Contour-based lung dose prediction for breast proton therapy.

Abstract:

PURPOSE:This study evaluates the feasibility of lung dose prediction based on target contour and patient anatomy for breast patients treated with proton therapy. METHODS:Fifty-two randomly selected patients were included in the cohort, who were treated to 50.4-66.4 Gy(RBE) to the left (36), right (15), or bilateral (1) breast with uniform scanning (32) or pencil beam scanning (20). Anterior-oblique beams were used for each patient. The prescription doses were all scaled to 50.4 Gy(RBE) for the current analysis. Isotropic expansions of the planning target volume of various margins m were retrospectively generated and compared with isodose volumes in the ipsilateral lung. The fractional volume V of each expansion contour within the ipsilateral lung was compared with dose-volume data of clinical plans to establish the relationship between the margin m and dose D for the ipsilateral lung such that VD  = V(m). This relationship enables prediction of dose-volume VD from V(m), which could be derived from contours before any plan is generated, providing a goal of plan quality. Lung V20 Gy(RBE) and V5 Gy(RBE) were considered for this pilot study, while the results could be generalized to other dose levels and/or other organs. RESULTS:The actual V20 Gy(RBE) ranged from 6% to 23%. No statistically significant difference in V20 Gy(RBE) was found between breast irradiation and chest wall irradiation (P = 0.8) or between left-side and right-side treatment (P = 0.9). It was found that V(1.1 cm) predicted V20 Gy(RBE) to within 5% root-mean-square deviation (RMSD) and V(2.2 cm) predicted V5 Gy(RBE) to within 6% RMSD. CONCLUSION:A contour-based model was established to predict dose to ipsilateral lung in breast treatment. Clinically relevant accuracy was demonstrated. This model facilitates dose prediction before treatment planning. It could serve as a guide toward realistic clinical goals in the planning stage.

journal_name

J Appl Clin Med Phys

authors

Zeng C,Sine K,Mah D

doi

10.1002/acm2.12436

subject

Has Abstract

pub_date

2018-11-01 00:00:00

pages

53-59

issue

6

issn

1526-9914

journal_volume

19

pub_type

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