Neuroimaging in Precision Medicine

An overview of the role of neuroimaging biomarkers in the “Medicine of Tomorrow”, based on each patient’s own genotype and phenotype.

About Precision Medicine

Precision medicine, also called personalized medicine, involves coupling established clinical–pathological indexes with state-of-the-art molecular and/or imaging profiling to create diagnostic, prognostic, and therapeutic strategies precisely tailored to each patient's requirements (Mirnezami et al. 2012). Said simply, it aims to provide the right dose of the right drug for the right indication for the right patient at the right time (Frueh. 2005).

While evidence based medicine relies on data from large clinical trials in patient populations, precision medicine relies on the classification of patients into subpopulations that differ in their susceptibility to a particular disease, in the biology and/or prognosis of those diseases, or in response to a specific treatment. It entails the customization of care based on a patient’s genotype and phenotype (i.e. observable characteristics, influenced by gene expression and exposure to other environmental factors) and the genotype and phenotype of a patient’s disease (Boland. 2014).

Precision medicine is often associated with genomics. However, genes involved in most neurological and psychiatric diseases are multiple, and there is no one-to-one mapping between single genes and clinical endpoints. Precision medicine in the brain should, therefore, integrate multiple biomarkers, based on clinical, behavioral, genomic, electrophysiological, and neuroimaging measurements (Williams & Gordon. 2011). A new field of research, neuroimaging genetics, is emerging at the crossroad of multiple disciplines.

Imaging in Precision Medicine

The phenotype includes phenomena that can be identified, enumerated, measured, and described, by technology such as imaging, leading to an "imaging phenotype" of disease manifestation (Boland. 2014). The biomarkers can be at the morphological (e.g., MRI), functional (e.g., fMRI), metabolic (e.g. FDG-PET), micro-environmental (e.g. MR perfusion), or molecular level (e.g. spectroscopy).

The "spot sign score" (Romero et al. 2013) has been used as an imaging phenotype for the prognosis of expansion, mortality, and clinical outcome in patients with intracerebral hemorrhage (ICH) (Boland. 2014). A score, from 0 to 3, is calculated based on the contrast within the area of hemorrhage on CT angiography. Sub phenotypes in intracerebral hemorrhage correlate highly with hematoma expansion and clinical outcome (Romero et al. 2013). The spot sign score is also being used to segment patients into sub phenotypes for clinical trials of ultra-early hemostatic therapy Factor VII (Boland. 2014).

For treatment monitoring and optimization, imaging could be used as a companion diagnostic test (CoDx), measuring biomarkers in order to assess if the patient belongs to a subpopulation that will respond to the drug (Kuo. 2013). For example, in patients with Alzheimer's disease, measurement of brain atrophy or quantitative FDG PET could be used early in the treatment in order to identify drug responders. This new application of existing diagnostic techniques is called theranostics.

Application to Clinical Practice and Clinical Trials

In his State of the Union Address in January 2015, President Obama launched a new "Precision Medicine Initiative", leading to "a new era of medicine  —  one that delivers the right treatment at the right time" (read more...). For patients, getting personalized diagnosis would make it possible to avoid treatment schemes based on trial-and-error. This would make treatments faster and more efficient. At the public health level, the emergence of precision medicine would reduce the social burden of diseases, and spare millions of dollars spent each year on useless medical treatments, while improving each individual's own health.

In clinical trials testing new drugs against neurological and psychiatric disorders, an approach based on precision medicine, and relevant biomarkers, would make it possible to better stratify the patient population (Bonner. 2015), and thereby to avoid failure of the trial at the group level, whereas the treatment is effective in a subset of patients.

References

  • Boland. The role of imaging in the era of personalized / precision medicine. Imaging Biomarkers in Clinical Trials: Current Practice & Future Trends. Harvard Medical School 2014.
  • Bonner. Radiology’s Role in Precision Medicine. Diagnostic Imaging 2015.
  • Budz & Hilton. Precision medicine: Using biomarkers to accelerate clinical development. White Paper, PPD 2013.
  • Frueh. Personalized medicine: What is it? How will it affect health care? 11th Annual FDA Science Forum. Washington 2005.
  • Kuo. Personalized medicine advances toward radiology. Diagnostic Imaging 2013.
  • Mirnezami et al. Preparing for precision medicine. N Engl J Med 2012, 366:489-491.
  • Romero et al. Prospective validation of the computed tomographic angiography spot sign score for intracerebral hemorrhage. Stroke 2013, 44:3097-3102.
  • Williams & Gordon. Personalized medicine and integrative neuroscience: Towards consensus markers for disorders of brain health. In Integrative Neuroscience and Personalized Medicine. Oxford University Press 2011.

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