Removing grass clippings reduces bermudagrass mite (Acari: Eriophyidae) infestation during turfgrass regrowth.

Bermudagrass mite (Aceria cynodoniensis Sayed) infestation stunts bermudagrass (Cynodon spp. [Poales: Poaceae]) growth, leading to thinned turf and lower aesthetic and recreational value. Bermudagrass mites cause characteristic symptoms called witch's brooms, including shortened internodes and leaves and the proliferation of tillers. Grass clippings produced by mowing or scalping bermudagrass harbor mites, which abandon the desiccating grass clippings and spread to surrounding turfgrass. Dropped grass clippings can lead to infestation of new turfgrass. Nursery experiments were conducted with potted bermudagrass to determine the effect of removing witch's brooms or grass clippings after scalping on witch's broom densities on the recovering bermudagrass. Additionally, laboratory experiments were conducted to assess the potential for mites to abandon detached witch's brooms and to evaluate mite survival after leaving their hosts. The number of initial witch's brooms and individually removing witch's brooms did not affect subsequent witch's broom densities, suggesting that infested but asymptomatic terminals later developed into witch's brooms. Removing grass clippings after scalping reduced witch's broom densities by over 65% in two trials. Most mites (96%) abandoned witch's brooms within 48 h after detaching witch's brooms, and adult mites survived an average of 5.6 h after removal from the host plant. Removing clippings after scalping may improve bermudagrass mite management and limit damage on the recovering turfgrass. Additionally, clippings resulting from regular mowing or scalping should be disposed of properly because this study demonstrates that mites abandon desiccating host plants and survive sufficiently long to infest surrounding turfgrass.

Translating AI to Clinical Practice: Overcoming Data Shift with Explainability.

To translate artificial intelligence (AI) algorithms into clinical practice requires generalizability of models to real-world data. One of the main obstacles to generalizability is data shift, a data distribution mismatch between model training and real environments. Explainable AI techniques offer tools to detect and mitigate the data shift problem and develop reliable AI for clinical practice. Most medical AI is trained with datasets gathered from limited environments, such as restricted disease populations and center-dependent acquisition conditions. The data shift that commonly exists in the limited training set often causes a significant performance decrease in the deployment environment. To develop a medical application, it is important to detect potential data shift and its impact on clinical translation. During AI training stages, from premodel analysis to in-model and post hoc explanations, explainability can play a key role in detecting model susceptibility to data shift, which is otherwise hidden because the test data have the same biased distribution as the training data. Performance-based model assessments cannot effectively distinguish the model overfitting to training data bias without enriched test sets from external environments. In the absence of such external data, explainability techniques can aid in translating AI to clinical practice as a tool to detect and mitigate potential failures due to data shift. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Effect of indacaterol/glycopyrronium on ventilation and perfusion in COPD: a randomized trial.

RATIONALE: The long-acting ß2-agonist/long-acting muscarinic antagonist combination indacaterol/glycopyrronium (IND/GLY) elicits bronchodilation, improves symptoms, and reduces exacerbations in COPD. Magnetic resonance imaging (MRI) of the lung with hyperpolarized gas and gadolinium contrast enhancement enables assessment of whole lung functional responses to IND/GLY. OBJECTIVES: The primary objective was assessment of effect of IND/GLY on global ventilated lung volume (%VV) versus placebo in COPD. Lung function, regional ventilation and perfusion in response to IND/GLY were also measured. METHODS: This double-blind, randomized, placebo-controlled, crossover study assessed %VV and pulmonary perfusion in patients with moderate-to-severe COPD after 8 days of once-daily IND/GLY treatment (110/50 µg) followed by 8 days of placebo, or vice versa, using inhaled hyperpolarized 3He gas and gadolinium contrast-enhanced MRI, respectively. Lung function measures including spirometry were performed for each treatment after 8 days. MEASUREMENTS AND MAIN RESULTS: Of 31 patients randomized, 29 completed both treatment periods. IND/GLY increased global %VV versus placebo (61.73% vs. 56.73%, respectively, least squares means treatment difference: 5.00% [90% CI 1.40 to 8.60]; P = 0.025). IND/GLY improved whole lung index of ventilation volume to perfusion volume (V/Q) ratio versus placebo; 94% (90% CI 83 to 105) versus 86% (90% CI 75 to 97; P = 0.047), respectively. IND/GLY showed a trend to improve diffusing capacity for carbon monoxide (DLCO) (+ 0.66 mL/min/mmHg; P = 0.082). By Day 8, forced expiratory volume in 1 s (FEV1) was increased by 0.32 L versus placebo (90% CI 0.26 to 0.38; P < 0.0001), substantiating earlier findings and providing evidence of assay sensitivity for this trial. CONCLUSIONS: IND/GLY improved lung ventilation assessed by 3He MRI after 1 week of treatment. This observation may provide mechanistic support for the symptomatic clinical benefit shown with IND/GLY in COPD. Clinical trial registered with www.clinicaltrials.gov (NCT02634983).

Prediction of idiopathic pulmonary fibrosis progression using early quantitative changes on CT imaging for a short term of clinical 18-24-month follow-ups.

OBJECTIVE: High-resolution computed tomography (HRCT) plays an indispensable role in the diagnosis of idiopathic pulmonary fibrosis (IPF). Due to unpredictability in progression and the short median survival of 2-5 years, it is critical to delineate the patients with rapid progression. The aim is to evaluate the predictability of IPF progression using the early quantitative changes. METHODS: Automated texture-based quantitative lung fibrosis (QLF) was calculated from the anonymized HRCT. Two datasets were collected retrospectively: (1) a pilot study of 35 subjects with three sequential scans (baseline and 6 and 12 months) to obtain a threshold, where visual assessments were stable at 6 months but worsened at 12 months; (2) 157 independent subjects to test the threshold. Landmark Cox regressions were used to compare the progression-free survival (PFS) defined by pulmonary function using the threshold from the early changes in QLF. C-indexes were reported as estimations of the concordance of prediction. RESULTS: A threshold of 4% QLF change at 6 months corresponded to the mean change that worsened on HRCT visually at 12 months from the pilot study. Using the threshold, significant differences were found in the independent dataset (hazard ratio (HZ) = 5.92, p = 0.001 by Cox model, C-index = 0.71 at the most severe lobe; and HZ = 3.22, p = 0.012, C-index = 0.68 in the whole lung). Median PFS was 11.9 months for subjects with ≥ 4% changes, whereas median PFS was greater than 18 months for subjects with < 4% changes at the most severe lobe. CONCLUSION: Early structural changes on HRCT using a quantitative score can predict progression in lung function. KEY POINTS: • Changes on HRCT using quantitative texture-based scores can play a pivotal role for providing information and an aid tool for timely management decision for patients with IPF. • Quantitative changes on HRCT of 4% or more, which matched 6-month prior changes with visual assessment of worsening, can play a pivotal role for providing prediction of clinical progression by 3-5 folds higher in the next incidence, compared with those of subjects with less than 4% changes. • Early structural changes of 4% or more in a paired HRCT scans derived by quantitative scores can predict the progression in lung function in 1-2 years in subjects with IPF, which is critical information for timely management decision for subjects with IPF where the median survival is 2 to 5 years.

Correction to: Toward clinically usable CAD for lung cancer screening with computed tomography.

The original version of this article, published on 24 July 2014, unfortunately contained a mistake. In section "Discussion," a sentence was worded incorrectly.

Comparative Performance of Fungicides, Biofungicides, and Host Plant Defense Inducers in Suppression of Phytophthora Root Rot in Flowering Dogwood During Simulated Root Flooding Events.

During flooding events in nurseries, Phytophthora root rot caused by Phytophthora cinnamomi Rands often causes damage that leads to complete crop loss. In this study, we evaluated the efficacy of fungicides, biofungicides, and host plant defense inducers for preventive and curative control of Phytophthora root rot on flowering dogwood (Cornus florida L.) seedlings exposed to a simulated flood event of 1, 3, or 7 days. In two greenhouse trials, preventive (7 days before flooding) or curative (1 day after flooding) drench treatments were applied to dogwood seedlings artificially inoculated with P. cinnamomi. The plants were flooded by maintaining standing water for 1, 3, or 7 days. After the trials, plant growth data (total plant weight, root weight, plant height, and plant width) were recorded, and root systems were assessed for disease severity using a scale of 0 to 100% of roots affected, and subsamples were plated on PARPH-V8 medium to determine the percent recovery of the Phytophthora pathogen. Plants preventively treated with Subdue MAXX had reduced disease severity relative to the nontreated, inoculated plants (positive control) flooded 1, 3, or 7 days in both trials. Pageant Intrinsic and Segovis treatments also had lower disease severity than the positive control at all flooding durations in trial two, but not trial one. In trial one, preventive and curative treatments of Orkestra Intrinsic had reduced disease severity compared with the positive control at 1 and 3 days of flooding, whereas curative treatments of Empress Intrinsic and Tartan Stressgard also were effective at 1 and 3 days of flooding in trial one. The host plant defense inducers (Aliette 80 WDG, Signature Xtra, and Actigard) were inconsistent and ineffective at reducing disease severity when applied as preventive or curative treatments. Preventive treatments of the biofungicides RootShield Plus+ and MBI-110 had consistently lower disease severity than the positive control at 1 day of flooding but not 3 or 7 days of flooding. Potentially, growers can use information from this study to manage Phytophthora root rot during flooding or in areas of the nursery that often experience high soil moisture levels.

Unusual Presentation of Infantile Myofibroma in the Deep Palm of a Child: A Case Report and Discussion of the Differential Diagnosis.

Infantile myofibroma or myofibromatosis is a myofibroblastic and fibroblastic proliferation that is most commonly reported in children younger than 2 years of age. It is a benign process composed histologically of a biphasic pattern of spindle-shaped cells surrounding a zone of less differentiated cells in a hemangiopericytoma-like pattern. We report this tumor in a unique presentation in the deep palm of a 2-year-old child without skin ulceration and with an intimate association with the median nerve. The well-circumscribed nature of the tumor facilitated complete excision with neural preservation. Final pathology was consistent with an unusual type of myofibroma or myofibromatosis. Conservative management with partial excision has been advocated for these masses because of potential surgical morbidity and its benign nature. This case report highlights the differential diagnosis of uncommon soft tissue tumors in the pediatric hand as well as the importance of a surgeon's surgical assessment in guiding treatment.

Transitions to different patterns of interstitial lung disease in scleroderma with and without treatment.

OBJECTIVES: The aim is to investigate whether the 12-month quantitative changes in high-resolution CT (HRCT) measures of interstitial lung disease (ILD) are different, and to understand how they change, in patients with scleroderma-related ILD who receive drug therapy versus placebo. METHODS: HRCT images were acquired at baseline and at 12 months in 83 participants in Scleroderma Lung Study I, a clinical trial comparing treatment with oral cyclophosphamide versus placebo. A computer-aided model was used to quantify the extent of fibrotic reticulation, ground glass and honeycomb patterns and quantitative ILD (QILD: sum of these patterns) in the whole lung and the lung zone (upper, middle or lower) of maximal disease involvement. RESULTS: Mean QILD score decreased by 3.9% in the cyclophosphamide group while increasing by 4.2% in the placebo group in the most severe zone (p=0.01) and decreased by 3.2% in the cyclophosphamide group while increasing by 2.2% in the placebo group in the whole lung (p=0.03). Transitional probabilities demonstrated greater changes from a fibrotic to either a ground glass or normal pattern in the cyclophosphamide group and the reverse in the placebo group. CONCLUSIONS: Changes in quantitative HRCT measures of ILD provide a sensitive indication of disease progression and response to treatment. TRIAL REGISTRATION NUMBER: NCT00004563; Post-results.

45 Years of Simultaneous Le Fort III and Le Fort I Osteotomies: A Systematic Literature Review.

OBJECTIVE: To review and collectively summarize our knowledge of simultaneous Le Fort III and Le Fort I osteotomies. DESIGN: A PubMed search using "Le Fort III," "simultaneous Le Fort III and Le Fort I," "combined Le Fort III and Le Fort I," "dual midface," and "segmental midface" was performed. Articles with relevant abstracts were obtained for formal review. A new case of simultaneous Le Fort III and Le Fort I is presented to describe and discuss specific operative indications and surgical decisions. RESULTS: There were 14 articles that met inclusion criteria with reports of simultaneous Le Fort III and Le Fort I osteotomies. A total of 20 cases were present in the literature. No major complications were reported. We performed combined Le Fort III with Le Fort I osteotomies in a 25-year-old patient with Crouzon syndrome who had undergone a previous Le Fort III at the age of 4 years. The patient tolerated the procedure well, and postoperatively, her exophthalmos and class III malocclusion were corrected. CONCLUSIONS: Simultaneous Le Fort III and Le Fort I can correct differential upper and lower midface hypoplasia and is a well-tolerated procedure in the mature facial skeleton. This systematic review improves our understanding of the surgical technique and indications for a procedure that can correct complex midfacial deformities.

Environmental factors that contribute to upper eyelid ptosis: a study of identical twins.

BACKGROUND: Current literature provides little information about the impact of environmental exposures on the severity of acquired blepharoptosis. OBJECTIVE: The authors assessed environmental factors that may contribute to eyelid ptosis in a population of identical twins. METHODS: Photographs of 286 sets of twins from a prospectively collected database from 2008 to 2010 were reviewed. The authors identified 96 sets of identical twins (192 individual persons) who had differing severity of ptosis. Digital photographs were analyzed, and the degree of ptosis was measured in each eye of every subject. The external factors that could potentially contribute to blepharoptosis were taken into consideration. The authors then assessed the correlations of 9 different environmental risk factors with ptosis. Generalized linear mixed model were constructed to determine the associations of ptosis measurements with environmental risk factors obtained from the subject survey database. RESULTS: The mean level of upper eyelid ptosis in the study population was 1.1 mm. The mean difference in ptosis between twins was 0.5 mm. Wearing contact lenses, either hard or soft, was significantly associated with ptosis. The mean ptosis measurement among twins who did not wear contact lenses was 1.0 mm; for those who wore soft contact lenses, the mean was 1.41 mm, and for those who wore hard contact lenses, the mean was 1.84 mm. CONCLUSIONS: Acquired ptosis is not linked to body mass index, smoking behavior, sun exposure, alcohol use, work stress, or sleep. Wearing either hard or soft lenses was associated with an increased risk of ptosis. These influences are independent of genetic predisposition. LEVEL OF EVIDENCE: 3 Diagnostic.

Three-Dimensional Changes in the Midface Following Malar Calcium Hydroxyapatite Injection in a Cadaver Model.

BACKGROUND: Three-dimensional (3D) changes in the midface following malar calcium hydroxyapatite (CaHa) injection have not been systematically analyzed. OBJECTIVES: The authors analyzed 3D volume changes in midface and naso-labial fold (NLF) volume, as well as lateral movement in the NLF/naso-labial crease (NLC) junction following malar injection of CaHa in a cadaver model. METHODS: A single surgeon injected CaHa in the supraperiosteal plane. Sequential images were obtained with the VECTRA 3D system pre- and post-1.5- and 3-cc CaHa injections. All measurements were performed by a single examiner. Injection location was verified anatomically. RESULTS: Injections were performed in 16 fresh cadaver hemi-faces. Maximal increases in projection were centered on the malar injection site, with associated decreases in projection and volume in the infero-medial locations. Relative mean increases in volume of 3.16 cc and 4.94 cc were observed following the 1.5-cc and 3-cc injections, respectively. There was a relative decrease in the volume of the NLF of -0.3 cc and -0.4 cc following the 1.5- and 3-cc injections, respectively. Injection of CaHa was associated with lateral movements of the NLF-NLC junction at the level of the nasal sill, philtral columns, and oral commissure, measuring 2.7, 2.5, and 1.9 mm and 2.8, 2.9, and 2.4 mm following the 1.5- and 3-cc injections, respectively. Anatomical dissection verified the location in the supraperiosteal space and within the middle malar fat pad. CONCLUSIONS: Following malar CaHa injection, 3D photographic analysis showed a measureable lifting effect with recruitment of ptotic tissue and lateral movement of the NLF-NLC junction in a cadaver model.

Intra- and interscan reproducibility using Fourier Analysis of STimulated Echoes (FAST) for the rapid and robust quantification of left ventricular twist.

PURPOSE: To assess the intra- and interscan reproducibility of LV twist using FAST. Assessing the reproducibility of the measurement of new MRI biomarkers is an important part of validation. Fourier Analysis of STimulated Echoes (FAST) is a new MRI tissue tagging method that has recently been shown to compare favorably with conventional estimates of left ventricular (LV) twist from cardiac tagged images, but with significantly reduced user interaction time. MATERIALS AND METHODS: Healthy volunteers (N = 10) were scanned twice using FAST over 1 week. On day 1, two measurements of LV twist were collected for intrascan comparisons. Measurements for LV twist were again collected on day 8 for interscan assessment. LV short-axis tagged images were acquired on a 3 Tesla (T) scanner to ensure detectability of tags during early and mid-diastole. Peak LV twist is reported as mean ± SD. Reproducibility was assessed using the concordance correlation coefficient (CCC) and the repeatability coefficient (RC) (95% confidence interval [CI] range). RESULTS: Mean peak twist measurements were 13.4 ± 4.3° (day 1, scan 1), 13.6 ± 3.7° (day 1, scan 2), and 13.0 ± 2.7° (day 8). Bland-Altman analysis resulted in intra- and interscan bias and 95% CI of -0.6° [-1.0°, 1.6°] and 1.4° (-1.0°, 3.0°), respectively. The Bland-Altman RC for peak LV twist was 2.6° and 4.0° for intra- and interscan, respectively. The CCC was 0.9 and 0.6 for peak LV twist for intra- and interscan, respectively. CONCLUSION: FAST is a semi-automated method that provides a quick and quantitative assessment of LV systolic and diastolic twist that demonstrates high intrascan and moderate interscan reproducibility in preliminary studies.

Toward clinically usable CAD for lung cancer screening with computed tomography.

OBJECTIVES: The purpose of this study was to define clinically appropriate, computer-aided lung nodule detection (CAD) requirements and protocols based on recent screening trials. In the following paper, we describe a CAD evaluation methodology based on a publically available, annotated computed tomography (CT) image data set, and demonstrate the evaluation of a new CAD system with the functionality and performance required for adoption in clinical practice. METHODS: A new automated lung nodule detection and measurement system was developed that incorporates intensity thresholding, a Euclidean Distance Transformation, and segmentation based on watersheds. System performance was evaluated against the Lung Imaging Database Consortium (LIDC) CT reference data set. RESULTS: The test set comprised thin-section CT scans from 108 LIDC subjects. The median (±IQR) sensitivity per subject was 100 (±37.5) for nodules ≥ 4 mm and 100 (±8.33) for nodules ≥ 8 mm. The corresponding false positive rates were 0 (±2.0) and 0 (±1.0), respectively. The concordance correlation coefficient between the CAD nodule diameter and the LIDC reference was 0.91, and for volume it was 0.90. CONCLUSIONS: The new CAD system shows high nodule sensitivity with a low false positive rate. Automated volume measurements have strong agreement with the reference standard. Thus, it provides comprehensive, clinically-usable lung nodule detection and assessment functionality. KEY POINTS: • CAD requirements can be based on lung cancer screening trial results. • CAD systems can be evaluated using publically available annotated CT image databases. • A new CAD system was developed with a low false positive rate. • The CAD system has reliable measurement tools needed for clinical use.

Diagnostic performance comparison of the Chartis System and high-resolution computerized tomography fissure analysis for planning endoscopic lung volume reduction.

BACKGROUND AND OBJECTIVE: Endobronchial valve (EBV) therapy is optimized in patients who demonstrate little or no collateral ventilation (CV). The accuracy of the Chartis System and visual assessment of high-resolution computerized tomography (HRCT) fissure completeness by a core radiology laboratory for classifying CV status was compared by evaluating the relationship of each method with target lobe volume reduction (TLVR) after EBV placement. METHODS: Retrospective HRCT fissure analysis of a study population who underwent catheter-based measurement of CV followed by complete occlusion of the targeted lobe by EBV. Accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the HRCT fissure analysis and the catheter-based measurement of CV for predicting TLVR was determined. RESULTS: Accuracy for correctly classifying TLVR with EBV was similar for Chartis System and HRCT fissure analysis (74 vs 77%). The sensitivity and specificity of the Chartis measurement were 86% and 61% and those of HRCT fissure analysis 75% and 79%. Patients with TLVR ≥ 350 mL had statistically significant improvement in respiratory function, exercise performance and quality of life measures. CONCLUSIONS: When evaluating patients for likelihood of successful EBV therapy, the Chartis System CV assessment and HRCT fissure analysis appear to have comparable accuracy. Both techniques were found to be beneficial for EBV procedure planning.

Assessing variability in non-contrast CT for the evaluation of stroke: The effect of CT image reconstruction conditions on AI-based CAD measurements of ASPECTS value and hypodense volume.

Purpose: To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume. The purpose of this work was to investigate the effects of CT reconstruction kernel and slice thickness on ASPECTS and hypodense volume. Methods: The NCCT series image data of 87 patients imaged with a CT stroke protocol at our institution were reconstructed with 3 kernels (H10s-smooth, H40s-medium, H70h-sharp) and 2 slice thicknesses (1.5mm and 5mm) to create a reference condition (H40s/5mm) and 5 non-reference conditions. Each reconstruction for each patient was analyzed with the Brainomix e-Stroke software (Brainomix, Oxford, England) which yields an ASPECTS value and measure of total hypodense volume (mL). Results: An ASPECTS value was returned for 74 of 87 cases in the reference condition (13 failures). ASPECTS in non-reference conditions changed from that measured in the reference condition for 59 cases, 7 of which changed above or below the clinical threshold of 7 for 3 non-reference conditions. ANOVA tests were performed to compare the differences in protocols, Dunnett's post-hoc tests were performed after ANOVA, and a significance level of p < 0.05 was defined. There was no significant effect of kernel (p = 0.91), a significant effect of slice thickness (p < 0.01) and no significant interaction between these factors (p = 0.91). Post-hoc tests indicated no significant difference between ASPECTS estimated in the reference and any non-reference conditions. There was a significant effect of kernel (p < 0.01) and slice thickness (p < 0.01) on hypodense volume, however there was no significant interaction between these factors (p = 0.79). Post-hoc tests indicated significantly different hypodense volume measurements for H10s/1.5mm (p = 0.03), H40s/1.5mm (p < 0.01), H70h/5mm (p < 0.01). No significant difference was found in hypodense volume measured in the H10s/5mm condition (p = 0.96). Conclusion: Automated ASPECTS and hypodense volume measurements can be significantly impacted by reconstruction kernel and slice thickness.

Quantifying lung fissure integrity using a three-dimensional patch-based convolutional neural network on CT images for emphysema treatment planning.

Purpose: Evaluation of lung fissure integrity is required to determine whether emphysema patients have complete fissures and are candidates for endobronchial valve (EBV) therapy. We propose a deep learning (DL) approach to segment fissures using a three-dimensional patch-based convolutional neural network (CNN) and quantitatively assess fissure integrity on CT to evaluate it in subjects with severe emphysema. Approach: From an anonymized image database of patients with severe emphysema, 129 CT scans were used. Lung lobe segmentations were performed to identify lobar regions, and the boundaries among these regions were used to construct approximate interlobar regions of interest (ROIs). The interlobar ROIs were annotated by expert image analysts to identify voxels where the fissure was present and create a reference ROI that excluded non-fissure voxels (where the fissure is incomplete). A CNN configured by nnU-Net was trained using 86 CT scans and their corresponding reference ROIs to segment the ROIs of left oblique fissure (LOF), right oblique fissure (ROF), and right horizontal fissure (RHF). For an independent test set of 43 cases, fissure integrity was quantified by mapping the segmented fissure ROI along the interlobar ROI. A fissure integrity score (FIS) was then calculated as the percentage of labeled fissure voxels divided by total voxels in the interlobar ROI. Predicted FIS (p-FIS) was quantified from the CNN output, and statistical analyses were performed comparing p-FIS and reference FIS (r-FIS). Results: The absolute percent error mean (±SD) between r-FIS and p-FIS for the test set was 4.0% (±4.1%), 6.0% (±9.3%), and 12.2% (±12.5%) for the LOF, ROF, and RHF, respectively. Conclusions: A DL approach was developed to segment lung fissures on CT images and accurately quantify FIS. It has potential to assist in the identification of emphysema patients who would benefit from EBV treatment.

Quantitative Computed Tomography Lung COVID Scores with Laboratory Markers: Utilization to Predict Rapid Progression and Monitor Longitudinal Changes in Patients with Coronavirus 2019 (COVID-19) Pneumonia.

Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses: (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.

Bermudagrass mite (Acari: Eriophyidae) infestation worsens in response to increasing nitrogen fertility and decreasing irrigation volume but not mowing height.

Severe bermudagrass mite (Aceria cynodoniensis Sayed) infestation stunts turfgrass growth and reduces the aesthetic and recreational value of managed bermudagrass. Management practices, such as fertilization, mowing, and irrigation, may impact bermudagrass mite infestation and damage, but empirical evidence is lacking. Two 20 wk experiments were conducted with potted bermudagrass in a greenhouse or nursery to evaluate the effect of varying nitrogen rates (0, 24.5, or 49 kg N/ha), mowing heights (1.3, 2.5, 3.8, or 5 cm), and irrigation rates (60%, 100%, or 140% evapotranspiration [ET] rate) on the densities of witch's brooms (i.e., stunted and deformed terminals symptomatic of infestation) and bermudagrass mites. Increasing nitrogen fertility from 0 to 49 kg N/ha increased witch's broom and bermudagrass mite densities by 292% and 339%, respectively. Bermudagrass fertilized with nitrogen maintained higher turf quality than unfertilized grass despite greater mite damage. Decreasing irrigation from 140% to 60% of the ET rate also increased witch's broom densities by 124%. Mowing height did not consistently affect witch's broom or mite densities. Witch's broom and mite densities were positively correlated and followed a general trend with greater densities in April-August and a decline in densities in August-October. These findings suggest that nitrogen fertilization and water stress influence bermudagrass mite damage. Thus, limiting nitrogen fertilization to a level necessary to maintain turfgrass health and quality (0.5 kg N/ha) and minimizing turfgrass water stress can complement current chemical control strategies as part of an integrated pest management program.

SimpleMind: An open-source software environment that adds thinking to deep neural networks.

Deep neural networks (DNNs) detect patterns in data and have shown versatility and strong performance in many computer vision applications. However, DNNs alone are susceptible to obvious mistakes that violate simple, common sense concepts and are limited in their ability to use explicit knowledge to guide their search and decision making. While overall DNN performance metrics may be good, these obvious errors, coupled with a lack of explainability, have prevented widespread adoption for crucial tasks such as medical image analysis. The purpose of this paper is to introduce SimpleMind, an open-source software environment for Cognitive AI focused on medical image understanding. It allows creation of a knowledge base that describes expected characteristics and relationships between image objects in an intuitive human-readable form. The knowledge base can then be applied to an input image to recognize and understand its content. SimpleMind brings thinking to DNNs by: (1) providing methods for reasoning with the knowledge base about image content, such as spatial inferencing and conditional reasoning to check DNN outputs; (2) applying process knowledge, in the form of general-purpose software agents, that are dynamically chained together to accomplish image preprocessing, DNN prediction, and result post-processing, and (3) performing automatic co-optimization of all knowledge base parameters to adapt agents to specific problems. SimpleMind enables reasoning on multiple detected objects to ensure consistency, providing cross-checking between DNN outputs. This machine reasoning improves the reliability and trustworthiness of DNNs through an interpretable model and explainable decisions. Proof-of-principle example applications are provided that demonstrate how SimpleMind supports and improves deep neural networks by embedding them within a Cognitive AI environment.

Automated Endotracheal Tube Placement Check Using Semantically Embedded Deep Neural Networks.

RATIONALE AND OBJECTIVES: To develop artificial intelligence (AI) system that assists in checking endotracheal tube (ETT) placement on chest X-rays (CXRs) and evaluate whether it can move into clinical validation as a quality improvement tool. MATERIALS AND METHODS: A retrospective data set including 2000 de-identified images from intensive care unit patients was split into 1488 for training and 512 for testing. AI was developed to automatically identify the ETT, trachea, and carina using semantically embedded neural networks that combine a declarative knowledge base with deep neural networks. To check the ETT tip placement, a "safe zone" was computed as the region inside the trachea and 3-7 cm above the carina. Two AI outputs were evaluated: (1) ETT overlay, (2) ETT misplacement alert messages. Clinically relevant performance metrics were compared against prespecified thresholds of >85% overlay accuracy and positive predictive value (PPV) > 30% and negative predictive value NPV > 95% for alerts to move into clinical validation. RESULTS: An ETT was present in 285 of 512 test cases. The AI detected 95% (271/285) of ETTs, 233 (86%) of these with accurate tip localization. The system (correctly) did not generate an ETT overlay in 221/227 CXRs where the tube was absent for an overall overlay accuracy of 89% (454/512). The alert messages indicating that either the ETT was misplaced or not detected had a PPV of 83% (265/320) and NPV of 98% (188/192). CONCLUSION: The chest X-ray AI met prespecified performance thresholds to move into clinical validation.