Is it Possible to Differentiate Malignant Mediastinal Nodes from Benign Nodes by Size?

Arita, Tomohiro; Matsumoto, Tsuneo; Kuramitsu, T; Kawamura, Masaki; Matsunaga, Naofumi; Sugi, Kazuro; Esato, Kensuke

doi:10.1378/chest.110.4.1004

Cited by 98 publications

(30 citation statements)

References 16 publications

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“…Whereas healthy lymph nodes vary between 1 and 20 mm in diameter (along their longitudinal axis assuming ellipsoidal shape), 12 benign and malignant ones can grow up to about 5 to 35 mm. 13 In any case, they often touch or infiltrate nearby vessels and soft tissue, which can additionally alter their shape. These characteristics make a clear definition of our search space very difficult.…”

Section: Methodsmentioning

confidence: 99%

Automatic mediastinal lymph node detection in chest CT

Feuerstein

Deguchi

Kitasaka

et al. 2009

Medical Imaging 2009: Computer-Aided Diagnosis

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Computed tomography (CT) of the chest is a very common staging investigation for the assessment of mediastinal, hilar, and intrapulmonary lymph nodes in the context of lung cancer. In the current clinical workflow, the detection and assessment of lymph nodes is usually performed manually, which can be error-prone and timeconsuming. We therefore propose a method for the automatic detection of mediastinal, hilar, and intrapulmonary lymph node candidates in contrast-enhanced chest CT. Based on the segmentation of important mediastinal anatomy (bronchial tree, aortic arch) and making use of anatomical knowledge, we utilize Hessian eigenvalues to detect lymph node candidates. As lymph nodes can be characterized as blob-like structures of varying size and shape within a specific intensity interval, we can utilize these characteristics to reduce the number of false positive candidates significantly. We applied our method to 5 cases suspected to have lung cancer. The processing time of our algorithm did not exceed 6 minutes, and we achieved an average sensitivity of 82.1% and an average precision of 13.3%.

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Section: Methodsmentioning

confidence: 99%

Automatic mediastinal lymph node detection in chest CT

Feuerstein

Deguchi

Kitasaka

et al. 2009

Medical Imaging 2009: Computer-Aided Diagnosis

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“…The diagnostic performance of CT in mediastinal nodal staging is limited because of the use of size criteria to differentiate between benign and malignant lesions. Histopathologic studies showed that 21% of the metastases are in normalsized lymph nodes (8), whereas no malignancy is found in 40% of the enlarged lymph nodes, especially in patients with poststenotic pneumonia (9). The use of MRI provides no improvement over CT (10), even with new superparamagnetic contrast agents (11).…”

mentioning

confidence: 99%

18F-FDG PET for Mediastinal Staging of Lung Cancer: Which SUV Threshold Makes Sense?

Hellwig

Graeter²,

Ukena

et al. 2007

Journal of Nuclear Medicine

173

111

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18 F-FDG PET is the most accurate noninvasive modality for staging mediastinal lymph nodes in lung cancer. Besides using visual image interpretation, some institutions use standardized uptake value (SUV) measurements in lymph nodes. Mostly, an SUV of 2.5 is used as the cutoff, but this choice was never deduced from respective studies. Receiver operating characteristic (ROC) analyses demonstrated that SUV thresholds of more than 4 resulted in the highest accuracy. But these high cutoffs imply high false-negative rates (FNRs). The aim of our evaluation was to determine an optimal SUV threshold and to compare its diagnostic performance with the results of visual interpretation. Methods: This retrospective study included 95 patients with suspected lung cancer who underwent mediastinoscopy/mediastinal lymphadenectomy after 18 F-FDG PET (90-150 min after 250 MBq of 18 F-FDG). Maximum SUV was measured in 371 lymph node regions biopsied afterward and visually interpreted using a 6-level score (2 2 2 through 1 1 1). Diagnostic performance was assessed by ROC analysis. FNR and false-positive rate (FPR), the sum of both error rates (FNR 1 FPR), and diagnostic accuracy were plotted against a hypothetical SUV threshold to determine the optimum SUV threshold. Results: SUVs in metastatic lymph nodes were higher (mean 6 SD, 7.1 6 4.5; range, 1.4-26.9; n 5 70) than in tumor-free lymph node stations (2.4 6 1.7; range, 0.6-14.9; n 5 301; P , 0.01). Inflammatory lymph nodes exhibited slightly increased SUVs (2.7 6 2.0; range, 0.8-14.9; n 5 146). The plot of error rates featured a minimum of the sum FNR 1 FPR for an SUV of 2.5. With increasing SUV threshold, the FPR decreased most prominently up to that value whereas a continuous rise of FNR was noticed. Highest diagnostic accuracy was achieved with an SUV of 4.5. The areas under the ROC curves demonstrated that visual interpretation tends to be more accurate than SUV quantification (visual, 0.930 6 0.022; SUV, 0.899 6 0.025; P 5 0.241). Using an SUV of 2.5 as the threshold, the resulting sensitivity, specificity, and negative predictive value were 89%, 84%, and 96%, respectively. Conclusion: For mediastinal staging, the choice of an SUV of 2.5 as the threshold is justified because FNR 1 FPR is minimized. The resulting high negative predictive value of 96% allows the omission of mediastinoscopy in patients with negative mediastinal findings on 18 F-FDG PET images. For the experienced observer, visual analysis should be relied on primarily, with calculation of the SUV used, at most, as a secondary aid. For the less experienced observer, the SUV may be of greater value.

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“…Literature reports rather good specificity of CT (about 80%) and moderate sensitivity (not above 60%) [1]. From a clinical point of view, this may infer that one enlarged mediastinal lymph node (short axis ≥1 cm) in a patient affected by lung cancer may result negative for metastasis in 4 cases out of 10, whereas identification of metastasis may be achieved in up to 20% of normal size lymph nodes (short axis <1 cm).…”

Section: Computed Tomography (Ct)mentioning

confidence: 97%

Mediastinal staging in lung cancer: a rational approach

Ceron¹,

Michieletto²,

Zamperlin³

2016

Monaldi Arch Chest Dis

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imaging techniques such as CT (Computed Tomography) and PET (Positron Emission Tomography), mini-invasive techniques, as TBNA (Transbronchial Needle Aspiration), EBUS-TBNA (Ultrasound-Guided Transbronchial Needle Aspiration), EUS-FNA (Endoscopic Ultra Sound Fine-Needle Aspiration), and/or surgical techniques as mediastinoscopy, thoracoscopy, mediastinothomy. Each of these techniques provides different sensitivity, specificity and predictive value: all these characteristics need to be well considered and adequately used to achieve the best possible outcome, best exploitation of available resources and least discomfort for the patient. Particularly, indicators which may suggest the need for further examination of mediastinum, following a negative CT and PET, will be discussed in this review; need for surgical confirmation after negative TBNA will be considered, also.

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Is it Possible to Differentiate Malignant Mediastinal Nodes from Benign Nodes by Size?

Cited by 98 publications

References 16 publications

Automatic mediastinal lymph node detection in chest CT

Automatic mediastinal lymph node detection in chest CT

18F-FDG PET for Mediastinal Staging of Lung Cancer: Which SUV Threshold Makes Sense?

Mediastinal staging in lung cancer: a rational approach

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