Viewing Study NCT06492486



Ignite Creation Date: 2024-07-17 @ 11:21 AM
Last Modification Date: 2024-10-26 @ 3:34 PM
Study NCT ID: NCT06492486
Status: NOT_YET_RECRUITING
Last Update Posted: 2024-07-09
First Post: 2024-07-02

Brief Title: Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow
Sponsor: Tata Memorial Centre
Organization: Tata Memorial Centre

Study Overview

Official Title: Glioma Adaptive Radiotherapy With Development of an Artificial Intelligence Workflow
Status: NOT_YET_RECRUITING
Status Verified Date: 2024-07
Last Known Status: None
Delayed Posting: No
If Stopped, Why?: Not Stopped
Has Expanded Access: False
If Expanded Access, NCT#: N/A
Has Expanded Access, NCT# Status: N/A
Acronym: GLADIATOR
Brief Summary: Gliomas are common primary brain tumors in adults Gliomas can be classified into different types based on tumor grade histopathological features and molecular characteristics The common types of diffuse gliomas include glioblastoma astrocytoma and oligodendroglioma The standard treatment for diffuse gliomas includes surgery followed by radiation and chemotherapy As per standard institutional practice a uniform dose of radiation is delivered to the disease area and MRI is done before and after the treatment In this study MRI and PET scan will be done before starting the treatment and standard dose of radiation will be delivered The interval imaging will be done twice during the course of treatment with MRI and PET followed by dose modifications The CT MRI and PET will be combined Based on PET imaging specific dose will be altered and delivered to specific areas Dose modification will be done with the help of artificial intelligence Participants assessment will be done at regular intervals

Modifications in radiation plans are done based on the changes in disease seen in scans is likely to improve the accuracy of RT treatments Dose modifications based on imaging to resistant areas will help achieve better tumor control reduce treatment-related toxicities precise delivery of the RT and adjusting doses to the organs at risk OAR and changes in disease leading to better treatment compliance Creating an artificial intelligence framework in radiation oncology promises to improve quality of workflow treatment planning and RT delivery

The aim of the study is to develop an artificial intelligence workflow for treatment of glioma with adaptive radiotherapy This study will be conducted in Tata Memorial Centre on a population of 60 patients for a duration of 2 years The total study duration is 4 years
Detailed Description: Glioblastoma multiforme GBM represents grade 4 diffuse gliomas accounting for the most common primary malignant central nervous system CNS tumors in adults GBM is treated with radiotherapy RT and concurrent chemotherapy following maximal safe resection with a median survival of approximately 15-18 months GBM harbors significant intratumoral heterogeneity with areas of multiclonal and hypoxic areas rendering higher chances of disease relapse following standard RT

Similarly distinct compartments can be well appreciated on magnetic resonance imaging MRI enhancing tumor core TC with central necrotic areas and the peritumoral region PTR which consists of microscopic tumor infiltration and vasogenic edema Similar to regions of radioresistant areas within the TC the microscopic disease in the PTR plays a vital role in disease relapse Other grade 2 and 3 diffuse gliomas include isocitrate dehydrogenase IDH mutant astrocytoma and oligodendroglioma In the recent World Health Organization WHO classification of CNS tumors molecular information is combined with histopathological information for integrated classification IDH-wildtype tumors are further molecularly characterized and considered as GBM since the prognosis is shown to be dismal Oligodendrogliomas are confirmed based on the presence of deletion of 1p19q chromosomal arms Grade 23 diffuse gliomas are typically seen as tumors with T2-weighted hyperintense tumors The treatment is similar to GBM with maximal safe resection followed by radiation and concurrent and adjuvant chemotherapy

Radiotherapy for Diffuse Gliomas Radiotherapy RT forms an integral role in the multimodality management of diffuse gliomas Radiation is indicated in low-grade gliomas with high-risk features or high-grade gliomas following maximal safe resection The radiation RT in diffuse gliomas in GBM is delivered using conformal techniques to the residual disease and cavity called the gross tumor volume GTV The surrounding area is included in the clinical target volume CTV to treat areas of microscopic disease For GBM an expansion of 15 -2 cm is done from the GTV which is identified as an enhancing area on T1c sequences to include areas of PTR T2w hyperintensity and edited from anatomical barriers like meninges and dural reflections For IDH-mutant gliomas the residual tumor and cavity identified as T2w hyperintensity region are included as GTV and further expansion of 5-10 mm is done to be included as CTV The standard practice involves delivering a uniform dose of radiation to the planning target volume PTV which encompasses an isotropic margin expansion surrounding the CTV to account for set-up uncertainties In GBM and IDHmutant high-grade astrocytoma the total dose of 594-60 Gy is delivered over 6-7 weeks with 18-2 Gy per fraction A relatively lower dose of radiation in the range of 540-594 Gy is delivered over 6-7 weeks using 18-2 Gy per fraction for oligodendrogliomas As per the current paradigm radiation is planned on computed tomography CT for dose computation and MRI for visualization of target volumes and organs at risk OAR done once before treatment based on which fractionated radiation is delivered over 6- 7 weeks Recent evidence with MRI undertaken during the course of treatment has demonstrated the changes in dynamics of the residual disease surgical cavity and also the OARs in a proportion of patients suggesting that treatment is delivered based on imaging at a single time-point can lead to inaccuracies Therefore adaptive radiotherapy ART to modify radiation plans based on the spatial changes of the target volume and OAR is likely to improve the accuracy of RT treatments Also serial imaging during treatment can be used to identify areas of tumor or PTR showing refractory disease or vasogenic edema with provisions for biological modifications of RT doses The use of conformal radiation techniques like intensity-modulated radiotherapy IMRT volumetric modulated arc therapy VMAT can enable delivery of differential radiation doses precisely to different areas of the target volume known as dose painting Positron Emission Tomography PET Functional imaging with positron emission tomography PET has attained wide popularity in oncology in disease staging identifying hypoxic areas and guiding radiation planning For gliomas amino acid PET like O-2-18F fluoroethyl -L-tyrosine FET or Fluorodopa F-DOPA has been proven effective with areas of a higher tumor to white matter ratio suggestive areas of active disease 19 The use of PET scans during treatment can help identify areas refractory to RT reflected by higher uptake of the radioisotope Higher doses to such regions provide a window for biological adaption and can potentially improve control rates Similarly quantitative analysis of imaging more popularly known as radiomics can help differentiate areas of microscopic tumor from vasogenic edema in the PTR which otherwise appears similar to conventional imaging Artificial Intelligence The role of artificial intelligence in oncology is increasingly recognized ranging from optimization of healthcare resource utilization and decision-making to quantitative image analysis for prognostication and the potential ability to serve as a noninvasive biomarker The practice of contemporary radiation oncology heavily relies on the interaction of humans and machines in almost every treatment planning process including contouring of target volumes OAR treatment-planning processes and during treatment delivery Creating an artificial intelligence framework in radiation oncology promises to improve workflow efficiency and accuracy and enable treatment planning and delivery rapidly and efficiently The use of adaptive radiotherapy will be further facilitated using machine learning algorithms with appropriate identification of patients to be benefitted from volumetric or biological adaptation autosegmentation of targetOAR automated treatment planning and biological modification based on spatial and temporal changes of quantitative imaging parameters Standard institutional practice The standard institutional practice includes a dose of 594 Gy in 33 fractions over 65 weeks for patients with glioblastoma and 558 Gy in 31 fractions over 6 weeks for patients with oligodendroglioma Concurrent temozolomide is used for all patients undergoing radiation at the dose of 75 mgm 2 of body surface area during the course of radiation with weekly monitoring on blood counts All radiation treatments are planned based on single time CT and MRI scan without any scheduled interval scans during radiation and no adaptation is done Adjuvant chemotherapy with temozolomide is started after 4 weeks of radiation completion at dose of 150 mgm 2 for five days and repeated on monthly basis and dose escalated to 200 mgm 2 if tolerating well and normal blood counts As standard practice 6 and 12 cycles of temozolomide are scheduled for GBM and IDH-mutant glioma astrocytoma and oligodendroglioma respectively After treatment completion clinical follow-up is scheduled every 3-6 months in the first 2 years and thereafter every 6-12 months for all the patients Surveillance imaging is scheduled every 6-12 months in the first 5 years and thereafter on annual basis or interval imaging undertaken as prompted clinically

Study Oversight

Has Oversight DMC: None
Is a FDA Regulated Drug?: False
Is a FDA Regulated Device?: False
Is an Unapproved Device?: None
Is a PPSD?: None
Is a US Export?: None
Is an FDA AA801 Violation?: None