C. Chad Quarles1
1MD Anderson Cancer Center, United States
Synopsis
Keywords: Neuro: Brain, Image acquisition: Quantification, Cross-organ: Cancer
At the end of this lecture participants should be able to: 1) describe quantitative neuroimaging methods that are currently used across the spectrum of brain tumor patient care; 2) describe current applications of neuroimaging methods for brain tumor patients, including diagnosis, prognosis, neurosurgical and radiotherapy guidance, and response prediction and assessment, and 3) describe emerging neuroimaging methods and their potential uses in brain tumor patient management.
Objectives
At the end of this lecture participants should be able to:
- Describe quantitative neuroimaging methods that are currently used across the spectrum of brain tumor patient care
- Describe current applications of neuroimaging methods for brain tumor patients, including diagnosis, prognosis, neurosurgical and radiotherapy guidance, and response prediction and assessment
- Describe emerging neuroimaging methods and their potential uses in brain tumor patient management.
Introduction
Imaging with MRI is leveraged at every stage of brain tumor patient management. Most routine protocols include pre- and post-contrast T1-weighted imaging, T2-weighted FLAIR, diffusion weighted imaging, and T2-weighted imaging. These sequences provide sensitivity to contrast agent accumulation in regions of neovascularization, the presence of non-enhancing tumor associated with lower grade lesions and infiltrating cells in high grade tumors, vasogenic edema, and tumor cellularity. However, due to the complex pathophysiology of brain tumors these methods often lack specificity, which can impact critical clinical decisions. Quantitative Neuroimaging Methods
These limitations have long served as the motivation for the development and application of quantitative image-based biomarkers that report on specific biologic attributes of brain tumors. Several quantitative imaging methods, such as diffusion tensor imaging (DTI), functional MRI (fMRI), magnetic resonance spectroscopy (MRS), and perfusion imaging with dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE) and/or arterial spin labeling (ASL) have sufficiently matured, such that vendor provided (and FDA-cleared) acquisition and analysis tools are available and increasingly used in the clinic. These quantitative imaging methods, and their biologic basis in the context of brain tumors, will be reviewed in the lecture. Current Clinical Applications
For most high-grade brain tumors, image-guided surgical resection is first line therapy. The primary aim is to remove the entire contrast enhancing lesion, termed a gross total resection, while minimizing damage to adjacent eloquent areas. Quantitative DTI and task-based fMRI enables preoperative assessment of the integrity and location of white matter fiber tracts (and potential tumor invasion) and tumor-associated cortical defects, respectively. Following surgery, the resection bed, any residual enhancing tissue, and regions of FLAIR abnormality are typically used to guide radiotherapy treatment planning, including target identification, dose distribution and normal tissue contouring. Quantitative imaging methods, like DTI and MRSI metabolic maps, can improve delineation of tumor extent and help spare sensitive brain regions. For patients undergoing systemic therapy (e.g. chemotherapy, targeted therapies) or tumor treating fields, treatment response is primarily evaluated using serial changes in contrast enhancement and/or FLAIR hyperintensity (e.g. new or expanding region of enhancement being indicative of progression or recurrence). With these routine MRI methods, a common clinical challenge for primary and metastatic brain tumors is to differentiate between tumor recurrence and post-treatment radiation effects, as both can result in contrast enhancement. Many sites have adopted quantitative imaging methods, including DSC, MRS, DCE, and ASL, to differentiate between these conditions. Emerging Quantitative Imaging Methods and Clinical Applications
The innovation of new quantitative and biologically specific imaging methods and/or clinical applications of such methods continues to be a highly active research field. For example, there has been a renewed interest in spectroscopic imaging of deuterated metabolites, a method termed deuterium metabolic imaging (DMI). Studies with deuterated glucose, administered orally, have demonstrated the potential of DMI to image glycolytic and oxidative metabolism (e.g. quantitative measures of glucose, lactate, glutamine/glutamate concentration) in preclinical models of and patients with brain tumors (1). Methods like DMI could be informative at all stages of patient care. In the context of radiotherapy, quantitative image-based biomarkers are used to define biology-based target volumes, either for dose intensification or hypofractionated regimens. In a study involving newly diagnosed glioblastoma patients (2), DWI and DSC-MRI were used to define the hypercellular and hyperperfused tumor volumes, respectively, and these regions were treated with 30 fractions up to 75 Gy (as compared to standard 60 Gy). As compared to standard of care, treatment yielded encouraging overall survival and did not reduce cognitive function or quality of life. A promising, and transformative, new approach leverages quantitative neuroimaging methods to generate predictive digital twins for optimizing treatment regimens for high grade glioma patients. In silico studies were recently used to demonstrate that digital twins could be used to optimize radiotherapy dose regimens that aim to maximize tumor control and minimize any associated toxicity (3). With the growing use of multi-omics to characterize the molecular and genetic signatures of brain cancers, recent studies have sought to identify quantitative and biophysically explainable imaging markers that can inform precision medicine. In a study involving high grade glioma patients, 111 spatially matched transcriptomics and multi-parametric MRI samples from non-enhancing regions (potentially reflection zones of infiltration) revealed that quantitative DSC-MRI parameters could identify tumor subpopulations with aggressive molecular signatures driving tumor progression (4). This lecture will also introduce efforts to establish robust resting-state network mapping for neurosurgical resection of brain tumors. While task-based fMRI can provide mapping of speech and motor areas, it is dependent on the patient’s cognitive status, cooperation, and age. In contrast, resting state MRI enables mapping of all functional networks independent of task performance (5). Acknowledgements
No acknowledgement found.References
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