Journal of the Korean Society of Radiology (대한영상의학회지)

The Korean Society of Radiology (대한영상의학회)
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Semi-Quantitative Analysis for Determining the Optimal Threshold Value on CT to Measure the Solid Portion of Pulmonary Subsolid Nodules

폐의 아고형결절에서 침습적 병소를 검출하기 위한 반-정량 분석을 통한 최적의 CT 임계 값 결정

  • Sunyong Lee (Department of Radiology and the Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Da Hyun Lee (Department of Radiology and the Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Jae Ho Lee (Department of Radiology and the Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Sungsoo Lee (Department of Thoracic and Cardiovascular Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Kyunghwa Han (Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine) ;
  • Chul Hwan Park (Department of Radiology and the Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine) ;
  • Tae Hoon Kim (Department of Radiology and the Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine)
  • 이선용 (연세대학교 의과대학 강남세브란스병원 영상의학과, 방사선의과학연구소) ;
  • 이다현 (연세대학교 의과대학 강남세브란스병원 영상의학과, 방사선의과학연구소) ;
  • 이재호 (연세대학교 의과대학 강남세브란스병원 영상의학과, 방사선의과학연구소) ;
  • 이성수 (연세대학교 의과대학 강남세브란스병원 흉부외과) ;
  • 한경화 (연세대학교 의과대학 세브란스병원 영상의학과) ;
  • 박철환 (연세대학교 의과대학 강남세브란스병원 영상의학과, 방사선의과학연구소) ;
  • 김태훈 (연세대학교 의과대학 강남세브란스병원 영상의학과, 방사선의과학연구소)
  • Received : 2020.04.06
  • Accepted : 2020.08.09
  • Published : 2021.05.01
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Abstract

Purpose This study aimed to investigate the optimal threshold value in Hounsfield units (HU) on CT to detect the solid components of pulmonary subsolid nodules using pathologic invasive foci as reference. Materials and Methods Thin-section non-enhanced chest CT scans of 25 patients with pathologically confirmed minimally invasive adenocarcinoma were retrospectively reviewed. On CT images, the solid portion was defined as the area with higher attenuation than various HU thresholds ranging from -600 to -100 HU in 50-HU intervals. The solid portion was measured as the largest diameter on axial images and as the maximum diameter on multiplanar reconstruction images. A linear mixed model was used to evaluate bias in each threshold by using the pathological size of invasive foci as reference. Results At a threshold of -400 HU, the biases were lowest between the largest/maximum diameter of the solid portion of subsolid nodule and the size of invasive foci of the pathological specimen, with 0.388 and -0.0176, respectively. They showed insignificant difference (p = 0.2682, p = 0.963, respectively) at a threshold of -400 HU. Conclusion For quantitative analysis, -400 HU may be the optimal threshold to define the solid portion of subsolid nodules as a surrogate marker of invasive foci.

목적 병리학적 침습성 병소를 기준으로 폐 아고형결절의 고형 부분을 진단하기 위한 최적의 CT 임계값을 알아보고자 하였다. 대상과 방법 병리적으로 최소 침습성 선암이 확진된 25명의 환자에 대해 비조영증강 흉부 CT 영상을 후향적으로 분석하였다. CT 영상에서 고형 부분은 -600부터 -100 Hounsfield units (이하 HU) 단위 사이에서 50 HU 간격의 다양한 임계치보다 높은 감쇠를 나타내는 영역으로 정의되었다. 각 임계치에서 고형부분의 축상 영상 최대 직경과 다면재구성 영상 최대 직경을 각각 측정한 후, 선형 혼합 모델을 이용하여 병리적 침습성 병소 크기와 비교하였다. 결과 -400 HU 단위의 임계값에서 아고형결절의 고형 부분의 크기와 침습성 병소의 크기는 통계학적으로 유의미한 차이를 보이지 않았으며(축상 영상: p = 0.2682, 다면재구성 영상: p = 0.963) 오차가 가장 적었다(축상 영상: 0.388, 다면재구성 영상: -0.0176). 결론 아고형결절의 침습성 병소를 진단하기 위해, -400 HU 단위가 고형 부분을 정의하는 최적의 정량 분석 임계값일 수 있다.

Keywords

Acknowledgement

The scientific guarantor of this publication is Tae Hoon Kim (Department of Radiology and the Research Institute of Radiological Science, Gangnam Severance Hospital, Yonsei University College of Medicine). Kyunghwa Han, an expert in statistics, provided statistical analysis and advice.

References

  1. Hansell DM, Bankier AA, MacMahon H, McLoud TC, Muller NL, Remy J. Fleischner Society: glossary of terms for thoracic imaging. Radiology 2008;246:697-722 https://doi.org/10.1148/radiol.2462070712
  2. MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Mayo JR, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017. Radiology 2017;284:228-243 https://doi.org/10.1148/radiol.2017161659
  3. Heuvelmans MA, Oudkerk M. Management of subsolid pulmonary nodules in CT lung cancer screening. J Thorac Dis 2015;7:1103-1106
  4. American College of Radiology. Lung CT Screening Reporting & Data System (Lung-RADS), version 1.1. Available at. https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/Lung-Rads. Published 2019. Accessed Mar 5, 2020
  5. Detterbeck FC, Boffa DJ, Kim AW, Tanoue LT. The eighth edition lung cancer stage classification. Chest 2017;151:193-203
  6. Travis WD, Brambilla E, Noguchi M, Nicholson AG, Geisinger KR, Yatabe Y, et al. International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary classification of lung adenocarcinoma. J Thorac Oncol 2011;6:244-285 https://doi.org/10.1097/JTO.0b013e318206a221
  7. Lee HY, Lee KS. Ground-glass opacity nodules: histopathology, imaging evaluation, and clinical implications. J Thorac Imaging 2011;26:106-118 https://doi.org/10.1097/RTI.0b013e3181fbaa64
  8. Ridge CA, Yildirim A, Boiselle PM, Franquet T, Schaefer-Prokop CM, Tack D, et al. Differentiating between subsolid and solid pulmonary nodules at CT: inter- and intraobserver agreement between experienced thoracic radiologists. Radiology 2016;278:888-896 https://doi.org/10.1148/radiol.2015150714
  9. Penn A, Ma M, Chou BB, Tseng JR, Phan P. Inter-reader variability when applying the 2013 Fleischner guidelines for potential solitary subsolid lung nodules. Acta Radiol 2015;56:1180-1186 https://doi.org/10.1177/0284185114551975
  10. Kakinuma R, Ashizawa K, Kuriyama K, Fukushima A, Ishikawa H, Kamiya H, et al. Measurement of focal ground-glass opacity diameters on CT images: interobserver agreement in regard to identifying increases in the size of ground-glass opacities. Acad Radiol 2012;19:389-394 https://doi.org/10.1016/j.acra.2011.12.002
  11. Matsuguma H, Nakahara R, Anraku M, Kondo T, Tsuura Y, Kamiyama Y, et al. Objective definition and measurement method of ground-glass opacity for planning limited resection in patients with clinical stage IA adenocarcinoma of the lung. Eur J Cardiothorac Surg 2004;25:1102-1106 https://doi.org/10.1016/j.ejcts.2004.02.004
  12. Ko JP, Suh J, Ibidapo O, Escalon JG, Li J, Pass H, et al. Lung adenocarcinoma: correlation of quantitative CT findings with pathologic findings. Radiology 2016;280:931-939 https://doi.org/10.1148/radiol.2016142975
  13. Cohen JG, Goo JM, Yoo RE, Park CM, Lee CH, Van Ginneken B, et al. Software performance in segmenting ground-glass and solid components of subsolid nodules in pulmonary adenocarcinomas. Eur Radiol 2016;26:4465-4474 https://doi.org/10.1007/s00330-016-4317-3
  14. Travis WD, Brambilla E, Nicholson AG, Yatabe Y, Austin JHM, Beasley MB, et al. The 2015 World Health Organization classification of lung tumors: impact of genetic, clinical and radiologic advances since the 2004 classification. J Thorac Oncol 2015;10:1243-1260 https://doi.org/10.1097/JTO.0000000000000630
  15. White S, Pharoah M. Oral radiology: principles and interpretation. 4th ed. St. Louis, MO: Mosby 2009:270-274
  16. Gucuk A, Uyeturk U. Usefulness of hounsfield unit and density in the assessment and treatment of urinary stones. World J Nephrol 2014;3:282-286 https://doi.org/10.5527/wjn.v3.i4.282
  17. Aoki T, Hanamiya M, Uramoto H, Hisaoka M, Yamashita Y, Korogi Y. Adenocarcinomas with predominant ground-glass opacity: correlation of morphology and molecular biomarkers. Radiology 2012;264:590-596 https://doi.org/10.1148/radiol.12111337
  18. Gandara DR, Aberle D, Lau D, Jett J, Akhurst T, Heelan R, et al. Radiographic imaging of bronchioloalveolar carcinoma: screening, patterns of presentation and response assessment. J Thorac Oncol 2006;1:S20-26 https://doi.org/10.1016/S1556-0864(15)30005-8
  19. Naidich DP, Bankier AA, MacMahon H, Schaefer-Prokop CM, Pistolesi M, Goo JM, et al. Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society. Radiology 2013;266:304-317 https://doi.org/10.1148/radiol.12120628
  20. Lee JH, Kim TH, Lee S, Han K, Byun MK, Chang YS, et al. High versus low attenuation thresholds to determine the solid component of ground-glass opacity nodules. PLoS One 2018;13:e0205490
  21. Chae HD, Park CM, Park SJ, Lee SM, Kim KG, Goo JM. Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas. Radiology 2014;273:285-293 https://doi.org/10.1148/radiol.14132187
  22. Son JY, Lee HY, Lee KS, Kim JH, Han J, Jeong JY, et al. Quantitative CT analysis of pulmonary ground-glass opacity nodules for the distinction of invasive adenocarcinoma from pre-invasive or minimally invasive adenocarcinoma. PLoS One 2014;9:e104066
  23. Luo T, Xu K, Zhang Z, Zhang L, Wu S. Radiomic features from computed tomography to differentiate invasive pulmonary adenocarcinomas from non-invasive pulmonary adenocarcinomas appearing as part-solid ground-glass nodules. Chin J Cancer Res 2019;31:329-338 https://doi.org/10.21147/j.issn.1000-9604.2019.02.07
  24. Gong J, Liu J, Hao W, Nie S, Zheng B, Wang S, et al. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images. Eur Radiol 2020;30:1847-1855 https://doi.org/10.1007/s00330-019-06533-w
  25. Lee KH, Goo JM, Park SJ, Wi JY, Chung DH, Go H, et al. Correlation between the size of the solid component on thin-section CT and the invasive component on pathology in small lung adenocarcinomas manifesting as ground-glass nodules. J Thorac Oncol 2014;9:74-82 https://doi.org/10.1097/JTO.0000000000000019