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.

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.

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.

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.

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.

Effects of the addition of quantitative apparent diffusion coefficient data on the diagnostic performance of the PI-RADS v2 scoring system to detect clinically significant prostate cancer.

PURPOSE: To evaluate the impact of the addition of quantitative apparent diffusion coefficient (ADC) data into the diagnostic performance of the Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) scoring system to predict clinically significant prostate cancer (CSPCa). METHODS: We retrospectively included 91 consecutive patients who underwent prostate multiparametric magnetic resonance imaging (mp-MRI) and histopathological evaluation. Mp-MRI images were reported by the PI-RADSv2 scoring system and patients were divided into groups considering the likelihood of CSPCa. ADC value and ratio were obtained. Findings were correlated with histopathological data. RESULTS: CSPCa was found in 41.8% of cases (n = 38). PI-RADSv2 score 3-5 yielded a sensitivity of 97.4% (95% confidence intervals 86.5-99.5), a specificity of 50.9% (37.9-63.9), and AUC of 0.74 (0.67-0.81) to predict CSPCa. ADC value < 750 µm2/s and an ADC ratio < 0.62 were the most accurate thresholds for differentiation of CSPCa, with AUC of 0.81 and 0.76, respectively. Combined PI-RADSv2 score 3-5 and ADC value < 750 µm2/s yielded a specificity of 84.9 (72.9-92.2), sensitivity of 70.3 (54.2-82.5), and AUC of 0.77 (0.68-0.86). Combined PI-RADSv2 score 3-5 and ADC ratio < 0.62 yielded a specificity of 86.5 (74.7-93.3), sensitivity of was 64.9 (48.8-78.2), and AUC of 0.75 (0.66-0.84). CONCLUSION: Quantitative ADC data might not be beneficial to be used routinely in mp-MR imaging as criteria to detect clinically significant lesions due to the reduced sensitivity. Instead, when prostate lesions present a PI-RADSv2 score ≥ 3, additional quantitative ADC criteria can be helpful to increase the PI-RADS score specificity.

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.

Fluorine 18-FDG PET/CT and Diffusion-weighted MRI for Malignant versus Benign Pulmonary Lesions: A Meta-Analysis.

Purpose To perform a meta-analysis of the literature to compare the diagnostic performance of fluorine 18 fluorodeoxyglucose PET/CT and diffusion-weighted (DW) MRI in the differentiation of malignant and benign pulmonary nodules and masses. Materials and Methods Published English-language studies on the diagnostic accuracy of PET/CT and/or DW MRI in the characterization of pulmonary lesions were searched in relevant databases through December 2017. The primary focus was on studies in which joint DW MRI and PET/CT were performed in the entire study population, to reduce interstudy heterogeneity. For DW MRI, lesion-to-spinal cord signal intensity ratio and apparent diffusion coefficient were evaluated; for PET/CT, maximum standard uptake value was evaluated. The pooled sensitivities, specificities, diagnostic odds ratios, and areas under the receiver operating characteristic curve (AUCs) for PET/CT and DW MRI were determined along with 95% confidence intervals (CIs). Results Thirty-seven studies met the inclusion criteria, with a total of 4224 participants and 4463 lesions (3090 malignant lesions [69.2%]). In the primary analysis of joint DW MRI and PET/CT studies (n = 6), DW MRI had a pooled sensitivity and specificity of 83% (95% CI: 75%, 89%) and 91% (95% CI: 80%, 96%), respectively, compared with 78% (95% CI: 70%, 84%) (P = .01 vs DW MRI) and 81% (95% CI: 72%, 88%) (P = .056 vs DW MRI) for PET/CT. DW MRI yielded an AUC of 0.93 (95% CI: 0.90, 0.95), versus 0.86 (95% CI: 0.83, 0.89) for PET/CT (P = .001). The diagnostic odds ratio of DW MRI (50 [95% CI: 19, 132]) was superior to that of PET/CT (15 [95% CI: 7, 32]) (P = .006). Conclusion The diagnostic performance of diffusion-weighted MRI is comparable or superior to that of fluorine 18 fluorodeoxyglucose PET/CT in the differentiation of malignant and benign pulmonary lesions. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Schiebler in this issue.

Multiparametric Magnetic Resonance Imaging in the Assessment of Pulmonary Hypertension: Initial Experience of a One-Stop Study.

INTRODUCTION: Our goal was to assess the diagnostic performance of magnetic resonance imaging (MRI) as a single method to diagnose pulmonary hypertension (PH) compared to right heart catheterization (RHC), computed tomography (CT), and ventilation/perfusion (V/Q) scintigraphy. METHODS: We identified 35 patients diagnosed with PH by RHC in our institution who have also undergone a CT, a scintigraphy, and an MRI within a month. All cases were discussed in multidisciplinary meetings. We performed correlations between the MRI-derived hemodynamic parameters and those from RHC. The sensitivity and specificity of MRI were determined to identify its diagnostic performance to identify chronic thromboembolic pulmonary hypertension (CTEPH) and interstitial lung disease PH. The gold standard reference for the diagnosis of CTEPH and ILD was based on a review of multimodality imaging (V/Q scintigraphy and CT scan) and clinical findings. RESULTS: Our results showed a good correlation between the hemodynamic parameters of cardiac MRI and RHC. Pulmonary vascular resistance had the best correlation between both methods (r = 0.923). The sensitivity and specificity of MRI to diagnose CTEPH was 100 and 96.8%, respectively. For the ILD-related PH, the MRI yielded a sensitivity of 60.0% and a specificity of 100%. Additionally, cardiac MRI was able to confirm all cases of PAH due to congenital heart disease initially detected by echocardiography. CONCLUSIONS: MRI represents a promising imaging modality as an initial, single-shot study, for patients with suspected PH with the advantages of being non-invasive and having no radiation exposure.

Correction to: Multiparametric Magnetic Resonance Imaging in the Assessment of Pulmonary Hypertension: Initial Experience of a One-Stop Study.

The original version of this article unfortunately contained a mistake. There is a typo in the coauthor name, it should be Stephan Altmayer.

Advances in Imaging and Automated Quantification of Malignant Pulmonary Diseases: A State-of-the-Art Review.

Quantitative imaging in lung cancer is a rapidly evolving modality in radiology that is changing clinical practice from a qualitative analysis of imaging features to a more dynamic, spatial, and phenotypical characterization of suspected lesions. Some quantitative parameters, such as the use of 18F-FDG PET/CT-derived standard uptake values (SUV), have already been incorporated into current practice as it provides important information for diagnosis, staging, and treatment response of patients with lung cancer. A growing body of evidence is emerging to support the use of quantitative parameters from other modalities. CT-derived volumetric assessment, CT and MRI lung perfusion scans, and diffusion-weighted MRI are some of the examples. Software-assisted technologies are the future of quantitative analyses in order to decrease intra- and inter-observer variability. In the era of "big data", widespread incorporation of radiomics (extracting quantitative information from medical images by converting them into minable high-dimensional data) will allow medical imaging to surpass its current status quo and provide more accurate histological correlations and prognostic value in lung cancer. This is a comprehensive review of some of the quantitative image methods and computer-aided systems to the diagnosis and follow-up of patients with lung cancer.

Use of MDCT to Assess the Results of Bronchial Thermoplasty.

OBJECTIVE: The purpose of this study was to evaluate the use of MDCT to assess response to bronchial thermoplasty treatment for severe persistent asthma. MATERIALS AND METHODS: MDCT data from 26 patients with severe persistent asthma who underwent imaging before and after bronchial thermoplasty were analyzed retrospectively. Changes in the following parameters were assessed: total lung volume, mean lung density, airway wall thickness, CT air trapping index (attenuation < -856 HU), and expiratory-inspiratory ratio of mean lung density (E/I index). Asthma Quality of Life Questionnaire score changes were also assessed. RESULTS: Median total lung volumes before and after bronchial thermoplasty were 2668 mL (range, 2226-3096 mL) and 2399 mL (range, 1964-2802 mL; p = 0.08), respectively. Patients also showed a pattern of obstruction improvement in air trapping values (median before thermoplasty, 14.25%; median after thermoplasty, 3.65%; p < 0.001] and in mean lung density values ± SD (before thermoplasty, -702 ± 72 HU; after thermoplasty, -655 ± 66 HU; p < 0.01). Median airway wall thickness also decreased after bronchial thermoplasty (before thermoplasty, 1.5 mm; after thermoplasty, 1.1 mm; p < 0.05). There was a mean Asthma Quality of Life Questionnaire overall score change of 1.00 ± 1.35 (p < 0.001), indicating asthma clinical improvement. CONCLUSION: Our study showed improvement in CT measurements after bronchial thermoplasty, along with Asthma Quality of Life Questionnaire score changes. Thus, MDCT could be useful for imaging evaluation of patients undergoing this treatment.

Magnetic Resonance Imaging of Pulmonary Embolism: Diagnostic Accuracy of Unenhanced MR and Influence in Mortality Rates.

OBJECTIVES: We evaluated the diagnostic value for pulmonary embolism (PE) of the True fast imaging with steady-state precession (TrueFISP) MRI, a method that allows the visualization of pulmonary vasculature without breath holding or intravenous contrast. METHODS: This is a prospective investigation including 93 patients with suspected PE. All patients underwent TrueFISP MRI after undergoing CT pulmonary angiography (CTPA). Two independent readers evaluated each MR study, and consensus was obtained. CTPA results were analysed by a third independent reviewer and these results served as the reference standard. A fourth radiologist was responsible for evaluating if lesions found on MRI for both analysis were the same and if these were the correspondent lesions on the CTPA. Sensitivity, specificity, predictive values and accuracy were calculated. Evidence for death from PE within the 1-year follow-up was also assessed. RESULTS: Two patients could not undergo the real-time MRI and were excluded from the study. PE prevalence was 22%. During the 1-year follow-up period, eight patients died, whereas PE was responsible for 12.5% of cases. Between patients who developed PE, only 5% died due to this condition. There were no differences between MR and CT embolism detection in these subjects. MR sequences had a sensitivity of 85%, specificity was 98.6% and accuracy was 95.6%. Agreement between readers was high (κ= 0.87). CONCLUSIONS: Compared with contrast-enhanced CT, unenhanced MR sequences demonstrate good accuracy and no differences in the mortality rates in 1 year were detected.

"Pulmonary Vein Sign" for Pulmonary Embolism Diagnosis in Computed Tomography Angiography.

PURPOSES: Considering that pulmonary arterial obstruction decreases venous flow, we hypothesized that filling defects in pulmonary veins can be identified in areas adjacent to pulmonary embolism (PE). This sign was named the "pulmonary vein sign" (PVS), and we evaluated its prevalence and performance for PE diagnosis in computed tomography pulmonary angiography (CTPA). METHODS: This retrospective study enrolled consecutive patients with clinical suspicion of PE who underwent CTPA scan. The PVS was defined by the following criteria: (a) presence of a homogeneous filling defect of at least 2 cm in a pulmonary vein; (b) attenuation of the left atrium > 160 Hounsfield units. Using the cases that presented PE on CTPA as reference, sensitivity, specificity, and positive and negative predictive values were calculated for PVS. RESULTS: In total, 119 patients (73 female; mean age, 62 years) were included in this study. PE was diagnosed in 44 (35.8%) patients. The PVS was present in 16 out of 44 patients with PE. Sensitivity was 36.36% (95% confidence interval (CI) 22.83-52.26%); specificity, 98.67% (95% CI 91.79-99.93%); positive predictive value, 94.12% (95% CI 69.24-99.69%); negative predictive value, 72.55% (95% CI 62.67-80.70%). The Kappa index for the PVS was good (0.801; 95% CI 0.645-0.957). PVS was correlated with lobar and segmental pulmonary embolism (p < 0.01). CONCLUSION: Despite a low sensitivity, presence of the pulmonary vein sign was highly specific for PE, with a good agreement between readers. This sign could contribute for PE diagnosis on CTPA studies.

Performance of magnetic resonance imaging in pulmonary fungal disease compared to high-resolution computed tomography.

To evaluate the performance of magnetic resonance imaging (MRI) compared to computed tomography (CT) in patients diagnosed with pulmonary mycosis. We prospectively included 21 patients diagnosed with pulmonary mycosis between January 2013 and October 2014. Inclusion criteria were presence of respiratory symptoms, histopathological diagnosis of mycosis and absence of mycosis treatment. Reviewers identified one predominant imaging pattern per patient: nodular, reticular or airspace pattern. Afterwards, all CT findings were analysed separately per lobe and compared to MRI. Nodular pattern was the most common found (CT: 76.20%; MRI: 80.96%), followed by airspace pattern (CT and MRI: 9.52%) and reticular (CT: 9.52%; MRI: 4.76%). Compared to CT, MRI performance varied according to radiological finding and pulmonary region. For nodules, MRI presented high sensitivity (100% [95% CI: 93.52-100]) and specificity (100% [95% CI: 92.00-100]). For bronchiectasis and septal thickening, there were poorer positive predictive values (33.33% [95% CI: 1.77-87.47]; and 83.33% [95% CI: 50.88-97.06] respectively). As specificity and negative predictive value had superior results than sensitivity and positive predictive value, rather than for diagnosis of this condition, MRI might be more considered for the follow-up of patients with pulmonary mycosis, an alternative to multiple radiation exposures with CT follow-up.

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.