Derivation and validation of a clinical model to identify cryptococcosis from suspected malignant pulmonary nodules: A dual-center case-control study.
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ABSTRACT:
SUBMITTER: Mao B
PROVIDER: S-EPMC8506637 | biostudies-literature | 2021 Oct
REPOSITORIES: biostudies-literature
Publications
Derivation and validation of a clinical model to identify cryptococcosis from suspected malignant pulmonary nodules: A dual-center case-control study.
Mao Bei B Zhang Hai H Wang Wen-Wen WW Lu Hai-Wen HW Yang Jia-Wei JW Jiang Sen S Ye Xiao-Dan XD Li Feng F Xu Jin-Fu JF
Clinical and translational medicine 20211001 10
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Project description:Rationale: Screening for non-small cell lung cancer is associated with earlier diagnosis and reduced mortality but also increased harm caused by invasive follow-up of benign pulmonary nodules. Lung tumorigenesis activates the immune system, components of which could serve as tumor-specific biomarkers. Objectives: To profile tumor-derived autoantibodies as peripheral biomarkers of malignant pulmonary nodules. Methods: High-density protein arrays were used to define the specificity of autoantibodies isolated from B cells of 10 resected lung tumors. These tumor-derived autoantibodies were also examined as free or complexed to antigen in the plasma of the same 10 patients and matched benign nodule control subjects. Promising autoantibodies were further analyzed in an independent cohort of 250 nodule-positive patients. Measurements and Main Results: Thirteen tumor B-cell-derived autoantibodies isolated ex vivo showed greater than or equal to 50% sensitivity and greater than or equal to 70% specificity for lung cancer. In plasma, 11 of 13 autoantibodies were present both complexed to and free from antigen. In the larger validation cohort, 5 of 13 tumor-derived autoantibodies remained significantly elevated in cancers. A combination of four of these autoantibodies could detect malignant nodules with an area under the curve of 0.74 and had an area under the curve of 0.78 in a subcohort of indeterminate (8-20 mm in the longest diameter) pulmonary nodules. Conclusions: Our novel pipeline identifies tumor-derived autoantibodies that could effectively serve as blood biomarkers for malignant pulmonary nodule diagnosis. This approach has future implications for both a cost-effective and noninvasive approach to determine nodule malignancy for widespread low-dose computed tomography screening.
| S-EPMC6519849 | biostudies-literature
Project description:BackgroundThe conventional diagnosis and treatment for highly suspected malignant pulmonary nodules (PNs) can avoid unnecessary treatment to some extent. However, the relatively separate puncture processes may not only increase puncture-related complications, but also increase the patient's radiation exposure and hospitalization costs. The purpose of this study was to retrospectively analyze the effectiveness of simultaneous percutaneous microwave ablation (MWA) and percutaneous biopsy (PB) for PNs.MethodsFrom August 2015 to August 2022, 65 consecutive patients [48 solid nodules, 6 ground glass opacities (GGOs), 11 mixed nodules] with suspected single malignant PN underwent MWA and PB combination treatments at the First Affiliated Hospital of Zhengzhou University. The total of 30 patients in Group A underwent synchronous PB and MWA (strategy: low-power MWA-PB-high-power MWA), whereas 35 patients in Group B underwent asynchronous PB and MWA. The technical success, complete ablation (CA), complications, total procedure time (TPT), patient exposure dose (PED), hospitalization time, and costs were compared. An independent samples t-, χ2, or Fisher's exact tests were used.ResultsThe technical success (100% vs. 100%) and CA (100% vs. 97.1%) rates were not significantly different between Groups A and B. The complications of intrapulmonary hemorrhage (16.7% vs. 41.4%, P=0.02) and hemoptysis (0% vs. 8.6%, P=0.04) were significantly different between Groups A and B. TPT (41.6±7.9 vs. 57.3±8.8 min, P<0.001), PED (12.9±1.4 vs. 19.4±2.3 mSv, P<0.001), hospitalization stay (4.7±1.3 vs. 9.1±2.1 days, P<0.001) and costs (3,768.8±652.9 vs. 4,508.0±514.1 USD, P<0.001) also showed significant differences between Groups A and B.ConclusionsSynchronous PB and MWA for PNs is a safe and effective strategy that can decrease bleeding, PED, the hospitalization stay, and costs.
| S-EPMC10585563 | biostudies-literature
Project description:A serum miRNA combination could be a favourable classifier to differentiate malignant pulmonary nodules from benign pulmonary nodules.
2023-08-27 | GSE157074 | GEO
Project description:ImportanceThe improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of chest radiographs for the diagnosis of lung cancer.ObjectiveTo assess the performance of a deep learning-based nodule detection algorithm for the detection of lung cancer on chest radiographs from participants in the National Lung Screening Trial (NLST).Design, setting, and participantsThis diagnostic study used data from participants in the NLST ro assess the performance of a deep learning-based artificial intelligence (AI) algorithm for the detection of pulmonary nodules and lung cancer on chest radiographs using separate training (in-house) and validation (NLST) data sets. Baseline (T0) posteroanterior chest radiographs from 5485 participants (full T0 data set) were used to assess lung cancer detection performance, and a subset of 577 of these images (nodule data set) were used to assess nodule detection performance. Participants aged 55 to 74 years who currently or formerly (ie, quit within the past 15 years) smoked cigarettes for 30 pack-years or more were enrolled in the NLST at 23 US centers between August 2002 and April 2004. Information on lung cancer diagnoses was collected through December 31, 2009. Analyses were performed between August 20, 2019, and February 14, 2020.ExposuresAbnormality scores produced by the AI algorithm.Main outcomes and measuresThe performance of an AI algorithm for the detection of lung nodules and lung cancer on radiographs, with lung cancer incidence and mortality as primary end points.ResultsA total of 5485 participants (mean [SD] age, 61.7 [5.0] years; 3030 men [55.2%]) were included, with a median follow-up duration of 6.5 years (interquartile range, 6.1-6.9 years). For the nodule data set, the sensitivity and specificity of the AI algorithm for the detection of pulmonary nodules were 86.2% (95% CI, 77.8%-94.6%) and 85.0% (95% CI, 81.9%-88.1%), respectively. For the detection of all cancers, the sensitivity was 75.0% (95% CI, 62.8%-87.2%), the specificity was 83.3% (95% CI, 82.3%-84.3%), the positive predictive value was 3.8% (95% CI, 2.6%-5.0%), and the negative predictive value was 99.8% (95% CI, 99.6%-99.9%). For the detection of malignant pulmonary nodules in all images of the full T0 data set, the sensitivity was 94.1% (95% CI, 86.2%-100.0%), the specificity was 83.3% (95% CI, 82.3%-84.3%), the positive predictive value was 3.4% (95% CI, 2.2%-4.5%), and the negative predictive value was 100.0% (95% CI, 99.9%-100.0%). In digital radiographs of the nodule data set, the AI algorithm had higher sensitivity (96.0% [95% CI, 88.3%-100.0%] vs 88.0% [95% CI, 75.3%-100.0%]; P = .32) and higher specificity (93.2% [95% CI, 89.9%-96.5%] vs 82.8% [95% CI, 77.8%-87.8%]; P = .001) for nodule detection compared with the NLST radiologists. For malignant pulmonary nodule detection on digital radiographs of the full T0 data set, the sensitivity of the AI algorithm was higher (100.0% [95% CI, 100.0%-100.0%] vs 94.1% [95% CI, 82.9%-100.0%]; P = .32) compared with the NLST radiologists, and the specificity (90.9% [95% CI, 89.6%-92.1%] vs 91.0% [95% CI, 89.7%-92.2%]; P = .91), positive predictive value (8.2% [95% CI, 4.4%-11.9%] vs 7.8% [95% CI, 4.1%-11.5%]; P = .65), and negative predictive value (100.0% [95% CI, 100.0%-100.0%] vs 99.9% [95% CI, 99.8%-100.0%]; P = .32) were similar to those of NLST radiologists.Conclusions and relevanceIn this study, the AI algorithm performed better than NLST radiologists for the detection of pulmonary nodules on digital radiographs. When used as a second reader, the AI algorithm may help to detect lung cancer.
| S-EPMC7516603 | biostudies-literature
Project description:BackgroundPatients with pulmonary hypertension due to left heart disease (PH-LHD) have overlapping clinical features with pulmonary arterial hypertension making diagnosis reliant on right heart catheterization (RHC). This study aimed to investigate computed tomography pulmonary angiography (CTPA) derived cardiopulmonary structural metrics, in comparison to magnetic resonance imaging (MRI) for the diagnosis of left heart disease in patients with suspected pulmonary hypertension.MethodsPatients with suspected pulmonary hypertension who underwent CTPA, MRI and RHC were identified. Measurements of the cardiac chambers and vessels were recorded from CTPA and MRI. The diagnostic thresholds of individual measurements to detect elevated pulmonary arterial wedge pressure (PAWP) were identified in a derivation cohort (n = 235). Individual CT and MRI derived metrics were tested in validation cohort (n = 211).Results446 patients, of which 88 had left heart disease. Left atrial area was a strong predictor of elevated PAWP>15 mm Hg and PAWP>18 mm Hg, area under curve (AUC) 0.854, and AUC 0.873 respectively. Similar accuracy was also identified for MRI derived LA volume, AUC 0.852 and AUC 0.878 for PAWP > 15 and 18 mm Hg, respectively. Left atrial area of 26.8 cm2 and 30.0 cm2 were optimal specific thresholds for identification of PAWP > 15 and 18 mm Hg, had sensitivity of 60%/53% and specificity 89%/94%, respectively in a validation cohort.ConclusionsCTPA and MRI derived left atrial size identifies left heart disease in suspected pulmonary hypertension with high specificity. The proposed diagnostic thresholds for elevated left atrial area on routine CTPA may be a useful to indicate the diagnosis of left heart disease in suspected pulmonary hypertension.
| S-EPMC5899969 | biostudies-literature
Project description:BackgroundOver 80,000 people undergo pulmonary resection for a lung nodule in the United States each year. Small nodules are frequently missed or difficult to find despite preoperative imaging. We hypothesized that near-infrared (NIR) imaging technology could be used to identify and locate lung nodules during surgery.MethodsWe enrolled 18 patients who were diagnosed with a pulmonary nodule that required resection. All patients had a fine-cut 1-mm computed tomography scan preoperatively. The patients were given systemic 5 mg/kg indocyanine green and then underwent an open thoracotomy 24 hours later. The NIR imaging was used to identify the primary nodule and search for additional nodules that were not found by visual inspection or manual palpation of the ipsilateral lung.ResultsManual palpation and visual inspection identified all 18 primary pulmonary nodules and no additional lesions. Intraoperative NIR imaging detected 16 out of the 18 primary nodules. The NIR imaging also identified 5 additional subcentimeter nodules; 3 metastatic adenocarcinomas and 2 metastatic sarcomas. This technology could identify nodules as small as 0.2 cm and as deep as 1.3 cm from the pleural surface. This approach discovered 3 nodules that were in different lobes than the primary tumor. Nodule fluorescence was independent of size, metabolic activity, histology, tumor grade and vascularity.ConclusionsThis is the first-in-human demonstration of identifying pulmonary nodules during thoracic surgery with NIR imaging without a priori knowledge of their location or existence. The NIR imaging can detect pulmonary nodules during lung resections that are poorly visualized on computed tomography and difficult to discriminate on finger palpation.
| S-EPMC4185369 | biostudies-literature
Project description:BackgroundThe lung is one of the most common target organs for malignant tumor metastasis. The existence of lung metastasis may have a decisive effect on the choice of treatment regimen. Minute pulmonary meningothelial-like nodules (MPMNs) usually present as ground-glass opacity or solid nodules, mimicking the imaging findings of malignant pulmonary nodules. This study summarizes the clinical, radiological, and pathological features of MPMNs to distinguish them from malignant pulmonary nodules.MethodsThe Guangdong Lung Cancer Institute Pathology Information System was searched using the key words "minute meningothelioid nodules" and "lung." Patients who underwent pulmonary resection from 23 February 2009 to 31 May 2017 were included in the study. The 11th edition of Rosai and Ackerman's Surgical Pathology was used to confirm the diagnosis. The clinical, imaging, and pathological characteristics of MPMNs were recorded.ResultsTwelve patients had MPMNs. MPMNs were associated with cancerous or precancerous lesions (10/12), female gender (11/12), and non-smokers (11/12). Four patients were misdiagnosed with malignant pulmonary nodules before surgery. Positron emission tomography-computed tomography revealed an increased maximum standardized uptake value in one patient. Immunohistochemistry identified eight specimens positive for vimentin, EMA, and PR and negative for TTF-1 and CK.ConclusionsMPMNs tend to coexist with malignant tumors, mimicking the imaging findings of malignant pulmonary nodules, thus resulting in misdiagnosis. Dynamic monitoring or an invasive examination may help to distinguish MPMNs from malignant lesions.
| S-EPMC6501004 | biostudies-literature
Project description:ImportanceIn patients with suspected pulmonary embolism (PE), overuse of diagnostic imaging is an important point of concern.ObjectiveTo derive and validate a 4-level pretest probability rule (4-Level Pulmonary Embolism Clinical Probability Score [4PEPS]) that makes it possible to rule out PE solely on clinical criteria and optimized D-dimer measurement to safely decrease imaging testing for suspected PE.Design, setting, and participantsThis study included consecutive outpatients suspected of having PE from US and European emergency departments. Individual data from 3 merged management studies (n = 11 114; overall prevalence of PE, 11%) were used for the derivation cohort and internal validation cohort. The external validation cohorts were taken from 2 independent studies, the first with a high PE prevalence (n = 1548; prevalence, 21.5%) and the second with a moderate PE prevalence (n = 1669; prevalence, 11.7%). A prior definition of pretest probability target values to achieve a posttest probability less than 2% was used on the basis of the negative likelihood ratios of D-dimer. Data were collected from January 2003 to April 2016, and data were analyzed from June 2018 to August 2019.Main outcomes and measuresThe rate of PE diagnosed during the initial workup or during follow-up and the rate of imaging testing.ResultsOf the 5588 patients in the derivation cohort, 3441 (61.8%) were female, and the mean (SD) age was 52 (18.5) years. The 4PEPS comprises 13 clinical variables scored from -2 to 5. It results in the following strategy: (1) very low probability of PE if 4PEPS is less than 0: PE ruled out without testing; (2) low probability of PE if 4PEPS is 0 to 5: PE ruled out if D-dimer level is less than 1.0 μg/mL; (3) moderate probability of PE if 4PEPS is 6 to 12: PE ruled out if D-dimer level is less than the age-adjusted cutoff value; (4) high probability of PE if 4PEPS is greater than 12: PE ruled out by imaging without preceding D-dimer test. In the first and the second external validation cohorts, the area under the receiver operator characteristic curves were 0.79 (95% CI, 0.76 to 0.82) and 0.78 (95% CI, 0.74 to 0.81), respectively. The false-negative testing rates if the 4PEPS strategy had been applied were 0.71% (95% CI, 0.37 to 1.23) and 0.89% (95% CI, 0.53 to 1.49), respectively. The absolute reductions in imaging testing were -22% (95% CI, -26 to -19) and -19% (95% CI, -22 to -16) in the first and second external validation cohorts, respectively. The 4PEPS strategy compared favorably with all recent strategies in terms of imaging testing.Conclusions and relevanceThe 4PEPS strategy may lead to a substantial and safe reduction in imaging testing for patients with suspected PE. It should now be tested in a formal outcome study.
| S-EPMC7931139 | biostudies-literature
Project description:Serum microRNA panel to differentiate malignant pulmonary nodules from benign pulmonary nodules
| PRJNA660019 | ENA
Project description:The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosing the extent of lung cancer lesions. There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmonary nodules, but traditional CNN models focus more on the local features of pulmonary nodules and lack the extraction of global features of pulmonary nodules. To solve this problem, a Cross fusion attention ViT (Cross-ViT) network that fuses local features extracted by CNN and global features extracted by Transformer is proposed. The network first extracts different features independently through two branches and then performs feature fusion through the Cross fusion attention module. Cross-ViT can effectively capture and process both local and global information of lung nodules, which improves the accuracy of classifying the benign and malignant nature of pulmonary nodules. Experimental validation was performed on the LUNA16 dataset, and the accuracy, precision, recall and F1 score reached 91.04%, 91.42%, 92.45% and 91.92%, respectively, and the accuracy, precision, recall and F1 score with SENet as CNN branch reached 92.43%, 94.27%, 91.68% and 92.96%, respectively. The results show that the accuracy, precision, recall and F1 score of the proposed method are 0.3%, 0.11%, 4.52% and 3.03% higher than those of the average optimal method, respectively, and the performance of Cross-ViT network for benign and malignant classification is better than most classification methods.
| S-EPMC11798455 | biostudies-literature