Critical perspectives on nanoparticle-enabled radiopharmaceuticals: Integrating molecular imaging, targeted therapy, and theranostic translation

The performance of current multimodal imaging contrast agents is often constrained by the tunability of nanomaterial structural design. Herein, the influence of nanostructure on the overall imaging performance of a composite nanomaterial for multimodal imaging of brain tumors is studied. Newly designed near‐infrared molecules (TC1) are encapsulated into nanocomposites with ultrasmall iron oxide nanoparticles (UIONPs), forming stable nanoagents for multimodal imaging and photothermal therapy (PTT). Through a modified nanoprecipitation method, the synthesis of nanocomposites denoted as HALF is realized, in which UIONPs are restricted to half of the nanosphere. Such a unique nanostructure that physically separates TC1 and UIONPs is found with capabilities of mitigating fluorescence quenching, preserving the good performance of photoacoustic imaging, and enhancing the magnetic resonance imaging signals. Decorated with a peptide ligand cRGD for better brain tumor targeting, HALF‐cRGD is evaluated both in vitro and in vivo as imaging contrast agents and photothermal therapeutic agents. The good imaging performance and PTT effect of HALF‐cRGD in mice models indicate that the rational design and control of nanostructures could optimize multimodal imaging performance using the same components.

Multimodal microscopic imaging with deep learning for highly effective diagnosis of breast cancer

High cardiovascular risk in chronic kidney disease (CKD) patients appears only partly attributable to atherosclerosis, with much of the remaining risk being ascribed to other vasculature abnormalities, including endothelial dysfunction, arterial stiffness and vascular calcification (VC). To date, these factors have been primarily studied in isolation or in dialysis patients. This study performed a global vascular assessment in moderate CKD and assessed the relationships with both traditional and novel risk factors. This was a prospective cross-sectional analysis of 120 patients (age 60 ± 10 years; estimated glomerular filtration rate 25-60 mL/min/1.73m(2)). Demographic, clinical and biochemical characterization was performed. VC was characterized by lateral lumbar radiograph; arterial stiffness by aortic pulse-wave velocity (PWV); atheroma burden by carotid intima-media thickness (cIMT) and endothelial function by flow-mediated dilation (FMD) of the brachial artery. VC was highly prevalent (74%), and FMD generally poor (FMDΔ 3.3 ± 3.3%). There were significant correlations between all vascular parameters; although these were predominantly explained by age. cIMT was independently associated with classical risks and also PWV (adjusted standardized β = 0.31, P = 0.001). However, traditional risks showed almost no independent associations with other vascular measurements. In contrast, serum phosphate and 1,25-dihydroxyvitamin D (1,25-OHD) correlated with PWV and the presence of VC, respectively. After adjustment, every 1 pg/mL increase in 1,25-OHD was related to a 3% reduction in the chance of VC (odds ratio 0.97; 95% confidence interval 0.94-1.00, P = 0.03). Medication use, HOMA-IR and C-reactive protein did not correlate with any of the vascular measures. This study demonstrates extensive vascular disease across multimodality imaging in moderate CKD. Atherosclerotic burden correlated with traditional risks and PWV, while higher 1,25-OHD was associated with less VC. The lack of association between renal function and imaging indices raises the possibility of a threshold, rather than graded uraemic effect on vascular health that warrants further exploration.

Postmodernism emerged in the mid-20th century in the context of postwar Europe where philosophers and artists were taking increasingly skeptical and critical positions on modernist thinking and practice. Postmodernism is not a single organized and coherent perspective; it is a collection of related philosophies, techniques, models, and perspectives that take a skeptical and critical perspective on thinking and practice. Ontologically, postmodernism is predicated on the belief that power and its underlying meanings, manipulations, and ideologies shape our ability to act in and think about the world. Epistemologically, postmodernism seeks to explore and understand underlying meanings, structures, and intents in the world and to consider alternative explanations and interpretations for them. Axiologically, postmodernism can be used to analyze value in the context of inequity, oppression, and hegemony within social systems and structures. Due to the lack of coherence within postmodernist thought, there is no one definitive methodological stance. However, there are many postmodernism-informed methodological stances, which vary both in terms of what is examined and how it is examined. As an approach within medical education, postmodernist perspectives can help to expose and analyze the political and ideological positioning of much of what is done, particularly in the interests of addressing systemic problems of justice and equity. It is somewhat paradoxical that postmodernism allows researchers to challenge the nature and expression of truth, and it allows them to problematize and deconstruct the ideologies and agendas of those who are themselves challenging the nature and expression of truth.

Interpretation of Subretinal Fluid Using OCT in Intermediate Age-Related Macular Degeneration

Multimodal retinal imaging to detect and understand Alzheimer's and Parkinson's disease.

Multimodal medical image fusion towards future research: A review

Potential Clinical Utility and Feasibility of Combined Left Atrial Appendage Closure and Positioning of Miniaturized Pacemaker Through a Single Right Femoral Vein Access.

X-ray computed tomography (CT) imaging plays an essential role in disease diagnosis due to its noninvasive, painless mode and superior penetration depth. However, the resolution of the soft tissue ...

The GaoFen-3 (GF-3) satellite is the only synthetic aperture radar (SAR) satellite in the High-Resolution Earth Observation System Project, which is the first C-band full-polarization SAR satellite in China. In this paper, we proposed some error sources-based weight strategies to improve the geometric performance of multi-mode GF-3 satellite SAR images without using ground control points (GCPs). To get enough tie points, a robust SAR image registration method and the SAR-features from accelerated segment test (SAR-FAST) method is used to achieve the image registration and tie point extraction. Then, the original position of these tie points in object-space is calculated with the help of the space intersection method. With the dataset clustered by the density-based spatial clustering of applications with noise (DBSCAN) algorithm, we undertake the block adjustment with a bias-compensated rational function model (RFM) aided to improve the geometric performance of these multi-mode GF-3 satellite SAR images. Different weight strategies are proposed to develop the normal equation matrix according to the error sources analysis of GF-3 satellite SAR images, and the preconditioned conjugate gradient (PCG) method is utilized to solve the normal equation. The experimental results indicate that our proposed method can improve the geometric positioning accuracy of GF-3 satellite SAR images within 2 pixels.

Multi-modality imaging provides coregistered PET-CT and SPECT-CT images; however such multi-modality workflows usually consist of sequential scans from the individual imaging components for each modality. This typical workflow may result in long scan times limiting throughput of the imaging system. Conversely, acquiring multi-modality data simultaneously may improve correlation and registration of images, improve temporal alignment of the acquired data, increase imaging throughput, and benefit the scanned subject by minimizing time under anesthetic. In this work, we demonstrate the feasibility and procedure for modifying a commercially available preclinical SPECT-CT platform to enable simultaneous SPECT-CT acquisition. We also evaluate the performance of simultaneous SPECT-CT tomographic imaging with this modified system. Performance was accessed using a 57Co source and image quality was evaluated with 99mTc phantoms in a series of simultaneous SPECT-CT scans.

This study aimed to examine the diagnosis performance of 99mTc-methoxyisobutylisonitrisonitrile (99mTc-MIBI) and multimodality imaging [ultrasound, single-photon emission computed tomography/computed tomography (SPECT/CT)] for hyperparathyroidism (HPT). From Nov. 2009 to Dec. 2015, clinical data of a total of 43 HPT patients (16 males and 27 females; 26-70 years old, average age: 51.60±10.66 years old) were retrospectively analyzed. Among them, 19 patients with primary hyperparathyroidism (PHPT) underwent 99mTc-MIBI planar imaging, 24 [15 with PHPT and 9 with secondary hyperparathyroidism (SHPT)] underwent SPECT/CT hybrid imaging, and 41 (33 with PHPT and 8 with SHPT) had neck ultrasound imaging. Final diagnosis was determined by pathological examination after surgery. The positive rate was compared between different imaging modalities, and the correlation analysis was conducted between imaging results and lesion size or serum parathyroid hormone (PTH) level. The results showed that the total positive rates of 99mTc-MIBI imaging, ultrasound, and the two combined imaging in the 43 HPT cases were 90.70% (39/43), 58.54% (24/41), and 100% (41/41), respectively. According to lesion numbers, the positive rates were 79.10% (53/67), 53.23% (33/62), and 88.71% (55/62), respectively. SPECT/CT hybrid images were positive in all the 24 patients who underwent this examination. The mean maximum diameters of the lesions in 99mTc-MIBI positive and negative patients were 1.96±0.95 cm and 1.36±0.67 cm respectively, with statistically significant difference noted (P=0.03). The T/NT of 99mTc-MIBI imaging at the early phase was correlated positively with serum PTH level (r=0.40, P=0.01). The T/NT of 99mTc-MIBI imaging at both the early phase and the delay phase was correlated positively with lesion size (r=0.51, and r=0.45, respectively; P<0.01 for both). It was concluded that 99mTc-MIBI imaging presents significant value for location diagnosis of HPT, especially when combined with SPECT/CT hybrid imaging or ultrasound. The 99mTc-MIBI uptake correlates positively with serum PTH level and lesion size.

Simultaneous photoacoustic microscopy, spectral-domain optical coherence tomography, and fluorescein microscopy multi-modality retinal imaging

This study assessed the predictive performance and relative importance of clinical, multimodal imaging, and angiographic characteristics for predicting the clinical outcome of endovascular treatment for acute ischemic stroke. A consecutive series of 246 patients with acute ischemic stroke and large vessel occlusion in the anterior circulation who underwent endovascular treatment between April 2014 and January 2018 was analyzed. Clinical, conventional imaging (electronic Alberta Stroke Program Early CT Score, acute ischemic volume, site of vessel occlusion, and collateral score), and advanced imaging characteristics (CT-perfusion with quantification of ischemic penumbra and infarct core volumes) before treatment as well as angiographic (interval groin puncture-recanalization, modified Thrombolysis in Cerebral Infarction score) and postinterventional clinical (National Institutes of Health Stroke Scale score after 24 hours) and imaging characteristics (electronic Alberta Stroke Program Early CT Score, final infarction volume after 18-36 hours) were assessed. The modified Rankin Scale (mRS) score at 90 days (mRS-90) was used to measure patient outcome (favorable outcome: mRS-90 ≤2 versus unfavorable outcome: mRS-90 >2). Machine-learning with gradient boosting classifiers was used to assess the performance and relative importance of the extracted characteristics for predicting mRS-90. Baseline clinical and conventional imaging characteristics predicted mRS-90 with an area under the receiver operating characteristics curve of 0.740 (95% CI, 0.733-0.747) and an accuracy of 0.711 (95% CI, 0.705-0.717). Advanced imaging with CT-perfusion did not improved the predictive performance (area under the receiver operating characteristics curve, 0.747 [95% CI, 0.740-0.755]; accuracy, 0.720 [95% CI, 0.714-0.727]; P=0.150). Further inclusion of angiographic and postinterventional characteristics significantly improved the predictive performance (area under the receiver operating characteristics curve, 0.856 [95% CI, 0.850-0.861]; accuracy, 0.804 [95% CI, 0.799-0.810]; P<0.001). The most important parameters for predicting mRS 90 were National Institutes of Health Stroke Scale score after 24 hours (importance =100%), premorbid mRS score (importance =44%) and final infarction volume on postinterventional CT after 18 to 36 hours (importance =32%). Integrative assessment of clinical, multimodal imaging, and angiographic characteristics with machine-learning allowed to accurately predict the clinical outcome following endovascular treatment for acute ischemic stroke. Thereby, premorbid mRS was the most important clinical predictor for mRS-90, and the final infarction volume was the most important imaging predictor, while the extent of hemodynamic impairment on CT-perfusion before treatment had limited importance.

Earth observation using remote sensing data is a trending research field across the globe. In this perspective, image registration is a mandatory data processing step for any kind of time series data analytics. Feature-based image registration is one of the prominent categories for superimposing multi-temporal and multi-modal images over each other. The paper provides a comprehensive and comparative survey of feature detection/description techniques for remote sensing images. In addition, outlier removal algorithms are explored in detail to generate putative keypoint correspondences for accurate transformation parameter estimation. The experiments are conducted on multiple remote sensing image pairs comprising visible, Synthetic Aperture Radar (SAR) and infrared images that provide diverse characteristics of the feature target. The co-registration accuracy is quantified for all possible combinations of feature detection/description with outlier removal, and best amalgamation is visually verified to check sub-pixel spatial alignment by swiping multi-temporal or multi-modal images over each other. It has been found that SIFT performs better in optical image registration, whereas A-KAZE feature detection has an upper edge at SAR image registration task. Marginalizing Sample Consensus (MAGSAC) and Mode Guided (MG) based outlier removal techniques achieves better pruning performance for multi-temporal optical and SAR images respectively. The comparative evaluation indicates that Motion Smoothness Constraint (MSC) optimization shows optimal performance for multi-modal remote sensing images. The best possible Root Mean Square Error (RMSE) achieved for multi-temporal optical images is 0.44 pixel whereas for multi-temporal SAR images, it is 0.46 pixels. The RMSE achieved for multi-modal images is 0.48 pixel using combination of SIFT with MSC.