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Quantitative radiomic and iodine imaging features have been explored for diagnosis and characterization of tumors. In this work, we invistigate combined whole-lesion radiomic and iodine analysis for the differentiation of pulmonary tumors on contrast-enhanced dual-energy CT (DECT) chest images. 100 biopsy-proven solid lung lesions on contrast-enhanced DECT chest exams within 3 months of histopathologic sampling were identified. Lesions were volumetrically segmented using open-source software. Lesion segmentations and iodine density volumes were loaded into a radiomics prototype for quantitative analysis. Univariate analysis was performed to determine differences in volumetric iodine concentration (mean, median, maximum, minimum, 10th percentile, 90th percentile) and first and higher order radiomic features (n = 1212) between pulmonary tumors. Analyses were performed using a 2-sample t test, and filtered for false discoveries using Benjamini–Hochberg method. 100 individuals (mean age 65 ± 13 years; 59 women) with 64 primary and 36 metastatic lung lesions were included. Only one iodine concentration parameter, absolute minimum iodine, significantly differed between primary and metastatic pulmonary tumors (FDR-adjusted p = 0.015, AUC 0.69). 310 (FDR-adjusted p = 0.0008 to p = 0.0491) radiomic features differed between primary and metastatic lung tumors. Of these, 21 features achieved AUC ≥ 0.75. In subset analyses of lesions imaged by non-CTPA protocol (n = 72), 191 features significantly differed between primary and metastatic tumors, 19 of which achieved AUC ≥ 0.75. In subset analysis of tumors without history of prior treatment (n = 59), 40 features significantly differed between primary and metastatic tumors, 11 of which achieved AUC ≥ 0.75. Volumetric radiomic analysis provides differentiating capability beyond iodine quantification. While a high number of radiomic features differentiated primary versus metastatic pulmonary tumors, fewer features demonstrated good individual discriminatory utility.

IntroductionAzithromycin (AZM) reduces pulmonary inflammation and exacerbations in patients with COPD having emphysema. The antimicrobial effects of AZM on the lower airway microbiome are not known and may contribute to its beneficial effects. Here we tested whether AZM treatment affects the lung microbiome and bacterial metabolites that might contribute to changes in levels of inflammatory cytokines in the airways.Methods20 smokers (current or ex-smokers) with emphysema were randomised to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements performed in acellular BAL fluid included 16S rRNA gene sequences and quantity; 39 cytokines, chemokines and growth factors and 119 identified metabolites. The response to lipopolysaccharide (LPS) by alveolar macrophages after ex-vivo treatment with AZM or bacterial metabolites was assessed.ResultsCompared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Compared with placebo, AZM treatment led to reduced in-vivo levels of chemokine (C-X-C) ligand 1 (CXCL1), tumour necrosis factor (TNF)-α, interleukin (IL)-13 and IL-12p40 in BAL, but increased bacterial metabolites including glycolic acid, indol-3-acetate and linoleic acid. Glycolic acid and indol-3-acetate, but not AZM, blunted ex-vivo LPS-induced alveolar macrophage generation of CXCL1, TNF-α, IL-13 and IL-12p40.ConclusionAZM treatment altered both lung microbiota and metabolome, affecting anti-inflammatory bacterial metabolites that may contribute to its therapeutic effects.Trial registration numberNCT02557958.

Objective: To describe pathologic findings in symptomatic World Trade Center-exposed local workers, residents, and cleanup workers enrolled in a treatment program. Methods: Twelve patients underwent surgical lung biopsy for suspected interstitial lung disease (group 1, n = 6) or abnormal pulmonary function tests (group 2, n = 6). High-resolution computed axial tomography and pathologic findings were coded. Scanning electron microscopy with energy-dispersive x-ray spectroscopy was performed. Results: High-resolution computed axial tomography showed reticular findings (group 1) or normal or airway-related findings (group 2). Pulmonary function tests were predominantly restrictive. Interstitial fibrosis, emphysematous change, and small airway abnormalities were seen. All cases had opaque and biréfringent particles within macrophages, and examined particles contained silica, aluminum silicates, titanium dioxide, talc, and metals. Conclusions: In symptomatic World Trade Center-exposed individuals, pathologic findings suggest a common exposure resulting in alveolar loss and a diverse response to injury.

The objective of this study is to assess the impact on nodule detection and efficiency using a computer-aided detection (CAD) device seamlessly integrated into a commercially available picture archiving and communication system (PACS). Forty-eight consecutive low-dose thoracic computed tomography studies were retrospectively included from an ongoing multi-institutional screening study. CAD results were sent to PACS as a separate image series for each study. Five fellowship-trained thoracic radiologists interpreted each case first on contiguous 5 mm sections, then evaluated the CAD output series (with CAD marks on corresponding axial sections). The standard of reference was based on three-reader agreement with expert adjudication. The time to interpret CAD marking was automatically recorded. A total of 134 true-positive nodules, measuring 3 mm and larger were included in our study; with 85 ≥ 4 and 50 ≥ 5 mm in size. Readers detection improved significantly in each size category when using CAD, respectively, from 44 to 57 % for ≥3 mm, 48 to 61 % for ≥4 mm, and 44 to 60 % for ≥5 mm. CAD stand-alone sensitivity was 65, 68, and 66 % for nodules ≥3, ≥4, and ≥5 mm, respectively, with CAD significantly increasing the false positives for two readers only. The average time to interpret and annotate a CAD mark was 15.1 s, after localizing it in the original image series. The integration of CAD into PACS increases reader sensitivity with minimal impact on interpretation time and supports such implementation into daily clinical practice.

If undiagnosed and untreated, 38% of patients with aortic dissection will die by 24 hours with 50% mortality by 48 hours. [...] it is important to rapidly and accurately identify aortic dissections.

Surface morphology is an important indicator of malignant potential for solid-type lung nodules detected at CT, but is difficult to assess subjectively. Automated methods for morphology assessment have previously been described using a common measure of nodule shape, representative of the broad class of existing methods, termed area-to-perimeter-length ratio ( APR ). APR is static and thus highly susceptible to alterations by random noise and artifacts in image acquisition. We introduce and analyze the self-overlap ( SO ) method as a dynamic automated morphology detection scheme. SO measures the degree of change of nodule masks upon Gaussian blurring. We hypothesized that this new metric would afford equally high accuracy and superior precision than APR. Application of the two methods to a set of 119 patient lung nodules and a set of simulation nodules showed our approach to be slightly more accurate and on the order of ten times as precise, respectively. The dynamic quality of this new automated metric renders it less sensitive to image noise and artifacts than APR, and as such, SO is a potentially useful measure of cancer risk for solid-type lung nodules detected on CT.

Worldwide, lung cancer is responsible for the largest number of cancer‐related deaths, and reducing tobacco consumption is the most effective way to reduce lung cancer mortality. Standard therapy options continue to include surgery, radiotherapy, and/or chemotherapy. As lung cancer is a heterogeneous disease, it is hoped that translational proteomic and genomic research will advance our understanding of driver molecular pathways and allow development of more effective, less toxic, targeted therapies. Recent developments in immunotherapy have generated significant excitement and represent a novel therapeutic strategy, which has already impacted current standard of care.

Purpose Pathogenic variants affecting MLH1 , MSH2 , MSH6 , and PMS2 cause Lynch syndrome and result in different but imprecisely known cancer risks. This study aimed to provide age and organ-specific cancer risks according to gene and gender and to determine survival after cancer. Methods We conducted an international, multicenter prospective observational study using independent test and validation cohorts of carriers of class 4 or class 5 variants. After validation the cohorts were merged providing 6350 participants and 51,646 follow-up years. Results There were 1808 prospectively observed cancers. Pathogenic MLH1 and MSH2 variants caused high penetrance dominant cancer syndromes sharing similar colorectal, endometrial, and ovarian cancer risks, but older MSH2 carriers had higher risk of cancers of the upper urinary tract, upper gastrointestinal tract, brain, and particularly prostate. Pathogenic MSH6 variants caused a sex-limited trait with high endometrial cancer risk but only modestly increased colorectal cancer risk in both genders. We did not demonstrate a significantly increased cancer risk in carriers of pathogenic PMS2 variants. Ten-year crude survival was over 80% following colon, endometrial, or ovarian cancer. Conclusion Management guidelines for Lynch syndrome may require revision in light of these different gene and gender-specific risks and the good prognosis for the most commonly associated cancers.

IntroductionFamily history (FmH) of young-onset type 2 diabetes (YOD) and 1-hour plasma glucose (PG) during the 75-g oral glucose tolerance test predicts incident diabetes, although their interactions remain unknown.Research design and methodsIn a workforce cohort established in 1998–2003, we ascertained their glycemic status in 2012–2014. We examined the interaction between FmH-YOD and 1-hour PG in predicting diabetes and used receiver operating characteristics (ROC) analysis to compare the performance of 1-hour PG in participants with or without FmH-YOD.ResultsAmong 583 participants (median age (IQR)=41 (36–47) years, 43.7% men, body mass index=23.3 (21.2–26) kg/m2, 40.3% (n=235) had FmH-YOD, 1-hour PG=8.1 (6.4–10.1) mmol/L), 99 (17%) had developed diabetes at a follow-up of 12.1 (11.3–13.1) years. In the FmH-YOD group, 45% in the high 1-hour PG group and 17% in the normal 1-hour PG group developed diabetes. The respective figures were 16% and 1.8% in the FmH-NONE group. Both FmH-YOD and 1-hour PG predicted diabetes with a negative interaction between FmH-YOD and 1-hour PG (OR 0.72, 95% CI 0.55 to 0.93, p=0.013). Compared with (FmH-NONE/normal 1-hour PG) group, the ORs of incident diabetes in (FmH-NONE/high 1-hour PG), (FmH-YOD/normal 1-hour PG), (FmH-YOD/high 1-hour PG) groups were 7.4 (95% CI 1.6 to 35.1, p=0.011), 18 (95% CI 3.3 to 98.1, p=0.001) and 28.2 (95% CI 5.5 to 145.9, p<0.001), respectively. In ROC analysis, the C-statistics of 1-hour PG dropped from 0.83 (95% CI 0.76 to 0.90, p<0.001) in the FmH-NONE group to 0.69 (95% CI 0.62 to 0.76, p<0.001) in the FmH-YOD group (difference=0.14 (95% CI 0.04–0.24), p=0.006) where fasting PG (FPG) was the best predictor (0.792 (95% CI 0.730–0.853), p<0.001).ConclusionsFPG outperformed 1-hour PG in predicting incident diabetes in people with FmH-YOD, calling for precise classification and preventive strategies.

Introduction: The influence of corticosteroid therapy before or after the onset of Clostridioides difficile infections (CDIs) on the clinical outcomes of adults with hospital-onset CDIs was investigated. Materials and Methods: A clinical study was conducted on the medical wards of a teaching hospital between January 2013 and April 2020. Adults (aged [greater than or equal to] 20 years) with hospital-onset CDIs (ie, symptom onset at least 48 hours after hospitalization) were included. \"Corticosteroid therapy during acute CDIs\" was defined as the receipt of a corticosteroid at the prednisolone equivalent (PE) dose of [greater than or equal to] 10 mg for at least 48 hours within one week after the CDI diagnosis. \"Prior corticosteroid exposure\" was defined as the receipt of a corticosteroid at the PE dose of [greater than or equal to] 5 mg PE for at least 48 hours within one month before the CDI diagnosis. Results: Of the 243 adults with hospital-onset CDIs, patients (44, 18.1%) who received corticosteroid therapy during acute CDIs were more likely to have prior corticosteroid exposure (86.4% vs 11.9%, P <0.001) and CDI episodes in intensive care units (31.8% vs 10.8%, P =0.001). Of note, a crucial association between corticosteroid therapy during acute CDIs and CDI recurrence was evidenced (13.6% vs 1.5%, P =0.002). Prior corticosteroid exposure was not associated with favorable CDI outcomes in terms of successful treatment (78.3% vs 74.9%, P =0.89), in-hospital crude mortality (17.4% vs 24.0%, P =0.61), or CDI recurrence (4.3% vs 5.3%, P = 1.00). However, for 177 patients without prior corticosteroid exposure, corticosteroid therapy during acute CDIs was linked to a higher proportion of CDI recurrence (33.3% vs 5.3%, P =0.046). Conclusion: Corticosteroid therapy during acute CDIs might impact the recurrence of CDIs, particularly in those with a lack of prior corticosteroid exposure. Keywords: steroid, prednisolone, Clostridioides difficile, diarrhea, recurrence, intensive care unit, immunosuppression