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Record W3164810066

Developing a Microbubble-based Contrast Agent for X-ray Phase Contrast Imaging to Detect Neovasculature in Breast Cancer

2021· dissertation· en· W3164810066 on OpenAlexaboutno aff
Ngoc Ton

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2021
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsContrast (vision)Breast cancerMicrobubblesPhase contrast microscopyPhase-contrast imagingMedicineBiomedical engineeringRadiologyCancerUltrasoundComputer scienceOpticsInternal medicinePhysicsArtificial intelligence
DOInot available

Abstract

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X-ray phase contrast imaging (XPC) generates contrast from refraction and scattering of X-rays, unlike absorption in conventional radiology. This technique greatly improves the sharpness of boundaries and reveals micro-structured tissues that are not easily detected by conventional absorption-based X-rays. XPC can be performed at high energy, so the absorbed radiation is reduced. Ultrasound microbubbles (MBs) with biocompatible composition and gas content can maximize the X-ray refraction and scattering. Multiple studies have investigated MBs and XPC, but they share a common feature: no uniform parameters in MBs, leading to the inconsistent findings on the efficacy of MBs. Our primary goal was to develop a contrast agent for XPC by assessing which MB characteristics affect contrast the most. Gas-filled MBs were constructed with two shell materials: phospholipid and polyvinyl-alcohol (PVA). Polydisperse lipid-MBs were size separated using centrifugation. Two populations of PVA-MBs were generated by different homogenizers: 2-3 μm and 3-4 μm. A subset of PVA-MBs 3-4 μm were either coated or integrated with superparamagnetic iron oxide nanoparticles (SPIONs). MBs were then immobilized in agar at three concentrations: 5×10⁷ (high), 5×10⁶ (moderate), and 5×10⁵ MBs/ml (low). MBs were imaged by synchrotron at the Canadian Light Source with In-line phase contrast imaging (PCI) and Multiple-image Radiography (MIR). The refraction contrast in PCI was measured by detecting phase object numbers and comparing the mean pixel values (MPV: 0/255) of MBs to agar in minimum intensity projections (MIN) and maximum intensity projections (MAX). Lipid-MBs 6-10 μm, lipid-MBs 4-6 μm and 4-layer SPION-coated PVA-MBs were significantly different (p < 0.05) at three concentrations. In MAX, the contrast was observed with lipid-MBs 6-10 μm and lipid MBs 4-6 μm, whereas only lipid-MBs 6-10 μm showed a significant increase in MPV at the moderate concentration. In MIN, a significant decrease in MPV was observed from lipid MBs 6-10 μm and lipid-MBs 4-6 μm at the high concentration. With MIR, the contrast intensity was measured by comparing the MPV of MBs to agar in the absorption, refraction and ultra-small-angle X-ray scattering (USAXS) images. We only observed a significant increase in MPV in lipid-MBs 6-10 μm (p = 0.02) in the USAXS at the high concentration. These data suggest that lipid-MBs greater than 4 μm are a promising contrast agent for PCI, where 5×10⁶ MB/ml is possibly the lowest detectable concentration in tissues. With MIR, lipid-MBs 6-10 μm are a potential contrast medium for USAXS, and the minimum concentration in tissues may be 5×10⁷ MB/ml. Magnetic resonance imaging (MRI) is a non-ionizing radiation imaging approach that is excellent at visualizing soft tissues. This modality often makes use of gadolinium-based contrast agents to visualize vasculature and blood flow. However, there is controversy about gadolinium’s toxicity, so we aimed to develop a vascular-restricted contrast agent for MRI based on MBs and SPIONs, a known T2 contrast agent. There are two methods to bind SPIONs to polymer-shell MBs: SPION-coated and SPION-integrated MBs. My goal was to compare these methods and determine which approach results in optimal MB detection in T2-weighted MRI. Multiple concentrations of MBs were immobilized with agar in 1.5 ml tubes and then imaged in 3 Tesla Siemens MRI scanner. The signal intensity was identified in 70 mm² circular ROI and measured MPV in 8-bit grayscale (0-255). We imaged SPION-coated MBs and SPION-integrated MBs at two different concentrations and found that all tested MBs generated T2 contrast. For both types of SPION-coated MBs, the differences among the concentrations ranging from 25 μl - 200 μl were not detectable. No change in the signal was seen from the SPION-integrated MBs compared to the agar and plain PVA-MBs except for the highest concentration. Both MBs coated with one and three layers of SPIONs generated a high T2 contrast. Based on these data, I performed a dosage study to determine the lowest detectable concentration of single layer SPION-coated MBs, which was determined to be 5 × 10⁵ MBs/ml.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.223
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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