The Impact of Tumor Treating Fields on Glioblastoma Progression Patterns

Glas, Martin; Ballo, Matthew T.; Bomzon, Zéev; Urman, Noa; Levi, Shay; Lavy-Shahaf, Gitit; Jeyapalan, Suriya; Sio, Terence T.; DeRose, Paul; Misch, Martin; Taillibert, Sophie; Ram, Zvi; Hottinger, Andreas F.; Easaw, Jacob C.; Kim, Chae-Yong; Mohan, Suyash; Stupp, Roger

doi:10.1016/j.ijrobp.2021.12.152

Cited by 29 publications

(19 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The treatment requires the chronic placement of transducer arrays that generate alternating electric fields on the patient’s head. Recent studies suggest that increased electric fields intensity is associated with better treatment outcomes ( Ballo et al, 2019 ; Glas et al, 2022 ). TTFields treatment planning requires the segmentation of GBM tissues on post-operative MR images for evaluating the distribution of TTFields in the tumor.…”

Section: Introductionmentioning

confidence: 99%

Post-operative glioblastoma multiforme segmentation with uncertainty estimation

Gazit¹,

Faran²,

Stepovoy³

et al. 2022

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Segmentation of post-operative glioblastoma multiforme (GBM) is essential for the planning of Tumor Treating Fields (TTFields) treatment and other clinical applications. Recent methods developed for pre-operative GBM segmentation perform poorly on post-operative GBM MRI scans. In this paper we present a method for the segmentation of GBM in post-operative patients. Our method incorporates an ensemble of segmentation networks and the Kullback–Leibler divergence agreement score in the objective function to estimate the prediction label uncertainty and cope with noisy labels and inter-observer variability. Moreover, our method integrates the surgery type and computes non-tumorous tissue delineation to automatically segment the tumor. We trained and validated our method on a dataset of 340 enhanced T1 MRI scans of patients that were treated with TTFields (270 scans for train and 70 scans for test). For validation, we developed a tool that uses the uncertainty map along with the segmentation result. Our tool allows visualization and fast editing of the tissues to improve the results dependent on user preference. Three physicians reviewed and graded our segmentation and editing tool on 12 different MRI scans. The validation set average (SD) Dice scores were 0.81 (0.11), 0.71 (0.24), 0.64 (0.25), and 0.68 (0.19) for whole-tumor, resection, necrotic-core, and enhancing-tissue, respectively. The physicians rated 72% of the segmented GBMs acceptable for treatment planning or better. Another 22% can be edited manually in a reasonable time to achieve a clinically acceptable result. According to these results, the proposed method for GBM segmentation can be integrated into TTFields treatment planning software in order to shorten the planning process. To conclude, we have extended a state-of-the-art pre-operative GBM segmentation method with surgery-type, anatomical information, and uncertainty visualization to facilitate a clinically viable segmentation of post-operative GBM for TTFields treatment planning.

show abstract

Section: Introductionmentioning

confidence: 99%

Post-operative glioblastoma multiforme segmentation with uncertainty estimation

Gazit¹,

Faran²,

Stepovoy³

et al. 2022

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Glas M et al. ( 61 ) reported a direct correlation between TTFields dose distribution and tumor response, confirming the therapeutic activity of TTFields and the reason for optimizing array placement to maximize the TTFields dose in regions with the highest risk of progression.…”

Section: Discussionmentioning

confidence: 85%

Research on application of tumor treating fields in glioblastoma: A bibliometric and visual analysis

Du¹,

Chen²,

Yu³

et al. 2022

Front. Oncol.

View full text Add to dashboard Cite

BackgroundGlioblastoma, one of the common tumors of the central nervous system (CNS), is prone to recurrence even after standard treatment protocols. As an innovative physiotherapy method emerging in recent years, the tumor treating fields (TTFields) technique has been approved for the treatment of glioblastoma due to its non-invasive and portable features. The purpose of this study is to visualize and analyze the scientific results and research trends in TTFields therapy for glioblastoma.MethodsPublications related to TTFields therapy for glioblastoma were searched in the Web of Science Core Collection (WoSCC) database in September 2022. A bibliometric and visual analysis of publications in this field was performed mainly using CiteSpace and R software for country/region, author, journal, reference and keyword.ResultsA total of 618 publications in this field were retrieved, and 248 were finally obtained according to the search criteria, including 159 articles (64.11%) and 89 reviews (37.89%). The cumulative number of publications increased year by year, with an average growth rate (AGR) of 28.50%. The test results of Pearson correlation coefficient showed a high positive correlation between publications and citations (r=0.937, p<0.001). The USA had the largest number of publications (123, 49.60%), followed by Germany (32, 12.90%) and China (30, 12.10%). As for the country/region collaborations, the USA cooperated most closely with other countries/regions, followed by Germany and China. The degree of collaboration (DC) between countries/regions was 25.81%. The institutions with the largest number of publications were Tel Aviv Univ (10), Harvard Med Sch (10) and Novocure Ltd (10). Moreover, Wong E (18) possessed the greatest number of publications, followed by Weinberg U (11) and Kirson E (10). The DC between authors was 97.58%. STUPP R (236) was the most cited author followed by KIRSON ED (164) and GILADI M (104). JOURNAL OF NEURO-ONCOLOGY (22) was the journal with the largest number of published publications (75), followed by FRONTIERS IN ONCOLOGY (15) and CANCERS (13). The top 10 keywords that occurred frequently included glioblastoma (156), tumor treating field (152), temozolomide (134), randomized phase III (48), brain (46), survivor (46), cancer (44), trial (42), alternating electric field (42) and radiotherapy (36). Furthermore, cluster analysis was performed on the basis of keyword co-occurrence, and finally 15 clusters were formed to determine the current research status and future development trend of TTFields therapy for glioblastoma.ConclusionTTFields has been increasingly known as the fourth novel physical anti-tumor therapy in addition to surgery, radiotherapy and anti-tumor drugs. Cooperation and communication between countries/regions need to be enhanced in future research. Several studies have demonstrated the therapeutic potential of TTFields in glioma, and its application alone or in combination with other treatments has become a current research hotspot.

show abstract

“…TTFields has been approved in the treatment of first-time presentation and recurrent glioblastoma, potentially extending survival in some cases by more than 5 months [ 99 ]. Increased usage time through the day and increased electric field dose delivery to the tumour are both associated with improved survival [ 100 ]. The mechanism by which TTFields inhibits tumor growth is not well understood, but there is evidence supporting disruption of the mitotic spindle and activation of a localized immune response as potential mechanisms [ 101 , 102 ].…”

Section: Transcranial Alternating Current Stimulation (Tacs)mentioning

confidence: 99%

Neuromodulation techniques – From non-invasive brain stimulation to deep brain stimulation

Davidson,

Bhattacharya,

Sarica

et al. 2024

Neurotherapeutics

View full text Add to dashboard Cite

The Impact of Tumor Treating Fields on Glioblastoma Progression Patterns

Cited by 29 publications

References 29 publications

Post-operative glioblastoma multiforme segmentation with uncertainty estimation

Post-operative glioblastoma multiforme segmentation with uncertainty estimation

Research on application of tumor treating fields in glioblastoma: A bibliometric and visual analysis

Neuromodulation techniques – From non-invasive brain stimulation to deep brain stimulation

Contact Info

Product

Resources

About