CYB5R3 functions as a tumor suppressor by inducing ER stress-mediated apoptosis in lung cancer cells via the PERK-ATF4 and IRE1α-JNK pathways.

Cytochrome b5 reductase 3 (CYB5R3) is involved in various cellular metabolic processes, including fatty acid synthesis and drug metabolism. However, the role of CYB5R3 in cancer development remains poorly understood. Here, we show that CYB5R3 expression is downregulated in human lung cancer cell lines and tissues. Adenoviral overexpression of CYB5R3 suppresses lung cancer cell growth in vitro and in vivo. However, CYB5R3 deficiency promotes tumorigenesis and metastasis in mouse models. Transcriptome analysis revealed that apoptosis- and endoplasmic reticulum (ER) stress-related genes are upregulated in CYB5R3-overexpressing lung cancer cells. Metabolomic analysis revealed that CYB5R3 overexpression increased the production of nicotinamide adenine dinucleotide (NAD+) and oxidized glutathione (GSSG). Ectopic CYB5R3 is mainly localized in the ER, where CYB5R3-dependent ER stress signaling is induced via activation of protein kinase RNA-like ER kinase (PERK) and inositol-requiring enzyme 1 alpha (IRE1α). Moreover, NAD+ activates poly (ADP-ribose) polymerase16 (PARP16), an ER-resident protein, to promote ADP-ribosylation of PERK and IRE1α and induce ER stress. In addition, CYB5R3 induces the generation of reactive oxygen species and caspase-9-dependent intrinsic cell death. Our findings highlight the importance of CYB5R3 as a tumor suppressor for the development of CYB5R3-based therapeutics for lung cancer.

CellTrackVis: interactive browser-based visualization for analyzing cell trajectories and lineages.

BACKGROUND: Automatic cell tracking methods enable practitioners to analyze cell behaviors efficiently. Notwithstanding the continuous development of relevant software, user-friendly visualization tools have room for further improvements. Typical visualization mostly comes with main cell tracking tools as a simple plug-in, or relies on specific software/platforms. Although some tools are standalone, limited visual interactivity is provided, or otherwise cell tracking outputs are partially visualized. RESULTS: This paper proposes a self-reliant visualization system, CellTrackVis, to support quick and easy analysis of cell behaviors. Interconnected views help users discover meaningful patterns of cell motions and divisions in common web browsers. Specifically, cell trajectory, lineage, and quantified information are respectively visualized in a coordinated interface. In particular, immediate interactions among modules enable the study of cell tracking outputs to be more effective, and also each component is highly customizable for various biological tasks. CONCLUSIONS: CellTrackVis is a standalone browser-based visualization tool. Source codes and data sets are freely available at http://github.com/scbeom/celltrackvis with the tutorial at http://scbeom.github.io/ctv_tutorial .

Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.

No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra-low-dose chest computed tomography, reconstructed using deep learning-based algorithms. This is an important issue in lung cancer screening. Our study aimed to investigate the accuracy of semiautomatic volume measurement of solid nodules and ground-glass nodules, using two deep learning-based image reconstruction algorithms (Truefidelity and ClariCT.AI), compared with iterative reconstruction (ASiR-V) in low-dose and ultra-low-dose settings. We performed computed tomography scans of solid nodules and ground-glass nodules of different diameters placed in a phantom at four radiation doses (120 kVp/220 mA, 120 kVp/90 mA, 120 kVp/40 mA, and 80 kVp/40 mA). Each scan was reconstructed using Truefidelity, ClariCT.AI, and ASiR-V. The solid nodule and ground-glass nodule volumes were measured semiautomatically. The gold-standard volumes could be calculated using the diameter since all nodule phantoms are perfectly spherical. Subsequently, absolute percentage measurement errors of the measured volumes were calculated. Image noise was also calculated. Across all nodules at all dose settings, the absolute percentage measurement errors of Truefidelity and ClariCT.AI were less than 11%; they were significantly lower with Truefidelity or ClariCT.AI than with ASiR-V (all P<0.05). The absolute percentage measurement errors for the smallest solid nodule (3 mm) reconstructed by Truefidelity or ClariCT.AI at all dose settings were significantly lower than those of this nodule reconstructed by ASiR-V (all P<0.05). Furthermore, the lowest absolute percentage measurement errors for ground-glass nodules were observed with Truefidelity or ClariCT.AI at all dose settings. The absolute percentage measurement errors for ground-glass nodules reconstructed with Truefidelity at ultra-low-dose settings were significantly lower than those of all sizes of ground-glass nodules reconstructed with ASiR-V (all P<0.05). Image noise was lowest with Truefidelity (all P<0.05). In conclusion, the deep learning-based algorithms were more accurate for volume measurements of both solid nodules and ground-glass nodules than ASiR-V at both low-dose and ultra-low-dose settings.

A Novel Mutation in the MBTPS2 Gene Resulting in Ichthyosis Follicularis, Atrichia, and Photophobia Syndrome.

Ichthyosis follicularis, atrichia, and photophobia (IFAP) syndrome is a rare genetic disorder caused by mutations in the MBTPS2 gene. It is characterized by ichthyosis and alopecia from birth. Photophobia may be present in infancy or early childhood. Its mode of inheritance is X-linked recessive; thus, it mostly affects male. The disease severity varies, ranging from mild cases limited to the skin to the severe variant involving multiple extracutaneous features. A 7-year-old boy presented with scanty hair on scalp and eyebrows at birth. On physical examination, scaly patches were observed on the whole body and spiky follicular hyperkeratotic papules were observed on the face and trunk. He also suffered from severe photophobia. Histopathological examination of the scalp showed miniaturized hair follicles without perifollicular fibrosis. Genetic analysis revealed a novel mutation in the MBTPS2 gene which was a homozygous missense mutation of c.245T>C leading to an amino-acid substitution from phenylalanine to serine (p.Phe82Ser). We diagnosed this patient with IFAP syndrome. To date, 25 pathogenic MBTPS2 gene mutations have been identified. To our knowledge, c.245T>C is a novel homozygous missense mutation in the MBTPS2 gene, which has not been reported in Human Gene Mutation Database, ClinVar Database, and Leiden Open Variation Database. Previous reports suggested genotype-phenotype correlations in the MBTPS2 gene mutations. Supported by a previous notion that genotype correlates with phenotype, this novel mutation can be a predictive factor for the mild form of IFAP syndrome, restricted to the classic symptom triad.

Prognosis for Pneumonic-Type Invasive Mucinous Adenocarcinoma in a Single Lobe on CT: Is It Reasonable to Designate It as Clinical T3?

OBJECTIVE: To compare pneumonic-type invasive mucinous adenocarcinoma (pIMA) confined to a single lobe with clinical T2, T3, and T4 stage lung cancer without pathological node metastasis regarding survival after curative surgery and to identify prognostic factors for pIMA. MATERIALS AND METHODS: From January 2010 to December 2017, 41 patients (15 male; mean age ± standard deviation, 66.0 ± 9.9 years) who had pIMA confined to a single lobe on computed tomography (CT) and underwent curative surgery were identified in two tertiary hospitals. Three hundred and thirteen patients (222 male; 66.3 ± 9.4 years) who had non-small cell lung cancer (NSCLC) without pathological node metastasis and underwent curative surgery in one participating institution formed a reference group. Relapse-free survival (RFS) and overall survival (OS) were calculated using the Kaplan-Meier method. Cox proportional hazard regression analysis was performed to identify factors associated with the survival of patients with pIMA. RESULTS: The 5-year RFS and OS rates in patients with pIMA were 33.1% and 56.0%, respectively, compared with 74.3% and 91%, 64.3% and 71.8%, and 46.9% and 49.5% for patients with clinical stage T2, T3, and T4 NSCLC in the reference group, respectively. The RFS of patients with pIMA was comparable to that of patients with clinical stage T4 NSCLC and significantly worse than that of patients with clinical stage T3 NSCLC (p = 0.012). The differences in OS between patients with pIMA and those with clinical stage T3 or T4 NSCLC were not significant (p = 0.11 and p = 0.37, respectively). In patients with pIMA, the presence of separate nodules was a significant factor associated with poor RFS and OS {unadjusted hazard ratio (HR), 4.66 (95% confidence interval [CI], 1.95-11.11), p < 0.001 for RFS; adjusted HR, 4.53 (95% CI, 1.59-12.89), p = 0.005 for OS}. CONCLUSION: The RFS of patients with pIMA was comparable to that of patients with clinical stage T4 lung cancer. Separate nodules on CT were associated with poor RFS and OS in patients with pIMA.

Application of computer-aided diagnosis for Lung-RADS categorization in CT screening for lung cancer: effect on inter-reader agreement.

OBJECTIVES: To evaluate the effects of computer-aided diagnosis (CAD) on inter-reader agreement in Lung Imaging Reporting and Data System (Lung-RADS) categorization. METHODS: Two hundred baseline CT scans covering all Lung-RADS categories were randomly selected from the National Lung Cancer Screening Trial. Five radiologists independently reviewed the CT scans and assigned Lung-RADS categories without CAD and with CAD. The CAD system presented up to five of the most risk-dominant nodules with measurements and predicted Lung-RADS category. Inter-reader agreement was analyzed using multirater Fleiss κ statistics. RESULTS: The five readers reported 139-151 negative screening results without CAD and 126-142 with CAD. With CAD, readers tended to upstage (average, 12.3%) rather than downstage Lung-RADS category (average, 4.4%). Inter-reader agreement of five readers for Lung-RADS categorization was moderate (Fleiss kappa, 0.60 [95% confidence interval, 0.57, 0.63]) without CAD, and slightly improved to substantial (Fleiss kappa, 0.65 [95% CI, 0.63, 0.68]) with CAD. The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% [201/371] vs. 63.6% [232/365]). The proportion of disagreement in nodule size measurement was reduced from 5.1% (102/2000) to 3.1% (62/2000) with the use of CAD (p < 0.001). In 31 cancer-positive cases, substantial management discrepancies (category 1/2 vs. 4A/B) between reader pairs decreased with application of CAD (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004). CONCLUSIONS: Application of CAD demonstrated a minor improvement in inter-reader agreement of Lung-RADS category, while showing the potential to reduce measurement variability and substantial management change in cancer-positive cases. KEY POINTS: • Inter-reader agreement of five readers for Lung-RADS categorization was minimally improved by application of CAD, with a Fleiss kappa value of 0.60 to 0.65. • The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% vs. 63.6%). • In 31 cancer-positive cases, substantial management discrepancies between reader pairs, referring to a difference in follow-up interval of at least 9 months (category 1/2 vs. 4A/B), were reduced in half by application of CAD (32/310 to 16/310) (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004).

Utility of a Deep Learning Algorithm for Detection of Reticular Opacity on Chest Radiography in Patients With Interstitial Lung Disease.

BACKGROUND. Deep learning has been heavily explored for pulmonary nodule detection on chest radiographs. Detection of reticular opacity in interstitial lung disease (ILD) is challenging and may also benefit from a deep learning algorithm (DLA). OBJECTIVE. The purpose of this study was to evaluate the utility of a DLA for detection of reticular opacity on chest radiographs of patients with surgically confirmed ILD. METHODS. This retrospective study included 197 patients (130 men, 67 women; mean age, 62.6 ± 7.6 [SD] years) with surgically proven ILD between January 2017 and December 2018 who underwent preoperative chest radiography and chest CT within a 30-day interval. A total of 197 age- and sex-matched control patients with normal chest radiographs were randomly selected. A commercially available DLA was used to detect lower lobe or subpleural abnormalities; those matching the reticular opacity location on CT were deemed true-positive. Six readers (three thoracic radiologists, three residents) independently reviewed radiographs with and without the DLA for the presence of reticular opacity. Interobserver agreement was assessed. Diagnostic performance was compared among interpretations. Subanalysis was performed according to CT-based classification of the severity of reticular opacity. Performance of the DLA was also assessed on 102 chest radiographs from a second institution (51 patients with ILD, 51 matched patients in the control group). RESULTS. Interobserver agreement was moderate (κ = 0.517) for readers alone and almost perfect (κ = 0.870) for readers using the DLA. Sensitivity, specificity, and accuracy of the DLA for reticular opacity were 98.0%, 99.0%, and 98.5%; of pooled readers alone were 77.3%, 92.3%, and 84.8%; and of readers using the DLA were 93.8%, 97.3%, and 95.6%. All metrics were significantly better (all p ≤ .002) for the DLA and for readers using the DLA than for readers alone. Sensitivity for readers without and with the DLA were 66.7% and 86.8% for mild disease, 84.2% and 98.8% for moderate disease, and 87.3% and 100.0% for severe disease. The DLA had 100.0% accuracy at the second institution. CONCLUSION. The DLA outperformed readers in detection of reticular opacity, and use of the DLA improved reader performance and interobserver agreement. The benefit of the DLA was more notable in sensitivity than in specificity and was maintained in mild disease. CLINICAL IMPACT. Use of the DLA may facilitate detection of reticular opacity on chest radiographs in the early stages of ILD.

Differentiating pulmonary metastasis from benign lung nodules in thyroid cancer patients using dual-energy CT parameters.

OBJECTIVES: To explore the importance of quantitative characteristics of dual-energy CT (DECT) between pulmonary metastasis and benign lung nodules in thyroid cancer. METHODS: In this retrospective study, we identified 63 patients from our institution's database with pathologically proven thyroid cancer who underwent DECT to assess pulmonary metastasis. Among these patients, 22 had 55 pulmonary metastases, and 41 had 97 benign nodules. If nodules showed increased iodine uptake on I-131 single-photon emission computed tomography-computed tomography or increased size in follow-up CT, they were considered metastatic. We compared the clinical findings and DECT parameters of both groups and performed a receiver operating characteristic analysis to evaluate the optimal cutoff values of the DECT parameters. RESULTS: Patients with metastases were significantly older than patients with benign nodules (p = 0.048). The DECT parameters of the metastatic nodules were significantly higher than those of the benign nodules (iodine concentration [IC], 5.61 ± 2.02 mg/mL vs. 1.61 ± 0.98 mg/mL; normalized IC [NIC], 0.60 ± 0.20 vs. 0.16 ± 0.11; NIC using pulmonary artery [NICPA], 0.60 ± 0.44 vs. 0.15 ± 0.11; slope of the spectral attenuation curves [λHU], 5.18 ± 2.54 vs. 2.12 ± 1.39; and Z-effective value [Zeff], 10.0 ± 0.94 vs. 8.79 ± 0.75; all p < 0.001). In the subgroup analysis according to nodule size, all DECT parameters of the metastatic nodules in all subgroups were significantly higher than those of the benign nodules (all p < 0.05). The cutoff values for IC, NIC, λHU, NICPA, and Zeff for diagnosing metastases were 3.10, 0.29, 3.57, 0.28, and 9.34, respectively (all p < 0.001). CONCLUSIONS: DECT parameters can help to differentiate metastatic and benign lung nodules in thyroid cancer. KEY POINTS: • DECT parameters can help to differentiate metastatic and benign lung nodules in patients with thyroid cancer. • DECT parameters showed a significant difference between benign lung nodules and lung metastases, even for nodules with diameters ≥ 3 mm and < 5 mm. • Among the DECT parameters, the highest diagnostic accuracy for differentiating pulmonary metastases from benign lung nodules was achieved with the NIC and IC, followed by the NICPA and λHU, and their cutoff values were 0.29, 3.10, 0.28, and 3.57, respectively.

Decolorization of Textile Dye by Spore Surface Displayed Small Laccase for the Enhanced Thermal Stability and Robust Repeated Reaction.

In this study, we tried to decolorize synthetic dyes using small laccase (SLAC) from Streptomyces coelicolor, which is resistant to pH, temperature change, and traditional inhibitors for the actual industrial applications using spore surface display system. We inserted SLAC-His6 tag at the C-terminal of CotE anchoring motif. The proper surface expression of CotE-SLAC fusion protein on the surface of Bacillus subtilis spore was verified with flow cytometry using FITC labeled anti-His6 tag antibody. After 6 h of reaction, more than 90% of Indigo carmine was decomposed using recombinant SLAC displaying Bacillus spore, whereas less than 10% of Indigo carmine was decomposed with wild type spore. Over 70% of laccase activity was retained with recombinant SLAC displaying spore, which was heat-treated for 3 h at 90°C. For eight rounds of repeated decomposition of Indigo carmine, no significant decrease of enzymatic activity was observed. This showed the robust characteristics of spore display format for repeated and harsh condition reactions.

Prognostic Value of Computed Tomographic Coronary Angiography for Long-Term Major Adverse Cardiac Events after Liver Transplantation.

Computed tomographic coronary angiography (CTCA) has prognostic value for early major adverse cardiac events (MACEs) after liver transplantation. However, the association between CTCA and long-term MACEs in liver transplant (LT) recipients remains unknown. We evaluated the association between CTCA and long-term MACEs within 5 years after living donor liver transplantation (LDLT). A total of 628 LDLT recipients who underwent CTCA were analyzed between 2010 and 2012. MACEs were investigated within 5 years after LDLT. The factors associated with long-term MACEs in transplant recipients were evaluated. Only 48 (7.6%) patients developed MACEs. In the Fine and Gray competing risk regression, a coronary artery calcium score (CACS) of >400 combined with obstructive coronary artery disease (CAD) (subdistribution hazard ratio: 5.01, 95% confidence interval: 2.37-10.58, p < 0.001), age (1.05, 1.01-1.10, p = 0.018), diabetes mellitus (2.43, 1.37-4.29, p = 0.002), dyslipidemia (2.45, 1.23-4.70, p = 0.023), and creatinine (1.19, 1.08-1.30, p < 0.001) were independently associated with long-term MACEs. CACS (>400) combined with obstructive CAD may be associated with MACEs within 5 years after LDLT, suggesting the importance of preoperative noninvasive CTCA in LT recipients. The evaluation of coronary artery stenosis on CTCA combined with CACS may have a prognostic value for long-term MACEs in LT recipients.

Cryosurgery as a Minimally Invasive Alternative Treatment for a Patient with Erosive Adenomatosis of the Nipple.

Erosive adenomatosis of the nipple (EAN), also known as nipple adenoma, florid papillomatosis, or papillary adenoma of the nipple, is a benign neoplasm originating from a lactiferous duct of the breast. Although the potential for malignant change is invariably negligible, the nature of the disease is quite intractable despite several treatment methods. Surgical excision is known as the treatment of choice, but this invasive approach is generally not acceptable to the vast majority of patients due to the cosmetic outcomes. Cryosurgery could be an alternative choice to preserve the structure of the nipple-areola complex, though its application has not been studied due to the paucity of cases. A 22-year-old female presented with a unilateral, crater-like erosion of the left nipple with serosanguineous discharge. The skin biopsy revealed proliferation of tubular structures, which corresponded to EAN. She was treated with 4 sessions of cryosurgery (open cryospray with liquid nitrogen) over 6 months, and the skin lesion resolved completely without any recurrence for 12 months. Although further study is required to determine the optimal treatment regimen for EAN, cryosurgery should be considered as an effective option to surgical excision.

CT radiomics-based prediction of anaplastic lymphoma kinase and epidermal growth factor receptor mutations in lung adenocarcinoma.

PURPOSE: To develop and validate a CT-based radiomic model to simultaneously diagnose anaplastic lymphoma kinase (ALK) rearrangements and epidermal growth factor receptor (EGFR) mutation status of lung adenocarcinoma and to assess whether peritumoural radiomic features add value in the prediction of mutation status. METHODS: 503 patients with pathologically proven lung adenocarcinoma containing information on the mutation status were retrospectively included. Intratumoural and peritumoural radiomic features of the primary lesion were extracted from CT. We proposed two-level stepwise binary radiomics-based classification models to diagnose ALK (step1) and EGFR mutation status (step2). The performance of proposed models and added value of peritumoural radiomic features were evaluated by using the areas under receiver operating characteristic curves (AUC) and Obuchowski index in the development and validation sets. RESULTS: Regarding the prediction of ALK rearrangement, the diagnostic performance of the intratumoural radiomic model showed the AUC of 0.77 and 0.68 for the development and validation sets, respectively. As for EGFR mutation, the diagnostic performance of the intratumoural radiomic model showed the AUCs of 0.64 and 0.62 for the development and validation sets, respectively. The radiomics added value to the model based on clinical features (development set [radiomics + clinical model vs. clinical model]: Obuchowski index, 0.76 vs. 0.66, p < 0.001; validation set: 0.69 vs. 0.61, p = 0.075). Adding peritumoural features resulted in no improvement in terms of model performance. CONCLUSION: The CT radiomics-based model allowed the simultaneous prediction of the presence of ALK and EGFR mutations while adding value to the clinical features.

Novel Resectable Myocardial Model Using Hybrid Three-Dimensional Printing and Silicone Molding for Mock Myectomy for Apical Hypertrophic Cardiomyopathy.

OBJECTIVE: We implemented a novel resectable myocardial model for mock myectomy using a hybrid method of three-dimensional (3D) printing and silicone molding for patients with apical hypertrophic cardiomyopathy (ApHCM). MATERIALS AND METHODS: From January 2019 through May 2020, 3D models from three patients with ApHCM were generated using the end-diastolic cardiac CT phase image. After computer-aided designing of measures to prevent structural deformation during silicone injection into molding, 3D printing was performed to reproduce anatomic details and molds for the left ventricular (LV) myocardial mass. We compared the myocardial thickness of each cardiac segment and the LV myocardial mass and cavity volumes between the myocardial model images and cardiac CT images. The surgeon performed mock surgery, and we compared the volume and weight of the resected silicone and myocardium. RESULTS: During the mock surgery, the surgeon could determine an ideal site for the incision and the optimal extent of myocardial resection. The mean differences in the measured myocardial thickness of the model (0.3, 1.0, 6.9, and 7.3 mm in the basal, midventricular, apical segments, and apex, respectively) and volume of the LV myocardial mass and chamber (36.9 mL and 14.8 mL, 2.9 mL and -9.4 mL, and 6.0 mL and -3.0 mL in basal, mid-ventricular and apical segments, respectively) were consistent with cardiac CT. The volume and weight of the resected silicone were similar to those of the resected myocardium (6 mL [6.2 g] of silicone and 5 mL [5.3 g] of the myocardium in patient 2; 12 mL [12.5 g] of silicone and 11.2 mL [11.8 g] of the myocardium in patient 3). CONCLUSION: Our 3D model created using hybrid 3D printing and silicone molding may be useful for determining the extent of surgery and planning surgery guided by a rehearsal platform for ApHCM.

Effectiveness of radiologist training in improving reader agreement for Lung-RADS 4X categorization.

OBJECTIVES: To identify the agreement on Lung CT Screening Reporting and Data System 4X categorization between radiologists and an expert-adjudicated reference standard and to investigate whether training led to improvement of the agreement measures and diagnostic potential for lung cancer. METHODS: Category 4 nodules in the Korean Lung Cancer Screening Project were identified retrospectively, and each 4X nodule was matched with one 4A or 4B nodule. An expert panel re-evaluated the categories and determined the reference standard. Nineteen radiologists were asked to determine the presence of CT features of malignancy and 4X categorization for each nodule. A review was performed in two sessions, and training material was given after session 1. Agreement on 4X categorization between radiologists and the expert-adjudicated reference standard and agreement between radiologist-assessed 4X categorization and lung cancer diagnosis were evaluated. RESULTS: The 48 expert-adjudicated 4X nodules and 64 non-4X nodules were evenly distributed in each session. The proportion of category 4X decreased after training (56.4% ± 16.9% vs. 33.4% ± 8.0%; p < 0.001). Cohen's κ indicated poor agreement (0.39 ± 0.16) in session 1, but agreement improved in session 2 (0.47 ± 0.09; p = 0.03). The increase in agreement in session 2 was observed among inexperienced radiologists (p < 0.05), and experienced and inexperienced reviewers exhibited comparable agreement performance in session 2 (p > 0.05). All agreement measures between radiologist-assessed 4X categorization and lung cancer diagnosis increased in session 2 (p < 0.05). CONCLUSION: Radiologist training can improve reader agreement on 4X categorization, leading to enhanced diagnostic performance for lung cancer. KEY POINTS: • Agreement on 4X categorization between radiologists and an expert-adjudicated reference standard was initially poor, but improved significantly after training. • The mean proportion of 4X categorization by 19 radiologists decreased from 56.4% ± 16.9% in session 1 to 33.4% ± 8.0% in session 2. • All agreement measures between the 4X categorization and lung cancer diagnosis increased significantly in session 2, implying that appropriate training and guidance increased the diagnostic potential of category 4X.

COVID-19 infection with asymptomatic or mild disease severity in young patients: Clinical course and association between prevalence of pneumonia and viral load.

Few studies have focused on clinical courses or viral loads in young asymptomatic or mild patients with COVID-19 infection. We sought to better understand the clinical course and association between viral load and prevalence of pneumonia in young COVID-19 patients with asymptomatic or mild disease severity. In this retrospective study, 106 COVID-19 young patients with asymptomatic or mild disease severity were analyzed for clinical characteristics, clinical course, prevalence of radiologically proven pneumonia and viral load. The cut-off value of viral load for presence of pneumonia was also investigated. The mean age was 28.0±9.3 years. Eleven patients (10.4%) experienced viral remission within one week of diagnosis, but one (0.9%) transferred to the hospital due to aggravation of pneumonia. Patients with pneumonia had significantly higher viral load than those without, and the cut-off value of the Ct value for presence of pneumonia were 31.38. The patients with pneumonia had significantly slower recovery times than those without. Diarrhea was significantly more common in patients with pneumonia than patients without pneumonia. In conclusion, most young asymptomatic and mildly symptomatic patients showed stable clinical course. There were significant differences in viral load and recovery times between patients with and without pneumonia.

New Bacterial Surface Display System Development and Application Based on Bacillus subtilis YuaB Biofilm Component as an Anchoring Motif.

Bacterial surface display system has been adopted in various biotechnological applications. In the case of Bacillus subtilis, most of the studies have been developed using spore based surface display system utilizing the inherent rigidity of spore against heat, alkali, and shear stress. But, spore harvest, purification and separation need additional cost and labor. To eliminate this procedure and to use the gram-positive nature of B. subtilis, YuaB, which is one of the major B. subtilis biofilm components and locates in the cell wall, based cell surface display system, is developed. P43 promoter driven overexpression of YuaB-His6 tag does not hamper bacterial cell growth and promoted biofilm formation of recombinant strain. Flow cytometry of recombinant strain and its protoplast using FITC-Anti His6 antibody, verified that YuaB locate in plasma membrane and protrude to the outside of cell wall, which means YuaB can be used as very efficient anchoring motif. Using surface expressed YuaB-His6 tag, removal of divalent metal ion, Cu2+ and Ni2+, was tried to test its possibility for the environmental application of developed system.

Use of a Commercially Available Deep Learning Algorithm to Measure the Solid Portions of Lung Cancer Manifesting as Subsolid Lesions at CT: Comparisons with Radiologists and Invasive Component Size at Pathologic Examination.

Background The solid portion size of lung cancer lesions manifesting as subsolid lesions is key in their management, but the automatic measurement of such lesions by means of a deep learning (DL) algorithm needs evaluation. Purpose To evaluate the performance of a commercially available DL algorithm for automatic measurement of the solid portion of surgically proven lung adenocarcinomas manifesting as subsolid lesions. Materials and Methods Surgically proven lung adenocarcinomas manifesting as subsolid lesions on CT images between January 2018 and December 2018 were retrospectively included. Five radiologists independently measured the maximal axial diameter of the solid portion of lesions. The DL algorithm automatically segmented and measured the maximal axial diameter of the solid portion. Reader measurements, software measurements, and invasive component size at pathologic examination were compared by using intraclass correlation coefficient (ICC) and Bland-Altman plots. Results A total of 448 patients (mean age, 63 years ± 10 [standard deviation]; 264 women) with 448 lesions were evaluated (invasive component size, 3-65 mm). The measurement agreements between each radiologist and the DL algorithm were very good (ICC range, 0.82-0.89). When a radiologist was replaced with the DL algorithm, the ICCs ranged from 0.87 to 0.90, with an ICC of 0.90 among five radiologists. The mean difference between the DL algorithm and each radiologist ranged from -3.7 to 1.5 mm. The widest 95% limit of agreement between the DL algorithm and each radiologist (-15.7 to 8.3 mm) was wider than pairwise comparisons of radiologists (-7.7 to 13.0 mm). The agreement between the DL algorithm and invasive component size at pathologic evaluation was good, with an ICC of 0.67. Measurements by the DL algorithm (mean difference, -6.0 mm) and radiologists (mean difference, -7.5 to -2.3 mm) both underestimated invasive component size. Conclusion Automatic measurements of solid portions of lung cancer manifesting as subsolid lesions by the deep learning algorithm were comparable with manual measurements and showed good agreement with invasive component size at pathologic evaluation. © RSNA, 2021 Online supplemental material is available for this article.

Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.

OBJECTIVES: To evaluate a deep learning-based model using model-generated segmentation masks to differentiate invasive pulmonary adenocarcinoma (IPA) from preinvasive lesions or minimally invasive adenocarcinoma (MIA) on CT, making comparisons with radiologist-derived measurements of solid portion size. METHODS: Four hundred eleven subsolid nodules (SSNs) (120 preinvasive lesions or MIAs and 291 IPAs) in 333 patients who underwent surgery between June 2010 and August 2016 were retrospectively included to develop the model (370 SSNs in 293 patients for training and 41 SSNs in 40 patients for tuning). Ninety SSNs of 2 cm or smaller (45 preinvasive lesions or MIAs and 45 IPAs) resected in 2018 formed a validation set. Six radiologists measured the solid portion of each nodule. Performances of the model and radiologists were assessed using receiver operating characteristics curve analysis. RESULTS: The deep learning model differentiated IPA from preinvasive lesions or MIA with areas under the curve (AUCs) of 0.914, 0.956, and 0.833 for the training, tuning, and validation sets, respectively. The mean AUC of the radiologists was 0.835 in the validation set, without significant differences between radiologists and the model (p = 0.97). The sensitivity, specificity, and accuracy of the model were 71% (32/45), 87% (39/45), and 79% (71/90), respectively, whereas the corresponding values of the radiologists were 75.2% (203/270), 76.7% (207/270), and 75.9% (410/540) with a 5-mm threshold for the solid portion size. CONCLUSIONS: The performance of the model for differentiating IPA from preinvasive lesions or MIA was comparable to that of the radiologists' measurements of solid portion size. KEY POINTS: • A deep learning-based model differentiated IPA from preinvasive lesions or MIA with AUCs of 0.914 and 0.956 for the training and tuning sets, respectively. • In the validation set including subsolid nodules of 2 cm or smaller, the model showed an AUC of 0.833, being on par with the performance of the solid portion size measurements made by the radiologists (AUC, 0.835; p = 0.97). • SSNs with a solid portion measuring > 10 mm on CT showed a high probability of being IPA (positive predictive value, 93.5-100.0%).

Computer-aided Detection of Subsolid Nodules at Chest CT: Improved Performance with Deep Learning-based CT Section Thickness Reduction.

Background Studies on the optimal CT section thickness for detecting subsolid nodules (SSNs) with computer-aided detection (CAD) are lacking. Purpose To assess the effect of CT section thickness on CAD performance in the detection of SSNs and to investigate whether deep learning-based super-resolution algorithms for reducing CT section thickness can improve performance. Materials and Methods CT images obtained with 1-, 3-, and 5-mm-thick sections were obtained in patients who underwent surgery between March 2018 and December 2018. Patients with resected synchronous SSNs and those without SSNs (negative controls) were retrospectively evaluated. The SSNs, which ranged from 6 to 30 mm, were labeled ground-truth lesions. A deep learning-based CAD system was applied to SSN detection on CT images of each section thickness and those converted from 3- and 5-mm section thickness into 1-mm section thickness by using the super-resolution algorithm. The CAD performance on each section thickness was evaluated and compared by using the jackknife alternative free response receiver operating characteristic figure of merit. Results A total of 308 patients (mean age ± standard deviation, 62 years ± 10; 183 women) with 424 SSNs (310 part-solid and 114 nonsolid nodules) and 182 patients without SSNs (mean age, 65 years ± 10; 97 men) were evaluated. The figures of merit differed across the three section thicknesses (0.92, 0.90, and 0.89 for 1, 3, and 5 mm, respectively; P = .04) and between 1- and 5-mm sections (P = .04). The figures of merit varied for nonsolid nodules (0.78, 0.72, and 0.66 for 1, 3, and 5 mm, respectively; P < .001) but not for part-solid nodules (range, 0.93-0.94; P = .76). The super-resolution algorithm improved CAD sensitivity on 3- and 5-mm-thick sections (P = .02 for 3 mm, P < .001 for 5 mm). Conclusion Computer-aided detection (CAD) of subsolid nodules performed better at 1-mm section thickness CT than at 3- and 5-mm section thickness CT, particularly with nonsolid nodules. Application of a super-resolution algorithm improved the sensitivity of CAD at 3- and 5-mm section thickness CT. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Goo in this issue.

Nitrates administered by spray versus tablet: comparison of coronary vasodilation on CT angiography.

OBJECTIVES: To compare the coronary vasodilation effects of spray with those induced by tablet administration in coronary CT angiography (CCTA). METHODS: A total of 2024 patients who underwent CCTA were identified for this retrospective study, including 828 patients with spray (spray group) and 1169 with tablets (tablet group). Of these, 93 patients underwent CCTA at least twice using both spray and tablets. The number of measurable segments and diameters of all 18 segments was measured. The number of measurable segments was compared between groups. RESULTS: No statistically significant differences were evident between these two groups in terms of clinical characteristics. All coronary segments except the ramus intermedius (RI) and left posterior descending artery (L-PDA) were significantly larger in the spray group than in the tablet group (all p < 0.001). In peripheral and branch vessels, as well as in central and main coronary arteries, the diameters were significantly larger in the spray group than in the tablet group (all p < 0.001). Although not always statistically significant, all coronary segments tended to be more measurable on CCTA with spray than with tablet. In the subgroup that underwent CCTA twice using both spray and tablets, all coronary segments except the RI, obtuse marginal artery 2 (OM2), and L-PDA were significantly larger in the spray group than in the tablet group (all p < 0.05). CONCLUSION: Lingual isosorbide dinitrate (ISDN) spray was more efficacious than sublingual nitroglycerin (NTG) tablets in coronary vasodilation for CCTA. Therefore, lingual ISDN spray should be preferred over sublingual NTG tablets for CCTA. KEY POINTS: • Lingual ISDN spray was more efficacious than sublingual NTG tablet for coronary vasodilation in coronary CT angiography, even in elderly patients. • The diameters of all coronary segments except RI and L-PDA were significantly larger, and there were significantly more coronary segments greater than 1.5 mm, except RI and L-PDA, in the spray group than in the tablet group in the whole study group. • Even in peripheral and branch vessels, the diameters of coronary arteries were significantly larger in the spray group than in the tablet group, and they were also larger in elderly patients.