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High-contrast, high-resolution imaging of biomedical specimens is indispensable for studying organ function and pathologies. Conventional histology, the gold standard for soft-tissue visualization, is limited by its anisotropic spatial resolution, elaborate sample preparation, and lack of quantitative image information. X-ray absorption or phase tomography have been identified as promising alternatives enabling non-destructive, distortion-free three-dimensional (3D) imaging. However, reaching sufficient contrast and resolution with a simple experimental procedure remains a major challenge. Here, we present a solution based on x-ray phase tomography through speckle-based imaging (SBI). We demonstrate on a mouse kidney that SBI delivers comprehensive 3D maps of hydrated, unstained soft tissue, revealing its microstructure and delivering quantitative tissue-density values at a density resolution of better than 2 mg/cm 3 and spatial resolution of better than 8 µm. We expect that SBI virtual histology will find widespread application in biomedicine and will open up new possibilities for research and histopathology.

A contrast agent for X-ray micro computed tomography (μCT), called XlinCA, that combines reliable perfusion and permanent retention and contrast properties, was developed for ex vivo imaging.

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Abstract

IntroductionLike a fingerprint, ear shape is a unique personal feature that should be reconstructed with a high fidelity during reconstructive surgery. Ear cartilage tissue engineering (TE) advantageously offers the possibility to use novel 3D manufacturing techniques to reconstruct the ear, thus allowing for a detailed auricular shape. However it also requires detailed patient-specific images of the 3D cartilage structures of the patient’s intact contralateral ear (if available). Therefore the aim of this study was to develop and evaluate an imaging strategy for acquiring patient-specific ear cartilage shape, with sufficient precision and accuracy for use in a clinical setting.Methods and MaterialsMagnetic resonance imaging (MRI) was performed on 14 volunteer and six cadaveric auricles and manually segmented. Reproducibility of cartilage volume (Cg.V), surface (Cg.S) and thickness (Cg.Th) was assessed, to determine whether raters could repeatedly define the same volume of interest. Additionally, six cadaveric auricles were harvested, scanned and segmented using the same procedure, then dissected and scanned using high resolution micro-CT. Correlation between MR and micro-CT measurements was assessed to determine accuracy.ResultsGood inter- and intra-rater reproducibility was observed (precision errors <4% for Cg.S and <9% for Cg.V and Cg.Th). Intraclass correlations were good for Cg.V and Cg.S (>0.82), but low for Cg.Th (<0.23) due to similar average Cg.Th between patients. However Pearson’s coefficients showed that the ability to detect local cartilage shape variations is unaffected. Good correlation between clinical MRI and micro-CT (r>0.95) demonstrated high accuracy.Discussion and ConclusionThis study demonstrated that precision and accuracy of the proposed method was high enough to detect patient-specific variation in ear cartilage geometry. The present study provides a clinical strategy to access the necessary information required for the production of 3D ear scaffolds for TE purposes, including detailed patient-specific shape. Furthermore, the protocol is applicable in daily clinical practice with existing infrastructure.

Hard X-ray tomography with Paganin's widespread single-distance phase retrieval filter improves contrast-to-noise ratio (CNR) while reducing spatial resolution (SR). We demonstrate that a Gaussian filter provided larger CNR at high SR with interpretable density measurements for two medically relevant soft tissue samples. Paganin's filter produced larger CNR at low SR, though a priori assumptions were generally false and image quality gains diminish for CNR > 1. Therefore, simple absorption measurements of low-Z specimens combined with Gaussian filtering can provide improved image quality and model-independent density measurements compared to single-distance phase retrieval.