SignificanceStandardization of fluorescence molecular imaging (FMI) is critical for ensuring quality control in guiding surgical procedures. To accurately evaluate system performance, two metrics, the signal-to-noise ratio (SNR) and contrast, are widely employed. However, there is currently no consensus on how these metrics can be computed.AimWe aim to examine the impact of SNR and contrast definitions on the performance assessment of FMI systems.ApproachWe quantified the SNR and contrast of six near-infrared FMI systems by imaging a multi-parametric phantom. Based on approaches commonly used in the literature, we quantified seven SNRs and four contrast values considering different background regions and/or formulas. Then, we calculated benchmarking (BM) scores and respective rank values for each system.ResultsWe show that the performance assessment of an FMI system changes depending on the background locations and the applied quantification method. For a single system, the different metrics can vary up to ∼35 dB (SNR), ∼8.65 a.u. (contrast), and ∼0.67 a.u. (BM score).ConclusionsThe definition of precise guidelines for FMI performance assessment is imperative to ensure successful clinical translation of the technology. Such guidelines can also enable quality control for the already clinically approved indocyanine green-based fluorescence image-guided surgery.
SignificanceIntravascular near-infrared fluorescence (NIRF) imaging aims to improve the inspection of vascular pathology using fluorescent agents with specificity to vascular disease biomarkers. The method has been developed to operate in tandem with an anatomical modality, such as intravascular ultrasound (IVUS), and complements anatomical readings with pathophysiological contrast, enhancing the information obtained from the hybrid examination.AimHowever, attenuation of NIRF signals by blood challenges NIRF quantification. We propose a new method for attenuation correction in NIRF intravascular imaging based on a fluorophore-coated guidewire that is used as a reference for the fluorescence measurement and provides a real-time measurement of blood attenuation during the NIRF examination.ApproachWe examine the performance of the method in a porcine coronary artery ex vivo and phantoms using a 3.2F NIRF-IVUS catheter.ResultsWe demonstrate marked improvement over uncorrected signals of up to 4.5-fold and errors of <11 % for target signals acquired at distances up to 1 mm from the catheter system employed.ConclusionsThe method offers a potential means of improving the accuracy of intravascular NIRF imaging under in vivo conditions.
Significance: Near-infrared fluorescence molecular endoscopy (NIR-FME) is an innovative technique allowing for in vivo visualization of molecular processes in hollow organs. Despite its potential for clinical translation, NIR-FME still faces challenges, for example, the lack of consensus in performing quality control and standardization of procedures and systems. This may hamper the clinical approval of the technology by authorities and its acceptance by endoscopists. Until now, several clinical trials using NIR-FME have been performed. However, most of these trials had different study designs, making comparison difficult.
Aim: We describe the need for standardization in NIR-FME, provide a pathway for setting up a standardized clinical study, and describe future perspectives for NIR-FME.
Body: Standardization is challenging due to many parameters. Invariable parameters refer to the hardware specifications. Variable parameters refer to movement or tissue optical properties. Phantoms can be of aid when defining the influence of these variables or when standardizing a procedure.
Conclusion: There is a need for standardization in NIR-FME and hurdles still need to be overcome before a widespread clinical implementation of NIR-FME can be realized. When these hurdles are overcome, clinical outcomes can be compared and systems can be benchmarked, enabling clinical implementation.
CR760, a croconaine dye with excellent optical properties, was synthesized in a single step and subsequently nano-formulated for optoacoustic imaging and photothermal therapy of cancer.
The capability to increase the robustness to scattering has become a crucial request for communication protocols and imaging systems. Here we perform a complete analysis regarding the spatial features and the polarization of structured beams propagating in different scattering media. We observe different behaviors for structured light scattered by a solution of polystyrene latex beads in water and by tissue-mimicking phantom. The reported study can help in establishing a framework for the application of structured light illumination in imaging and diagnostic.
Scattering phenomena affect light propagation through any kind of medium from free space to biological tissues. Finding appropriate strategies to increase the robustness to scattering is the common requirement in developing both communication protocols and imaging systems. Recently, structured light has attracted attention due to its seeming scattering resistance in terms of transmissivity and spatial behavior. Moreover, correlation between optical polarization and orbital angular momentum (OAM), which characterizes the so-called vector vortex beam (VVB) states, seems to allow for the preservation of the polarization pattern. We extend the analysis by investigating both the spatial features and the polarization structure of vectorial optical vortexes propagating in scattering media with different concentrations. Among the observed features, we find a sudden swift decrease in contrast ratio for Gaussian, OAM, and VVB modes for concentrations of the adopted scattering media exceeding 0.09%. Our analysis provides a more general and complete study on the propagation of structured light in dispersive and scattering media.
Significance: Expanded use of fluorescence-guided surgery with devices approved for use with indocyanine green (ICG) has led to a range of commercial systems available. There is a compelling need to be able to independently characterize system performance and allow for cross-system comparisons.
Aim: The goal of this work is to expand on previous proposed fluorescence imaging standard designs to develop a long-term stable phantom that spectrally matches ICG characteristics and utilizes 3D printing technology for incorporating tissue-equivalent materials.
Approach: A batch of test targets was created to assess ICG concentration sensitivity in the 0.3- to 1000-nM range, tissue-equivalent depth sensitivity down to 6 mm, and spatial resolution with a USAF test chart. Comparisons were completed with a range of systems that have significantly different imaging capabilities and applications, including the Li-Cor® Odyssey, Li-Cor® Pearl, PerkinElmer® Solaris, and Stryker® Spy Elite.
Results: Imaging of the ICG-matching phantoms with all four commercially available systems showed the ability to benchmark system performance and allow for cross-system comparisons. The fluorescence tests were able to assess differences in the detectable concentrations of ICG with sensitivity differences >10× for preclinical and clinical systems. Furthermore, the tests successfully assessed system differences in the depth-signal decay rate, as well as resolution performance and image artifacts. The manufacturing variations, photostability, and mechanical design of the tests showed promise in providing long-term stable standards for fluorescence imaging.
Conclusions: The presented ICG-matching phantom provides a major step toward standardizing performance characterization and cross-system comparisons for devices approved for use with ICG. The developed hybrid manufacturing platform can incorporate long-term stable fluorescing agents with 3D printed tissue-equivalent material. Further, long-term testing of the phantom and refinements to the manufacturing process are necessary for future implementation as a widely adopted fluorescence imaging standard.
Fluorescence imaging for surgical guidance is a proven modality that allows for visualization of fluorescent markers in numerous biological imaging applications. As the field continues to develop there is an urgent need for fluorescence-imaging standards that enable system characterization and performance monitoring. Here, we present a long-term stable standard that mimics indocynine green (ICG) spectral behavior and is capable of probing the sensitivity of commercially available imaging systems. The standard is composed of three different tests: a varying concentration sensitivity test (0.1nM-3000nM), a tissue-equivalent-depth sensitivity test (0.2mm-7mm), and a 1951 USFA fluorescence resolution test. The fluorescence standard platform developed can incorporate 3-D printing with tissue-equivalent layers, enabling a wide variety of anatomical-specific designs. The manufacturing capabilities developed allow for incorporation of different fluorophores for applications beyond ICG and NIR.
Fluorescence-guided intervention is increasingly considered for real-time intra-operative oncological applications. Herein we propose a novel composite phantom for standardization and quality control, which could serve as a framework toward good clinical practices.
A critical issue associated with the clinical translation of fluorescence molecular imaging relates to the reproducibility of the collected measurements. In particular, images acquired from the same target using different fluorescence cameras may vary considerably when the employed systems have markedly different specifications. Methods that standardize fluorescence imaging are therefore becoming necessary for assessing the performance of fluorescence systems and agents and for providing a reference to the data collected. In the work presented herein we propose a composite phantom for integrating multiple targets within the field of view of a fluorescence camera. Each quadrant of this phantom resolves different fluorescence features: (1) sensitivity as a function of the optical properties; (2) sensitivity as a function of the depth from the top surface; (3) resolution of the fluorescence and optical imaging; and (4) cross-talk from the excitation light. In addition, there exist structures in the phantom for assessing homogeneity of the incident illumination. In order to validate our main hypothesis that standardization of fluorescence imaging systems is feasible through imaging such a phantom, we employed two systems of different specifications and quantified all relevant performance metrics. The derived results showcase the feasibility of fluorescence cameras calibration. Additionally, we demonstrate a methodology of comparing fluorescence cameras by means of benchmarking scoring. We expect that such approaches will boost the clinical translation of fluorescence molecular imaging and will allow for the investigation of novel fluorescence agents.
To extend sensitivity field for effective optoacoustic imaging, a novel concept of a non-mechanical point spread function (PSF) adjustment is proposed. Method was validated on phantoms and showed to be useful for distance-adaptive imaging.
Despite recent advances in fluorescence imaging, standardization of systems remains an unmet need. We developed a new comprehensive phantom that resolves multiple system parameters simultaneously and could be used for system performance comparison.
Lack of standardization in fluorescence imaging challenges its clinical translation. We investigate the use of a composite phantom to perform standardization, which could serve as a framework toward the benchmarking of fluorescence imaging systems.
The current standard of care for early stages of breast cancer is breast-conserving surgery (BCS). BCS involves a lumpectomy procedure, during which the tumor is removed with a rim of normal tissue-if cancer cells found in that rim of tissue, it is called a positive margin and means part of the tumor remains in the breast. Currently there is no method to determine if cancer cells exist at the margins of lumpectomy specimens aside from time-intensive histology methods that result in reoperations in up to 38% of cases. We used fluorescence lifetime imaging (FLIm) to measure time-resolved autofluorescence from N=13 ex vivo human breast cancer specimens (N=10 patients undergoing lumpectomy or mastectomy) and compared our results to histology. Tumor (both invasive and ductal carcinoma in situ), fibrous tissue, fat and fat necrosis have unique fluorescence signatures. For instance, between 500-580 nm, fluorescence lifetime of tumor was shortest (4.7 ± 0.4 ns) compared to fibrous tissue (5.5 ± 0.7 ns) and fat (7.0 ± 0.1 ns), P<0.05 (ANOVA). These differences are due to the biochemical properties of lipid, nicotineamide adenine dinucleotide (NADH) and collagen fibers in the fat, tumor and fibrous tissue, respectively. Additionally, the FLIm data is augmented to video of the breast tissue with image processing algorithms that track a blue (450 nm) aiming beam used in parallel with the 355 nm excitation beam. This allows for accurate histologic co-registration and in the future will allow for three-dimensional lumpectomy surfaces to be imaged for cancer margin delineation.
Autofluorescence lifetime spectroscopy is a promising non-invasive label-free tool for characterization of biological tissues and shows potential to report structural and biochemical alterations in tissue owing to pathological transformations. In particular, when combined with fiber-optic based instruments, autofluorescence lifetime measurements can enhance intraoperative diagnosis and provide guidance in surgical procedures. We investigate the potential of a fiber-optic based multi-spectral time-resolved fluorescence spectroscopy instrument to characterize the autofluorescence fingerprint associated with histologic, morphologic and metabolic changes in tissue that can provide real-time contrast between healthy and tumor regions in vivo and guide clinicians during resection of diseased areas during transoral robotic surgery. To provide immediate feedback to the surgeons, we employ tracking of an aiming beam that co-registers our point measurements with the robot camera images and allows visualization of the surgical area augmented with autofluorescence lifetime data in the surgeon’s console in real-time. For each patient, autofluorescence lifetime measurements were acquired from normal, diseased and surgically altered tissue, both in vivo (pre- and post-resection) and ex vivo. Initial results indicate tumor and normal regions can be distinguished based on changes in lifetime parameters measured in vivo, when the tumor is located superficially. In particular, results show that autofluorescence lifetime of tumor is shorter than that of normal tissue (p < 0.05, n = 3). If clinical diagnostic efficacy is demonstrated throughout this on-going study, we believe that this method has the potential to become a valuable tool for real-time intraoperative diagnosis and guidance during transoral robot assisted cancer removal interventions.
Fluorescence molecular imaging (FMI) has shown potential to detect and delineate cancer during surgery or diagnostic endoscopy. Recent progress on imaging systems has allowed sensitive detection of fluorescent agents even in video rate mode. However, lack of standardization in fluorescence imaging challenges the clinical application of FMI, since the use of different systems may lead to different results from a given study, even when using the same fluorescent agent. In this work, we investigate the use of a composite fluorescence phantom, employed as an FMI standard, to offer a comprehensive method for validation and standardization of the performance of different imaging systems. To exclude user interaction, all phantom features are automatically extracted from the acquired epi-illumination color and fluorescence images, using appropriately constructed templates. These features are then employed to characterize the performance and compare different cameras to each other. The proposed method could serve as a framework toward the calibration and benchmarking of FMI systems, to facilitate their clinical translation.
Fluorescence imaging has been considered for over a half-century as a modality that could assist surgical guidance and visualization. The administration of fluorescent molecules with sensitivity to disease biomarkers and their imaging using a fluorescence camera can outline pathophysiological parameters of tissue invisible to the human eye during operation. The advent of fluorescent agents that target specific cellular responses and molecular pathways of disease has facilitated the intraoperative identification of cancer with improved sensitivity and specificity over nonspecific fluorescent dyes that only outline the vascular system and enhanced permeability effects. With these new abilities come unique requirements for developing phantoms to calibrate imaging systems and algorithms. We briefly review herein progress with fluorescence phantoms employed to validate fluorescence imaging systems and results. We identify current limitations and discuss the level of phantom complexity that may be required for developing a universal strategy for fluorescence imaging calibration. Finally, we present a phantom design that could be used as a tool for interlaboratory system performance evaluation.
KEYWORDS: Fluorescence lifetime imaging, Data modeling, Data acquisition, Classification systems, Tissues, Clinical research, Animal model studies, Library classification systems, Diagnostics, Current controlled current source
The progression of atherosclerosis in coronary vessels involves distinct pathological changes in the vessel wall. These changes manifest in the formation of a variety of plaque sub-types. The ability to detect and distinguish these plaques, especially thin-cap fibroatheromas (TCFA) may be relevant for guiding percutaneous coronary intervention as well as investigating new therapeutics. In this work we demonstrate the ability of fluorescence lifetime imaging (FLIm) derived parameters (lifetime values from sub-bands 390/40 nm, 452/45 nm and 542/50 nm respectively) for generating classification maps for identifying eight different atherosclerotic plaque sub-types in ex vivo human coronary vessels. The classification was performed using a support vector machine based classifier that was built from data gathered from sixteen coronary vessels in a previous study. This classifier was validated in the current study using an independent set of FLIm data acquired from four additional coronary vessels with a new rotational FLIm system. Classification maps were compared to co-registered histological data. Results show that the classification maps allow identification of the eight different plaque sub-types despite the fact that new data was gathered with a different FLIm system. Regions with diffuse intimal thickening (n=10), fibrotic tissue (n=2) and thick-cap fibroatheroma (n=1) were correctly identified on the classification map. The ability to identify different plaque types using FLIm data alone may serve as a powerful clinical and research tool for studying atherosclerosis in animal models as well as in humans.
Fluorescence lifetime imaging has been shown to be a robust technique for biochemical and functional characterization
of tissues and to present great potential for intraoperative tissue diagnosis and guidance of surgical procedures. We
report a technique for real-time mapping of fluorescence parameters (i.e. lifetime values) onto the location from where
the fluorescence measurements were taken. This is achieved by merging a 450 nm aiming beam generated by a diode
laser with the excitation light in a single delivery/collection fiber and by continuously imaging the region of interest with
a color CMOS camera. The interrogated locations are then extracted from the acquired frames via color-based
segmentation of the aiming beam. Assuming a Gaussian profile of the imaged aiming beam, the segmentation results are
fitted to ellipses that are dynamically scaled at the full width of three automatically estimated thresholds (50%, 75%,
90%) of the Gaussian distribution's maximum value. This enables the dynamic augmentation of the white-light video
frames with the corresponding fluorescence decay parameters. A fluorescence phantom and fresh tissue samples were
used to evaluate this method with motorized and hand-held scanning measurements. At 640x512 pixels resolution the
area of interest augmented with fluorescence decay parameters can be imaged at an average 34 frames per second. The
developed method has the potential to become a valuable tool for real-time display of optical spectroscopy data during
continuous scanning applications that subsequently can be used for tissue characterization and diagnosis.
During breast conserving surgery (BCS), which is the preferred approach to treat most early stage breast cancers, the
surgeon attempts to excise the tumor volume, surrounded by thin margin of normal tissue. The intra-operative
assessment of cancerous areas is a challenging procedure, with the surgeon usually relying on visual or tactile guidance.
This study evaluates whether time-resolved fluorescence spectroscopy (TRFS) presents the potential to address this
problem. Point TRFS measurements were obtained from 19 fresh tissue slices (7 patients) and parameters that
characterize the transient signals were quantified via constrained least squares deconvolution scheme. Fibrotic tissue
(FT, n=69), adipose tissue (AT, n=76), and invasive ductal carcinoma (IDC, n=27) were identified in histology and
univariate statistical analysis, followed by multi-comparison test, was applied to the corresponding lifetime data.
Significant differentiation between the three tissue types exists at 390 nm and 500 nm bands. The average lifetime is
3.23±0.74 ns for AT, 4.21±0.83 ns for FT and 4.71±0.35 ns (p<0.05) for IDC at 390 nm. Due to the smaller contribution
of collagen in AT the average lifetime value is different from FT and IDC. Additionally, although intensity
measurements do not show difference between FT and IDC, lifetime can distinguish them. Similarly, in 500 nm these
values are 7.01±1.08 ns, 5.43±1.05 ns and 4.39±0.88 ns correspondingly (p<0.05) and this contrast is due to
differentiation in retinol or flavins relative concentration, mostly contributing to AT. Results demonstrate the potential of
TRFS to intra-operatively characterize BCS breast excised tissue in real-time and assess tumor margins.
We report a scanning imaging system that enables high speed multispectral fluorescence lifetime imaging (FLIm) of
coronary arteries. This system combines a custom low profile (3 Fr) imaging catheter using a 200 μm core side viewing
UV-grade silica fiber optic, an acquisition system able to measure fluorescence decays over four spectral bands at 20
kHz and a fast data analysis and display module. In vivo use of the system has been optimized, with particular emphasis
on clearing blood from the optical pathway. A short acquisition time (5 seconds for a 20 mm long coronary segment)
enabled data acquisition during a bolus saline solution injection through the 7 Fr catheter guide. The injection parameters
were precisely controlled using a power injector and optimized to provide good image quality while limiting the bolus
injection duration and volume (12 cc/s, 80 cc total volume). The ability of the system to acquire data in vivo was
validated in healthy swine by imaging different sections of the left anterior descending (LAD) coronary. A stent coated
with fluorescent markers was placed in the LAD and imaged, demonstrating the ability of the system to discriminate in
vivo different fluorescent features and structures from the vessel background fluorescence using spectral and lifetime
information. Intensity en face images over the four bands of the instrument were available within seconds whereas
lifetime images were computed in 2 minutes, providing efficient feedback during the procedure. This successful
demonstration of FLIm in coronaries enables future study of atherosclerotic cardiovascular diseases.
We report the development and validation of a hybrid intravascular diagnostic system combining multispectral fluorescence lifetime imaging (FLIm) and intravascular ultrasound (IVUS) for cardiovascular imaging applications. A prototype FLIm system based on fluorescence pulse sampling technique providing information on artery biochemical composition was integrated with a commercial IVUS system providing information on artery morphology. A customized 3-Fr bimodal catheter combining a rotational side-view fiberoptic and a 40-MHz IVUS transducer was constructed for sequential helical scanning (rotation and pullback) of tubular structures. Validation of this bimodal approach was conducted in pig heart coronary arteries. Spatial resolution, fluorescence detection efficiency, pulse broadening effect, and lifetime measurement variability of the FLIm system were systematically evaluated. Current results show that this system is capable of temporarily resolving the fluorescence emission simultaneously in multiple spectral channels in a single pullback sequence. Accurate measurements of fluorescence decay characteristics from arterial segments can be obtained rapidly (e.g., 20 mm in 5 s), and accurate co-registration of fluorescence and ultrasound features can be achieved. The current finding demonstrates the compatibility of FLIm instrumentation with in vivo clinical investigations and its potential to complement conventional IVUS during catheterization procedures.
The risk of atherosclerosis plaque rupture cannot be assessed by the current imaging systems and thus new multi-modal
technologies are under investigation. This includes combining a new fluorescence lifetime imaging (FLIm) technique,
which is sensitive to plaque biochemical features, with conventional intravascular ultrasound (IVUS), which provides
information on plaque morphology. In this study we present an automated method allowing for the co-registration of
imaging data acquired based on these two techniques. Intraluminal studies were conducted in ex-vivo segments of human
coronaries with a multimodal catheter integrating a commercial IVUS (40 MHz) and a rotational side-viewing fiber
based multispectral FLIm system (355 nm excitation, 390±20, 452±22 and 542±25 nm acquisition wavelengths). The proposed method relies on the lumen/intima boundary extraction from the IVUS polar images. Image restoration is applied for the noise reduction and edge enhancement, while gray-scale peak tracing over the A-lines of the IVUS polar images is applied for the lumen boundary extraction. The detection of the guide-wire artifact is used for the angular
registration between FLIm and IVUS data, after which the lifetime values can be mapped onto the segmented
lumen/intima interface. The segmentation accuracy has been assessed against manual tracings, providing 0.120±0.054
mm mean Hausdorff distance. This method makes the bi-modal FLIm and IVUS approach feasible for comprehensive
intravascular diagnostic by providing co-registered biochemical and morphological information about atherosclerotic
plaques.
In this work a miniature photometric stereo system is presented, targeting the three-dimensional structural reconstruction of various fabric types. This is a supportive module to a robot system, attempting to solve the well known “laundry problem”. The miniature device has been designed for mounting onto the robot gripper. It is composed of a low-cost off-the-shelf camera, operating in macro mode, and eight light emitting diodes. The synchronization between image acquisition and lighting direction is controlled by an Arduino Nano board and software triggering. The ambient light has been addressed by a cylindrical enclosure. The direction of illumination is recovered by locating the reflection or the brightest point on a mirror sphere, while a flatfielding process compensates for the non-uniform illumination. For the evaluation of this prototype, the classical photometric stereo methodology has been used. The preliminary results on a large number of textiles are very promising for the successful integration of the miniature module to the robot system. The required interaction with the robot is implemented through the estimation of the Brenner’s focus measure. This metric successfully assesses the focus quality with reduced time requirements in comparison to other well accepted focus metrics. Besides the targeting application, the small size of the developed system makes it a very promising candidate for applications with space restrictions, like the quality control in industrial production lines or object recognition based on structural information and in applications where easiness in operation and light-weight are required, like those in the Biomedical field, and especially in dermatology.
KEYWORDS: Radiative transfer, Diffusion, Monte Carlo methods, Luminescence, 3D modeling, Molecular imaging, Chemical elements, Phase shifts, Modulation, Optical properties
The solution of the forward problem in fluorescence molecular imaging strongly influences the successful convergence of the fluorophore reconstruction. The most common approach to meeting this problem has been to apply the diffusion approximation. However, this model is a first-order angular approximation of the radiative transfer equation, and thus is subject to some well-known limitations. This manuscript proposes a methodology that confronts these limitations by applying the radiative transfer equation in spatial regions in which the diffusion approximation gives decreased accuracy. The explicit integro differential equations that formulate this model were solved by applying the Galerkin finite element approximation. The required spatial discretization of the investigated domain was implemented through the Delaunay triangulation, while the azimuthal discretization scheme was used for the angular space. This model has been evaluated on two simulation geometries and the results were compared with results from an independent Monte Carlo method and the radiative transfer equation by calculating the absolute values of the relative errors between these models. The results show that the proposed forward solver can approximate the radiative transfer equation and the Monte Carlo method with better than 95% accuracy, while the accuracy of the diffusion approximation is approximately 10% lower.
Most of the reported fluorescence imaging methods and systems highlight the need for three-dimensional information of
the inspected region surface geometry. The scope of this manuscript is to introduce an epi-illumination fluorescence
imaging system, which has been enhanced with a binocular machine vision system for the translation of the inverse
problem solution to the global coordinates system. The epi-illumination fluorescence imaging system is consisted of a
structured scanning excitation source, which increases the spatial differentiation of the measured data, and a telecentric
lens, which increases the angular differentiation. On the other hand, the binocular system is based on the projection of a
structured light pattern on the inspected area, for the solution of the correspondence problem between the stereo pair. The
functionality of the system has been evaluated on tissue phantoms and calibration objects. The reconstruction accuracy
of the fluorophores distribution, as resulted from the root mean square error between the actual distribution and the
outcome of the forward solver, was more than 80%. On the other hand, the surface three-dimensional reconstruction of
the inspected region presented 0.067±0.004 mm accuracy, as resulted from the mean Euclidean distance between the
three-dimensional position of the real world points and those reconstructed.
The solution of the forward problem in fluorescence molecular imaging is among the most important premises for the
successful confrontation of the inverse reconstruction problem. To date, the most typical approach has been the
application of the diffusion approximation as the forward model. This model is basically a first order angular
approximation for the radiative transfer equation, and thus it presents certain limitations. The scope of this manuscript is
to present the dual coupled radiative transfer equation and diffusion approximation model for the solution of the forward
problem in fluorescence molecular imaging. The integro-differential equations of its weak formalism were solved via the
finite elements method. Algorithmic blocks with cubature rules and analytical solutions of the multiple integrals have
been constructed for the solution. Furthermore, specialized mapping matrices have been developed to assembly the finite
elements matrix. As a radiative transfer equation based model, the integration over the angular discretization was
implemented analytically, while quadrature rules were applied whenever required. Finally, this model was evaluated on
numerous virtual phantoms and its relative accuracy, with respect to the radiative transfer equation, was over 95%, when
the widely applied diffusion approximation presented almost 85% corresponding relative accuracy for the fluorescence
emission.
Prostate cancer is a common disease among men with an increasing number of incidences during the last three decades.
Histopathological grading of prostate cancer is based on tissue structural abnormalities. Gleason grading system is the
gold standard and is based on the organization features of prostatic glands. However, till now there is an uncertainty
assign Gleason grade to intermediate stages of the disease, Gleason 3 and Gleason 4. The aim of this study was to
explore the possibility of introducing fluorescent probes in this prostate cancer Gleason grading problem. Propidium
Iodide with cellular nuclei binding pattern and Alexa 488-WGA with selectivity in polysaccharides with sialic acid
residues were finally chosen. Their localisation patterns were assessed using confocal microscopy. Their colocalisation
degree was quantified using special developed algorithms of image processing and analysis. The introduced metrics of
colocalisation were successfully used to correct classify samples in Gleason 3 and Gleason 4 grades. These metrics were
found appropriate to correctly classify 93.10 % of the images into the two classes using the logistic algorithm. The
integration of confocal microscopy along with fluorescent probes to pathologist routine, is an approach that cloud lead to
prognostic advances.
One of the major challenges in biomedical imaging is the extraction of quantified information from the acquired images.
Light and tissue interaction leads to the acquisition of images that present inconsistent intensity profiles and thus the
accurate identification of the regions of interest is a rather complicated process. On the other hand, the complex
geometries and the tangent objects that very often are present in the acquired images, lead to either false detections or to
the merging, shrinkage or expansion of the regions of interest. In this paper an algorithm, which is based on alternating
sequential filtering and watershed transformation, is proposed for the segmentation of biomedical images. This algorithm
has been tested over two applications, each one based on different acquisition system, and the results illustrate its
accuracy in segmenting the regions of interest.
Although fluorescence imaging has been applied in tumour diagnosis from the early 90s, just the last few years it has met
an increasing scientific interest due to the advances in the biophotonics field and the combined technological progress of
the acquisition and computational systems. In addition there are expectations that fluorescence imaging will be further
developed and applied in deep tumour diagnosis in the years to come. However, this evolving field of imaging sciences
has still to encounter important challenges. Among them is the expression of an accurate forward model for the solution
of the reconstruction problem. The scope of this work is to introduce a three dimensional coupled radiative transfer and
diffusion approximation model, applicable on the fluorescence imaging. Furthermore, the solver incorporates the super-ellipsoid
models and sophisticated image processing algorithms to additionally provide a-priori estimation about the
fluorophores distribution, information that is very important for the solution of the inverse problem. Simulation
experiments have proven that the proposed methodology preserves the accuracy levels of the radiative transfer equation
and the time efficacy of the diffusion approximation, while in the same time shows extended success on the registration
between acquired and simulated images.
Images of high geometrical complexity are found in various applications in the fields of image processing and computer
vision. Medical imaging is such an application, where the processing of digitized images reveals vital information for the
therapeutic or diagnostic algorithms. However, the segmentation of these images has been proved to be one of the most
challenging topics in modern computer vision algorithms. The light interaction with tissues and the geometrical
complexity with the tangent objects are among the most common reasons that many segmentation techniques nowadays
are strictly related to specific applications and image acquisition protocols. In this paper a sophisticated segmentation
algorithm is introduced that succeeds into overcoming the application dependent accuracy levels. This algorithm is based
on morphological sequential filtering, combined with a watershed transformation. The results on various biomedical test
images present increased accuracy, which is independent of the image acquisition protocol. This method can provide
researchers with a valuable tool, which makes the classification or the follow-up faster, more accurate and objective.
One of the most challenging problems in medical imaging is to "see" a tumour embedded into tissue, which is a turbid
medium, by using fluorescent probes for tumour labeling. This problem, despite the efforts made during the last years,
has not been fully encountered yet, due to the non-linear nature of the inverse problem and the convergence failures of
many optimization techniques. This paper describes a robust solution of the inverse problem, based on data fitting and
image fine-tuning techniques. As a forward solver the coupled radiative transfer equation and diffusion approximation
model is proposed and compromised via a finite element method, enhanced with adaptive multi-grids for faster and more
accurate convergence. A database is constructed by application of the forward model on virtual tumours with known
geometry, and thus fluorophore distribution, embedded into simulated tissues. The fitting procedure produces the best
matching between the real and virtual data, and thus provides the initial estimation of the fluorophore distribution. Using
this information, the coupled radiative transfer equation and diffusion approximation model has the required initial
values for a computational reasonable and successful convergence during the image fine-tuning application.
Prostate cancer is a common malignancy among maturing men and the second leading cause of cancer death in USA.
Histopathological grading of prostate cancer is based on tissue structural abnormalities. Gleason grading system is the
gold standard and is based on the organization features of prostatic glands. Although Gleason score has contributed on
cancer prognosis and on treatment planning, its accuracy is about 58%, with this percentage to be lower in GG2, GG3
and GG5 grading. On the other hand it is strongly affected by "inter- and intra observer variations", making the whole
process very subjective. Therefore, there is need for the development of grading tools based on imaging and computer
vision techniques for a more accurate prostate cancer prognosis.
The aim of this paper is the development of a novel method for objective grading of biopsy specimen in order to support
histopathological prognosis of the tumor. This new method is based on texture analysis techniques, and particularly on
Gray Level Co-occurrence Matrix (GLCM) that estimates image properties related to second order statistics.
Histopathological images of prostate cancer, from Gleason grade2 to Gleason grade 5, were acquired and subjected to
image texture analysis. Thirteen texture characteristics were calculated from this matrix as they were proposed by
Haralick. Using stepwise variable selection, a subset of four characteristics were selected and used for the description
and classification of each image field. The selected characteristics profile was used for grading the specimen with the
multiparameter statistical method of multiple logistic discrimination analysis. The subset of these characteristics
provided 87% correct grading of the specimens. The addition of any of the remaining characteristics did not improve
significantly the diagnostic ability of the method. This study demonstrated that texture analysis techniques could provide
valuable grading decision support to the pathologists, concerning prostate cancer prognosis.
This paper describes the development of a novel gauging computer vision system for murine non-melanoma skin cancer
tumours volume imaging. The system utilized binocular stereovision, enhanced through the use of telecentric lenses.
These lenses optically compromised for the distortion factors and provided orthographic projection, leading to parallax
free image acquisition. In order to improve the resolution of the system, a structured light projector, with 450 nm
dominant wavelength, was used to illuminate the target with a custom pattern. Robust image processing algorithms
granted accurate segmentation, feature recognition, labeling and correlation between the stereo pairs. Under these
premises, the well-known "matching" problem was resolved successfully and geometrical interpolation provided an
accurate three-dimensional reconstruction of the tumour volume. Through back-projection of the calibration object the
resolution of the system was calculated up to 0.04 mm. The system was applied to measure the induced geometrical
alterations of the tumour after PDT by using the Fosgel photosensitizer, excited by a laser diode emitting at 652 nm. The
measurement of the volume induced alterations after each PDT treatment and up to the final tumour shrinkage is critical,
to compare PDT efficacy between different protocols.
Computer vision advancements have not till now achieved the accurate 3D reconstruction of objects smaller than 1cm diameter. Although this problem is of great importance in dermatology for Non Melanoma Skin Cancer diagnosis and therapy, has not yet been solved. This paper describes the development of a novel volumetric method for NMSC animal model tumors, using a binocular vision system. Monitoring NMSC tumors volume changes during PDT will grant important information for the assessment of the therapeutic progress and the efficiency of the applied drug. The vision system was designed taking into account the targets size and the flexibility. By using high resolution cameras with telecentric lenses most distortion factors were reduced significantly. Furthermore, z-axis movement was possible without requiring calibration, in contrary to wide angle lenses. The calibration was achieved by means of adapted photogrammetric technique. The required time for calibrating both cameras was less than a minute. For accuracy expansion, a structured light projector was used. The captured stereo-pair images were processed with modified morphological filters to improve background contrast and minimize noise. The determination of conjugate points was achieved via maximum correlation values and region properties, thus decreasing significantly the computational cost. The 3D reconstruction algorithm has been assessed with objects of known volumes and applied to animal model tumors with less than 0.6cm diameter. The achieved precision was at very high levels providing a standard deviation of 0.0313mm. The robustness of our system is based on the overall approach and on the size of the targets.
The scope of this work was to determine the Kubelka-Munk scattering and absorption coefficients of healthy and atherosclerotic animal model aorta, from 200 to 1100 nm. Furthermore, using the measured and calculated optical properties, special algorithms were developed in order to discriminate healthy from diseased aorta. Diffuse reflectance and total transmittance were measured via a dual beam diffuse reflectance spectrometer. Inverse Kubelka-Munk Model was applied to calculate the diffusion scattering and absorption coefficients. Diffuse absorption coefficients varied from ~200 cm-1 at 300 nm to ~3 cm-1 at 1100 nm. Kubelka-Munk scattering coefficients ranged from ~100 cm-1 at 200 nm to ~6 cm-1 at 1100 nm. Appropriate discrimination algorithms were developed in order to characterize a specimen as healthy or atherosclerotic. The first algorithm was based on the ratio of diffuse reflectance to the reflectance in infinity. The gradient of this ratio at 390 and 440 nm effectively separated healthy from atherosclerotic aorta. The discrimination between the two groups was succeeded using multivariate statistical analysis and verified by histopathology. The second discrimination algorithm was based on the ratio of diffuse reflectance to the baseline reflectance of each specimen. Effective discrimination of healthy and atherosclerotic aorta was achieved at 370 and 500 nm.
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