Brooke Tornifoglio

This study evaluates the relationship between two Siemens SWE modalities, Virtual Touch Imaging and Quantification (VTIQ) and Virtual Touch Quantification (VTq). It then compares VTIQ-derived apparent moduli and mechanically-derived engineering moduli in ex vivo porcine adipose tissue under controlled compression. Fresh porcine adipose tissue (N=3) was prepared for uniaxial compression testing (n = 6/donor) at 5 mm/min to 55% strain and for SWE (n = 3/donor) using a Siemens ACUSON S2000 system under step-wise compression to 50% in 10% increments. Mechanical engineering moduli were calculated at ±2% strain windows between 10-50% compression. VTIQ moduli were extracted from colour-mapped elastograms using an in-house MATLAB script. Two-way ANOVA with Sidak post hoc comparisons, and regression and correlation analyses were performed. VTIQ yielded significantly higher moduli than VTq across all donor groups (p<0.0001), with weak-to-moderate correlations (R2=0.03-0.31), indicating the methods are not interchangeable for adipose tissue characterisation. Both VTIQ and uniaxial compression demonstrated a significant increase in stiffness with increasing compression; however, moduli diverged substantially. VTIQ moduli ranged from 68.33±46.21 (10% compression) to 129.98±110.67 kPa (50% compression) in a linear trend, while mechanically-derived moduli increased more exponentially from 5.76±1.39 kPa (10% compression) to 848.19±437.65 kPa (50% compression). Moderate-to-strong positive correlations were observed between methods (R2 = 0.27-0.7). VTIQ demonstrated the ability to capture compression-dependent strain-stiffening in porcine adipose tissue, supporting its potential as a non-invasive relative stiffness indicator. Despite differences in the physical properties measured by SWE and uniaxial compression, both methods captured changes in tissue mechanical behaviour with increasing compression.

Visualising and quantifying vascular 3D microstructure are essential for linking it to mechanics and disease. This study evaluated Phospho-Tungstic Acid (PTA) and 1:2 Hafnium-substituted Wells Dawson Polyoxometalate (1:2 Hf-POM) as Contrast-Enhancing Staining Agents (CESAs) for X-ray based 3D Histology (X3DH) using Contrast-Enhanced Micro-focus Computed Tomography (CECT), as alternatives to classical 2D histology for visualising and quantifying collagen and elastin.Native and enzymatically digested porcine carotid artery segments, with varying elastin and collagen content, were CESA-stained and μCT-imaged to generate X3DH data, used to calculate Elastin-Stained Volume Fraction (E-SVF). Equivalent CESA-stained and unstained sections underwent Verhoeff’s (VH), Picrosirius Red (PR), and Haematoxylin–Eosin (H&E) histology to measure Elastin-Stained Area Fraction (E-SAF), Collagen-SAF (C-SAF), and cell density. X3DH results were compared with histology to evaluate correspondence and staining effects. Both CESAs produced strong signal colocalisation with elastic lamellae and weaker staining in the remaining ECM.E-SVF for both CESAs correlated strongly with E-SAF, but E-SVF values were about two times lower than E-SAF (r2PTA=0.86, p<0.0001, slopePTA=0.42 | r21:2-Hf-POM=0.86, p<0.0001, slope1:2-Hf-POM=0.49). This highlights CECT as a non-destructive, accurate method for quantifying vascular microstructure with fewer artefacts than classical 2D histology. VH and PR staining were visually and quantitatively (±10% E-SAF and C-SAF equivalence) unaffected by CESA-staining. PTA-staining with cryopreservation caused loss of nucleic contrast, while 1:2 Hf-POM influenced ECM haematoxylin uptake, reducing nuclei visualisation and cell count accuracy in H&E histology. Both CESAs bind non-specifically but preferentially to elastin, enabling reliable quantification. However, vascular collagen remains difficult to visualise as ECM is non-specifically stained.

Background Neovascularisation, the formation of new vessels within atherosclerotic plaques, has been associated with plaque progression and intraplaque haemorrhage. However, the relationship between neovascularisation and mechanical failure of plaques remains unclear. A better understanding of this link could improve rupture risk prediction beyond traditional reliance on arterial stenosis. Methods Human carotid plaques (n=7) from endarterectomy were sectioned into circumferential strips (n=25) and tested under uniaxial tension with digital image correlation (DIC) to determine ultimate tensile (UT) stress, UT strain, and elastic moduli. Immunohistochemistry with CD31 staining quantified neovascularisation. K-means clustering based on UT stress and strain identified mechanical phenotypes. A decision tree classifier was trained using neovascularisation percentage as the predictor. Results Neovascularisation showed a moderate negative correlation with UT strain (r = -0.46, p = 0.028), indicating plaques with greater neovascularisation failed at lower strains. K-means clustering identified two groups: Cluster 1 (lower UT strain) had significantly higher neovascularisation (median 2.21%) and greater initial stiffness than Cluster 2 (median 1.27%, p < 0.01). The decision tree using neovascularisation alone achieved 78.3% classification accuracy, with an area under the curve of 0.78. DIC analysis revealed rupture consistently occurred at regions of elevated local strain. Conclusion This study demonstrates a link between neovascularisation and mechanical failure in atherosclerotic plaques. Higher neovascularisation was associated with lower UT strain, suggesting it contributes to mechanical instability. These findings support the role of neovascularisation as a marker of plaque vulnerability and encourage its integration into ultrasound-based risk assessment strategies, such as contrast-enhanced ultrasound.

Purpose: The aim is to establish the relationship between carotid susceptibility and microstructural components in diseased carotid arteries. Methods: Excised cadaveric carotid arteries ( n = 5) were scanned using high‐resolution QSM at 7 Tesla. After ex vivo imaging, all samples were brought to histology and stained for elastin, collagen, cells, and calcium. An image registration pipeline was used in combination with semi‐quantitative, regional histology analysis to evaluate relationships between MRI and microstructural components. Results: Weak, non‐significant ( p > 0.05) correlations were found between all components and regional magnitude and R ₂ * measurements. A significant, moderate negative correlation between the elastin fraction and regional magnetic susceptibility, r _elastin = −0.63 ( p < 0.0001) was found, as well as a significant, moderate negative correlation between collagen and regional magnetic susceptibility, r _collagen = −0.59 ( p < 0.0001). Conclusion: Tissue magnetic susceptibility in diseased human carotid arteries was shown to be significantly correlated with the dominant microstructural components of pathological human cadaver samples—elastin and collagen. Knowing that elastin and collagen are disrupted in vascular disease progression, QSM offers clinically translatable potential for novel disease biomarkers.

Changes in the microstructure of the aortic wall precede the progression of various aortic pathologies, including aneurysms and dissection. Current clinical decisions with regards to surgical planning and/or radiological intervention are guided by geometric features, such as aortic diameter, since clinical imaging lacks tissue microstructural information. The aim of this proof‐of‐concept work is to investigate a non‐invasive imaging method, diffusion tensor imaging (DTI), in ex vivo aortic tissue to gain insights into the microstructure. This study examines healthy, aneurysm and a type B chronic dissection aortae, via DTI. DTI‐derived metrics, such as the fractional anisotropy, mean diffusivity, helical angle and tractography, were examined in each morphology. The results from this work highlighted distinct differences in fractional anisotropy (healthy, 0.24 ± 0.008; aneurysmal, 0.19 ± 0.002; dissected, 0.13 ± 0.006) and a larger variation in the helical angle in the dissected aorta compared to healthy (39.28 ± 11.93° vs. 26.12 ± 4.60°, respectively). These differences were validated by histological characterisation. This study demonstrates the sensitivity of DTI to pathological changes in aortic tissue, highlighting the potential of this methodology to provide improved clinical insight.

Despite significant growth in the field of tissue engineering over the past decades, non‐invasive, non‐destructive methods to characterize the cellularisation of grafts are lacking. Here, in a proof‐of‐concept study, a non‐invasive magnetic resonance imaging method, diffusion tensor imaging (DTI), within acellular and cellularised vascular grafts is investigated. Using decellularised porcine carotid grafts, smooth muscle cells are cultured dynamically for two weeks with terminal time points at day 3, 7, and 14. Grafts are fixed at each time point and investigated by DTI in an ex vivo set up. Semi‐quantitative histology is used as a ground truth for collagen, elastin, and cell density changes over time. DTI‐derived metrics, namely the fractional anisotropy, mean diffusivity, and tractography, are significantly different between day 3 and day 7 grafts and distinguish between acellular and cellularised grafts. Specifically, increasing fractional anisotropy is correlated to increasing cell density. The results from this study show the potential of MR‐DTI in the field of tissue engineering, offering non‐invasive, non‐destructive insight into graft cellularisation.