Predictive value of SAR based quality indicators for head and neck hyperthermia treatment quality

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 R 2 T50 ¼ 0.72 and R 2 T90 ¼0.66. The inter-patient analysis identified the highest correlation with TC25 (R 2 T50 ¼ 0.76, R 2 T90 ¼0.54) and TC50 (R 2 T50 ¼ 0.74, R 2 T90 ¼ 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. ARTICLE HISTORY

Applying a repetitive time‐reversal method to reduce input power of a wearable hyperthermia applicator for breast cancer treatment

“…In the results section, SAR‐based indicators have been evaluated versus two thermal‐based indicators, T50 and T90. These parameters indicate the lowest temperature covering 50% and 90% of the HTV, respectively 50,51,53‐57 …”

Hyperthermia Treatment Planning: Clinical Application and Ongoing Developments

“…Quality indicators suitable for use as objective function should therefore have a good correlation with predicted temperatures. Commonly used objective functions that satisfy this criterion are the hot spot-target SAR quotient (HTQ) and the SAR target coverage (TC) [41][42][43][44]. The HTQ is defined as the ratio between the average SAR in a small normal tissue volume representing hot spots, e.g.…”

“…The HTQ is defined as the ratio between the average SAR in a small normal tissue volume representing hot spots, e.g. the 50 ml, 1% or 0.1% normal tissue volume with the highest SAR, and the volume averaged SAR in the target [41,42]. The TC can be defined as the tumour volume percentage covered by the 25% (TC25) or 50% (TC50) iso-SAR [42][43][44].…”

“…the 50 ml, 1% or 0.1% normal tissue volume with the highest SAR, and the volume averaged SAR in the target [41,42]. The TC can be defined as the tumour volume percentage covered by the 25% (TC25) or 50% (TC50) iso-SAR [42][43][44]. However, a disadvantage of SAR-based optimization remains that important cooling mechanisms as perfusion and bolus cooling are difficult to account for.…”

The Potential of Adjusting Water Bolus Liquid Properties for Economic and Precise MR Thermometry Guided Radiofrequency Hyperthermia

“…Then, the field was optimized using Matlab-based in-house developed adaptive hyperthermia tool VEDO [30]. The effect on the power deposition patterns were evaluated using hyperthermia treatment planning (HTP) parameters target-to-hotspot quotient (THQ) and the target coverage of the 50% iso-SAR volume (TC50) [31,32]. To calculate the effect on power efficiency, total input power was increased until the maximum predicted temperature in the healthy tissue reached 44 • C. This power was then used to compare the effect of the change in measured dielectric property for each solution on power efficiency, i.e., heat loss in the WB.…”