Neuroimaging deals with the in vivo applications of various techniques to illustrate and study the structural & functional characteristics of the nervous system. Neuroimaging can be classified into two categories:
• Structural neuroimaging, which involves the imaging of the structure of the nervous system and the diagnosis of intracranial injuries and tumours.
• Functional imaging, which involves the study and diagnosis of metabolic diseases and cognitive research.
The most widely used techniques involved in the process of neuroimaging are:
1. Computed Tomography (CT) or Computed Axial Tomography (CAT), in which X-ray images of the brain from various directions are taken and presented as cross-sections of the brain.
2. Magnetic Resonance Imaging (MRI), which uses magnetic fields and radio waves to obtain high-resolution 2D or 3D images of the brain.
3. Positron Emission Tomography (PET), which measures emissions from radioactively labelled metabolically active chemicals (radiotracer) injected into the bloodstream and processing the data obtained to produce 2D or 3D images of the brain.
Neuroimaging techniques can be widely used to study and assess the structure of the brain and its different regions which can be further applied to identify various disorders associated with each region of the brain. They can also be used to identify inflammations and treat intracranial tumours, arteriovenous malformations and other surgically treatable conditions. Beyond this clinical approach, the applications of brain imaging have drastically changed our views of assessment of the brain structure and function, along with their association with disease and disorders.
Extensive research is undergoing to apply the various neuroimaging techniques to study disorders such as schizophrenia, ADHD and depression. An example of such a study is given below:
To understand the progression of a first-episode schizophrenia (FES) to chronic schizophrenia (CS), MRI findings were obtained and grey matter changes were studied. Studies in ultra-high-resolution samples have depicted abnormalities in frontal, temporal, and limbic regions of the brain may predate the onset of schizophrenia. Sample brain images obtained from people diagnosed with FES and CS were studied to find alterations in grey matter in different regions of the brain. The following observations were noted:
• Both groups showed alterations in the inferior frontal lobe, cingulate gyri, insula and cerebellum.
• Chronic schizophrenia was characterised by reduced grey matter in the medial frontal lobe, dorsolateral prefrontal cortex, postcentral gyrus, uncus, temporal lobe gyri and para-hippocampus.
• First episode schizophrenia was characterised by reduced grey matter activity in the basal ganglia, temporal lobe gyri, amygdala and precentral gyrus.
Aforementioned neuroimaging studies can not only help to identify the regions affected or responsible for a certain disease but can also help to track the disorder throughout its course, starting from the disease onset till maturity and its peak. Abnormalities, even if they are subtle in magnitude, can be linked to various regions of the brain through such images. Identifying the association of a certain region of the brain to a particular disease can not only help us to study the role of that particular region in the onset and progression of the disorder but can also aid in the development of target drugs to limit or repress the disorders. Application of AI and machine learning in neuroimaging techniques can further resolve many more mysteries entangled within the fabric of the human mind. Hence, it can be concluded that neuroimaging techniques can be used as invaluable tools to investigate and treat mental illness and neurological disorders in the future.
• Structural neuroimaging, which involves the imaging of the structure of the nervous system and the diagnosis of intracranial injuries and tumours.
• Functional imaging, which involves the study and diagnosis of metabolic diseases and cognitive research.
The most widely used techniques involved in the process of neuroimaging are:
1. Computed Tomography (CT) or Computed Axial Tomography (CAT), in which X-ray images of the brain from various directions are taken and presented as cross-sections of the brain.
2. Magnetic Resonance Imaging (MRI), which uses magnetic fields and radio waves to obtain high-resolution 2D or 3D images of the brain.
3. Positron Emission Tomography (PET), which measures emissions from radioactively labelled metabolically active chemicals (radiotracer) injected into the bloodstream and processing the data obtained to produce 2D or 3D images of the brain.
Neuroimaging techniques can be widely used to study and assess the structure of the brain and its different regions which can be further applied to identify various disorders associated with each region of the brain. They can also be used to identify inflammations and treat intracranial tumours, arteriovenous malformations and other surgically treatable conditions. Beyond this clinical approach, the applications of brain imaging have drastically changed our views of assessment of the brain structure and function, along with their association with disease and disorders.
Extensive research is undergoing to apply the various neuroimaging techniques to study disorders such as schizophrenia, ADHD and depression. An example of such a study is given below:
To understand the progression of a first-episode schizophrenia (FES) to chronic schizophrenia (CS), MRI findings were obtained and grey matter changes were studied. Studies in ultra-high-resolution samples have depicted abnormalities in frontal, temporal, and limbic regions of the brain may predate the onset of schizophrenia. Sample brain images obtained from people diagnosed with FES and CS were studied to find alterations in grey matter in different regions of the brain. The following observations were noted:
• Both groups showed alterations in the inferior frontal lobe, cingulate gyri, insula and cerebellum.
• Chronic schizophrenia was characterised by reduced grey matter in the medial frontal lobe, dorsolateral prefrontal cortex, postcentral gyrus, uncus, temporal lobe gyri and para-hippocampus.
• First episode schizophrenia was characterised by reduced grey matter activity in the basal ganglia, temporal lobe gyri, amygdala and precentral gyrus.
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Figure: Study showing grey matter abnormalities in different stages of schizophrenia. |
Aforementioned neuroimaging studies can not only help to identify the regions affected or responsible for a certain disease but can also help to track the disorder throughout its course, starting from the disease onset till maturity and its peak. Abnormalities, even if they are subtle in magnitude, can be linked to various regions of the brain through such images. Identifying the association of a certain region of the brain to a particular disease can not only help us to study the role of that particular region in the onset and progression of the disorder but can also aid in the development of target drugs to limit or repress the disorders. Application of AI and machine learning in neuroimaging techniques can further resolve many more mysteries entangled within the fabric of the human mind. Hence, it can be concluded that neuroimaging techniques can be used as invaluable tools to investigate and treat mental illness and neurological disorders in the future.
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Figure: Brain MRI with annotations of major structures. |
Saswata Mitra
Department-Biotechnology
2ND Year
2ND Year
I have a few questions on your article
ReplyDelete1. As the study schizophrenia and other psychotic disorders are subjective and symptom based? What is the chance neuroimaging assessmemt inaccuracies to correctly diagnose a disease.
2. How to deal with patients who are dependent on electronic devices/metals, such as pacemakers to undergo MRI, since the magnetic field influx might interfere with the results or even cause burns.
Regarding the first question, errors in the analysis of a certain disease can take place but adopting computer assisted methods for scan based diagnosis drastically reduces the probability of an inaccurate diagnosis. Application of AI and advanced machine learning can be extremely helpful for screening purposes.
DeleteRegarding the second one, we CT scan or PET scan can be applied as an alternative to MRI scans since they do not involve the use of a radio field in the process. While PET scans involve the application of radiotracers, which are can cause hazards in some subjects; CT scans involve the use of X-ray images taken from various directions to produce a model of the subject brain and hence is less susceptible to interfere with pacemakers.
Thank you :)
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