In the human brain there two major types of cells: on one hand there are neurons, which are the electrically active cells which control our thinking, moving, breathing, heart beating, body temperature etcetera, and on the other hand there are glial cells which provide support and protection for the neurons in the brain. These glial cells may change their nature during our life, and may turn into tumor cells, which than rapidly increase in number by uncontrolled cell division. The tumors of glial cells are called gliomas. Since there are various glial-cells sub-types, there are also various glioma tumor types (e.g. ependymomas, astrocytomas, oligodendrogliomas). Further, there are less aggressive gliomas, the so-called low grade gliomas, and rapid growing, aggressive gliomas, the so-called high-grade gliomas. The World Health Organization (WHO) made a classification system for glioma distinguishing based on their aggressiveness: low grade glioma are those of WHO grade I and II; the very aggressive, malignant, glioma are of WHO grade III and IV. This SNF study focuses on malignant [WHO grade-III-IV] brain tumors for which have an overall incidence of 5 per 100000 people per year, and are the most common brain tumors.
For the diagnostics of brain tumors, magnetic resonance imaging (MRI) is the neuroimaging method of first choice since it enables not only the measurement of the tumor location and size, but also allows insights regarding tumor aggressiveness by the application of contrast agents, tumor sub-typing using magnetic resonance spectroscopy (MRS), the blood-flow through the tumor tissue, and quantification of the severity of brain swelling (edema) by measuring the diffusion of the water molecule in the tumor. Nevertheless, the gold standard for initial diagnosis of brain tumors is the histological examination of biopsies. In a image guided surgical intervention the neurosurgeon removes a tumor tissue to be examined by a pathologist. If the location of the tumor does not allow to take a biopsy, for instance in tumors of the brain stem, diagnostics by neuroimaging methods is of utmost importance.
Criteria for Tumor-Progression
During the course of the disease, glioma change their size and aggressiveness. This process is called tumor progression. Neuroimaging criteria have been defined in the beginning of the nineties of last century that define imaging criteria for progression. These so-called Macdonald criteria also define whether the tumor is said to be stable, or shows progression, i.e. increases size and changes its level of aggressiveness. Since the first definition of these Macdonald criteria the treatment of glioma has changed a great deal. The tumors are nowadays treated with a combination of radiation therapy and chemo-therapy with temozolomide. Very recently, new anti-angiogenic drugs came on the market that slows down or prevent the growth of new blood-vessels that feed the brain-tumor, and by this, to stop further tumor growth. Radiation therapy changes the characteristics of the blood-brain-barrier and the irradiated tissue will show signal enhancement in T1-weighted MR-images. Signal enhancement however is in untreated tumors associated with high grade gliomas. This means that an irradiated low-grade tumor may appear as an high-grade tumor after therapy. This effect is recognized, and is called pseudo-progression of the tumor. The effect of anti-angiogenic drugs is opposite: the T1-signal enhancement” disappears due to restoration of the blood-brain-barrier, but the tumor is still there. This effect is called pseudo-response. These effects were recognized by the Response Assessment in Neuro-Oncology (RANO) Working Group that adapted the Macdonald criteria for glioma progression classification.
At the time of the first formulation of the Macdonald criteria at the beginning of the nineties of the last century, a standard MR-examination consisted predominantly of T1- and T2-weighted MR-imaging. In the meantime MR neuro-imaging techniques have developed tremendously. As mentioned above, diffusion weighted imaging (DWI-MRI), perfusion weighted imaging (PWI-MRI) have been established today, and are frequently applied for initial tumor diagnosis and tumor-progression evaluation. Also MRS has established itself as a valuable tool for initial tumor diagnostics and progression evaluation. Despite the fact that these techniques have been established, their use in tumor-progression evaluation in the RANO criteria is still very limited.
During the last 30 years the analysis of digital medical MR-images has considerably improved. There are novel computer aided methods available now for automatic tumor detection within the images, and automatic tissue classification. This study will focus on the use of so-called “texture parameters” in combination with advanced statistical classification methods.
Aims of this Study
The primary aim of our proposal is to improve the reliability of tumor progression evaluation. To do so, this study foresees the acquisition of T1-, T2-weighted, perfusion-, diffusion-weighted MR-images, as well as localized MR-spectra of de novo glioma patients before, during and after treatment by neurosurgery, radio-chemotherapy and/or anti-angiogenic therapy. With the aid of a tumor progression analysis tool that will be further developed during the study, the clinician can analyze simultaneously all MRI/MRS data and can extract relevant tumor progression information from the tool. At least 80 so-called image texture analysis will be derived from the MRI an MRS datasets for 90 high grade glioma patients as a function of time. MR-measurements will be made at first diagnosis, after neuro-surgery, and during the standard regular 3 month interval follow-up examinations for a period of 2 years. We hypothesize that by retrospective analysis of the collected data, we will be able to distinguish true tumor-progression from pseudo-progression, and true tumor-response to therapy, from pseudo-response, enabling targeted patient treatment in the future.