Appropriateness and imaging outcomes of ultrasound, CT, and MR in the emergency department: a retrospective analysis from an urban academic center.

PURPOSE: To evaluate the appropriateness and outcomes of ultrasound (US), computed tomography (CT), and magnetic resonance (MR) orders in the ED. METHODS: We retrospectively reviewed consecutive US, CT, and MR orders for adult ED patients at a tertiary care urban academic center from January to March 2019. The American College of Radiology Appropriateness Criteria (ACRAC) guidelines were primarily used to classify imaging orders as "appropriate" or "inappropriate". Two radiologists in consensus judged specific clinical scenarios that were unavailable in the ACRAC. Final imaging reports were compared with the initial clinical suspicion for imaging and categorized into "normal", "compatible with initial diagnosis", "alternative diagnosis", or "inconclusive". The sample was powered to show a prevalence of inappropriate orders of 30% with a margin of error of 5%. RESULTS: The rate of inappropriate orders was 59.4% for US, 29.1% for CT, and 33.3% for MR. The most commonly imaged systems for each modality were neuro (130/330) and gastrointestinal (95/330) for CT, genitourinary (132/330) and gastrointestinal (121/330) for US, neuro (273/330) and gastrointestinal (37/330) for MR. Compared to inappropriately ordered tests, the final reports of appropriate orders were nearly three times more likely to demonstrate findings compatible with the initial diagnosis for all modalities: US (45.5 vs. 14.3%, p < 0.001), CT (46.6 vs. 14.6%, p < 0.001), and MR (56.3 vs. 21.8%, p < 0.001). Inappropriate orders were more likely to show no abnormalities compared to appropriate orders: US (65.8 vs. 38.8%, p < 0.001), CT (62.5 vs. 34.2%, p < 0.001), and MR (61.8 vs. 38.7%, p < 0.001). CONCLUSION: The prevalence of inappropriate imaging orders in the ED was 59.4% for US, 29.1% for CT, and 33.3% for MR. Appropriately ordered imaging was three times more likely to yield findings compatible with the initial diagnosis across all modalities.

A Tree-Based Heuristic for the One-Dimensional Cutting Stock Problem Optimization Using Leftovers.

Cutting problems consist of cutting a set of objects available in stock in order to produce the desired items in specified quantities and sizes. The cutting process can generate leftovers (which can be reused in the case of new demand) or losses (which are discarded). This paper presents a tree-based heuristic method for minimizing the number of cut bars in the one-dimensional cutting process, satisfying the item demand in an unlimited bar quantity of just one type. The results of simulations are compared with the RGRL1 algorithm and with the limiting values for this considered type of problem. The results show that the proposed heuristic reduces processing time and the number of bars needed in the cutting process, while it provides a larger leftover (by grouping losses) for the one-dimensional cutting stock problem. The heuristic contributes to reduction in raw materials or manufacturing costs in industrial processes.

Natural Language Processing for the Identification of Incidental Lung Nodules in Computed Tomography Reports: A Quality Control Tool.

PURPOSE: To evaluate the diagnostic performance of a natural language processing (NLP) model in detecting incidental lung nodules (ILNs) in unstructured chest computed tomography (CT) reports. METHODS: All unstructured consecutive reports of chest CT scans performed at a tertiary hospital between 2020 and 2021 were retrospectively reviewed (n = 21,542) to train the NLP tool. Internal validation was performed using reference readings by two radiologists of both CT scans and reports, using a different external cohort of 300 chest CT scans. Second, external validation was performed in a cohort of all random unstructured chest CT reports from 57 different hospitals conducted in May 2022. A review by the same thoracic radiologists was used as the gold standard. The sensitivity, specificity, and accuracy were calculated. RESULTS: Of 21,542 CT reports, 484 mentioned at least one ILN (mean age, 71 ± 17.6 [standard deviation] years; women, 52%) and were included in the training set. In the internal validation (n = 300), the NLP tool detected ILN with a sensitivity of 100.0% (95% CI, 97.6 to 100.0), a specificity of 95.9% (95% CI, 91.3 to 98.5), and an accuracy of 98.0% (95% CI, 95.7 to 99.3). In the external validation (n = 977), the NLP tool yielded a sensitivity of 98.4% (95% CI, 94.5 to 99.8), a specificity of 98.6% (95% CI, 97.5 to 99.3), and an accuracy of 98.6% (95% CI, 97.6 to 99.2). Twelve months after the initial reports, 8 (8.60%) patients had a final diagnosis of lung cancer, among which 2 (2.15%) would have been lost to follow-up without the NLP tool. CONCLUSION: NLP can be used to identify ILNs in unstructured reports with high accuracy, allowing a timely recall of patients and a potential diagnosis of early-stage lung cancer that might have been lost to follow-up.

CT imaging findings in lung transplant recipients with COVID-19.

OBJECTIVES: Our goal was to compare the chest computed tomography (CT) imaging findings of COVID-19 in lung transplant recipients (LTR) and a group of non-transplanted controls (NTC). METHODS: This retrospective study included 51 consecutive LTR hospitalized with COVID-19 from two centers. A total of 75 NTC were included for comparison. Images were classified regarding the standardized RSNA category, main pattern of lung attenuation, and longitudinal and axial distribution. Quantitative CT (QCT) analysis was performed to evaluate percentage of high attenuation areas (%HAA, threshold -250 to -700 HU). CT scoring was used to measure severity of parenchymal abnormalities. RESULTS: The imaging findings of COVID-19 in LTR were significantly different from controls regarding the RSNA classification and pattern of lung attenuation. LTR had a significantly higher proportion of patients with an indeterminate pattern on CT (0.31 vs. 0.11, p = 0.014). The most frequent pattern of attenuation in LTR was predominantly consolidation (0.39 vs. 0.22, p = 0.144) followed by a mixed pattern of ground-glass opacities (GGO) and consolidation (0.37 vs. 0.20, adjusted p = 0.102). On the other hand, the most common pattern in NTC was GGO predominant (0.58 vs. 0.24 of LTR, p = 0.001). LTR had significantly more severe parenchymal disease measured by CT score and %HAA by QCT (0.372 ± 0.08 vs. 0.148 ± 0.06, p < 0.001). CONCLUSION: The most frequent finding of COVID-19 in LTR is a predominant pattern of consolidation. Compared to NTC, LTR more frequently demonstrated an indeterminate pattern according to the RSNA classification and more extensive lung abnormalities on QCT and semi-quantitative scoring. KEY POINTS: • The most common CT finding of COVID-19 in LTR is a predominant pattern of consolidation followed by a mixed pattern of GGO and consolidation, while controls more often have a predominant pattern of GGO. • LTR more often presents with an indeterminate pattern of COVID-19 by RSNA classification than controls; therefore, molecular testing for COVID-19 is essential for LTR presenting with lower airway infection independently of imaging findings. • LTR had more extensive disease by semi-quantitative CT score and increased percentage areas of high attenuation on QCT.

Narrowing the Differential Diagnosis of Cystic Lesions in Smokers with Expiratory CT Acquisition Using the Cyst-Airway Communication Hypothesis.

The aim of this study was to assess percentage respiratory changes (δ) in the size of pulmonary cysts of different smoking-related etiologies. Retrospectively, we measured the cystic lesions due to histopathological-confirmed honeycombing from interstitial pulmonary fibrosis, pulmonary Langerhans cell histiocytosis (PLCH), and paraseptal emphysema, using paired inspiratory and expiratory CT scans. In a sample of 72 patients and 216 lesions, the mean diameter of PLCH and honeycombing decreased during expiration (PLCH, δ = 60.9%; p = 0.001; honeycombing, δ = 47.5%; p = 0.014). Conversely, paraseptal emphysema did not show any changes (δ = 5.2%; p = 0.34). In summary, our results demonstrated that cysts in smokers with PLCH and honeycombing fibrosis get smaller during expiratory CT scans, whereas the size of cystic-like lesions due to paraseptal emphysema and bullae tend to remain constant during respiratory cycles. These results support the hypothesis of cyst-airway communication in some cystic diseases, which could assist in the differential diagnosis in smoking-related lung diseases.

The diagnostic value of magnetic resonance imaging compared to computed tomography in the evaluation of fat-containing thoracic lesions.

Intrathoracic fat-containing lesions may arise in the mediastinum, lungs, pleura, or chest wall. While CT can be helpful in the detection and diagnosis of these lesions, it can only do so if the lesions contain macroscopic fat. Furthermore, because CT cannot demonstrate microscopic or intravoxel fat, it can fail to identify and diagnose microscopic fat-containing lesions. MRI, employing spectral and chemical shift fat suppression techniques, can identify both macroscopic and microscopic fat, with resultant enhanced capability to diagnose these intrathoracic lesions non-invasively and without ionizing radiation. This paper aims to review the CT and MRI findings of fat-containing lesions of the chest and describes the fat-suppression techniques utilized in their assessment.

Letter on the results of the BASiNET method in the paper 'A systematic evaluation of computational tools for lncRNA identification'.

This letter points out a conceptual error made by the authors of a published paper, which presents a review and evaluation of computational methods in lncRNA identification. The error was made in the execution of the BASiNET method when considering an example file (toy model) made available by the authors with the aim of showing how a classification model could be stored in a file for later use. In this letter, this error is contextualized, the correct use of the BASiNET method is pointed out and the results of its correct execution to one of the datasets used in the review article are presented. The results clearly show the misuse of the method and present its correct use so that it can be fairly compared with other methods in the literature and prevent its misuse from being replicated by new studies.

The Normal Lung Index From Quantitative Computed Tomography for the Evaluation of Obstructive and Restrictive Lung Disease.

PURPOSE: Our objective was to evaluate whether the normal lung index (NLI) from quantitative computed tomography (QCT) analysis can be used to predict mortality as well as pulmonary function tests (PFTs) in patients with chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). MATERIALS AND METHODS: Normal subjects (n=20) and patients with COPD (n=172) and ILD (n=114) who underwent PFTs and chest CT were enrolled retrospectively in this study. QCT measures included the NLI, defined as the ratio of the lung with attenuation between -950 and -700 Hounsfield units (HU) over the total lung volume (-1024 to -250 HU, mL), high-attenuation area (-700 to -250 HU, %), emphysema index (>6% of pixels < -950 HU), skewness, kurtosis, and mean lung attenuation. Coefficients of correlation between QCT measurements and PFT results in all subjects were calculated. Univariate and multivariate survival analyses were performed to assess mortality prediction by disease. RESULTS: The Pearson correlation analysis showed that the NLI correlated moderately with the forced expiratory volume in 1 second in subjects with COPD (r=0.490, P<0.001) and the forced vital capacity in subjects with ILD (r=0.452, P<0.001). Multivariate analysis revealed that the NLI of <70% was a significant independent predictor of mortality in subjects with COPD (hazard ratio=3.14, P=0.034) and ILD (hazard ratio=2.72, P=0.005). CONCLUSION: QCT analysis, specifically the NLI, can also be used to predict mortality in individuals with COPD and ILD.

Quantitative Computed Tomography: What Clinical Questions Can it Answer in Chronic Lung Disease?

Quantitative computed tomography (QCT) has recently gained an important role in the functional assessment of chronic lung disease. Its capacity in diagnostic, staging, and prognostic evaluation in this setting is similar to that of traditional pulmonary function testing. Furthermore, it can demonstrate lung injury before the alteration of pulmonary function test parameters, and it enables the classification of disease phenotypes, contributing to the customization of therapy and performance of comparative studies without the intra- and inter-observer variation that occurs with qualitative analysis. In this review, we address technical issues with QCT analysis and demonstrate the ability of this modality to answer clinical questions encountered in daily practice in the management of patients with chronic lung disease.

Expiratory CT scanning in COVID-19 patients: can we add useful data?

OBJECTIVE: To evaluate small airway disease in COVID-19 patients using the prevalence of air trapping (AT) and correlating it with clinical outcomes. The relationship between CT-based opacities in small blood vessels and ventilation in patients with SARS-CoV-2 pneumonia was also assessed. METHODS: We retrospectively included 53 patients with positive RT-PCR results for SARS-CoV-2 between March and April of 2020. All subjects underwent HRCT scanning, including inspiratory and expiratory acquisitions. Subjects were divided into two groups based on visual identification of AT. Small blood vessel volumes were estimated by means of cross-sectional areas < 5 mm2 (BV5) derived from automated segmentation algorithms. Mixed-effect models were obtained to represent the BV5 as a function of CT-based lobar opacities and lobar ventilation. RESULTS: Of the 53 participants, AT was identified in 23 (43.4%). The presence of AT was associated with increased SpO2 at admission (OR = 1.25; 95% CI, 1.07-1.45; p = 0.004) and reduced D-dimer levels (OR = 0.99; 95% CI, 0.99-0.99; p = 0.039). Patients with AT were less likely to be hospitalized (OR = 0.27; 95% CI, 0.08-0.89; p = 0.032). There was a significant but weak inverse correlation between BV5 and CT-based lobar opacities (R2 = 0.19; p = 0.03), as well as a nonsignificant and weak direct correlation between BV5 and lobar ventilation (R2 = 0.08; p = 0.54). CONCLUSIONS: AT is a common finding in patients with COVID-19 that undergo expiratory CT scanning. The presence of AT may correlate with higher SpO2 at admission, lower D-dimer levels, and fewer hospitalizations when compared with absence of AT. Also, the volume of small pulmonary vessels may negatively correlate with CT opacities but not with lobar ventilation.

Expiratory CT scanning in COVID-19 patients: can we add useful data? / TC expiratória em pacientes com COVID-19: podemos adicionar dados úteis?

ABSTRACT Objective: To evaluate small airway disease in COVID-19 patients using the prevalence of air trapping (AT) and correlating it with clinical outcomes. The relationship between CT-based opacities in small blood vessels and ventilation in patients with SARS-CoV-2 pneumonia was also assessed. Methods: We retrospectively included 53 patients with positive RT-PCR results for SARS-CoV-2 between March and April of 2020. All subjects underwent HRCT scanning, including inspiratory and expiratory acquisitions. Subjects were divided into two groups based on visual identification of AT. Small blood vessel volumes were estimated by means of cross-sectional areas < 5 mm2 (BV5) derived from automated segmentation algorithms. Mixed-effect models were obtained to represent the BV5 as a function of CT-based lobar opacities and lobar ventilation. Results: Of the 53 participants, AT was identified in 23 (43.4%). The presence of AT was associated with increased SpO2 at admission (OR = 1.25; 95% CI, 1.07-1.45; p = 0.004) and reduced D-dimer levels (OR = 0.99; 95% CI, 0.99-0.99; p = 0.039). Patients with AT were less likely to be hospitalized (OR = 0.27; 95% CI, 0.08-0.89; p = 0.032). There was a significant but weak inverse correlation between BV5 and CT-based lobar opacities (R2 = 0.19; p = 0.03), as well as a nonsignificant and weak direct correlation between BV5 and lobar ventilation (R2 = 0.08; p = 0.54). Conclusions: AT is a common finding in patients with COVID-19 that undergo expiratory CT scanning. The presence of AT may correlate with higher SpO2 at admission, lower D-dimer levels, and fewer hospitalizations when compared with absence of AT. Also, the volume of small pulmonary vessels may negatively correlate with CT opacities but not with lobar ventilation.

RESUMO Objetivo: Avaliar a doença das pequenas vias aéreas em pacientes com COVID-19 por meio da prevalência de aprisionamento aéreo (AA) e sua correlação com desfechos clínicos. Também foi avaliada a relação entre opacidades tomográficas nos pequenos vasos sanguíneos e ventilação em pacientes com pneumonia por SARS-CoV-2. Métodos: Foram incluídos, retrospectivamente, 53 pacientes com teste de RT-PCR positivo para SARS-CoV-2 entre março e abril de 2020. Todos os indivíduos foram submetidos à TCAR, incluindo aquisições inspiratórias e expiratórias. Os indivíduos foram divididos em dois grupos com base na identificação visual de AA. Os volumes dos pequenos vasos sanguíneos foram estimados por meio de seções transversais < 5 mm2 (VS5) derivadas de algoritmos automatizados de segmentação. Modelos de efeito misto foram obtidos para representar o VS5 em função das opacidades lobares tomográficas e da ventilação lobar. Resultados: Identificou-se AA em 23 (43,4%) dos 53 participantes. A presença de AA apresentou associação com SpO2 elevada na admissão (OR = 1,25; IC95%: 1,07-1,45; p = 0,004) e níveis reduzidos de dímero D (OR = 0,99; IC95%: 0,99-0,99; p = 0,039). Pacientes com AA apresentaram menor probabilidade de hospitalização (OR = 0,27; IC95%: 0,08-0,89; p = 0,032). Houve correlação inversa significativa, mas fraca, entre VS5 e opacidades lobares tomográficas (R2 = 0,19; p = 0,03) e correlação direta não significativa e fraca entre VS5 e ventilação lobar (R2 = 0,08; p = 0,54). Conclusões: AA é um achado comum em pacientes com COVID-19 submetidos à TC expiratória. A presença de AA pode apresentar correlação com SpO2 elevada na admissão, níveis reduzidos de dímero D e menor probabilidade de hospitalização. Além disso, o volume dos pequenos vasos pulmonares pode apresentar correlação negativa com opacidades tomográficas, mas não com ventilação lobar.

Three-dimensional virtual planning for nodule resection in solid organs: A systematic review and meta-analysis.

OBJECTIVES: To systematically review the effects of 3D-imaging virtual planning for nodule resection in the following solid organs: lung, liver, and kidney. METHODS: MEDLINE, EMBASE, and Cochrane Library were searched through September 31, 2020 to include randomized and non-randomized controlled studies that compared outcomes of surgical resection of lung, liver, or kidney nodule resection with and without 3D virtual planning with computed tomography. From each article, the mean operation time (OT), mean estimated blood loss (EBL), mean postoperative hospital stay (POHS), and the number of postoperative events (POE) were extracted. The effect size (ES) of 3D virtual planning vs. non-3D planning was extracted from each study to calculate the pooled measurements for continuous variables (OT, EBL, POHS). Data were pooled using a random-effects model. RESULTS: The literature search yielded 2397 studies and 10 met the inclusion criteria with a total of 897 patients. There was a significant difference in OT between groups with a moderate ES favoring the 3D group (ES,-0.56; 95%CI: 0.91,-0.29; I2 = 83.1%; p < .001). Regarding EBL, there was a significant difference between 3D and non-3D with a small ES favoring IGS (ES,-0.18; 95%CI: 0.33,-0.02; I2 = 22.5%; p = .0236). There was no difference between the 3D and non-3D groups for both POHS (POHS ES,-0.15; 95%CI: 0.39,0.10; I2 = 37.0%; p = .174) and POE (POE odds ratio (OR),0.80; 95%CI:0.54,1.19; I2 = 0.0%; p = .0.973). CONCLUSIONS: 3D-imaging planning for surgical resection of lung, kidney, and liver nodules could reduce OT and EBL with no effects on immediate POHS and POE. Improvements in these perioperative variables could improve medium and long-term postoperative clinical outcomes.

High-resolution CT pulmonary findings in children with severe asthma

Abstract Objective: To compare quantitative CT parameters between children with severe asthma and healthy subjects, correlating to their clinical features. Methods: We retrospectively analyzed CT data from 19 school-aged children (5-17 years) with severe asthma and 19 control school-aged children with pectus excavatum. The following CT parameters were evaluated: total lung volume (TLV), mean lung density (MLD), CT air trapping index (AT%) (attenuation ≤856 HU), airway wall thickness (AWT), and percentage of airway wall thickness (AWT%). Multi-detector computed tomography (MDCT) data were correlated to the following clinical parameters: forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), forced expiratory flow at 25-75% (FEF 25-75%), FEV1/FVC ratio, sputum and bronchoalveolar lavage analysis, serum IgE levels, and previous hospitalizations due to asthma. Results: Asthma patients presented higher mean values of AT% (23.8 ± 6.7% vs. controls, 9.7 ± 3.2%), AWT (1.46 ± 0.22 mm vs. controls, 0.47 ± −735 ± 28 HU vs. controls, −666 ± 19 HU). Mean AT% was 29.0 ± 4.7% in subjects with previous hospitalization against 19.2 ± 5.0% in those with no prior hospitalization (p < 0.001). AT% presented very strong negative correlations with FVC (r = −0.933, p < 0.001) and FEV1 (r = −0.841, p < 0.001) and a moderate correlation with FEF 25-75% (r = −0.608, p = 0.007). AT% correlation with FEV1/FVC ratio and serum IgE was weak (r = −0.184, p = 0.452, and r = −0.363, p = 0.202) Conclusion: Children with severe asthma present differences in quantitative chest CT scans compared to healthy controls with strong correlations with pulmonary function tests and previous hospitalizations due to asthma.

High-resolution CT pulmonary findings in children with severe asthma.

OBJECTIVE: To compare quantitative CT parameters between children with severe asthma and healthy subjects, correlating to their clinical features. METHODS: We retrospectively analyzed CT data from 19 school-aged children (5-17 years) with severe asthma and 19 control school-aged children with pectus excavatum. The following CT parameters were evaluated: total lung volume (TLV), mean lung density (MLD), CT air trapping index (AT%) (attenuation ≤856 HU), airway wall thickness (AWT), and percentage of airway wall thickness (AWT%). Multi-detector computed tomography (MDCT) data were correlated to the following clinical parameters: forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), forced expiratory flow at 25-75% (FEF 25-75%), FEV1/FVC ratio, sputum and bronchoalveolar lavage analysis, serum IgE levels, and previous hospitalizations due to asthma. RESULTS: Asthma patients presented higher mean values of AT% (23.8 ±â€¯6.7% vs. controls, 9.7 ±â€¯3.2%), AWT (1.46 ±â€¯0.22 mm vs. controls, 0.47 ±â€¯-735 ±â€¯28 HU vs. controls, -666 ±â€¯19 HU). Mean AT% was 29.0 ±â€¯4.7% in subjects with previous hospitalization against 19.2 ±â€¯5.0% in those with no prior hospitalization (p < 0.001). AT% presented very strong negative correlations with FVC (r = -0.933, p < 0.001) and FEV1 (r = -0.841, p < 0.001) and a moderate correlation with FEF 25-75% (r = -0.608, p = 0.007). AT% correlation with FEV1/FVC ratio and serum IgE was weak (r = -0.184, p = 0.452, and r = -0.363, p = 0.202) CONCLUSION: Children with severe asthma present differences in quantitative chest CT scans compared to healthy controls with strong correlations with pulmonary function tests and previous hospitalizations due to asthma.

Coronavirus Disease 2019 (COVID-19) Pneumonia Presentations in Chest Computed Tomography: A Pictorial Review.

Despite imaging not being a tool for novel coronavirus disease 2019 (COVID-19) diagnosis, there has been an increased number of chest computed tomography (CT) scans done worldwide. There are no pathognomonic CT features for COVID-19 pneumonia, as findings are also common in other infectious diseases and noninfectious aetiologies. Nonetheless, point-of-care physicians should be familiarized with the most common imaging presentations of the COVID-19. In this pictorial review, we have summarized the most reported imaging features of COVID-19 pneumonia, including possible differential diagnosis according to the CT finding.

COVID-19 mimics on chest CT: a pictorial review and radiologic guide.

Chest imaging is often used as a complementary tool in the evaluation of coronavirus disease 2019 (COVID-19) patients, helping physicians to augment their clinical suspicion. Despite not being diagnostic for COVID-19, chest CT may help clinicians to isolate high suspicion patients with suggestive imaging findings. However, COVID-19 findings on CT are also common to other pulmonary infections and non-infectious diseases, and radiologists and point-of-care physicians should be aware of possible mimickers. This state-of-the-art review goal is to summarize and illustrate possible etiologies that may have a similar pattern on chest CT as COVID-19. The review encompasses both infectious etiologies, such as non-COVID viral pneumonia, Mycoplasma pneumoniae, Pneumocystis jiroveci, and pulmonary granulomatous infectious, and non-infectious disorders, such as pulmonary embolism, fat embolism, cryptogenic organizing pneumonia, non-specific interstitial pneumonia, desquamative interstitial pneumonia, and acute and chronic eosinophilic pneumonia.

Subspecialized radiology reporting: productivity and impact on the turnaround times for radiology reports in a middle-income country.

OBJECTIVE: To evaluate the effect that transitioning from a model of general radiology reporting to one of subspecialized radiology reporting has on report turnaround times (TATs) and on productivity in the radiology department of a hospital in a middle-income country. MATERIALS AND METHODS: The reporting workflow in our radiology department was changed from general reporting (any radiologist reporting imaging studies for any specialty) to subspecialized reporting (radiologists exclusively reporting imaging studies that fall within their subspecialty-abdominal, musculoskeletal, cardiothoracic, emergency, or neurological imaging). This was a retrospective study in which we compared general reporting with subspecialized reporting in terms of the following variables: the TAT; the proportions of reports completed within 2 h and within 24 h (TAT-2h and TAT- 24 h, respectively); and productivity. Data were collected over two 24-month periods (2015-2016 for general reporting and 2017-2018 for subspecialized reporting). RESULTS: A total of 208,516 reports were generated. The median report TAT decreased from 49.1 h and 52.9 h in 2015 and 2016, respectively, to 16.1 h and 15.2 h in 2017 and 2018, respectively (p < 0.001). The TAT-2h also improved, increasing from 8.7% and 7.9% in 2015 and 2016, respectively, to 52.0% and 61.3% in 2017 and 2018, respectively (p < 0.001), as did the TAT- 24 h, which increased from 12.1% and 14.1% in 2015 and 2016, respectively, to 74.3% and 78.7% in 2017 and 2018, respectively (p < 0.001). Between the two periods, the total number of scans performed increased by 33% (p = 0.001). CONCLUSION: The implementation of a subspecialized reporting system significantly improved the median TAT for radiology reports, as well as increasing the TAT-2h and TAT- 24 h, during a time of increased productivity.

OBJETIVO: Avaliar o efeito da transição de um modelo de laudos em radiologia realizados por radiologistas gerais para um modelo relatado por subespecialização no tempo de resposta de relatórios (TAT) em radiologia e produtividade em um departamento de radiologia em um país em desenvolvimento. MATERIAIS E MÉTODOS: O fluxo em nosso departamento foi modificado de um sistema de relatórios gerais (qualquer radiologista lauda exames de imagem de qualquer especialidade) para um sistema de subespecialização (radiologistas laudam exclusivamente exames de imagem pertencente a sua subespecialidade - abdominal, musculoesquelético, cardiotorácico, emergência e neurologia). Este estudo retrospectivo avaliou a TAT, TAT-2 horas e TAT-24 horas e a produtividade num período de 24 meses de relatórios gerais (2015-2016) comparado a um período de 24 meses do sistema de subespecialização (2017-2018). RESULTADOS: No total, 208.516 laudos foram gerados. A TAT reportada reduziu de uma média de 49,1-52,9 horas durante o período geral para 15,2-16,1 horas durante o período de relatórios por subespecialidade (p < 0,001). TAT-2 horas e TAT- 24 horas aumentaram significativamente de 7,9-8,7% para 52,0-61,3% e de 12,1-14,1% para 74,3-78,7%, respectivamente (p < 0.001). O número total de exames aumentou em 33% (p = 0.001) comparando os dois períodos. CONCLUSÃO: A implementação de um sistema de laudos por subespecialidade aumentou o TAT em radiologia, incluindo benefícios no TAT-2 horas e TAT-24 horas durante um período de aumento da produtividade.

Comparison of the computed tomography findings in COVID-19 and other viral pneumonia in immunocompetent adults: a systematic review and meta-analysis.

OBJECTIVES: To compare the chest computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) to other non-COVID viral pneumonia. METHODS: MEDLINE, EMBASE, and Cochrane databases were searched through April 04, 2020, for published English language studies. Studies were eligible if they included immunocompetent patients with up to 14 days of viral pneumonia. Subjects had a respiratory tract sample test positive for COVID-19, adenovirus, influenza A, rhinovirus, parainfluenza, or respiratory syncytial virus. We only included observational studies and case series with more than ten patients. The pooled prevalence of each chest CT pattern or finding was calculated with 95% confidence intervals (95% CI). RESULTS: From 2263 studies identified, 33 were eligible for inclusion, with a total of 1911 patients (COVID-19, n = 934; non-COVID, n = 977). Frequent CT features for both COVID-19 and non-COVID viral pneumonia were a mixed pattern of ground-glass opacity (GGO) and consolidation (COVID-19, 0.37; 0.17-0.56; non-COVID, 0.46; 0.35-0.58) or predominantly GGO pattern (COVID-19, 0.42; 0.28-0.55; non-COVID 0.25; 0.17-0.32), bilateral distribution (COVID-19, 0.81; 0.77-0.85; non-COVID, 0.69; 0.54-0.84), and involvement of lower lobes (COVID-19, 0.88; 0.80-0.95; non-COVID, 0.61; 0.50-0.82). COVID-19 pneumonia presented a higher prevalence of peripheral distribution (COVID-19 0.77; 0.67-0.87; non-COVID 0.34; 0.18-0.49), and involvement of upper (COVID-19, 0.77; 0.65-0.88; non-COVID 0.18; 0.10-0.27) and middle lobes (COVID-19, 0.61; 0.47-0.76; non-COVID 0.24; 0.11-0.38). CONCLUSION: Except for a higher prevalence of peripheral distribution, involvement of upper and middle lobes, COVID-19, and non-COVID viral pneumonia had overlapping chest CT findings. KEY POINTS: • Most common CT findings of coronavirus disease 2019 (COVID-19) were a predominant pattern of ground-glass opacity (GGO), followed by a mixed pattern of GGO and consolidation, bilateral disease, peripheral distribution, and lower lobe involvement. • Most frequent CT findings of non-COVID viral pneumonia were a predominantly mixed pattern of GGO and consolidation, followed by a predominant pattern of GGO, bilateral disease, random or diffuse distribution, and lower lobe involvement. • COVID-19 pneumonia presented a higher prevalence of peripheral distribution, and involvement of upper and middle lobes compared with non-COVID viral pneumonia.

18F-FDG PET/CT and whole-body MRI diagnostic performance in M staging for non-small cell lung cancer: a systematic review and meta-analysis.

OBJECTIVES: To evaluate the diagnostic test accuracy of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT), whole-body magnetic resonance imaging (WB-MRI), and whole-body diffusion-weighted imaging (WB-DWI) for the detection of metastases in patients with non-small cell lung cancer (NSCLC). METHODS: MEDLINE, Embase, and Cochrane Library databases were searched up to June 2019. Studies were selected if they reported data that could be used to construct contingency tables to compare 18F-FDG PET/CT, WB-MRI, and WB-DWI. Two authors independently extracted data on study characteristics and assessed methodological quality using the Quality Assessment of Diagnostic Accuracy Studies. Forest plots were generated for sensitivity and specificity of 18F-FDG PET/CT, WB-MRI, and whole-body diffusion-weighted imaging (WB-DWI). Summary receiver operating characteristic plots were created. RESULTS: The 4 studies meeting inclusion criteria had a total of 564 patients and 559 lesions, 233 of which were metastases. In studies of 18F-FDG PET/CT, the pooled estimates of sensitivity and specificity were 0.83 (95% confidence interval [CI], 0.54-0.95) and 0.93 (95% CI, 0.87-0.96), respectively. For WB-MRI, pooled sensitivity was 0.92 (95% CI, 0.18-1.00) and pooled specificity was 0.93 (95% CI, 0.85-0.95). Pooled sensitivity and specificity for WB-DWI were 0.78 (95% CI, 0.46-0.93) and 0.91 (95% CI, 0.79-0.96), respectively. There was no statistical difference between the diagnostic odds ratio of WB-MRI and WB-DWI compared with that of PET/CT (p = 0.186 for WB-DWI; p = 0.638 for WB-MRI). CONCLUSION: WB-MRI and DWI are radiation-free alternatives with comparable diagnostic performance to 18F-FDG PET/CT for M staging of NSCLC. KEY POINTS: • Whole-body MRI with or without diffusion-weighted imaging has a high accuracy for the diagnostic evaluation of metastases in patients with non-small cell lung cancer. • Whole-body MRI may be used as a non-invasive and radiation-free alternative to positron emission tomography with CT with similar diagnostic performance.

Effects of Transcutaneous Electrical Nerve Stimulation on Pain, Pulmonary Function, and Respiratory Muscle Strength After Posterolateral Thoracotomy: A Randomized Controlled Trial.

PURPOSE: To evaluate the effects of transcutaneous electrical nerve stimulation (TENS) compared to placebo TENS and a control group on pain, pulmonary function, respiratory muscle strength, and analgesic medications in the postoperative period of thoracotomy in an Intensive care unit (ICU). METHODS: Patients who had undergone posterolateral thoracotomy were randomly allocated to receive TENS during ICU stay, or placebo TENS, or into the control group. All groups received conventional physiotherapy. We analysed the intensity of pain, pulmonary function, respiratory muscle strength, and use of analgesia medications. Outcomes were evaluated before surgery, immediately after, 24 and 48 h after ICU admission. RESULTS: Forty-five patients were included. Regarding pain perception, there was no difference between groups (p = 0.172), but there was a significant reduction in pain intensity for patients receiving TENS after first physiotherapy session compared to baseline (4.7 ± 3.2 vs 3.3 ± 2.6; p < 0.05). All groups had a decrease in forced vital capacity (FVC) after surgery (p < 0.001). There was no difference between the groups regarding the use of analgesic medications, but a higher intake of morphine and acetaminophen were observed for the control (p = 0.037) and placebo group (p = 0.035), respectively. CONCLUSION: The use of TENS provides a little benefit of pain (in the first 12 h) but failed to demonstrate any improvement in the recovery of ICU patients after 48 h of posterolateral thoracotomy. TRIAL REGISTRATION: NCT02438241.