Does volume perfusion computed tomography enable differentiation of metastatic and non-metastatic mediastinal lymph nodes in lung cancer patients? A feasibility study

Spira, Daniel; Wecker, Matthias; Spira, Sven Michael; Hetzel, Jürgen; Spengler, Werner; Sauter, Alexander; Horger, Marius

doi:10.1102/1470-7330.2013.0033

Cited by 10 publications

(5 citation statements)

References 32 publications

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“…41 Our finding was consistent with the research of Aoyagi et al 39 According to Daniel et al, no significant differences of perfusion characteristics could be found between metastatic and non-metastatic lymph nodes. 42 There were several limitations in this study. Firstly, the sample sizes of T 1 -and T 2 -staged oesophageal SCC are not large because the symptoms of these patients are not obvious and referral to hospital at early stage.…”

Section: Discussionmentioning

confidence: 91%

Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

Huang

Chen

Zhang

et al. 2018

The British Journal of Radiology

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Section: Discussionmentioning

confidence: 91%

Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

Huang

Chen

Zhang

et al. 2018

The British Journal of Radiology

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“…As stated in a previous study (3), different findings of measured perfusion parameters can be partly explained by the different techniques that were used for DCE measurements in the different perfusion studies used in the past (14,(16)(17)(18)(19)(20)(21)(22). Nevertheless, the robustness of the applied MR protocol in the present study for the evalua- with lung cancer found no significant differences in perfusion characteristics between benign and malignant LNs (23). Taking all the above-mentioned data from prior studies into account, the technique of DCE measurement in LNstaging for patients with lung cancer is not yet reliably applicable in a daily clinical setting.…”

Section: Discussionmentioning

confidence: 58%

Impact of FDG-PET and Dynamic Contrast-Enhanced MRI in Comparison with DWI for N-Staging in Lung Cancer Patients

et al. 2018

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Background: Regarding mediastinal N-staging in lung cancer patients, computed tomography (CT), magnetic resonance imaging (MRI), and integrated 18 Fluorine-fluorodeoxyglucose-positron emission tomography/CT ( 18 F-FDG-PET/CT) are the most widespread imaging methodologies in clinical routine. Objectives: In order to further extract information from non-invasive staging, we evaluated the use of 18 F-FDG-PET/CT and dynamic contrast enhanced (DCE) and diffusion-weighted imaging (DWI) MRI using histopathology as the diagnostic gold standard. Patients and Methods: A total number of 50 patients had undergone MRI of the chest within two weeks prior to surgery for histopathological proof. DCE-MRI was evaluated on the basis of region of interest (ROI)-based signal intensity/time (SI/T) curves in the respective mediastinal lymph nodes (LNs). In total, 28 LNs could be allocated to the corresponding histopathological findings, as well as to corresponding findings in 18 F-FDG-PET/CT. Results: Malignant LNs presented with significantly higher FDG uptake in PET. Significant differences between malignant and benign LNs were found for DCE-MRI regarding the parameters MaxE, 4-minutes value, SE, EP and EP/MaxE. In DWI-MRI, malignant LNs presented with significantly lower signal intensity compared to benign LNs (p < 0.01). An apparent diffusion coefficient (ADC) threshold of 1528 mm 2 /s was found to exclude malignancy for LNs that are above the threshold. Conclusion: 18 F-FDG-PET in addition with MRI that includes DWI might improve mediastinal N-staging, which is of interest in cases of FDG-equivocal LNs. An ADC threshold of 1528 mm 2 /s might potentially help to further classify LNs with indefinite PET-findings. DCE-MRI of mediastinal LNs seems not yet to be approved for clinical routine.

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“…Heterogeneity is an important feature of malignancy, presumably reflecting infiltration, angiogenesis and necrosis ( 33 – 35 ). Studies of perfusion CT suggested that the blood flow might be more heterogeneous in metastatic nodes than in nonmetastatic nodes ( 36 ). However, it was difficult to tell subtle differences by the naked eye, even for experienced radiologists.…”

Section: Discussionmentioning

confidence: 99%

Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT Imaging

et al. 2021

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PurposeTo establish and validate a radiomics model to estimate the malignancy of mediastinal lymph nodes (LNs) based on contrast-enhanced CT imaging.MethodIn total, 201 pathologically confirmed mediastinal LNs from 129 patients were enrolled and assigned to training and test sets. Radiomics features were extracted from the region of interest (ROI) delineated on venous-phase CT imaging of LN. Feature selection was performed with least absolute shrinkage and selection operator (LASSO) binary logistic regression. Multivariate logistic regression was performed with the backward stepwise elimination. A model was fitted to associate mediastinal LN malignancy with selected features. The performance of the model was assessed and compared to that of five other machine learning algorithms (support vector machine, naive Bayes, random forest, decision tree, K-nearest neighbor) using receiver operating characteristic (ROC) curves. Calibration curves and Hosmer-Lemeshow tests were used to assess the calibration degree. Decision curve analysis (DCA) was used to assess the clinical usefulness of the logistic regression model in both the training and test sets. Stratified analysis was performed for different scanners and slice thicknesses.ResultAmong the six machine learning methods, the logistic regression model with the eight strongest features showed a significant association with mediastinal LN status and the satisfactory diagnostic performance for distinguishing malignant LNs from benign LNs. The accuracy, sensitivity, specificity and area under the ROC curve (AUC) were 0.850/0.803, 0.821/0.806, 0.893/0.800, and 0.922/0.850 in the training/test sets, respectively. The Hosmer-Lemeshow test showed that the P value was > 0.05, indicating good calibration, and the calibration curves showed good agreement between the classifications and actual observations. DCA showed that the model would obtain more benefit when the threshold probability was between 30% and 90% in the test set. Stratified analysis showed that the performance was not affected by different scanners or slice thicknesses. There was no significant difference (DeLong test, P > 0.05) between any two subgroups, which showed the generalization of the radiomics score across different factors.ConclusionThe model we built could help assist the preoperative estimation of mediastinal LN malignancy based on contrast-enhanced CT imaging, with stability for different scanners and slice thicknesses.

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Does volume perfusion computed tomography enable differentiation of metastatic and non-metastatic mediastinal lymph nodes in lung cancer patients? A feasibility study

Cited by 10 publications

References 32 publications

Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

Intravoxel incoherent motion diffusion-weighted imaging of resectable oesophageal squamous cell carcinoma: association with tumour stage

Impact of FDG-PET and Dynamic Contrast-Enhanced MRI in Comparison with DWI for N-Staging in Lung Cancer Patients

Preoperatively Estimating the Malignant Potential of Mediastinal Lymph Nodes: A Pilot Study Toward Establishing a Robust Radiomics Model Based on Contrast-Enhanced CT Imaging

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