10.3 Diffuse optical tomography and functional imaging
4 min read•august 9, 2024
Diffuse optical tomography uses near-infrared light to peek inside our bodies. It's like having X-ray vision, but safer and better for seeing blood flow and oxygen levels. This tech can map brain activity, spot breast tumors, and keep tabs on patients in critical care.
The magic happens when light travels through tissue, getting absorbed and scattered along the way. By measuring how the light changes, we can create 3D images of what's going on inside. It's non-invasive and gives real-time info on tissue health and function.
Principles of Diffuse Optical Tomography
Near-Infrared Light Propagation in Tissue
Top images from around the web for Near-Infrared Light Propagation in Tissue
Realistic Numerical and Analytical Modeling of Light Scattering in Brain Tissue for Optogenetic ... View original
Is this image relevant?
Frontiers | Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of ... View original
Is this image relevant?
Frontiers | Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of ... View original
Is this image relevant?
Realistic Numerical and Analytical Modeling of Light Scattering in Brain Tissue for Optogenetic ... View original
Is this image relevant?
Frontiers | Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of ... View original
Is this image relevant?
1 of 3
Top images from around the web for Near-Infrared Light Propagation in Tissue
Realistic Numerical and Analytical Modeling of Light Scattering in Brain Tissue for Optogenetic ... View original
Is this image relevant?
Frontiers | Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of ... View original
Is this image relevant?
Frontiers | Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of ... View original
Is this image relevant?
Realistic Numerical and Analytical Modeling of Light Scattering in Brain Tissue for Optogenetic ... View original
Is this image relevant?
Frontiers | Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of ... View original
Is this image relevant?
1 of 3
utilizes light in the 650-900 nm wavelength range
Light in this range penetrates deeper into biological tissues compared to visible light
Penetration depth ranges from several millimeters to a few centimeters depending on tissue type
Near-infrared light interacts with tissue through and processes
Absorption primarily occurs due to hemoglobin, water, and lipids in tissue
Scattering results from refractive index mismatches at cellular and subcellular structures
Tissue Optical Properties and Light Propagation Models
Tissue scattering dominates over absorption in the near-infrared region
Scattering coefficient (μs) quantifies the number of scattering events per unit length
Typical values for μs in soft tissues range from 10 to 100 cm^-1
Absorption coefficient (μa) measures the probability of photon absorption per unit path length
μa values for most soft tissues in the near-infrared range from 0.1 to 1 cm^-1
Diffusion approximation simplifies light propagation modeling in highly scattering media
Assumes light transport can be described by a diffusion equation
Valid when scattering dominates over absorption (μs >> μa)
Provides a computationally efficient method for modeling photon transport in tissue
Measurement Techniques and Instrumentation
Continuous wave (CW) systems use constant intensity light sources
Measure changes in light intensity after passing through tissue
Time-domain systems employ ultra-short light pulses (picoseconds)
Measure temporal distribution of photons (time-of-flight)
Frequency-domain systems utilize intensity-modulated light sources
Measure amplitude attenuation and phase shift of detected light
Detectors include photomultiplier tubes, avalanche photodiodes, and CCD cameras
Multiple source-detector pairs arranged on the tissue surface enable 3D imaging
Reconstruction and Imaging
Image Reconstruction Algorithms and Techniques
Linear reconstruction methods assume small perturbations in optical properties
Utilize sensitivity matrices to relate changes in measurements to optical property changes
Non-linear reconstruction methods iteratively solve the forward and inverse problems
Forward problem calculates light propagation for given optical properties
Inverse problem estimates optical properties from measured data
address ill-posedness of the inverse problem
Tikhonov regularization adds a penalty term to the objective function
Total variation regularization promotes piecewise constant solutions
Iterative algorithms (conjugate gradient, Gauss-Newton) optimize the reconstruction process
Multispectral reconstruction incorporates data from multiple wavelengths simultaneously
Oxygen Saturation Mapping and Functional Imaging
mapping measures spatial distribution of tissue oxygenation
Utilizes spectral differences between oxy- and deoxyhemoglobin
Typically uses measurements at two or more wavelengths
Calculates relative concentrations of oxy- and deoxyhemoglobin
Oxygen saturation (SO2) computed as ratio of oxyhemoglobin to total hemoglobin
Functional imaging tracks changes in hemodynamics and metabolism over time
Measures variations in oxy- and deoxyhemoglobin concentrations
Can detect local changes in blood flow and oxygen consumption
Temporal ranges from seconds to minutes depending on the system
Spatial resolution typically 5-10 mm for deep tissue imaging
Clinical Applications
Functional Brain Imaging and Neurological Disorders
Functional measures cortical activation patterns
Detects local changes in cerebral blood flow and oxygenation
Applications include studying cognitive processes and language development
Can be used to assess brain function in infants and children
Advantages over fMRI include portability and tolerance of subject movement
Neurological disorder assessment includes stroke and traumatic brain injury
Monitors cerebral oxygenation and blood flow in critical care settings
Potential for early detection of ischemia and guiding therapeutic interventions
Limitations include lower spatial resolution compared to fMRI
restricted to outer cortical regions
Breast Cancer Detection and Characterization
Breast cancer detection utilizes differences in optical properties between healthy and tumor tissue
Tumors typically exhibit increased blood volume and metabolism
Higher concentrations of hemoglobin and altered scattering properties
Can detect tumors as small as 5-10 mm in diameter
Combines with other imaging modalities (X-ray mammography, ultrasound) for improved diagnosis
Potential for monitoring response to neoadjuvant chemotherapy
Tracks changes in tumor vascularity and metabolism during treatment
Non-invasive and does not use ionizing radiation
Challenges include high false-positive rates and limited sensitivity for deep tumors
Ongoing research focuses on improving specificity and depth sensitivity
Hemodynamic Monitoring in Critical Care
Hemodynamic monitoring assesses tissue perfusion and oxygenation
Applications in intensive care units and during surgery
Measures regional tissue oxygenation in organs (brain, muscle, abdominal viscera)
Can detect early signs of shock and guide fluid resuscitation
Monitors cerebral oxygenation during cardiac surgery and carotid endarterectomy
Assesses peripheral perfusion in patients with sepsis or trauma
Advantages include continuous, non-invasive monitoring at the bedside
Limitations include motion artifacts and variability in probe placement
Research ongoing to develop wearable devices for long-term monitoring
Integration with other physiological monitors for comprehensive patient assessment