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Preoperative assessment of parietal pleural invasion/adhesion of subpleural lung cancer: advantage of software-assisted analysis of 4-dimensional dynamic-ventilation computed tomography

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To evaluate the accuracy of four-dimensional (4D) dynamic-ventilation computed tomography (CT) scanning coupled with our novel image analysis software to diagnose parietal pleural invasion/adhesion of peripheral (subpleural) lung cancer.

Methods

Eighteen patients with subpleural lung cancer underwent both 4D dynamic-ventilation CT during free breathing and conventional (static) chest CT during preoperative assessment. The absence of parietal pleural invasion/adhesion was surgically confirmed in 13 patients, while the presence of parietal pleural invasion/adhesion was confirmed in 5 patients. Two chest radiologists, who were blinded to patient status, cooperatively evaluated the presence of pleural invasion/adhesion using two different imaging modalities: (i) conventional high-resolution CT images, reconstructed in the axial, coronal, and sagittal directions, and (ii) 4D dynamic-ventilation CT images combined with a color map created by image analysis software to visualize movement differences between the lung surface and chest wall. Parameters of diagnostic accuracy were assessed, including a receiver operating characteristic analysis.

Results

Software-assisted 4D dynamic-ventilation CT images achieved perfect diagnostic accuracy for pleural invasion/adhesion (sensitivity, 100%; specificity, 100%; area under the curve [AUC], 1.000) compared to conventional chest CT (sensitivity, 60%; specificity, 77%; AUC, 0.846).

Conclusion

Software-assisted 4D dynamic-ventilation CT can be considered as a novel imaging approach for accurate preoperative analysis of pleural invasion/adhesion of peripheral lung cancer.

Key Points

• 4D dynamic-ventilation CT can correctly assess parietal pleural invasion/adhesion of peripheral lung cancer.

• A unique color map clearly demonstrates parietal pleural invasion/adhesion.

• Our technique can be expanded to diagnose “benign” pleural adhesions for safer thoracoscopic surgery.

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Abbreviations

AUC:

Area under the curve

CT:

Computed tomography

IRB:

Institutional Review Board

MR:

Magnetic resonance

US:

Ultrasound

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Acknowledgements

The authors greatly thank Dr. Shinsuke Tsukagoshi, Ms. Misae Kobayashi, and Mr. Shun Muramatsu for their technical support.

The ACTIve Study Group currently consists of the following institutions:

Ohara General Hospital, Fukushima-City, Fukushima, Japan; (Kotaro Sakuma, MD, Hiroshi Moriya, MD, PhD)

Saitama International Medical Center, Saitama Medical University, Hidaka, Saitama, Japan; (Fumikazu Sakai, MD, PhD)

Kanagawa Cardiovascular and Respiratory Center, Yokohama, Kanagawa, Japan; (Tae Iwasawa, MD, PhD)

Shiga University of Medical Science, Otsu, Shiga, Japan; (Yukihiro Nagatani, MD, Norihisa Nitta, MD, Kiyoshi Murata, MD)

Osaka University, Suita, Osaka, Japan; (Masahiro Yanagawa, MD, PhD, Osamu Honda, MD, PhD, Noriyuki Tomiyama, MD, PhD)

Osaka Medical College, Takatsuki, Osaka, Japan; (Mitsuhiro Koyama, MD, PhD)

Tenri Hospital, Tenri, Nara, Japan; (Yuko Nishimoto, MD, Satoshi Noma, MD, PhD)

Kobe University, Kobe, Hyogo, Japan; (Yoshiharu Ohno, MD, PhD)

University of Occupational and Environmental Health, Kita-kyushu, Fukuoka, Japan; (Takatoshi Aoki, MD, PhD)

University of the Ryukyus, Nishihara, Okinawa, Japan; (Tsuneo Yamashiro, MD, Maho Tsubakimoto, MD, Yanyan Xu, MD, Sadayuki Murayama, MD, PhD)

Funding

The authors state that this work has not received any funding. However, this work has been partially supported by a research grant that Dr. Yamashiro received from the Japan Society for the Promotion of Science (Kakenhi-16K19837).

Author information

Authors and Affiliations

  1. Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, 207 Uehara, Nishihara, Okinawa, 903-0215, Japan

    Tsuneo Yamashiro, Maho Tsubakimoto & Sadayuki Murayama

  2. Department of Radiology, Ohara General Hospital, Fukushima City, Fukushima, Japan

    Hiroshi Moriya

  3. Department of Radiology, Shiga University of Medical Science, Otsu, Shiga, Japan

    Yukihiro Nagatani

  4. Healthcare IT Development Center, Canon Medical Systems Corporation, Otawara, Tochigi, Japan

    Tatsuya Kimoto

Authors
  1. Tsuneo Yamashiro
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  2. Hiroshi Moriya
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  3. Maho Tsubakimoto
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  4. Yukihiro Nagatani
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  5. Tatsuya Kimoto
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  6. Sadayuki Murayama
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Consortia

for the ACTIve Study Group investigators

  • Kotaro Sakuma
  • , Hiroshi Moriya
  • , Fumikazu Sakai
  • , Tae Iwasawa
  • , Yukihiro Nagatani
  • , Norihisa Nitta
  • , Kiyoshi Murata
  • , Masahiro Yanagawa
  • , Osamu Honda
  • , Noriyuki Tomiyama
  • , Mitsuhiro Koyama
  • , Yuko Nishimoto
  • , Satoshi Noma
  • , Yoshiharu Ohno
  • , Takatoshi Aoki
  • , Tsuneo Yamashiro
  • , Maho Tsubakimoto
  • , Yanyan Xu
  •  & Sadayuki Murayama

Corresponding author

Correspondence to Tsuneo Yamashiro.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Dr. Yamashiro (first author).

Conflict of interest

University of the Ryukyus, Ohara General Hospital, and Shiga University of Medical Science received a research grant from Canon Medical Systems. Mr. Kimoto is an employee of Canon Medical Systems.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board of Ohara General Hospital.

Ethical approval

Institutional Review Board approval was obtained at Ohara General Hospital.

Study subjects or cohorts overlap

Among the 18 subjects analyzed in this study, 13 had previously been included in a different research study using a completely different diagnostic approach. Thus, the results presented here do not overlap with the results presented in the previous report. Please refer to the following paper that has been attached with the manuscript as a PDF file.

Sakuma K, et al Parietal pleural invasion/adhesion of subpleural lung cancer: quantitative four-dimensional CT analysis using dynamic-ventilatory scanning. Eur J Radiol. 2017; 86(2): 36–44. doi: https://doi.org/10.1016/j.ejrad.2016.12.004.

Methodology

• Retrospective

• Observational

• Performed at one institution

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Yamashiro, T., Moriya, H., Tsubakimoto, M. et al. Preoperative assessment of parietal pleural invasion/adhesion of subpleural lung cancer: advantage of software-assisted analysis of 4-dimensional dynamic-ventilation computed tomography. Eur Radiol 29, 5247–5252 (2019). https://doi.org/10.1007/s00330-019-06131-w

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  • DOI: https://doi.org/10.1007/s00330-019-06131-w

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