Improving the prediction of lung adenocarcinoma invasive component on CT: Value of a vessel removal algorithm during software segmentation of subsolid nodules.
Purpose: To evaluate the value of a vessel removal algorithm in segmentation of subsolid nodules by comparing the software solid component measurement on CT, before and after vessel removal, with the measurement of the invasive component on pathology in lung adenocarcinomas manifesting as subsolid n...
| Publicado en: | European Journal of Radiology Vol. 100; pp. 58 - 66 |
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| Autores principales: | , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Mar2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=128203520&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 128203520 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0720048X 3S7 jtl: European Journal of Radiology issn: 0720048X maglogo: N pubinfo: dt: Mar2018 vid: 100 pid: 1004 pub: Elsevier B.V. artinfo: ui: 128203520 128203520 NLM29496080 10.1016/j.ejrad.2018.01.016 NLM29496080 128203520 ppf: 58 ppct: 8 formats: tig: atl: Improving the prediction of lung adenocarcinoma invasive component on CT: Value of a vessel removal algorithm during software segmentation of subsolid nodules. aug: au: Garzelli, Lorenzo Goo, Jin Mo Ahn, Su Yeon Chae, Kum Ju Park, Chang Min Jung, Julip Hong, Helen affil: Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea sug: subj: Image Processing, Computer Assisted Methods Adenocarcinoma Pathology Lung Neoplasms Adenocarcinoma Lung Neoplasms Pathology Tomography, X-Ray Computed Methods Neoplasm Invasiveness Predictive Value of Tests Adult Lung Pathology Male Retrospective Design Lung Young Adult Reproducibility of Results Aged Algorithms Middle Age Female Adult: 19-44 years Aged: 65+ years Middle Aged: 45-64 years Male Female ab: Purpose: To evaluate the value of a vessel removal algorithm in segmentation of subsolid nodules by comparing the software solid component measurement on CT, before and after vessel removal, with the measurement of the invasive component on pathology in lung adenocarcinomas manifesting as subsolid nodules.Materials and Methods: Between January 2014 and June 2015, 73 subsolid nodules with an invasive component of ≤10 mm on pathology were selected for analyses. For each nodule, semi-automated segmentation was performed by 2 radiologists and 3-dimensional (D) longest, axial longest and effective diameters of solid component were obtained from software, before and after using a vessel removal tool. These measurements were compared with the invasive component diameter on pathology using the paired t-test and Pearson's correlation test.Results: Sixty-eight successfully segmented subsolid nodules were included. The mean maximal diameter of the invasive component on pathology was 4.6 mm (range, 0-10 mm). The correlation between software and pathology measurements was significant (p < 0.01) and the correlation after vessel removal (r = 0.49-0.54) was better than before vessel removal (r = 0.27-0.41). The mean measurement difference between solid component on CT and invasive tumor on pathology was significantly larger before vessel removal than after vessel removal in all measurements. The smallest mean measurement difference was obtained with 3D longest diameter of solid component after vessel removal in both readers (-0.26 mm to 0.10 mm), with no significant difference from pathology (p = 0.53-0.83).Conclusion: By adding a vessel removal algorithm in software segmentation of subsolid nodules, the prediction of invasive component in lung adenocarcinomas can be improved. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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