P11.37 Evaluating water content and electrical properties at 200 kHz in brain and GBM tumor tissue of three TTFields patients with conventional imaging

BACKGROUND

Electrical properties (EPs) of brain tissue, specifically brain tumors, crucially determine the field distribution of Tumor Treating Fields (TTFields), an anti-mitotic treatment approved for glioblastoma multiforme (GBM). Due to the correlation of TTFields efficacy and field intensity at the tumor region, the knowledge of EPs in each patient is of great importance for patient-specific planning of treatment. Water content electrical properties tomography (wEPT) is a non-invasive imaging technique using water content (WC) maps obtained from rapidly acquired and processed conventional sequences to estimate the EPs of brain tissue at 128 MHz. The WC maps of this approach are constructed from two spin echo sequences similar to a T1 and a PD image. Following previous studies in rat tumor models demonstrating promising wEPT mapping of EPs in the brain at 200, this study examines the feasibility of this approach in human GBM patients.

MATERIAL AND METHODS

For three patients of the EF-14 trial population, we divided T1 and PD images pixel-by-pixel to obtain the image ratio. Using a transfer function, WC maps were generated and maps of the electrical conductivity σ and the relative permittivity ε r at 200 kHz were calculated with two different equations.

RESULTS

The median value of estimated WC remains similar in healthy brain tissues among all patients, ~73.5% in the white matter, ~82% in the gray matter. The median values of wEPT-estimated σ at 200 kHz in the white matter is ~0.09 S/m and in the gray matter ~0.18 S/m, corresponding median values of ε r at 200 kHz are ~2100 and ~3000 in white and gray matter respectively. Contrary, in the tumor the spread between the median values of WC and EPs is much higher. Stating the most important findings, in the necrosis median WC are 90.3%, 92.3%, 85.2% in patients 1–3 respectively with corresponding median σ values of 0.494, 0.657, 0.25 S/m. In the enhancing tumor the spread of median WC is even higher (67.2%, 83.6%, 85.5%), yet lower spread but also very heterogeneous median σ values of 0.075 S/m, 0.208, 0.259 S/m are estimated with wEPT.

CONCLUSION

Our results demonstrate the adaption of wEPT for mapping of WC and EPs at 200 kHz in three human GBM patients. In contrast to the vastly irregular tumor tissue, our estimations in healthy brain tissue are similar between patients and in accordance with EPs experimentally measured during our animal experiments and consistent with reported values in the literature. Hence, wEPT is a promising, fast technique based on regular MRI that might help patient-specific treatment planning of TTFields therapy, although the mapping of tumor tissue needs further confirmation in a greater population and investigations of EPs of excised tumor tissue samples should be conducted.

P11.50 The dielectric properties of brain tumor tissue

BACKGROUND

Recently, tumor treating fields (TTFields) were established for the treatment of newly diagnosed GBM. One of the most crucial parameters defining the treatment efficacy of TTFields is the electric field intensity. The dielectric properties of the normal intracranial compartments are well established, allowing the prediction of the electric field distribution. In contrast, there is no data available about the dielectric properties of brain tumor tissue. In this study we determined the dielectric properties of brain tumors by analyzing resected tissue following a fast acquisition protocol. To account for the intratumoral heterogeneity, different regions of the tumor were analyzed separately.

MATERIAL AND METHODS

A cohort of 84 patients with tumors of different histology and malignancy grade have been recruited (meningioma: n=26; brain metastases n=18; low grade glioma n=6; glioblastoma n=34). Tissue probes were acquired whenever possible from the vital tumor area, and perinecrotic compartment identified intraoperatively using neuronavigation, intraoperative ultrasound and fluorescence guidance. After acquisition, the tissue was measured immediately to avoid artifacts induced by temperature change, differences of fluid composition as well as post resection ischemia. A fragment was dissected from each tissue sample and was placed into a cylindrical cell with a known diameter. Two parallel electrodes were placed on both sides of the sample and the thickness of the tissue was measured using a micrometer. The impedance was recorded at frequencies 20Hz-1MHz using a software specifically developed for this study, which controls the LCR meter (Keysight Technologies, Santa Rosa, USA). The measured impedance was translated into dielectric properties of the sample (conductivity and relative permittivity) based on the parallel plate model, the recorded complex impedance and the geometry of the samples. Each tissue probe was fixed, H&E stained and histologically analyzed.

RESULTS

We found significant differences between the conductivity of different types of tumors with meningiomas showing the lowest conductivity (mean conductivity [S/m]: 0.193; range: 0.327 - 0.113) and GBM tissue exhibiting the highest conductivity values (mean conductivity [S/m]: 0.402; range: 0.893 - 0.157). Consistently, the perinecrotic areas of tumors displayed lower conductivity values compared to the solid tumor compartments. Also, we found a significant intratumoral heterogeneity in tumors of one specific histological diagnosis.

CONCLUSION

The dielectric properties of intracranial tumors appear to be depending on histological class and malignancy grade and show significant intratumoral heterogeneity. These results may allow a more precise modelling of electric field intensity distribution within the tumor.

P14.69 Evaluation of electric field intensity delivered by Tumor-Treating Fields therapy to PET-defined metabolic volumes in recurrent glioblastomas

BACKGROUND

Tumor-Treating Fields (TTFields) therapy is a clinical treatment option for patients with newly-diagnosed and recurrent glioblastomas. Electric field intensities (EFIs) delivered to the tumor mass may affect treatment responses. In this study, we used the patients’ neuroimaging data to create realistic head models and evaluate: (i) the magnitude of EFIs delivered to the tumor mass; (ii) factors affecting the EFI values; and (iii) factors affecting treatment responses as assessed by amino acid PET.

MATERIAL AND METHODS

Fourteen recurrent glioblastomas in 9 patients were evaluated with α-[11C]-methyl-L-tryptophan (AMT)-PET before and up to 3 months after TTFields therapy (mean follow-up: 2.3 months). Individual MRI and CT scans were used to create patient-specific realistic head models and simulate TTFields delivery to the tumors. For each direction of treatment (antero-posterior, left-right), two 9-disk transducer arrays were simulated using disks placed according to the patients’ NovoTAL System™ based treatment plan. To generate TTFields, an alternating voltage difference (200V peak-to-peak, 200 kHz) was imposed on the outer surfaces of the disks. The simulations were performed using the Sim4Life V3.0 (ZMT-Zurich) quasi-electrostatic solver. The field intensities were normalized to simulate 2A peak-to-peak current supplied by the device. 3D EFI maps were created and fused with the pre- and post-TTFields PET images to measure EFIs delivered to the PET-defined metabolic tumor volume. Interval changes of static AMT uptake and kinetic PET variables were also evaluated.

RESULTS

The mean EFI delivered to the tumors varied between 1.34–2.43 V/cm (mean: 1.86 V/cm). Fronto-parietal tumors received higher mean EFI than temporal lobe tumors (p=0.05). Most tumors showed decreasing (n=9) or stable (n=4) AMT uptake on follow-up PET imaging after TTFields therapy. Higher EFIs delivered to the tumors (r=-0.56, p=0.04) and concomitant bevacizumab treatment (n=7, p=0.01) were associated with a greater PET response. On tracer kinetic analysis, the AMT uptake responses correlated with transport rate changes (p=0.04).

CONCLUSION

TTFields treatment of recurrent glioblastomas delivers variable EFIs to the metabolic tumor volume. Treatment responses on PET are driven by decreased amino acid transport rates, whose magnitude is associated with higher EFIs delivered to the tumor mass and also with concomitant antiangiogenic treatment in those with combined therapy. (The cost of the PET scans was supported by a grant from NovoCure Ltd., Haifa, Israel)

P11.18 Tumor treating fields (TTFields) treatment of spinal cord metastases

BACKGROUND

Tumor Treating Fields (TTFields) is an anti-mitotic cancer treatment approved for the treatment of Glioblastoma multiforme (GBM) and is currently also investigated in a phase III trial in 1–10 brain metastases from non-small cell lung cancer (METIS). Apart from spread to the brain, some cancer types, such as breast cancer, lung cancer, and melanoma, may lead to metastatic spread to the spinal cord. Previous studies have shown that reported transducer array layouts for the treatment of abdominal/pelvic tumors (e.g. pancreatic cancer), with one pair of arrays positioned on the anterior and posterior of the patient, and the second pair of arrays placed on each side of the thorax, yield therapeutically insufficient field intensities of <1 V/cm in the spinal cord. This finding probably results from the anatomical structure of the spine, consisting of the cerebrospinal fluid as a highly conductive layer, encased by a resistive bone structure that shunts the current delivered across the body by the arrays away from the spine. This simulation-based study aimed at resolving this challenge by identifying novel array layouts on the body that effectively deliver TTFields to the spine.

MATERIAL AND METHODS

For the simulations of the TTFields delivery to the spine, a human male 34 years old realistic computational model (DUKE v3.1 by ITI’S, Zurich) and the ZMT’s Sim4Life v4.0 electro-quasi-static solver was utilized. TTFields were simulated by imposing an alternating current with a current density of 200 mA/disk and a frequency of 150 kHz on the outer surfaces of the disks of each pair of arrays.

RESULTS

For one of the tested array layouts, a high electric field was shown to be induced within the spinal cord and surrounding CSF: Our calculations of mean field intensity within the spine and nerves from vertebrae T8-T9 at the top to L3-L4 at the bottom added up to 1.77 V/cm. This layout consisted of the placement of a pair of arrays on the back of the patient, with one array positioned above the section in the spine to which treatment would be delivered, and the other array positioned below the target section. Notably, the resulting electric field is directed along the spine in this setting (ie, vertically).

CONCLUSION

Our results demonstrate that treatment of the whole spinal cord and nerves in a single direction can be achieved by placing a pair of transducer arrays on the patient’s back: one array on the neck, and one at the bottom of the spine. For the development of an active treatment in the perpendicular direction, further studies need to be conducted.

P11.25 Assessing electrical properties of cells as predictive marker for patient-specific TTFields response and optimal frequency

BACKGROUND

Tumor treating fields (TTFields) are currently approved for the treatment of glioblastoma multiforme (GBM, using 200 kHz), and being tested in other tumor types such as non-small cell lung cancer and brain metastases occurring in this indication (LUNAR and METIS trials, using 150 kHz). Response to TTFields in cancer cells was empirically shown to be frequency-dependent specific for cell type; however, there are no markers available predicting optimal frequency or response in different cancer types or individual patients to date. There is evidence indicating electrical properties determine the optimal anti-mitotic frequency. This study analyzed the correlation of electrical properties of cells with their optimal TTFields frequency and sensitivity using the 3DEP reader (LabTech) to determine the electrical properties with the help of Dielectrophoresis (DEP) force. With this technique, cell movements within electric fields of different frequencies can by analyzed based on the physical effect of DEP, exercising a force on polarizable particles inside a non-homogeneous electric field.

MATERIAL AND METHODS

We used the 3DEP reader to obtain baseline properties (permittivity and conductivity) of 17 different cell lines of several tumor types. The resulting curves were analyzed by a 2-way ANOVA. Additionally, we determined the optimal frequency for maximum cytotoxic effect for each cell line using the inovitroTM system and eventually compared with the detected electrical properties.

RESULTS

We found cell lines with an optimal TTFields frequency of 150 kHz (corresponding to cells with a membrane capacitance in the lower range of the observed 3DEP curves, n=9) to possess significantly different (p<0.001) electrical properties from cells with an optimal TTFields frequency of 200 kHz (n=8). According to the curve differences in the lower frequency range, the measure of membrane capacitance served as a good predictor for TTFields response.

CONCLUSION

This study showed a correlation of cell membrane capacitance and optimal TTFields frequency and response. Our results provide a substantial rationale for further studies investigating the predictive potential of electrical properties of tumor cells as a measure for the optimal frequency and sensitivity to TTFields in individual patients.

Modelling Tumor Treating Fields for the treatment of lung-based tumors

Tumor Treating Fields (TTFields), low-intensity electric fields in the frequency range of 100-500 kHz, exhibit antimitotic activity in cancer cells. TTFields were approved by the U. S. Food and Drug Administration for the treatment of recurrent glioblastoma in 2011. Preclinical evidence and pilot studies suggest that TTFields could be effective for treating certain types of lung cancer, and that treatment efficacy depends on the electric field intensity. To optimize TTFields delivery to the lungs, it is important to understand how TTFields distribute within the chest. Here we present simulations showing how TTFields are distributed in the thorax and torso, and demonstrate how the electric field distribution within the body can be controlled by personalizing the layout of the arrays used to deliver the field.