Feasibility of Individualized, Model-guided Optimization of Proton Beam Treatment Planning in Patients With Low Grade Glioma (INDIGO)

University Hospital Heidelberg

Status and phase: Enrolling; Phase 2

Conditions: Low Grade Glioma

Treatments: Other: model-guided optimization of treatment plan; Other: standard treatment plan, no optimization

Study type: Interventional

Funder types: Other

Identifiers

NCT05964569

RadOnk-Indigo

Details and patient eligibility

About

Low-grade glioma (LGG) represent typically slowly growing primary brain tumors with world health organization (WHO) grade I or II who affect young adults around their fourth decade. Radiological feature on MRI is a predominantly T2 hyperintense signal, LGG show typically no contrast uptake. Radiotherapy plays an important role in the treatment of LGG. However, not least because of the good prognosis with long term survivorship the timing of radiotherapy has been discussed controversially. In order to avoid long term sequelae such as neurocognitive impairment, malignant transformation or secondary neoplasms initiation was often postponed as long as possible

Full description

Since patients with low grade glioma are expected to become long-term survivors, the prevention of long-term sequelae is particularly important. In addition to disease progression, also treatment related side effects such as decline of neurocognitive function, endocrine impairment or sensorineural deficits can have a negative impact on patient's quality of life.

Owing to the biophysical properties of protons with an inverse depth dose profile compared to photons and a steep dose fall of to the normal tissue, there is a strong rationale for the use of PRT in the treatment of patients with low-grade glioma. Although data from large randomized trials are still missing there is increasing evidence from smaller prospective trials and retrospective analyses that the expected advantages indeed transform into clinical advantages.

However, in about 20 % of all patients, late contrast-enhancing brain lesions (CEBL) appear on follow-up MR images 6 - 24 months after treatment. At HIT in Heidelberg and at OncoRay in Dresden, CEBLs have been observed to occur at very distinct locations in the brain and relative to the treatment field. Retrospective analysis has elucidated potential key factors that lead to CEBL occurrence. However, avoidance of CEBLs is hardly feasible using conventional treatment planning strategies. Model-aided risk avoidance denotes the use of model-based CEBL risk calculations as an auxiliary tool for clinical treatment planning: Model-based risk calculations and risk reduction via software-based optimization help the clinician to minimize risk of CEBL occurrence during treatment planning.

Enrollment: 120 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Age > 18 years
• histologically proven low-grade glioma
• indication for definitive or adjuvant radiotherapy
• ability to understand character and personal consequences of the clinical trial
• written informed consent

Exclusion criteria

• previous cerebral irradiation
• contraindication for contrast-enhanced MRI
• neurofibromatosis
• participation in another clinical trial with competing objectives

Trial design

Primary purpose: Treatment

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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120 participants in 2 patient groups

Standard treatment plan

Active Comparator group

Description:

Model-based NTCP is calculated after plan approval, however, no further adjustments are to be made to the approved treatment plan

Treatment:

Other: standard treatment plan, no optimization

Optimized treatment plan

Experimental group

Description:

Allocated to Control Calculation of normal tissue complication probability (NTCP) Model-guided replanning. Replanning is performed with Raysearch Raystation. Optimizations objectives are: 1. the optimization objectives that control the maximum dose in the target volume employ a variable, LETd-dependent model for RBE that allows us to include the RBE-variations predicted by the NTCP model 2. the periventricular volume, defined as the volume closer than 4 mm to the ventricular wall, is included into the optimization with a constraint on its Equivalent Uniform Dose (EUD) and with the variable RBE model described above. Thereby, the combined effect of the RBE variation and increased sensitivity of the periventricular volume, as predicted by the NTCP model, is included. The effectiveness of the re-planning is verified by a second NTCP computation.

Treatment:

Other: model-guided optimization of treatment plan