Multifunctional Poly(Acrylic Acid)-Coated EuBiGd2O3 Nanocomposite as an Effective Contrast Agent in Spectral Photon Counting CT, MRI, and Fluorescence Imaging
Bibliographic record
Abstract
Yusuf O Ibrahim,1,2 Nabil Maalej,1,2 Aamir Younis Raja,1 Ahsanulhaq Qurashi,3 Mohamed Rahmani,4,8 Thenmozhi Venkatachalam,4 Osama Abdullah,5 Haidee J Paterson,5 Gobind Das,1 Curtis C Bradley,1 Rasha A Nasser,6 Charalampos Pitsalidis1,7,8 1Department of Physics, Khalifa University of Science and Technology, Abu Dhabi, 127788, United Arab Emirates; 2Functional Biomaterials Group, Khalifa University of Science and Technology, Abu Dhabi, 127788, United Arab Emirates; 3Department of Chemistry, Khalifa University of Science and Technology, Abu Dhabi, 127788, United Arab Emirates; 4Department of Biological Sciences, College of Medicine & Health Sciences, Khalifa University, Abu Dhabi, 127788, United Arab Emirates; 5Core Technology Platform Operations, New York University Abu Dhabi, Abu Dhabi, 129188, United Arab Emirates; 6Department of Biomedical Engineering and Biotechnology, Khalifa University of Science and Technology, Abu Dhabi, 127788, United Arab Emirates; 7Advanced Research and Innovation Center (ARIC) Khalifa University, Abu Dhabi, 127788, United Arab Emirates; 8Center for Biotechnology, Khalifa University, Abu Dhabi, 127788, United Arab EmiratesCorrespondence: Nabil Maalej, Email nabil.maalej@ku.ac.aeIntroduction: Recently, diagnostic methods based on multimodal and non-invasive imaging, such as MRI and CT scanners, have been developed for accurate cancer diagnosis. A key limitation of these imaging systems is their low contrast. Therefore, developing stable, non-toxic, and efficient multimodal imaging contrast agents is desirable. In this work, we demonstrated the synthesis of a poly(acrylic acid) (PAA) â coated nanoparticles (NPs), PAA@EuBiGd2O3-NPs as an imaging agent for contrast enhancement in spectral photon-counting computed tomography (SPCCT), magnetic resonance imaging (MRI) and fluorescence imaging (FL).Methods: We synthesized PAA-coated EuBiGd2O3-NPs using a polyol method by dissolving metal nitrates and PAA in triethylene glycol. NaOH solution was added under constant heating at 180°C. The nanoparticles were precipitated with the addition of ethanol, then washed, dried, calcined at 600°C, and redispersed in water for further studies. The nanoparticles were characterized using TEM, SEM, XRD, XPS, FTIR, and PL spectroscopy. PAA@EuBiGd2O3-NPs were tested in vitro for their cytocompatibility with lung cancer epithelial cells (A549). The nanocomposite image contrast enhancement was evaluated using SPCCT, MRI, and FL imaging.Results: The cell viability study showed that PAA@EuBiGd2O3-NPs is safe up to 250 μg/mL, exhibiting IC50 values of 365.8 and 337.8 μg/mL after 24 and 48 hours, respectively. The NPs have strong X-ray attenuation with a slope of ~61 HUmL/mg, as determined from the SPCCT concentration-dependent analysis. The MRI of the NPs reveals a high T1 contrast with a relaxivity of 11.77 mMâ 1sâ 1. Fluorescence imaging of cells incubated with PAA@EuBiGd2Oâ-NPs shows strong red luminescence.Conclusion: The new nanocomposite has proven to be an effective trimodal contrast agent with high attenuation in CT, enhanced T1 signal in MRI, and strong red luminescence in FL imaging with promising diagnostic capabilities. Keywords: multifunctional nanoparticles, multimodal imaging, spectral photon-counting CT, magnetic resonance imaging, fluorescence imaging
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".