Article
The size of mediastinal lymph nodes and its relation with metastatic involvement: a meta-analysis.
Department of Nuclear Medicine and PET Research, VU University Medical Center, De Boelelaan 1117, 1081HV Amsterdam, The Netherlands.
European Journal of Cardio-Thoracic Surgery (impact factor:
2.55).
02/2006;
29(1):26-9.
DOI:10.1016/j.ejcts.2005.10.002
pp.26-9
Source: PubMed
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Citations (0)
- Cited In (6)
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Article: Lymph node detection and segmentation in chest CT data using discriminative learning and a spatial prior.
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ABSTRACT: Lymph nodes have high clinical relevance and routinely need to be considered in clinical practice. Automatic detection is, however, challenging due to clutter and low contrast. In this paper, a method is presented that fully automatically detects and segments lymph nodes in 3-D computed tomography images of the chest. Lymph nodes can easily be confused with other structures, it is therefore vital to incorporate as much anatomical prior knowledge as possible in order to achieve a good detection performance. Here, a learned prior of the spatial distribution is used to model this knowledge. Different prior types with increasing complexity are proposed and compared to each other. This is combined with a powerful discriminative model that detects lymph nodes from their appearance. It first generates a number of candidates of possible lymph node center positions. Then, a segmentation method is initialized with a detected candidate. The graph cuts method is adapted to the problem of lymph nodes segmentation. We propose a setting that requires only a single positive seed and at the same time solves the small cut problem of graph cuts. Furthermore, we propose a feature set that is extracted from the segmentation. A classifier is trained on this feature set and used to reject false alarms. Cross-validation on 54 CT datasets showed that for a fixed number of four false alarms per volume image, the detection rate is well more than doubled when using the spatial prior. In total, our proposed method detects mediastinal lymph nodes with a true positive rate of 52.0% at the cost of only 3.1 false alarms per volume image and a true positive rate of 60.9% with 6.1 false alarms per volume image, which compares favorably to prior work on mediastinal lymph node detection.Medical image analysis 11/2012; · 3.09 Impact Factor -
Article: ACR Appropriateness Criteria® noninvasive clinical staging of bronchogenic carcinoma.
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ABSTRACT: In order to appropriately manage patients with lung cancer, it is necessary to properly stage the tumor. The ACR Appropriateness Criteria is designed to provide an overview of the value of different imaging techniques in the non-invasive staging of lung cancer and allow for the rational selection of imaging studies to arrive at the appropriate clinical stage.Journal of thoracic imaging 11/2010; 25(4):W107-11. · 1.42 Impact Factor -
Article: [Role of FDG-PET scanning in stage IIIAN2 non-small cell lung cancer].
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ABSTRACT: Patients with clinical stage IIIAN2 non-small cell lung cancer (NSCLC) are a heterogeneous subgroup in term of prognosis and therapeutic management. The optimal management of this patient group is a major focus for thoracic oncology research and the concept of multimodality treatment has recently been introduced. This approach combines induction chemotherapy or radiochemotherapy followed by surgery in the case of mediastinal lymph node down-staging. positron emission tomography computed tomography with [18F]-fluorodesoxyglucose (FDG-PET) is a molecular and metabolic imaging modality which combines the metabolic data of PET with morphological data from CT. FDG-PET has become a standard in lung cancer management since the different indications listed in the standards, options and recommendations (SOR) of the FNCLCC. However, the potential specific importance of FDG-PET in IIIAN2 patients needs to be addressed further. In this setting, the authors' objective is to review the potential role of metabolic imaging in stage IIIAN2 NSCLC, taking into account new multimodality treatments. In stage IIIAN2, FDG-PET has performed better than morphoradiological imaging for baseline and postinduction lymph node staging, the identification of distant metastasis, and determining prognosis, as well as assessing the response to treatment.Revue des Maladies Respiratoires 02/2012; 29(2):149-60. · 0.59 Impact Factor
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Keywords
14 studies
available studies
computed tomography
conditional test performance
CT results
different size categories
enlarged lymph nodes
FDG-PET
FDG-PET performance characteristics
lymph node enlargement
lymph nodes
metastatic involvement
N2 disease
negative FDG-PET result
non-small-cell lung cancer
Positron emission tomography
post-test probabilities
post-test probability
recent results
stratify patients