scholarly journals Tumor-Treating Fields at EMBC 2019: A Roadmap to Developing a Framework for TTFields Dosimetry and Treatment Planning

2020 ◽  
pp. 3-17
Author(s):  
Ze’ev Bomzon ◽  
Cornelia Wenger ◽  
Martin Proescholdt ◽  
Suyash Mohan
Keyword(s):  
Patient Outcome ◽  
Treatment Planning ◽  
Electric Fields ◽  
Dose Distribution ◽  
Pleural Mesothelioma ◽  
Adaptive Planning ◽  
Tumor Bed ◽  
Short Overview ◽  
Tumor Treating Fields ◽  
Rigorous Treatment

AbstractTumor Treating Fields (TTFields) are electric fields known to exert an anti-mitotic effect on cancerous tumors. TTFields have been approved for the treatment of glioblastoma and malignant pleural mesothelioma. Recent studies have shown a correlation between TTFields doses delivered to the tumor bed and patient survival. These findings suggest that patient outcome could be significantly improved with rigorous treatment planning, in which numerical simulations are used to plan treatment in order to optimize delivery of TTFields to the tumor bed.Performing such adaptive planning in a practical and meaningful manner requires a rigorous and scientifically proven framework defining TTFields dose and showing how dose distribution influences disease progression in different malignancies (TTFields dosimetry). At EMBC 2019, several talks discussing key components related to TTFields dosimetry and treatment planning were presented. Here we provide a short overview of this work and discuss how it sets the foundations for the emerging field of TTFields dosimetry and treatment planning.

RBIO-01. DEVELOPING THE FRAMEWORK FOR TUMOR TREATING FIELDS (TTFIELDS) TREATMENT PLANNING FOR A PATIENT WITH ASTROCYTOMA IN THE SPINAL CORD

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi191-vi191
Author(s):  
Jennifer de Los Santos ◽  
Smadar Arvatz ◽  
Oshrit Zeevi ◽  
Shay Levi ◽  
Noa Urman ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Treatment Planning ◽  
Spinal Tumor ◽  
Specific Model ◽  
Patient Specific ◽  
Transducer Array ◽  
Tumor Bed ◽  
Tumor Treating Fields ◽  
Transducer Arrays ◽  
Healthy Female

Abstract The use of Tumor Treating Fields (TTFields) following resection and chemoradiation has increased survival in patients with Glioblastoma. Patient-specific planning for TTFields transducer array placement has been demonstrated to maximize TTFields dose at the tumor: providing higher TTFields intensity (≥ 1.0 V/cm) and power density (≥ 1.1 mW/cm3) which are associated with improved overall survival. Treatment planning was performed for a 48 year old patient following T10-L1 laminectomy, gross total resection, and postoperative chemoradiation for an anaplastic astrocytoma of the spinal cord. An MRI at 3 weeks following chemoradiation showed tumor recurrence. Based on the post-chemoradiation MRI, a patient-specific model was created. The model was created by modifying a realistic computational phantom of a healthy female. To mimic the laminectomy, the lamina in T10-L1 was removed, and the region assigned electric conductivity similar to that of muscle. A virtual mass was introduced into the spinal cord. Virtual transducer arrays were placed on the model at multiple positions, and delivery of TTFields simulated. The dose delivered by different transducer array layouts was calculated, and the layouts that yielded maximal dose to the tumor and spine identified. Transducer array layouts, in which the arrays were placed on the back of the patient with one array above the tumor and one array below the tumor, yielded the highest doses at the tumor site. Such layouts yielded TTFields doses of over 3.4mW/cm3 which is well above the threshold dose of 1.1 mW/cm3 reported previously [Ballo et al. Red Jour 2019]. The framework developed for TTFields dosimetry and treatment planning for this spinal tumor will have the potential to increase dose delivery to the tumor bed while optimizing placement that may enhance comfort and encourage device usage.

scholarly journals NIMG-65. STUDY OF LOCAL PERTURBATION IN COMPUTATIONAL MODELLING ON TUMOR TREATING FIELDS (TTFIELDS) THERAPY

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii162-ii162
Author(s):  
Oshrit Zeevi ◽  
Zeev Bomzon ◽  
Tal Marciano
Keyword(s):  
Electric Field ◽  
Treatment Planning ◽  
Computational Models ◽  
Computational Modelling ◽  
Clinical Trial Data ◽  
Patient Specific ◽  
Local Perturbation ◽  
Tumor Bed ◽  
Tumor Treating Fields ◽  
Local Perturbations

Abstract INTRODUCTION Tumor Treating Fields (TTFields) are an approved therapy for glioblastoma (GBM). A recent study combining post-hoc analysis of clinical trial data and extensive computational modelling demonstrated that TTFields dose at the tumor has a direct impact on patient survival (Ballo MT, et al. Int J Radiat Oncol Biol Phys, 2019). Hence, there is rationale for developing TTFields treatment planning tools that rely on numerical simulations and patient-specific computational models. To assist in the development of such tools is it important to understand how inaccuracies in the computational models influence the estimation of the TTFields dose delivered to the tumor bed. Here we analyze the effect of local perturbations in patient-specific head models on TTFields dose at the tumor bed. METHODS Finite element models of human heads with tumor were created. To create defects in the models, conductive spheres with varying conductivities and radii were placed into the model’s brains at different distances from the tumor. Virtual transducer arrays were placed on the models, and delivery of TTFields numerically simulated. The error in the electric field induced by the defects as a function of defect conductivity, radius, and distance to tumor was investigated. RESULTS Simulations showed that when a defect of radius R is placed at a distance, d >7R, the error is below 1% regardless of the defect conductivity. Further the defects induced errors in the electric field that were below 1% when σrR/d < 0.16, where σrR/d < 0.16, where σr = (σsphere – σsurrounding)/(σsphere + σsurrounding).σsurroundings is the average conductivity around the sphere and σsphere is the conductivity of the sphere. CONCLUSIONS This study demonstrates the limited impact of local perturbations in the model on the calculated field distribution. These results could be used as guidelines on required model accuracy for TTFields treatment planning.

Analysis of the EF-14 phase III trial reveals that tumor treating fields alter progression patterns in glioblastoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 2055-2055
Author(s):  
Suriya A. Jeyapalan ◽  
Steven A Toms ◽  
Andreas Felix Hottinger ◽  
Lawrence Kleinberg ◽  
Erqi Pollom ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Electric Fields ◽  
Growth Patterns ◽  
T Test ◽  
Phase Iii ◽  
Tumor Bed ◽  
Tumor Treating Fields ◽  
Alternating Electric Fields ◽  
Trial Testing ◽  
Chi Squared

2055 Background: The EF-14 [NCT00916409] trial showed that addition of alternating electric fields (Tumor Treating Fields, TTFields) to Temozolomide (TMZ) resulted in improved survival in newly diagnosed Glioblastoma (GBM) patients with supratentorial tumors treated compared to TMZ alone. TTFields delivery is planned to optimize dose at the tumor bed, leading to the hypothesis that TTFields treated patients are more likely to exhibit distal progressions, including progression to the infratentorial brain where TTFields dose is minimal when targeting the supratentorium. Here we present analysis of the EF-14 trial testing this hypothesis. Methods: Patients on treatment for more than two months who had an MRI that exhibited progression were included in the study (treatment: N=280/466, control: N=122/229). Regions of enhancing tumor, necrosis and resection were contoured on T1 contrast MRIs acquired at baseline and at the date of first progression. New lesions at progression were classified as distal if they appeared outside of a Proximal Boundary Zone (PBZ) of 20 mm surrounding the lesions identified in the baseline MRI. The rate of occurrence of distal progressions in the TTFields-treated arm was compared to the rate observed in the control arm. Patients with (distal) infratentorial progression were identified. Results: Distal progressions were more common in the treatment arm (49/280 (18%) vs. 10/122 (8%) P<0.02; chi-squared). Infratentorial progression were observed in 4% (10 patients) of the treatment arm vs. 0 patients in the control (P<0.002 t-test). Distal lesions at progression were more distant from the original lesion in the TTFields treated arm (58.57 + 28.12 mm vs 46.61 + 20.48 mm, P<0.02; Wilcoxon rank sum test. The relative tumor growth rates in TTFields treated patients were significantly slower than those observed in the control arm (0.036+ 0.126 ml/day vs. 0.036+ 0.183 ml/day P<0.03; t-test). Conclusions: This analysis indicates that adding TTFields to TMZ could impact GBM growth patterns. The results suggest that TTFields increases local control of tumor growth, emphasizing the need for adaptive treatment after progression to control progressing disease. Clinical trial information: NCT00916409.

A general approach to optimizing tumor treating fields therapy.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14668-e14668
Author(s):  
Zeev Bomzon ◽  
Noa Urman ◽  
Hadas Sara Hershkovich ◽  
Eilon David Kirson ◽  
Ariel Naveh ◽  
...  
Keyword(s):  
Field Distribution ◽  
Electric Fields ◽  
Computational Models ◽  
Array Size ◽  
Patient Comfort ◽  
Improve Patient Survival ◽  
Tumor Bed ◽  
Tumor Treating Fields ◽  
Alternating Electric Fields ◽  
Improve Patient

e14668 Background: Tumor Treating Fields (TTFields) are alternating electric fields used to non-invasively treat cancer. TTFields are delivered via transducer arrays placed on the skin close to the tumor. Post-hoc analysis [1] has shown that delivering higher field power to the tumor and increasing usage (percent of time patient is actively treated) improve patient survival. Thus, optimizing the position of arrays to maximize TTFields power at the tumor could improve survival. At the same time, minimizing the array area to maximize patient comfort and consequently maximizing usage is also likely to improve survival. However, optimizing TTFields delivery is non-trivial since the field distribution is influenced by array positioning and geometry, the anatomy of the patient and the heterogeneous electric properties of different tissues. Here we present a general approach to optimizing Tumor Treating Fields using numerical simulations. Methods: Delivery of TTFields to the brains, lungs and abdomens of realistic computational models was investigated. The effect of the transducer array size and position on the field distribution within the phantoms was analyzed, and an approach for optimizing TTFields delivery developed. Results: Field power is generally highest in the region between the arrays, with larger arrays generally delivering higher field power. Anatomical features such as bones, the spine or a resection cavity significantly influence the field within this region. A general approach to optimizing TTFields delivery is: Maximize field power by using the largest arrays possible. To maximize patient comfort, array size are chose so that significant portions of the skin in the region of disease are not covered by the arrays. Place virtual arrays on a realistic computational model of the patient such that the tumor is located between them and simulate TTFields delivery to the patient. Apply an iterative algorithm to shift the arrays around their initial positions until field power in the tumor bed is maximized. Conclusions: We have developed a general approach to optimizing delivery of TTFields to the tumor. Effective TTFields treatment planning is expected to improve patient outcome. [1] Ballo et. al., submitted to RED Journal 2018.

scholarly journals NIMG-06. DOES PERSONALIZING TUMOR TREATING FIELDS(TTFIELDS) WITH NOVOTAL IN GLIOBLASTOMA TREATMENT PLANNING MAKE A DIFFERENCE? INSIGHTS FROM ELECTRIC FIELD SIMULATION STUDIES

2016 ◽  
Vol 18 (suppl_6) ◽  
pp. vi124-vi124
Author(s):  
Aafia Chaudhry ◽  
Ze’ev Bomzon ◽  
Hadas Sara Hershkovich ◽  
Dario Garcia-Carracedo ◽  
Cornelia Wenger ◽  
...  
Keyword(s):  
Electric Field ◽  
Treatment Planning ◽  
Simulation Studies ◽  
Tumor Treating Fields ◽  
Field Simulation

EQUIVALENT UNIFORM DOSE SENSITIVITY TO CHANGES IN ABSORBED DOSE DISTRIBUTION

2013 ◽  
Vol 06 (01) ◽  
pp. 1250069
Author(s):  
FRANCISCO CUTANDA-HENRÍQUEZ ◽  
SILVIA VARGAS-CASTRILLÓN
Keyword(s):  
Treatment Planning ◽  
Dose Distribution ◽  
Absorbed Dose ◽  
Target Volume ◽  
Simple Expression ◽  
External Beam Radiation ◽  
Equivalent Uniform Dose ◽  
Beam Radiation ◽  
Dose Volume Histograms ◽  
Small Change

Treatment planning in external beam radiation therapy (EBRT) utilizes dose volume histograms (DVHs) as optimization and evaluation tools. They present the fraction of planning target volume (PTV) receiving more than a given absorbed dose, against the absorbed dose values, and a number of radiobiological indices can be computed with their help. Equivalent uniform dose (EUD) is the absorbed dose that, uniformly imparted, would yield the same biological effect on a tumor as the dose distribution described by the DVH. Uncertainty and missing information can affect the dose distribution, therefore DVHs can be modeled as samples from a set of possible outcomes. This work studies the sensitivity of the EUD index when a small change in absorbed dose distribution takes place. EUD is treated as a functional on the set of DVHs. Defining a Lévy distance on this set and using a suitable expansion of the functional, a very simple expression for a bound on the variation of EUD when the dose distribution changes is found. This bound is easily interpreted in terms of standard treatment planning practice.

scholarly journals Quality Assurance of Dose Distribution of Photon Beam Planning by Anisotropic Analytical Algorithm (AAA)

2013 ◽  
Vol 4 (1) ◽  
pp. 43-49
Author(s):  
M Jahangir Alam ◽  
Syed Md Akram Hussain ◽  
Kamila Afroj ◽  
Shyam Kishore Shrivastava
Keyword(s):  
Quality Assurance ◽  
Treatment Planning ◽  
Dose Distribution ◽  
Maximum Dose ◽  
Photon Beam ◽  
Field Size ◽  
Planning System ◽  
Treatment Planning System ◽  
Anisotropic Analytical Algorithm ◽  
Analytical Algorithm

A three dimensional treatment planning system has been installed in the Oncology Center, Bangladesh. This system is based on the Anisotropic Analytical Algorithm (AAA). The aim of this study is to verify the validity of photon dose distribution which is calculated by this treatment planning system by comparing it with measured photon beam data in real water phantom. To do this verification, a quality assurance program, consisting of six tests, was performed. In this program, both the calculated output factors and dose at different conditions were compared with the measurement. As a result of that comparison, we found that the calculated output factor was in excellent agreement with the measured factors. Doses at depths beyond the depth of maximum dose calculated on-axis or off-axis in both the fields or penumbra region were found in good agreement with the measured dose under all conditions of energy, SSD and field size, for open and wedged fields. In the build up region, calculated and measured doses only agree (with a difference 2.0%) for field sizes > 5 × 5 cm2 up to 25 × 25 cm2. For smaller fields, the difference was higher than 2.0% because of the difficulty in dosimetry in that region. Dose calculation using treatment planning system based on the Anisotropic Analytical Algorithm (AAA) is accurate enough for clinical use except when calculating dose at depths above maximum dose for small field size.DOI: http://dx.doi.org/10.3329/bjmp.v4i1.14686 Bangladesh Journal of Medical Physics Vol.4 No.1 2011 43-49

Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique

2018 ◽  
Vol 46 (1) ◽  
pp. 370-381 ◽  
Author(s):  
Jiawei Fan ◽  
Jiazhou Wang ◽  
Zhi Chen ◽  
Chaosu Hu ◽  
Zhen Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Treatment Planning ◽  
Dose Distribution ◽  
Three Dimensional ◽  
Learning Technique ◽  
Automatic Treatment

scholarly journals P14.114 Tumor treating fields in glioblastoma clinical practice guidelines: a European and North American landscape analysis

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii95-iii95
Author(s):  
A Lawson McLean ◽  
R Kalff ◽  
J Walter
Keyword(s):  
Clinical Practice ◽  
Electric Fields ◽  
Clinical Practice Guidelines ◽  
Practice Guidelines ◽  
Medical Oncology ◽  
German Society ◽  
Landscape Analysis ◽  
Science Literature ◽  
Tumor Treating Fields ◽  
Care Protocol

Abstract BACKGROUND Tumor treating fields (TTFields) are low-intensity alternating electric fields delivered at intermediate frequencies to disrupt cancer cell division and inhibit tumor growth, with significantly longer mean lifetime survival of 1.8 additional years in glioblastoma (GBM). International, national and local clinical practice guidelines have implications for clinical, personal and policy decision-making. Furthermore, they may impact on patients’ decisions to choose treatment at a given institution or even lead to commencement of legal proceedings for withholding therapies recommended by international guidelines. We performed an in-depth landscape analysis of clinical practice guidelines for GBM in Europe and North America to explore variation in treatment recommendations with a specific focus on TTFields. MATERIAL AND METHODS A systematic search was conducted of web sites of international guideline developers, relevant cancer agencies and the MEDLINE and Web of Science literature databases. The following information was extracted from each document meeting the inclusion criteria: whether TTFields is discussed and/or recommended in the guideline, the indications for and role of TTFields in the care protocol, the strength of the recommendation and any constraints placed on the situations where this therapy can or may be offered, including on cost grounds, where applicable. Dates of production and validity periods of the guidelines were also noted. In addition, standard operating procedures (SOPs) from several accredited comprehensive cancer centres in Germany, covering GBM care are compared, with a series of clinical vignettes presented. RESULTS The guidelines produced by the National Comprehensive Cancer Network (USA), National Institute for Health and Care Excellence (UK), German Society for Neurology, German Society for Haematology and Medical Oncology, European Association for Neuro-Oncology and European Society for Medical Oncology were critically compared. Wide variation in recommendations relating to the TTFields therapy was observed. Many guidelines had not been updated to reflect the results of the EF-14 study. CONCLUSION Discrepancy in the adoption of TTFields across clinical practice guidelines and SOPs has potential implications for care practices. This ultimately affects patient outcomes, safety and quality of care. Ideally, guidelines should be updated dynamically when new evidence indicates a need for a substantive change in the guideline based on a priori criteria. An ongoing revision process for guidelines, perhaps with shorter validity periods or a more flexible approach, may facilitate more expedient adoption of novel therapies in clinical practice guidelines and in practice. Meanwhile, therapies significantly improving OS and PFS should be recommended to patients and this should be documented.

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