AI Lung Segmentation and Perfusion Analysis of Dual-Energy CT Can Help to Distinguish COVID-19 Infiltrates from Visually Similar Immunotherapy-Related Pneumonitis Findings and Can Optimize Radiological Workflows

(1) To explore the potential impact of an AI dual-energy CT (DECT) prototype on decision making and workflows by investigating its capabilities to differentiate COVID-19 from immunotherapy-related pneumonitis. (2) Methods: From 3 April 2020 to 12 February 2021, DECT from biometrically matching patients with COVID-19, pneumonitis, and inconspicuous findings were selected from our clinical routine. Three blinded readers independently scored each pulmonary lobe analogous to CO-RADS. Inter-rater agreement was determined with an intraclass correlation coefficient (ICC). Averaged perfusion metrics per lobe (iodine uptake in mg, volume without vessels in ml, iodine concentration in mg/mL) were extracted using manual segmentation and an AI DECT prototype. A generalized linear mixed model was used to investigate metric validity and potential distinctions at equal CO-RADS scores. Multinomial regression measured the contribution “Reader”, “CO-RADS score”, and “perfusion metrics” to diagnosis. The time to diagnosis was measured for manual vs. AI segmentation. (3) Results: We included 105 patients (62 ± 13 years, mean BMI 27 ± 2). There were no significant differences between manually and AI-extracted perfusion metrics (p = 0.999). Regardless of the CO-RADS score, iodine uptake and concentration per lobe were significantly higher in COVID-19 than in pneumonitis (p < 0.001). In regression, iodine uptake had a greater contribution to diagnosis than CO-RADS scoring (Odds Ratio (OR) = 1.82 [95%CI 1.10–2.99] vs. OR = 0.20 [95%CI 0.14–0.29]). The AI prototype extracted the relevant perfusion metrics significantly faster than radiologists (10 ± 1 vs. 15 ± 2 min, p < 0.001). (4) Conclusions: The investigated AI prototype positively impacts decision making and workflows by extracting perfusion metrics that differentiate COVID-19 from visually similar pneumonitis significantly faster than radiologists.

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Gouty arthritis: decision-making following dual-energy CT scan in clinical practice, a retrospective analysis

Clinical Rheumatology ◽

10.1007/s10067-018-3980-y ◽

2018 ◽

Vol 37 (7) ◽

pp. 1879-1884 ◽

Cited By ~ 3

Author(s):

M. Gamala ◽

S. P. Linn-Rasker ◽

M. Nix ◽

B. G. F. Heggelman ◽

J. M. van Laar ◽

...

Keyword(s):

Decision Making ◽

Clinical Practice ◽

Ct Scan ◽

Retrospective Analysis ◽

Gouty Arthritis ◽

Dual Energy ◽

Dual Energy Ct

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Prediction of Hemorrhage after Successful Recanalization in Patients with Acute Ischemic Stroke: Improved Risk Stratification Using Dual-Energy CT Parenchymal Iodine Concentration Ratio Relative to the Superior Sagittal Sinus

American Journal of Neuroradiology ◽

10.3174/ajnr.a6345 ◽

2020 ◽

Vol 41 (1) ◽

pp. 64-70

Author(s):

D. Byrne ◽

J.P. Walsh ◽

H. Schmiedeskamp ◽

F. Settecase ◽

M.K.S. Heran ◽

...

Keyword(s):

Ischemic Stroke ◽

Risk Stratification ◽

Acute Ischemic Stroke ◽

Concentration Ratio ◽

Superior Sagittal Sinus ◽

Iodine Concentration ◽

Dual Energy ◽

Dual Energy Ct ◽

Sagittal Sinus

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Assessment of iodine uptake by pancreatic cancer following chemotherapy using dual-energy CT

Abdominal Radiology ◽

10.1007/s00261-017-1338-6 ◽

2018 ◽

Vol 43 (2) ◽

pp. 445-456 ◽

Cited By ~ 9

Author(s):

Satomi Kawamoto ◽

Matthew. K. Fuld ◽

Daniel Laheru ◽

Peng Huang ◽

Elliot K. Fishman

Keyword(s):

Pancreatic Cancer ◽

Dual Energy ◽

Iodine Uptake ◽

Dual Energy Ct

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On the givenness of OV word order: a (re)examination of OV/VO variation in Old English

English Language and Linguistics ◽

10.1017/s1360674318000187 ◽

2018 ◽

Vol 24 (1) ◽

pp. 1-22

Author(s):

TARA STRUIK ◽

ANS VAN KEMENADE

Keyword(s):

Word Order ◽

Information Structure ◽

Mixed Model ◽

Linear Mixed Model ◽

Multinomial Regression ◽

Corpus Study ◽

History Of ◽

The Given ◽

New Hypothesis ◽

Multinomial Regression Analysis

OV/VO variation in the history of English has been a long-debated issue. Where earlier approaches were concerned with the grammatical status of the variation (see van Kemenade 1987; Pintzuk 1999 and many others), the debate has shifted more recently to explaining the variation from a pragmatic perspective (see Bech 2001; Taylor & Pintzuk 2012a), focusing on the given-before-new hypothesis (Gundel 1988) and its consequences for OV/VO. While the work by Taylor & Pintzuk (2012a) focuses specifically on the newness of VO orders, the present study is particularly concerned with the givenness of OV word order. It is hypothesized that OV orders are the result of leftward movement from VO orders, triggered by givenness. A corpus study on a database of subclauses with two verbs and a direct object, collected from the YCOE (Taylor et al.2003) corpus, and subsequent multinomial regression analysis within a generalized linear mixed model shows that OV word order is reserved for given objects, while VO objects are much more mixed in terms of information structure. We argue that these results are more in line with an analysis which derives all occurring word orders from a VO base than an analysis which proposes the opposite.

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Identification of benign and malignant thyroid nodules by in vivo iodine concentration measurement using single-source dual energy CT

Medicine ◽

10.1097/md.0000000000004816 ◽

2016 ◽

Vol 95 (39) ◽

pp. e4816 ◽

Cited By ~ 9

Author(s):

Shun-Yu Gao ◽

Xiao-Yan Zhang ◽

Wei Wei ◽

Xiao-Ting Li ◽

Yan-Ling Li ◽

...

Keyword(s):

Thyroid Nodules ◽

Iodine Concentration ◽

Dual Energy ◽

Concentration Measurement ◽

Dual Energy Ct ◽

Single Source

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Diagnostic Accuracy of Attenuation Difference and Iodine Concentration Thresholds at Rapid-Kilovoltage-Switching Dual-Energy CT for Detection of Enhancement in Renal Masses

American Journal of Roentgenology ◽

10.2214/ajr.18.20990 ◽

2019 ◽

Vol 213 (3) ◽

pp. 619-625 ◽

Cited By ~ 6

Author(s):

Nima Sadoughi ◽

Satheesh Krishna ◽

David B. Macdonald ◽

Robert Chatelain ◽

Trevor A. Flood ◽

...

Keyword(s):

Diagnostic Accuracy ◽

Iodine Concentration ◽

Dual Energy ◽

Dual Energy Ct ◽

Renal Masses

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Estimating age-time-dependent malaria force of infection accounting for unobserved heterogeneity

Epidemiology and Infection ◽

10.1017/s0950268817001297 ◽

2017 ◽

Vol 145 (12) ◽

pp. 2545-2562 ◽

Cited By ~ 2

Author(s):

L. MUGENYI ◽

S. ABRAMS ◽

N. HENS

Keyword(s):

Malaria Transmission ◽

Mixed Model ◽

Linear Mixed Model ◽

Unobserved Heterogeneity ◽

Parasite Clearance ◽

Generalized Linear Mixed Model ◽

Intrinsic Variability ◽

Force Of Infection ◽

Transmission Setting ◽

Potential Impact

SUMMARYDespite well-recognized heterogeneity in malaria transmission, key parameters such as the force of infection (FOI) are generally estimated ignoring the intrinsic variability in individual infection risks. Given the potential impact of heterogeneity on the estimation of the FOI, we estimate this quantity accounting for both observed and unobserved heterogeneity. We used cohort data of children aged 0·5–10 years evaluated for the presence of malaria parasites at three sites in Uganda. Assuming a Susceptible–Infected–Susceptible model, we show how the FOI relates to the point prevalence, enabling the estimation of the FOI by modelling the prevalence using a generalized linear mixed model. We derive bounds for varying parasite clearance distributions. The resulting FOI varies significantly with age and is estimated to be highest among children aged 5–10 years in areas of high and medium malaria transmission and highest in children aged below 1 year in a low transmission setting. Heterogeneity is greater between than within households and it increases with decreasing risk of malaria infection. This suggests that next to the individual's age, heterogeneity in malaria FOI may be attributed to household conditions. When estimating the FOI, accounting for both observed and unobserved heterogeneity in malaria acquisition is important for refining malaria spread models.

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Construction of a Lymph Node Metastasis Nomogram Prediction Model Based on Dual-Energy CT Radiomics of Gastric Cancer Lesions

10.21203/rs.3.rs-510637/v1 ◽

2021 ◽

Author(s):

Hong-li CUN ◽

Qian-ting DUAN ◽

Ying-ying DING ◽

Da-fu Zhang ◽

Ling YANG ◽

...

Keyword(s):

Gastric Cancer ◽

Tumor Markers ◽

Iodine Concentration ◽

Dual Energy ◽

Dual Energy Ct ◽

Test Set ◽

Serum Tumor Markers ◽

Node Metastasis ◽

Preoperative Serum ◽

Auc Value

Abstract Background This study aimed to explore the value of gastric cancer (GC) tumor markers and dual-energy CT（DECT） scans of arterial and venous GC lesions with quantitative iodine concentration (IC) and radiomics, to predict lymph node metastasis (LNM) in patients with GC. Methods This prospective study comprised of 177 patients that underwent dual-energy CT scans before surgery, and were subsequently diagnosed with GC by postoperative pathology. Serum tumor markers and arterial phases (AP) and venous phases (VP) of GC lesion iodine concentration (IC) and normalized iodine concentration (nIC) were analyzed. Patients were divided into either the LNM group or non-LNM group according to pathological results. The Wilcoxon rank-sum test was used to compare the serum tumor markers, IC, and nIC of the 2 groups, and a ROC curve was drawn to evaluate their effectiveness in predicting LNM in patients with GC. After using the Siemens syngo.via Frontier Radiomics software to extract radiomics features , all patients were randomly divided into a train set and a test set with a 7:3 ratio to predict GC LNM. Results Among the 177 patients with GC, 83 were diagnosed with LNM, while 94 did not have LNM. The preoperative serum tumor markers CA125, CA199, and CEA were statistically significant for predicting the presence of LNM (P<0.05). In the transfer group, AP and VP IC were 2.63 mg/ml (2.3, 3.00) and 3.60 mg/ml (3.23, 4.03) respectively, with corresponding areas under the curve (AUC) of 0.83 and 0.91. The nIC was 0.18 mg/ml (0.15, 0.21) and 0.78 mg/ml (0.65, 0.86); the AUC curve was 0.79 and 0.87. Both the IC and nIC were higher in the patients with LNM than those without LNM (P<0.05). Establishing a random forest (RF) model based on the radiomics extracted from the GC lesions had a high diagnostic value in predicting whether the lymph nodes in patients with GC were metastatic. The RF model AUC value was 0.959 for the train set and 0.977 for the test set. The AUC value of the nomogram predicting LNM was 0.996 for the train set and 0.976 for the test set. Conclusion Models based on preoperative serum tumor markers (CA125, CA199, and CEA) in patients with GC, quantitative dual-energy CT parameter values of the lesions (AP and VP IC, nIC), and radiomics have a higher diagnosis of LNM. The value of nomogram in combination with multi-parameter analysis is higher diagnosis of LNM, which can provide a reliable basis for preoperative evaluation of LNM.

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The sentence repetition task as a measure of sign language proficiency

Applied Psycholinguistics ◽

10.1017/s0142716421000436 ◽

2021 ◽

pp. 1-19

Author(s):

Krister Schönström ◽

Peter C. Hauser

Keyword(s):

Sign Language ◽

Language Proficiency ◽

Mixed Model ◽

Linear Mixed Model ◽

Intraclass Correlation ◽

Linguistic Knowledge ◽

Internal Reliability ◽

Sentence Repetition ◽

Language Research ◽

The Impact

Abstract Sign language research is important for our understanding of languages in general and for the impact it has on policy and on the lives of deaf people. There is a need for a sign language proficiency measure, to use as a grouping or continuous variable, both in psycholinguistics and in other sign language research. This article describes the development of a Swedish Sign Language Sentence Repetition Test (STS-SRT) and the evidence that supports the validity of the test’s interpretation and use. The STS-SRT was administered to 44 deaf adults and children, and was shown to have excellent internal reliability (Cronbach’s alpha of 0.915) and inter-rater reliability (Intraclass Correlation Coefficient [ICC] = 0.900, p < .001). A linear mixed model analysis revealed that adults scored 20.2% higher than children, and delayed sign language acquisition were associated with lower scores. As the sign span of sentences increased, participants relied on their implicit linguistic knowledge to scaffold their sentence repetitions beyond rote memory. The results provide reliability and validity evidence to support the use of STS-SRT in research as a measure of STS proficiency.

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