Dataset Information

CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer.

ABSTRACT: Objectives: To investigate the potential of computed tomography (CT)-based texture analysis and elastographic data provided by endobronchial ultrasonography (EBUS) for differentiating the mediastinal lymphadenopathy by sarcoidosis and small cell lung cancer (SCLC) metastasis.

Methods: Sixteen patients with sarcoidosis and 14 with SCLC were enrolled. On CT images showing the largest mediastinal lymph node, a fixed region of interest was drawn on the node, and texture features were automatically measured. Among the 30 patients, 19 (12 sarcoidosis and 7 SCLC) underwent endobronchial ultrasound transbronchial needle aspiration, and the fat-to-lesion strain ratio (FLR) was recorded. Texture features and FLRs were compared between the 2 patient groups. Logistic regression analysis was performed to evaluate the diagnostic accuracy of these measurements.

Results: Of the 31 texture features, the differences between 11 texture features of CT ROIs in the patients with sarcoidosis versus patients with SCLC were significant. Among them, the grey-level run length matrix with high gray-level run emphasis (GLRLM-HGRE) showed the greatest difference (P<0.01). Differences between FLRs were significant (P<0.05). Logistic regression analysis together with receiver operating characteristic curve analysis demonstrated that the FLR combined with the GLRLM-HGRE showed a high diagnostic accuracy (100% sensitivity, 92% specificity, 0.988 area under the curve) for discriminating between sarcoidosis and SCLC.

Conclusion: Texture analysis, particularly combined with the FLR, is useful for discriminating between mediastinal lymphadenopathy caused by sarcoidosis from that caused by metastasis from SCLC.

SUBMITTER: Koda E

PROVIDER: S-EPMC7710054 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer.

Koda Eriko E Yamashiro Tsuneo T Onoe Rintaro R Handa Hiroshi H Azagami Shinya S Matsushita Shoichiro S Tomita Hayato H Inoue Takeo T Mineshita Masamichi M

PloS one 20201202 12

<h4>Objectives</h4>To investigate the potential of computed tomography (CT)-based texture analysis and elastographic data provided by endobronchial ultrasonography (EBUS) for differentiating the mediastinal lymphadenopathy by sarcoidosis and small cell lung cancer (SCLC) metastasis.<h4>Methods</h4>Sixteen patients with sarcoidosis and 14 with SCLC were enrolled. On CT images showing the largest mediastinal lymph node, a fixed region of interest was drawn on the node, and texture features were au ...[more]

PMID: 33264372

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Project description:BackgroundEndobronchial ultrasound (EBUS)-guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis, or TB. However, improved methods for discriminating between TB and sarcoidosis and excluding malignancy are still needed. We sought to evaluate the role of genomewide transcriptional profiling to aid diagnostic processes in this setting.MethodsMediastinal lymph node samples from 88 individuals were obtained by EBUS-guided aspiration for investigation of mediastinal lymphadenopathy and subjected to transcriptional profiling in addition to conventional laboratory assessments. Computational strategies were used to evaluate the potential for using the transcriptome to distinguish between diagnostic categories.ResultsMolecular signatures associated with granulomas or neoplastic and metastatic processes were clearly discernible in granulomatous and malignant lymph node samples, respectively. Support vector machine (SVM) learning using differentially expressed genes showed excellent sensitivity and specificity profiles in receiver operating characteristic curve analysis with area under curve values > 0.9 for discriminating between granulomatous and nongranulomatous disease, TB and sarcoidosis, and between cancer and reactive lymphadenopathy. A two-step decision tree using SVM to distinguish granulomatous and nongranulomatous disease, then between TB and sarcoidosis in granulomatous cases, and between cancer and reactive lymphadenopathy in nongranulomatous cases, achieved > 90% specificity for each diagnosis and afforded greater sensitivity than existing tests to detect TB and cancer. In some diagnostically ambiguous cases, computational classification predicted granulomatous disease or cancer before pathologic abnormalities were evident.ConclusionsMachine learning analysis of transcriptional profiling in mediastinal lymphadenopathy may significantly improve the clinical utility of EBUS-guided biopsies.

Project description:BackgroundThe current preferred approach for surgical mediastinal staging of non-small-cell lung carcinoma is video-assisted mediastinoscopy. An alternative technique in which lymph nodes are resected instead of biopsied is video-assisted mediastinoscopic lymphadenectomy (VAMLA) that is suggested to be superior in detecting N2 disease. Yet, evidence is conflicting and furthermore limited by sample size. The objective was to compare mediastinal staging through VAMLA and video-assisted mediastinoscopy.MethodsA single-center cohort study was conducted. All consecutive patients that underwent surgical mediastinal staging of non-small-cell lung carcinoma by VAMLA (2011 to 2018) were compared to historic video-assisted mediastinoscopy controls (2007 to 2011). Patients with negative surgical mediastinal staging underwent subsequent anatomical resection with systematic regional lymphadenectomy. Primary outcome was the sensitivity and negative predictive value for detecting N2 disease.ResultsTwo-hundred-sixty-nine video-assisted mediastinoscopic lymphadenectomies and 118 video-assisted mediastinoscopies were performed. The prevalence of N2 disease was 20% and 26% respectively in the VAMLA and video-assisted mediastinoscopy group, while the rate of unforeseen pN2 resulting from lymph node dissection during anatomical resection was 4% and 11%, respectively. Invasive staging using VAMLA demonstrated superior sensitivity of 0.82 and a negative predictive value of 0.96 when compared to video-assisted mediastinoscopy (0.62 and 0.89, respectively), offering a 64% decrease in risk of unforeseen pN2 following anatomical resection. However, VAMLA is also associated with a 75% risk increase on complications (P=0.36).ConclusionsWe conclude that performing invasive mediastinal lymph node assessment for staging of non-small-cell lung carcinoma, VAMLA should be the preferred technique with superior sensitivity and negative predictive value in detecting N2 disease. Though, VAMLA is also associated with an increased risk of complications.

Dataset Information

CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer.

Publications

CT texture analysis of mediastinal lymphadenopathy: Combining with US-based elastographic parameter and discrimination between sarcoidosis and lymph node metastasis from small cell lung cancer.

Similar Datasets

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