Experimental validation of a high-resolution diffuse optical imaging modality: photomagnetic imaging

Gold nanoparticle-mediated photothermal therapy guidance with multi-wavelength photomagnetic imaging

Difficulty in heating tumors with high spatial selectivity while protecting surrounding healthy tissues from thermal harm is a challenge for cancer photothermal treatment (PTT). To mitigate this problem, PTT mediated by photothermal agents (PTAs) has been established as a potential therapeutic technique to boost selectivity and reduce damage to surrounding healthy tissues. Various gold nanoparticles (AuNP) have been effectively utilized as PTAs, mainly using strategies to target cancerous tissue and increase selective thermal damage. Meanwhile, imaging can be used in tandem to monitor the AuNP distribution and guide the PTT. Mainly, the parameters impacting the induced temperature can be determined using simulation tools before treatment for effective PTT. However, accurate simulations can only be performed if the amount of AuNPs accumulated in the tumor is known. This study introduces Photo-Magnetic Imaging (PMI), which can appropriately recover the AuNP concentration to guide the PTT. Using multi-wavelength measurements, PMI can provide AuNP concentration based on their distinct absorption spectra. Tissue-simulating phantom studies are conducted to demonstrate the potential of PMI in recovering AuNP concentration for PTT planning. The recovered AuNP concentration is used to model the temperature increase accurately in a small inclusion representing tumor using a multiphysics solver that takes into account the light propagation and heat diffusion in turbid media.

Self-Guided Algorithm for Fast Image Reconstruction in Photo-Magnetic Imaging: Artificial Intelligence-Assisted Approach

Previously, we introduced photomagnetic imaging (PMI) that synergistically utilizes laser light to slightly elevate the tissue temperature and magnetic resonance thermometry (MRT) to measure the induced temperature. The MRT temperature maps are then converted into absorption maps using a dedicated PMI image reconstruction algorithm. In the MRT maps, the presence of abnormalities such as tumors would create a notable high contrast due to their higher hemoglobin levels. In this study, we present a new artificial intelligence-based image reconstruction algorithm that improves the accuracy and spatial resolution of the recovered absorption maps while reducing the recovery time. Technically, a supervised machine learning approach was used to detect and delineate the boundary of tumors directly from the MRT maps based on their temperature contrast to the background. This information was further utilized as a soft functional a priori in the standard PMI algorithm to enhance the absorption recovery. Our new method was evaluated on a tissue-like phantom with two inclusions representing tumors. The reconstructed absorption map showed that the well-trained neural network not only increased the PMI spatial resolution but also improved the accuracy of the recovered absorption to as low as a 2% percentage error, reduced the artifacts by 15%, and accelerated the image reconstruction process approximately 9-fold.

Fast ICCD-based temperature modulated fluorescence tomography

Fluorescence tomography (FT) has become a powerful preclinical imaging modality with a great potential for several clinical applications. Although it has superior sensitivity and utilizes low-cost instrumentation, the highly scattering nature of bio-tissue makes FT in thick samples challenging, resulting in poor resolution and low quantitative accuracy. To overcome the limitations of FT, we previously introduced a novel method, termed temperature modulated fluorescence tomography (TMFT), which is based on two key elements: (1) temperature-sensitive fluorescent agents (ThermoDots) and (2) high-intensity focused ultrasound (HIFU). The fluorescence emission of ThermoDots increases up to hundredfold with only several degree temperature elevation. The exceptional and reversible response of these ThermoDots enables their modulation, which effectively allows their localization using the HIFU. Their localization is then used as functional a priori during the FT image reconstruction process to resolve their distribution with higher spatial resolution. The last version of the TMFT system was based on a cooled CCD camera utilizing a step-and-shoot mode, which necessitated long total imaging time only for a small selected region of interest (ROI). In this paper, we present the latest version of our TMFT technology, which uses a much faster continuous HIFU scanning mode based on an intensified CCD (ICCD) camera. This new, to the best of our knowledge, version can capture the whole field-of-view (FOV) of 50×30m m 2 at once and reduces the total imaging time down to 30 min, while preserving the same high resolution (∼1.3m m) and superior quantitative accuracy (<7% error) as the previous versions. Therefore, this new method is an important step toward utilization of TMFT for preclinical imaging.

Development of a preclinical CCD-based temperature modulated fluorescence tomography platform

In preclinical research, fluorescence molecular tomography (FMT) is the most sensitive imaging modality to interrogate whole-body and provide 3D distribution of fluorescent contract agents. Despite its superior sensitivity, its mediocre spatial-resolution has been the main barrier to its clinical translation. This limitation is mainly due to the high scattering of optical photons in biological tissue together with the limited boundary measurements that lead to an undetermined and ill-posed inverse problem. To overcome the limitations of FMT, we previously introduced a novel method termed, Temperature Modulated Fluorescence Tomography (TMFT). TMFT utilizes thermos-sensitive fluorescent agents (ThermoDots) as a key component and localizes them with high-intensity focused ultrasound (HIFU). Scanning the focused HIFU beam having a diameter Ø = 1.3 mm across the tissue while monitoring the variation in the measured fluorescence signals reveals the position of the ThermoDots with high spatial accuracy. We have formerly built a prototype TMFT system that uses optical fibers for detection. In this paper, we present an upgraded version using a CCD camera-based detection that enables non-contact imaging. In this version, the animal under investigation is placed on an ultrasound transparent membrane, which eliminates the need for its immersion in optical matching fluids that were required by the fiber-based system. This CCD-based system will pave the way for convenient and wide-spread use of TMFT in preclinical research. Its performance validation on phantom studies demonstrates that high spatial-resolution (∼1.3 mm) and quantitative accuracy in recovered fluorophore concentration (<3% error) can be achieved.

Multiwavelength photo-magnetic imaging algorithm improved for direct chromophore concentration recovery using spectral constraints

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.

Multi-Wavelength Photo-Magnetic Imaging System for Photothermal Therapy Guidance

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.

Resolving tissue chromophore concentration at MRI resolution using multi-wavelength photo-magnetic imaging

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%.

A thermo-sensitive fluorescent agent based method for excitation light leakage rejection for fluorescence molecular tomography

Fluorescence molecular tomography (FMT) is widely used in preclinical oncology research. FMT is the only imaging technique able to provide 3D distribution of fluorescent probes within thick highly scattering media. However, its integration into clinical medicine has been hampered by its low spatial resolution caused by the undetermined and ill-posed nature of its reconstruction algorithm. Another major factor degrading the quality of FMT images is the large backscattered excitation light component leaking through the rejection filters and coinciding with the weak fluorescent signal arising from a low tissue fluorescence concentration. In this paper, we present a new method based on the use of a novel thermo-sensitive fluorescence probe. In fact, the excitation light leakage is accurately estimated from a set of measurements performed at different temperatures and then is corrected for in the tomographic data. The obtained results show a considerable improvement in both spatial resolution and quantitative accuracy of FMT images due to the proper correction of fluorescent signals.

Ex vivo validation of photo-magnetic imaging

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.

An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

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.

Real-time photo-magnetic 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.