ABSTRACT
INTRODUCTION: Endoscopic third ventriculostomy (ETV) is becoming an increasingly widespread treatment for hydrocephalus, but research is primarily based on paediatric populations. In 2009, Kulkarni et al created the ETV Success score to predict the outcome of ETV in children. The purpose of this study is to create a prognostic model to predict the success of ETV for adult patients with hydrocephalus. The ability to predict who will benefit from an ETV will allow better primary patient selection both for ETV and shunting. This would reduce additional second procedures due to primary treatment failure. A success score specific for adults could also be used as a communication tool to provide better information and guidance to patients. METHODS AND ANALYSIS: The study will adhere to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis reporting guidelines and conducted as a retrospective chart review of all patients≥18 years of age treated with ETV at the participating centres between 1 January 2010 and 31 December 2018. Data collection is conducted locally in a standardised database. Univariate analysis will be used to identify several strong predictors to be included in a multivariate logistic regression model. The model will be validated using K-fold cross validation. Discrimination will be assessed using area under the receiver operating characteristic curve (AUROC) and calibration with calibration belt plots. ETHICS AND DISSEMINATION: The study is approved by appropriate ethics or patient safety boards in all participating countries. TRIAL REGISTRATION NUMBER: NCT04773938; Pre-results.
Subject(s)
Hydrocephalus , Third Ventricle , Adult , Child , Humans , Hydrocephalus/surgery , Infant , Multicenter Studies as Topic , Prognosis , Retrospective Studies , Third Ventricle/surgery , Treatment Outcome , Ventriculostomy/methodsABSTRACT
Skull-remodeling surgery has been proposed to enhance the dose of tumor treating fields in glioblastoma treatment. This abstract describes the finite element methods used to plan the surgery and evaluate the treatment efficacy.
Subject(s)
Brain Neoplasms , Brain Neoplasms/surgery , Finite Element Analysis , Glioblastoma , Humans , Skull , Treatment OutcomeABSTRACT
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.
Subject(s)
Brain Neoplasms/therapy , Brain/radiation effects , Electric Stimulation Therapy , Electrodes , Brain Neoplasms/diagnostic imaging , Brain Neoplasms/pathology , Electromagnetic Fields , Humans , Magnetic Resonance Imaging , Models, Anatomic , NeuroimagingABSTRACT
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.