Impact of tumor position, conductivity distribution and tissue homogeneity on the distribution of tumor treating fields in a human brain:A computer modeling study

Tumor treating fields (TTFields) are increasingly used in the treatment of glioblastoma. TTFields inhibit cancer growth through induction of alternating electrical fields. To optimize TTFields efficacy, it is necessary to understand the factors determining the strength and distribution of TTFields. In this study, we provide simple guiding principles for clinicians to assess the distribution and the local efficacy of TTFields in various clinical scenarios.We calculated the TTFields distribution using finite element methods applied to a realistic head model. Dielectric property estimates were taken from the literature. Twentyfour tumors were virtually introduced at locations systematically varied relative to the applied field. In addition, we investigated the impact of central tumor necrosis on the induced field.Local field "hot spots" occurred at the sulcal fundi and in deep tumors embedded in white matter. The field strength was not higher for tumors close to the active electrode. Left/right field directions were generally superior to anterior/posterior directions. Central necrosis focally enhanced the field near tumor boundaries perpendicular to the applied field and introduced significant field non-uniformity within the tumor.The TTFields distribution is largely determined by local conductivity differences. The well conducting tumor tissue creates a preferred pathway for current flow, which increases the field intensity in the tumor boundaries and surrounding regions perpendicular to the applied field. The cerebrospinal fluid plays a significant role in shaping the current pathways and funnels currents through the ventricles and sulci towards deeper regions, which thereby experience higher fields. Clinicians may apply these principles to better understand how TTFields will affect individual patients and possibly predict where local recurrence may occur. Accurate predictions should, however, be based on patient specific models. Future work is needed to assess the robustness of the presented results towards variations in conductivity

Enhancing predicted efficacy of tumor treating fields therapy of glioblastoma using targeted surgical craniectomy: A computer modeling study

OBJECTIVE:The present work proposes a new clinical approach to TTFields therapy of glioblastoma. The approach combines targeted surgical skull removal (craniectomy) with TTFields therapy to enhance the induced electrical field in the underlying tumor tissue. Using computer simulations, we explore the potential of the intervention to improve the clinical efficacy of TTFields therapy of brain cancer. METHODS:We used finite element analysis to calculate the electrical field distribution in realistic head models based on MRI data from two patients: One with left cortical/subcortical glioblastoma and one with deeply seated right thalamic anaplastic astrocytoma. Field strength was assessed in the tumor regions before and after virtual removal of bone areas of varying shape and size (10 to 100 mm) immediately above the tumor. Field strength was evaluated before and after tumor resection to assess realistic clinical scenarios. RESULTS:For the superficial tumor, removal of a standard craniotomy bone flap increased the electrical field strength by 60-70% in the tumor. The percentage of tissue in expected growth arrest or regression was increased from negligible values to 30-50%. The observed effects were highly focal and targeted at the regions of pathology underlying the craniectomy. No significant changes were observed in surrounding healthy tissues. Median field strengths in tumor tissue increased with increasing craniectomy diameter up to 50-70 mm. Multiple smaller burr holes were more efficient than single craniectomies of equivalent area. Craniectomy caused no significant field enhancement in the deeply seated tumor, but rather a focal enhancement in the brain tissue underlying the skull defect. CONCLUSIONS:Our results provide theoretical evidence that small and clinically feasible craniectomies may provide significant enhancement of TTFields intensity in cerebral hemispheric tumors without severely compromising brain protection or causing unacceptable heating in healthy tissues. A clinical trial is being planned to validate safety and efficacy

Importance of electrode position for the distribution of tumor treating fields (TTFields) in a human brain. Identification of effective layouts through systematic analysis of array positions for multiple tumor locations

<div><p>Tumor treating fields (TTFields) is a new modality used for the treatment of glioblastoma. It is based on antineoplastic low-intensity electric fields induced by two pairs of electrode arrays placed on the patient’s scalp. The layout of the arrays greatly impacts the intensity (dose) of TTFields in the pathology. The present study systematically characterizes the impact of array position on the TTFields distribution calculated in a realistic human head model using finite element methods. We investigate systematic rotations of arrays around a central craniocaudal axis of the head and identify optimal layouts for a large range of (nineteen) different frontoparietal tumor positions. In addition, we present comprehensive graphical representations and animations to support the users’ understanding of TTFields. For most tumors, we identified two optimal array positions. These positions varied with the translation of the tumor in the anterior-posterior direction but not in the left-right direction. The two optimal directions were oriented approximately orthogonally and when combining two pairs of orthogonal arrays, equivalent to clinical TTFields therapy, we correspondingly found a single optimum position. In most cases, an oblique layout with the fields oriented at forty-five degrees to the sagittal plane was superior to the commonly used anterior-posterior and left-right combinations of arrays. The oblique configuration may be used as an effective and viable configuration for most frontoparietal tumors. Our results may be applied to assist clinical decision-making in various challenging situations associated with TTFields. This includes situations in which circumstances, such as therapy-induced skin rash, scar tissue or shunt therapy, etc., require layouts alternative to the prescribed. More accurate distributions should, however, be based on patient-specific models. Future work is needed to assess the robustness of the presented results towards variations in conductivity.</p></div

Digitale Gesundheitsanwendungen (DiGA) im Spannungsfeld von Fortschritt und Kritik : Diskussionsbeitrag der Fachgruppe „Digital Health“ der Gesellschaft für Informatik e. V. = Digital health applications (DiGA) in the area of tension between progress and criticism – Discussion paper from the “Digital health” specialist group of the German Informatics Society

Im Dezember 2019 wurden in Deutschland Digitale Gesundheitsanwendungen (DiGA) in die Regelversorgung aufgenommen und können somit durch die gesetzlichen Krankenkassen erstattet werden, um PatientInnen bei der Behandlung von Erkrankungen oder Beeinträchtigungen zu unterstützen. Inzwischen gibt es 48 DiGA (Stand: Oktober 2023) im Verzeichnis des Bundesinstituts für Arzneimittel und Medizinprodukte (BfArM), die vor allem in den Bereichen mentale Gesundheit, Hormone und Stoffwechsel sowie Muskeln, Knochen und Gelenke eingesetzt werden. In diesem Artikel beschreibt die Fachgruppe „Digital Health“ der Gesellschaft für Informatik e. V. (GI) die aktuellen Entwicklungen rund um die DiGA sowie das derzeitige Stimmungsbild zu Themen wie Nutzerzentrierung, Akzeptanz von PatientInnen und Behandelnden sowie Innovationspotenzial. Zusammenfassend haben DiGA in den letzten 3 Jahren eine positive Entwicklung in Form eines langsam steigenden Angebots verschiedener DiGA und Leistungsbereiche erfahren. Nichtsdestotrotz sind in einigen Bereichen noch erhebliche regulatorische Weichenstellungen notwendig, um DiGA langfristig in der Regelversorgung zu etablieren. Zentrale Herausforderungen bestehen u. a. in der Nutzerzentrierung oder in der nachhaltigen Verwendung der Anwendungen

An overview and a roadmap for artificial intelligence in hematology and oncology

BACKGROUND Artificial intelligence (AI) is influencing our society on many levels and has broad implications for the future practice of hematology and oncology. However, for many medical professionals and researchers, it often remains unclear what AI can and cannot do, and what are promising areas for a sensible application of AI in hematology and oncology. Finally, the limits and perils of using AI in oncology are not obvious to many healthcare professionals. METHODS In this article, we provide an expert-based consensus statement by the joint Working Group on "Artificial Intelligence in Hematology and Oncology" by the German Society of Hematology and Oncology (DGHO), the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), and the Special Interest Group Digital Health of the German Informatics Society (GI). We provide a conceptual framework for AI in hematology and oncology. RESULTS First, we propose a technological definition, which we deliberately set in a narrow frame to mainly include the technical developments of the last ten years. Second, we present a taxonomy of clinically relevant AI systems, structured according to the type of clinical data they are used to analyze. Third, we show an overview of potential applications, including clinical, research, and educational environments with a focus on hematology and oncology. CONCLUSION Thus, this article provides a point of reference for hematologists and oncologists, and at the same time sets forth a framework for the further development and clinical deployment of AI in hematology and oncology in the future

Reimbursement of innovative pharmaceuticals in English and Spanish hospitals-The example of isavuconazole.

Funder: Pfizer; Id: http://dx.doi.org/10.13039/100004319BACKGROUND: Kron et al (Mycoses, 64, 2021, 86) found cost savings for the use of the innovative pharmaceutical isavuconazole in the inpatient setting in Germany (Bismarck-based healthcare system). Little is known about the reimbursement of innovative pharmaceuticals in the inpatient setting of Beveridge-based healthcare systems. OBJECTIVES: The aim of this study was to evaluate the market access process and reimbursement of isavuconazole, exemplary for innovative pharmaceuticals, in England and Spain. PATIENTS/METHODS: Market access processes of both countries were described. Focussing on typical patient clusters for isavuconazole treatment, reimbursement data regarding inpatients with (i) allogeneic haematopoietic stem cell transplantation or (ii) acute myeloid leukaemia was considered. Data were publicly available and of high topicality (England 2020/2021, Spain 2018). Discounting and a currency conversion to Euro were applied. RESULTS: This study showed that market access processes of both countries are broadly similar. Further, full reimbursement of isavuconazole as an innovative pharmaceutical may lead to reduction in resource utilisation. Without medication costs, isavuconazole can thus result in cost savings for both patient clusters due to a reduction in length of stay. CONCLUSIONS: Expenses for innovative pharmaceuticals may be balanced or even lead to cost savings due to a reduction in length of stay. The latter contributes to a greater patient benefit. For both healthcare system, the analyses highlighted drugs' cost-effectiveness and assessing its added value into reimbursement decisions is highly relevant

An overview and a roadmap for artificial intelligence in hematology and oncology.

Artificial intelligence (AI) is influencing our society on many levels and has broad implications for the future practice of hematology and oncology. However, for many medical professionals and researchers, it often remains unclear what AI can and cannot do, and what are promising areas for a sensible application of AI in hematology and oncology. Finally, the limits and perils of using AI in oncology are not obvious to many healthcare professionals

Imaging Neuroscience opening editorial

In this editorial we introduce a new non-profit open access journal, Imaging Neuroscience. In April 2023, editors of the journals NeuroImage and NeuroImage:Reports resigned, and a month later launched Imaging Neuroscience. NeuroImage had long been the leading journal in the field of neuroimaging. While the move to fully open access in 2020 represented a positive step toward modern academic practices, the publication fee was set to a level that the editors found unethical and unsustainable. The publisher of NeuroImage, Elsevier, was unwilling to reduce the fee after much discussion. This led us to launch Imaging Neuroscience with MIT Press, intended to replace NeuroImage as our field’s leading journal, but with greater control by the neuroimaging academic community over publication fees and adoption of modern and ethical publishing practices

A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement

Background: Low intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation (tACS or tDCS), applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional magnetic resonance imaging (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. Objective: To develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency, and reproducibility (ContES Checklist). Methods: A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists (EP) through the International Network of the tES-fMRI (INTF) Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC based on a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed using the checklist. Results: Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (1) technological factors, (2) safety and noise tests, and (3) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. Conclusions: Use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies, and increase methodological transparency and reproducibility