Imaging Tool Research Articles

Development of RBL-STEM Learning to Improve Students' Conjecturing Thinking Skills in Asymmetric Cryptography Problems in Blockchain Technology Using Super (a,d)-Hyperedge Antimagic Total Labeling of Hypergraphs

The rapid evolution of blockchain technology underscores the need to enhance students' conjecturing thinking skills. Research-Based Learning (RBL), combined with Science, Technology, Engineering, and Mathematics (STEM) approaches, offers an effective framework for this purpose. This study aims to explore RBL-STEM activities, describe the process of developing RBL-STEM learning materials, and analyze the effectiveness of these resources in improving students' conjecturing thinking abilities. Using a research and development (R&D) methodology, the study produced various learning tools, including assignment designs, worksheets, and learning outcome assessments. The developed materials demonstrated a validity score of 96.80%. A trial conducted with 37 students revealed that the RBL-STEM resources were highly effective (92.12%) and practical (97.71%), with students showing strong engagement and positive feedback. The study found significant improvements in students’ conjecturing thinking skills as they tackled super -hyperedge antimagic total labeling problems in the context of asymmetric cryptography for blockchain technology. Students' proficiency levels were categorized into three groups: high, medium, and low. Statistical analysis, phase imaging, N-Vivo software, and word cloud tools validated the results, further confirming the enhancement of conjecturing thinking skills. This research highlights the potential of RBL-STEM to develop critical thinking abilities in practical applications, such as solving complex blockchain-related problems.

Use of analytical strategies to understand spatial chemical variation in bacterial surface communities.

Not only do surface-growing microbes such as biofilms display specific traits compared to planktonic cells, but also they display many heterogeneous behaviors over many spatial and temporal contexts. While the application of molecular genetics tools to extract or visualize gene expression or regulatory function data is now common in studying surface growth, the use of analytical chemistry tools to visualize the spatiotemporal distribution of chemical products synthesized by these surface microbes is less common. Here, we review chemical imaging tools that have been used to inform our understanding of surface-growing microbes. We highlight the use of confocal Raman Microscopy, surface-enhanced Raman spectroscopy, matrix-assisted laser desorption/ionization, secondary ion mass spectrometry, desorption electrospray ionization, and electrochemical imaging that have been applied to assess two-dimensional chemical profiles of bacteria. We specifically discuss the use of these tools to study rhamnolipids, alkylquinolones, and phenazines of the bacterium Pseudomonas aeruginosa.

Toward low-noise on-chip plasmonic three-dimensional biological cell imaging

Enhancing accessibility to affordable and efficient cell imaging tools has been a longstanding worldwide objective for rapid disease detection and diagnosis. We present an innovative approach to this goal, introducing a compact, portable, and user-friendly three-dimensional (3D) cell imaging platform leveraging silicon photonics and the surface plasmon coupled emission (SPCE) phenomenon. Central to our method is a specially designed slide that incorporates a fundamental SPCE structure seamlessly integrated with a silicon nitride (SiN) waveguide. We introduce a grooved array on the slide to couple light into the waveguide, interfacing with a broadband light source. This source is employed to excite fluorescently labeled cells. The excitation is achieved using edge coupling through the SiN waveguide, directing the excitation light to the specimen placed on the SPCE platform. This integrated architecture eliminates the necessity for an additional filter to extract the required light for fluorophore excitation while enabling precise excitation of labeled cells. Following the fluorophore excitation, the emitted SPCE signals are captured and subjected to analysis. We have developed an imaging algorithm based on the emitted light patterns, which we comprehensively detail through theoretical demonstration. This algorithm has the remarkable capability of achieving 3D cell imaging. This fusion of optics and computational techniques can significantly impact the domain of cell imaging by enabling the development of easily accessible and portable point-of-care (POC) imaging tools.

Simultaneous measurement of multimode squeezing through multimode phase-sensitive amplification

Multimode squeezed light is an increasingly popular tool in photonic quantum technologies, including sensing, imaging, and computation. Meanwhile, the existing methods of its characterization are technically complicated, which reduces the level of squeezing, and mostly deal with a single mode at a time. Here, for the first time, to the best of our knowledge, we employ optical parametric amplification to characterize multiple squeezing eigenmodes simultaneously. We retrieve the shapes and squeezing degrees of all modes at once through direct detection followed by modal decomposition. This method is tolerant to inefficient detection and does not require a local oscillator. For a spectrally and spatially multimode squeezed vacuum, we characterize eight strongest spatial modes, obtaining squeezing and anti-squeezing values of up to −5.2 ± 0.2 dB and 8.6 ± 0.3 dB, respectively, despite the 50% detection loss. This work, being the first exploration of an optical parametric amplifier’s multimode capability for squeezing detection, paves the way for the real-time detection of multimode squeezing.

Dry Powder Inhalers for Delivery of Synthetic Biomolecules

This manuscript provides a comprehensive review of advancements in dry powder inhaler (DPI) technology for pulmonary and systemic drug delivery, focusing on proteins, peptides, nucleic acids, and small molecules. Innovations in spray-drying (SD), spray freeze-drying (SFD), and nanocarrier engineering have led to enhanced stability, bioactivity, and aerosol performance. Studies reveal the critical role of excipients, particle morphology, and device design in optimizing deposition and therapeutic efficacy. Applications include asthma, cystic fibrosis, tuberculosis (TB), and lung cancer, with emerging platforms such as ternary formulations and siRNA-loaded systems demonstrating significant clinical potential. Challenges such as stability, scalability, and patient adherence are addressed through novel strategies, including Quality by Design (QbD) approaches and advanced imaging tools. This work outlines pathways for future innovation in pulmonary drug delivery.

Early Division of the Paramedian Forehead Flap: A Systematic Review and Retrospective Analysis.

To determine whether and when early division of the paramedian forehead flap may be safely performed. PubMed (NLM), Scopus (Elsevier), and Embase (Elsevier). A systematic search of PubMed, Scopus, and Embase was conducted according to PRISMA guidelines. Data extraction included time to pedicle division, patient and defect characteristics, and postoperative complications. Additionally, a retrospective analysis of patients at our institution was performed to augment the cohort. A total of 103 patients (85 from 6 studies identified via systematic review and 18 via retrospective review) underwent early flap division defined as 16 days and earlier. The average time to division was 9.89 days (3-16). There were no cases of flap loss, and complications were rare. Several studies excluded full thickness defects. Five studies included patients requiring cartilage grafting, although some limited this to less than 50% of the defect area. All patients in our retrospective cohort had partial thickness defects and none required cartilage grafting. Despite smoking being a major risk factor for vascular disease, 13.7% of patients were current smokers. Several studies utilized imaging tools such as indocyanine green angiography to assess flap perfusion. Notably, in these instances, no cases were delayed due to lack of adequate neovascularization. Early paramedian forehead flap division may be an option in select patients with partial thickness nasal defects. Adjunct imaging may be a cost-effective method of evaluating appropriate timing of division. NA Laryngoscope, 2025.

The Role of Artificial Intelligence in Urogynecology: Current Applications and Future Prospects

Artificial intelligence (AI) is the new medical hot topic, being applied mainly in specialties with a strong imaging component. In the domain of gynecology, AI has been tested and shown vast potential in several areas with promising results, with an emphasis on oncology. However, fewer studies have been made focusing on urogynecology, a branch of gynecology known for using multiple imaging exams (IEs) and tests in the management of women’s pelvic floor health. This review aims to illustrate the current state of AI in urogynecology, namely with the use of machine learning (ML) and deep learning (DL) in diagnostics and as imaging tools, discuss possible future prospects for AI in this field, and go over its limitations that challenge its safe implementation.

Retrospectively Quantified T2 Improves Detection of Clinically Significant Peripheral Zone Prostate Cancer

Background: Multiparametric MRI (mpMRI) as a non-invasive imaging tool is important in prostate cancer (PCa) detection and localization. Combined with radiomics analysis, features extracted from mpMRI have been utilized to predict PCa aggressiveness. T2 mapping provides quantitative information in PCa diagnoses but is not routinely available in clinical practice. Previous work from our group developed a deep learning-based method to estimate T2 maps from clinically acquired T1- and T2-weighted images. This study aims to evaluate the added value of the estimated T2 map by combining it with conventional T2-weighted images for detecting clinically significant PCa (csPCa). Methods: An amount of 76 peripheral zone prostate lesions, including clinically significant and insignificant cases, were retrospectively analyzed. Radiomic features were extracted from conventional T2-weighted images and deep learning-estimated T2 maps, followed by feature selection and model development using five-fold cross-validation. Logistic regression and Gaussian Process classifiers were employed to develop the prediction models, with performance evaluated by area under the curve (AUC) and accuracy metrics. Results: The model incorporating features from both T2-weighted images and estimated T2 maps achieved an AUC of 0.803, significantly outperforming the model based solely on T2-weighted image features (AUC of 0.700, p = 0.048). Conclusions: Radiomics features extracted from deep learning-estimated T2 maps provide additional quantitative information that improves the prediction of peripheral zone csPCa aggressiveness, potentially enhancing risk stratification in non-invasive PCa diagnostics.

Diuresis During 18F-Flotufolastat (rhPSMA-7.3) PET/CT Improves Recurrence Detection After Prostatectomy: A Prospective Phase II Trial.

Radiopharmaceuticals targeting prostate-specific membrane antigen (PSMA) have emerged as a sensitive tool for PET imaging of prostate cancer (PCa) recurrence. Yet urinary bladder activity may obscure the visualization of prostate bed recurrence. Among the Food and Drug Administration-approved PSMA radiopharmaceuticals, 18F-flotufolastat (rhPSMA-7.3) has the lowest urinary excreted activity. We investigated the impact of diuresis with intravenous furosemide and oral hydration on bladder activity and PCa recurrence detection in patients with PCa after prostatectomy with biochemical recurrence. Methods: This phase II study (NCT05779943) prospectively recruited men with PCa after prostatectomy with a rising prostate-specific antigen (PSA) level of at least 0.1 ng/mL. All patients had 2 18F-flotufolastat PET/CT scans, one with 20 mg of furosemide administered intravenously with the radiotracer and the other without. SUVmean, SUVmax, and bladder volume were compared between the with- and without-furosemide PET/CT studies. PCa lesion detection was compared between the 2 sets of scans. Results: Twenty men with a median PSA of 0.61 ng/mL (interquartile range, 0.18-1.15) completed both sets of scans. Bladder activity was significantly lower for the with- than the without-furosemide studies, at a median SUVmax of 4.20 (range, 1.70-19.80) versus 13.35 (range, 3.90-165.4), respectively (P = 0.014), and a median SUVmean of 2.95 (range, 0.80-17.60) versus 10.00 (range, 1.90-140.00), respectively (P = 0.017). Multivariable analysis demonstrated that both furosemide administration and bladder distention were independent covariates for reduced bladder activity. At the prostate bed region level, the recurrence detection rates were 17 of 20 (85%) and 12 of 20 (60%) for the with- and without-furosemide studies, respectively (P = 0.025). No difference in detection rates was present at the per-patient, pelvic, or extrapelvic regions between the 2 sets of studies. Three of 20 without-furosemide studies had a mild noninterfering peribladder halo artifact, but none had an artifact with furosemide. Conclusion: In men with biochemical recurrence and a PSA level of at least 0.1 ng/mL after prostatectomy for PCa, a strategy with 18F-flotufolastat PET/CT and concordant low-dose furosemide further reduces urinary bladder intensity and increases local recurrence detection. Even without the use of a diuretic, relative bladder distension alone also reduces bladder activity, though not to the same degree as with a diuretic.

The Use of Bone Biomarkers, Imaging Tools, and Genetic Tests in the Diagnosis of Rare Bone Disorders.

Rare bone diseases are clinically and genetically heterogenous. Despite those differences, the underlying pathophysiology is not infrequently different. Several of these diseases are characterized by abnormal bone metabolism and turnover with subsequent abnormalities in markers of bone turnover, rendering them useful adjuncts in the diagnostic process. As most rare bone diseases are inherited, genetic testing for implicated pathogenic variants, where known, is another relevant tool that can aid in diagnosis. While some skeletal disorders can be localized or monostotic, others can involve multiple skeletal sites and warrant imaging tools to localize them and determine the severity of disease and/or presence of complications as well as to assess bone quality and the potential risk of fractures. Rare bone disorders pose a great challenge in their diagnosis, ultimately resulting in delayed diagnosis, higher risk of complications and a poor quality of life in affected individuals. In this review we discuss the biochemical and radiological tools that can be utilized to diagnose selected orphan bone disorders, the clinical utility and limitations of these diagnostic tools, and areas where future research is warranted.

Deuterated Nanopolymers for Renal and Lymphatic Imaging via Quantitative Deuterium MRI.

Deuterium (2H) MRI is an emerging tool for noninvasive imaging. We explore the integration of 2H MRI with deuterated multifunctional nanopolymers for deuterated particle imaging (DPI). To this end, amine-terminated G5-polyamidoamine (PAMAM) dendrimers were labeled with deuterated acetyl surface groups, leading to highly 2H-loaded bioparticles, making them ideal for imaging studies. The accumulation of ∼5 nm PAMAM dendrimers in the kidneys could then be seen by 2H MRI with high submillimeter resolution. The natural abundance HDO signal provided an internal concentration reference to these measurements, leading to quantitative dynamic maps showing distinct nanopolymer uptakes within the renal compartments. Further, these nanopolymers allowed us to obtain in vivo maps of activity in the lymph nodes in an inflammatory rodent leg model, demonstrating these deuterated nanopolymers' potential as a novel class of contrast agents for the quantitative mapping of physiological processes.

Multichrome encoding-based multiplexed, spatially resolved imaging reveals single-cell RNA epigenetic modifications heterogeneity

Understanding the heterogeneity of epigenetic modifications within single cells is pivotal for unraveling the nature of the complexity of gene expression and cellular function. In this study, we have developed a strategy based on multichrome encoding and “AND” Boolean logic recognition for multiplexed, spatially resolved imaging of single-cell RNA epigenetic modifications, termed as PRoximity Exchange-assisted Encoding of Multichrome (PREEM). Through the implementation of this strategy, we can now map the expression and nuclear distribution of multiple site-specific RNA N6-methyladenosine (m6A) modifications at the single-molecule resolution level in single-cells, and reveal the previously unknown heterogeneity. Notably, we demonstrate how these patterns change after treatment with various drugs. Moreover, cyclic imaging with tailed DNA self-assembly further suggest the scalability and adaptability of PREEM’s design. As an innovative epigenetic modification imaging tool, PREEM not only broadens the horizons of single-cell epigenetics research, enabling joint analysis of multiple targets beyond the limitations of imaging channels, but also reveals cell-to-cell variability, thereby enhancing our capacity to explore cellular functions.

THE ROLE OF DYNAMIC CERVICAL MRI IN DETERMINING THE LEVEL OF POSTERIOR DECOMPRESSION IN CERVICAL SPONDYLOTIC MYELOPATHY.

Cervical spondylotic myelopathy (CSM) is a leading cause of spinal cord dysfunction in adults, often progressing silently. Static MRI is the standard imaging tool but may miss compression caused by neck movement. Dynamic MRI, by capturing flexion and extension views, provides a clearer picture of spinal cord compression, aiding surgical planning and improving outcomes. However, its use is limited due to higher costs and specialized requirements, making its clinical value essential to assess. Eighty-two CSM patients undergoing posterior decompression surgery were divided into two groups: static MRI-based planning (n=43) and combined static and dynamic MRI-based planning (n=39). Neurological outcomes were evaluated using modified Japanese Orthopaedic Association (mJOA) and Visual Analog Scale (VAS) scores pre- and postoperatively. Compression levels identified on static and dynamic MRI were compared. Demographic characteristics were similar between groups. Dynamic MRI identified additional compression levels, mainly at C5-C6 and C6-C7, in 18 patients. Patients in the dynamic MRI group showed significantly greater improvements in mJOA scores (mean: 15.8 ± 1.6 vs. 14.5 ± 1.8, p=0.01) and VAS scores (mean: 3.2 ± 1.4 vs. 4.5 ± 1.8, p=0.01) compared to the static MRI group. Dynamic cervical MRI enhances the identification of compression levels overlooked by static MRI, improving surgical precision and postoperative outcomes in CSM patients. Incorporating dynamic MRI into routine preoperative evaluations may be particularly beneficial for complex, multilevel cases.

Cardiovascular Risk Factor and Atherosclerosis in Rheumatoid Arthritis (RA).

To highlight advancements in managing traditional and rheumatoid arthritis (RA) specific risk factors and the impact of RA treatments on cardiovascular outcomes. Advancements in rheumatoid arthritis management have paralleled declining trends in cardiovascular disease risks. Biomarkers like CRP, Lipoprotein(a), Apolipoprotein B 100, and imaging tools such as coronary artery calcium scoring enhance cardiovascular risk stratification, particularly in intermediate-risk RA patients. While effective RA treatments, have demonstrated substantial cardiovascular benefits, subclass differences were noted in high-risk patients. Increased risk of cardiovascular disease is driven by chronic inflammation, altered lipid metabolism, and traditional risk factors. Effective RA treatment significantly lowers cardiovascular events. Standard treatment of hypertension, diabetes and hypercholesterolemia are effective and lowers RA disease activity and inflammatory markers. While RA is considered a risk enhancing state in calculating CV risk scores, currently there exists no RA disease -specific blood pressure, blood sugar or lipid targets.

Hybrid Data Augmentation Strategies for Robust Deep Learning Classification of Corneal Topographic MapTopographic Map.

Deep learning has emerged as a powerful tool in medical imaging, particularly for corneal topographic map classification. However, the scarcity of labeled data poses a significant challenge to achieving robust performance. This study investigates the impact of various data augmentation strategies on enhancing the performance of a customized convolutional neural network model for corneal topographic map classification. We propose a hybrid data augmentation approach that combines traditional transformations, generative adversarial networks, and specific generative models. Experimental results demonstrate that the hybrid data augmentation method, achieves the highest accuracy of 99.54%, significantly outperforming individual data augmentation techniques. This hybrid approach not only improves model accuracy but also mitigates overfitting issues, making it a promising solution for medical image classification tasks with limited data availability.

Combined Nanodrops Imaging and Ultrasound Localization Microscopy for Detecting Intracerebral Hemorrhage.

Advanced imaging methods are crucial for understanding stroke mechanisms and discovering effective treatments to reduce bleeding and enhance recovery. In pre-clinical in vivo stroke imaging, MRI, CT and optical imaging are commonly used to evaluate stroke outcomes in rodent models. However, MRI and CT have limited spatial resolution for rodent brains, and optical imaging is hindered by limited imaging depth of penetration. Here we introduce a novel contrast-enhanced ultrasound imaging method to overcome these challenges and characterize intracerebral hemorrhage with unique insights. We combined microbubble-based ultrasound localization microscopy (ULM) and nanodrop (ND)-based vessel leakage imaging to achieve simultaneous microvascular imaging and hemorrhage detection. ULM maps brain-wide cerebral vasculature with high spatial resolution and identifies microvascular impairments around hemorrhagic areas. NDs are sub-micron liquid-core particles that can extravasate due to blood-brain barrier breakdown, serving as positive contrast agents to detect hemorrhage sites. Our findings demonstrate that NDs could effectively accumulate in the hemorrhagic site and reveal the location of the bleeding areas upon activation by focused ultrasound beams. ULM further reveals the microvascular damage manifested in the form of reduced vascularity and decreased blood flow velocity across areas affected by the hemorrhagic stroke. The results demonstrate that sequential ULM combined with ND imaging is a useful imaging tool for basic in vivo research in stroke with rodent models where brain-wide detection of active bleeding and microvascular impairment are essential.

Modeling and Optimization of Distillation Column for Separation of 18O Isotope with Mathematical Model

Positron emission tomography (PET) is an advanced imaging tool for the diagnosis and staging of cancer tumors. This method is based on the detection of increased glycolytic activity in malignant cells, in which cell glucose is concentrated because of an increase in membrane glucose transporters, as well as an increase in some key enzymes, such as hexokinase, which are responsible for glucose phosphorylation. Therefore, for this type of imaging, drugs containing glucose are needed. On the other hand, with the expansion of the use of PET imaging devices, the need for drugs for this type of imaging method [fluorodeoxyglucose drug (FDG)] has also increased significantly. FDG is a drug tracer used in the medical imaging technique of PET. The production of FDG requires the production of 18F and, as a result, reaching 18O with a richness of more than 95%. There are various methods to produce oxygen with high richness. Among these methods, using a distillation column is a suitable method to produce oxygen, which has low efficiency and high production cost. Optimization of the distillation column can reduce the cost of producing high-rich oxygen. Numerical methods are one of the useful techniques for optimization. In this study, the distillation column has been computerized using mathematical models, and then by changing the number of inputs, including the height of the pipes, the temperature of the input of the distillation column has been optimized. Results show that the maximum separation of the desired isotope concentration in the distillation tower depends on the type of isotope desired and the condition of the device and is independent of the type of feed. Also, the input feed has no effect on the concentration distribution.

Diffusion transformer model with compact prior for low-dose PET reconstruction.

Positron emission tomography (PET) is an advanced medical imaging technique that plays a crucial role in non-invasive clinical diagnosis. However, while reducing radiation exposure through low-dose PET scans is beneficial for patient safety, it often results in insufficient statistical data. This scarcity of data poses significant challenges for accurately reconstructing high-quality images, which are essential for reliable diagnostic outcomes. In this research, we propose a diffusion transformer model (DTM) guided by joint compact prior (JCP) to enhance the reconstruction quality of low-dose PET imaging. In light of current research findings, we present a pioneering PET reconstruction model that integrates diffusion and transformer models for joint optimization. This model combines the powerful distribution mapping abilities of diffusion models with the capacity of transformers to capture long-range dependencies, offering significant advantages for low-dose PET reconstruction. Additionally, the incorporation of the lesion refining block and alternating direction method of multipliers (ADMM) enhance the recovery capability of lesion regions and preserves detail information, solving blurring problems in lesion areas and texture details of most deep learning frameworks. Experimental results demonstrate the effectiveness of DTM in enhancing image quality and preserving critical clinical information for low-dose PET scans. Our approach not only reduces radiation exposure risks but also provides a more reliable PET imaging tool for early disease detection and patient management.

Musculoskeletal ultrasound in rheumatologic diseases

Musculoskeletal ultrasound has become a valuable imaging tool in the diagnosis and management of rheumatologic disorders. Expertise in recognizing sonographic findings of pathology is the basis for its successful application in clinical use. This article will provide descriptions and a pictorial essay of ultrasound findings in common musculoskeletal manifestations of rheumatologic disorders.

The [18F] F-PSMA Probe: Chemical Perspectives.

This study discusses the chemical perspectives of the [18F]F-PSMA probe, a pivotal tool in prostate cancer imaging. [18F]Fluorine, a positron emitter with a half-life of 109.8 minutes, is produced in a cyclotron by bombarding [18O]-enriched targets with protons. The chemistry of this isotope parallels that of stable fluorine, facilitating its use in positron emission tomography (PET). The synthesis of [18F]F-PSMA involves a nucleophilic substitution (SN1) reaction, where [18F]fluoride ion replaces a leaving group in the precursor molecule. Prostate-specific membrane antigen (PSMA) is highly expressed in prostate cancer cells, making it a crucial target for imaging. PSMA-targeted radioligands, such as [68Ga]Ga-PSMA-11, [18F]F-DCFPyL, and [99mTc]Tc-PSMA-I&S, bind to the extracellular domain of PSMA, enabling precise imaging. The design of PSMA radiotracers incorporates specific targeting moieties, functional groups for radiolabeling, and linkers to maintain binding affinity and pharmacokinetics. Common linkers include aliphatic, aromatic, peptide-based, and polyethylene glycol structures, while functional groups like tosylate and PyTFP are used for efficient [18F]fluorination. This review aims to elucidate the main linker and reactions in order to optimize these components to improve imaging sensitivity and specificity in detecting prostate cancer.