Literature DB >> 29380154

Development and Validation of Segmentation Method for Lung Cancer Volumetry on Chest CT.

Young Jae Kim1,2, Seung Hyun Lee2, Kun Young Lim3, Kwang Gi Kim4.   

Abstract

The set of criteria called Response Evaluation Criteria In Solid Tumors (RECIST) is used to evaluate the remedial effects of lung cancer, whereby the size of a lesion can be measured in one dimension (diameter). Volumetric evaluation is desirable for estimating the size of a lesion accurately, but there are several constraints and limitations to calculating the volume in clinical trials. In this study, we developed a method to detect lesions automatically, with minimal intervention by the user, and calculate their volume. Our proposed method, called a spherical region-growing method (SPRG), uses segmentation that starts from a seed point set by the user. SPRG is a modification of an existing region-growing method that is based on a sphere instead of pixels. The SPRG method detects lesions while preventing leakage to neighboring tissues, because the sphere is grown, i.e., neighboring voxels are added, only when all the voxels meet the required conditions. In this study, two radiologists segmented lung tumors using a manual method and the proposed method, and the results of both methods were compared. The proposed method showed a high sensitivity of 81.68-84.81% and a high dice similarity coefficient (DSC) of 0.86-0.88 compared with the manual method. In addition, the SPRG intraclass correlation coefficient (ICC) was 0.998 (CI 0.997-0.999, p < 0.01), showing that the SPRG method is highly reliable. If our proposed method is used for segmentation and volumetric measurement of lesions, then objective and accurate results and shorter data analysis time are possible.

Entities:  

Keywords:  Computed tomography; Computer-assisted diagnosis; Lung cancer; Response evaluation criteria in solid tumors; Tumor volume

Mesh:

Year:  2018        PMID: 29380154      PMCID: PMC6113144          DOI: 10.1007/s10278-018-0051-5

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  10 in total

Review 1.  Computer-aided diagnosis: how to move from the laboratory to the clinic.

Authors:  Bram van Ginneken; Cornelia M Schaefer-Prokop; Mathias Prokop
Journal:  Radiology       Date:  2011-12       Impact factor: 11.105

2.  Lung cancer: computerized quantification of tumor response--initial results.

Authors:  Binsheng Zhao; Lawrence H Schwartz; Chaya S Moskowitz; Michelle S Ginsberg; Naiyer A Rizvi; Mark G Kris
Journal:  Radiology       Date:  2006-12       Impact factor: 11.105

Review 3.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

4.  On the origin of the bilateral filter and ways to improve it.

Authors:  Michael Elad
Journal:  IEEE Trans Image Process       Date:  2002       Impact factor: 10.856

Review 5.  Chemotherapy in small cell lung cancer.

Authors:  K Osterlind
Journal:  Eur Respir J       Date:  2001-12       Impact factor: 16.671

6.  Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria.

Authors:  Katharina Marten; Florian Auer; Stefan Schmidt; Gerhard Kohl; Ernst J Rummeny; Christoph Engelke
Journal:  Eur Radiol       Date:  2005-12-06       Impact factor: 5.315

7.  Cancer statistics, 2014.

Authors:  Rebecca Siegel; Jiemin Ma; Zhaohui Zou; Ahmedin Jemal
Journal:  CA Cancer J Clin       Date:  2014-01-07       Impact factor: 508.702

8.  Automated Delineation of Lung Tumors from CT Images Using a Single Click Ensemble Segmentation Approach.

Authors:  Yuhua Gu; Virendra Kumar; Lawrence O Hall; Dmitry B Goldgof; Ching-Yen Li; René Korn; Claus Bendtsen; Emmanuel Rios Velazquez; Andre Dekker; Hugo Aerts; Philippe Lambin; Xiuli Li; Jie Tian; Robert A Gatenby; Robert J Gillies
Journal:  Pattern Recognit       Date:  2013-03-01       Impact factor: 7.740

9.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

10.  Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

Authors:  Yu Guo; Yuanming Feng; Jian Sun; Ning Zhang; Wang Lin; Yu Sa; Ping Wang
Journal:  Comput Math Methods Med       Date:  2014-05-29       Impact factor: 2.238

  10 in total
  1 in total

Review 1.  Radiomics in Triple Negative Breast Cancer: New Horizons in an Aggressive Subtype of the Disease.

Authors:  Camil Ciprian Mireștean; Constantin Volovăț; Roxana Irina Iancu; Dragoș Petru Teodor Iancu
Journal:  J Clin Med       Date:  2022-01-26       Impact factor: 4.241

  1 in total

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