An optimized approach to nonlinear iterative reconstruction of magnetic resonance imaging (MRI)–guided near-infrared spectral tomography (NIRST) images was developed using an L-curve-based algorithm for the choice of regularization parameter. This approach was applied to clinical exam data to maximize the reconstructed values differentiating malignant and benign lesions. MRI/NIRST data from 25 patients with abnormal breast readings (BI-RADS category 4-5) were analyzed using this optimal regularization methodology, and the results showed enhanced p values and area under the curve (AUC) for the task of differentiating malignant from benign lesions. Of the four absorption parameters and two scatter parameters, the most significant differences for benign versus malignant were total hemoglobin (HbT) and tissue optical index (TOI) with pvalues=0.01 and 0.001, and AUC values=0.79 and 0.94, respectively, in terms of HbT and TOI. This dramatically improved the values relative to fixed regularization (pvalue=0.02 and 0.003; AUC=0.75 and 0.83) showing that more differentiation was possible with the optimal method. Through a combination of both biomarkers, HbT and TOI, the AUC increased from 82.9% (fixed regulation=0.1) to 94.3% (optimal method).
A hybrid frequency domain (FD)-continuous wave (CW) MRI/NIRS system was validated in a clinical trial involving patients with at least ACR 4 radiologic findings in Xi’an, China. In this study, MRI guided nonlinear iterative reconstruction of near-infrared spectroscopy (NIRS) images with limited phase data is investigated. In addition, a systematic optimization of the system hardware design has been conducted as well. We are able to get less than 3% variation in tumor contrast to the surrounding normal tissue, by reducing the number of FD detectors from 16 to 6, showing the potential of reducing the FD detectors. Furthermore, a lookup table of the scattering properties has been made by averaging four MRI-identified breast density groups. By using this look-up table for the patient with the noisy phase data, similar AUCs and p-values are achieved for differentiating the malignant from benign patients.
A portable hybrid frequency domain (FD)-continuous wave (CW) Near-Infrared spectroscopy NIRS system has been developed for quantifying changes in total hemoglobin, oxygen saturation and water content in the breast during neoadjuvant chemotherapy. Simultaneous acquisition of two sets of 3 FD channels and 3 CW channels could be completed within 1 min. System calibration and homogeneous phantom measurement show phase variation less than 3% when PMT gain from 0.7 to 1.1 was used. The study of integrating this system into the workflow of clinical oncology practice is ongoing.
Tissue spectroscopy inside the magnetic resonance imaging (MRI) system adds a significant value by measuring fast vascular hemoglobin responses or completing spectroscopic identification of diagnostically relevant molecules. Advances in this type of spectroscopy instrumentation have largely focused on fiber coupling into and out of the MRI; however, nonmagnetic detectors can now be placed inside the scanner with signal amplification performed remotely to the high field environment for optimized light detection. In this study, the two possible detector options, such as silicon photodiodes (PD) and silicon photomultipliers (SiPM), were systematically examined for dynamic range and wavelength performance. Results show that PDs offer 108 (160 dB) dynamic range with sensitivity down to 1 pW, whereas SiPMs have 107 (140 dB) dynamic range and sensitivity down to 10 pW. A second major difference is the spectral sensitivity of the two detectors. Here, wavelengths in the 940 nm range are efficiently captured by PDs (but not SiPMs), likely making them the superior choice for broadband spectroscopy guided by MRI.
A new optical parallel detection system of hybrid frequency and continuous-wave domains was developed to improve the data quality and accuracy in recovery of all breast optical properties. This new system was deployed in a previously existing system for magnetic resonance imaging (MRI)-guided spectroscopy, and allows incorporation of additional near-infrared wavelengths beyond 850 nm, with interlaced channels of photomultiplier tubes (PMTs) and silicon photodiodes (PDs). The acquisition time for obtaining frequency-domain data at six wavelengths (660, 735, 785, 808, 826, and 849 nm) and continuous-wave data at three wavelengths (903, 912, and 948 nm) is 12 min. The dynamic ranges of the detected signal are 105 and 106 for PMT and PD detectors, respectively. Compared to the previous detection system, the SNR ratio of frequency-domain detection was improved by nearly 103 through the addition of an RF amplifier and the utilization of programmable gain. The current system is being utilized in a clinical trial imaging suspected breast cancer tumors as detected by contrast MRI scans.
KEYWORDS: Calibration, Data modeling, Magnetic resonance imaging, Optical properties, Breast, Near infrared spectroscopy, Oxygen, Breast cancer, Optical fibers, Scattering
We have presented methodology to calibrate data in NIRS/MRI imaging versus an absolute reference phantom and results in both phantoms and healthy volunteers. This method directly calibrates data to a diffusion-based model, takes advantage of patient specific geometry from MRI prior information, and generates an initial guess without the need for a large data set. This method of calibration allows for more accurate quantification of total hemoglobin, oxygen saturation, water content, scattering, and lipid concentration as compared with other, slope-based methods. We found the main source of error in the method to be derived from incorrect assignment of reference phantom optical properties rather than initial guess in reconstruction. We also present examples of phantom and breast images from a combined frequency domain and continuous wave MRI-coupled NIRS system. We were able to recover phantom data within 10% of expected contrast and within 10% of the actual value using this method and compare these results with slope-based calibration methods. Finally, we were able to use this technique to calibrate and reconstruct images from healthy volunteers. Representative images are shown and discussion is provided for comparison with existing literature. These methods work towards fully combining the synergistic attributes of MRI and NIRS for in-vivo imaging of breast cancer. Complete software and hardware integration in dual modality instruments is especially important due to the complexity of the technology and success will contribute to complex anatomical and molecular prognostic information that can be readily obtained in clinical use.
A main problem with tomographic fluorescence recovery is that it can only reliably recover images of high contrast to background ratio, which is a problematic issue when the fluorescent contrast in a region of interest is near a significant source of background contrast, such as organs of filtration. A method is presented here, combining the resolution of structural image guidance with the benefits of using multiple fluorescent tracers, one targeted to the tumor of interest and one untargeted, in order to substantially improve the accuracy of recovered contrast values for targeted tracer concentration. Using the normalized subtraction in the data space, the recovery of lower contrast regions can be dramatically improved by suppressing the effect of larger perturbations which appear in both the targeted and untargeted fluorescence data sets. This methodology has significant potential value when imaging near excretory organs such as liver, lung, kidneys and bladder, depending upon the agent to be imaged.
KEYWORDS: Data acquisition, Signal to noise ratio, Breast, Sensors, Near infrared, Signal detection, Diffuse optical tomography, Photodiodes, Chromophores, Continuous wave operation
A new optical parallel detection system of both frequency and continuous wave domains was developed to improve the data quality and accuracy in recovery of all breast optical properties. This new system combines frequency domain (FD) measurements using photomultiplier tubes and continuous wavelengths (CW) measurements using photodiode detectors in order to incorporate addition NIR wavelengths up to 948nm. The FD measurements use 6 wavelengths (660, 735, 785, 808, 826, and 849 nm) while the CW use three wavelengths (903, 912, and 948nm). The frequency domain part of the system is described in detail and steps taken to improve signal to noise ratio are discussed. Furthermore, different acquisition procedures were tested in order to reduce the duration of a complete 9 wavelength acquisition.
Diffuse fluorescence tomography requires high contrast-to-background ratios to accurately reconstruct inclusions of interest. This is a problem when imaging the uptake of fluorescently labeled molecularly targeted tracers in tissue, which can result in high levels of heterogeneously distributed background uptake. We present a dual-tracer background subtraction approach, wherein signal from the uptake of an untargeted tracer is subtracted from targeted tracer signal prior to image reconstruction, resulting in maps of targeted tracer binding. The approach is demonstrated in simulations, a phantom study, and in a mouse glioma imaging study, demonstrating substantial improvement over conventional and homogenous background subtraction image reconstruction approaches.
In this work a generalization of the approach allowing time-domain (TD) excitation and fluorescence data to be
generated using a finite element model (FEM) is introduced. This new functionality allows simulation of temporal point-spread
functions (TPSF) for a heterogeneous scattering and absorbing media of arbitrary geometry. In the first part of
this paper, the approach used to develop a computationally efficient model for solving the time-dependent diffusion
equation for excitation and fluorescence data is presented. In the second part, a detailed theoretical evaluation of the
method is given by comparing the developed FEM simulations with analytical and Monte Carlo data. The total fluence
(intensity data), shows qualitative match whereas meantime of flight is almost identical among the three models for both
excitation and emission data. The results show that the model is reliable and warrants its use for future TD applications
where diffusion modelling can be used.
The superior sensitivity and dynamic range of photodetection using time-correlated single-photon counting (TCSPC)
technology can extend the diameter of specimens that can be imaged with fluorescence molecular tomography (FMT)
and extend the minimum fluorescence concentration that can be reconstructed. To test these limits, a multi-modal system
combining microcomputed tomography (microCT) and time-domain TCSPC FMT was used to image a 5 cm-diameter
tissue-simulating cylindrical phantom containing an inclusion of various concentrations of AlexaFluor 647, mixed with
1% intralipid in water. This was repeated at lower concentrations for a 2.5 cm-diameter cylindrical phantom.
Fluorescence tomography images were reconstructed using the structural information obtained from the microCT (outer
surface of the interrogated sample) as prior information for light transport modeling. Results are presented showing that
the location of the fluorescent inclusion can be reconstructed down to nanomolar concentrations in the 5 cm phantom
and down to sub-nanomolar concentrations in the 25 mm phantom. The ability to reconstruct fluorescence images of
these phantoms demonstrates that an unprecedented level of sensitivity can be achieved with time-domain TCSPC
fluorescence tomography allowing this technology to be used for applications involving animals larger than mice as well
as for applications where limited contrast is available.
A fluorescence imaging system was designed to interface with a microCT device. We focus on refining the workflow for
meshing and the coordinate registration of the two systems. The former is performed by projection imaging in the
microCT, reconstructing a volume, segmenting using image processing software, and meshing using the NIRFAST
software. The coordinate registration is performed by exploiting the geometry of the fluorescence system. We determine
the location of the geometrical center of a subject, which can be used to derive a translation between instruments. The
co-registration is validated by imaging optical phantoms.
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