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We present experimental results that validate our imaging technique termed photomagnetic imaging (PMI). PMI illuminates the medium under investigation with a near-infrared light and measures the induced temperature increase using magnetic resonance imaging. A multiphysics solver combining light and heat propagation is used to model spatiotemporal distribution of temperature increase. Furthermore, a dedicated PMI reconstruction algorithm has been developed to reveal high-resolution optical absorption maps from temperature measurements. Being able to perform measurements at any point within the medium, PMI overcomes the limitations of conventional diffuse optical imaging. We present experimental results obtained on agarose phantoms mimicking biological tissue with inclusions having either different sizes or absorption contrasts, located at various depths. The reconstructed images show that PMI can successfully resolve these inclusions with high resolution and recover their absorption coefficient with high-quantitative accuracy. Even a 1-mm inclusion located 6-mm deep is recovered successfully and its absorption coefficient is underestimated by only 32%. The improved PMI system presented here successfully operates under the maximum skin exposure limits defined by the American National Standards Institute, which opens up the exciting possibility of its future clinical use for diagnostic purposes.

In this paper, we establish the mathematical framework of a novel imaging technique, namely Photo-magnetic Imaging (PMI). PMI uses laser to illuminate biological tissues and measure the induced temperature variations using magnetic resonance imaging (MRI). PMI overcomes the limitation of conventional optical imaging and allows imaging of optical contrast at MRI spatial resolution. The image reconstruction for PMI, using a finite element-based algorithm with iterative approach, is presented in this paper. The quantitative accuracy of PMI is investigated for various inclusion sizes, depths and absorption values. Then, a comparison between conventional Diffuse Optical Tomography (DOT) and PMI is carried out to illustrate the superior performance of PMI. An example is presented showing that two 2 mm diameter inclusions embedded 4.5 mm deep and located side by side in a 25 mm diameter circular geometry medium is recovered as a single 6 mm diameter object with DOT. However, these two objects are not only effectively resolved with PMI, but their true concentration are also recovered successfully.

Due to the strong scattering nature of biological tissue, optical imaging beyond the diffusion limit suffers from low spatial resolution. In this letter, we present an imaging technique, laser-induced photo-thermal magnetic imaging (PMI), which uses laser illumination to induce temperature increase in a medium and magnetic resonance imaging to map the spatially varying temperature, which is proportional to absorbed energy. This technique can provide high-resolution images of optical absorption and can potentially be used for small animal as well as breast cancer and lymph node imaging. First, we describe the theory of PMI, including the modeling of light propagation and heat transfer in tissue. We also present experimental data with corresponding predictions from theoretical models, which show excellent agreement. V C 2012 American Institute of Physics.

In this work, we present a new analytical approach to model continuous wave laser induced temperature in highly homogeneous turbid media. First, the diffusion equation is used to model light transport and a comprehensive solution is derived analytically by obtaining a special Greens' function. Next, the time-dependent bio-heat equation is used to describe the induced heat increase and propagation within the medium. The bio-heat equation is solved analytically utilizing the separation of variables technique. Our theoretical model is successfully validated using numerical simulations and experimental studies with agarose phantoms and ex-vivo chicken breast samples. The encouraging results show that our method can be implemented as a simulation tool to determine important laser parameters that govern the magnitude of temperature rise within homogenous biological tissue or organs.

We recently introduced a new high-resolution diffuse optical imaging technique termed photo-magnetic imaging (PMI), which utilizes magnetic resonance thermometry (MRT) to monitor the 3D temperature distribution induced in a medium illuminated with a near-infrared light. The spatiotemporal temperature distribution due to light absorption can be accurately estimated using a combined photon propagation and heat diffusion model. High-resolution optical absorption images are then obtained by iteratively minimizing the error between the measured and modeled temperature distributions. We have previously demonstrated the feasibility of PMI with experimental studies using tissue simulating agarose phantoms. In this Letter, we present the preliminary ex vivo PMI results obtained with a chicken breast sample. Similarly to the results obtained on phantoms, the reconstructed images reveal that PMI can quantitatively resolve an inclusion with a 3 mm diameter embedded deep in a biological tissue sample with only 10% error. These encouraging results demonstrate the high performance of PMI in ex vivo biological tissue and its potential for in vivo imaging.

We previously introduced a new high resolution diffuse optical imaging modality termed, photo-magnetic imaging (PMI). PMI irradiates the object under investigation with near-infrared light and monitors the variations of temperature using magnetic resonance thermometry (MRT). In this paper, we present a real-time PMI image reconstruction algorithm that uses analytic methods to solve the forward problem and assemble the Jacobian matrix much faster. The new algorithm is validated using real MRT measured temperature maps. In fact, it accelerates the reconstruction process by more than 250 times compared to a single iteration of the FEM-based algorithm, which opens the possibility for the real-time PMI.

We previously introduced Photo-Magnetic Imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using Magnetic Resonance Thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation Finite Element Method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.