Bellizzi GG, Drizdal T, van Rhoon GC, Crocco L, Isernia T, Paulides MM. Predictive value of SAR based quality indicators for head and neck hyperthermia treatment quality.
Int J Hyperthermia 2019;
36:456-465. [PMID:
30973030 DOI:
10.1080/02656736.2019.1590652]
[Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Academic Contribution Register] [Indexed: 12/15/2022] Open
Abstract
PURPOSE
Hyperthermia treatment quality determines treatment effectiveness as shown by the clinically derived thermal-dose effect relations. SAR based optimization factors are used as possible surrogate for temperature, since they are not affected by thermal tissue properties uncertainty and variations. Previously, target coverage (TC) at the 25% and 50% iso-SAR level was shown predictive for treatment outcome in superficial hyperthermia and the target-to-hot-spot-quotient (THQ) was shown to highly correlate with predictive temperature in deep pelvic hyperthermia. Here, we investigate the correlation with temperature for THQ and TC using an 'intermediate' scenario: semi-deep hyperthermia in the head & neck region using the HYPERcollar3D.
METHODS
Fifteen patient-specific models and two different planning approaches were used, including random perturbations to circumvent optimization bias. The predicted SAR indicators were compared to predicted target temperature distribution indicators T50 and T90, i.e., the median and 90th percentile temperature respectively.
RESULTS
The intra-patient analysis identified THQ, TC25 and TC50 as good temperature surrogates: with a mean correlation coefficient R2T50 = 0.72 and R2T90=0.66. The inter-patient analysis identified the highest correlation with TC25 (R2T50 = 0.76, R2T90=0.54) and TC50 (R2T50 = 0.74, R2T90 = 0.56).
CONCLUSION
Our investigation confirmed the validity of our current strategy for deep hyperthermia in the head & neck based on a combination of THQ and TC25. TC50 was identified as the best surrogate since it enables optimization and patient inclusion decision making using one single parameter.
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