Assessment of therapeutic response and treatment planning for brain tumors using metabolic and physiological MRI

Abstract

MRI is routinely used for diagnosis, treatment planning and assessment of response to therapy for patients with glioma. Gliomas are spatially heterogeneous and infiltrative lesions that are quite variable in terms of their response to therapy. Patients classified as having low-grade histology have a median overall survival of 7 years or more, but need to be monitored carefully to make sure that their tumor does not upgrade to a more malignant phenotype. Patients with the most aggressive grade IV histology have a median overall survival of 12–15 months and often undergo multiple surgeries and adjuvant therapies in an attempt to control their disease. Despite improvements in the spatial resolution and sensitivity of anatomic images, there remain considerable ambiguities in the interpretation of changes in the size of the gadolinium-enhancing lesion on T1-weighted images as a measure of treatment response, and in differentiating between treatment effects and infiltrating tumor within the larger T2 lesion. The planning of focal therapies, such as surgery, radiation and targeted drug delivery, as well as a more reliable assessment of the response to therapy, would benefit considerably from the integration of metabolic and physiological imaging techniques into routine clinical MR examinations. Advanced methods that have been shown to provide valuable data for patients with glioma are diffusion, perfusion and spectroscopic imaging. Multiparametric examinations that include the acquisition of such data are able to assess tumor cellularity, hypoxia, disruption of normal tissue architecture, changes in vascular density and vessel permeability, in addition to the standard measures of changes in the volume of enhancing and nonenhancing anatomic lesions. This is particularly critical for the interpretation of the results of Phase I and Phase II clinical trials of novel therapies, which are increasingly including agents that are designed to have anti-angiogenic and anti-proliferative properties as opposed to having a direct effect on tumor cell viability.

Prognostic Value of Dynamic Susceptibility Contrast-Enhanced and Diffusion-Weighted MR Imaging in Patients with Glioblastomas

“…34,35,38 Law et al 30 suggested that rCBV measurements in low-grade gliomas correlated more accurately with time to progression than the initial histopathologic grading of the tumor. Although Oh et al 18 suggested that rCBV had no predictive value with respect to the prognosis in GBM, they evaluated GBM tumors after surgical resection; thus, it is unclear whether the extent of surgery played a role in determining the prognostic value in their study.…”

Advances in Diagnostic and Treatment Modalities for Intracranial Tumors

“…, 60 Both MRI‐ and CT‐based dynamic contrast‐enhanced techniques have been described in canine tumors to assess blood volume, perfusion, and permeability (Fig 2). 66, 67 As with other imaging techniques, assessment of vascular parameters in veterinary patients has limitations for diagnosis66, 67; however, utility in monitoring vascular response to therapies including radiation has been reported 68.…”

“…Magnetic resonance metabolic imaging of brain tumors by using proton magnetic resonance spectroscopy ( 1 H MRS) allows determination of the chemical composition of tumor tissue, and it is a commonly used complementary technique in human neurooncology 60. MRS techniques have been described in normal canine brain,72, 74 and experimentally in canine models of nonneoplastic brain disease 75, 76, 77…”

“…Similar to human medicine, it is likely that combined use of these techniques together with standard imaging will provide the optimal information for therapeutic planning, tumor stratification, and assessment of therapeutic response, particularly when used in a linear manner 60, 82, 83…”

Watching tumours gasp and die with MRI: the promise of hyperpolarised13C MR spectroscopic imaging

“…We have also known since the 1970s that it is possible to detect MR signals from tissue metabolites [15]. The problem is that these are present at ,10 000 times lower concentration than tissue water protons and therefore it is not possible to image them at clinical magnetic field strengths, except at relatively low spatial (1 cm 3 ) and temporal (5-10 min) resolution [16]. Moreover, single spectra or spectroscopic images of tissue metabolites lack dynamic information about metabolic fluxes.…”