Pneumothorax detection in chest radiographs: optimizing artificial intelligence system for accuracy and confounding bias reduction using in-image annotations in algorithm training

OBJECTIVES Diagnostic accuracy of artificial intelligence (AI) pneumothorax (PTX) detection in chest radiographs (CXR) is limited by the noisy annotation quality of public training data and confounding thoracic tubes (TT). We hypothesize that in-image annotations of the dehiscent visceral pleura for algorithm training boosts algorithm's performance and suppresses confounders. METHODS Our single-center evaluation cohort of 3062 supine CXRs includes 760 PTX-positive cases with radiological annotations of PTX size and inserted TTs. Three step-by-step improved algorithms (differing in algorithm architecture, training data from public datasets/clinical sites, and in-image annotations included in algorithm training) were characterized by area under the receiver operating characteristics (AUROC) in detailed subgroup analyses and referenced to the well-established \textquotedblCheXNet\textquotedbl algorithm. RESULTS Performances of established algorithms exclusively trained on publicly available data without in-image annotations are limited to AUROCs of 0.778 and strongly biased towards TTs that can completely eliminate algorithm's discriminative power in individual subgroups. Contrarily, our final \textquotedblalgorithm 2\textquotedbl which was trained on a lower number of images but additionally with in-image annotations of the dehiscent pleura achieved an overall AUROC of 0.877 for unilateral PTX detection with a significantly reduced TT-related confounding bias. CONCLUSIONS We demonstrated strong limitations of an established PTX-detecting AI algorithm that can be significantly reduced by designing an AI system capable of learning to both classify and localize PTX. Our results are aimed at drawing attention to the necessity of high-quality in-image localization in training data to reduce the risks of unintentionally biasing the training process of pathology-detecting AI algorithms. KEY POINTS • Established pneumothorax-detecting artificial intelligence algorithms trained on public training data are strongly limited and biased by confounding thoracic tubes. • We used high-quality in-image annotated training data to effectively boost algorithm performance and suppress the impact of confounding thoracic tubes. • Based on our results, we hypothesize that even hidden confounders might be effectively addressed by in-image annotations of pathology-related image features

Clinically focused multi-cohort benchmarking as a tool for external validation of artificial intelligence algorithm performance in basic chest radiography analysis

Artificial intelligence (AI) algorithms evaluating [supine] chest radiographs ([S]CXRs) have remarkably increased in number recently. Since training and validation are often performed on subsets of the same overall dataset, external validation is mandatory to reproduce results and reveal potential training errors. We applied a multicohort benchmarking to the publicly accessible (S)CXR analyzing AI algorithm CheXNet, comprising three clinically relevant study cohorts which differ in patient positioning ([S]CXRs), the applied reference standards (CT-/[S]CXR-based) and the possibility to also compare algorithm classification with different medical experts’ reading performance. The study cohorts include [1] a cohort, characterized by 563 CXRs acquired in the emergency unit that were evaluated by 9 readers (radiologists and non-radiologists) in terms of 4 common pathologies, [2] a collection of 6,248 SCXRs annotated by radiologists in terms of pneumothorax presence, its size and presence of inserted thoracic tube material which allowed for subgroup and confounding bias analysis and [3] a cohort consisting of 166 patients with SCXRs that were evaluated by radiologists for underlying causes of basal lung opacities, all of those cases having been correlated to a timely acquired computed tomography scan (SCXR and CT within < 90 min). CheXNet non-significantly exceeded the radiology resident (RR) consensus in the detection of suspicious lung nodules (cohort [1], AUC AI/RR: 0.851/0.839, p = 0.793) and the radiological readers in the detection of basal pneumonia (cohort [3], AUC AI/reader consensus: 0.825/0.782, p = 0.390) and basal pleural effusion (cohort [3], AUC AI/reader consensus: 0.762/0.710, p = 0.336) in SCXR, partly with AUC values higher than originally published (“Nodule”: 0.780, “Infiltration”: 0.735, “Effusion”: 0.864). The classifier “Infiltration” turned out to be very dependent on patient positioning (best in CXR, worst in SCXR). The pneumothorax SCXR cohort [2] revealed poor algorithm performance in CXRs without inserted thoracic material and in the detection of small pneumothoraces, which can be explained by a known systematic confounding error in the algorithm training process. The benefit of clinically relevant external validation is demonstrated by the differences in algorithm performance as compared to the original publication. Our multi-cohort benchmarking finally enables the consideration of confounders, different reference standards and patient positioning as well as the AI performance comparison with differentially qualified medical readers

Associations between sex, body mass index and the individual microglial response in Alzheimer's disease

Background and objectives18-kDa translocator protein position-emission-tomography (TSPO-PET) imaging emerged for in vivo assessment of neuroinflammation in Alzheimer's disease (AD) research. Sex and obesity effects on TSPO-PET binding have been reported for cognitively normal humans (CN), but such effects have not yet been systematically evaluated in patients with AD. Thus, we aimed to investigate the impact of sex and obesity on the relationship between beta-amyloid-accumulation and microglial activation in AD.Methods49 patients with AD (29 females, all A beta-positive) and 15 A beta-negative CN (8 female) underwent TSPO-PET ([18F]GE-180) and beta-amyloid-PET ([18F]flutemetamol) imaging. In 24 patients with AD (14 females), tau-PET ([18F]PI-2620) was additionally available. The brain was parcellated into 218 cortical regions and standardized-uptake-value-ratios (SUVr, cerebellar reference) were calculated. Per region and tracer, the regional increase of PET SUVr (z-score) was calculated for AD against CN. The regression derived linear effect of regional A beta-PET on TSPO-PET was used to determine the A beta-plaque-dependent microglial response (slope) and the A beta-plaque-independent microglial response (intercept) at the individual patient level. All read-outs were compared between sexes and tested for a moderation effect of sex on associations with body mass index (BMI).ResultsIn AD, females showed higher mean cortical TSPO-PET z-scores (0.91 +/- 0.49;males 0.30 +/- 0.75;p = 0.002), while A beta-PET z-scores were similar. The A beta-plaque-independent microglial response was stronger in females with AD (+ 0.37 +/- 0.38;males with AD - 0.33 +/- 0.87;p = 0.006), pronounced at the prodromal stage. On the contrary, the A beta-plaque-dependent microglial response was not different between sexes. The A beta-plaque-independent microglial response was significantly associated with tau-PET in females (Braak-II regions: r = 0.757, p = 0.003), but not in males. BMI and the A beta-plaque-independent microglial response were significantly associated in females (r = 0.44, p = 0.018) but not in males (BMI*sex interaction: F(3,52) = 3.077, p = 0.005).ConclusionWhile microglia response to fibrillar A beta is similar between sexes, women with AD show a stronger A beta-plaque-independent microglia response. This sex difference in A beta-independent microglial activation may be associated with tau accumulation. BMI is positively associated with the A beta-plaque-independent microglia response in females with AD but not in males, indicating that sex and obesity need to be considered when studying neuroinflammation in AD

Microglial activation and connectivity in Alzheimer disease and aging

OBJECTIVE Alzheimer disease (AD) is characterized by amyloid β (Aβ) plaques and neurofibrillary tau tangles, but increasing evidence suggests that neuroinflammation also plays a key role, driven by the activation of microglia. Aβ and tau pathology appear to spread along pathways of highly connected brain regions, but it remains elusive whether microglial activation follows a similar distribution pattern. Here, we assess whether connectivity is associated with microglia activation patterns. METHODS We included 32 Aβ-positive early AD subjects (18 women, 14 men) and 18 Aβ-negative age-matched healthy controls (10 women, 8 men) from the prospective ActiGliA (Activity of Cerebral Networks, Amyloid and Microglia in Aging and Alzheimer's Disease) study. All participants underwent microglial activation positron emission tomography (PET) with the third-generation mitochondrial 18 kDa translocator protein (TSPO) ligand [18 F]GE-180 and magnetic resonance imaging (MRI) to measure resting-state functional and structural connectivity. RESULTS We found that inter-regional covariance in TSPO-PET and standardized uptake value ratio was preferentially distributed along functionally highly connected brain regions, with MRI structural connectivity showing a weaker association with microglial activation. AD patients showed increased TSPO-PET tracer uptake bilaterally in the anterior medial temporal lobe compared to controls, and higher TSPO-PET uptake was associated with cognitive impairment and dementia severity in a disease stage-dependent manner. INTERPRETATION Microglial activation distributes preferentially along highly connected brain regions, similar to tau pathology. These findings support the important role of microglia in neurodegeneration, and we speculate that pathology spreads throughout the brain along vulnerable connectivity pathways. ANN NEUROL 2022

Individual regional associations between Aβ-, tau- and neurodegeneration (ATN) with microglial activation in patients with primary and secondary tauopathies

& beta;-amyloid (A & beta;) and tau aggregation as well as neuronal injury and atrophy (ATN) are the major hallmarks of Alzheimer's disease (AD), and biomarkers for these hallmarks have been linked to neuroinflammation. However, the detailed regional associations of these biomarkers with microglial activation in individual patients remain to be elucidated. We investigated a cohort of 55 patients with AD and primary tauopathies and 10 healthy controls that underwent TSPO-, A & beta;-, tau-, and perfusion-surrogate-PET, as well as structural MRI. Z-score deviations for 246 brain regions were calculated and biomarker contributions of A & beta;(A), tau (T), perfusion (N1), and gray matter atrophy (N2) to microglial activation (TSPO, I) were calculated for each individual subject. Individual ATN-related microglial activation was correlated with clinical performance and CSF soluble TREM2 (sTREM2) concentrations. In typical and atypical AD, regional tau was stronger and more frequently associated with microglial activation when compared to regional A & beta;(AD: & beta;(T) = 0.412 & PLUSMN;0.196 vs. & beta;(A) = 0.142 & PLUSMN;0.123, p < 0.001;AD-CBS: & beta;(T) = 0.385 & PLUSMN;0.176 vs. & beta;(A) = 0.131 & PLUSMN;0.186, p = 0.031). The strong association between regional tau and microglia reproduced well in primary tauopathies (& beta;(T) = 0.418 & PLUSMN;0.154). Stronger individual associations between tau and microglial activation were associated with poorer clinical performance. In patients with 4RT, sTREM2 levels showed a positive association with tau-related microglial activation. Tau pathology has strong regional associations with microglial activation in primary and secondary tauopathies. Tau and A & beta;related microglial response indices may serve as a two-dimensional in vivo assessment of neuroinflammation in neurodegenerative diseases

Individual regional associations between Aβ-, tau- and neurodegeneration (ATN) with microglial activation in patients with primary and secondary tauopathies.

β-amyloid (Aβ) and tau aggregation as well as neuronal injury and atrophy (ATN) are the major hallmarks of Alzheimer's disease (AD), and biomarkers for these hallmarks have been linked to neuroinflammation. However, the detailed regional associations of these biomarkers with microglial activation in individual patients remain to be elucidated. We investigated a cohort of 55 patients with AD and primary tauopathies and 10 healthy controls that underwent TSPO-, Aβ-, tau-, and perfusion-surrogate-PET, as well as structural MRI. Z-score deviations for 246 brain regions were calculated and biomarker contributions of Aβ (A), tau (T), perfusion (N1), and gray matter atrophy (N2) to microglial activation (TSPO, I) were calculated for each individual subject. Individual ATN-related microglial activation was correlated with clinical performance and CSF soluble TREM2 (sTREM2) concentrations. In typical and atypical AD, regional tau was stronger and more frequently associated with microglial activation when compared to regional Aβ (AD: βT = 0.412 ± 0.196 vs. βA = 0.142 ± 0.123, p < 0.001; AD-CBS: βT = 0.385 ± 0.176 vs. βA = 0.131 ± 0.186, p = 0.031). The strong association between regional tau and microglia reproduced well in primary tauopathies (βT = 0.418 ± 0.154). Stronger individual associations between tau and microglial activation were associated with poorer clinical performance. In patients with 4RT, sTREM2 levels showed a positive association with tau-related microglial activation. Tau pathology has strong regional associations with microglial activation in primary and secondary tauopathies. Tau and Aβ related microglial response indices may serve as a two-dimensional in vivo assessment of neuroinflammation in neurodegenerative diseases

Übergänge am Arbeitsmarkt und Qualität von Beschäftigung

Kapitel C befasst sich mit "Übergängen am Arbeitsmarkt und Qualität von Beschäftigung". Parallel zur günstigeren Arbeitsmarktentwicklung hat sich die Polarisierung des deutschen Arbeitsmarktes verschärft: Die Spreizung des Lohngefüges hat sich deutlich verstärkt, "atypische" Beschäftigungsverhältnisse wie Leiharbeit, befristete Beschäftigung, Teilzeit- und Mini-Jobs haben stark an Bedeutung gewonnen. Die Autorinnen und Autoren dieses Kapitels analysieren die Entwicklung atypischer Beschäftigungsverhältnisse in den vergangenen Jahren und gehen der Frage nach, inwieweit diese Erwerbsformen eine Brücke in stabile und existenzsichernde Beschäftigung bilden

Microglial Activation and Connectivity in Alzheimer Disease and Aging

Objective Alzheimer disease (AD) is characterized by amyloid beta (A beta) plaques and neurofibrillary tau tangles, but increasing evidence suggests that neuroinflammation also plays a key role, driven by the activation of microglia. A beta and tau pathology appear to spread along pathways of highly connected brain regions, but it remains elusive whether microglial activation follows a similar distribution pattern. Here, we assess whether connectivity is associated with microglia activation patterns. Methods We included 32 A beta-positive early AD subjects (18 women, 14 men) and 18 A beta-negative age-matched healthy controls (10 women, 8 men) from the prospective ActiGliA (Activity of Cerebral Networks, Amyloid and Microglia in Aging and Alzheimer's Disease) study. All participants underwent microglial activation positron emission tomography (PET) with the third-generation mitochondrial 18 kDa translocator protein (TSPO) ligand [F-18]GE-180 and magnetic resonance imaging (MRI) to measure resting-state functional and structural connectivity. Results We found that inter-regional covariance in TSPO-PET and standardized uptake value ratio was preferentially distributed along functionally highly connected brain regions, with MRI structural connectivity showing a weaker association with microglial activation. AD patients showed increased TSPO-PET tracer uptake bilaterally in the anterior medial temporal lobe compared to controls, and higher TSPO-PET uptake was associated with cognitive impairment and dementia severity in a disease stage-dependent manner. Interpretation Microglial activation distributes preferentially along highly connected brain regions, similar to tau pathology. These findings support the important role of microglia in neurodegeneration, and we speculate that pathology spreads throughout the brain along vulnerable connectivity pathways. ANN NEUROL 202