Robust inference of baseline optical properties of the human head with three-dimensional segmentation from magnetic resonance imaging.

We model the capability of a small (6-optode) time-resolved diffuse optical tomography (DOT) system to infer baseline absorption and reduced scattering coefficients of the tissues of the human head (scalp, skull, and brain). Our heterogeneous three-dimensional diffusion forward model uses tissue geometry from segmented magnetic resonance (MR) data. Handling the inverse problem by use of Bayesian inference and introducing a realistic noise model, we predict coefficient error bars in terms of detected photon number and assumed model error. We demonstrate the large improvement that a MR-segmented model can provide: 2-10% error in brain coefficients (for 2 x 10(6) photons, 5% model error). We sample from the exact posterior and show robustness to numerical model error. This opens up the possibility of simultaneous DOT and MR for quantitative cortically constrained functional neuroimaging.

[1]  R. D. Richtmyer,et al.  Difference methods for initial-value problems , 1959 .

[2]  R. D. Richtmyer,et al.  Difference methods for initial-value problems , 1959 .

[3]  S. J. Press,et al.  Applied multivariate analysis : using Bayesian and frequentist methods of inference , 1984 .

[4]  A J Devaney,et al.  Reconstructive tomography with diffracting wavefields , 1986 .

[5]  S. Gull.  Bayesian Inductive Inference and Maximum Entropy , 1988 .

[6]  J. Berger.  Statistical Decision Theory and Bayesian Analysis , 1988 .

[7]  D. Delpy,et al.  Characterization of the near infrared absorption spectra of cytochrome aa3 and haemoglobin for the non-invasive monitoring of cerebral oxygenation. , 1988, Biochimica et biophysica acta.

[8]  B. Wilson,et al.  Time resolved reflectance and transmittance for the non-invasive measurement of tissue optical properties. , 1989, Applied optics.

[9]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[10]  T. Fearn,et al.  Bayesian statistics : principles, models, and applications , 1990 .

[11]  F. Guess.  Bayesian Statistics: Principles, Models, and Applications , 1990 .

[12]  Alfano,et al.  When does the diffusion approximation fail to describe photon transport in random media? , 1990, Physical review letters.

[13]  Randall L. Barbour,et al.  A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data , 1993, Other Conferences.

[14]  R. Ilmoniemi,et al.  Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .

[15]  E. Gratton,et al.  Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry , 1995 .

[16]  S R Arridge,et al.  Statistical basis for the determination of optical pathlength in tissue. , 1995, Physics in medicine and biology.

[17]  Arridge,et al.  Reconstruction in optical tomography using MRI based prior knowledge , 1995 .

[18]  J. W. Thomas.  Numerical Partial Differential Equations: Finite Difference Methods , 1995 .

[19]  Alessandro Torricelli,et al.  Time-resolved imaging on a realistic tissue phantom: μ(s)' and μ(a) images versus time-integrated images. , 1996, Applied optics.

[20]  D. S. Sivia,et al.  Data Analysis , 1996, Encyclopedia of Evolutionary Psychological Science.

[21]  A G Yodh,et al.  Does the photon-diffusion coefficient depend on absorption? , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[22]  Akira Ishimaru,et al.  Wave propagation and scattering in random media , 1997 .

[23]  E. Reynolds,et al.  Introduction to a Discussion on Near-infrared spectroscopy and imaging of living systems. , 1997 .

[24]  D. Hood,et al.  Fast and Localized Event-Related Optical Signals (EROS) in the Human Occipital Cortex: Comparisons with the Visual Evoked Potential and fMRI , 1997, NeuroImage.

[25]  S. Arridge,et al.  Optical imaging in medicine: II. Modelling and reconstruction , 1997, Physics in medicine and biology.

[26]  A. Villringer,et al.  Non-invasive optical spectroscopy and imaging of human brain function , 1997, Trends in Neurosciences.

[27]  E. Reynolds,et al.  Preface for a Discussion on Near–infrared spectroscopy and imaging of living systems , 1997 .

[28]  Kenneth M. Hanson,et al.  Model-based image reconstruction from time-resolved diffusion data , 1997, Medical Imaging.

[29]  M. Schweiger,et al.  Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head. , 1997, Applied optics.

[30]  A G Yodh,et al.  Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis. , 1997, Applied optics.

[31]  M. Patterson,et al.  Noninvasive determination of the optical properties of two-layered turbid media , 1998 .

[32]  A. Kienle,et al.  Investigation of two-layered turbid media with time-resolved reflectance. , 1998, Applied optics.

[33]  S Arridge,et al.  A gradient-based optimisation scheme foroptical tomography. , 1998, Optics express.

[34]  R. Alcouffe,et al.  Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues. , 1998, Physics in medicine and biology.

[35]  Alexander D. Klose,et al.  Two- and three-dimensional optical tomography of finger joints for diagnostics of rheumatoid arthritis , 1998, European Conference on Biomedical Optics.

[36]  P M Schlag,et al.  Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods. , 1998, Applied optics.

[37]  Kenneth M. Hanson,et al.  Inversion Based on Computational Simulations , 1998 .

[38]  Geoff K. Nicholls,et al.  Prior modeling and posterior sampling in impedance imaging , 1998, Optics & Photonics.

[39]  Gábor Székely,et al.  Magnetic Resonance Imaging Based Correction and Reconstruction of Positron Emission Tomography Images , 1999, EMMCVPR.

[40]  S R Arridge,et al.  Optical tomographic reconstruction in a complex head model using a priori region boundary information. , 1999, Physics in medicine and biology.

[41]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[42]  A. Kienle,et al.  In vivo determination of the optical properties of muscle with time-resolved reflectance using a layered model. , 1999, Physics in medicine and biology.

[43]  Alexander D. Klose,et al.  Gradient-based iterative image reconstruction scheme for time-resolved optical tomography , 1999, IEEE Transactions on Medical Imaging.

[44]  S. Arridge.  Optical tomography in medical imaging , 1999 .

[45]  D Boas,et al.  Systematic diffuse optical image errors resulting from uncertainty in the background optical properties. , 1999, Optics express.

[46]  P. Marquet,et al.  In vivo local determination of tissue optical properties: applications to human brain. , 1999, Applied optics.

[47]  M J Eppstein,et al.  Biomedical optical tomography using dynamic parameterization and bayesian conditioning on photon migration measurements. , 1999, Applied optics.

[48]  D. M. Schmidt,et al.  Bayesian inference applied to the electromagnetic inverse problem , 1998, Human brain mapping.

[49]  Wai-Fung Cheong,et al.  Bedside Imaging of Intracranial Hemorrhage in the Neonate Using Light: Comparison with Ultrasound, Computed Tomography, and Magnetic Resonance Imaging , 1999, Pediatric Research.

[50]  D. Benaron,et al.  Bedside Imaging of Intracranial Hemorrhage in the Neonate Using Light: Comparison with Ultrasound, Computed Tomography, and Magnetic Resonance Imaging , 1999, Pediatric Research.

[51]  W D Heiss,et al.  Ischemic Penumbra: Evidence From Functional Imaging in Man , 2000, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[52]  G. Curio,et al.  Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head , 2000, Neuroscience Letters.

[53]  Arridge,et al.  Optical tomography in the presence of void regions , 2000, Journal of the Optical Society of America. A, Optics, image science, and vision.

[54]  E Miller,et al.  A shape-based reconstruction technique for DPDW data. , 2000, Optics express.

[55]  S Arridge,et al.  Recovery of piecewise constant coefficients in optical diffusion tomography. , 2000, Optics express.

[56]  Ivo W. Kwee.  Towards a Bayesian Framework for Optical Tomography , 2000 .

[57]  D. Delpy,et al.  A 32-channel time-resolved instrument for medical optical tomography , 2000 .

[58]  V. Ntziachristos,et al.  Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[59]  E. Somersalo,et al.  Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography , 2000 .

[60]  Hans Lüders,et al.  Atlas of Regional Anatomy of the Brain Using MRI: With Functional Correlations , 2000 .

[61]  Eric L. Miller,et al.  Imaging the body with diffuse optical tomography , 2001, IEEE Signal Process. Mag..

[62]  D. Boas,et al.  Bedside functional imaging of the premature infant brain during passive motor activation , 1999, Photonics West - Biomedical Optics.

[63]  J. Devaney,et al.  Reconstructive tomography with diffracting wavefields , 1986 .

[64]  S R Arridge,et al.  Three-dimensional time-resolved optical tomography of a conical breast phantom. , 2001, Applied optics.

[65]  D Boas,et al.  Simultaneous imaging and optode calibration with diffuse optical tomography. , 2001, Optics express.

[66]  R. Cubeddu,et al.  In vivo optical characterization of human tissues from 610 to 1010 nm by time-resolved reflectance spectroscopy. , 2001, Physics in medicine and biology.

[67]  R Cubeddu,et al.  Reconstruction of absorber concentrations in a two-layer structure by use of multidistance time-resolved reflectance spectroscopy. , 2001, Optics letters.

[68]  J. Spanier,et al.  Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues. , 2001, Optics letters.

[69]  Albert Cerussi,et al.  Noninvasive functional optical spectroscopy of human breast tissue , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[70]  Simon R. Arridge,et al.  Effect of roughness in nondiffusive regions within diffusive media , 2001 .

[71]  B. Pogue,et al.  Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast. , 2001, Radiology.

[72]  Kevin J Webb,et al.  Source-detector calibration in three-dimensional Bayesian optical diffusion tomography. , 2002, Journal of the Optical Society of America. A, Optics, image science, and vision.

[73]  V. Ntziachristos,et al.  MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions. , 2002, Neoplasia.

[74]  Karl J. Friston,et al.  Bayesian Estimation of Dynamical Systems: An Application to fMRI , 2002, NeuroImage.

[75]  David A. Boas,et al.  A Quantitative Comparison of Simultaneous BOLD fMRI and NIRS Recordings during Functional Brain Activation , 2002, NeuroImage.

[76]  Feng Gao,et al.  Improvement of image quality in diffuse optical tomography by use of full time-resolved data. , 2002, Applied optics.

[77]  David J. C. MacKay,et al.  Information Theory, Inference, and Learning Algorithms , 2004, IEEE Transactions on Information Theory.