Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography

The specificity of molecular and functional photoacoustic (PA) images depends on the accuracy of the photoacoustic absorption spectroscopy. The PA signal is proportional to the product of the optical absorption coefficient and local light fluence; quantitative PA measurements of the optical absorption coefficient therefore require an accurate estimation of optical fluence. Light-modeling aided by diffuse optical tomography (DOT) can be used to map the required fluence and to reduce errors in traditional PA spectroscopic analysis. As a proof-of-concept, we designed a tissue-mimicking phantom to demonstrate how fluence-related artifacts in PA images can lead to misrepresentations of tissue properties. To correct for these inaccuracies, the internal fluence in the tissue phantom was estimated by using DOT to reconstruct spatial distributions of the absorption and reduced scattering coefficients of multiple targets within the phantom. The derived fluence map, which only consisted of low spatial frequency components, was used to correct PA images of the phantom. Once calibrated to a known absorber, this method reduced errors in estimated absorption coefficients from 33% to 6%. These results experimentally demonstrate that combining DOT with PA imaging can significantly reduce fluence-related errors in PA images, while producing quantitatively accurate, high-resolution images of the optical absorption coefficient

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer’s, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging

Quantitative high-resolution photoacoustic spectroscopy by combining photoacoustic imaging with diffuse optical tomography

The specificity of both molecular and functional photoacoustic (PA) images depends on the accuracy of the photoacoustic absorption spectroscopy. Because the PA signal is a product of both the optical absorption coefficient and the local light fluence, quantitative PA measurements of absorption require an accurate estimate of the optical fluence. Lightmodeling aided by diffuse optical tomography (DOT) methods can be used to provide the required fluence map and to reduce errors in traditional PA spectroscopic analysis. As a proof-ofconcept, we designed a phantom to demonstrate artifacts commonly found in photoacoustic tomography (PAT) and how fluence-related artifacts in PAT images can lead to misrepresentations of tissue properties. Specifically, we show that without accounting for fluence-related inhomogeneities in our phantom, errors in estimates of the absorption coefficient from a PAT image were as much as 33%. To correct for this problem, DOT was used to reconstruct spatial distributions of the absorption coefficients of the phantom, and along with the surface fluence distribution from the PAT system, we calculated the fluence everywhere in the phantom. This fluence map was used to correct PAT images of the phantom, reducing the error in the estimated absorption coefficient from the PAT image to less than 5%. Thus, we demonstrate experimentally that combining DOT with PAT can significantly reduce fluence-related errors in PAT images, as well as produce quantitatively accurate, highresolution images of the optical absorption coefficient

Imaging technology in mice enhances human brain research

Photoacoustic tomography offering a large field of view and high spatial resolution enables, for the first time, noninvasive imaging of resting-state functional connectivity in the murine brain

Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography

The specificity of molecular and functional photoacoustic (PA) images depends on the accuracy of the photoacoustic absorption spectroscopy. The PA signal is proportional to the product of the optical absorption coefficient and local light fluence; quantitative PA measurements of the optical absorption coefficient therefore require an accurate estimation of optical fluence. Light-modeling aided by diffuse optical tomography (DOT) can be used to map the required fluence and to reduce errors in traditional PA spectroscopic analysis. As a proof-of-concept, we designed a tissue-mimicking phantom to demonstrate how fluence-related artifacts in PA images can lead to misrepresentations of tissue properties. To correct for these inaccuracies, the internal fluence in the tissue phantom was estimated by using DOT to reconstruct spatial distributions of the absorption and reduced scattering coefficients of multiple targets within the phantom. The derived fluence map, which only consisted of low spatial frequency components, was used to correct PA images of the phantom. Once calibrated to a known absorber, this method reduced errors in estimated absorption coefficients from 33% to 6%. These results experimentally demonstrate that combining DOT with PA imaging can significantly reduce fluence-related errors in PA images, while producing quantitatively accurate, high-resolution images of the optical absorption coefficient

Resting-state functional connectivity imaging of the mouse brain using photoacoustic tomography

Resting-state functional connectivity (RSFC) imaging is an emerging neuroimaging approach that aims to identify spontaneous cerebral hemodynamic fluctuations and their associated functional connections. Clinical studies have demonstrated that RSFC is altered in brain disorders such as stroke, Alzheimer’s, autism, and epilepsy. However, conventional neuroimaging modalities cannot easily be applied to mice, the most widely used model species for human brain disease studies. For instance, functional magnetic resonance imaging (fMRI) of mice requires a very high magnetic field to obtain a sufficient signal-to-noise ratio and spatial resolution. Functional connectivity mapping with optical intrinsic signal imaging (fcOIS) is an alternative method. Due to the diffusion of light in tissue, the spatial resolution of fcOIS is limited, and experiments have been performed using an exposed skull preparation. In this study, we show for the first time, the use of photoacoustic computed tomography (PACT) to noninvasively image resting-state functional connectivity in the mouse brain, with a large field of view and a high spatial resolution. Bilateral correlations were observed in eight regions, as well as several subregions. These findings agreed well with the Paxinos mouse brain atlas. This study showed that PACT is a promising, non-invasive modality for small-animal functional brain imaging

Quantitative high-resolution photoacoustic spectroscopy by combining photoacoustic imaging with diffuse optical tomography

The specificity of both molecular and functional photoacoustic (PA) images depends on the accuracy of the photoacoustic absorption spectroscopy. Because the PA signal is a product of both the optical absorption coefficient and the local light fluence, quantitative PA measurements of absorption require an accurate estimate of the optical fluence. Lightmodeling aided by diffuse optical tomography (DOT) methods can be used to provide the required fluence map and to reduce errors in traditional PA spectroscopic analysis. As a proof-ofconcept, we designed a phantom to demonstrate artifacts commonly found in photoacoustic tomography (PAT) and how fluence-related artifacts in PAT images can lead to misrepresentations of tissue properties. Specifically, we show that without accounting for fluence-related inhomogeneities in our phantom, errors in estimates of the absorption coefficient from a PAT image were as much as 33%. To correct for this problem, DOT was used to reconstruct spatial distributions of the absorption coefficients of the phantom, and along with the surface fluence distribution from the PAT system, we calculated the fluence everywhere in the phantom. This fluence map was used to correct PAT images of the phantom, reducing the error in the estimated absorption coefficient from the PAT image to less than 5%. Thus, we demonstrate experimentally that combining DOT with PAT can significantly reduce fluence-related errors in PAT images, as well as produce quantitatively accurate, highresolution images of the optical absorption coefficient

Imaging technology in mice enhances human brain research

Photoacoustic tomography offering a large field of view and high spatial resolution enables, for the first time, noninvasive imaging of resting-state functional connectivity in the murine brain

Structure of the TPR Domain of AIP: Lack of Client Protein Interaction with the C-Terminal alpha-7 Helix of the TPR Domain of AIP Is Sufficient for Pituitary Adenoma Predisposition

PMCID: PMC3534021This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited