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Comparison between CT- and MRI-derived head and neck cancer target volumes using an integrated MRI-tri-60Co teletherapy device

  • Original Research
  • Published:
Journal of Radiation Oncology

Abstract

Purpose

Radiation treatment planning is typically based on the identification of a gross tumor volume (GTV) using computed tomography (CT). The clinical implementation of an integrated MRI-radiation therapy delivery unit allows for a strict comparison of CT- and MRI-derived GTVs for head and neck cancer.

Materials and methods

Twenty-six consecutive patients with squamous cell carcinoma of the head and neck were selected and planned for intensity-modulated radiotherapy (IMRT) on a novel tri-60Co teletherapy system equipped with a 0.35 T MRI (ViewRay Incorporated, Oakwood Village, OH). All patients had measurable disease. Pre-treatment MRIs were imported into a contouring interface where the primary GTV were assessed and compared to those obtained from a registered CT with the patient in the identical position and immobilization apparatus.

Results

The median GTV as derived from the CT and MRI was 27.2 cm3 (range 3.8 to 155.0 cm3) and 34.9 cm3 (range, 5.0 to 189.5 cm3), respectively (p = 0.01). The MRI-derived GTV was larger than the CT-derived GTV in 21 of the 26 cases and was smaller in the remaining 5 cases. Among the 21 cases where the MRI-derived GTV was larger, the median difference in absolute GTV per individual patient was 6.9 cm3 (range 2.1 to 33.4 cm3), representing a 25% difference on average. The median concordance index for patients with de novo versus recurrent disease was 0.83 and 0.66, respectively (p = 0.03).

Conclusion

Significant differences in GTV extent were noted between MRI- and CT-derived ViewRay images. The implications for treatment planning are discussed.

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References

  1. Wardman K, Prestwich RJ, Gooding MJ et al (2016) The feasibility of atlas-based automatic segmentation of MRI for head and neck radiotherapy planning. J Appl Clin Med Phys 17:6051

    Article  Google Scholar 

  2. Van Dijke CF, van Waes PF (1992) Head and neck tumors, MRI versus CT: a technology assessment pilot study. Eur J Radiol 14(3):235–239. https://doi.org/10.1016/0720-048X(92)90094-P

    Article  PubMed  Google Scholar 

  3. Emami B, Sethi A, Petruzzelli GJ (2003) Influence of MRI on target volume delineation and IMRT planning in nasopharyngeal carcinoma. Int J Radiat Oncol Biol Phys 57(2):481–488. https://doi.org/10.1016/S0360-3016(03)00570-4

    Article  PubMed  Google Scholar 

  4. Rasch C, Keus R, Pameijer FA, Koops W, de Ru V, Muller S, Touw A, Bartelink H, van Herk M, Lebesque JV (1997) The potential impact of CT-MRI matching on tumor volume delineation in advanced head and neck cancer. Int J Radiat Oncol Biol Phys 39(4):841–848. https://doi.org/10.1016/S0360-3016(97)00465-3

    Article  PubMed  CAS  Google Scholar 

  5. Thiagaragan A, Caria N, Schoder H et al (2012) Target volume delineation in oropharyngeal cancer: impact of PET, MRI, and physical examination. Int J Radiat Oncol Biol Phys 83(1):220–227. https://doi.org/10.1016/j.ijrobp.2011.05.060

    Article  Google Scholar 

  6. Ahmed M, Schmidt M, Sohaib A, Kong C, Burke K, Richardson C, Usher M, Brennan S, Riddell A, Davies M, Newbold K, Harrington KJ, Nutting CM (2010) The value of magnetic resonance imaging in target volume delineation of base of tongue tumors—a study using flexible surface coils. Radiother Oncol 94(2):161–167. https://doi.org/10.1016/j.radonc.2009.12.021

    Article  PubMed  Google Scholar 

  7. Hanvey S, McJury M, Tho LM, Glegg M, Thomson M, Grose D, James A, Rizwanullah M, Paterson C, Foster J (2013) The influence of MRI scan position on patients with oropharyngeal cancer undergoing radical radiotherapy. Radiat Oncol 8(1):129. https://doi.org/10.1186/1748-717X-8-129

    Article  PubMed  PubMed Central  Google Scholar 

  8. Cannon DM, Lee NY (2008) Recurrence in region of spared parotid gland after definitive intensity-modulated radiotherapy for head and neck cancer. Int J Radiat Oncol Biol Phys 70(3):660–665. https://doi.org/10.1016/j.ijrobp.2007.09.018

    Article  PubMed  Google Scholar 

  9. Seitz O, Chambron-Pinho N, Middendorp M, Sader R, Mack M, Vogl TJ, Bisdas S (2009) 18F-Fluorodeoxyglucose-PET/CT to evaluate tumor, nodal disease, and gross tumor volume of oropharyngeal and oral cavity cancer: comparison with MR imaging and validation with surgical specimen. Neuroradiology 51(10):677–686. https://doi.org/10.1007/s00234-009-0586-8

    Article  PubMed  Google Scholar 

  10. Liao XB, Mao YP, Liu LZ et al (2008) How does magnetic resonance imaging influence staging according to AJCC staging system fornasopharyngeal carcinoma compared with computed tomography? Int J Radiat Oncol Biol Phys 72:1268–1277

    Article  Google Scholar 

  11. Chung NN, Ting LL, Hsu WC, Lui LT, Wang PM (2004) Impact of magnetic resonance imaging versus CT on nasopharyngeal carcinoma: primary tumor target delineation for radiotherapy. Head Neck 26(3):241–246. https://doi.org/10.1002/hed.10378

    Article  PubMed  Google Scholar 

  12. Bolzoni A, Cappiello J, Piazza C, Peretti G, Maroldi R, Farina D, Nicolai P (2004) Diagnostic accuracy of magnetic resonance imaging in the assessment of mandibular involvement in oral-oropharyngeal squamous cell carcinoma: a prospective study. Arch Otolaryngol Head Neck Surg 130(7):837–843. https://doi.org/10.1001/archotol.130.7.837

    Article  PubMed  Google Scholar 

  13. Banko B, Dukic V, Milovanovic J et al (2011) Diagnostic significance of magnetic resonance imaging in preoperative evaluation of patients with laryngeal tumors. Eur Arch Otorhinolaryngol 268(11):1617–1623. https://doi.org/10.1007/s00405-011-1701-0

    Article  PubMed  Google Scholar 

  14. Loevner LA, Yousem DM, Montone KT, Weber R, Chalian AA, Weinstein GS (1997) Can radiologist accurately predict preepiglottic space invasion with MR imaging? AJR Am J Roentgenol 169(6):1681–1687. https://doi.org/10.2214/ajr.169.6.9393190

    Article  PubMed  CAS  Google Scholar 

  15. Park JO, Jung SL, Joo YH, Jung CK, Cho KJ, Kim MS (2011) Diagnostic accuracy of magnetic resonance imaging (MRI) in the assessment of tumor invasion depth in oral/oropharyngeal cancer. Oral Oncol 47(5):381–386. https://doi.org/10.1016/j.oraloncology.2011.03.012

    Article  PubMed  Google Scholar 

  16. Van der Hoorn A, van Laar PJ, Holtman GA, Westerlann HE (2017) Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with head and neck tumors, a systematic review and meta-analysis. PLoS One 12(5):e0177986. https://doi.org/10.1371/journal.pone.0177986

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Weygand J, Fuller CD, Ibbott GS, Mohamed ASR, Ding Y, Yang J, Hwang KP, Wang J (2016) Spatial precision in magnetic resonance imaging-guided radiation therapy: the role of geometric distortion. Int J Radiat Oncolo Biol Phys 95(4):1304–1316. https://doi.org/10.1016/j.ijrobp.2016.02.059

    Article  Google Scholar 

  18. Stanescu T, Wachowicz K, Jaffray DA (2012) Characterization of tissue magnetic susceptibility-induced distortions for MRIgRT. Med Phys 39(12):7185–7193. https://doi.org/10.1118/1.4764481

    Article  PubMed  CAS  Google Scholar 

  19. Chen X, Prior P, Chen GP et al (2016) Technical note: dose effects of 1.5 T transverse magnetic field on tissue interfaces in MRI-guided radiotherapy. Med Phys 43(8Part1):4797–4802. https://doi.org/10.1118/1.4959534

    Article  PubMed  Google Scholar 

  20. Anderson CM, Sun W, Buatti JM et al (2014) Interobserver and intermodality variability in GTV delineation on CT, FDG-PET, and MR images of head and neck cancer. Jacobs J Radiat Oncol 1:006

    PubMed  PubMed Central  Google Scholar 

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Correspondence to Allen M. Chen.

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The authors declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Statement of informed consent was not applicable since the manuscript does not contain any patient data.

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Chen, A.M., Raghavan, G., Cao, M. et al. Comparison between CT- and MRI-derived head and neck cancer target volumes using an integrated MRI-tri-60Co teletherapy device. J Radiat Oncol 7, 147–155 (2018). https://doi.org/10.1007/s13566-017-0337-0

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  • DOI: https://doi.org/10.1007/s13566-017-0337-0

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