1,720,996 research outputs found
Using paired-agent principles and widefield fluorescence optical projection tomography to rapidly identify and localize lymph node micro metastases
No full textThe proof-of-concept presented here utilizes a micro metastatic lymph node mode, where porcine lymph nodes are first implanted with a 200-micron human cancer cell spheroid. The lymph nodes are then infused with 40 nM ABY-029 and IRDye 700Dx-Affibody isotype conjugate, followed by widefield multi-channel imaging of 700 nm, 800 nm fluorescence and transmission images across 12 projections, followed by tomographic reconstruction of each channel. Absorption and fluorescence sensitivity matrices needed for reconstructions are created through monte-carlo simulations of photon propagation through the imaging system. Each channel is reconstructed separately at a resolution of 87x87x65 voxels, followed by calculation of binding potential (BP) maps as the ratio of the two fluorescence reconstructions, minus 1. The BP reconstruction is then overlaid onto the absorption reconstruction and the location of the EGFR+ tumor spheroid is isolated in the 3D reconstruction through inspection. These procedures are proposed for intraoperative use.</p
Intraoperative Assessment of Surgical Margins in Head And Neck Cancer Resection Using Time-Domain Fluorescence Imaging
No full textRapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to over- or under-resection of cancerous tissues and follow-up treatments such as ‘call-back’ surgery and chemotherapy. Current techniques utilizing direct measurement of tumor margins in frozen section pathology are slow, which can prevent surgeons from acting on information before a patient is sent home. Other fluorescence techniques require the measurement of margins via captured images that are overlayed with fluorescent data. This method is flawed, as measuring depth from captured images loses spatial information. Intensity-based fluorescence techniques utilizing tumor-to-background ratios do not decouple the effects of concentration from the depth information acquired. Thus, it is necessary to perform an objective measurement to determine depths of surgical margins. This thesis focuses on the theory, device design, simulation development, and overall viability of time-domain fluorescence imaging as an alternative method of determining surgical margin depths. Characteristic regressions were generated using a thresholding method on acquired time-domain fluorescence signals, which were used to convert time-domain data to a depth value. These were applied to an image space to generate a depth map of a modelled tissue sample. All modeling was performed on homogeneous media using Monte Carlo simulations, providing high accuracy at the cost of increased computational time. In practice, the imaging process should be completed within a span of under 20 minutes for a full tissue sample, rather than 20 minutes for a single slice of the sample. This thesis also explores the effects of different thresholding levels on the accuracy of depth determination, as well as the precautions to be taken regarding hardware limitations and signal noise
Intraoperative Assessment of Surgical Margins in Head And Neck Cancer Resection Using Time-Domain Fluorescence Imaging
No full textRapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to over- or under-resection of cancerous tissues and follow-up treatments such as ‘call-back’ surgery and chemotherapy. Current techniques utilizing direct measurement of tumor margins in frozen section pathology are slow, which can prevent surgeons from acting on information before a patient is sent home. Other fluorescence techniques require the measurement of margins via captured images that are overlayed with fluorescent data. This method is flawed, as measuring depth from captured images loses spatial information. Intensity-based fluorescence techniques utilizing tumor-to-background ratios do not decouple the effects of concentration from the depth information acquired. Thus, it is necessary to perform an objective measurement to determine depths of surgical margins. This thesis focuses on the theory, device design, simulation development, and overall viability of time-domain fluorescence imaging as an alternative method of determining surgical margin depths. Characteristic regressions were generated using a thresholding method on acquired time-domain fluorescence signals, which were used to convert time-domain data to a depth value. These were applied to an image space to generate a depth map of a modelled tissue sample. All modeling was performed on homogeneous media using Monte Carlo simulations, providing high accuracy at the cost of increased computational time. In practice, the imaging process should be completed within a span of under 20 minutes for a full tissue sample, rather than 20 minutes for a single slice of the sample. This thesis also explores the effects of different thresholding levels on the accuracy of depth determination, as well as the precautions to be taken regarding hardware limitations and signal noise
Quantification of Vascular Permeability in the Retina Using Fluorescein Videoangiography Data as a Biomarker for Early Diabetic Retinopathy
No full textDiabetic retinopathy, which is the most common reason for blindness in the working-age population, affects over one-third of those who have had diabetes for over ten years. High blood sugar level (hyperglycemia) in the blood damages blood vessels and tight junction at the blood-retinal barrier (BRB). Chronic inflammation leads to changes in vascular health, and over time blood vessels tend to get damaged and exhibit higher “leakage” or permeability. In the late stage of DR, hemorrhages can occur, leading to irreversible damage of neuronal tissue in the retina and vision loss. In the clinic, there are some biomarkers and imaging modalities used to diagnose DR based on some of the more severe products of DR (e.g., hemorrhage), but there is no non-invasive, highly sensitive method to detect diabetic retinopathy before clinical signs occur, when mitigating therapies could be more effective. In this thesis, indicator dilution theory was explored to modeling the temporal dynamics of fluorescein in the retina after intravenous injection, with an aim to quantitatively map subtle changes in retinal blood flow and vascular permeability that could preempt subsequent irreversible damage. Specifically, a simplified version of indicator dilution theory—namely the “adiabatic approximation in tissue homogeneity” (AATH) model—was used to estimate physiological parameters such as the blood flow (F) and the extraction fraction (E: a parameter coupled with vascular permeability) from retinal fluorescein videoangiography data. The AATH fitting protocol was optimized through simulations using a more complex model (the AATH-vascular heterogeneity model, AATH-VH). It was determined that a two-step least square fitting method was more sensitive than a single-step least square fitting of AATH to simulated data to evaluate vascular permeability in early diabetic retinopathy.
The optimized data analysis protocol was then evaluated in an initial clinical study comparing healthy control subjects to those with moderate non-proliferative DR. Volumetric blood flow and retinal vascular permeability maps were compared between patient groups with clear increases in extraction fraction observed in the mild NPDR patients compared to control. These promising early data have been the foundation to an ongoing 5 year study tracking 100 Diabetic patients with no DR so see if early changes in vascular permeability can predict which patients are more likely to progress to DR
Intraoperative tumor margin detection using nanoparticles: protocol optimization through kinetic modeling
No full textClear margins (no tumor on the surface of the resected tissues) is essential to minimize tumor recurrence and prolong survival for wide local excision cancer surgeries. However, standard methods of margin assessment cannot be carried out within the time frame of surgery (meaning patients with positive margins are suggested to undergo call-back surgeries). Intraoperative molecular imaging of cell surface receptors can offer a solution; however, substantial nonspecific diffusion and retention of imaging agents in resected tissues remains a significant challenge to identifying cancer reliably. Recently, “paired-agent” methods—which employ co-administration of a control-imaging agent with a targeting agent—have been applied to thick-sample staining and rinsing applications to account for background staining. This dissertation aimed to optimize paired-agent molecular imaging tumor-to-healthy tissue discrimination through mathematical modeling.Two simplified mathematical models—the rinsing paired-agent model (RPAM) and the serial staining model (SSM)—were derived and tested in accurate simulation models (also developed as a component of this dissertation,) and in preclinical cancer models. More specifically, RPAM was demonstrated to be capable of providing more accurate estimates of receptor concentration than more standard “ratiometric” methods (essentially dividing the targeted agent signal by the control agent signal), and the model was insensitive to the variability of rinsing time from one image to the next. Though it was noted in experiments, that regardless of the approach taken, a very large fraction of signal was removed upon the first rinse, leading to large “gaps” in the data that would be available to RPAM. The SSM, on the other hand, provided a model that could be applied to serial staining data, which yielded a more gradual change in signal between imaging.Considering the multidimensional complexity of paired-agent topical tissue molecular imaging (with diffusion, imaging agent chemical/binding properties, tissue staining, rinsing, imaging, and data analysis protocols all being subject to alteration), thorough optimization margin analysis imaging protocols is untractable using experiments alone. Therefore, a salient feature of this dissertation was the development and validation of a “forward” mathematical diffusion and binding model for in silico testing of proposed paired-agent staining and rinsing protocols in thick tissue
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Rapid Ex Vivo Detection of Cancer in Excised Lymph Nodes: Development of a Tissue Model and Initial Results
No full textThere are millions of new head and neck cancers diagnosed each year, and it is one of the most aggressive cancers. The typical first line of therapy for head and neck cancers is surgery; however, if the cancer has spread (metastasized) from the primary tumor, more advanced surgery and/or adjuvant therapy (chemotherapy and or radiation therapy) can be indicated. Clinically, metastasis is diagnosed by surgically removing one or more lymph nodes draining the primary tumor during the primary tumor resection. Each lymph node located and removed adds to the morbidity of the procedure, so many clinics are moving toward a “sentinel” lymph node biopsy strategy, where only the first lymph node draining the tumor is removed and sent to pathology. Assessment of the node for cancer can take up to a week. If this lymph node is found to have cancer, the patient is then asked to return for a secondary surgery where a complete neck dissection is carried out (removal of all the lymph nodes in the side of the neck ipsilateral to the tumor). This delay in diagnosis is stressful on patients, adds health care costs, and considering the invasiveness of some primary tumor resections, some patients opt not to return for callback surgeries even though it would improve their chances of survival. This thesis presents efforts to test the ability for a fluorescence molecular imaging system called “agent-dependent enhanced photon tomography” (ADEPT) to be able to detect cancer in an excised sentinel lymph node while the patient is still on the operating table. This would allow a significant reduction in the number of patients requiring callback surgeries. Specifically, this thesis explores (in chapter 1) the development of a porcine lymph node fresh tissue model using implanted human cancer spheroids to act as realistic models of a freshly excised sentinel lymph node; (in chapter 2) the advancement of this tissue model to include a range of cancer burden levels and cancer cells strains; (and in chapter 3) a first demonstration of the ADEPT system applied to these realistic tissue models to detect clinically relevant levels of cancer. The ADEPT is a prototype designed specifically for the purpose of being faster in terms of processing and eliminates the need for patient to come back surgeries. We were able to validate ADEPT by incorporating a metastatic model mimicking a human lymph node and verifying the presence of cancer tumor that was manually injected into the lymph node followed by infusion of imaging agents
A three-dimensional tissue molecular imaging system based on angular domain optical projection tomography: Applications in lymph node biopsy
No full textSentinel lymph node biopsy is a good prognostic factor for several cancers as therapeutic decisions are often determined by the results. Despite this importance, false negatives remain common because of standard pathology procedures that aim only to detect macrometastases (> 2 mm diameter) and leave more than 99% of lymph node volumes unassessed. While it is possible to section tissue samples more thoroughly, a subsequent 10x increase in pathologist read time is undesirable. Therefore, a more sensitive and rapid approach for lymph node evaluation is warranted.Our proposed solution was the development of an angle-restricted optical projection tomography system to provide high resolution quantitative imaging of whole lymph nodes prior to conventional pathology. Two main strategies were employed: 1) early photon imaging achieved with angular restriction to minimize the number of detected multiply scattered photons that add to imaging blur; and 2) paired-agent molecular imaging, which can quantify targeted biomolecule concentrations through co-administration of targeted and control imaging agents.This thesis focused primarily on the first aspect; however, all work was performed with paired-agent imaging in mind, such that the technique can be implemented directly in future studies. The first chapter presents a proof-of-concept that verifies the utility of angle-domain imaging for evaluation of low scattering lymph nodes. Filtered backprojection and strict angle restriction for scatter rejection were sufficient to detect and localize clinically relevant metastases. In the second chapter, improvements were made to the system so that detection efficiency could be improved, and the system was more rigorously characterized in terms of reconstruction accuracy and limits of detection. Finally, the third chapter presents the investigation of alternate reconstruction techniques to push the limits of achievable resolution and image quality. The overall findings of this work demonstrate the potential for an angle-restricted tomography system to provide significant improvements of metastases detection sensitivity in excised lymph nodes compared to conventional pathology at a fraction of the time and cost
Non-invasive quantification of cancer drug targets: Mathematical models for paired-agent molecular imaging
No full textCancer is among the leading causes of death worldwide. Incidence of cancer is rising at a rate that is almost completely nullifying improvements in cancer treatment and the heterogeneity of advanced disease poses significant complications for the development of effective therapies. With more aggressive cancers tending to display abnormally high expression of signaling receptors associated cell proliferation - receptors that tend to be expressed at very low levels by healthy cells in adulthood - many new cancer-specific “molecular therapies” have been developed to target and block these pathways. However, not all cancers overexpress the same proliferation pathways, so many have proposed molecular imaging as a non-invasive means of identifying on a patient-by-patient basis, which specific targets may be overexpressed to tailor therapies to the individual (“precision medicine”). The primary goal of this thesis was to develop and validate some of the first non-invasive means of measuring drug-target concentrations prior to therapy and the first measures of drug-target occupancy during therapy to ultimately predict and monitor the efficacy of cancer molecular therapy. All work was founded on paired-agent molecular imaging protocols that employ co-administration of two imaging agents: one agent that is targeted to the biomolecule of interest (e.g. a cell surface signaling receptor that may be overexpressed by a cancer), and a second, “control” (“untargeted”) agent that is as chemically similar to the targeted agent as possible, but that does not bind to the biomolecule of interest. In all paired-agent imaging strategies, the signal from the control agent is used to account for delivery and nonspecific retention effects that can confound the relationship between the targeted imaging agent concentration in a region-of-interest (ROI) and the targeted biomolecule concentration in that ROI
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