastatic PSCC receiving first-line ICI were abstracted using the deidentified nationwide Clinico-Genomic Database (CGDB) from January 1, 2011, through December 31, 2022. Exposure: Comprehensive genomic profiling was performed using FoundationOne and FoundationOne CDx assays from Foundation Medicine Inc. Main outcomes and measures: The spectrum of genetic alterations by TMB level in PSCC, the percentage of germline genetic alterations, and the outcome (overall survival with routine clinical treatment) by TMB of chemotherapy-naive patients with PSCC who received ICI treatment up front were assessed in this descriptive study. Results: Among 397 patients (median [IQR] age, 65 [54-73] years; 266 [67.0%] of European, 83 [20.9%] of admixed American, and 34 [8.5%] of African or other genomic ancestry), the median (IQR) age (eg, 65 [53-73] years for low TMB vs 68 [61-78] years for TMB ≥10 mut/Mb) and genomic ancestry distribution (eg, European 228 of 339 [67.3%] for low TMB vs 38 of 58 [65.5%] for TMB ≥10 mut/Mb) were similar between TMB subgroups. There were 339 PSCC cases (85.4%) with low TMB, 40 cases (10.1%) with high TMB, and 18 cases (4.5%) with very high TMB. Comparisons of TMB of 10 mut/Mb or higher vs low TMB showed an enrichment of genetic alterations in PIK3CA (48.3% vs 18.3%; P < .001) and KMT2D (29.3% vs 7.7%; P < .001) and less frequent genetic alterations in CDKN2A (25.9% vs 45.7%; P = .05). Most genetic alterations did not co-occur. Human papillomavirus identification was more frequent as TMB increased: 28.3% for low TMB, 50.0% for high, and 72.2% for very high. In total, 95 of 1377 genetic alterations (6.9%) were germline. Of 10 patients identified from the CGDB receiving frontline ICIs, median (IQR) follow-up was 9.9 months. Four patients had overall survival with clinical treatment of more than 12 months, including 2 of 3 patients with TMB of 10 mut/Mb or higher. Conclusions and Relevance: In this cohort study of advanced metastatic PSCC based on TMB levels, significant differences were observed for biomarkers in nearly 15% of patients with a TMB of 10 mut/Mb or higher. Germline testing and ICI-based therapy should be integrated into the management of selected PSCC cases.

Mortality surrogates in combined pulmonary fibrosis and emphysema.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) with co-existent emphysema, termed combined pulmonary fibrosis and emphysema (CPFE) may associate with reduced forced vital capacity (FVC) declines compared to non-CPFE IPF patients. We examined associations between mortality and functional measures of disease progression in two IPF cohorts. METHODS: Visual emphysema presence (>0% emphysema) scored on computed tomography identified CPFE patients (CPFE:non-CPFE: derivation cohort=317:183; replication cohort=358:152), who were subgrouped using 10%, or 15% visual emphysema thresholds, and an unsupervised machine learning model considering emphysema and ILD extents. Baseline characteristics, 1-year relative FVC and diffusing capacity of the lung for carbon monoxide (DLco) decline (linear mixed-effects models), and their associations with mortality (multivariable Cox regression models) were compared across non-CPFE and CPFE subgroups. RESULTS: In both IPF cohorts, CPFE patients with ≥10% emphysema had a greater smoking history and lower baseline DLco compared to CPFE patients with <10% emphysema. Using multivariable Cox regression analyses in patients with ≥10% emphysema, 1-year DLco decline showed stronger mortality associations than 1-year FVC decline. Results were maintained in patients suitable for therapeutic IPF trials and in subjects subgrouped by ≥15% emphysema and using unsupervised machine learning. Importantly, the unsupervised machine learning approach identified CPFE patients in whom FVC decline did not associate strongly with mortality. In non-CPFE IPF patients, 1-year FVC declines ≥5% and ≥10% showed strong mortality associations. CONCLUSION: When assessing disease progression in IPF, DLco decline should be considered in patients with ≥10% emphysema and a ≥5% 1-year relative FVC decline threshold considered in non-CPFE IPF patients.

Evaluating a Remote Monitoring Program for Respiratory Diseases: Prospective Observational Study.

BACKGROUND: Patients with chronic respiratory diseases and those in the postdischarge period following hospitalization because of COVID-19 are particularly vulnerable, and little is known about the changes in their symptoms and physiological parameters. Continuous remote monitoring of physiological parameters and symptom changes offers the potential for timely intervention, improved patient outcomes, and reduced health care costs. OBJECTIVE: This study investigated whether a real-time multimodal program using commercially available wearable technology, home-based Bluetooth-enabled spirometers, finger pulse oximeters, and smartphone apps is feasible and acceptable for patients with chronic respiratory diseases, as well as the value of low-burden, long-term passive data collection. METHODS: In a 3-arm prospective observational cohort feasibility study, we recruited 60 patients from the Royal Free Hospital and University College Hospital. These patients had been diagnosed with interstitial lung disease, chronic obstructive pulmonary disease, or post-COVID-19 condition (n=20 per group) and were followed for 180 days. This study used a comprehensive remote monitoring system designed to provide real-time and relevant data for both patients and clinicians. Data were collected using REDCap (Research Electronic Data Capture; Vanderbilt University) periodic surveys, Remote Assessment of Disease and Relapses-base active app questionnaires, wearables, finger pulse oximeters, smartphone apps, and Bluetooth home-based spirometry. The feasibility of remote monitoring was measured through adherence to the protocol, engagement during the follow-up period, retention rate, acceptability, and data integrity. RESULTS: Lowest-burden passive data collection methods, via wearables, demonstrated superior adherence, engagement, and retention compared with active data collection methods, with an average wearable use of 18.66 (SD 4.69) hours daily (77.8% of the day), 123.91 (SD 33.73) hours weekly (72.6% of the week), and 463.82 (SD 156.70) hours monthly (64.4% of the month). Highest-burden spirometry tasks and high-burden active app tasks had the lowest adherence, engagement, and retention, followed by low-burden questionnaires. Spirometry and active questionnaires had the lowest retention at 0.5 survival probability, indicating that they were the most burdensome. Adherence to and quality of home spirometry were analyzed; of the 7200 sessions requested, 4248 (59%) were performed. Of these, 90.3% (3836/4248) were of acceptable quality according to American Thoracic Society grading. Inclusion of protocol holidays improved retention measures. The technologies used were generally well received. CONCLUSIONS: Our findings provide evidence supporting the feasibility and acceptability of remote monitoring for capturing both subjective and objective data from various sources for respiratory diseases. The high engagement level observed with passively collected data suggests the potential of wearables for long-term, user-friendly remote monitoring in respiratory disease management. The unique piloting of certain features such as protocol holidays, alert notifications for missing data, and flexible support from the study team provides a reference for future studies in this field. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/28873.

Learning from multiple annotators for medical image segmentation.

Supervised machine learning methods have been widely developed for segmentation tasks in recent years. However, the quality of labels has high impact on the predictive performance of these algorithms. This issue is particularly acute in the medical image domain, where both the cost of annotation and the inter-observer variability are high. Different human experts contribute estimates of the "actual" segmentation labels in a typical label acquisition process, influenced by their personal biases and competency levels. The performance of automatic segmentation algorithms is limited when these noisy labels are used as the expert consensus label. In this work, we use two coupled CNNs to jointly learn, from purely noisy observations alone, the reliability of individual annotators and the expert consensus label distributions. The separation of the two is achieved by maximally describing the annotator's "unreliable behavior" (we call it "maximally unreliable") while achieving high fidelity with the noisy training data. We first create a toy segmentation dataset using MNIST and investigate the properties of the proposed algorithm. We then use three public medical imaging segmentation datasets to demonstrate our method's efficacy, including both simulated (where necessary) and real-world annotations: 1) ISBI2015 (multiple-sclerosis lesions); 2) BraTS (brain tumors); 3) LIDC-IDRI (lung abnormalities). Finally, we create a real-world multiple sclerosis lesion dataset (QSMSC at UCL: Queen Square Multiple Sclerosis Center at UCL, UK) with manual segmentations from 4 different annotators (3 radiologists with different level skills and 1 expert to generate the expert consensus label). In all datasets, our method consistently outperforms competing methods and relevant baselines, especially when the number of annotations is small and the amount of disagreement is large. The studies also reveal that the system is capable of capturing the complicated spatial characteristics of annotators' mistakes.

A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study.

In this study, we present a hybrid CNN-RNN approach to investigate long-term survival of subjects in a lung cancer screening study. Subjects who died of cardiovascular and respiratory causes were identified whereby the CNN model was used to capture imaging features in the CT scans and the RNN model was used to investigate time series and thus global information. To account for heterogeneity in patients' follow-up times, two different variants of LSTM models were evaluated, each incorporating different strategies to address irregularities in follow-up time. The models were trained on subjects who underwent cardiovascular and respiratory deaths and a control cohort matched to participant age, gender, and smoking history. The combined model can achieve an AUC of 0.76 which outperforms humans at cardiovascular mortality prediction. The corresponding F1 and Matthews Correlation Coefficient are 0.63 and 0.42 respectively. The generalisability of the model is further validated on an 'external' cohort. The same models were applied to survival analysis with the Cox Proportional Hazard model. It was demonstrated that incorporating the follow-up history can lead to improvement in survival prediction. The Cox neural network can achieve an IPCW C-index of 0.75 on the internal dataset and 0.69 on an external dataset. Delineating subjects at increased risk of cardiorespiratory mortality can alert clinicians to request further more detailed functional or imaging studies to improve the assessment of cardiorespiratory disease burden. Such strategies may uncover unsuspected and under-recognised pathologies thereby potentially reducing patient morbidity.