Acta Neurochirurgica

, Volume 156, Issue 8, pp 1483–1489 | Cite as

Dosimetric comparison of absolute and relative dose distributions between tissue maximum ratio and convolution algorithms for acoustic neurinoma plans in Gamma Knife radiosurgery

  • Hisato Nakazawa
  • Masataka Komori
  • Yuta Shibamoto
  • Takahiko Tsugawa
  • Yoshimasa Mori
  • Tatsuya Kobayashi
Clinical Article - Neurosurgical Techniques
First Online:
Received:
Accepted:

Abstract

Background

The treatment planning for Gamma Knife (GK) stereotactic radiosurgery (SRS) that performs dose calculations based on tissue maximum ratio (TMR) algorithm has disadvantages in predicting dose in tissue heterogeneity. The latest version of the planning software is equipped with a convolution dose algorithm as an optional extra and the new algorithm is able to compensate for head inhomogeneity. However, the effect of this improved calculation method requires detailed validation in clinical cases. In this study, we compared absolute and relative dose distributions of treatment plans for acoustic neurinoma between TMR and the convolution calculation.

Methods

Twenty-nine clinically used plans created by TMR algorithm were recalculated by convolution method. Differences between TMR and convolution were evaluated in terms of absolute dose (beam-on time), dosimetric parameters including target coverage, selectivity, conformity index, gradient index, radical homogeneity index and the dose-volume relationship.

Results

The discrepancy in estimated absolute dose to the target ranged from 1 to 7 % between TMR and convolution. In addition, dosimetric parameters of the two methods achieved statistical significance. However, it was difficult to see the change of relative dose distribution by visual assessment on a monitor.

Conclusions

Convolution, heterogeneity correction calculation, and the algorithm are necessary to reduce the dosimetric uncertainty of each case in GK SRS.

Keywords

Dose calculation Gamma knife Stereotactic radiosurgery Tissue maximum ratio algorithm Convolution algorithm 
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Notes

Conflicts of interest

None.

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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  • Hisato Nakazawa
    • 1
    • 2
  • Masataka Komori
    • 1
  • Yuta Shibamoto
    • 3
  • Takahiko Tsugawa
    • 2
  • Yoshimasa Mori
    • 4
  • Tatsuya Kobayashi
    • 2
  1. 1.Department of Radiological SciencesNagoya University Graduate School of MedicineNagoyaJapan
  2. 2.Nagoya Radiosurgery CenterNagoya Kyoritsu HospitalNagoyaJapan
  3. 3.Department of RadiologyNagoya City University Graduate School of Medical SciencesNagoyaJapan
  4. 4.Department of Radiology and Radiation OncologyAichi Medical UniversityNagakuteJapan

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