Search

To determine relationships between prophylactic inferior vena cava filter (IVCF) insertion and pulmonary embolism (PE), deep venous thrombosis (DVT), and in-hospital mortality outcomes in patients with severe traumatic pelvic/lower extremity, intracranial, and spinal cord injuries.Adult patients with severe traumatic pelvic/lower extremity, intracranial, and spinal cord injuries admitted to level I-IV trauma centers were selected from the National Trauma Data Bank (NTDB). IVCFs that were inserted both ≤48 h after admission and before a lower extremity venous ultrasound were defined as prophylactic. Associations between prophylactic IVCF insertion and PE, DVT, and overall mortality outcomes during admission were estimated using logistic regression models after propensity score matching. Additionally, factors predictive of prophylactic IVCF insertion were estimated using multivariate logistic regression.Of 462,838 patients, 11,938 (2.6%) underwent prophylactic IVCF insertion. Prophylactic IVCF utilization decreased over time (6.3% in 2008 to 1.8% in 2015). Factors associated with prophylactic IVCF placement were injury pattern, trauma center level/region, Injury Severity Score, and race. Prophylactic IVCF placement was positively associated with PE (Odds Ratio (OR): 5.25, p 0.01) and DVT (OR: 5.55, p 0.01), but negatively associated with in-hospital mortality compared to the propensity score-matched control group (OR: 0.46, p 0.01).Prophylactic IVCF insertion in adult patients with severe pelvic/lower extremity fractures, intracranial injuries, and spinal cord injuries was negatively associated with in-hospital mortality, but positively associated with VTE. Further research evaluating the use of prophylactic IVCF placement in trauma patients with these specific severe injury types may be warranted.

Metabolic syndrome describes a constellation of reversible cardiometabolic abnormalities associated with cardiovascular risk and diabetes. The present study investigates the use of fully automated abdominal CT-based biometric measures for opportunistic identification of metabolic syndrome in adults without symptoms.International Diabetes Federation criteria were applied to a cohort of 9223 adults without symptoms who underwent unenhanced abdominal CT. After patients with insufficient clinical data for diagnosis were excluded, the final cohort consisted of 7785 adults (mean age, 57.0 years; 4361 women and 3424 men). Previously validated and fully automated CT-based algorithms for quantifying muscle, visceral and subcutaneous fat, liver fat, and abdominal aortic calcification were applied to this final cohort.A total of 738 subjects (9.5% of all subjects; mean age, 56.7 years; 372 women and 366 men) met the clinical criteria for metabolic syndrome. Subsequent major cardiovascular events occurred more frequently in the cohort with metabolic syndrome (Fully automated quantitative tissue measures of fat, muscle, and liver derived from abdominal CT scans can help identify individuals who are at risk for metabolic syndrome. These visceral measures can be opportunistically applied to CT scans obtained for other clinical indications, and they may ultimately provide a more direct and useful definition of metabolic syndrome.

Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role of AI to support cardiac radiologist in their day-to-day tasks, assisting in segmentation, quantification, and reporting tasks. In addition, AI algorithms can be also utilized to optimize image reconstruction and image quality. Since these algorithms will play an important role in the field of cardiac radiology, it is increasingly important for radiologists to be familiar with the potential applications of AI. The main focus of this article is to provide an overview of cardiac-related AI applications for CT and MRI studies, as well as non-imaging-based applications for reporting and image optimization.

Objective: The purpose was to evaluate reader variability between experienced and in-training radiologists of COVID-19 pneumonia severity on chest radiograph (CXR), and to create a multireader database suitable for AI development. Methods: In this study, CXRs from polymerase chain reaction positive COVID-19 patients were reviewed. Six experienced cardiothoracic radiologists and two residents classified each CXR according to severity. One radiologist performed the classification twice to assess intraobserver variability. Severity classification was assessed using a 4-class system: normal (0), mild (1), moderate (2), and severe (3). A median severity score (Rad Med) for each CXR was determined for the six radiologists for development of a multireader database (XCOMS). Kendal Tau correlation and percentage of disagreement were calculated to assess variability. Results: A total of 397 patients (1208 CXRs) were included (mean age, 60 years SD ± 1), 189 men). Interobserver variability between the radiologists ranges between 0.67 and 0.78. Compared to the Rad Med score, the radiologists show good correlation between 0.79–0.88. Residents show slightly lower interobserver agreement of 0.66 with each other and between 0.69 and 0.71 with experienced radiologists. Intraobserver agreement was high with a correlation coefficient of 0.77. In 220 (18%), 707 (59%), 259 (21%) and 22 (2%) CXRs there was a 0, 1, 2 or 3 class-difference. In 594 (50%) CXRs the median scores of the residents and the radiologists were similar, in 578 (48%) and 36 (3%) CXRs there was a 1 and 2 class-difference. Conclusion: Experienced and in-training radiologists demonstrate good inter- and intraobserver agreement in COVID-19 pneumonia severity classification. A higher percentage of disagreement was observed in moderate cases, which may affect training of AI algorithms. Advances in knowledge: Most AI algorithms are trained on data labeled by a single expert. This study shows that for COVID-19 X-ray severity classification there is significant variability and disagreement between radiologist and between residents.

Ischemic cardiomyopathy (ICM) is one of the most common causes of congestive heart failure. In patients with ICM, tissue characterization with cardiac magnetic resonance imaging (CMR) allows for evaluation of myocardial abnormalities in acute and chronic settings. Myocardial edema, microvascular obstruction (MVO), intracardiac thrombus, intramyocardial hemorrhage, and late gadolinium enhancement of the myocardium are easily depicted using standard CMR sequences. In the acute setting, tissue characterization is mainly focused on assessment of ventricular thrombus and MVO, which are associated with poor prognosis. Conversely, in chronic ICM, it is important to depict late gadolinium enhancement and myocardial ischemia using stress perfusion sequences. Overall, with CMR's ability to accurately characterize myocardial tissue in acute and chronic ICM, it represents a valuable diagnostic and prognostic imaging method for treatment planning. In particular, tissue characterization abnormalities in the acute setting can provide information regarding the patients that may develop major adverse cardiac event and show the presence of ventricular thrombus; in the chronic setting, evaluation of viable myocardium can be fundamental for planning myocardial revascularization. In this review, the main findings on tissue characterization are illustrated in acute and chronic settings using qualitative and quantitative tissue characterization.

The purpose of this work was to assess the performance of a convolutional neural network (CNN) for automatic thoracic aortic measurements in a heterogeneous population. From June 2018 to May 2019, this study retrospectively analyzed 250 chest CT scans with or without contrast enhancement and electrocardiographic gating from a heterogeneous population with or without aortic pathologic findings. Aortic diameters at nine locations and maximum aortic diameter were measured manually and with an algorithm (Artificial Intelligence Rad Companion Chest CT prototype, Siemens Healthineers) by using a CNN. A total of 233 examinations performed with 15 scanners from three vendors in 233 patients (median age, 65 years [IQR, 54–72 years]; 144 men) were analyzed: 68 (29%) without pathologic findings, 72 (31%) with aneurysm, 51 (22%) with dissection, and 42 (18%) with repair. No evidence of a difference was observed in maximum aortic diameter between manual and automatic measurements (P = .48). Overall measurements displayed a bias of −1.5 mm and a coefficient of repeatability of 8.0 mm at Bland-Altman analyses. Contrast enhancement, location, pathologic finding, and positioning inaccuracy negatively influenced reproducibility (P < .003). Sites with dissection or repair showed lower agreement than did sites without. The CNN performed well in measuring thoracic aortic diameters in a heterogeneous multivendor CT dataset. Keywords: CT, Vascular, Aorta © RSNA, 2022

16 Pags.- 8 Figs. This article is licensed under a Creative Commons Attribution 4.0 International License., Our understanding of polyploid genome evolution is constrained because we cannot know the exact founders of a particular polyploid. To differentiate between founder effects and post polyploidization evolution, we use a pan-genomic approach to study the allotetraploid Brachypodium hybridum and its diploid progenitors. Comparative analysis suggests that most B. hybridum whole gene presence/absence variation is part of the standing variation in its diploid progenitors. Analysis of nuclear single nucleotide variants, plastomes and k-mers associated with retrotransposons reveals two independent origins for B. hybridum, ~1.4 and ~0.14 million years ago. Examination of gene expression in the younger B. hybridum lineage reveals no bias in overall subgenome expression. Our results are consistent with a gradual accumulation of genomic changes after polyploidization and a lack of subgenome expression dominance. Significantly, if we did not use a pan-genomic approach, we would grossly overestimate the number of genomic changes attributable to post polyploidization evolution., The work conducted by the US DOE Joint Genome Institute is supported by the Office of Science of the US Department of Energy under Contract no. DE-AC02-05CH11231 and User Agreement No. FP00006675 between the University of Zaragoza (User) and the DOE (Community Science Program 503504 proposal); S.J. was supported by the DOE Office of Science Graduate Student Research Program; P.C., B.C.-M., A.D.P., and R.S. were supported by a Spanish Ministry of Economy and Competitiveness grant CGL2016-79790-P; P.C., A.D.P., and R.S. were supported by a Bioflora A01-17 grant co-funded by the Spanish Aragon Government and the European Social Fund. R.H., E.W., and J.L. were supported by the National Science Centre Poland (grants DEC-2012/04/A/NZ3/00572 and DEC-2014/14/M/NZ2/00519). J.H.D. and C.N. were supported by Leverhulme Trust (grant no. 10754). A.C.E. and A.D. were supported by the European Research Council under the European Union’s Seventh Framework Program (FP7/2007-2013)/ERC grant agreement no [GA335691 “Effectomics”], the Austrian Science Fund (FWF): [P27429-B22, P27818-B22, I 3033-B22], and the Austrian Academy of Science (OEAW).

Summary: Background: Body CT scans are frequently done for a wide range of clinical indications, but potentially valuable biometric information typically goes unused. We aimed to compare the prognostic ability of automated CT-based body composition biomarkers derived from previously developed deep-learning and feature-based algorithms with that of clinical parameters (Framingham risk score [FRS] and body-mass index [BMI]) for predicting major cardiovascular events and overall survival in an adult screening cohort. Methods: In this retrospective cohort study, mature and fully automated CT-based algorithms with predefined metrics for quantifying aortic calcification, muscle density, ratio of visceral to subcutaneous fat, liver fat, and bone mineral density were applied to a generally healthy asymptomatic outpatient cohort of adults aged 18 years or older undergoing abdominal CT for routine colorectal cancer screening. To assess the association between the predictive measures (CT-based vs FRS and BMI) and downstream adverse events (death or myocardial infarction, cerebrovascular accident, or congestive heart failure subsequent to CT scanning), we used both an event-free survival analysis and logistic regression to compute receiver operating characteristic curves (ROCs) . Findings: 9223 people (mean age 57·1 years [SD 7·8]; 5152 [56%] women and 4071 [44%] men) who underwent CT scans between April, 2004, and December, 2016, were included in this analysis. In the longitudinal clinical follow-up (median 8·8 years [IQR 5·1–11·6]), subsequent major cardiovascular events or death occurred in 1831 (20%) patients. Significant differences were observed for all five automated CT-based body composition measures according to adverse events (p

Transfer learning is a common practice in image classification with deep learning where the available data is often limited for training a complex model with millions of parameters. However, transferring language models requires special attention since cross-domain vocabularies (e.g. between news articles and radiology reports) do not always overlap as the pixel intensity range overlaps mostly for images. We present a concept of similar domain adaptation where we transfer an inter-institutional language model between two different modalities (ultrasound to MRI) to capture liver abnormalities. Our experiments show that such transfer is more effective for performing shared targeted task than generic language space transfer. We use MRI screening exam reports for hepatocellular carcinoma as the use-case and apply the transfer language space strategy to automatically label thousands of imaging exams.

Background Body composition data from abdominal CT scans have the potential to opportunistically identify those at risk for future fracture. Purpose To apply automated bone, muscle, and fat tools to noncontrast CT to assess performance for predicting major osteoporotic fractures and to compare with the Fracture Risk Assessment Tool (FRAX) reference standard. Materials and Methods Fully automated bone attenuation (L1-level attenuation), muscle attenuation (L3-level attenuation), and fat (L1-level visceral-to-subcutaneous [V/S] ratio) measures were derived from noncontrast low-dose abdominal CT scans in a generally healthy asymptomatic adult outpatient cohort from 2004 to 2016. The FRAX score was calculated from data derived from an algorithmic electronic health record search. The cohort was assessed for subsequent future fragility fractures. Subset analysis was performed for patients evaluated with dual x-ray absorptiometry (n = 2106). Hazard ratios (HRs) and receiver operating characteristic curve analyses were performed. Results A total of 9223 adults were evaluated (mean age, 57 years ± 8 [standard deviation]; 5152 women) at CT and were followed over a median time of 8.8 years (interquartile range, 5.1-11.6 years), with documented subsequent major osteoporotic fractures in 7.4% (n = 686), including hip fractures in 2.4% (n = 219). Comparing the highest-risk quartile with the other three quartiles, HRs for bone attenuation, muscle attenuation, V/S fat ratio, and FRAX were 2.1, 1.9, 0.98, and 2.5 for any fragility fracture and 2.0, 2.5, 1.1, and 2.5 for femoral fractures, respectively (P < .001 for all except V/S ratio, which was P ≥ .51). Area under the receiver operating characteristic curve (AUC) values for fragility fracture were 0.71, 0.65, 0.51, and 0.72 at 2 years and 0.63, 0.62, 0.52, and 0.65 at 10 years, respectively. For hip fractures, 2-year AUC for muscle attenuation alone was 0.75 compared with 0.73 for FRAX (P = .43). Multivariable 2-year AUC combining bone and muscle attenuation was 0.73 for any fragility fracture and 0.76 for hip fractures, respectively (P ≥ .73 compared with FRAX). For the subset with dual x-ray absorptiometry T-scores, 2-year AUC was 0.74 for bone attenuation and 0.65 for FRAX (P = .11). Conclusion Automated bone and muscle imaging biomarkers derived from CT scans provided comparable performance to Fracture Risk Assessment Tool score for presymptomatic prediction of future osteoporotic fractures. Muscle attenuation alone provided effective hip fracture prediction. © RSNA, 2020 See also the editorial by Smith in this issue.

Artificial intelligence (AI) will continue to cause substantial changes within the field of radiology, and it will become increasingly important for clinicians to be familiar with several concepts behind AI algorithms in order to effectively guide their clinical implementation. This review aims to give medical professionals the basic information needed to understand AI development and research. The general concepts behind several AI algorithms, including their data requirements, training, and evaluation methods are explained. The potential legal implications of using AI algorithms in clinical practice are also discussed.

We sought to determine if vertebral trabecular attenuation values measured on routine body computed tomography (CT) scans obtained for a variety of unrelated indications can predict future osteoporotic fractures at multiple skeletal sites. For this Health Insurance Portability and Accountability Act (HIPAA)-compliant and Institutional Review Board (IRB)-approved retrospective cohort study, trabecular attenuation of the first lumbar vertebra was measured in 1966 consecutive older adults who underwent chest and/or abdominal CT at a single institution over the course of 1 year. New pathologic fragility fractures that occurred after a patient's CT study date were identified through an electronic health record database query using International Classification of Diseases (ICD)-9 codes for vertebral, hip, and extremity fractures. Univariate and multivariate Cox proportional hazards regression were performed to determine the effect of L1 trabecular attenuation on fracture-free survival. Age at CT, sex, and presence of a prior fragility fracture were included as confounders in multivariate survival analysis. Model discriminative capability was assessed through calculation of an optimism-corrected concordance index. A total of 507 patients (mean age 73.4 ± 6.3 years; 277 women, 230 men) were included in the final analysis. The median post-CT follow-up interval was 5.8 years (interquartile range 2.1-11.0 years). Univariate analysis showed that L1 attenuation values ≤90 Hounsfield units (HU) are significantly associated with decreased fracture-free survival (p < 0.001 by log-rank test). After adjusting for age, sex, prior fracture, glucocorticoid use, bisphosphonate use, chronic kidney disease, tobacco use, ethanol abuse, cancer history, and rheumatoid arthritis history, multivariate analysis demonstrated a persistent modest effect of L1 attenuation on fracture-free survival (hazard ratio [HR] = 0.63 per 10-unit increase; 95% confidence interval [CI] 0.47-0.85). The model concordance index was 0.700. Ten-year probabilities for major osteoporosis-related fractures straddled the treatment threshold for most subcohorts over the observed L1 HU range. In conclusion, for patients undergoing body CT scanning for any indication, L1 vertebral trabecular attenuation is a simple measure that, when ≤90 HU, identifies patients with a significant decrease in fracture-free survival. © 2018 American Society for Bone and Mineral Research.

Low bone mineral density (osteoporosis and osteopenia) leading to fragility fractures is associated with significant morbidity and mortality in our aging population. This condition is grossly underdiagnosed due to both insufficient screening and its silent nature prior to complicating fragility fractures. Body CT scans are commonly obtained among older adults for a wide variety of indications and contain rich data regarding bone health that are often ignored. At the University of Wisconsin, we have sought to harness this CT information for “opportunistic” osteoporosis screening. In this article, we review the various CT-based approaches we have taken to date, including routine assessment of the spine for both vertebral fractures and trabecular density, as well as assessment of the hip, deriving femoral neck T-scores that are essentially equivalent to dual-energy x-ray absorptiometry (DXA). Future directions of research and clinical implementation are also discussed.

Hip fracture is a major consequence of low bone mineral density, which is treatable but underdiagnosed. The purpose of this case-control study is to determine whether lumbar vertebral trabecular attenuation, vertebral compression fractures, and femoral neck T scores readily derived from abdominopelvic CT scans obtained for various indications are associated with future hip fragility fracture.A cohort of 204 patients with hip fracture (130 women and 74 men; mean age, 74.3 years) who had undergone abdominopelvic CT before fracture occurred (mean interval, 24.8 months) was compared with an age- and sex-matched control cohort without hip fracture. L1 trabecular attenuation, vertebral compression fractures of grades 2 and 3, and femoral neck T scores derived from asynchronous quantitative CT were recorded. The presence of one or more clinical risk factor for fracture was also recorded. Multivariate logistic regression models were used to determine the association of each measurement with the occurrence of hip fracture.The mean L1 trabecular attenuation value, the presence of one or more vertebral compression fracture, and CT-derived femoral neck T scores were all significantly different in patients with hip fracture versus control subjects (p0.01). Logistic regression models showed a significant association of all measurements with hip fracture outcome after adjustments were made for age, sex, and the presence of one or more clinical risk factor. L1 trabecular attenuation and CT-derived femoral neck T scores showed moderate accuracy in differentiating case and control patients (AUC, 0.70 and 0.78, respectively).L1 trabecular attenuation, CT-derived femoral neck T scores, and the presence of at least one vertebral compression fracture on CT are all associated with future hip fragility fracture in adults undergoing routine abdominopelvic CT for a variety of conditions.

Effective implementation of technology that facilitates accurate and high-throughput screening of thousands of field-grown lines is critical for accelerating crop improvement and breeding strategies for higher yield and disease tolerance. Progress in the development of field-based high throughput phenotyping methods has advanced considerably in the last 10 years through technological progress in sensor development and high-performance computing. Here, we review recent advances in high throughput field phenotyping technologies designed to inform the genetics of quantitative traits, including crop yield and disease tolerance. Successful application of phenotyping platforms to advance crop breeding and identify and monitor disease requires: (1) high resolution of imaging and environmental sensors; (2) quality data products that facilitate computer vision, machine learning and GIS; (3) capacity infrastructure for data management and analysis; and (4) automated environmental data collection. Accelerated breeding for agriculturally relevant crop traits is key to the development of improved varieties and is critically dependent on high-resolution, high-throughput field-scale phenotyping technologies that can efficiently discriminate better performing lines within a larger population and across multiple environments.

Sorghum bicolor is a promising cellulosic feedstock crop for bioenergy because of its potential for high biomass yields. However, in its early growth phases, sorghum is sensitive to cold stress, preventing early planting in temperate environments. Cold temperature adaptability is vital for the successful cultivation of both bioenergy and grain sorghum at higher latitudes and elevations, and for early season planting or to extend the growing season. Identification of genes and alleles that enhance biomass accumulation of sorghum grown under early cold stress would enable the development of improved bioenergy sorghum through breeding or genetic engineering. We conducted image-based phenotyping on 369 accessions from the sorghum Bioenergy Association Panel (BAP) in a controlled environment with early cold treatment. The BAP is a collection of densely genotyped and racially, geographically, and phenotypically diverse accessions. The plants were weighed, watered, and imaged daily to measure growth dynamics and water use efficiency (WUE). Daily, non-destructive imaging allowed for a temporal analysis of growth-related traits in response to cold stress. We performed a genome-wide association study (GWAS) to identify candidate genomic intervals and genes controlling response to early cold stress. GWAS identified transient quantitative trait loci (QTL) strongly associated with each growth-related trait, permitting an investigation into the genetic basis of cold stress response at different stages of development. The analysis identified a priori and novel candidate genes associated with growth-related traits and the temporal response to cold stress.SIGNIFICANCE STATEMENTGenome-wide association study of bioenergy sorghum accessions phenotyped under early season cold stress revealed transient QTLs for highly heritable biomass and growth-related traits that appeared as the temperature increased and plants developed. Sorghum accessions clustered into multiple groups for each heritable trait with distinct growth profiles. GWAS identified candidate genes associated with growth traits and cold stress responses. The top-performing accessions with the highest growth-related trait values over time and temperature shifts will be useful for further genetic analysis and breeding or engineering efforts directed at biomass yield enhancements.

The purpose of the study was to determine the prevalence of ischemic and alternative diagnoses and the diagnostic accuracy of CT angiography (CTA) in the setting of suspected acute mesenteric ischemia (AMI). We included 959 patients undergoing CTA for the evaluation of suspected AMI. The final clinical diagnosis was used to determine the prevalence of ischemic and alternative diagnoses and to calculate the diagnostic accuracy of CTA. Prevalence of diagnoses by age, sex, and admission status was compared using Cochran–Armitage and χ 2 tests. Prevalence was 18.8% (180/959) for AMI and 61.2% (587/959) for specific alternative diagnoses. In the remaining 20.0% (192/959), no clear clinical diagnosis was established. The most frequent alternative diagnoses were small-bowel obstruction (10.4%; 61/587), infectious colitis (8.7%; 51/587), pneumonia (6.5%; 38/587), cholecystitis (6.1%; 36/587), and diverticulitis (5.6%; 33/587). Prevalence of specific alternative diagnoses varied significantly according to both age (p

Summary Miscanthus spp. are promising lignocellulosic energy crops, but cell wall recalcitrance to deconstruction still hinders their widespread use as bioenergy and biomaterial feedstocks. Identification of cell wall characteristics desirable for biorefining applications is crucial for lignocellulosic biomass improvement. However, the task of scoring biomass quality is often complicated by the lack of a reference for a given feedstock. A multidimensional cell wall analysis was performed to generate a reference profile for leaf and stem biomass from several miscanthus genotypes harvested at three developmentally distinct time points. A comprehensive suite of 155 monoclonal antibodies was used to monitor changes in distribution, structure and extractability of noncellulosic cell wall matrix glycans. Glycan microarrays complemented with immunohistochemistry elucidated the nature of compositional variation, and in situ distribution of carbohydrate epitopes. Key observations demonstrated that there are crucial differences in miscanthus cell wall glycomes, which may impact biomass amenability to deconstruction. For the first time, variations in miscanthus cell wall glycan components were comprehensively characterized across different harvests, organs and genotypes, to generate a representative reference profile for miscanthus cell wall biomass. Ultimately, this portrait of the miscanthus cell wall will help to steer breeding and genetic engineering strategies for the development of superior energy crops.

Background Abdominal and thoracic CT provide a valuable opportunity for osteoporosis screening regardless of the clinical indication for imaging. Purpose To establish reference normative ranges for first lumbar vertebra (L1) trabecular attenuation values across all adult ages to measure bone mineral density (BMD) at routine CT. Materials and Methods Reference data were constructed from 20 374 abdominal and/or thoracic CT examinations performed at 120 kV. Data were derived from adults (mean age, 60 years ± 12 [standard deviation]; 56.1% [11 428 of 20 374] women). CT examinations were performed with (n = 4263) or without (n = 16 111) intravenous contrast agent administration for a variety of unrelated clinical indications between 2000 and 2018. L1 Hounsfield unit measurement was obtained either with a customized automated tool (n = 11 270) or manually by individual readers (n = 9104). The effects of patient age, sex, contrast agent, and manual region-of-interest versus fully automated L1 Hounsfield unit measurement were assessed using multivariable logistic regression analysis. Results Mean L1 attenuation decreased linearly with age at a rate of 2.5 HU per year, averaging 226 HU ± 44 for patients younger than 30 years and 89 HU ± 38 for patients 90 years or older. Women had a higher mean L1 attenuation compared with men (P < .008) until menopause, after which both groups had similar values. Administration of intravenous contrast agent resulted in negligible differences in mean L1 attenuation values except in patients younger than 40 years. The fully automated method resulted in measurements that were average 21 HU higher compared with manual measurement (P < .004); at intrapatient subanalysis, this difference was related to the level of transverse measurement used (midvertebra vs off-midline level). Conclusion Normative ranges of L1 vertebra trabecular attenuation were established across all adult ages, and these can serve as a quick reference at routine CT to identify adults with low bone mineral density who are at risk for osteoporosis. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Smith in this issue.

The automated BMD tool was retrospectively applied to non-contrast abdominal CT scans in 1603 consecutive asymptomatic adults (mean age, 55.9 years; 770 M/833 F) undergoing longitudinal screening (mean interval, 5.7 years; range, 1.0-12.3 years). The spinal column was automatically segmented, with standardized L1 and L2 anterior trabecular ROI placement. Automated and manual L1 HU values were compared, as were automated supine-prone measures. L1-L2 CT attenuation values were converted to BMD values through a linear regression model. BMD values and changes were assessed according to age and gender.Success rate of the automated BMD tool was 99.8 % (four failed cases). Both automated supine vs prone and manual vs automated L1 attenuation measurements showed good agreement. Overall mean annual rate of bone loss was greater in females than males (-2.0% vs -1.0%), but the age-specific rate declined faster in females from age 50 (-2.1%) to age 65 (-0.3%) compared with males (-0.9% to -0.5%). Mean BMD was higher in females than males at age 50 (143.6 vs 135.1 mg cmThis robust, fully automated CT BMD tool allows for both individualized and population-based assessment. Mean BMD was lower in men than women aged 50-60, but accelerated post-menopausal bone loss in women resulted in lower values beyond age 60.This fully automated tool can be applied to routine abdominal CT scans for prospective or retrospective opportunistic BMD assessment, including change over time. Mean BMD was lower in men compared with women aged 50-60 years, but accelerated bone loss in women during this early post-menopausal period resulted in lower BMD values for women beyond age 60.

Grass biomass is comprised chiefly of secondary walls that surround fiber and xylem cells. A regulatory network of interacting transcription factors in part regulates cell wall thickening. We identified Brachypodium distachyon SECONDARY WALL ASSOCIATED MYB1 (SWAM1) as a potential regulator of secondary cell wall biosynthesis based on gene expression, phylogeny, and transgenic plant phenotypes. SWAM1 interacts with cellulose and lignin gene promoters with preferential binding to AC-rich sequence motifs commonly found in the promoters of cell wall-related genes. SWAM1 overexpression (SWAM-OE) lines had greater above-ground biomass with only a slight change in flowering time while SWAM1 dominant repressor (SWAM1-DR) plants were severely dwarfed with a striking reduction in lignin of sclerenchyma fibers and stem epidermal cell length. Cellulose, hemicellulose, and lignin genes were significantly down-regulated in SWAM1-DR plants and up-regulated in SWAM1-OE plants. There was no reduction in bioconversion yield in SWAM1-OE lines; however, it was significantly increased for SWAM1-DR samples. Phylogenetic and syntenic analyses strongly suggest that the SWAM1 clade was present in the last common ancestor between eudicots and grasses, but is not in the Brassicaceae. Collectively, these data suggest that SWAM1 is a transcriptional activator of secondary cell wall thickening and biomass accumulation in B. distachyon.

A dual-fluorescent-dye protocol to visualize and quantify Clostridium phytofermentans ISDg (ATCC 700394) cells growing on insoluble cellulosic substrates was developed by combining calcofluor white staining of the growth substrate with cell staining using the nucleic acid dye Syto 9. Cell growth, cell substrate attachment, and fermentation product formation were investigated in cultures containing either Whatman no. 1 filter paper, wild-type Sorghum bicolor , or a reduced-lignin S. bicolor double mutant ( bmr-6 bmr-12 double mutant) as the growth substrate. After 3 days of growth, cell numbers in cultures grown on filter paper as the substrate were 6.0- and 2.2-fold higher than cell numbers in cultures with wild-type sorghum and double mutant sorghum, respectively. However, cells produced more ethanol per cell when grown with either sorghum substrate than with filter paper as the substrate. Ethanol yields of cultures were significantly higher with double mutant sorghum than with wild-type sorghum or filter paper as the substrate. Moreover, ethanol production correlated with cell attachment in sorghum cultures: 90% of cells were directly attached to the double mutant sorghum substrate, while only 76% of cells were attached to wild-type sorghum substrate. With filter paper as the growth substrate, ethanol production was correlated with cell number; however, with either wild-type or mutant sorghum, ethanol production did not correlate with cell number, suggesting that only a portion of the microbial cell population was active during growth on sorghum. The dual-staining procedure described here may be used to visualize and enumerate cells directly on insoluble cellulosic substrates, enabling in-depth studies of interactions of microbes with plant biomass.

To evaluate semi-automated measurement of liver surface nodularity (LSN) on MDCT in a cause-specific cohort of patients with chronic hepatitis C virus infection (HCV) for identification of hepatic fibrosis (stages F0–4). MDCT scans in patients with known HCV were evaluated with an independently validated, semi-automated LSN measurement tool. Consecutive LSN measurements along the anterior liver surface were performed to derive mean LSN scores. Scores were compared with METAVIR fibrosis stage (F0–4). Fibrosis stages F0–3 were based on biopsy results within 1 year of CT. Most patients with cirrhosis (F4) also had biopsy within 1 year; the remaining cases had unequivocal clinical/imaging evidence of cirrhosis and biopsy was not indicated. 288 patients (79F/209M; mean age, 49.7 years) with known HCV were stratified based on METAVIR fibrosis stage: F0 (n = 43), F1 (n = 29), F2 (n = 53), F3 (n = 37), and F4 (n = 126). LSN scores increased with increasing fibrosis (mean: F0 = 2.3 ± 0.2, F1 = 2.4 ± 0.3, F2 = 2.6 ± 0.5, F3 = 2.9 ± 0.6, F4 = 3.8 ± 1.0; p

We sought to determine if vertebral trabecular attenuation values measured on routine body CT scans obtained for a variety of unrelated indications can predict future osteoporotic fractures at multiple skeletal sites. For this HIPAA-compliant and IRB-approved retrospective cohort study, trabecular attenuation of the first lumbar vertebra was measured in 1966 consecutive older adults who underwent chest and/or abdominal CT at a single institution over the course of one year. New pathologic fragility fractures that occurred after a patient’s CT study date were identified through an electronic health record database query using ICD-9 codes for vertebral, hip, and extremity fractures. Univariate and multivariate Cox proportional hazards regression were performed to determine the effect of L1 trabecular attenuation on fracture-free survival. Age at CT, gender, and presence of a prior fragility fracture were included as confounders in multivariate survival analysis. Model discriminative capability was assessed through calculation of an optimism-corrected concordance index. A total of 507 patients (mean age 73.4 ± 6.3 years; 277 women, 230 men) were included in the final analysis. The median post-CT follow-up interval was 5.8 years (interquartile range 2.1 – 11.0 years). Univariate analysis showed that L1 attenuation values ≤90 HU are significantly associated with decreased fracture-free survival (p< 0.001 by log-rank test). After adjusting for age, gender, prior fracture, glucocorticoid use, bisphosphonate use, chronic kidney disease, tobacco use, ethanol abuse, cancer history, and rheumatoid arthritis history, multivariate analysis demonstrated a persistent modest effect of L1 attenuation on fracture-free survival (HR: 0.63 per 10-unit increase; 95% CI: 0.47 – 0.85). The model concordance index was 0.700. Ten-year probabilities for major osteoporosis-related fractures straddled the treatment threshold for most sub-cohorts over the observed L1 HU range. In conclusion, for patients undergoing body CT scanning for any indication, L1 vertebral trabecular attenuation is a simple measure that, when ≤90 HU, identifies patients with a significant decrease in fracture free survival.

Radiologists interpreting body CT scans may be the first to identify osteoporosis and associated vertebral fractures. This study correlates L1 trabecular attenuation measurements with prevalent vertebral body fractures in older adults undergoing routine CT.Mean L1 trabecular attenuation was measured at thoracoabdominal CT in 1966 consecutive adults (983 men and 983 women) 65 years and older (mean age, 74.1 ± 6.6 [SD] years). Sagittal reconstructions and lateral scouts were analyzed for moderate or severe thoracolumbar vertebral compression fractures according to the Genant semiquantitative assessment method. The diagnostic performance of L1 attenuation for the evaluation of prevalent vertebral fractures was assessed, including ROC curve analysis.A total of 162 (8.2%) individuals (mean age, 78.3 years; 66 men, 96 women) had at least one moderate or severe vertebral fracture. The mean L1 attenuation was 70.2 HU among patients with a prevalent fracture, whereas it was 132.3 HU among patients without fracture (p0.001). The prevalence of moderate or severe vertebral compression fractures was 32.5% when L1 attenuation was ≤ 90 HU. Prevalence increased to 49.2% with L1 attenuation of ≤ 50 HU. ROC curve analysis determined an optimal threshold of 90 HU (sensitivity = 86.9%, specificity = 83.9%), with a corresponding AUC of 0.895. The odds ratio of having a moderate or severe vertebral compression fracture was 31.9 for L1 attenuation ≤ 90 HU (95% CI, 20.2-50.5; p0.001).Patients with moderate or severe vertebral compression fractures have significantly lower L1 attenuation values than patients who do not. L1 attenuation ≤ 90 HU may represent an optimal threshold for determining risk for osteoporotic vertebral fractures.

To determine if identifiable hepatic textural features are present at abdominal CT in patients with colorectal cancer (CRC) prior to the development of CT-detectable hepatic metastases. Four filtration–histogram texture features (standard deviation, skewness, entropy and kurtosis) were extracted from the liver parenchyma on portal venous phase CT images at staging and post-treatment surveillance. Surveillance scans corresponded to the last scan prior to the development of CT-detectable CRC liver metastases in 29 patients (median time interval, 6 months), and these were compared with interval-matched surveillance scans in 60 CRC patients who did not develop liver metastases. Predictive models of liver metastasis-free survival and overall survival were built using regularised Cox proportional hazards regression. Texture features did not significantly differ between cases and controls. For Cox models using all features as predictors, all coefficients were shrunk to zero, suggesting no association between any CT texture features and outcomes. Prognostic indices derived from entropy features at surveillance CT incorrectly classified patients into risk groups for future liver metastases (p < 0.001). On surveillance CT scans immediately prior to the development of CRC liver metastases, we found no evidence suggesting that changes in identifiable hepatic texture features were predictive of their development. • No correlation between liver texture features and metastasis-free survival was observed. • Liver texture features incorrectly classified patients into risk groups for liver metastases. • Standardised texture analysis workflows need to be developed to improve research reproducibility.

The small, annual grass (L.) Beauv., a close relative of wheat ( L.) and barley ( L.), is a powerful model system for cereals and bioenergy grasses. Genome-wide association studies (GWAS) of natural variation can elucidate the genetic basis of complex traits but have been so far limited in by the lack of large numbers of well-characterized and sufficiently diverse accessions. Here, we report on genotyping-by-sequencing (GBS) of 84 , seven , and three accessions with diverse geographic origins including Albania, Armenia, Georgia, Italy, Spain, and Turkey. Over 90,000 high-quality single-nucleotide polymorphisms (SNPs) distributed across the Bd21 reference genome were identified. Our results confirm the hybrid nature of the genome, which appears as a mosaic of -like and -like sequences. Analysis of more than 50,000 SNPs for the accessions revealed three distinct, genetically defined populations. Surprisingly, these genomic profiles are associated with differences in flowering time rather than with broad geographic origin. High levels of differentiation in loci associated with floral development support the differences in flowering phenology between populations. Genome-wide association studies combining genotypic and phenotypic data also suggest the presence of one or more photoperiodism, circadian clock, and vernalization genes in loci associated with flowering time variation within populations. Our characterization elucidates genes underlying population differences, expands the germplasm resources available for , and illustrates the feasibility and limitations of GWAS in this model grass.

The small, annual grass Brachypodium distachyon (L.) Beauv., a close relative of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), is a powerful model system for cereals and bioenergy grasses. Genome-wide association studies (GWAS) of natural variation can elucidate the genetic basis of complex traits but have been so far limited in B. distachyon by the lack of large numbers of well-characterized and sufficiently diverse accessions. Here, we report on genotyping-by-sequencing (GBS) of 84 B. distachyon, seven B. hybridum, and three B. stacei accessions with diverse geographic origins including Albania, Armenia, Georgia, Italy, Spain, and Turkey. Over 90,000 high-quality single-nucleotide polymorphisms (SNPs) distributed across the Bd21 reference genome were identified. Our results confirm the hybrid nature of the B. hybridum genome, which appears as a mosaic of B. distachyon-like and B. stacei-like sequences. Analysis of more than 50,000 SNPs for the B. distachyon accessions revealed three distinct, genetically defined populations. Surprisingly, these genomic profiles are associated with differences in flowering time rather than with broad geographic origin. High levels of differentiation in loci associated with floral development support the differences in flowering phenology between B. distachyon populations. Genome-wide association studies combining genotypic and phenotypic data also suggest the presence of one or more photoperiodism, circadian clock, and vernalization genes in loci associated with flowering time variation within B. distachyon populations. Our characterization elucidates genes underlying population differences, expands the germplasm resources available for Brachypodium, and illustrates the feasibility and limitations of GWAS in this model grass.

OBJECTIVE: To investigate a fully automated CT-based adiposity tool, applying it to a longitudinal adult screening cohort. METHODS: A validated automated adipose tissue segmentation algorithm was applied to non-contrast abdominal CT scans in 8852 consecutive asymptomatic adults (mean age, 57.1 years; 3926 M/4926 F) undergoing colonography screening. The tool was also applied to follow-up CT scans in a subset of 1584 individuals undergoing longitudinal surveillance (mean interval, 5.6 years). Visceral and subcutaneous adipose tissue (VAT and SAT) volumes were segmented at levels T12-L5. Primary adipose results are reported herein for the L1 level as mean cross-sectional area. CT-based adipose measurements at initial CT and change over time were analyzed. RESULTS: Mean VAT values were significantly higher in males (205.8 ± 107.5 vs 108.1 ± 82.4 cm(2); p < 0.001), whereas mean SAT values were significantly higher in females (171.3 ± 111.3 vs 124.3 ± 79.7 cm(2); p < 0.001). The VAT/SAT ratio at L1 was three times higher in males (1.8 ± 0.7 vs 0.6 ± 0.4; p < 0.001). At longitudinal follow-up CT, mean VAT/SAT ratio change was positive in males, but negative in females. Among the 502 individuals where the VAT/SAT ratio increased at follow-up CT, 333 (66.3%) were males. Half of patients (49.6%; 786/1585) showed an interval increase in both VAT and SAT at follow-up CT. CONCLUSION: This robust, fully automated CT adiposity tool allows for both individualized and population-based assessment of visceral and subcutaneous abdominal fat. Such data could be automatically derived at abdominal CT regardless of the study indication, potentially allowing for opportunistic cardiovascular risk stratification. ADVANCES IN KNOWLEDGE: The CT-based adiposity tool described herein allows for fully automated measurement of visceral and subcutaneous abdominal fat, which can be used for assessing cardiovascular risk, metabolic syndrome, and for change over time.

Background Cholinergic neurons have been identified with the acetylcholine synthetic enzyme choline acetyltransferase (ChAT). However, ChAT is difficult to localize in newly differentiated peripheral neurons making the study of cholinergic neuronal development problematic. Consequently, researchers have used mouse reporter lines to indicate the presence of ChAT. Methods Our objective was to determine which ChAT reporter line was the most sensitive indicator of ChAT expression. We utilized two different fluorescent ChAT reporter lines (ChAT-GFP and ChAT-Cre;R26R:floxSTOP:tdTomato) together with immunolocalization of ChAT protein (ChAT-IR) to characterize the spatial and temporal expression of ChAT in myenteric neurons throughout enteric nervous system (ENS) development. Key Results ChAT-IR cells were first seen in the intestine at E10.5, even within the migration wavefront of neural precursors. Myenteric neurons within the distal small intestine (dSI) and proximal colon were first labeled by ChAT-IR, then ChAT-GFP, and finally ChAT-Cre tdTomato. The percentage of ChAT-IR neurons is equivalent to adult levels in the dSI by E13.5 and proximal colon by P0. After these stages, the percentages remained relatively constant throughout development despite dramatic changes in neuronal density. Conclusions & Inferences These observations indicate that neurotransmitter expression occurs early and there is only a brief gap between neurogenesis and neurotransmitter expression. Our finding that the proportion of ChAT myenteric neurons reached adult levels during embryonic development suggests that the fate of cholinergic neurons is tightly regulated and that their differentiation might influence further neuronal development. ChAT-GFP is a more accurate indicator of early ENS cholinergic neuronal differentiation than the ChAT-Cre;R26R:floxSTOP:tdTomato reporter mouse.

Lignocellulosic biomass is a source of low cost polysaccharides that some microbes can deconstruct and convert into liquid transportation fuel. Feedstocks vary in their ease of use depending on their source and handing. Estimating conversion amenability is useful to determine the effects of biomass pretreatment and genetic potential for the purposes of energy crop breeding and genetics. Here we describe a small-scale high-throughput assay that measures ethanol production from a culture of plant biomass and the ethanologen Clostridium phytofermentans.

Lignocellulosic biomass is a source of low cost polysaccharides that some microbes can deconstruct and convert into liquid transportation fuel. Feedstocks vary in their ease of use depending on their source and handing. Estimating conversion amenability is useful to determine the effects of biomass pretreatment and genetic potential for the purposes of energy crop breeding and genetics. Here we describe a small-scale high-throughput assay that measures ethanol production from a culture of plant biomass and the ethanologen Clostridium phytofermentans.

Background There is currently considerable interest in developing renewable sources of energy. One strategy is the biological conversion of plant biomass to liquid transportation fuel. Several technical hurdles impinge upon the economic feasibility of this strategy, including the development of energy crops amenable to facile deconstruction. Reliable assays to characterize feedstock quality are needed to measure the effects of pre-treatment and processing and of the plant and microbial genetic diversity that influence bioconversion efficiency. Results We used the anaerobic bacterium Clostridium phytofermentans to develop a robust assay for biomass digestibility and conversion to biofuels. The assay utilizes the ability of the microbe to convert biomass directly into ethanol with little or no pre-treatment. Plant samples were added to an anaerobic minimal medium and inoculated with C. phytofermentans, incubated for 3 days, after which the culture supernatant was analyzed for ethanol concentration. The assay detected significant differences in the supernatant ethanol from wild-type sorghum compared with brown midrib sorghum mutants previously shown to be highly digestible. Compositional analysis of the biomass before and after inoculation suggested that differences in xylan metabolism were partly responsible for the differences in ethanol yields. Additionally, we characterized the natural genetic variation for conversion efficiency in Brachypodium distachyon and shrub willow (Salix spp.). Conclusion Our results agree with those from previous studies of lignin mutants using enzymatic saccharification-based approaches. However, the use of C. phytofermentans takes into consideration specific organismal interactions, which will be crucial for simultaneous saccharification fermentation or consolidated bioprocessing. The ability to detect such phenotypic variation facilitates the genetic analysis of mechanisms underlying plant feedstock quality.

Opportunistic osteoporosis screening using abdominal CT scans obtained for other purposes has the potential to increase detection of those at increased risk for fragility fractures. We sought to combine the tasks of density measurement and vertebral fracture assessment on the sagittal view. We confirm that this represents a robust approach and recommend its implementation in clinical practice. Opportunistic osteoporosis screening at routine abdominal CT has been proposed by measuring axial (transverse) L1 trabecular attenuation and by sagittal reconstruction for vertebral fracture assessment. We sought to combine this dual evaluation on the sagittal reconstruction alone to improve efficiency. Routine contrast-enhanced abdominal CT scans performed for any indication on 571 consecutive adults age 60 years or older (mean age 70.7 years) were retrospectively analyzed. These were performed at a single center over a 3-month period. L1 trabecular attenuation was measured using an ovoid region-of-interest on both the transverse and sagittal series. The sagittal reconstruction was also analyzed for moderate-to-severe vertebral compression fractures using the Genant visual semi-quantitative method. Likely osteoporosis was defined by a moderate-to-severe fracture and/or sagittal L1 trabecular attenuation of ≤110 Hounsfield units (HU) (previously found to be >90 % specific for osteoporosis on our calibrated GE CT scanners at 120 kVp). Correlation was made with hip and spine dual X-ray absorptiometry (DXA). Mean absolute difference in L1 trabecular attenuation between transverse and sagittal reconstructions was 6.7 HU (±5.7) or 6.2 %. The transverse and sagittal HU measurements were in agreement (i.e., both measurements above or below this threshold) in 94.5 % of cases at the 110-HU cutoff. A total of 243 (42.3 %) patients had likely osteoporosis by CT criteria, of which only 48 (19.8 %) had previous DXA screening. Assessment of the sagittal view alone at routine abdominal CT for both vertebral fractures and trabecular bone mineral density provides a rapid and effective opportunistic screen for detecting individuals at increased risk for fragility fractures.

Background Lignin is a significant barrier in the conversion of plant biomass to bioethanol. Cinnamyl alcohol dehydrogenase (CAD) and caffeic acid O-methyltransferase (COMT) catalyze key steps in the pathway of lignin monomer biosynthesis. Brown midrib mutants in Zea mays and Sorghum bicolor with impaired CAD or COMT activity have attracted considerable agronomic interest for their altered lignin composition and improved digestibility. Here, we identified and functionally characterized candidate genes encoding CAD and COMT enzymes in the grass model species Brachypodium distachyon with the aim of improving crops for efficient biofuel production. Results We developed transgenic plants overexpressing artificial microRNA designed to silence BdCAD1 or BdCOMT4. Both transgenes caused altered flowering time and increased stem count and weight. Downregulation of BdCAD1 caused a leaf brown midrib phenotype, the first time this phenotype has been observed in a C3 plant. While acetyl bromide soluble lignin measurements were equivalent in BdCAD1 downregulated and control plants, histochemical staining and thioacidolysis indicated a decrease in lignin syringyl units and reduced syringyl/guaiacyl ratio in the transgenic plants. BdCOMT4 downregulated plants exhibited a reduction in total lignin content and decreased Maule staining of syringyl units in stem. Ethanol yield by microbial fermentation was enhanced in amiR-cad1-8 plants. Conclusion These results have elucidated two key genes in the lignin biosynthetic pathway in B. distachyon that, when perturbed, may result in greater stem biomass yield and bioconversion efficiency.