Anthropomorphic Polydimethylsiloxane silicone-based phantom for Diffuse Optical Imaging

The accuracy and clinical utility of diffuse optical imaging systems rely on continuous advancements in instrumentation, theoretical modeling, and computational methods, alongside strategies to overcome persistent barriers to clinical translation. A key challenge in diffuse optical imaging research is the development of computationally efficient numerical models that accurately describe light-tissue interactions in complex anatomical domains, along with the validation of these models and novel instrumentation using realistic tissue-mimicking phantoms. Although diffuse optical imaging remains a promising area of research for applications such as cancer detection and functional brain activity assessment, progress has been limited by the lack of anatomically complex optical phantoms and the high computational cost of Monte Carlo simulations required to model light propagation. This dissertation addresses these challenges through two key innovations. First, we designed a multi-filament-mixing 3-D printing platform which enables spatially varying absorption, scattering, and luminescent optical properties by dynamically blending multiple commercially available filaments. This platform facilitates the design and fabrication of anatomically accurate phantoms with precise control over optical absorbance and scattering parameters, while also incorporating tunable luminescence intensity through the embedding of phosphorescent materials. We printed several benchmark phantoms showcasing our method's capability of generating complex anatomical shapes with continuously varying optical properties. This method should therefore allow for the design and easy fabrication of highly complex, anatomically accurate phantoms for benchmarking, calibration, and training across a wide range of diffuse optical imaging applications. Second, we introduce a memory-efficient parametric modeling approach to address the computational challenges in capturing detected photon partial path length (PPL) distributions in Monte Carlo simulations. This method utilizes numerical stochastic estimation techniques, such as the Box-Cox transformation, skew-normal distribution modeling, and rejection sampling, to efficiently approximate the PPL distribution with a small set of statistical parameters. This approach significantly reduces the memory footprint of large-scale Monte Carlo simulations, while remaining generalizable to anatomically accurate domains. Furthermore, the ability to regenerate an arbitrary number of detected photon PPLs using the recorded parametric PPL models demonstrates significant computational savings while retaining high levels of accuracy. Together, these findings enable more accessible and accurate diffuse optical imaging modeling by substantially reducing the computational costs typically associated with simulating light transport in complex anatomical domains. In summary, this dissertation presents experimental and computational advancements that are broadly applicable to diffuse optical imaging research. Both innovations are generalizable to complex tissue-like domains, enhancing their relevance across a wide range of applications. These contributions support the continued development of diffuse optical imaging technologies and promote their clinical translation, helping to enable more accessible, cost-effective, and practical imaging systems.--Author's abstract

Optical imaging of fluorescent probes is an essential tool for investigation of molecular events in small animals for drug developments. In order to get localization and quantification information of fluorescent labels, CEA-LETI has developed efficient approaches in classical reflectance imaging as well as in diffuse optical tomographic imaging with continuous and temporal signals. This paper presents an overview of the different approaches investigated and their performances. High quality fluorescence reflectance imaging is obtained thanks to the development of an original "multiple wavelengths" system. The uniformity of the excitation light surface area is better than 15%. Combined with the use of adapted fluorescent probes, this system enables an accurate detection of pathological tissues, such as nodules, beneath the animal's observed area. Performances for the detection of ovarian nodules on a nude mouse are shown. In order to investigate deeper inside animals and get 3D localization, diffuse optical tomography systems are being developed for both slab and cylindrical geometries. For these two geometries, our reconstruction algorithms are based on analytical expression of light diffusion. Thanks to an accurate introduction of light/matter interaction process in the algorithms, high quality reconstructions of tumors in mice have been obtained. Reconstruction of lung tumors on mice are presented. By the use of temporal diffuse optical imaging, localization and quantification performances can be improved at the price of a more sophisticated acquisition system and more elaborate information processing methods. Such a system based on a pulsed laser diode and a time correlated single photon counting system has been set up. Performances of this system for localization and quantification of fluorescent probes are presented.

Optical techniques based on photon migration are rapidly emerging as a promising alternative and/or augmentation of existing medical imaging modalities. For example, real time studies of hemodynamic changes in brain tissue are possible as a step towards optical functional brain imaging. Time-resolved implementations of these techniques allow for discrimination between scattering and absorption and for depth resolution. They require sub-nanosecond pulsed light sources with high repetition rate and sufficient power for deep enough tissue penetration. Picosecond diode lasers satisfy the clinical demands of economy, compact size, and reliability almost perfectly. Today multi-channel diode laser devices are commercially available and are widely used in diffuse optical imaging and spectroscopy, in particular in optical tomography and breast cancer detection. However, the output powers of these devices are just about sufficient for moderate tissue penetration depths. An improvement that does not compromise the advantages of the diode laser sources is amplification of the diode laser output by means of solid state tapered amplifiers. We present an amplified light source for use in NIR diffuse optical spectroscopy and imaging, providing pulse widths as short as 100 ps, adjustable repetition rates up to 80 MHz, and peak power levels as high as 7 Watts, corresponding to average power levels exceeding 100 mW. In combination with time-resolved photon counting electronics matching the high throughput demands in conjunction with the new source, state-of-the-art systems for diffuse optical imaging can be built. System design features and possible application examples are presented.

Background: Sarcomas account for almost 15% of all childhood cancers and 40-60% of these patients develop locally recurrent or metastatic disease. Currently in many sarcomas, the only clinically accepted prognostic marker in patients with localized disease is the percent of tumor necrosis at the time of surgery. Diffuse Optical Spectroscopic Imaging (DOSI) is an emerging near-infrared (NIR) imaging technique that non-invasively measures quantitative functional information and may provide a new means to monitor and predict chemotherapy response in sarcoma which could impact treatment decisions. Here we evaluate the feasibility of measuring pediatric sarcomas with DOSI. Methods: Patients diagnosed with either Ewing’s Sarcoma or osteosarcoma underwent DOSI measurement at multiple time points during their course of neoadjuvant chemotherapy. A handheld probe was used to take point measurements in a 1 cm spaced grid at tumor and contralateral normal locations. The measurement area was approximately 6 x 7 cm and a single point measurement typically took 15-30 s, which includes the time it takes to position the probe, ensure good contact between the probe and the skin, and acquire data. The optical properties, and absolute concentrations of oxyhemoglobin (ctHbO2), deoxyhemoglobin (ctHb), water (ctH2O), and lipids were compared between tumor and normal measurements. Results: To date, one osteosarcoma and two Ewing’s sarcoma patients have been measured. At baseline and early in treatment, all subjects had a statistical difference in total hemoglobin concentration between the affected and contralateral normal tissues (p < 0.05 for Student’s t-test, Kolmogorov-Smirnov test, and Mann-Whitney rank test). Statistical differences also appeared in oxyhemoglobin, deoxyhemoglobin, oxygen saturation, water, lipids, scattering amplitude, and scattering power although longitudinal trends varied across patients. Conclusions: DOSI can be utilized to measure optical properties and to obtain functional information in bone sarcoma patients. It can detect differences between affected and normal tissue. A better understanding of the optical properties in this patient population is needed. Larger data sets are needed to characterize and quantify sarcoma optical properties and treatment response dynamics, ideally finding a functional biomarker associated with pathologic response. Additional accrual of primary bone sarcoma patients and normal volunteers is ongoing. Citation Format: Hannah M. Peterson, Bang H. Hoang, David Geller, Richard Gorlick, Rui Yang, Jeremy Berger, Janet Tingling, Michael Roth, Jonathan Gill, Darren Roblyer. Clinical feasibility of chemotherapy monitoring for bone sarcoma patients with diffuse optical spectroscopic imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 699. doi:10.1158/1538-7445.AM2017-699

We present high spatial density, multi-modal, parallel-plate Diffuse Optical Tomography (DOT) imaging systems for the purpose of breast tumor detection. One hybrid instrument provides time domain (TD) and continuous wave (CW) DOT at 64 source fiber positions. The TD diffuse optical spectroscopy with PMT- detection produces low-resolution images of absolute tissue scattering and absorption while the spatially dense array of CCD-coupled detector fibers (108 detectors) provides higher-resolution CW images of relative tissue optical properties. Reconstruction of the tissue optical properties, along with total hemoglobin concentration and tissue oxygen saturation, is performed using the TOAST software suite. Comparison of the spatially-dense DOT images and MR images allows for a robust validation of DOT against an accepted clinical modality. Additionally, the structural information from co-registered MR images is used as a spatial prior to improve the quality of the functional optical images and provide more accurate quantification of the optical and hemodynamic properties of tumors. We also present an optical-only imaging system that provides frequency domain (FD) DOT at 209 source positions with full CCD detection and incorporates optical fringe projection profilometry to determine the breast boundary. This profilometry serves as a spatial constraint, improving the quality of the DOT reconstructions while retaining the benefits of an optical-only device. We present initial images from both human subjects and phantoms to display the utility of high spatial density data and multi-modal information in DOT reconstruction with the two systems.

The adaptive finite element method (AFEM) is an effective way to retain enough resolution in selected regions while improving computational efficiency for reconstruction in fluorescent molecular tomography (FMT). In addition, background optical properties acquired by diffuse optical tomography (DOT) will improve the quality of reconstructed images. In this work, a DOT-guided adaptive reconstruction method (DGARM) is proposed, in which DOT is introduced into an adaptive reconstruction framework of FMT. Besides being used as functional a priori information in the forward modeling, the reconstructed local absorption coefficients in DOT are also used to form internal structural a priori information, which is further used to identify regions of interest (ROIs) in the mesh refinement of the adaptive procedure. Because optical properties are recovered before the formulation of FMT, a linear relationship is established between the fluorescent field and boundary measurements. We implemented numerical simulations and physical experiments to evaluate the performance of the algorithm. Compared with the strategies of uniform meshing with DOT and AFEM without DOT, DGAM improves localization accuracy of the reconstruction of fluorescence inclusion.

A region-based approach of image reconstruction using the finite element method is developed for diffuse optical tomography (DOT). The method is based on the framework of the pixel-based DOT methodology and on an assumption that different anatomical regions have their respective sets of the homogeneous optical properties distributions. With this hypothesis, the region-based DOT solution greatly improves the ill-posedness of the inverse problem by reducing the number of unknowns to be reconstructed. The experimental validation of the methodology is performed on a solid phantom employing a multi-channel DOT system of lock-in photon-counting mode, as well as compared with the traditional pixel-based reconstruction results, demonstrate that the proposed DOT methodology presents a promising tool of in vivo reconstructing background optical structures with the aid of anatomical a priori . Key words: Diffuse optical tomography, Region-based reconstruction, Pixel-based reconstruction, Optical properties.

Convergence rate calculation of simultaneous iterative reconstruction technique algorithm for diffuse optical tomography image reconstruction: A feasibility study

Background: Optical-based imaging modalities play an important role in assessing breast tissue composition by measuring optical property contrast from endogenous chromophores. The advantages of optical techniques are the use of non-ionizing radiation, ease of use, and relatively low cost. The primary objective of this study is to examine changes in optically derived parameters (i.e., deoxy-hemoglobin concentration, ctHHb) from different breast cancer subtypes under neoadjuvant chemotherapy (NAC), and correlate with tumor pathologic complete response (pCR). Methods: This retrospective study evaluated 89 tumors in total divided into three distinct subtypes: HR+/HER2- (n=34), HER2+ (n=27), and TNBC (n=28). All patients were imaged at baseline, before starting NAC (TP0), and two weeks after receiving one cycle of taxane-based chemotherapy (TP1). HER2+ breast cancer patients also received HER2-target therapy. pCR was defined as complete absence of invasive carcinoma in the breast and lymph node(s) (ypT0/is ypN0 Mx) at the time of surgery. Whole breast volume was imaged by a diffuse optical tomography breast imaging system (DOTBIS) using low-intensity near-infrared light. ctHHb tumor volume concentration was normalized by the non-affected health tissue ctHHb mean value (ctHHbN). For each molecular subgroup, we conducted an independent-samples t-test to determine if there was a difference in ctHHbN levels at TP1 compared to TP0 between patients with a pCR and non-pCR. Significance was assumed at a confidence interval of 95% (α = 0.05). Results: In total, 69 patients were imaged with DOTIBS at both time points, TP0 and TP1. HR+/HER2-, TNBC and HER2+ accounted for 32% (n=23), 37% (n=22) and 30% (n=22), respectively. The ratio between ctHHbN levels measured at TP1 and TP0 was statistically significantly lower in the pCR group than non-pCR for the HER2+ and HR+/HER2- molecular subgroups, Table 1. Conclusion: Aligned to the current practices in breast cancer management based on the characterization of breast cancer subtypes, our work evaluated changes in DOTBIS optically derived features and pCR status for different subtypes. We observed that ctHHbN levels change after two weeks of NAC and these changes are modifiable according to pCR status and are dependent on immunophenotype. Table 1.Ratio between ctHHbN levels measured at TP1 and TP0 between pCR and non-pCR according to different molecular subtypes.Molecular SubtypepCR (mean ± SD )non-pCR (mean ± SD )p-valueHR+/HER2- (n=23)0.77 ± 0.22 (n=6)1.14 ± 0.24 (n=17).01HER2+ (n=24)0.74 ± 0.30 (n=15)1.54 ± 0.98 (n=9).04TNBC (n=22)0.96 ± 0.38 (n=4)1.29 ± 0.37 (n=18).18Bold values indicate statistical significance at p<.05 level. Citation Format: Mirella L Altoe, Kevin M Kalinsky, Hua Guo, Hanina Hibshoosh, Mariella Tejada, Katherine D Crew, Melissa K Accordino, Meghna S Trivedi, Alessandro Marone, Hyun K Kim, Andreas H Hielscher, Dawn L Hershman. Prediction of breast cancer response to neoadjuvant chemotherapy in different biological breast cancer subtypes using diffuse optical tomography [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-02-04.

Screening X-ray mammography is limited by false positives and negatives leading to unnecessary physical and psychological morbidity. Diffuse Optical Imaging using harmless near infra red light, provides lesion detection based on functional abnormalities and represents a novel diagnostic arm that could complement traditional mammography. Reviews of optical breast imaging have not been systematic, are focused mainly on technological developments, and have become superseded by rapid technological advancement. The aim of this study is to review clinically orientated studies involving approximately 2,000 women in whom optical mammography has been used to evaluate the healthy or diseased breast. The results suggest that approximately 85% of breast lesions are detectable on optical mammography. Spectroscopic resolution of tissue haemoglobin composition and oxygen saturation may improve the detectability of breast diseases. Results suggest that breast lesions contain approximately twice the haemoglobin concentration of background tissue. Current evidence suggests that it is not possible to distinguish benign from malignant disease using optical imaging techniques in isolation. Methods to improve the performance of Diffuse Optical Imaging, such as better spectral coverage with additional wavelengths, improved modelling of light transport in tissues and the use of extrinsic dyes may augment lesion detection and characterisation. Future research should involve large clinical trials to determine the overall sensitivity and specificity of optical imaging techniques as well as to establish patient satisfaction and economic viability.

Diffuse optical imaging (DOI) is a label-free, safe, inexpensive, and quantitative imaging modality that provides metabolic and molecular contrast in tissue using visible or near-infrared light. DOI modalities can image up to several centimeters deep in tissue, providing access to a wide range of human tissues and organ sites. DOI technologies have benefitted from several decades of academic research, which has provided a variety of platforms that prioritize imaging depth, resolution, field-of-view, spectral content, and other application-specific criteria. Until recently, however, acquisition and processing speeds have represented a stubborn barrier to further clinical exploration and implementation. Over the last several years, advances in high-speed data acquisition enabled by high-speed digital electronics, newly available sources and detectors, and innovative new scanning methods have led to major improvements in DOI rates. These advances are now being coupled with new data processing algorithms that utilize deep learning and other computationally efficient methods to provide rapid or real-time feedback in the clinic. Together, these improvements have the potential to help advance DOI technologies to the point where major impacts can be made in clinical care. Here, we review recent advances in acquisition and processing speed for several important DOI modalities.

We recently applied time domain near infrared diffuse optical spectroscopy (TD-NIRS) to monitor hemodynamics of the cardiac wall (oxy and desoxyhemoglobin concentration, saturation, oedema) on anesthetized swine models. Published results prove that NIRS signal can provide information on myocardial hemodynamic parameters not obtainable with conventional diagnostic clinical tools.1 Nevertheless, the high cost of equipment, acquisition length, sensitivity to ambient light are factors limiting its clinical adoption. This paper introduces a novel approach, based on the use of wavelength and code division multiplexing, applicable to TD-NIRS as well as diffuse optical imaging systems (both topography and tomography); the approach, called WS-CDM (wavelength and space code division mltiplexing), essentially consists of a double stage intensity modulation of multiwavelength CW laser sources using orthogonal codes and their parallel correlation-based decoding after propagation in the tissue; it promises better signal to noise ratio (SNR), higher acquisition speed, robustness to ambient light and lower costs compared to both the conventional systems and the more recent spread spectrum approach based on single modulation with pseudo-random bit sequences (PRBS).2 Parallel acquisition of several wavelengths and from several locations is achievable. TD-NIRS experimental results guided Matlab-based simulations aimed at correlating different coding sequences, lengths, spectrum spreading factor, with the WS-CDM performances on such tissues (achievable SNR, acquisition and reconstruction speed, robustness to channel inequalization, ...). Simulations results and preliminary experimental validation confirm the significant improvements that WS-CDM could bring to diffuse optical imaging (not limited to cardiac functional imaging).

There are different studies that allow detecting the presence of cancer cells in a patient; however, the time it takes to obtain a correct diagnosis is critical for these cases. This work presents the design and construction of a prototype as first approach for a microtomograph based on Diffuse Optical Tomography (DOT). Diffused Optical Tomography is a technique that uses light from the Near Infrared Region (NIR) to measure tissue’s optical properties that has become relevant for the medical field due to it being a non-invasive technique. The main goal of this device is to be able to detect and analyze cancerous tumors by measuring diffuse photon densities in turbid media. As a first phase of the development, this project integrates an image acquisition mechanism, an image processing interface at software level developed with Blender to exploit a GPU architecture to optimize the execution time.

Near infrared (NIR) diffused optical tomography (DOT) is emerging as a potential tool of non-invasively diagnosing woman breast cancers, neonatal brain hypoxia, and other human organ diseases. The intensive and worldwide investigations in theory and experiment have revealed the possibility of NIR DOT in providing both anatomical and functional information of biological tissue simultaneously, which is important for distinguishing between healthy and diseased tissues, such as benign and malignant tumors. In this paper, our recent DOT experiments on human lower legs and forearms are presented using our time-resolved measuring system and image reconstruction algorithm based on the modified generalized pulse spectrum technique. It was found that the image quality in the experiments, including both the spatial resolution and the quantitativeness of the targets, was rather poor, and the interior blood vessels undisclosed in the absorption images. To clarify this issue, the influences of target contrast and size on the image reconstruction were investigated with simulated data. We have accordingly obtained the following observations: the quantitativeness of the reconstructed optical properties was prone to be spoiled by the small size ratio and high contrast of the interior targets (such as blood vessels) to the background, and the incompleteness of information embedded in the featured data-types, in addition to the experimental noise, evidently answers for the degradation of the spatial resolution and quantitativeness. It was shown in a further simulative investigation that the image quality could be substantially improved by making full use of the time-resolved data.

The important advantage of diffuse optical tomography (DOT) is the possibility of tissue functional diagnosis. However the possibility implements if only we separately reconstruct the spatial distributions of optical parameters, specifically the absorption and scattering coefficients. We have recently demonstrated that time-domain DOT based on the perturbation model by Lyubimov is capable of reconstructing absorbing inhomogeneities in tissue with a DOT high spatial resolution (better than 3 mm at a depth of 4 cm). This paper continues our research and focuses on the reconstruction of scattering inhomogeneities. We consider the flat layer transmission geometry which is traditional for optical mammography, and use diffusion approximation to derive analytical expressions for weight functions responsible for the reconstruction of scattering inhomogeneities. To confirm that our calculations are correct we perform a numerical experiment where we reconstruct a rectangular scattering object 10×8 cm in size with 4 circular scattering macroinhomogeneities 4 mm in diameter each, and a randomly inhomogeneous scattering structure. The inverse DOT problem is solved with a multiplicative algebraic reconstruction technique where interim iterations are processed through total variation norm minimization. The results suggest that our DOT method reliably resolves the scattering macroinhomogeneities of mentioned size against a randomly inhomogeneous structure.