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Radiation-induced second cancer risk from stereotactic ablative radiotherapy (SABR) for lung cancer: a review of planning studies

Published online by Cambridge University Press:  11 October 2017

Vasanthan Sakthivel*
Affiliation:
Research and Development Centre, Bharathiar University, Coimbatore, Tamil Nadu, India Advanced Medical Physics, Houston, TX, USA
Ganesh Kadirampatti Mani
Affiliation:
Research and Development Centre, Bharathiar University, Coimbatore, Tamil Nadu, India Department of Radiation Physics, Kidwai Memorial Institute of Oncology, Bangalore, Karnataka, India
Sunil Mani
Affiliation:
Advanced Medical Physics, Houston, TX, USA
Raghavendiran Boopathy
Affiliation:
Advanced Medical Physics, Houston, TX, USA
*
Correspondence to: Vasanthan Sakthivel, Bharathiar University, Coimbatore, Tamil Nadu 641046, India. Tel: +1 281 813 7776. E-mail:[email protected]

Abstract

Purpose

The aim of the current study was to (i) to calculate organ equivalent dose (OED) and (ii) to estimate excess absolute risks (EARs), lifetime attributable risks (LARs) and relative risks (RRs) from stereotactic ablative radiotherapy (SABR) for lung cancer to in-field, close to field, and out of field structures.

Methods

A total of five patients with T1, T2 (≤4 cm), N0, M0 medically inoperable non-small cell lung cancer were selected for treatment planning. Patient selection criteria were based on RTOG 0236. Five treatment deliveries were investigated: (i) three-dimensional conformal radiotherapy (3DCRT), (ii) intensity-modulated radiotherapy (IMRT), (iii) intensity-modulated radiotherapy with flattening filter free beam (IMRTF), (iv) volumetric modulated arc therapy (VMAT) and (v) volumetric modulated arc therapy with flattening filter free arcs (VMATF). Delineated normal structures included chest wall, left and right lung, trachea, small and large airways, spinal cord, oesophagus and involved ribs. All plans were prescribed to 60 Gy in five fractions to primary planning target volume (PTV) volume so that ≥98% of the PTV received ≥98% of the prescription dose and internal tumour volume received 100% of the prescription dose. The OED for all delineated normal structures was calculated using differential dose volume histograms. Using risk models, the age-dependent LAR’s and RR were calculated. Additionally, the secondary cancer risk for organs inside primary radiation was analysed using sarcoma and carcinoma risk models.

Results

For all patients, the mean V20 volumes from the SABR plans were 4·1% (3DRT), 11·8% (IMRT), and 12·7% (VMAT), respectively. The EAR (combining all organs EAR) for all the organs studied, ranged from 8·5 to 10·6/10,000 persons/year for VMATF and 3DCRT, respectively. The EAR (combining all organs EAR) for all the organs studied, ranged from 8·5 to 10·6/10,000 persons/year for VMATF and 3DCRT, respectively. The absolute EAR difference between IMRT and IMRTF was low ranging from 0·2 to 0·4/10,000 persons-year, whereas delivery difference (IMRT and VMAT) had a significant impact on EAR with absolute difference ranging from 0·5 to 1·0/10,000 persons-year for IMRT and VMAT and 1·1–1·5/10,000 persons-year for IMRTF, VMATF, respectively. The LAR data showed a strong dependence on age at exposure and the LAR decreased as a function of age at exposure. The absolute attributable risk of bone sarcoma was lower with the VMAT plan and was significantly higher with the 3DCRT plan.

Conclusion

From a clinical perspective, it should be concluded that all five solutions investigated in the study can offer high quality of patient treatments and only estimates of radiation-induced malignancies can truly differentiate among them. The results suggested it would be reasonable to use the cumulative LAR difference when needed to select between treatment techniques. In conclusion, the LAR of radiation-induced secondary cancer was significantly lower when using VMATF than when using IMRT for SABR lung patients. VMATF would be the right choice for the treatment of SABR lung patients in terms of LAR. However, more work is required for the specific estimation and long-term validation and updating of the models behind LAR estimation.

Type
Original Article
Copyright
© Cambridge University Press 2017 

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