Weighting Function Effects in a Direct Regularization Method for Image-Guided Near-Infrared Spectral Tomography of Breast Cancer.

Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast by 10%, the contrast to noise ratio by 20% and the full width half maximum (FWHM) by 30%. The results from phantoms and human images show that a linear inverse distance weighting function appears optimal, and that incorporation of this function can generally improve the recovered total hemoglobin contrast of the tumor to the normal surrounding tissue by more than 15% in human cases

Direct Regularization from Co-Registered Anatomical Images for MRI-Guided Near-Infrared Spectral Tomographic Image Reconstruction

Combining anatomical information from high resolution imaging modalities to guide near-infrared spectral tomography (NIRST) is an efficient strategy for improving the quality of the reconstructed spectral images. A new approach for incorporating image information directly into the inversion matrix regularization was examined using Direct Regularization from Images (DRI), which encodes the gray-scale data into the NIRST image reconstruction problem. This process has the benefit of eliminating user intervention such as image segmentation of distinct regions. Specifically, the Dynamic Contrast Enhanced Magnetic Resonance (DCE-MR) image intensity value differences within the anatomical image were used to implement an exponentially-weighted regularization function between the image pixels. The algorithm was validated using simulated reconstructions with noise, and the results showed that spatial resolution and robustness of the reconstructed images were significantly improved by appropriate choice of the regularization weight parameters. The proposed approach was also tested on in vivo breast data acquired in a recent clinical trial combining NIRST / MRI for cancer tumor characterization. Relative to the standard “no priors” diffuse recovery, the contrast of the tumor to the normal surrounding tissue increased from 2.4 to 3.6, and the difference between the tumor size segmented from DCE-MR images and reconstructed optical images decreased from 18% to 6%, while there was an overall decrease in surface artifacts

Automaticity in processing spatial-numerical associations: Evidence from a perceptual orientation judgment task of Arabic digits in frames.

Human adults are faster to respond to small/large numerals with their left/right hand when they judge the parity of numerals, which is known as the SNARC (spatial-numerical association of response codes) effect. It has been proposed that the size of the SNARC effect depends on response latencies. The current study introduced a perceptual orientation task, where participants were asked to judge the orientation of a digit or a frame surrounding the digit. The present study first confirmed the SNARC effect with native Chinese speakers (Experiment 1) using a parity task, and then examined whether the emergence and size of the SNARC effect depended on the response latencies (Experiments 2, 3, and 4) using a perceptual orientation judgment task. Our results suggested that (a) the automatic processing of response-related numerical-spatial information occurred with Chinese-speaking participants in the parity task; (b) the SNARC effect was also found when the task did not require semantic access; and (c) the size of the effect depended on the processing speed of the task-relevant dimension. Finally, we proposed an underlying mechanism to explain the SNARC effect in the perceptual orientation judgment task

Optimization of Fluorescent Imaging in the Operating Room through Pulsed Acquisition and Gating to Ambient Background Cycling

The design of fluorescence imaging instruments for surgical guidance is rapidly evolving, and a key issue is to efficiently capture signals with high ambient room lighting. Here, we introduce a novel time-gated approach to fluorescence imaging synchronizing acquisition to the 120 Hz light of the room, with pulsed LED excitation and gated ICCD detection. It is shown that under bright ambient room light this technique allows for the detection of physiologically relevant nanomolar fluorophore concentrations, and in particular reduces the light fluctuations present from the room lights, making low concentration measurements more reliable. This is particularly relevant for the light bands near 700nm that are more dominated by ambient lights

Portable, Parallel 9-Wavelength Near-Infrared Spectral Tomography (NIRST) System for Efficient Characterization of Breast Cancer within the Clinical Oncology Infusion Suite

A portable near-infrared spectral tomography (NIRST) system was developed with simultaneous frequency domain (FD) and continuous-wave (CW) optical measurements for efficient characterization of breast cancer in a clinical oncology setting. Simultaneous FD and CW recordings were implemented to speed up acquisition to 3 minutes for all 9 wavelengths, spanning a range from 661nm to 1064nm. An adjustable interface was designed to fit various breast sizes and shapes. Spatial images of oxy- and deoxy-hemoglobin, water, lipid, and scattering components were reconstructed using a 2D FEM approach. The system was tested on a group of 10 normal subjects, who were examined bilaterally and the recovered optical images were compared to radiographic breast density. Significantly higher total hemoglobin and water were estimated in the high density relative to low density groups. One patient with invasive ductal carcinoma was also examined and the cancer region was characterized as having a contrast ratio of 1.4 in total hemoglobin and 1.2 in water

Automatic And Robust Calibration of Optical Detector Arrays for Biomedical Diffuse Optical Spectroscopy

The design and testing of a new, fully automated, calibration approach is described. The process was used to calibrate an image-guided diffuse optical spectroscopy system with 16 photomultiplier tubes (PMTs), but can be extended to any large array of optical detectors and associated imaging geometry. The design goals were accomplished by developing a routine for robust automated calibration of the multi-detector array within 45 minutes. Our process was able to characterize individual detectors to a median norm of the residuals of 0.03 V for amplitude and 4.4 degrees in phase and achieved less than 5% variation between all the detectors at the 95% confidence interval for equivalent measurements. Repeatability of the calibrated data from the imaging system was found to be within 0.05 V for amplitude and 0.2 degrees for phase, and was used to evaluate tissue- simulating phantoms in two separate imaging geometries. Spectroscopic imaging of total hemoglobin concentration was recovered to within 5% of the true value in both cases. Future work will focus on streamlining the technology for use in a clinical setting with expectations of achieving accurate quantification of suspicious lesions in the breast

Optimization of Image Reconstruction for Magnetic Resonance Imaging–Guided Near-Infrared Diffuse Optical Spectroscopy in Breast

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)