Influence of patient models and numerical methods on predicted power deposition patterns

Wust, Peter; Nadobny, Jacek; Seebass, M.; Stalling, Detlev; Gellermann, Johanna; Hege, Hans Christian; Deuflhard, Peter; Félix, R.

doi:10.1080/026567399285512

Cited by 44 publications

(3 citation statements)

References 15 publications

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“…Wust et al showed that surface models, i.e. delineated tissue boundaries for each distinct organ or tissue region, each with assigned homogenous dielectric properties, match clinical results better than models that attempt to derive heterogeneous dielectric properties directly from CT data (14, 15). Similar results were obtained from attempts to use to MR-derived heterogeneous tissue models (16, 17).…”

Section: D Patient Modelingmentioning

confidence: 99%

Simulation techniques in hyperthermia treatment planning

Paulides

Stauffer

Neufeld

et al. 2013

International Journal of Hyperthermia

163

128

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Clinical trials have shown that hyperthermia (HT), i.e. an increase of tissue temperature to 39-44°C, significantly enhance radiotherapy and chemotherapy effectiveness (1). Driven by the developments in computational techniques and computing power, personalized hyperthermia treatment planning (HTP) has matured and has become a powerful tool for optimizing treatment quality. Electromagnetic, ultrasound, and thermal simulations using realistic clinical setups are now being performed to achieve patient-specific treatment optimization. In addition, extensive studies aimed to properly implement novel HT tools and techniques, and to assess the quality of HT, are becoming more common. In this paper, we review the simulation tools and techniques developed for clinical hyperthermia, and evaluate their current status on the path from “model” to “clinic”. In addition, we illustrate the major techniques employed for validation and optimization. HTP has become an essential tool for improvement, control, and assessment of HT treatment quality. As such, it plays a pivotal role in the quest to establish HT as an efficacious addition to multi-modality treatment of cancer.

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Section: D Patient Modelingmentioning

confidence: 99%

Simulation techniques in hyperthermia treatment planning

Paulides

Stauffer

Neufeld

et al. 2013

International Journal of Hyperthermia

163

128

View full text Add to dashboard Cite

show abstract

“…Wust et al have shown that absorbed power calculations based on manually delineated dielectric models yield a much better correlation with measurements during treatment than calculations using models created by Hounsfield Unit based automatic segmentation techniques [ 41 ]. Requirements to normal tissue delineation for HTP are higher than for radiotherapy treatment planning, because of the large variation in dielectric and thermal properties between different organs and tissue regions, and in particular the electromagnetic boundary conditions (4th Maxwell equation).…”

Section: Hyperthermia Treatment Planningmentioning

confidence: 99%

Current state of the art of regional hyperthermia treatment planning: a review

et al. 2015

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Locoregional hyperthermia, i.e. increasing the tumor temperature to 40–45 °C using an external heating device, is a very effective radio and chemosensitizer, which significantly improves clinical outcome. There is a clear thermal dose-effect relation, but the pursued optimal thermal dose of 43 °C for 1 h can often not be realized due to treatment limiting hot spots in normal tissue. Modern heating devices have a large number of independent antennas, which provides flexible power steering to optimize tumor heating and minimize hot spots, but manual selection of optimal settings is difficult. Treatment planning is a very valuable tool to improve locoregional heating. This paper reviews the developments in treatment planning software for tissue segmentation, electromagnetic field calculations, thermal modeling and optimization techniques. Over the last decade, simulation tools have become more advanced. On-line use has become possible by implementing algorithms on the graphical processing unit, which allows real-time computations. The number of applications using treatment planning is increasing rapidly and moving on from retrospective analyses towards assisting prospective clinical treatment strategies. Some clinically relevant applications will be discussed.

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“…The importance of HTP is also illustrated by the decision of the European Society on Hyperthermic Oncology (ESHO) to include HTP in their quality assurance guidelines for deep hyperthermia [15,[21][22][23]. HTP prediction accuracy is, however, strongly dependent on the patient model [24][25][26][27]. For head and neck hyperthermia, the study by Verhaart et al showed many tissues are required for an accurate and realistic representation [28].…”

Section: Introductionmentioning

confidence: 99%

Impact of Number of Segmented Tissues on SAR Prediction Accuracy in Deep Pelvic Hyperthermia Treatment Planning

VilasBoas‐Ribeiro

Rhoon

Drizdal

et al. 2020

Cancers

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In hyperthermia, the general opinion is that pre-treatment optimization of treatment settings requires a patient-specific model. For deep pelvic hyperthermia treatment planning (HTP), tissue models comprising four tissue categories are currently discriminated. For head and neck HTP, we found that more tissues are required for increasing accuracy. In this work, we evaluated the impact of the number of segmented tissues on the predicted specific absorption rate (SAR) for the pelvic region. Highly detailed anatomical models of five healthy volunteers were selected from a virtual database. For each model, seven lists with varying levels of segmentation detail were defined and used as an input for a modeling study. SAR changes were quantified using the change in target-to-hotspot-quotient and maximum SAR relative differences, with respect to the most detailed patient model. The main finding of this study was that the inclusion of high water content tissues in the segmentation may result in a clinically relevant impact on the SAR distribution and on the predicted hyperthermia treatment quality when considering our pre-established thresholds. In general, our results underline the current clinical segmentation protocol and help to prioritize any improvements.

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Influence of patient models and numerical methods on predicted power deposition patterns

Cited by 44 publications

References 15 publications

Simulation techniques in hyperthermia treatment planning

Simulation techniques in hyperthermia treatment planning

Current state of the art of regional hyperthermia treatment planning: a review

Impact of Number of Segmented Tissues on SAR Prediction Accuracy in Deep Pelvic Hyperthermia Treatment Planning

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