Strategic research agenda for biomedical imaging

A Visual Raman Nano-Delivery System Based on Thiophene Polymer for Microtumor Detection

A visual Raman nano-delivery system (NS) is a widely used technique for the visualization and diagnosis of tumors and various biological processes. Thiophene-based organic polymers exhibit excellent biocompatibility, making them promising candidates for development as a visual Raman NS. However, materials based on thiophene face limitations due to their absorption spectra not matching with NIR (near-infrared) excitation light, which makes it difficult to achieve enhanced Raman properties and also introduces potential fluorescence interference. In this study, we introduce a donor-acceptor (D-A)-structured thiophene-based polymer, PBDB-T. Due to the D-A molecular modulation, PBDB-T exhibits a narrow bandgap of Eg = 2.63 eV and a red-shifted absorption spectrum, with the absorption edge extending into the NIR region. Upon optimal excitation with 785 nm light, it achieves ultra-strong pre-resonant Raman enhancement while avoiding fluorescence interference. As an intrinsically sensitive visual Raman NS for in vivo imaging, the PBDB-T NS enables the diagnosis of microtumor regions with dimensions of 0.5 mm × 0.9 mm, and also successfully diagnoses deeper tumor tissues, with an in vivo circulation half-life of 14.5 h. This research unveils the potential application of PBDB-T as a NIR excited visual Raman NS for microtumor diagnosis, introducing a new platform for the advancement of "Visualized Drug Delivery Systems". Moreover, the aforementioned platform enables the development of a more diverse range of targeted visual drug delivery methods, which can be tailored to specific regions.

Fractal analysis of 4D dynamic myocardial stress-CT perfusion imaging differentiates micro- and macrovascular ischemia in a multi-center proof-of-concept study

Fractal analysis of dynamic, four-dimensional computed tomography myocardial perfusion (4D-CTP) imaging might have potential for noninvasive differentiation of microvascular ischemia and macrovascular coronary artery disease (CAD) using fractal dimension (FD) as quantitative parameter for perfusion complexity. This multi-center proof-of-concept study included 30 rigorously characterized patients from the AMPLIFiED trial with nonoverlapping and confirmed microvascular ischemia (n_micro = 10), macrovascular CAD (n_macro = 10), or normal myocardial perfusion (n_normal = 10) with invasive coronary angiography and fractional flow reserve (FFR) measurements as reference standard. Perfusion complexity was comparatively high in normal perfusion (FD_normal = 4.49, interquartile range [IQR]:4.46-4.53), moderately reduced in microvascular ischemia (FD_micro = 4.37, IQR:4.36-4.37), and strongly reduced in macrovascular CAD (FD_macro = 4.26, IQR:4.24-4.27), which allowed to differentiate both ischemia types, p < 0.001. Fractal analysis agreed excellently with perfusion state (κ = 0.96, AUC = 0.98), whereas myocardial blood flow (MBF) showed moderate agreement (κ = 0.77, AUC = 0.78). For detecting CAD patients, fractal analysis outperformed MBF estimation with sensitivity and specificity of 100% and 85% versus 100% and 25%, p = 0.02. In conclusion, fractal analysis of 4D-CTP allows to differentiate microvascular from macrovascular ischemia and improves detection of hemodynamically significant CAD in comparison to MBF estimation.

Towards standardizing retinal optical coherence tomography angiography: a review

The visualization and assessment of retinal microvasculature are important in the study, diagnosis, monitoring, and guidance of treatment of ocular and systemic diseases. With the introduction of optical coherence tomography angiography (OCTA), it has become possible to visualize the retinal microvasculature volumetrically and without a contrast agent. Many lab-based and commercial clinical instruments, imaging protocols and data analysis methods and metrics, have been applied, often inconsistently, resulting in a confusing picture that represents a major barrier to progress in applying OCTA to reduce the burden of disease. Open data and software sharing, and cross-comparison and pooling of data from different studies are rare. These inabilities have impeded building the large databases of annotated OCTA images of healthy and diseased retinas that are necessary to study and define characteristics of specific conditions. This paper addresses the steps needed to standardize OCTA imaging of the human retina to address these limitations. Through review of the OCTA literature, we identify issues and inconsistencies and propose minimum standards for imaging protocols, data analysis methods, metrics, reporting of findings, and clinical practice and, where this is not possible, we identify areas that require further investigation. We hope that this paper will encourage the unification of imaging protocols in OCTA, promote transparency in the process of data collection, analysis, and reporting, and facilitate increasing the impact of OCTA on retinal healthcare delivery and life science investigations.

FDG-PET Radiomics for Response Monitoring in Non-Small-Cell Lung Cancer Treated with Radiation Therapy

Simple Summary

In this study, we strive to identify clinically relevant image feature (IF) changes during chemoradiation in patients with non-small-cell lung cancer (NSCLC) to be able to predict tumor responses in an early stage of treatment. All patients underwent static (3D) and respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability such as noise, resolution and movement through breathing. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment.

Abstract

The aim of this study is to identify clinically relevant image feature (IF) changes during chemoradiation and evaluate their efficacy in predicting treatment response. Patients with non-small-cell lung cancer (NSCLC) were enrolled in two prospective trials (STRIPE, PET-Plan). We evaluated 48 patients who underwent static (3D) and retrospectively-respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment. Predictions of overall survival (OS), local recurrence (LR) and distant metastasis (DM) were evaluated. From 135 IFs, only 17 satisfied the required criteria of being normally distributed across 4D PET and robust between 3D and 4D images. Changes during treatment in the area-under-the-curve of the cumulative standard-uptake-value histogram (δ_AUCCSH) within primary tumor discriminated (AUC = 0.87, Specificity = 0.78) patients with and without LR. The resulted prognostic model was validated with a different segmentation method (AUC = 0.83) and in a different patient cohort (AUC = 0.63). The quantification of tumor FDG heterogeneity by δ_AUCCSH during chemoradiation correlated with the incidence of local recurrence and might be recommended for monitoring treatment response in patients with NSCLC.