Photo-magnetic imaging (PMI) is a novel diffuse optical imaging technique used to recover high resolution images of the optical absorption coefficient of bio-tissue. It uses near-infrared laser light to slightly warm up the tissue and measures the induced temperature using magnetic resonance thermometry (MRT). The measured temperature maps are then converted into absorption maps using a dedicated PMI image reconstruction algorithm. We present a convolutional neural network -based image reconstruction algorithm that improves the accuracy of the recovered absorption maps while reducing the recovery time. This approach directly delineates the boundaries of tumors on the MRT maps. These boundaries are then used to generate soft a priori information that will be employed to constrain the standard PMI image reconstruction algorithm. We evaluate the performance of the algorithm using a tissue-like phantom with an inclusion representing the presence of a potential tumor. The obtained results show that our new method can delineate the tumor region with an accuracy of ~96%.
We previously introduced Photo-Magnetic Imaging (PMI) as a true multi-modality imaging technique for non-invasive, high resolution optical tomography. With a simple add-on of continuous wave lasers to an existing MRI system, PMI converts the laser induced temperature increase measured by MR thermometry into tissue optical absorption map utilizing a dedicated Finite Element Model (FEM) based image reconstruction algorithm. The newly implemented multi-wavelength capabilities allow PMI to recover 3D tissue oxygenation maps as well as exogenous contrast agent distribution such as indocyanine green or gold nanoparticles with high-resolution and quantitative accuracy.
In photothermal therapy, heat generated from absorbed light energy is used to treat cancerous tissue. Thus, determining laser parameters that control temperature elevation prior to therapy is crucial for an effective outcome. These parameters can be defined by modeling the expected temperature increase via numerical simulations. The quality of these simulations highly depends on the accurate knowledge of optical properties of the treated tissue. Multi-wavelength Photo Magnetic Imaging (PMI) utilizes four laser wavelengths from the near infrared (NIR) window to induce a relatively low temperature increase, while measuring the laser-induced temperature increase using Magnetic Resonance Thermometry. These measured temperature maps are then used by the PMI image reconstruction algorithm to provide high spatial resolution absorption maps at these wavelengths. These absorption maps are then processed to recover the concentration of the main chromophores of the tissue, and consequently obtain its total optical absorption spectrum at any wavelength in the NIR region based on the Beer-Lambert law. In this paper, PMI was used to recover the absorption coefficient of a gelatin tissuesimulating phantom at four wavelengths. These spatially-resolved absorption values were used to successfully recover the concentration of the chromophores of the phantom and calculate its total absorption spectrum in the NIR spectral window with an error as low as ∼ 2.3%. Therefore, applications of photothermal therapy applied in NIR window can benefit from the absorption spectrum recovered by PMI to achieve accurate simulations and determine important laser parameters, which are key for accurate therapy planning.
High scattering in biological tissues severely degrades the spatial resolution of optical fluorescence imaging in thick tissue. As one of the most sensitive in vivo molecular imaging modalities, Fluorescence Tomography plays an essential role in preclinical studies. To overcome the limitations of FT, we introduced a novel method termed, temperature modulated fluorescence tomography (TMFT). TMFT is based on two key elements: 1) temperature sensitive fluorescent agent (ThermoDots) and 2) high intensity focused ultrasound (HIFU). TMFT localizes the position of the fluorescent ThermoDots by scanning a HIFU beam across the tissue while monitoring the variation in the measured fluorescence signals. Actually, a binary mask is built by monitoring the sudden jumps in the fluorescence signal corresponding to the HIFU scan over a position containing ThermoDots. This binary map is used as functional a priori during the FT image reconstruction process. TMFT not only allowed us to resolve ThermoDots with high spatial resolution (~1.3 mm), deep in tissue (~ 60 mm) but with high quantitative accuracy as well (< 3% error). In this paper, we present the latest prototype of TMFT. Here, the fluorescence signals are acquired using a CCD camera, which increases the sensitivity of the system compared to the previous fiber-based system.
KEYWORDS: Absorption, Chromophores, Temperature metrology, Spatial resolution, Inverse problems, Finite element methods, Magnetic resonance imaging, Image restoration, Near infrared
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.
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