Education & Certifications
Bachelor of Science, University of California, Los Angeles (2016)
- Correction to: Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures. European journal of nuclear medicine and molecular imaging 2021
Deep COVID DeteCT: an international experience on COVID-19 lung detection and prognosis using chest CT.
NPJ digital medicine
2021; 4 (1): 11
The Coronavirus disease 2019 (COVID-19) presents open questions in how we clinically diagnose and assess disease course. Recently, chest computed tomography (CT) has shown utility for COVID-19 diagnosis. In this study, we developed Deep COVID DeteCT (DCD), a deep learning convolutional neural network (CNN) that uses the entire chest CT volume to automatically predict COVID-19 (COVID+) from non-COVID-19 (COVID-) pneumonia and normal controls. We discuss training strategies and differences in performance across 13 international institutions and 8 countries. The inclusion of non-China sites in training significantly improved classification performance with area under the curve (AUCs) and accuracies above 0.8 on most test sites. Furthermore, using available follow-up scans, we investigate methods to track patient disease course and predict prognosis.
View details for DOI 10.1038/s41746-020-00369-1
View details for PubMedID 33514852
Incidence and prevalence of tuberculosis in incarcerated populations: a systematic review and meta-analysis.
The Lancet. Public health
Prisons are recognised as high-risk environments for tuberculosis, but there has been little systematic investigation of the global and regional incidence and prevalence of tuberculosis, and its determinants, in prisons. We did a systematic review and meta-analysis to assess the incidence and prevalence of tuberculosis in incarcerated populations by geographical region.In this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Knowledge, and the LILACS electronic database from Jan 1, 1980, to Nov 15, 2020, for cross-sectional and cohort studies reporting the incidence of Mycobacterium tuberculosis infection, incidence of tuberculosis, or prevalence of tuberculosis among incarcerated individuals in all geographical regions. We extracted data from individual studies, and calculated pooled estimates of incidence and prevalence through hierarchical Bayesian meta-regression modelling. We also did subgroup analyses by region. Incidence rate ratios between prisons and the general population were calculated by dividing the incidence of tuberculosis in prisons by WHO estimates of the national population-level incidence.We identified 159 relevant studies; 11 investigated the incidence of M tuberculosis infection (n=16 318), 51 investigated the incidence of tuberculosis (n=1 858 323), and 106 investigated the prevalence of tuberculosis (n=6 727 513) in incarcerated populations. The overall pooled incidence of M tuberculosis infection among prisoners was 15·0 (95% credible interval [CrI] 3·8-41·6) per 100 person-years. The incidence of tuberculosis (per 100 000 person-years) among prisoners was highest in studies from the WHO African (2190 [95% CrI 810-4840] cases) and South-East Asia (1550 [240-5300] cases) regions and in South America (970 [460-1860] cases), and lowest in North America (30 [20-50] cases) and the WHO Eastern Mediterranean region (270 [50-880] cases). The prevalence of tuberculosis was greater than 1000 per 100 000 prisoners in all global regions except for North America and the Western Pacific, and highest in the WHO South-East Asia region (1810 [95% CrI 670-4000] cases per 100 000 prisoners). The incidence rate ratio between prisons and the general population was much higher in South America (26·9; 95% CrI 17·1-40·1) than in other regions, but was nevertheless higher than ten in the WHO African (12·6; 6·2-22·3), Eastern Mediterranean (15·6; 6·5-32·5), and South-East Asia (11·7; 4·1-27·1) regions.Globally, people in prison are at high risk of contracting M tuberculosis infection and developing tuberculosis, with consistent disparities between prisons and the general population across regions. Tuberculosis control programmes should prioritise preventive interventions among incarcerated populations.US National Institutes of Health.
View details for DOI 10.1016/S2468-2667(21)00025-6
View details for PubMedID 33765455
Multi-classifier-based identification of COVID-19 from chest computed tomography using generalizable and interpretable radiomics features.
European journal of radiology
2021; 136: 109552
To investigate the efficacy of radiomics in diagnosing patients with coronavirus disease (COVID-19) and other types of viral pneumonia with clinical symptoms and CT signs similar to those of COVID-19.Between 18 January 2020 and 20 May 2020, 110 SARS-CoV-2 positive and 108 SARS-CoV-2 negative patients were retrospectively recruited from three hospitals based on the inclusion criteria. Manual segmentation of pneumonia lesions on CT scans was performed by four radiologists. The latest version of Pyradiomics was used for feature extraction. Four classifiers (linear classifier, k-nearest neighbour, least absolute shrinkage and selection operator [LASSO], and random forest) were used to differentiate SARS-CoV-2 positive and SARS-CoV-2 negative patients. Comparison of the performance of the classifiers and radiologists was evaluated by ROC curve and Kappa score.We manually segmented 16,053 CT slices, comprising 32,625 pneumonia lesions, from the CT scans of all patients. Using Pyradiomics, 120 radiomic features were extracted from each image. The key radiomic features screened by different classifiers varied and lead to significant differences in classification accuracy. The LASSO achieved the best performance (sensitivity: 72.2%, specificity: 75.1%, and AUC: 0.81) on the external validation dataset and attained excellent agreement (Kappa score: 0.89) with radiologists (average sensitivity: 75.6%, specificity: 78.2%, and AUC: 0.81). All classifiers indicated that "Original_Firstorder_RootMeanSquared" and "Original_Firstorder_Uniformity" were significant features for this task.We identified radiomic features that were significantly associated with the classification of COVID-19 pneumonia using multiple classifiers. The quantifiable interpretation of the differences in features between the two groups extends our understanding of CT imaging characteristics of COVID-19 pneumonia.
View details for DOI 10.1016/j.ejrad.2021.109552
View details for PubMedID 33497881
Eponyms are here to stay: Usage in the literature and among current neurology trainees.
To assess the historical trends of medical eponym use in neurology literature and knowledge and attitudes among current trainees related to eponyms.A comprehensive list of medical eponyms compiled from multiple online and print sources was queried against the titles and abstracts of PubMed articles authored by neurologists to assess historical prevalence in the literature from 1988 to 2013. We also surveyed current neurology trainees and trainees who have matched for residency in neurology, but not yet started neurology training, on their familiarity and attitudes toward eponyms.The yearly prevalence of eponyms among neurologist-authored publications ranged from 15% and 25%, with a mean of 21%. The total number of unique eponyms appearing in titles and abstracts increased from 693 in 1988 to 1,076 in 2013, representing 1.8% average annual growth. Our survey showed that residents with at least 1 year of neurology training reported familiarity with significantly more eponyms than those before neurology training (p < 0.001). For familiar eponyms, most residents were either unaware of an alternative descriptor or preferred using the eponym. Despite recognizing both the benefits and drawbacks of eponyms, the vast majority of trainees stated that historical precedent, pervasiveness, and ease of use would drive the continued use of eponyms in neurology.Eponyms will remain a cornerstone in medical education and communication moving forward. Educators in neurology should consider how best to integrate useful eponyms and alternative descriptors into residency training to enhance knowledge acquisition and retention.
View details for DOI 10.1212/WNL.0000000000008912
View details for PubMedID 31896619
Association of Pediatric Acute-Onset Neuropsychiatric Syndrome With Microstructural Differences in Brain Regions Detected via Diffusion-Weighted Magnetic Resonance Imaging.
JAMA network open
2020; 3 (5): e204063
Epidemiological studies indicate a link between obsessive-compulsive disorder and infections, particularly streptococcal pharyngitis. Pediatric acute-onset neuropsychiatric syndrome (PANS) manifests suddenly with obsessions, compulsions, and other behavioral disturbances, often after an infectious trigger. The current working model suggests a unifying inflammatory process involving the central nervous system, particularly the basal ganglia.To investigate whether diffusion-weighted magnetic resonance imaging (DWI) detects microstructural abnormalities across the brain regions of children with PANS.Case-control study performed at a single-center, multidisciplinary clinic in the United States focusing on the evaluation and treatment of children with PANS. Sixty consecutive patients who underwent 3 Tesla (T) magnetic resonance imaging (MRI) before immunomodulation from September 3, 2012, to March 30, 2018, were retrospectively reviewed for study inclusion. Six patients were excluded by blinded investigators because of imaging or motion artifacts, 3 patients for major pathologies, and 17 patients for suboptimal atlas image registration. In total, 34 patients with PANS before initiation of treatment were compared with 64 pediatric control participants.Using atlas-based MRI analysis, regional brain volume, diffusion, and cerebral blood flow were measured in the cerebral white matter, cerebral cortex, thalamus, caudate, putamen, pallidum, hippocampus, amygdala, nucleus accumbens, and brainstem. An age and sex-controlled multivariable analysis of covariance was used to compare patients with control participants.This study compared 34 patients with PANS (median age, 154 months; age range, 55-251 months; 17 girls and 17 boys) and 64 pediatric control participants (median age, 139 months; age range, 48-213 months); 41 girls and 23 boys). Multivariable analysis demonstrated a statistically significant difference in MRI parameters between patients with PANS and control participants (F21,74 = 6.91; P < .001; partial η2 = 0.662). All assessed brain regions had statistically significantly increased median diffusivity compared with 64 control participants. Specifically, the deep gray matter (eg, the thalamus, basal ganglia, and amygdala) demonstrated the most profound increases in diffusivity consistent with the cardinal clinical symptoms of obsessions, compulsions, emotional dysregulation, and sleep disturbances. No statistically significant differences were found regarding volume and cerebral blood flow.This study identifies cerebral microstructural differences in children with PANS in multiple brain structures, including the deep gray matter structures (eg, the thalamus, basal ganglia, and amygdala). Further study of MRI is warranted in prospective, clinical trials as a potential quantitative method for assessing patients under evaluation for PANS.
View details for DOI 10.1001/jamanetworkopen.2020.4063
View details for PubMedID 32364596
Cerebral volume and diffusion MRI changes in children with sensorineural hearing loss.
2020; 27: 102328
Sensorineural hearing loss (SNHL) is the most prevalent congenital sensory deficit in children. Information regarding underlying brain microstructure could offer insight into neural development in deaf children and potentially guide therapies that optimize language development. We sought to quantitatively evaluate MRI-based cerebral volume and gray matter microstructure children with SNHL.We conducted a retrospective study of children with SNHL who obtained brain MRI at 3 T. The study cohort comprised 63 children with congenital SNHL without known focal brain lesion or structural abnormality (33 males; mean age 5.3 years; age range 1 to 11.8 years) and 64 age-matched controls without neurological, developmental, or MRI-based brain macrostructure abnormality. An atlas-based analysis was used to extract quantitative volume and median diffusivity (ADC) in the following brain regions: cerebral cortex, thalamus, caudate, putamen, globus pallidus, hippocampus, amygdala, nucleus accumbens, brain stem, and cerebral white matter. SNHL patients were further stratified by severity scores and hearing loss etiology.Children with SNHL showed higher median ADC of the cortex (p = .019), thalamus (p < .001), caudate (p = .005), and brainstem (p = .003) and smaller brainstem volumes (p = .007) compared to controls. Patients with profound bilateral SNHL did not show any significant differences compared to patients with milder bilateral SNHL, but both cohorts independently had smaller brainstem volumes compared to controls. Children with unilateral SNHL showed greater amygdala volumes compared to controls (p = .021), but no differences were found comparing unilateral SNHL to bilateral SNHL. Based on etiology for SNHL, patients with Pendrin mutations showed higher ADC values in the brainstem (p = .029, respectively); patients with Connexin 26 showed higher ADC values in both the thalamus (p < .001) and brainstem (p < .001) compared to controls.SNHL patients showed significant differences in diffusion and volume in brain subregions, with region-specific findings for patients with Connexin 26 and Pendrin mutations. Future longitudinal studies could examine macro- and microstructure changes in children with SNHL over development and potential predictive role for MRI after interventions including cochlear implant outcome.
View details for DOI 10.1016/j.nicl.2020.102328
View details for PubMedID 32622314
Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures.
European journal of nuclear medicine and molecular imaging
High-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning methods to gain insights into the image features that drive CT-based for COVID-19 pneumonia prediction, and uncover CT image features significant for COVID-19 pneumonia from deep learning and radiomics framework.A total of 266 patients with COVID-19 and other viral pneumonia with clinical symptoms and CT signs similar to that of COVID-19 during the outbreak were retrospectively collected from three hospitals in China and the USA. All the pneumonia lesions on CT images were manually delineated by four radiologists. One hundred eighty-four patients (n = 93 COVID-19 positive; n = 91 COVID-19 negative; 24,216 pneumonia lesions from 12,001 CT image slices) from two hospitals from China served as discovery cohort for model development. Thirty-two patients (17 COVID-19 positive, 15 COVID-19 negative; 7883 pneumonia lesions from 3799 CT image slices) from a US hospital served as external validation cohort. A bi-directional adversarial network-based framework and PyRadiomics package were used to extract deep learning and radiomics features, respectively. Linear and Lasso classifiers were used to develop models predictive of COVID-19 versus non-COVID-19 viral pneumonia.120-dimensional deep learning image features and 120-dimensional radiomics features were extracted. Linear and Lasso classifiers identified 32 high-dimensional deep learning image features and 4 radiomics features associated with COVID-19 pneumonia diagnosis (P < 0.0001). Both models achieved sensitivity > 73% and specificity > 75% on external validation cohort with slight superior performance for radiomics Lasso classifier. Human expert diagnostic performance improved (increase by 16.5% and 11.6% in sensitivity and specificity, respectively) when using a combined deep learning-radiomics model.We uncover specific deep learning and radiomics features to add insight into interpretability of machine learning algorithms and compare deep learning and radiomics models for COVID-19 pneumonia that might serve to augment human diagnostic performance.
View details for DOI 10.1007/s00259-020-05075-4
View details for PubMedID 33094432
Pleiotropic jaw morphology links the evolution of mechanical modularity and functional feeding convergence in Lake Malawi cichlids.
Proceedings. Biological sciences
2019; 286 (1897): 20182358
Complexity in how mechanistic variation translates into ecological novelty could be critical to organismal diversification. For instance, when multiple distinct morphologies can generate the same mechanical or functional phenotype, this could mitigate trade-offs and/or provide alternative ways to meet the same ecological challenge. To investigate how this type of complexity shapes diversity in a classic adaptive radiation, we tested several evolutionary consequences of the anterior jaw four-bar linkage for Lake Malawi cichlid trophic diversification. Using a novel phylogenetic framework, we demonstrated that different mechanical outputs of the same four jaw elements are evolutionarily associated with both jaw protrusion distance and jaw protrusion angle. However, these two functional aspects of jaw protrusion have evolved independently. Additionally, although four-bar morphology showed little evidence for attraction to optima, there was substantial evidence of adaptive peaks for emergent four-bar linkage mechanics and jaw protrusion abilities among Malawi feeding guilds. Finally, we highlighted a clear case of two cichlid species that have -independently evolved to graze algae in less than 2 Myr and have converged on similar jaw protrusion abilities as well as four-bar linkage mechanics, but have evolved these similarities via non-convergent four-bar morphologies.
View details for PubMedID 30963830
View details for PubMedCentralID PMC6408893
A phylogenomic perspective on the robust capuchin monkey (Sapajus) radiation: First evidence for extensive population admixture across South America
MOLECULAR PHYLOGENETICS AND EVOLUTION
2018; 124: 137–50
Phylogenetic relationships amongst the robust capuchin monkeys (genus Sapajus) are poorly understood. Morphology-based taxonomies have recognized anywhere from one to twelve different species. The current IUCN (2017) classification lists eight robust capuchins: S. xanthosternos, S. nigritus, S. robustus, S. flavius, S. libidinosus, S. cay, S. apella and S. macrocephalus. Here, we assembled the first phylogenomic data set for Sapajus using ultra-conserved elements (UCEs) to reconstruct a capuchin phylogeny. All phylogenomic analyses strongly supported a deep divergence of Sapajus and Cebus clades within the capuchin monkeys, and provided support for Sapajus nigritus, S. robustus and S. xanthosternos as distinct species. However, the UCE phylogeny lumped the putative species S. cay, S. libidinosus, S. apella, S. macrocephalus, and S. flavius together as a single widespread lineage. A SNP phylogeny constructed from the UCE data was better resolved and recovered S. flavius and S. libidinosus as sister species; however, S. apella, S. macrocephalus, and S. cay individuals were recovered in two geographic clades, from northeastern and southwestern Amazon, rather than clustering by currently defined morphospecies. STRUCTURE analysis of population clustering revealed widespread admixture among Sapajus populations within the Amazon and even into the Cerrado and Atlantic Forest. Difficulty in assigning species by morphology may be a result of widespread population admixture facilitated through frequent movement across major rivers and even ecosystems by robust capuchin monkeys.
View details for PubMedID 29545109
Assessing quality of care through client satisfaction at an interprofessional student-run free clinic
JOURNAL OF INTERPROFESSIONAL CARE
2018; 32 (2): 203–10
Student-run free clinics (SRFCs) have become important contributors not only to improve access to primary-care services for homeless and uninsured populations but also to enhance health sciences student education. In order for SRFCs to reliably provide high quality healthcare services and educationally benefit students, it is imperative to assess client perceptions of the quality of care provided. The objective of this study was to evaluate the delivery of healthcare services through a client satisfaction questionnaire at the University of California, Los Angeles Mobile Clinic Project (UCLA MCP). From 2012 to 2015, 194 questionnaires that addressed demographic information, satisfaction with services and client outcomes were analysed. Satisfaction scores were evaluated on a four-point scale and differences in the composite satisfaction scores were assessed using Mann-Whitney U-tests. Half (50%) of the client respondents report that UCLA MCP is their primary source of health care (MCP primary care clients), while 81.3% reported that the clinic improved access to other healthcare resources. Overall, clients are highly satisfied with their experiences (Range: 3.5-3.9) and 62% have recommended our services to others. While MCP primary-care clients report significantly higher satisfaction scores than non-primary-care clients on average (p < 0.01), the mean composite scores for all subgroups are consistently high. The UCLA MCP clients perceive the clinic to provide high-quality healthcare services. This article presents a framework that may help other SRFCs evaluate clients' perception of the quality of their care, an essential building block for effective physician-client relationships.
View details for PubMedID 29182406
Phylogenomics of a putatively convergent novelty: did hypertrophied lips evolve once or repeatedly in Lake Malawi cichlid fishes?
BMC evolutionary biology
2018; 18 (1): 179
Phylogenies provide critical information about convergence during adaptive radiation. To test whether there have been multiple origins of a distinctive trophic phenotype in one of the most rapidly radiating groups known, we used ultra-conserved elements (UCEs) to examine the evolutionary affinities of Lake Malawi cichlids lineages exhibiting greatly hypertrophied lips.The hypertrophied lip cichlids Cheilochromis euchilus, Eclectochromis ornatus, Placidochromis "Mbenji fatlip", and Placidochromis milomo are all nested within the non-mbuna clade of Malawi cichlids based on both concatenated sequence and single nucleotide polymorphism (SNP) inferred phylogenies. Lichnochromis acuticeps that exhibits slightly hypertrophied lips also appears to have evolutionary affinities to this group. However, Chilotilapia rhoadesii that lacks hypertrophied lips was recovered as nested within the species Cheilochromis euchilus. Species tree reconstructions and analyses of introgression provided largely ambiguous patterns of Malawi cichlid evolution.Contrary to mitochondrial DNA phylogenies, bifurcating trees based on our 1024 UCE loci supported close affinities of Lake Malawi lineages with hypertrophied lips. However, incomplete lineage sorting in Malawi tends to render these inferences more tenuous. Phylogenomic analyses will continue to provide powerful inferences about whether phenotypic novelties arose once or multiple times during adaptive radiation.
View details for DOI 10.1186/s12862-018-1296-9
View details for PubMedID 30486792
Phylogenomic analysis of Lake Malawi cichlid fishes: Further evidence that the three-stage model of diversification does not fit
Molecular Phylogenetics and Evolution
2017; 114: 40-48
Adaptive radiations could often occur in discrete stages. For instance, the species flock of ∼1000 species of Lake Malawi cichlid fishes might have only diverged once between rocky and sandy environments during the initial stage of their diversification. All further diversification within the rock-dwelling (mbuna) or sand-dwelling (utaka) cichlids would have occurred during a subsequent second stage of extensive trophic evolution that was followed by a third stage of sexual trait divergence. We provide an improved phylogenetic framework for Malawi cichlids to test this three-stage hypothesis based on newly reconstructed phylogenetic relationships among 32 taxonomically disparate Malawi cichlids species. Using several reconstruction methods and 1037 ultra-conserved element (UCE) markers, we recovered a molecular phylogeny that confidently resolved relationships among most of the Malawi lineages sampled when a bifurcating framework was enforced. These bifurcating reconstructions also indicated that the sand-dwelling species Cyathochromis obliquidens was well-nested within the primarily rock-dwelling radiation known as the mbuna. In contrast to predictions from the three-stage model of vertebrate diversification, the recovered phylogeny reveals an initial colonization of rocky reefs, followed by substantial diversification of rock-dwelling lineages, and then at least one instance of subsequent evolution back into sandy habitats. This repeated evolution into major habitat types provides further evidence that the three-stage model of Malawi cichlid diversification has numerous exceptions.
View details for DOI 10.1016/j.ympev.2017.05.027
Replicated divergence in cichlid radiations mirrors a major vertebrate innovation
Proceedings of the Royal Society B: Biological Sciences
2016; 283 (1822)
View details for DOI 10.1098/rspb.2015.1413