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The ankles of ballet dancers are routinely under heavy loading that may lead to osteoarthritic changes. It would be clinically useful to identify such pathology as early as possible in a dancer's career. Therefore, the purpose of this study was to compare quantitative measurements in magnetic resonance (MR) images of the talocrural and talonavicular joints in ballet dancers and healthy non-dancers for use in formulating prediction of chronic injury and degenerative joint disease in these locations. Quantitative measurements in MR images of the talocrural and talonavicular joints were compared in 10 female ballet dancers, 10 healthy female non-dancers, and nine male ballet dancers. Fat-suppressed density-weighted proton, T1rho, and T2 mapping images were acquired with a 3.0 T MR scanner. Medial and lateral subchondral bone distance between the tibia and talus (MSBD and LSBD), axial navicular-talus axis angle (ANT angle), sagittal talar neck angle against the posterior talocalcaneal joint (TN angle), and curvature of navicular surface at the talonavicular joint were measured on sagittal images. The medial subchondral bone distance was found to be significantly larger in female dancers than female non-dancers (4.05 mm vs. 2.75 mm, p < 0.05), whereas there were no significant differences in LSBD (2.63 mm vs. 2.63 mm, p = 0.87). Axial navicular talus angles in female dancers were significantly larger than those in female non-dancers (38.9° vs. 24.3°, p < 0.05). There was a tendency for the TN angle to be smaller and navicular curvature (NC) to be larger in female dancers compared to female non-dancers, though the differences were not significant (TN angle: 16.6° vs. 22.3°, p = 0.09, and NC: 0.186 vs. 0.165, p = 0.28). There were no significant differences in T1rho or T2 values of talonavicular joint cartilage. These results show that the bony anatomy of dancers' ankles may adapt to the stresses placed on them by ballet.

Background Since ballet dancers begin their training before skeletal maturity, accurate and non-invasive identification of cartilage diseases is clinically important. Angle-dependent analysis of T1rho and T2 sequences can be useful for quantification of the composition of cartilage. Purpose To investigate the angle-dependent T1rho and T2 profiles of ankle cartilage in non-dancers and dancers. Material and Methods Ten female non-dancers, ten female dancers, and 9 male dancers were evaluated using T1rho and T2 mapping sequences. Manual segmentation of talar and tibial cartilage on these images was performed by two radiologists. Inter- and intra-rater reliabilities were calculated using intraclass correlation coefficients (ICCs) and Bland–Altman analysis. Mean thickness and volume of cartilage were estimated. Angle-dependent relaxation time profiles of talar and tibial cartilage were created. Results ICCs of the number of segmented pixels were poor to excellent. Bland–Altman plots indicated that differences were associated with segment sizes. Segmented cartilage on T1rho demonstrated larger thickness and volume than those on T2 in all populations. Male dancers showed larger cartilage thickness and volume than female dancers and non-dancers. Each cartilage demonstrated angular-dependent T1rho and T2 profiles. Minimal T1rho and T2 values were observed at approximately 180°–200°; higher values were seen at the angle closer to the magic angle. Minimal T2 value of talar cartilage of dancers was larger than that of non-dancers. Conclusion In this small cohort study, regional and sex variations of ankle cartilage T1rho and T2 values in dancers and non-dancers were demonstrated using an angle-dependent approach.

Rationale and Objectives Breast segmentation using the U-net architecture was implemented and tested in independent validation datasets to quantify fibroglandular tissue volume in breast MRI. Materials and Methods Two datasets were used. The training set was MRI of 286 patients with unilateral breast cancer. The segmentation was done on the contralateral normal breasts. The ground truth for the breast and fibroglandular tissue (FGT) was obtained by using a template-based segmentation method. The U-net deep learning algorithm was implemented to analyze the training set, and the final model was obtained using 10-fold cross-validation. The independent validation set was MRI of 28 normal volunteers acquired using four different MR scanners. Dice Similarity Coefficient (DSC), voxel-based accuracy, and Pearson's correlation were used to evaluate the performance. Results For the 10-fold cross-validation in the initial training set of 286 patients, the DSC range was 0.83–0.98 (mean 0.95 ± 0.02) for breast and 0.73–0.97 (mean 0.91 ± 0.03) for FGT; and the accuracy range was 0.92–0.99 (mean 0.98 ± 0.01) for breast and 0.87–0.99 (mean 0.97 ± 0.01) for FGT. For the entire 224 testing breasts of the 28 normal volunteers in the validation datasets, the mean DSC was 0.86 ± 0.05 for breast, 0.83 ± 0.06 for FGT; and the mean accuracy was 0.94 ± 0.03 for breast and 0.93 ± 0.04 for FGT. The testing results for MRI acquired using four different scanners were comparable. Conclusion Deep learning based on the U-net algorithm can achieve accurate segmentation results for the breast and FGT on MRI. It may provide a reliable and efficient method to process large number of MR images for quantitative analysis of breast density.

Multiwavelength photo-magnetic imaging (PMI) is a novel combination of diffuse optics and magnetic resonance imaging, to the best of our knowledge, that yields tissue chromophore concentration maps with high resolution and quantitative accuracy. Here, we present the first experimental results, to the best of our knowledge, obtained using a spectrally constrained PMI image reconstruction method, where chromophore concentration maps are directly recovered, unlike the conventional two-step approach that requires an intermediate step of reconstructing wavelength-dependent absorption coefficient maps. The imposition of the prior spectral information into the PMI inverse problem improves the reconstructed image quality and allows recovery of highly quantitative concentration maps, which are crucial for effective cancer detection and characterization. The obtained results demonstrate the higher performance of the direct reconstruction method. Indeed, the reconstructed concentration maps are not only of higher quality but also obtained approximately 2 times faster than the conventional method.

Background and objectives In photothermal therapy, cancerous tissue is treated by the heat generated from absorbed light energy. For effective photothermal therapy, the parameters affecting the induced temperature should be determined before the treatment by modeling the increase in temperature via numerical simulations. However, accurate simulations can only be achieved when utilizing the accurate optical, thermal, and physiological properties of the treated tissue. Here, we propose a multi-wavelength photo-magnetic imaging (PMI) technique that provides quantitative and spatially resolved tissue optical absorption maps at any wavelength within the near-infrared (NIR) window to assist accurate photothermal therapy planning. Study design/materials and methods The study was conducted using our recently developed multi-wavelength PMI system, which operates at four laser wavelengths (760, 808, 860, and 980 nm). An agar tissue-simulating phantom containing water, lipid, and ink was illuminated using these wavelengths, and the slight internal laser-induced temperature rise was measured using magnetic resonance thermometry (MRT). The phantom optical absorption was recovered at the used wavelengths using our dedicated PMI image reconstruction algorithm. These absorption maps were then used to resolve the concentration of the tissue chromophores, and thus deduce its optical absorption spectrum in the NIR region based on the Beer-Lambert law. Results The optical absorption of the phantom was successfully recovered at the used four wavelengths with an average error of ~1.9%. The recovered absorption coefficient was then used to simulate temperature variations inside the phantom. A comparison between the modeled temperature maps and the MRT measured ones showed that these maps are in a good agreement with an average pseudo R2 statistic of 0.992. These absorption values were used to successfully recover the concentration of the used chromophores. Finally, these concentrations are used to accurately calculate the total absorption spectrum of the phantom in the NIR spectral window with an average error as low as ~2.3%. Conclusions Multi-wavelength PMI demonstrated a great ability to assess the distribution of tissue chromophores, thus providing its total absorption at any wavelength within the NIR spectral range. Therefore, applications of photothermal therapy applied at NIR wavelengths can benefit from the absorption spectrum recovered by PMI to determine important parameters such as laser power as well as the laser exposure time needed to attain a specific increase in temperature prior to treatment. Lasers Surg. Med. 00:00-00, 2020. © 2020 Wiley Periodicals LLC.

Tomographically recovering chromophore concentrations usually requires the intermediate step of reconstructing absorption maps at different wavelengths first. Here, we present a method that allows to obtain these concentrations directly from measured magnetic resonance temperature maps.

Photo-Magnetic Imaging (PMI) is a novel multimodality imaging technique that provides optical absorption maps with high-resolution and quantitative accuracy. Here, we present the preliminary experimental validation results obtained using our new multi-wavelength PMI system.

Although diffuse optical tomography (DOT) is able to obtain valuable functional information, its routine use in clinic is hampered by its poor spatial resolution and quantitative accuracy. Previously, our team introduced Photo-Magnetic Imaging (PMI) to overcome the limitation of DOT. PMI is a hybrid modality that synergistically utilizes optics and Magnetic Resonance Imaging (MRI). While illuminating the imaged medium by near-infrared laser, the induced internal temperature increase is measured using Magnetic Resonance Thermometry (MRT). Using these MRT maps, optical absorption maps at the laser's wavelength can be recovered using the dedicated PMI image reconstruction algorithm. In this paper, we present the result of the first validation simulation study of multi-wavelength PMI that utilizes five different laser wavelengths ranging between 760 and 980 nm. Using the high resolution wavelength specific absorption maps, PMI successfully recovered the concentration of three dyes, used as chromophore in the composition of our phantom, with high spatial resolution and quantitative accuracy. By providing functional information at high resolution, multi-wavelength PMI will be a valuable tool for monitoring tissue physiology, cancer detection and monitoring.

Photo-magnetic imaging (PMI) is an emerging optical imaging modality that showed great performance on providing absorption maps with high resolution and quantitative accuracy. As a multi-modality technology, PMI warms up the imaged object using a near infrared laser while temperature variation is measured using magnetic resonance imaging. By probing tissue at multiple wavelengths, concentration of the main tissue chromophores such as oxy-and deoxy-hemoglobin, lipid, and water are obtained then used to derive functional parameters such as total hemoglobin concentration and relative oxygen saturation. In this paper, we present a multi-wavelength PMI system that was custom-built to host five different laser wavelengths. After recovering the high-resolution absorption maps, a least-squared minimization process was used to resolve the different chromophore concentration. The performance of the system was experimentally tested on a phantom with two different dyes. Their concentrations were successfully assessed with high spatial resolution and average accuracy of nearly 80%. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

In this study, we develop an analytical based simulation method to determine laser parameters such as laser power and its duration for laser induced thermal ablation. This method utilizes two important physical approaches to model i) the light propagation and ii) the change in temperature due to the laser absorption in turbid media. First, the photon density is obtained analytically from the solution of the diffusion equation by deriving a special Greens’ function. Next, the Pennes bio-heat equation is solved analytically for a source term consisting of the product of the photon density and the optical absorption coefficient. Our approach is validated with the results obtained by Finite Element Method (FEM) and experimental results acquired from the gold-nanoparticle embedded phantom.

Photo-Magnetic Imaging (PMI) is a novel diffuse optical imaging technique that yields high resolution optical absorption images. It is based on the measurement of the temperature increase of a given medium after its illumination with a near-infrared laser using Magnetic Resonance Thermometry (MRT). In this paper, we present the first multi-wavelengths PMI system able to provide oxy- and deoxyhemoglobin concentration maps with high spatial and quantitative accuracy.

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. (C) 2017 Optical Society of America.

In this study, we present a fast analytical approach for laser induced temperature increase in biological tissue. The whole problem consists of two main steps. These steps are the light propagation and heat transfer in tissue. We first obtain a detailed analytical solution for the diffusion equation based on an integral approach for specific boundary conditions. Secondly, we also solve the Pennes' bio-heat transfer equation analytically using the separation of variables technique and obtain the temperature induced by optical absorption of tissue. Here, heat source term consists of the local absorption and photon density, which will be determined from the diffusion equation. We find a very comprehensive solution for the diffusion equation by using an integral method for the Robin boundary condition. In other words, we obtain a particular Green's function in a different way. Next, we use this solution as a source term in the Pennes’ bio-heat equation by utilizing the heat convection boundary condition. It is important to note that these boundary conditions are good approximations for imaging of biological tissue. As a result, we obtain spatio-temporal temperature distribution inside the medium. First, our approach is validated by a numerical approach using a Finite Element Method (FEM). Next, we also validate our method by performing phantom and tissue experiments. Experimental data corresponding to spatio-temporal temperature distribution are recorded using magnetic resonance thermometry. The analytical results obtained by our method are in a very good agreement with ones obtained by the FEM and experiment.

We introduce a new Photo-Magnetic Imaging image reconstruction algorithm that uses analytical methods to solve both its forward and inverse problem, making it 33 times faster than a single iteration of our previous FEM-based algorithm.

Laser induced thermal ablation is a minimally invasive alternative to conventional surgery and can provide faster recovery times as well as reduction in complication rates. In this study, our purpose is to develop a simulation tool for therapy planning to determine important laser parameters that govern the magnitude of temperature rise and its duration in the tissue. This tool is based on the use of a new analytical approach to model laser induced temperature in turbid media. First, the diffusion equation is used for the light propagation and a comprehensive solution is derived analytically by obtaining a special Greens’ function. Next, the heat equation is also solved analytically for a source term given by the product of the solution of the diffusion equation and the local optical absorption. The results obtained with our theoretical model are successfully validated using experimental data.

A WDM–PON recycling incoming light to transmit upstream data has been analyzed. Effect of Rayleigh scattering, uneven energy distribution and noise accumulation are evaluated to achieve 80 km bidirectional communication with

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. (c) 2015 Optical Society of America

Multi-modality imaging leverages the competitive advantage of different imaging systems to improve the overall resolution and quantitative accuracy. Our new technique, Photo-Magnetic Imaging (PMI) is one of these true multi-modality imaging approaches, which can provide quantitative optical absorption map at MRI spatial resolution. PMI uses laser light to illuminate tissue and elevate its temperature while utilizing MR thermometry to measure the laser-induced temperature variation with high spatial resolution. The high-resolution temperature maps are later converted to tissue absorption maps by a finite element based inverse solver that is based on modeling of photon migration and heat diffusion in tissue. Previously, we have demonstrated the feasibility of PMI with phantom studies. Recently, we have managed to reduce the laser power under ANSI limit for maximum skin exposure therefore, we have well positioned PMI for in vivo imaging. Currently we are expanding our system by adding multi-wavelength imaging capability. This will allow us not only to resolve spatial distribution of tissue chromophores but also exogenous contrast agents. Although we test PMIs feasibility with animal studies, our future goal is to use PMI for breast cancer imaging due to its high translational potential.

We introduce an entirely new technique, termed Photo-Magnetic Imaging (PMI), which overcomes the limitation of pure optical imaging and provides optical absorption at MRI spatial resolution. PMI uses laser light to heat the medium under investigation and employs MR thermometry for the determination of spatially resolved optical absorption in the probed medium. A FEM-based PMI forward solver has been developed by modeling photon migration and heat diffusion in tissue to compare simulation results with measured MRI maps. We have successfully performed PMI using 2.5 cm diameter agar phantom with two low optical absorption contrast (x 4) inclusions under the ANSI limit. Currently, we are developing the PMI inverse solver and undertaking further phantom and in vivo experiments.

Since diffuse optical tomography (DOT) is a low spatial resolution modality, it is desirable to validate its quantitative accuracy with another well-established imaging modality, such as magnetic resonance imaging (MRI). In this work, we have used a polymer based bi-functional MRI-optical contrast agent (Gd-DTPA-polylysine-IR800) in collaboration with GE Global Research. This multi-modality contrast agent provided not only co-localization but also the same kinetics, to cross-validate two imaging modalities. Bi-functional agents are injected to the rats and pharmacokinetics at the bladder are recovered using both optical and MR imaging. DOT results are validated using MRI results as "gold standard"

Optical tomography at organ level is challenging due to highly scattering nature of the tissue. We have developed a novel true multimodality imaging technique, namely Photo-Magnetic Imaging (PMI), which provides superior spatial resolution and high quantitative accuracy even in thick tissue.

In this paper, we present a novel imaging technique, namely Photo-Magnetic Imaging (PMI), which overcomes the limitation of pure optical imaging and provides optical contrast at MRI spatial resolution.

It is difficult to cross-validate the parameters measured by different modalities. Our in vivo small animal study is the first to validate a true multi-modality system (combined MRI-DOT system) with a true multi-modality contrast agent.

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.

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.