Literature DB >> 15972985

High-resolution temperature-based optimization for hyperthermia treatment planning.

H P Kok1, P M A Van Haaren, J B Van de Kamer, J Wiersma, J D P Van Dijk, J Crezee.   

Abstract

In regional hyperthermia, optimization techniques are valuable in order to obtain amplitude/phase settings for the applicators to achieve maximal tumour heating without toxicity to normal tissue. We implemented a temperature-based optimization technique and maximized tumour temperature with constraints on normal tissue temperature to prevent hot spots. E-field distributions are the primary input for the optimization method. Due to computer limitations we are restricted to a resolution of 1 x 1 x 1 cm3 for E-field calculations, too low for reliable treatment planning. A major problem is the fact that hot spots at low-resolution (LR) do not always correspond to hot spots at high-resolution (HR), and vice versa. Thus, HR temperature-based optimization is necessary for adequate treatment planning and satisfactory results cannot be obtained with LR strategies. To obtain HR power density (PD) distributions from LR E-field calculations, a quasi-static zooming technique has been developed earlier at the UMC Utrecht. However, quasi-static zooming does not preserve phase information and therefore it does not provide the HR E-field information required for direct HR optimization. We combined quasi-static zooming with the optimization method to obtain a millimetre resolution temperature-based optimization strategy. First we performed a LR (1 cm) optimization and used the obtained settings to calculate the HR (2 mm) PD and corresponding HR temperature distribution. Next, we performed a HR optimization using an estimation of the new HR temperature distribution based on previous calculations. This estimation is based on the assumption that the HR and LR temperature distributions, though strongly different, respond in a similar way to amplitude/phase steering. To verify the newly obtained settings, we calculate the corresponding HR temperature distribution. This method was applied to several clinical situations and found to work very well. Deviations of this estimation method for the AMC-4 system were typically smaller than 0.2 degrees C in the volume of interest, which is accurate enough for treatment planning purposes.

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Year:  2005        PMID: 15972985     DOI: 10.1088/0031-9155/50/13/011

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  10 in total

1.  Novel multisensor probe for monitoring bladder temperature during locoregional chemohyperthermia for nonmuscle-invasive bladder cancer: technical feasibility study.

Authors:  Ernesto R Cordeiro; Debby E Geijsen; Paul J Zum Vörde Sive Vörding; Gerben Schooneveldt; Jan Sijbrands; Maarten C Hulshof; Jean de la Rosette; Theo M de Reijke; Hans Crezee
Journal:  J Endourol       Date:  2013-10-10       Impact factor: 2.942

2.  Guideline for the clinical application, documentation and analysis of clinical studies for regional deep hyperthermia: quality management in regional deep hyperthermia.

Authors:  G Bruggmoser; S Bauchowitz; R Canters; H Crezee; M Ehmann; J Gellermann; U Lamprecht; N Lomax; M B Messmer; O Ott; S Abdel-Rahman; M Schmidt; R Sauer; A Thomsen; R Wessalowski; G van Rhoon
Journal:  Strahlenther Onkol       Date:  2012-09       Impact factor: 3.621

3.  Computation of ultimate SAR amplification factors for radiofrequency hyperthermia in non-uniform body models: impact of frequency and tumour location.

Authors:  Bastien Guérin; Jorge F Villena; Athanasios G Polimeridis; Elfar Adalsteinsson; Luca Daniel; Jacob K White; Bruce R Rosen; Lawrence L Wald
Journal:  Int J Hyperthermia       Date:  2017-05-11       Impact factor: 3.914

4.  Temperature superposition for fast computation of 3D temperature distributions during optimization and planning of interstitial ultrasound hyperthermia treatments.

Authors:  Vasant A Salgaonkar; Punit Prakash; Chris J Diederich
Journal:  Int J Hyperthermia       Date:  2012       Impact factor: 3.914

Review 5.  Simulation techniques in hyperthermia treatment planning.

Authors:  Margarethus M Paulides; Paul R Stauffer; Esra Neufeld; Paolo F Maccarini; Adamos Kyriakou; Richard A M Canters; Chris J Diederich; Jurriaan F Bakker; Gerard C Van Rhoon
Journal:  Int J Hyperthermia       Date:  2013-05-14       Impact factor: 3.914

6.  Online feedback focusing algorithm for hyperthermia cancer treatment.

Authors:  Kung-Shan Cheng; Vadim Stakhursky; Paul Stauffer; Mark Dewhirst; Shiva K Das
Journal:  Int J Hyperthermia       Date:  2007-11       Impact factor: 3.914

Review 7.  Integrating Loco-Regional Hyperthermia Into the Current Oncology Practice: SWOT and TOWS Analyses.

Authors:  Niloy R Datta; H Petra Kok; Hans Crezee; Udo S Gaipl; Stephan Bodis
Journal:  Front Oncol       Date:  2020-06-12       Impact factor: 6.244

8.  Reaching Deeper: Absolute In Vivo Thermal Reading of Liver by Combining Superbright Ag2S Nanothermometers and In Silico Simulations.

Authors:  José Lifante; Yingli Shen; Irene Zabala Gutierrez; Irene Rubia-Rodríguez; Daniel Ortega; Nuria Fernandez; Sonia Melle; Miriam Granado; Jorge Rubio-Retama; Daniel Jaque; Erving Ximendes
Journal:  Adv Sci (Weinh)       Date:  2021-03-03       Impact factor: 16.806

9.  Fast Adaptive Temperature-Based Re-Optimization Strategies for On-Line Hot Spot Suppression during Locoregional Hyperthermia.

Authors:  H Petra Kok; Johannes Crezee
Journal:  Cancers (Basel)       Date:  2021-12-28       Impact factor: 6.639

Review 10.  The role of hyperthermia in the treatment of locally advanced cervical cancer: a comprehensive review.

Authors:  Marloes IJff; Johannes Crezee; Arlene L Oei; Lukas J A Stalpers; Henrike Westerveld
Journal:  Int J Gynecol Cancer       Date:  2022-01-19       Impact factor: 3.437

  10 in total

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