Quantifying Imaging Agent Binding and Dissociation in 3-D Cancer Spheroid Tissue Culture Using Paired-Agent Principles.

Binding kinetics play an important role in cancer diagnosis and therapeutics. However, current methods of quantifying binding kinetics fail to consider the three-dimensional environment that drugs and imaging agents experience in biological tissue. In response, a methodology to assay agent binding and dissociation in 3-D tissue culture was developed using paired-agent molecular imaging principles. To test the methodology, the uptakes of ABY-029 (an IRDye 800CW-labeled epidermal growth factor receptor (EGFR)-targeted antibody mimetic) and IRDye-700DX carboxylate in 3-D spheroids were measured in four different human cancer cell lines throughout staining and rinsing. A compartment model (optimized for the application) was then fit to the kinetic curves of both imaging agents to estimate binding and dissociation rate constants of the EGFR-targeted ABY-029 agent. A statistically significant correlation was observed between apparent association rate constant (k3) and the receptor concentration experimentally and in simulations (r = 0.99, p < 0.05). A statistically significant difference was found between effective k3 (apparent rate constant of ABY-029 binding to EGFR) values for cell lines with varying levels of EGFR expression (p < 0.05), with no significant difference found between cell lines and controls for other fit parameters. Additionally, a similar binding affinity profile compared to a gold standard method was determined by this model. This low-cost methodology to quantify imaging agent or drug binding affinity in clinically relevant 3-D tumor spheroid models can be used to guide timing of imaging in molecular guided surgery and could have implications in drug development.

Improved intraoperative identification of close margins in oral squamous cell carcinoma resections using a dual aperture fluorescence ratio approach: first in-human results.

Significance: Surgical excision is the main treatment for solid tumors in oral squamous cell carcinomas, where wide local excision (achieving a healthy tissue margin of >5 mm around the excised tumor) is the goal as it results in reduced local recurrence rates and improved overall survival. Aim: No clinical methods are available to assess the complete surgical margin intraoperatively while the patient is still on the operating table; and while recent intraoperative back-bench fluorescence-guided surgery approaches have shown promise for detecting "positive" inadequate margins (<1 mm), they have had limited success in the detection of "close" inadequate margins (1 to 5 mm). Here, a dual aperture fluorescence ratio (dAFR) approach was evaluated as a means of improving detection of close margins. Approach: The approach was evaluated on surgical specimens from patients who were administered a tumor-specific fluorescent imaging agent (cetuximab-800CW) prior to surgery. The dAFR approach was compared directly against standard wide-field fluorescence imaging and pathology measurements of margin thickness in specimens from three patients and a total of 12 margin locations (1 positive, 5 close, and 6 clear margins). Results: The area under the receiver operating characteristic curve, representing the ability to detect close compared to clear margins (>5 mm) was found to be 1.0 and 0.57 for dAFR and sAF, respectively. Improvements in dAFR were found to be statistically significant (p<0.02). Conclusions: These results provide evidence that the dAFR approach potentially improves detection of close surgical margins.

A cadaveric breast cancer tissue phantom for phase-contrast X-ray imaging applications.

BACKGROUND: As mammography X-ray imaging technologies advance and provide elevated contrast in soft tissues, a need has developed for reliable imaging phantoms for use in system design and component calibration. In advanced imaging modalities such as refraction-based methods, it is critical that developed phantoms capture the biological details seen in clinical precancerous and cancerous cases while minimizing artifacts that may be caused due to phantom production. This work presents the fabrication of a breast tissue imaging phantom from cadaveric breast tissue suitable for use in both transmission and refraction-enhanced imaging systems. METHODS: Human cancer cell tumors were grown orthotopically in nude athymic mice and implanted into the fixed tissue while maintaining the native tumor/adipose tissue interface. RESULTS: The resulting human-murine tissue hybrid phantom was mounted on a clear acrylic housing for absorption and refraction X-ray imaging. Digital breast tomosynthesis was also performed. CONCLUSION: Both attenuation-based imaging and refraction-based imaging of the phantom are presented to confirm the suitability of this phantom's use in both imaging modalities.

Quantifying imaging agent binding and dissociation in 3D cancer spheroid tissue culture using paired-agent principles.

Binding kinetics play an important role in cancer diagnosis and therapeutics. However, current methods of quantifying binding kinetics fail to consider the three-dimensional environment that drugs and imaging agents experience in biological tissue. In response, a methodology to assay agent binding and dissociation in 3D tissue culture was developed using paired-agent molecular imaging principles. To test the methodology, the uptakes of ABY-029 (an IRDye 800CW-labeled epidermal growth factor receptor (EGFR)-targeted antibody-mimetic) and IRDye 700DX-carboxylate in 3D spheroids were measured in four different human cancer cell lines throughout staining and rinsing. A compartment model (optimized for the application) was then fit to the kinetic curves of both imaging agents to estimate binding and dissociation rate constants of the EGFR targeted ABY-029 agent. A linear correlation was observed between apparent association rate constant (k3) and the receptor concentration experimentally and in simulations (r=0.99, p<0.05). Additionally, a similar binding affinity profile compared to a gold standard method was determined by this model. This low-cost methodology to quantify imaging agent or drug binding affinity in clinically relevant 3D tumor spheroid models, can be used to guide timing of imaging in molecular guided surgery and could have implications in drug development.

Special Section Guest Editorial: Hard X-Ray Tomography with Micrometer Resolution.

JMI guest editors introduce articles collected in the JMI Special Section on Hard X-Ray Tomography with Micrometer Resolution, a snapshot of this important niche area featured by hard x-ray tomography at the micrometer level.

Model-based system matrix for iterative reconstruction in sub-diffuse angular-domain fluorescence optical projection tomography.

This work concerns a fluorescence optical projection tomography system for low scattering tissue, like lymph nodes, with angular-domain rejection of highly scattered photons. In this regime, filtered backprojection (FBP) image reconstruction has been shown to provide reasonable quality images, yet here a comparison of image quality between images obtained by FBP and iterative image reconstruction with a Monte Carlo generated system matrix, demonstrate measurable improvements with the iterative method. Through simulated and experimental phantoms, iterative algorithms consistently outperformed FBP in terms of contrast and spatial resolution. Moreover, when projection number was reduced, in order to reduce total imaging time, iterative reconstruction suppressed artifacts that hampered the performance of FBP reconstruction (structural similarity of the reconstructed images with "truth" was improved from 0.15 ± 1.2 × 10-3 to 0.66 ± 0.02); and although the system matrix was generated for homogenous optical properties, when heterogeneity (62.98 cm-1 variance in µs ) was introduced to simulated phantoms, the results were still comparable (structural similarity homo: 0.67 ± 0.02 vs hetero: 0.66 ± 0.02).

Intraoperative Detection of Micrometastases in Whole Excised Lymph Nodes Using Fluorescent Paired-Agent Imaging Principles: Identification of a Suitable Staining and Rinsing Protocol.

PURPOSE: Correctly identifying nodal status is recognized as a critical prognostic factor in many cancer types and is essential to guide adjuvant treatment. Currently, surgical removal of lymph nodes followed by pathological examination is commonly performed as a standard-of-care to detect node metastases. However, conventional pathology protocols are time-consuming, yet less than 1 % of lymph node volumes are examined, resulting in a 30-60 % rate of missed micrometastases (0.2-2 mm in size). PROCEDURES: This study presents a method to fluorescently stain excised lymph nodes using paired-agent molecular imaging principles, which entail co-administration of a molecular-targeted imaging agent with a suitable control (untargeted) agent, whereby any nonspecific retention of the targeted agent is accounted for by the signal from the control agent. Specifically, it was demonstrated that by dual-needle continuous infusion of either an antibody-based imaging agent pair (epidermal growth factor receptor (EGFR) targeted agent: IRDye-800CW labeled Cetuximab; control agent: IRDye-700DX-IgG) or an Affibody-based pair (EGFR targeted Affibody® agent: ABY-029; control agent IRDYe-700DX carboxylate) at 0.3 ml/min. RESULTS: The results demonstrated the possibility to achieve >99 % sensitivity and > 95 % specificity for detection of a single micrometastasis (~0.2 mm diameter) in a whole lymph node within 22 min of tissue processing time. CONCLUSION: The detection capabilities offer substantial improvements over existing intraoperative lymph node biopsy methods (e.g., frozen pathology has a micrometastasis sensitivity <20 %).

Characterization of an angular domain fluorescence optical projection tomography system for mesoscopic lymph node imaging.

Transmittance and fluorescence optical projection tomography can offer high-resolution and high-contrast visualization of whole biological specimens; however, applications are limited to samples exhibiting minimal light scattering. Our previous work demonstrated that angular-domain techniques permitted imaging of ∼1cm diameter noncleared lymph nodes because of their low scattering nature. Here, an angle-restricted transmittance/fluorescence system is presented and characterized in terms of geometric and fluorescence concentration reconstruction accuracy as well as spatial resolution, depth of focus, and fluorescence limits of detection. Using lymph node mimicking phantoms, results demonstrated promising detection and localization capabilities relevant for clinical lymph node applications.

Do CNNs Solve the CT Inverse Problem?

OBJECTIVE: This work examines the claim made in the literature that the inverse problem associated with image reconstruction in sparse-view computed tomography (CT) can be solved with a convolutional neural network (CNN). METHODS: Training, and testing image/data pairs are generated in a dedicated breast CT simulation for sparse-view sampling, using two different object models. The trained CNN is tested to see if images can be accurately recovered from their corresponding sparse-view data. For reference, the same sparse-view CT data is reconstructed by the use of constrained total-variation (TV) minimization (TVmin), which exploits sparsity in the gradient magnitude image (GMI). RESULTS: There is a significant discrepancy between the image obtained with the CNN and the image that generated the data. TVmin is able to accurately reconstruct the test images. CONCLUSION: We find that the sparse-view CT inverse problem cannot be solved for the particular published CNN-based methodology that we chose, and the particular object model that we tested. SIGNIFICANCE: The inability of the CNN to solve the inverse problem associated with sparse-view CT, for the specific conditions of the presented simulation, draws into question similar unsupported claims being made for the use of CNNs and deep-learning to solve inverse problems in medical imaging.

Deep Learning Based Model Observer by U-Net.

Model Observers (MO) are algorithms designed to evaluate and optimize the parameters of new medical imaging reconstruction methodologies by providing a measure of human accuracy for a diagnostic task. In contrast with a computer-aided diagnosis system, MOs are not designed to outperform human diagnosis but only to find a defect if a radiologist would be able to detect it. These algorithms can economize and expedite the finding of optimal reconstruction parameters by reducing the number of sessions with expert radiologists, which are costly and prolonged. Convolutional Neural Networks (CNN or ConvNet) have been successfully used in the computer vision field for image classification, segmentation and video analytics. In this paper, we propose and test several U-Net configurations as MO for a defect localization task on synthetic images with different levels of correlated noisy backgrounds. Preliminary results show that the CNN based MO has potential and its accuracy correlates well with that of the human.

Angular restriction fluorescence optical projection tomography to localize micrometastases in lymph nodes.

Lymph node biopsy is a primary means of staging breast cancer, yet standard pathological techniques are time-consuming and typically sample less than 1% of the total node volume. A low-cost fluorescence optical projection tomography (OPT) protocol is demonstrated for rapid imaging of whole lymph nodes in three dimensions. The relatively low scattering properties of lymph node tissue can be leveraged to significantly improve spatial resolution of lymph node OPT by employing angular restriction of photon detection. It is demonstrated through porcine lymph node metastases models that simple filtered-backprojection reconstruction is sufficient to detect and localize 200-µm-diameter metastases (the smallest clinically significant) in 1-cm-diameter lymph nodes.

Preformed Vascular Networks Survive and Enhance Vascularization in Critical Sized Cranial Defects.

Vascular networks provide nutrients, oxygen, and progenitor cells that are essential for bone function. It has been proposed that a preformed vascular network may enhance the performance of engineered bone. In this study vascular networks were generated from human umbilical vein endothelial cell and mesenchymal stem cell spheroids encapsulated in fibrin scaffolds, and the stability of preformed vascular networks and their effect on bone regeneration were assessed in an in vivo bone model. Under optimized culture conditions, extensive vessel-like networks formed throughout the scaffolds in vitro. After vascular network formation, the vascularized scaffolds were implanted in a critical sized calvarial defect in nude rats. Immunohistochemical staining for CD31 showed that the preformed vascular networks survived and anastomosed with host tissue within 1 week of implantation. The prevascularized scaffolds enhanced overall vascularization after 1 and 4 weeks. Early bone formation around the perimeter of the defect area was visible in X-ray images of samples after 4 weeks. Prevascularized scaffolds may be a promising strategy for engineering vascularized bone.

Inter-laboratory comparison of channelized hotelling observer computation.

PURPOSE: The task-based assessment of image quality using model observers is increasingly used for the assessment of different imaging modalities. However, the performance computation of model observers needs standardization as well as a well-established trust in its implementation methodology and uncertainty estimation. The purpose of this work was to determine the degree of equivalence of the channelized Hotelling observer performance and uncertainty estimation using an intercomparison exercise. MATERIALS AND METHODS: Image samples to estimate model observer performance for detection tasks were generated from two-dimensional CT image slices of a uniform water phantom. A common set of images was sent to participating laboratories to perform and document the following tasks: (a) estimate the detectability index of a well-defined CHO and its uncertainty in three conditions involving different sized targets all at the same dose, and (b) apply this CHO to an image set where ground truth was unknown to participants (lower image dose). In addition, and on an optional basis, we asked the participating laboratories to (c) estimate the performance of real human observers from a psychophysical experiment of their choice. Each of the 13 participating laboratories was confidentially assigned a participant number and image sets could be downloaded through a secure server. Results were distributed with each participant recognizable by its number and then each laboratory was able to modify their results with justification as model observer calculation are not yet a routine and potentially error prone. RESULTS: Detectability index increased with signal size for all participants and was very consistent for 6 mm sized target while showing higher variability for 8 and 10 mm sized target. There was one order of magnitude between the lowest and the largest uncertainty estimation. CONCLUSIONS: This intercomparison helped define the state of the art of model observer performance computation and with thirteen participants, reflects openness and trust within the medical imaging community. The performance of a CHO with explicitly defined channels and a relatively large number of test images was consistently estimated by all participants. In contrast, the paper demonstrates that there is no agreement on estimating the variance of detectability in the training and testing setting.

Enhanced detection of early photons in time-domain optical imaging by running in the "dead-time" regime.

Optical tomography can yield anatomical and molecular information about biological tissue. However, its spatial resolution is poor in thick samples owing to high scatter. Early photon approaches, where photon arrival times are measured with time-resolved detectors, provide one means of improving spatial resolution through selection of photons that travel a straighter path. Here, a novel approach to significantly enhance detection of early photons in time-correlated single photon counting with avalanche photodiodes has been discussed. Results suggest that the early photon detection rate can be increased by about 10 orders of magnitude by running the detector in a dead-time regime.

Full receiver operating characteristic curve estimation using two alternative forced choice studies.

Task-based medical image quality is typically measured by the degree to which a human observer can perform a diagnostic task in a psychophysical human observer study. During a typical study, an observer is asked to provide a numerical score quantifying his confidence as to whether an image contains a diagnostic marker or not. Such scores are then used to measure the observers' diagnostic accuracy, summarized by the receiver operating characteristic (ROC) curve and the area under ROC curve. These types of human studies are difficult to arrange, costly, and time consuming. In addition, human observers involved in this type of study should be experts on the image genre to avoid inconsistent scoring through the lengthy study. In two-alternative forced choice (2AFC) studies, known to be faster, two images are compared simultaneously and a single indicator is given. Unfortunately, the 2AFC approach cannot lead to a full ROC curve or a set of image scores. The aim of this work is to propose a methodology in which multiple rounds of the 2AFC studies are used to re-estimate an image confidence score (a.k.a. rating, ranking) and generate the full ROC curve. In the proposed approach, we treat image confidence score as an unknown rating that needs to be estimated and 2AFC as a two-player match game. To achieve this, we use the ELO rating system, which is used for calculating the relative skill levels of players in competitor-versus-competitor games such as chess. The proposed methodology is not limited to ELO, and other rating methods such as TrueSkill™, Chessmetrics, or Glicko can be also used. The presented results, using simulated data, indicate that a full ROC curve can be recovered using several rounds of 2AFC studies and that the best pairing strategy starts with the first round of pairing abnormal versus normal images (as in the classical 2AFC approach) followed by a number of rounds using random pairing. In addition, the proposed method was tested in a pilot human observer study. These pilot results indicate that three to five rounds of 2AFC studies require less human observer time than a full scoring study and that the re-estimated ROC curves and associated area under ROC curve values have high statistical agreement with the full scoring study.

A computational model to generate simulated three-dimensional breast masses.

PURPOSE: To develop algorithms for creating realistic three-dimensional (3D) simulated breast masses and embedding them within actual clinical mammograms. The proposed techniques yield high-resolution simulated breast masses having randomized shapes, with user-defined mass type, size, location, and shape characteristics. METHODS: The authors describe a method of producing 3D digital simulations of breast masses and a technique for embedding these simulated masses within actual digitized mammograms. Simulated 3D breast masses were generated by using a modified stochastic Gaussian random sphere model to generate a central tumor mass, and an iterative fractal branching algorithm to add complex spicule structures. The simulated masses were embedded within actual digitized mammograms. The authors evaluated the realism of the resulting hybrid phantoms by generating corresponding left- and right-breast image pairs, consisting of one breast image containing a real mass, and the opposite breast image of the same patient containing a similar simulated mass. The authors then used computer-aided diagnosis (CAD) methods and expert radiologist readers to determine whether significant differences can be observed between the real and hybrid images. RESULTS: The authors found no statistically significant difference between the CAD features obtained from the real and simulated images of masses with either spiculated or nonspiculated margins. Likewise, the authors found that expert human readers performed very poorly in discriminating their hybrid images from real mammograms. CONCLUSIONS: The authors' proposed method permits the realistic simulation of 3D breast masses having user-defined characteristics, enabling the creation of a large set of hybrid breast images containing a well-characterized mass, embedded within real breast background. The computational nature of the model makes it suitable for detectability studies, evaluation of computer aided diagnosis algorithms, and teaching purposes.

Quantification of the binding potential of cell-surface receptors in fresh excised specimens via dual-probe modeling of SERS nanoparticles.

The complete removal of cancerous tissue is a central aim of surgical oncology, but is difficult to achieve in certain cases, especially when the removal of surrounding normal tissues must be minimized. Therefore, when post-operative pathology identifies residual tumor at the surgical margins, re-excision surgeries are often necessary. An intraoperative approach for tumor-margin assessment, insensitive to nonspecific sources of molecular probe accumulation and contrast, is presented employing kinetic-modeling analysis of dual-probe staining using surface-enhanced Raman scattering nanoparticles (SERS NPs). Human glioma (U251) and epidermoid (A431) tumors were implanted subcutaneously in six athymic mice. Fresh resected tissues were stained with an equimolar mixture of epidermal growth factor receptor (EGFR)-targeted and untargeted SERS NPs. The binding potential (BP; proportional to receptor concentration) of EGFR - a cell-surface receptor associated with cancer - was estimated from kinetic modeling of targeted and untargeted NP concentrations in response to serial rinsing. EGFR BPs in healthy, U251, and A431 tissues were 0.06 ± 0.14, 1.13 ± 0.40, and 2.23 ± 0.86, respectively, which agree with flow-cytometry measurements and published reports. The ability of this approach to quantify the BP of cell-surface biomarkers in fresh tissues opens up an accurate new approach to analyze tumor margins intraoperatively.

Analyzer-based phase-contrast imaging system using a micro focus X-ray source.

Here we describe a new in-laboratory analyzer based phase contrast-imaging (ABI) instrument using a conventional X-ray tube source (CXS) aimed at bio-medical imaging applications. Phase contrast-imaging allows visualization of soft tissue details usually obscured in conventional X-ray imaging. The ABI system design and major features are described in detail. The key advantage of the presented system, over the few existing CXS ABI systems, is that it does not require high precision components, i.e., CXS, X-ray detector, and electro-mechanical components. To overcome a main problem introduced by these components, identified as temperature stability, the system components are kept at a constant temperature inside of three enclosures, thus minimizing the electrical and mechanical thermal drifts. This is achieved by using thermoelectric (Peltier) cooling/heating modules that are easy to control precisely. For CXS we utilized a microfocus X-ray source with tungsten (W) anode material. In addition the proposed system eliminates tungsten's multiple spectral lines by selecting monochromator crystal size appropriately therefore eliminating need for the costly mismatched, two-crystal monochromator. The system imaging was fine-tuned for tungsten Kα1 line with the energy of 59.3 keV since it has been shown to be of great clinical significance by a number of researchers at synchrotron facilities. In this way a laboratory system that can be used for evaluating and quantifying tissue properties, initially explored at synchrotron facilities, would be of great interest to a larger research community. To demonstrate the imaging capability of our instrument we use a chicken thigh tissue sample.

Limited-angle tomography for analyzer-based phase-contrast x-ray imaging.

Multiple-image radiography (MIR) is an analyzer-based phase-contrast x-ray imaging method, which is emerging as a potential alternative to conventional radiography. MIR simultaneously generates three planar parametric images containing information about scattering, refraction and attenuation properties of the object. The MIR planar images are linear tomographic projections of the corresponding object properties, which allows reconstruction of volumetric images using computed tomography (CT) methods. However, when acquiring a full range of linear projections around the tissue of interest is not feasible or the scanning time is limited, limited-angle tomography techniques can be used to reconstruct these volumetric images near the central plane, which is the plane that contains the pivot point of the tomographic movement. In this work, we use computer simulations to explore the applicability of limited-angle tomography to MIR. We also investigate the accuracy of reconstructions as a function of number of tomographic angles for a fixed total radiation exposure. We use this function to find an optimal range of angles over which data should be acquired for limited-angle tomography MIR (LAT-MIR). Next, we apply the LAT-MIR technique to experimentally acquired MIR projections obtained in a cadaveric human thumb study. We compare the reconstructed slices near the central plane to the same slices reconstructed by CT-MIR using the full angular view around the object. Finally, we perform a task-based evaluation of LAT-MIR performance for different numbers of angular views, and use template matching to detect cartilage in the refraction image near the central plane. We use the signal-to-noise ratio of this test as the detectability metric to investigate an optimum range of tomographic angles for detecting soft tissues in LAT-MIR. Both results show that there is an optimum range of angular view for data acquisition where LAT-MIR yields the best performance, comparable to CT-MIR only if one considers volumetric images near the central plane and not the whole volume.

Noise and analyzer-crystal angular position analysis for analyzer-based phase-contrast imaging.

The analyzer-based phase-contrast x-ray imaging (ABI) method is emerging as a potential alternative to conventional radiography. Like many of the modern imaging techniques, ABI is a computed imaging method (meaning that images are calculated from raw data). ABI can simultaneously generate a number of planar parametric images containing information about absorption, refraction, and scattering properties of an object. These images are estimated from raw data acquired by measuring (sampling) the angular intensity profile of the x-ray beam passed through the object at different angular positions of the analyzer crystal. The noise in the estimated ABI parametric images depends upon imaging conditions like the source intensity (flux), measurements angular positions, object properties, and the estimation method. In this paper, we use the Cramér-Rao lower bound (CRLB) to quantify the noise properties in parametric images and to investigate the effect of source intensity, different analyzer-crystal angular positions and object properties on this bound, assuming a fixed radiation dose delivered to an object. The CRLB is the minimum bound for the variance of an unbiased estimator and defines the best noise performance that one can obtain regardless of which estimation method is used to estimate ABI parametric images. The main result of this paper is that the variance (hence the noise) in parametric images is directly proportional to the source intensity and only a limited number of analyzer-crystal angular measurements (eleven for uniform and three for optimal non-uniform) are required to get the best parametric images. The following angular measurements only spread the total dose to the measurements without improving or worsening CRLB, but the added measurements may improve parametric images by reducing estimation bias. Next, using CRLB we evaluate the multiple-image radiography, diffraction enhanced imaging and scatter diffraction enhanced imaging estimation techniques, though the proposed methodology can be used to evaluate any other ABI parametric image estimation technique.