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This retrospective study developed an automated algorithm for 3D segmentation of adipose tissue and paravertebral muscle on chest CT using artificial intelligence (AI) and assessed its feasibility. The study included patients from the Boston Lung Cancer Study (2000-2011). For adipose tissue quantification, 77 patients were included, while 245 were used for muscle quantification. The data were split into training and test sets, with manual segmentation as the ground truth. Subcutaneous and visceral adipose tissues (SAT and VAT) were segmented separately. Muscle area, mean attenuation value, and intermuscular adipose tissue percentage (IMAT%) were calculated in the paravertebral muscle segmentation. The AI algorithm was trained on the training sets, and its performance was evaluated on the test sets. The AI achieved Dice scores above 0.87 and showed excellent correlations for VAT/SAT ratios, muscle attenuation value, and IMAT% (correlation coefficients > 0.98, p < 0.001). The mean differences between the AI and ground truth were minimal (VAT/SAT ratio: 0.7%; muscle attenuation value: 1 HU; IMAT%: <1%). In conclusion, we developed a feasible AI algorithm for automated 3D segmentation of adipose tissue and paravertebral muscle on chest CT., Competing Interests: Declarations. Competing interests: The curation, analysis, and control of the data were performed by Akinori Hata, Xinan Wang, Jiyeon Song and Vladimir I. Valtchinov. The calculated data using AI-based software was provided by Yohei Muraguchi and Minoru Nakatsugawa.Yohei Muraguchi: Staff, Research & Development Center, Disease Applied Research Dept., Disease Research Group2, Canon Medical Systems Corporation, Tochigi, JapanMinoru Nakatsugawa: Group Manager, Research & Development Center, Advanced Technology Research Dept., Informatics Group, Canon Medical Systems Corporation, Tochigi, JapanYohei Muraguchi and Minoru Nakatsugawa do not have fiduciary responsibility to Canon Inc or Canon Medical Systems Corporation., (© 2024. The Author(s).)

Background It is increasingly recognized that interstitial lung abnormalities (ILAs) detected at CT have potential clinical implications, but automated identification of ILAs has not yet been fully established. Purpose To develop and test automated ILA probability prediction models using machine learning techniques on CT images. Materials and Methods This secondary analysis of a retrospective study included CT scans from patients in the Boston Lung Cancer Study collected between February 2004 and June 2017. Visual assessment of ILAs by two radiologists and a pulmonologist served as the ground truth. Automated ILA probability prediction models were developed that used a stepwise approach involving section inference and case inference models. The section inference model produced an ILA probability for each CT section, and the case inference model integrated these probabilities to generate the case-level ILA probability. For indeterminate sections and cases, both two- and three-label methods were evaluated. For the case inference model, we tested three machine learning classifiers (support vector machine [SVM], random forest [RF], and convolutional neural network [CNN]). Receiver operating characteristic analysis was performed to calculate the area under the receiver operating characteristic curve (AUC). Results A total of 1382 CT scans (mean patient age, 67 years ± 11 [SD]; 759 women) were included. Of the 1382 CT scans, 104 (8%) were assessed as having ILA, 492 (36%) as indeterminate for ILA, and 786 (57%) as without ILA according to ground-truth labeling. The cohort was divided into a training set ( n = 96; ILA, n = 48), a validation set ( n = 24; ILA, n = 12), and a test set ( n = 1262; ILA, n = 44). Among the models evaluated (two- and three-label section inference models; two- and three-label SVM, RF, and CNN case inference models), the model using the three-label method in the section inference model and the two-label method and RF in the case inference model achieved the highest AUC, at 0.87. Conclusion The model demonstrated substantial performance in estimating ILA probability, indicating its potential utility in clinical settings. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Zagurovskaya in this issue.

Little information is available regarding incidence and severity of pulmonary embolism (PE) across the periods of ancestral strain, Alpha, Delta, and Omicron variants. The aim of this study is to investigate the incidence and severity of PE over the dominant periods of ancestral strain and Alpha, Delta, and Omicron variants. We hypothesized that the incidence and the severity by proximity of PE in patients with the newer variants and vaccination would be decreased compared with those in ancestral and earlier variants. Patients with COVID-19 diagnosis between March 2020 and February 2022 and computed tomography pulmonary angiogram performed within a 6-week window around the diagnosis (-2 to +4 weeks) were studied retrospectively. The primary endpoints were the associations of the incidence and location of PE with the ancestral strain and each variant. Of the 720 coronavirus disease 2019 patients with computed tomography pulmonary angiogram (58.6 ± 17.2 years; 374 females), PE was diagnosed among 42/358 (12%) during the ancestral strain period, 5/60 (8%) during the Alpha variant period, 16/152 (11%) during the Delta variant period, and 13/150 (9%) during the Omicron variant period. The most proximal PE (ancestral strain vs variants) was located in the main/lobar arteries (31% vs 6%-40%), in the segmental arteries (52% vs 60%-75%), and in the subsegmental arteries (17% vs 0%-19%). There was no significant difference in both the incidence and location of PE across the periods, confirmed by multivariable logistic regression models. In summary, the incidence and severity of PE did not significantly differ across the periods of ancestral strain and Alpha, Delta, and Omicron variants., Competing Interests: MN reports research grant to the institution from Merck, Canon Medical Systems, AstraZeneca, and Daiichi Sankyo; and consulting fees from Daiichi Sankyo and AstraZeneca, outside the submitted work. CRGG reports stock ownership of GSK, Roche, and Novartis, outside the submitted work. GMH reports consulting fees from Boehringer Ingelheim, Gerson Lehrman Group, and Chugai Pharmaceuticals, outside the submitted work. BDL reports grants or contacts from NIH, Pieris Pharmaceuticals, SRA, and Sanofi; royalties or licenses from Propeller Health; consulting fees from AstraZeneca, NControl, Cartesian, Novartis, Gossamer Bio, and Thetis Pharmaceuticals; participation on a data safety monitoring board or advisory board from NIAID; and stock or stock options from Entrinsic Biosciences and Nocion Therapeutics, outside the submitted work. HH reports grants or contracts from Canon Medical Systems Inc and Konica-Minolta Inc; and consulting fees from Canon Medical Systems Inc and Mitsubishi Chemical Co, outside the submitted work. The other authors have no conflicts of interest to disclose., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

Introduction: Bedside cardiac assessment (BCA) is deficient across a spectrum of noncardiology trainees. Learners not taught BCA well may become instructors who do not teach well, creating a self-perpetuating problem. To improve BCA teaching and learning, we developed a high-quality, patient-centered curriculum for medicine clerkship students that could be flexibly implemented and accessible to other health professions learners., Methods: With a constructivist perspective, we aligned learning goals, activities, and assessments. The curriculum used a "listen before you auscultate" framework, capturing patient history as context for a six-step, systematic approach. In the flipped classroom, short videos and practice questions preceded two 1-hour class activities that integrated diagnostic reasoning, pathophysiology, physical diagnosis, and reflection. Activities included case discussions, jugular venous pressure evaluation, heart sound competitions, and simulated conversations with patients. Two hundred sixty-eight students at four US and international medical schools participated. We incorporated feedback, performed thematic analysis, and assessed learners' confidence and knowledge., Results: Low posttest data capture limited quantitative results. Students reported increased confidence in BCA ability. Knowledge increased in both BCA and control groups. Thematic analysis suggested instructional design strategies were effective and peer encounters, skills practice, and encounters with educators were meaningful., Discussion: The curriculum supported active learning of day-to-day clinical competencies and promoted professional identity formation alongside BCA ability. Feedback and increased confidence on the late-clerkship posttest suggested durable learning. We recommend approaches to confirm this and other elements of knowledge, skill acquisition, or behaviors and are surveying impacts on professional identity formation-related constructs., (© 2023 Meisel et al.)

Purpose: To investigate the association of the maximal severity of pneumonia on CT scans obtained within 6-week of diagnosis with the subsequent development of post-COVID-19 lung abnormalities (Co-LA)., Methods: COVID-19 patients diagnosed at our hospital between March 2020 and September 2021 were studied retrospectively. The patients were included if they had (1) at least one chest CT scan available within 6-week of diagnosis; and (2) at least one follow-up chest CT scan available ≥ 6 months after diagnosis, which were evaluated by two independent radiologists. Pneumonia Severity Categories were assigned on CT at diagnosis according to the CT patterns of pneumonia and extent as: 1) no pneumonia (Estimated Extent, 0%); 2) non-extensive pneumonia (GGO and OP, <40%); and 3) extensive pneumonia (extensive OP and DAD, >40%). Co-LA on follow-up CT scans, categorized using a 3-point Co-LA Score (0, No Co-LA; 1, Indeterminate Co-LA; and 2, Co-LA)., Results: Out of 132 patients, 42 patients (32%) developed Co-LA on their follow-up CT scans 6-24 months post diagnosis. The severity of COVID-19 pneumonia was associated with Co-LA: In 47 patients with extensive pneumonia, 33 patients (70%) developed Co-LA, of whom 18 (55%) developed fibrotic Co-LA. In 52 with non-extensive pneumonia, 9 (17%) developed Co-LA: In 33 with no pneumonia, none (0%) developed Co-LA., Conclusions: Higher severity of pneumonia at diagnosis was associated with the increased risk of development of Co-LA after 6-24 months of SARS-CoV-2 infection., (© 2023 The Authors.)

Purpose: To investigate the effect of vaccinations and boosters on the severity of COVID-19 pneumonia on CT scans during the period of Delta and Omicron variants., Methods: Retrospectively studied were 303 patients diagnosed with COVID-19 between July 2021 and February 2022, who had obtained at least one CT scan within 6 weeks around the COVID-19 diagnosis (-2 to +4 weeks). The severity of pneumonia was evaluated with a 6-point scale Pneumonia Score. The association between demographic and clinical data and vaccination status (booster/additional vaccination, complete vaccination and un-vaccination) and the difference between Pneumonia Scores by vaccination status were investigated., Results: Of 303 patients (59.4 ± 16.3 years; 178 females), 62 (20 %) were in the booster/additional vaccination group, 117 (39 %) in the complete vaccination group, and 124 (41 %) in the unvaccinated group. Interobserver agreement of the Pneumonia Score was high (weighted kappa score = 0.875). Patients in the booster/additionally vaccinated group tended to be older (P = 0.0085) and have more underlying comorbidities (P < 0.0001), and the Pneumonia Scores were lower in the booster/additionally vaccinated [median 2 (IQR 0-4)] and completely vaccinated groups [median 3 (IQR 1-4)] than those in the unvaccinated group [median 4 (IQR 2-4)], respectively (P < 0.0001 and P < 0.0001, respectively). A multivariable linear analysis adjusted for confounding factors confirmed the difference., Conclusion: Vaccinated patients, with or without booster/additional vaccination, had milder COVID-19 pneumonia on CT scans than unvaccinated patients during the period of Delta and Omicron variants. This study supports the efficacy of the vaccine against COVID-19 from a radiological perspective., Competing Interests: M.N. reports research grant to the institution from Merck, Canon Medical Systems, AstraZeneca, and Daiichi Sankyo; and consulting fees from Daiichi Sankyo and AstraZeneca, outside the submitted work. C.R.G.G. reports stock ownership of GSK, Roche, and Novartis, outside the submitted work. G.M.H. reports consulting fees from Boehringer Ingelheim, Gerson Lehrman Group, and Chugai Pharmaceuticals, outside the submitted work. B.D.L reports grants or contacts from NIH, Pieris Pharmaceuticals, SRA, and Sanofi; royalties or licenses from Propeller Health; consulting fees from AstraZeneca, NControl, Cartesian, Novartis, Gossamer Bio, and Thetis Pharmaceuticals; participation on a data safety monitoring board or advisory board from NIAID; and stock or stock options from Entrinsic Biosciences and Nocion Therapeutics, outside the submitted work. H.H. reports grants or contracts from Canon Medical Systems Inc and Konica-Minolta Inc; and consulting fees from Canon Medical Systems Inc and Mitsubishi Chemical Co, outside the submitted work. The other authors have no conflicts of interest to be disclosed related to this article., (© 2022 The Authors.)

Objective: This study aimed is to: (1) extend the Integrating the Biology and the Bedside (i2b2) data and application models to include medical imaging appropriate use criteria, enabling it to serve as a platform to monitor local impact of the Protecting Access to Medicare Act's (PAMA) imaging clinical decision support (CDS) requirements, and (2) validate the i2b2 extension using data from the Medicare Imaging Demonstration (MID) CDS implementation., Materials and Methods: This study provided a reference implementation and assessed its validity and reliability using data from the MID, the federal government's predecessor to PAMA's imaging CDS program. The Star Schema was extended to describe the interactions of imaging ordering providers with the CDS. New ontologies were added to enable mapping medical imaging appropriateness data to i2b2 schema. z-Ratio for testing the significance of the difference between 2 independent proportions was utilized., Results: The reference implementation used 26 327 orders for imaging examinations which were persisted to the modified i2b2 schema. As an illustration of the analytical capabilities of the Web Client, we report that 331/1192 or 28.1% of imaging orders were deemed appropriate by the CDS system at the end of the intervention period (September 2013), an increase from 162/1223 or 13.2% for the first month of the baseline period, December 2011 (P = .0212), consistent with previous studies., Conclusions: The i2b2 platform can be extended to monitor local impact of PAMA's appropriateness of imaging ordering CDS requirements., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background The clinical impact of interstitial lung abnormalities (ILAs) on poor prognosis has been reported in many studies, but risk stratification in ILA will contribute to clinical practice. Purpose To investigate the association of traction bronchiectasis/bronchiolectasis index (TBI) with mortality and clinical outcomes in individuals with ILA by using the COPDGene cohort. Materials and Methods This study was a secondary analysis of prospectively collected data. Chest CT scans of participants with ILA for traction bronchiectasis/bronchiolectasis were evaluated and outcomes were compared with participants without ILA from the COPDGene study (January 2008 to June 2011). TBI was classified as follows: TBI-0, ILA without traction bronchiectasis/bronchiolectasis; TBI-1, ILA with bronchiolectasis but without bronchiectasis or architectural distortion; TBI-2, ILA with mild to moderate traction bronchiectasis; and TBI-3, ILA with severe traction bronchiectasis and/or honeycombing. Clinical outcomes and overall survival were compared among the TBI groups and the non-ILA group by using multivariable linear regression model and Cox proportional hazards model, respectively. Results Overall, 5295 participants (median age, 59 years; IQR, 52-66 years; 2779 men) were included, and 582 participants with ILA and 4713 participants without ILA were identified. TBI groups were associated with poorer clinical outcomes such as quality of life scores in the multivariable linear regression model (TBI-0: coefficient, 3.2 [95% CI: 0.6, 5.7; P = .01]; TBI-1: coefficient, 3.3 [95% CI: 1.1, 5.6; P = .003]; TBI-2: coefficient, 7.6 [95% CI: 4.0, 11; P < .001]; TBI-3: coefficient, 32 [95% CI: 17, 48; P < .001]). The multivariable Cox model demonstrated that ILA without traction bronchiectasis (TBI-0-1) and with traction bronchiectasis (TBI-2-3) were associated with shorter overall survival (TBI-0-1: hazard ratio [HR], 1.4 [95% CI: 1.0, 1.9; P = .049]; TBI-2-3: HR, 3.8 [95% CI: 2.6, 5.6; P < .001]). Conclusion Traction bronchiectasis/bronchiolectasis was associated with poorer clinical outcomes compared with the group without interstitial lung abnormalities; TBI-2 and 3 were associated with shorter survival. © RSNA, 2022 Online supplemental material is available for this article . See also the editorial by Lee and Im in this issue.

Background: An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria., Method: The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve., Results: The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant., Conclusion: Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Study Design: A case-control study of risk alleles for degenerative disc disease (DDD) using magnetic resonance (MR) imaging for phenotyping., Objective: We aim to provide the first statistically adequately powered study of the relationship between the presence of common risk alleles and occurrence of DDD in Eastern US population., Summary of Background Data: Many genetic predisposing factors have been identified in elevating the risk of DDD, including common variants in VDR, COL1A1, AGC1, COL9A2/3 genes., Methods: We utilized the Mass General Brigham (MGB) Biobank in which subjects' Medical Record is linked with genotyped data from single-nucleotide polymorphism (SNP) arrays. Subjects with lumbosacral spine MR imaging studies were used to construct the Cases cohort; the Biobank's Controls cohort was used as the Control cohort. Odds ratios (OR) and False-discovery-rate (FDR) q values from multiple-hypotheses-testing corrections were used to assess the likelihood of DDD given occurrence of the listed DDD risk alleles., Results: Four-hundred-fourteen subjects (mean age = 64, range = 27 to 94) were Cases and 925 Controls (mean age = 46, range = 21-61). A systematic search has identified 25 SNPs in 18 genes in the SNP arrays. At univariate level, rs1544410 in VDR was significantly associated with DDD for male subjects (odds ratio [OR] = 0.594, P = 0.011). After adjustment for all significant variants and demographics, three predictor variables had a significant association with the outcome, age (OR = 1.130, q < 0.0001), rs143383 (OR = 1.951, q = 0.056), and rs3737821 (OR = 2.701, q = 0.069). A novel variant-to-variant correlation rs143383:rs763110 had a significant adjusted OR = 7.933, q = 0.070)., Conclusion: In this large-scale study of common variants' correlation with the presence of DDD in the Northeast United States, we have found a novel and significant variant-to-variant interaction to be associated with the risk of developing DDD, corroborating and necessitating the inclusion of gene-gene interactions in predictive risk model development for DDD.Level of Evidence: 4., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: The aim of this study is to assess the role of traction bronchiectasis/bronchiolectasis and its progression as a predictor for early fibrosis in interstitial lung abnormalities (ILA)., Methods: Three hundred twenty-seven ILA participants out of 5764 in the Age, Gene/Environment Susceptibility (AGES)-Reykjavik Study who had undergone chest CT twice with an interval of approximately five-years were enrolled in this study. Traction bronchiectasis/bronchiolectasis index (TBI) was classified on a four-point scale: 0, ILA without traction bronchiectasis/bronchiolectasis; 1, ILA with bronchiolectasis but without bronchiectasis or architectural distortion; 2, ILA with mild to moderate traction bronchiectasis; 3, ILA and severe traction bronchiectasis and/or honeycombing. Traction bronchiectasis (TB) progression was classified on a five-point scale: 1, Improved; 2, Probably improved; 3, No change; 4, Probably progressed; 5, Progressed. Overall survival (OS) among participants with different TB Progression Score and between the TB progression group and No TB progression group was also investigated. Hazard radio (HR) was estimated with Cox proportional hazards model., Results: The higher the TBI at baseline, the higher TB Progression Score (P < 0.001). All five participants with TBI = 3 at baseline progressed; 46 (90 %) of 51 participants with TBI = 2 progressed. TB progression was also associated with shorter OS with statistically significant difference (adjusted HR = 1.68, P < 0.001)., Conclusion: TB progression was visualized on chest CT frequently and clearly. It has the potential to be the predictor for poorer prognosis of ILA., (© 2021 The Author(s).)

Objectives: Quantify the expected rate of CT radiation dose alerts for three body regions using accepted radiation dose benchmarks and assess key determinants of alert frequency., Methods: This IRB-approved retrospective cohort study evaluated consecutive CT examinations performed between July and December 2013 within an academic medical system. CTDI vol x-ray tube output metrics were compared to the body-region-specific benchmark levels, Achievable Doses (AD), Diagnostic Reference Levels (DRL), and Dose Notification Values (DNV). A logistic regression model for the simulated alerts was fit as a function of the independent predictors: scanner, body region, gender, weight, and age., Results: For 17,000 exams, the proportion of events triggering alerts increased with patient weight. Significant covariates were scanner, body region, patient weight and patient age (all p < 0.0001). Odds of alert generation for the AD, DRL, and DNV benchmarks increased by 7.6%, 6.6% and 2.9% per kilogram, respectively, and by 0.8%, 1.1% and -2.7% per year of age (all p < 0.0001). Compared to the most highly optimized scanner, odds of alert generation varied by a factor of 595 for AD, 1126 for DRL, and 13 for DNV., Conclusion: Alert frequency was significantly correlated with weight, age, body region and scanner. Controllable factors include scanner functionality and associated protocol optimization. Patient factors driving alert frequency are predominantly weight, and to a lesser degree, age. Size-agnostic fixed dose thresholds can frequently produce false positive alerts in appropriately performed exams of large patients, while missing opportunities to identify outlier scans of higher-than-expected dose in small patients., (Copyright © 2021 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

Background: Interstitial lung abnormalities (ILA) can be detected on computed tomography (CT) in lung cancer patients and have an association with mortality in advanced non-small cell lung cancer (NSCLC) patients. The aim of this study is to demonstrate the significance of ILA for mortality in patients with stage I NSCLC using Boston Lung Cancer Study cohort., Methods: Two hundred and thirty-one patients with stage I NSCLC from 2000 to 2011 were investigated in this retrospective study (median age, 69 years; 93 males, 138 females). ILA was scored on baseline CT scans prior to treatment using a 3-point scale (0 = no evidence of ILA, 1 = equivocal for ILA, 2 = ILA) by a sequential reading method. ILA score 2 was considered the presence of ILA. The difference of overall survival (OS) for patients with different ILA scores were tested via log-rank test and multivariate Cox proportional hazards models were used to estimate hazard ratios (HRs) including ILA score, age, sex, smoking status, and treatment as the confounding variables., Results: ILA was present in 22 out of 231 patients (9.5%) with stage I NSCLC. The presence of ILA was associated with shorter OS (patients with ILA score 2, median 3.85 years [95% confidence interval (CI): 3.36 - not reached (NR)]; patients with ILA score 0 or 1, median 10.16 years [95%CI: 8.65 - NR]; P <  0.0001). In a Cox proportional hazards model, the presence of ILA remained significant for increased risk for death (HR = 2.88, P = 0.005) after adjusting for age, sex, smoking and treatment., Conclusions: ILA was detected on CT in 9.5% of patients with stage I NSCLC. The presence of ILA was significantly associated with a shorter OS and could be an imaging marker of shorter survival in stage I NSCLC.

Purpose: To investigate if the presence and severity of traction bronchiectasis/bronchiolectasis are associated with poorer survival in subjects with ILA., Method: The study included 3,594 subjects (378 subjects with ILA and 3,216 subjects without ILA) in AGES-Reykjavik Study. Chest CT scans of 378 subjects with ILA were evaluated for traction bronchiectasis/bronchiolectasis, defined as dilatation of bronchi/bronchioles within areas demonstrating ILA. Traction bronchiectasis/bronchiolectasis Index (TBI) was assigned as: TBI = 0, ILA without traction bronchiectasis/bronchiolectasis: TBI = 1, ILA with bronchiolectasis but without bronchiectasis or architectural distortion: TBI = 2, ILA with mild to moderate traction bronchiectasis: TBI = 3, ILA and severe traction bronchiectasis and/or honeycombing. Overall survival (OS) was compared among the subjects in different TBI groups and those without ILA., Results: The median OS was 12.93 years (95%CI; 12.67 - 13.43) in the subjects without ILA; 11.95 years (10.03 - not reached) in TBI-0 group; 8.52 years (7.57 - 9.30) in TBI-1 group; 7.63 years (6.09 - 9.10) in TBI-2 group; 5.40 years (1.85 - 5.98) in TBI-3 group. The multivariable Cox models demonstrated significantly shorter OS of TBI-1, TBI-2, and TBI-3 groups compared to subjects without ILA (P < 0.0001), whereas TBI-0 group had no significant OS difference compared to subjects without ILA, after adjusting for age, sex, and smoking status., Conclusions: The presence and severity of traction bronchiectasis/bronchiolectasis are associated with shorter survival. The traction bronchiectasis/bronchiolectasis is an important contributor to increased mortality among subjects with ILA., Competing Interests: Conflict of interest MN reports personal fees from Daiichi Sankyo, personal fees from AstraZeneca, grants from Research grant to the institution from Merck, grants from Research grant to the institution from Canon Medical systems, grants from Research grant to the institution from AstraZeneca, grants from Research grant to the institution from Daiichi Sankyo, personal fees from Roche, grants from NIH, outside the submitted work; RKP reports grants from NIH, during the conduct of the study; RSJE reports grants from Boehringer Ingelheim, personal fees from Boehringer Ingelheim, personal fees from Chiesi, grants from NHBLI, outside the submitted work; and he is also a founder and co-owner of Quantitative Imaging Solutions which is a company that provides image based consulting and develops software to enable data sharing.; RSJE is also a founder and co-owner of Quantitative Imaging Solutions which is a company that provides image based consulting and develops software to enable data sharing.: Dr. Washko reports grants from NIH, grants and other from Boehringer Ingelheim, other from Quantitative Imaging Solutions, other from PulmonX, grants from BTG Interventional Medicine, grants and other from Janssen Pharmaceuticals, other from GlaxoSmithKline, other from Novartis, other from Vertex, outside the submitted work; and Dr. Washko's spouse works for Biogen.; DAL reports personal fees from Boehringer Ingelheim, personal fees from Parexel, Inc, personal fees from Veracyte, Inc, outside the submitted work; In addition, DAL has a pending patent "Systems and methods for automatic detection and quantification of pathology using dynamic feature classification.": GMH reports personal fees from Boehringer-Ingelheim, personal fees from Gerson Lehrman Group, personal fees from Mitsubishi Chemical, outside the submitted work; HH reports grants from Canon Medical System Inc, grants from Konica Minolta Inc, other from Mitsubishi Chemical Inc, other from Canon Medical System Inc, outside the submitted work., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objective: Assess sensitivity, specificity, and accuracy of two approaches to identify patients with implantable devices that pose safety risks for MRI-an expert-derived approach and an ontology-derived natural language processing (NLP). Determine the proportion of clinical data that identify these implantable devices., Methods: This Institutional Review Board-approved retrospective study was performed at a 793-bed academic hospital. The expert-derived approach used an open-source software with a list of curated terms to query for implantable devices posing high safety risk ("MRI-Red") in patients undergoing MRI. The ontology-derived approach used an NLP system with terms mapped to Systematized Nomenclature of Medicine-Clinical Terms. Queries were performed in three clinical data types-25,000 radiology reports, 174,769 emergency department (ED) notes, and 41,085 other clinical reports (eg, cardiology, operating room, physician notes, radiology reports, pathology reports, patient letters). Sensitivity, specificity, and accuracy of both methods against manual review of a randomly sampled 465 reports were assessed and tested for significant differences between expert-derived and ontology-derived approaches using t test., Results: Accuracy, sensitivity, and specificity of expert-versus ontology-derived approaches were similar (0.83 versus 0.91, P = .080; 0.88 versus 0.96, P = .178; 0.82 versus 0.92, P = .110). The proportion of radiology reports, ED notes, and other clinical reports retrieved containing implantable devices with high safety risks for MRI ranged from 1.47% to 1.88%., Discussion: Artificial intelligence approaches such as expert-driven NLP and ontology-driven NLP have similar accuracy in identifying patients with implantable devices that pose high safety risks for MRI., (Copyright © 2019. Published by Elsevier Inc.)

Background: Presenting features of inflammatory bowel disease (IBD) are non-specific. We hypothesized that mRNA profiles could (1) identify genes and pathways involved in disease pathogenesis; (2) identify a molecular signature that differentiates IBD from other conditions; (3) provide insight into systemic and colon-specific dysregulation through study of the concordance of the gene expression., Methods: Children (8-18 years) were prospectively recruited at the time of diagnostic colonoscopy for possible IBD. We used transcriptome-wide mRNA profiling to study gene expression in colon biopsies and paired whole blood samples. Using blood mRNA measurements, we fit a regression model for disease state prediction that was validated in an independent test set of adult subjects (GSE3365)., Results: Ninety-eight children were recruited [39 Crohn's disease, 18 ulcerative colitis, 2 IBDU, 39 non-IBD]. There were 1,118 significantly differentially (IBD vs non-IBD) expressed genes in colon tissue, and 880 in blood. The direction of relative change in expression was concordant for 106/112 genes differentially expressed in both tissue types. The regression model from the blood mRNA measurements distinguished IBD vs non-IBD disease status in the independent test set with 80% accuracy using only 6 genes. The overlap of 5 immune and metabolic pathways in the two tissue types was significant (p<0.001)., Conclusions: Blood and colon tissue from patients with IBD share a common transcriptional profile dominated by immune and metabolic pathways. Our results suggest that peripheral blood expression levels of as few as 6 genes (IL7R, UBB, TXNIP, S100A8, ALAS2, and SLC2A3) may distinguish patients with IBD from non-IBD., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: AB has received research support form Prometheus, Janssen (ADAPT), and Abbvie (Envision), served on a data and safety monitoring board for Shire, royalties from Up-to-date, honoraria from Harvard University, CE outcomes, Alexion, Boston University, and Nutricia, performed medicolegal services for Fowler-White-Burnett and Cooney Scully Dowling and consulted for Best Doctors and Grand Rounds. RJG has received royalties from UpToDate. ISK has received speaking honoraria Takeda Pharmaceuticals. JAS has consulted for Takeda Pharmaceuticals and received research support from Biomedal S.L., Glutenostics LLC and Cour Pharmaceuticals. Nothing to disclose: ALB, IF, SG, HCH, LMK, SWK, JJL, NPP, FR, VIV.

OBJECTIVE. The purpose of this study is to investigate the magnitude of physician variation in the use of imaging and the factors associated with variation in an urban emergency department (ED) in the United States. MATERIALS AND METHODS. This retrospective cohort study was conducted from April 1, 2013, to March 31, 2014, in the ED of a level I adult trauma center in the northeastern United States. The study cohort included all patient visits to the ED during the study period. We built hierarchic and logistic regression models to determine per-physician utilization of low- and high-cost imaging, and we identified factors correlated with variation in use. Global (i.e., intraclass correlation coefficient) and individual variability metrics were used to profile physician variation after controlling for patient-, visit-, and physician-related covariates. RESULTS. A total of 56,793 patients presented to the ED during the study; of these patients, 49.5% (28,135) underwent imaging, with 38.2% (21,686) undergoing low-cost imaging and 21.9% (12,430) undergoing high-cost imaging. Statistically significant predictors of imaging orders were patient age and sex, number of secondary diagnoses, certain primary diagnoses, time of arrival in the ED, and ED crowding. Unadjusted and adjusted intraclass correlation coefficients were 0.0072 and 0.0066, respectively, for low-cost imaging, and 0.0097 and 0.0090, respectively, for high-cost imaging. The coefficient of variation for adjusted imaging odds ratios was 10.9% and 14.0% for low- and high-cost imaging, respectively, indicating a moderate degree of variation. CONCLUSION. Unexplained and moderate variation in imaging utilization exists among ED physicians, even after controlling for patient, visit, and physician characteristics. Improvement initiatives using well-defined ED imaging quality measures may help improve quality and reduce waste.

Background: Variability in radiation exposure from CT scans can be appropriate and driven by patient features such as body habitus. Quantitative analysis may be performed to discover instances of unwarranted radiation exposure and to reduce the probability of such occurrences in future patient visits. No universal process to perform identification of outliers is widely available, and access to expertise and resources is variable., Objective: The goal of this study is to develop an automated outlier detection procedure to identify all scans with an unanticipated high radiation exposure, given the characteristics of the patient and the type of the exam., Materials and Methods: This Institutional Review Board-approved retrospective cohort study was conducted from June 30, 2012 - December 31, 2013 in a quaternary academic medical center. The de-identified dataset contained 28 fields for 189,959 CT exams. We applied the variable selection method Least Absolute Shrinkage and Selection Operator (LASSO) to select important variables for predicting CT radiation dose. We then employed a regression approach that is robust to outliers, to learn from data a predictive model of CT radiation doses given important variables identified by LASSO. Patient visits whose predicted radiation dose was statistically different from the radiation dose actually received were identified as outliers., Results: Our methodology identified 1% of CT exams as outliers. The top-5 predictors discovered by LASSO and strongly correlated with radiation dose were Tube Current, kVp, Weight, Width of collimator, and Reference milliampere-seconds. A human expert validation of the outlier detection algorithm has yielded specificity of 0.85 [95% CI 0.78-0.92] and sensitivity of 0.91 [95% CI 0.85-0.97] (PPV = 0.84, NPV = 0.92). These values substantially outperform alternative methods we tested (F1 score 0.88 for our method against 0.51 for the alternatives)., Conclusion: The study developed and tested a novel, automated method for processing CT scanner meta-data to identify CT exams where patients received an unwarranted amount of radiation. Radiation safety and protocol review committees may use this technique to uncover systemic issues and reduce future incidents.

Background: When a paucity of clinical information is communicated from ordering physicians to radiologists at the time of radiology order entry, suboptimal imaging interpretations and patient care may result., Objectives: Compare documentation of relevant clinical information in electronic health record (EHR) provider note to computed tomography (CT) order requisition, prior to ordering of head CT for emergency department (ED) patients presenting with headache., Methods: In this institutional review board-approved retrospective observational study performed between April 1, 2013 and September 30, 2014 at an adult quaternary academic hospital, we reviewed data from 666 consecutive ED encounters for patients with headaches who received head CT. The primary outcome was the number of concept unique identifiers (CUIs) relating to headache extracted via ontology-based natural language processing from the history of present illness (HPI) section in ED notes compared with the number of concepts obtained from the imaging order requisition., Results: Our analysis was conducted on cases where the HPI note section was completed prior to image order entry, which occurred in 23.1% (154/666) of encounters. For these 154 encounters, the number of CUIs specific to headache per note extracted from the HPI (median = 3, interquartile range [IQR]: 2-4) was significantly greater than the number of CUIs per encounter obtained from the imaging order requisition (median = 1, IQR: 1-2; Wilcoxon signed rank p  < 0.0001). Extracted concepts from notes were distinct from order requisition indications in 92.9% (143/154) of cases., Conclusion: EHR provider notes are a valuable source of relevant clinical information at the time of imaging test ordering. Automated extraction of clinical information from notes to prepopulate imaging order requisitions may improve communication between ordering physicians and radiologists, enhance efficiency of ordering process by reducing redundant data entry, and may help improve clinical relevance of clinical decision support at the time of order entry, potentially reducing provider burnout from extraneous alerts., Competing Interests: None declared., (Georg Thieme Verlag KG Stuttgart · New York.)

Study Design: A case-control study of the Trp2/3 alleles of COL9A2/3 genes and their correlation with occurrence of Lumbar disc disease (DDD) as phenotyped by magnetic resonance imaging., Objective: To establish a better understanding of relationship between presence of said alleles and occurrence of DDD in South-Western Iranian population., Summary of Background Data: A number of genetic predisposing factors have been identified in elevating the risk of developing DDD. Specifically, the Trp2 and Trp3 alleles of COL9A2 and COL9A3 genes have been suggested as DDD risk variants., Methods: A total of 108 patients (mean age = 41±11.8 yrs, range = 20-66 yrs) with 57 controls (mean age = 35±10.0 yrs, range = 20-58 yrs) participated in the study. The frequency of G/A polymorphism in COL9A2 gene on location 326 on chromosome 1 and G/A/C/ or T polymorphism in 103 location of COL9A3 gene on chromosome 20 was assessed using a PCR short-primer technique. Outcome measure was defined as presence of DDD on MRI. Odds ratios (OR) and 95% confidence intervals (CI) were used to assess the likelihood of DDD given occurrence of Trp2(3)., Results: Each allele was present in both patients and controls. The Trp2 allele was positive in 28.5% of individuals (31.5% of patients; 22.8% of controls), OR 1.55 (0.71-3.56). The Trp3 allele, the frequency was 23.6% in all patients (26.9% patients; 17.5% controls), OR 1.72 (0.73-4.33). We observed a 5.8-fold increase in the odds of DDD in males when the Trp3 allele was present, OR 5.83 (1.09-9.98), P = 0.0273., Conclusion: Both Trp2 and Trp3 alleles occurred more frequently compared with other studied ethnicities. The sampled Iranian population exhibited a similar Trp2 frequency to a Southern Chinese population, and Trp3 occurrence to Finnish and Greek population. We found that male patient were much more likely to develop DDD when Trp 3 was present., Level of Evidence: N/A.

Motivation: We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBI's Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets., Results: Comprehensive pair-wise correlation and expression level profiles are calculated for both datasets (with sizes of 81 and 1463, respectively). We have used mapping and ranking across the Gene Ontology (GO) categories to quantify similarity between the two sets. GO mappings of the most correlated and highly expressed genes from the two datasets tightly match, with the notable exceptions of components of the ribosome, cell adhesion and immune response. That is, 10 877 or 48.8% of all measured genes do not change >10% of rank range between WBC and OO; only 878 (3.9%) change rank >50%. Two trans-tissue gene lists are defined, the most changing and the least changing genes in expression rank. We also provide a general, quantitative measure of the probability of expression rank and correlation profile in the OO system given the expression rank and correlation profile in the WBC dataset.

Trinucleotide repeats sequences (TRS) represent a common type of genomic DNA motif whose expansion is associated with a large number of human diseases. The driving molecular mechanisms of the TRS ongoing dynamic expansion across generations and within tissues and its influence on genomic DNA functions are not well understood. Here we report results for a novel and notable collective breathing behavior of genomic DNA of tandem TRS, leading to propensity for large local DNA transient openings at physiological temperature. Our Langevin molecular dynamics (LMD) and Markov Chain Monte Carlo (MCMC) simulations demonstrate that the patterns of openings of various TRSs depend specifically on their length. The collective propensity for DNA strand separation of repeated sequences serves as a precursor for outsized intermediate bubble states independently of the G/C-content. We report that repeats have the potential to interfere with the binding of transcription factors to their consensus sequence by altered DNA breathing dynamics in proximity of the binding sites. These observations might influence ongoing attempts to use LMD and MCMC simulations for TRS-related modeling of genomic DNA functionality in elucidating the common denominators of the dynamic TRS expansion mutation with potential therapeutic applications.