BF2-Azadipyrromethene Fluorophores for Intraoperative Vital Structure Identification.

A series of mono- and bis-polyethylene glycol (PEG)-substituted BF2-azadipyrromethene fluorophores have been synthesized with emissions in the near-infrared region (700-800 nm) for the purpose of fluorescence guided intraoperative imaging; chiefly ureter imaging. The Bis-PEGylation of fluorophores resulted in higher aqueous fluorescence quantum yields, with PEG chain lengths of 2.9 to 4.6 kDa being optimal. Fluorescence ureter identification was possible in a rodent model with the preference for renal excretion notable through comparative fluorescence intensities from the ureters, kidneys and liver. Ureteral identification was also successfully performed in a larger animal porcine model under abdominal surgical conditions. Three tested doses of 0.5, 0.25 and 0.1 mg/kg all successfully identified fluorescent ureters within 20 min of administration which was sustained up to 120 min. 3-D emission heat map imaging allowed the spatial and temporal changes in intensity due to the distinctive peristaltic waves of urine being transferred from the kidneys to the bladder to be identified. As the emission of these fluorophores could be spectrally distinguished from the clinically-used perfusion dye indocyanine green, it is envisaged that their combined use could be a step towards intraoperative colour coding of different tissues.

Dynamic NIR Fluorescence Imaging and Machine Learning Framework for Stratifying High vs. Low Notch-Dll4 Expressing Host Microenvironment in Triple-Negative Breast Cancer.

Delta like canonical notch ligand 4 (Dll4) expression levels in tumors are known to affect the efficacy of cancer therapies. This study aimed to develop a model to predict Dll4 expression levels in tumors using dynamic enhanced near-infrared (NIR) imaging with indocyanine green (ICG). Two rat-based consomic xenograft (CXM) strains of breast cancer with different Dll4 expression levels and eight congenic xenograft strains were studied. Principal component analysis (PCA) was used to visualize and segment tumors, and modified PCA techniques identified and analyzed tumor and normal regions of interest (ROIs). The average NIR intensity for each ROI was calculated from pixel brightness at each time interval, yielding easily interpretable features including the slope of initial ICG uptake, time to peak perfusion, and rate of ICG intensity change after reaching half-maximum intensity. Machine learning algorithms were applied to select discriminative features for classification, and model performance was evaluated with a confusion matrix, receiver operating characteristic curve, and area under the curve. The selected machine learning methods accurately identified host Dll4 expression alterations with sensitivity and specificity above 90%. This may enable stratification of patients for Dll4 targeted therapies. NIR imaging with ICG can noninvasively assess Dll4 expression levels in tumors and aid in effective decision making for cancer therapy.

Dual Color Imaging from a Single BF2-Azadipyrromethene Fluorophore Demonstrated in vivo for Lymph Node Identification.

Dual emissions at ~700 and 800 nm have been achieved from a single NIR-AZA fluorophore 1 by establishing parameters in which it can exist in either its isolated molecular or aggregated states. Dual near infrared (NIR) fluorescence color lymph node (LN) mapping with 1 was achieved in a large-animal porcine model, with injection site, channels and nodes all detectable at both 700 and 800 nm using a preclinical open camera system. The fluorophore was also compatible with imaging using two clinical instruments for fluorescence guided surgery. Methods: An NIR-AZA fluorophore with hydrophilic and phobic features was synthesised in a straightforward manner and its aggregation properties characterised spectroscopically and by TEM imaging. Toxicity was assessed in a rodent model and dual color fluorescence imaging evaluated by lymph node mapping in a large animal porcine models and in ex-vivo human tissue specimen. Results: Dual color fluorescence imaging has been achieved in the highly complex biomedical scenario of lymph node mapping. Emissions at 700 and 800 nm can be achieved from a single fluorophore by establishing molecular and aggregate forms. Fluorophore was compatible with clinical systems for fluorescence guided surgery and no toxicity was observed in high dosage testing. Conclusion: A new, biomedical compatible form of NIR-dual emission wavelength imaging has been established using a readily accessible fluorophore with significant scope for clinical translation.

Practical Perfusion Quantification in Multispectral Endoscopic Video: Using the Minutes after ICG Administration to Assess Tissue Pathology.

The wide availability of near infrared light sources in interventional medical imaging stacks enables non-invasive quantification of perfusion by using fluorescent dyes, typically Indocyanine Green (ICG). Due to their often leaky and chaotic vasculatures, intravenously administered ICG perfuses through cancerous tissues differently. We investigate here how a few characteristic values derived from the time series of fluorescence can be used in simple machine learning algorithms to distinguish benign lesions from cancers. These features capture the initial uptake of ICG in the colon, its peak fluorescence, and its early wash-out. By using simple, explainable algorithms we demonstrate, in clinical cases, that sensitivity (specificity) rates of over 95% (95%) for cancer classification can be achieved.

Using Contrast Motion to Generate Patient-Specific Blood Flow Simulations During Invasive Coronary Angiography.

Virtual fractional flow reserve (vFFR) is an emerging technology employing patient-specific computational fluid dynamics (CFD) simulations to infer the hemodynamic significance of a coronary stenosis. Patient-specific boundary conditions are an important aspect of this approach and while most efforts make use of lumped parameter models to capture key phenomena, they lack the ability to specify the associated parameters on a patient-specific basis. When applying vFFR in a catheter laboratory setting using X-ray angiograms as the basis for creating the simulations, there is some indirect functional information available through the observation of the radio-opaque contrast agent motion. In this work, we present a novel method for tuning the lumped parameter arterial resistances (commonly incorporated in such simulations), based on simulating the physics of the contrast motion and comparing the observed and simulated arrival times of the contrast front at key points within a coronary tree. We present proof of principle results on a synthetically generated coronary tree comprised of multiple segments, demonstrating that the method can successfully optimize the arterial resistances to reconstruct the underlying velocity and pressure fields, providing a potential new means to improve the patient specificity of simulation-based technologies in this area.