Elastic transformation of histological slices allows precise co-registration with microCT data sets for a refined virtual histology approach

Multiscale and multimodal imaging for three-dimensional vascular and histomorphological organ structure analysis of the pancreas

Exocrine and endocrine pancreas are interconnected anatomically and functionally, with vasculature facilitating bidirectional communication. Our understanding of this network remains limited, largely due to two-dimensional histology and missing combination with three-dimensional imaging. In this study, a multiscale 3D-imaging process was used to analyze a porcine pancreas. Clinical computed tomography, digital volume tomography, micro-computed tomography and Synchrotron-based propagation-based imaging were applied consecutively. Fields of view correlated inversely with attainable resolution from a whole organism level down to capillary structures with a voxel edge length of 2.0 µm. Segmented vascular networks from 3D-imaging data were correlated with tissue sections stained by immunohistochemistry and revealed highly vascularized regions to be intra-islet capillaries of islets of Langerhans. Generated 3D-datasets allowed for three-dimensional qualitative and quantitative organ and vessel structure analysis. Beyond this study, the method shows potential for application across a wide range of patho-morphology analyses and might possibly provide microstructural blueprints for biotissue engineering.

Prediction of preoperative microvascular invasion by dynamic radiomic analysis based on contrast-enhanced computed tomography

PURPOSE

Microvascular invasion (MVI) is a common complication of hepatocellular carcinoma (HCC) surgery, which is an important predictor of reduced surgical prognosis. This study aimed to develop a fully automated diagnostic model to predict pre-surgical MVI based on four-phase dynamic CT images.

METHODS

A total of 140 patients with HCC from two centers were retrospectively included (training set, n = 98; testing set, n = 42). All CT phases were aligned to the portal venous phase, and were then used to train a deep-learning model for liver tumor segmentation. Radiomics features were extracted from the tumor areas of original CT phases and pairwise subtraction images, as well as peritumoral features. Lastly, linear discriminant analysis (LDA) models were trained based on clinical features, radiomics features, and hybrid features, respectively. Models were evaluated by area under curve (AUC), accuracy, sensitivity, specificity, positive and negative predictive values (PPV and NPV).

RESULTS

Overall, 86 and 54 patients with MVI- (age, 55.92 ± 9.62 years; 68 men) and MVI+ (age, 53.59 ± 11.47 years; 43 men) were included. Average dice coefficients of liver tumor segmentation were 0.89 and 0.82 in training and testing sets, respectively. The model based on radiomics (AUC = 0.865, 95% CI: 0.725-0.951) showed slightly better performance than that based on clinical features (AUC = 0.841, 95% CI: 0.696-0.936). The classification model based on hybrid features achieved better performance in both training (AUC = 0.955, 95% CI: 0.893-0.987) and testing sets (AUC = 0.913, 95% CI: 0.785-0.978), compared with models based on clinical and radiomics features (p-value < 0.05). Moreover, the hybrid model also provided the best accuracy (0.857), sensitivity (0.875), and NPV (0.917).

CONCLUSION

The classification model based on multimodal intra- and peri-tumoral radiomics features can well predict HCC patients with MVI.

Characterization of transient and progressive pulmonary fibrosis by spatially correlated phase contrast microCT, classical histopathology and atomic force microscopy

Pulmonary fibrosis (PF) is a severe and progressive condition in which the lung becomes scarred over time resulting in pulmonary function impairment. Classical histopathology remains an important tool for micro-structural tissue assessment in the diagnosis of PF. A novel workflow based on spatial correlated propagation-based phase-contrast micro computed tomography (PBI-microCT), atomic force microscopy (AFM) and histopathology was developed and applied to two different preclinical mouse models of PF - the commonly used and well characterized Bleomycin-induced PF and a novel mouse model for progressive PF caused by conditional Nedd4-2 KO. The aim was to integrate structural and mechanical features from hallmarks of fibrotic lung tissue remodeling. PBI-microCT was used to assess structural alteration in whole fixed and paraffin embedded lungs, allowing for identification of fibrotic foci within the 3D context of the entire organ and facilitating targeted microtome sectioning of planes of interest for subsequent histopathology. Subsequently, these sections of interest were subjected to AFM to assess changes in the local tissue stiffness of previously identified structures of interest. 3D whole organ analysis showed clear morphological differences in 3D tissue porosity between transient and progressive PF and control lungs. By integrating the results obtained from targeted AFM analysis, it was possible to discriminate between the Bleomycin model and the novel conditional Nedd4-2 KO model using agglomerative cluster analysis. As our workflow for 3D spatial correlation of PBI, targeted histopathology and subsequent AFM is tailored around the standard procedure of formalin-fixed paraffin-embedded (FFPE) tissue specimens, it may be a powerful tool for the comprehensive tissue assessment beyond the scope of PF and preclinical research.

Evaluation of MR-safe bioptomes for MR-guided endomyocardial biopsy in minipigs: a potential radiation-free clinical approach

BACKGROUND

Diagnostic accuracy of endomyocardial biopsy could improve if clinically safe magnetic resonance (MR)-compatible bioptomes were available. We explored two novel MR-compatible cardiac bioptomes for performance, safety, and clinical viability, employing in vivo minipig trials and phase-contrast synchrotron radiation computed microtomography (SRµCT).

METHODS

Analysis of ex vivo obtained pig endomyocardial biopsies was performed using phase-contrast SRµCT and conventional two-dimensional histology. The technical performance was evaluated by measuring volume, inner and outer integrities, compression, and histological diagnostic value in 3 sets (6 per set) of biopsies for each experimental bioptome. The bioptomes were tested in vivo in 3 healthy minipigs per bioptome. The clinical feasibility was evaluated by procedural and cutting success as well as histological diagnostic value.

RESULTS

The bioptome with the 'grind-grind' design achieved similar values to control in compression (p = 0.822), inner (p = 0.628), and outer (p = 0.507), integrities ex vivo. It showed a better performance in the in vivo real-time MRI setting demonstrating a higher cutting success (91.7%) than the 'grind-anvil' (86.2%) design. In both ex vivo and in vivo evaluations, the 'grind-grind' design displayed sufficient diagnostic value (83% and 95%). The 'grind-anvil' design showed adequate diagnostic value both ex vivo and in vivo (78% and 87.5%) but was not comparable to control according to the three-dimensional (3D) analysis.

CONCLUSION

A novel MR-compatible bioptome was identified as plausible in a clinical setting. Additionally, SRµCT and subsequent 3D structural analysis could be valuable in the label-free investigation of myocardial tissue at a micrometer level.

RELEVANCE STATEMENT

Implementation of MR-guided biopsy can improve animal studies on structural myocardial changes at any point in an experimental setup. With further improvements in guiding catheters, MR-guided biopsy, using the new bioptome, has a potential to increase quality and diagnostic accuracy in patients both with structural and inflammatory cardiomyopathies.

KEY POINTS

• Novel MR-compatible bioptomes show promise for a clinical application. • SRµCT enabled detailed analysis of endomyocardial biopsies. • The bioptomes showed adequate in vivo performance without major complications.

Feasibility and safety of synchrotron-based X-ray phase contrast imaging as a technique complementary to histopathology analysis

X-ray phase contrast imaging (X-PCI) is a powerful technique for high-resolution, three-dimensional imaging of soft tissue samples in a non-destructive manner. In this technical report, we assess the quality of standard histopathological techniques performed on formalin-fixed, paraffin-embedded (FFPE) human tissue samples that have been irradiated with different doses of X-rays in the context of an X-PCI experiment. The data from this study demonstrate that routine histochemical and immunohistochemical staining quality as well as DNA and RNA analyses are not affected by previous X-PCI on human FFPE samples. From these data we conclude it is feasible and acceptable to perform X-PCI on FFPE human biopsies.

Hard X-ray full-field nanoimaging using a direct photon-counting detector

Full-field X-ray nanoimaging is a widely used tool in a broad range of scientific areas. In particular, for low-absorbing biological or medical samples, phase contrast methods have to be considered. Three well established phase contrast methods at the nanoscale are transmission X-ray microscopy with Zernike phase contrast, near-field holography and near-field ptychography. The high spatial resolution, however, often comes with the drawback of a lower signal-to-noise ratio and significantly longer scan times, compared with microimaging. In order to tackle these challenges a single-photon-counting detector has been implemented at the nanoimaging endstation of the beamline P05 at PETRA III (DESY, Hamburg) operated by Helmholtz-Zentrum Hereon. Thanks to the long sample-to-detector distance available, spatial resolutions of below 100 nm were reached in all three presented nanoimaging techniques. This work shows that a single-photon-counting detector in combination with a long sample-to-detector distance allows one to increase the time resolution for in situ nanoimaging, while keeping a high signal-to-noise level.

Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging

Classical analysis of biological samples requires the destruction of the tissue's integrity by cutting or grinding it down to thin slices for (Immuno)-histochemical staining and microscopic analysis. Despite high specificity, encoded in the stained 2D section of the whole tissue, the structural information, especially 3D information, is limited. Computed tomography (CT) or magnetic resonance imaging (MRI) scans performed prior to sectioning in combination with image registration algorithms provide an opportunity to regain access to morphological characteristics as well as to relate histological findings to the 3D structure of the local tissue environment. This review provides a summary of prevalent literature addressing the problem of multimodal coregistration of hard- and soft-tissue in microscopy and tomography. Grouped according to the complexity of the dimensions, including image-to-volume (2D ⟶ 3D), image-to-image (2D ⟶ 2D), and volume-to-volume (3D ⟶ 3D), selected currently applied approaches are investigated by comparing the method accuracy with respect to the limiting resolution of the tomography. Correlation of multimodal imaging could position itself as a useful tool allowing for precise histological diagnostic and allow the a priori planning of tissue extraction like biopsies.