Skip to main content
SpringerLink
Log in

Baseline drift vector of multiple points on body surface using a near-infrared camera

  • Scientific Paper
  • Published:
Physical and Engineering Sciences in Medicine Aims and scope Submit manuscript

Abstract

The purpose of this study was to extract the three-dimensional (3D) vector of the baseline drift baseline drift vector (BDV) of the specific points on the body surface and to demonstrate the importance of the 3D tracking of the body surface. Our system consisted of a near-infrared camera (NIC: Kinect V2) and software that recognized and tracked blue stickers as markers. We acquired 3D coordinates of 30 markers stuck on the body surface for 30 min for eight healthy volunteers and developed a simple technique to extract the BDV. The BDV on the sternum, rib, and abdomen was extracted from the measured data. BDV per min. was analyzed to estimate the frequency to exceed a given tolerance. Also, the correlation among BDVs for multiple body sites was analyzed. The longitudinal baseline drift was observed in the BDV of healthy volunteers. Among the eight volunteers, the maximum probability that the BDV per min. exceeded the tolerance of 1 mm and 2 mm was 30% and 15%, respectively. The correlation among BDVs of multiple body sites suggested a potential feasibility to distinguish the translational movement of the whole area and the respiratory movement. In conclusion, we constructed the 3D tracking system of multiple points on the body surface using a noninvasive NIC at a low cost and established the method to extract the BDV. The existence of the longitudinal baseline drift showed the importance of the 3D tracking in the body surface.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data availability

Not applicable.

Code availability

Not applicable.

References

  1. Videtic GM, Stephans K, Reddy C et al (2010) Intensity-modulated radiotherapy-based stereotactic body radiotherapy for medically inoperable early-stage lung cancer: excellent local control. Int J Radiat Oncol Biol Phys 77(2):344–349

    Article  Google Scholar 

  2. Yamashita H, Haga A, Takahashi W et al (2014) Volumetric modulated arc therapy for lung stereotactic radiation therapy can archive high local control rates. Radiat Oncol 9:243

    Article  Google Scholar 

  3. Giraud P, Yorke E, Jiang S, Simon L, Rosenzweig K, Mageras G (2006) Reduction of organ motion effects in IMRT and conformal 3D radiation delivery by using gating and tracking techniques. Cancer Radiother 10(5):269–282

    Article  CAS  Google Scholar 

  4. Worm ES, Hoyer M, Fledelius W, Hansen AT, Poulsen PR (2013) Variations in magnitude and directionality of respiratory target motion throughout full treatment course of stereotactic body radiotherapy for tumor in the liver. Acta Oncol 52(7):1437–1444

    Article  Google Scholar 

  5. Takao S, Miyamoto N, Matsuura T et al (2016) Intrafractional baseline shift or drift of lung tumor motion during gated radiation therapy with a real-time tumor-tracking system. Int J Radiat Oncol Biol Phys 94(1):172–180

    Article  Google Scholar 

  6. Seppenwoolde Y, Shirato H, Kitamura K et al (2002) Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. Int J Radiat Oncol Biol Phys 53(4):822–834

    Article  Google Scholar 

  7. Zhao B, Yang Y, Li T, Li X, Heron DE, Huq MS (2012) Dosimetric effect of intrafraction tumor motion in phase gated lung stereotactic body radiotherapy. Med Phys 39(11):6629–6637

    Article  Google Scholar 

  8. Peulen H, Belderbos J, Rossi M, Sonke JJ (2014) Mid-ventilation based PTV margin is stereotactic body radiotherapy (SBRT): a clinical evaluation. Radiother Oncol 110(3):511–516

    Article  Google Scholar 

  9. Tarohda TI, Ishiguro M, Hasegawa K et al (2011) The management of tumor motions in the stereotactic irradiation to lung cancer under the use of Abches to control active breathing. Med Phys 38(7):4141–4146

    Article  Google Scholar 

  10. Thiyagarajan R, Shinha SN, Ravichandran R et al (2016) Respiratory gated radiotherapy-pretreatment patient specific quality assurance. J Med Phys 41(1):65–70

    Article  Google Scholar 

  11. Cheung Y, Sawant A (2015) An externally and internally deformable, programmable lung motion phantom. Med Phys 42(5):2585–2593

    Article  Google Scholar 

  12. Freislederer P, Reiner M, Hoischen W et al (2015) Characteristics of gated treatment using an optical surface imaging and gating system on an Elekta linac. Radiat Oncol 10:68

    Article  Google Scholar 

  13. Willoughby T, Kupelian P, Pouliot J et al (2006) Target localization and real-time tracking using the calypso 4D localization system in patients with localized prostate cancer. Int J Radiat Oncol Biol Phys 65(2):528–534

    Article  Google Scholar 

  14. Onishi H, Kawakami H, Marino K et al (2005) A newly developed simple and accurate respiratory indicator relative to measurement of 2-point levels of abdominal and chest walls: for assurance of patient self-judged breath holding techniques for irradiation of lung cancer with small internal margin. Int J Radiat Oncol Biol Phys 63:S534

    Article  Google Scholar 

  15. Fayad H, Pan T, Pradier O, Visvikis D (2012) Patient specific respiratory motion modeling using a 3D patient’s external surface. Med Phys 39(6):3386–3395

    Article  Google Scholar 

  16. Lachat E, Macher H, Landes T, Grussenmeyer P (2015) Assessment and calibration of a RGB-D camera (Kinect v2 sensor) towards a potential use for close-range 3D modeling. Remote Sens 7(10):13070–13097

    Article  Google Scholar 

  17. Saito A, Ohashi A, Nishio T et al (2019) Automatic calibration of an arbitrarily-set near-infrared camera for patient surface respiratory monitoring. Med Phys 46(3):1163–1174

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by AMED under Grant Number 16he1002008h0002. We would like to thank Editage (www.editage.jp) for English language editing.

Funding

This research was supported by AMED under Grant Number 16he1002008h0002.

Author information

Authors and Affiliations

  1. Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami, Hiroshima, Hiroshima, 734-8551, Japan

    Atsuyuki Ohashi, Yuji Murakami & Yasushi Nagata

  2. Ashiya Radiotherapy Clinic Nozomi, 3-84 Yokocho, Ashiya, Hyogo, 659-0034, Japan

    Atsuyuki Ohashi, Hiroshi Watanabe & Koji Ikenaga

  3. Department of Medical Physics, Graduate School of Medicine, Tokyo Women’s Medical University, 8-1 Kawada-cho, Shinjuku, Tokyo, 162-8666, Japan

    Teiji Nishio

  4. Department of Radiation Oncology, Hiroshima University Hospital, 1-2-3 Kasumi, Minami, Hiroshima, Hiroshima, 734-8551, Japan

    Akito Saito

  5. Information and Communication Research Division, Mizuho Information & Research Institute, Inc., 2-3 Kanda-Nishikicho, Chiyoda-ku, Tokyo, 101-8443, Japan

    Daiki Hashimoto, Hidemasa Maekawa & Makiko Suitani

  6. Hiroshima High-Precision Radiotherapy Cancer Center, 3-2-2 Futabanosato, Higashi Ward, Hiroshima, Hiroshima, 732-0057, Japan

    Shuichi Ozawa

  7. Department of Radiation Oncology, Graduate School of Medicine, Tokyo Women’s Medical University, 8-1 Kawada-cho, Shinjuku, Tokyo, 162-8666, Japan

    Masato Tsuneda

  8. Insightec Japan K.K., Hachioji First Square 7F 3-20-6, Myojin-cho, Hachioji-shi, Tokyo, 192-0046, Japan

    Atsuyuki Ohashi

Authors
  1. Atsuyuki Ohashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Teiji Nishio
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Akito Saito
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Daiki Hashimoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hidemasa Maekawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yuji Murakami
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Shuichi Ozawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Makiko Suitani
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Masato Tsuneda
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Hiroshi Watanabe
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Koji Ikenaga
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Yasushi Nagata
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AO: Writing—Original draft, Software, Investigation, Methodology. TN: Project administration, Funding acquisition, Conceptualization, Writing—Review and editing. AS: Writing—Review and editing, Software, Methodology, Validation. DH: Software. HM: Software. YM: Methodology, Validation. SO: Investigation. MS: Software. MT: Software. HW: Investigation. KI: Supervision. YN: Supervision.

Corresponding author

Correspondence to Atsuyuki Ohashi.

Ethics declarations

Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Ethical approval

This study was approved by Institutional Review Board of Hiroshima University (E-542).

Consent to participate

Informed consent was obtained from all individual participants included in the study.

Consent for publication

The participant has consented to the submission of the scientific article to the journal.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ohashi, A., Nishio, T., Saito, A. et al. Baseline drift vector of multiple points on body surface using a near-infrared camera. Phys Eng Sci Med 45, 143–155 (2022). https://doi.org/10.1007/s13246-021-01097-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13246-021-01097-w

Keywords

Search

Navigation