Benefit of replacing the Sigma-60 by the Sigma-Eye applicator. A Monte Carlo-based uncertainty analysis.

BACKGROUND AND PURPOSE: To investigate the clinical benefit of replacing the BSD-2000 Sigma-60 with the Sigma-Eye applicator, taking into account effects of uncertainties in tissue and water bolus parameters. PATIENTS AND METHODS: For 20 patients, specific absorption rate (SAR) and temperature distributions were calculated and optimized, based on computed tomography (CT) scans in treatment position. The impact of uncertainties on predicted distributions was studied using a Monte Carlo uncertainty assessment. RESULTS: Replacing the Sigma-60 by the Sigma-Eye applicator resulted in a higher SAR in the tumor [on average a decrease of the hotspot tumor quotient (HTQ) by 24%; p < 0.001], and higher temperatures (T90: +0.4°C, p < 0.001; T50: +0.6°C, p < 0.001) using literature values and SAR optimization. When temperature optimization (T90) was used, a larger average increase was found (T90: +0.7°C, p < 0.001; T50: +0.8°C, p < 0.001). When taking into account uncertainties, a decrease of 23% in median HTQ (p < 0.001) and an increase in T50 and T90 of 0.4°C (p < 0.001) could be demonstrated. CONCLUSION: Based on this uncertainty analysis, significant and clinically relevant improvements in HTQ and tumor temperature were achieved when replacing the Sigma-60 by the Sigma-Eye applicator.

Optimizing deep hyperthermia treatments: are locations of patient pain complaints correlated with modelled SAR peak locations?

During deep hyperthermia treatment, patient pain complaints due to heating are common when maximizing power. Hence, there exists a good rationale to investigate whether the locations of predicted SAR peaks by hyperthermia treatment planning (HTP) are correlated with the locations of patient pain during treatment. A retrospective analysis was performed, using the treatment reports of 35 patients treated with deep hyperthermia controlled by extensive treatment planning. For various SAR indicators, the average distance from a SAR peak to a patient discomfort location was calculated, for each complaint. The investigated V(0.1 closest) (i.e. the part of the 0.1th SAR percentile closest to the patient complaint) performed the best, and leads to an average distance between the SAR peak and the complaint location of 3.9 cm. Other SAR indicators produced average distances that were all above 10 cm. Further, the predicted SAR peak location with V(0.1) provides a 77% match with the region of complaint. The current study demonstrates that HTP is able to provide a global indication of the regions where hotspots during treatment will most likely occur. Further development of this technology is necessary in order to use HTP as a valuable toll for objective and advanced SAR steering. The latter is especially valid for applications that enable 3D SAR steering.

A literature survey on indicators for characterisation and optimisation of SAR distributions in deep hyperthermia, a plea for standardisation.

PURPOSE: To evaluate the predictive value of SAR indicators by assessing the correlation of a SAR indicator with the corresponding predicted temperature. Ultimately, this should lead to a number of verified SAR indicators for characterization and optimization of a predicted SAR distribution. METHODS: A literature survey is followed by an evaluation of the SAR indicators on their functionality, using a set of heuristic classification criteria. To obtain an objective assessment of the predictive value for SAR characterisation, all SAR indicators are evaluated by correlating the value of the SAR indicator to the predicted target temperature when heated with the BSD2000 Sigma 60 applicator. Two methods were followed. First, the specificity of the SAR indicator to target temperature was assessed for each of the 36 patient-specific models, using 30 randomly chosen phase and amplitude settings. Secondly, each SAR indicator was used as a goal function to assess its suitability for optimisation purposes. RESULTS: Only a selected number of SAR indicators correlate well with tumour/target-temperature. Hence, for target-related properties, an adequate set of SAR indicators is found in the literature. For hotspots, modifications are desirable. For optimisation purposes, improved objective functions have been defined. CONCLUSIONS: From the correlation of the SAR indicators with tumour temperature, a preferred set of SAR indicators is derived: For target heating, 'average SAR ratio', 'Hotspot-target SAR ratio', and 'homogeneity coefficient' provide suitable objective criteria, while for hotspot reduction, 'Hotspot-target SAR ratio' is considered the most useful indicator. For optimisation procedures, 'Hotspot-target SAR ratio' is currently the most suitable objective function.

Patient positioning in deep hyperthermia: influences of inaccuracies, signal correction possibilities and optimization potential.

In this deep hyperthermia study, the robustness of SAR (specific absorption rate) patterns to patient-position variations is assessed, as well as the possibilities to correct for improper positioning and the benefits of non-standard positions. With a finite element model, the SAR distributions were predicted for ten patients at 33 positions. Position sensitivity is assessed for both SAR-focus steering, i.e. settings based on a calculated focus in a cylindrical patient representation, and HTP (hyperthermia treatment planning)-guided steering, i.e. model-based optimization of the SAR distribution. Position inaccuracies of less than 1 cm do not significantly affect SAR patterns. For SAR-focus steering, the SAR maximum is not always at the desired focus location, especially in the Y (anterior/posterior)- and Z (axial)-directions. For a maximum shift of 5 cm in all directions, both SAR-focus steering and HTP-guided steering are suitable to correct for improper positioning up to the level that none of the investigated positions appears preferable. Current positioning precision is sufficient in the X (right-left)-direction, but precision measurements are needed to reach the desired accuracy in the Y-direction. In the Z-direction, a cranial shift of the applicator is predicted to be beneficial. If the position is known accurately, correction of the treatment setting is possible without loss of heating efficiency. Additionally, no preferable positions exist.

Complaint-adaptive power density optimization as a tool for HTP-guided steering in deep hyperthermia treatment of pelvic tumors.

For an efficient clinical use of HTP (hyperthermia treatment planning), optimization methods are needed. In this study, a complaint-adaptive PD (power density) optimization as a tool for HTP-guided steering in deep hyperthermia of pelvic tumors is developed and tested. PD distribution in patients is predicted using FE-models. Two goal functions, Opt1 and Opt2, are applied to optimize PD distributions. Optimization consists of three steps: initial optimization, adaptive optimization after a first complaint and increasing the weight of a region after recurring complaints. Opt1 initially considers only target PD whereas Opt2 also takes into account hot spots. After patient complaints though, both limit PD in a region. Opt1 and Opt2 are evaluated in a phantom test, using patient models and during hyperthermia treatment. The phantom test and a sensitivity study in ten patient models, show that HTP-guided steering is most effective in peripheral complaint regions. Clinical evaluation in two groups of five patients shows that time between complaints is longer using Opt2 (p = 0.007). However, this does not lead to significantly different temperatures (T50s of 40.3 (Opt1) versus 40.1 degrees C (Opt2) (p = 0.898)). HTP-guided steering is feasible in terms of PD reduction in complaint regions and in time consumption. Opt2 is preferable in future use, because of better complaint reduction and control.