CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

Large, labeled datasets have driven deep learning methods to achieve expert-level performance on a variety of medical imaging tasks. We present CheXpert, a large dataset that contains 224,316 chest radiographs of 65,240 patients. We design a labeler to automatically detect the presence of 14 observations in radiology reports, capturing uncertainties inherent in radiograph interpretation. We investigate different approaches to using the uncertainty labels for training convolutional neural networks that output the probability of these observations given the available frontal and lateral radiographs. On a validation set of 200 chest radiographic studies which were manually annotated by 3 board-certified radiologists, we find that different uncertainty approaches are useful for different pathologies. We then evaluate our best model on a test set composed of 500 chest radiographic studies annotated by a consensus of 5 board-certified radiologists, and compare the performance of our model to that of 3 additional radiologists in the detection of 5 selected pathologies. On Cardiomegaly, Edema, and Pleural Effusion, the model ROC and PR curves lie above all 3 radiologist operating points. We release the dataset to the public as a standard benchmark to evaluate performance of chest radiograph interpretation models. The dataset is freely available at https://stanfordmlgroup.github.io/competitions/chexpert .Comment: Published in AAAI 201

Sex Differences in Cognitive Decline in Subjects with High Likelihood of Mild Cognitive Impairment due to Alzheimer’s disease

Sex differences in Alzheimer’s disease (AD) biology and progression are not yet fully characterized. The goal of this study is to examine the effect of sex on cognitive progression in subjects with high likelihood of mild cognitive impairment (MCI) due to Alzheimer’s and followed up to 10 years in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cerebrospinal fluid total-tau and amyloid-beta (Aβ42) ratio values were used to sub-classify 559 MCI subjects (216 females, 343 males) as having “high” or “low” likelihood for MCI due to Alzheimer’s. Data were analyzed using mixed-effects models incorporating all follow-ups. The worsening from baseline in Alzheimer’s Disease Assessment Scale-Cognitive score (mean, SD) (9 ± 12) in subjects with high likelihood of MCI due to Alzheimer’s was markedly greater than that in subjects with low likelihood (1 ± 6, p < 0.0001). Among MCI due to AD subjects, the mean worsening in cognitive score was significantly greater in females (11.58 ± 14) than in males (6.87 ± 11, p = 0.006). Our findings highlight the need to further investigate these findings in other populations and develop sex specific timelines for Alzheimer’s disease progression

Diffusion Tensor Magnetic Resonance Imaging of the Optic Nerves in Pediatric Hydrocephalus

OBJECTIVE While conventional imaging can readily identify ventricular enlargement in hydrocephalus, structural changes that underlie microscopic tissue injury might be more difficult to capture. MRI-based diffusion tensor imaging (DTI) uses properties of water motion to uncover changes in the tissue microenvironment. The authors hypothesized that DTI can identify alterations in optic nerve microstructure in children with hydrocephalus. METHODS The authors retrospectively reviewed 21 children (\u3c 18 years old) who underwent DTI before and after neurosurgical intervention for acute obstructive hydrocephalus from posterior fossa tumors. Their optic nerve quantitative DTI metrics of mean diffusivity (MD) and fractional anisotropy (FA) were compared to those of 21 age-matched healthy controls. RESULTS Patients with hydrocephalus had increased MD and decreased FA in bilateral optic nerves, compared to controls (p \u3c 0.001). Normalization of bilateral optic nerve MD and FA on short-term follow-up (median 1 day) after neurosurgical intervention was observed, as was near-complete recovery of MD on long-term follow-up (median 1.8 years). CONCLUSIONS DTI was used to demonstrate reversible alterations of optic nerve microstructure in children presenting acutely with obstructive hydrocephalus. Alterations in optic nerve MD and FA returned to near-normal levels on short- and long-term follow-up, suggesting that surgical intervention can restore optic nerve tissue microstructure. This technique is a safe, noninvasive imaging tool that quantifies alterations of neural tissue, with a potential role for evaluation of pediatric hydrocephalus

Diffusion Tensor Magnetic Resonance Imaging of the Optic Nerves in Pediatric Hydrocephalus

OBJECTIVE While conventional imaging can readily identify ventricular enlargement in hydrocephalus, structural changes that underlie microscopic tissue injury might be more difficult to capture. MRI-based diffusion tensor imaging (DTI) uses properties of water motion to uncover changes in the tissue microenvironment. The authors hypothesized that DTI can identify alterations in optic nerve microstructure in children with hydrocephalus. METHODS The authors retrospectively reviewed 21 children (\u3c 18 years old) who underwent DTI before and after neurosurgical intervention for acute obstructive hydrocephalus from posterior fossa tumors. Their optic nerve quantitative DTI metrics of mean diffusivity (MD) and fractional anisotropy (FA) were compared to those of 21 age-matched healthy controls. RESULTS Patients with hydrocephalus had increased MD and decreased FA in bilateral optic nerves, compared to controls (p \u3c 0.001). Normalization of bilateral optic nerve MD and FA on short-term follow-up (median 1 day) after neurosurgical intervention was observed, as was near-complete recovery of MD on long-term follow-up (median 1.8 years). CONCLUSIONS DTI was used to demonstrate reversible alterations of optic nerve microstructure in children presenting acutely with obstructive hydrocephalus. Alterations in optic nerve MD and FA returned to near-normal levels on short- and long-term follow-up, suggesting that surgical intervention can restore optic nerve tissue microstructure. This technique is a safe, noninvasive imaging tool that quantifies alterations of neural tissue, with a potential role for evaluation of pediatric hydrocephalus

Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach

Alzheimer’s disease (AD) is a major public health threat; however, despite decades of research, the disease mechanisms are not completely understood, and there is a significant dearth of predictive biomarkers. The availability of systems biology approaches has opened new avenues for understanding disease mechanisms at a pathway level. However, to the best of our knowledge, no prior study has characterized the nature of pathway crosstalks in AD, or examined their utility as biomarkers for diagnosis or prognosis. In this paper, we build the first computational crosstalk model of AD incorporating genetics, antecedent knowledge, and biomarkers from a national study to create a generic pathway crosstalk reference map and to characterize the nature of genetic and protein pathway crosstalks in mild cognitive impairment (MCI) subjects. We perform initial studies of the utility of incorporating these crosstalks as biomarkers for assessing the risk of MCI progression to AD dementia. Our analysis identified Single Nucleotide Polymorphism-enriched pathways representing six of the seven Kyoto Encyclopedia of Genes and Genomes pathway categories. Integrating pathway crosstalks as a predictor improved the accuracy by 11.7% compared to standard clinical parameters and apolipoprotein E ε4 status alone. Our findings highlight the importance of moving beyond discrete biomarkers to studying interactions among complex biological pathways