Investigating mediastinal lymph node stations segmentation on thoracic CT following experts guidelines

In radiation therapy, accurate delineation of mediastinal lymph node stations on thoracic CT is essential for both prognostication and treatment delivery. We propose an original approach based purely on geometrical considerations, without using grey levels, that follow the reference guidelines and attempt to replicate the delineation undertaken manually by the experts. The proposed method is a greedy process based on fuzzy relative position constraints. It progressively refines an initial region towards the target by using a set of predefined anatomical structures. Experiments were conducted with two CT images that were manually segmented by experts. Average Dice Similarly Coefficient between segmented and references stations was close to 77%. This fast method (30 sec) could potentially assist the expert, for example in detecting situations where the guidelines are not strictly followed. To our knowledge, this is the first time such an approach has been proposed for this problem.

[1]  Hans-Peter Meinzer,et al.  Lymph node segmentation on CT images by a shape model guided deformable surface methodh , 2008, SPIE Medical Imaging.

[2]  Isabelle Bloch,et al.  Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Randall K Ten Haken,et al.  CT-based definition of thoracic lymph node stations: an atlas from the University of Michigan. , 2005, International journal of radiation oncology, biology, physics.

[4]  William E. Higgins,et al.  Semi-automatic central-chest lymph-node definition from 3D MDCT images , 2010, Medical Imaging.

[5]  Nandita Mitra,et al.  Elective nodal irradiation (ENI) vs. involved field radiotherapy (IFRT) for locally advanced non-small cell lung cancer (NSCLC): A comparative analysis of toxicities and clinical outcomes. , 2010, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[6]  T. Naruke,et al.  Lymph node mapping and curability at various levels of metastasis in resected lung cancer. , 1978, The Journal of thoracic and cardiovascular surgery.

[7]  Lucyna Kepka,et al.  Delineation variation of lymph node stations for treatment planning in lung cancer radiotherapy. , 2007, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[8]  Hisao Asamura,et al.  The IASLC Lung Cancer Staging Project: A Proposal for a New International Lymph Node Map in the Forthcoming Seventh Edition of the TNM Classification for Lung Cancer , 2009, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

[9]  Lawrence B Marks,et al.  Elective nodal irradiation for locally advanced non-small-cell lung cancer: it's called cancer for a reason. , 2009, International journal of radiation oncology, biology, physics.

[10]  Daisuke Deguchi,et al.  Automatic mediastinal lymph node detection in chest CT , 2009, Medical Imaging.

[11]  Grégoire Malandain,et al.  Atlas-based delineation of lymph node levels in head and neck computed tomography images. , 2008, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[12]  C. Mountain,et al.  Regional lymph node classification for lung cancer staging. , 1997, Chest.