In practical multispectral computed tomography (MSCT), the scanning geometric parameters under different X-ray energy spectra are often inconsistent, and the distributions of the energy spectra are even ray-dependent. However, existing algorithms cannot effectively and accurately solve the associated image reconstruction problem. To address this limitation, using the proposed aggregated energy spectra, we approximate the Jacobian matrix of the nonlinear forward operator at certain special points (e.g., the zero point) as a block product of a diagonal matrix composed of projection matrices and a very small-scale matrix, and then based on this matrix with a special structure, propose an efficient and accurate image reconstruction algorithm tailored for geometric-inconsistent MSCT with ray-dependent energy spectra. Under appropriate conditions, we establish the convergence theory for the proposed algorithm. Furthermore, numerical experiments using both noiseless and noisy projection data are conducted to verify the performance of the proposed algorithm, which demonstrate that the efficiency and accuracy of this algorithm are much higher than existing algorithms, offering the flexibility and scalability to accommodate various MSCT imaging configurations.

Haematocrit influences blood viscosity and may affect coronary computational fluid dynamics (CFD). However, previous studies examined broad or pathological haematocrit ranges, and it remains unclear whether female-specific haematocrit variations within the physiological range produce meaningful changes in coronary haemodynamics. 15 female coronaries were analysed, including healthy arteries and diseased models with mild, moderate and severe stenosis. A haematocrit-dependent Carreau-Yasuda model was developed. CFD simulations were performed using the standard rheology model and a female-specific haematocrit-based model (40%). Time-averaged endothelial shear stress (TAESS), ESS gradient (ESSG), temporal shear variation index (TSVI), helicity, and low/high TAESS exposure were compared across coronary trees, arterial segments, bifurcations, stenosed vessels and corresponding narrowed regions. The female-specific model produced statistically significant differences from the standard model across all metrics and coronary regions (p < 0.05). However, the absolute differences were small, indicating a limited haemodynamic impact. Bland-Altman analysis showed narrow biases and limits of agreement. Linear regression demonstrated significant associations between inter-model differences and haemodynamic magnitude for TAESS, ESSG, helicity intensity, and adverse TAESS exposure, but the slopes were small. Similar findings were observed in stenosed arteries, where both models captured comparable flow disturbances across stenosis severities. Female-specific haematocrit variation within the physiological range is computationally detectable but haemodynamically negligible in coronary CFD. A standard rheology model is therefore likely sufficient for most coronary CFD studies, while personalised haematocrit modelling is more relevant for patients with abnormal haematocrit or rheology-focused studies.

With 890,000 annual new cases globally, head and neck squamous cell carcinoma has one of the highest recurrence rates among solid malignancies. Although frozen section analysis is the standard of care for intraoperative margin assessment, accurately relocating detected positive margins on the resection bed remains challenging due to imprecise alignment between resected specimens and their resection bed, compounded by post-resection mucosal tissue shrinkage. We present a biomechanics-driven deformable registration framework that corrects post-resection tissue deformation to provide intraoperative guidance. Our approach registers 3D specimen meshes to intraoperative resection bed point clouds using a deformable registration approach based on regularized Kelvinlet basis functions. The registration matches surface point clouds, fiducial landmarks, and boundary contour constraints that directly penalize perpendicular distance-to-agreement between specimen and resection bed boundaries. Across nine specimens from skin, buccal mucosa, and tongue sites, the overall mean target registration error was $11.11 \pm 4.07$ mm using rigid registration, which decreased to $8.20 \pm 2.68$ mm (26.19\% reduction) using deformable registration without contour constraint. The proposed contour-constrained deformable registration further reduced the error to $5.62 \pm 2.28$ mm, a 49.41\% reduction relative to rigid registration. We observed the largest reduction in the most clinically challenging tongue specimens. We also performed a systematic two-stage parameter search to characterize the relative importance of surface alignment, fiducial correspondences, contour constraint, and strain energy regularization. This search revealed that contour weighting dominates registration accuracy for tissue types with large lateral deformation, while the algorithm operates over a broad range of parameter combinations.

This manuscript introduces a novel method to assess tissue oxygen concentration via the quantum entanglement (QE) of photons originating from positronium which is produced within the patient's body during positron emission tomography. We also investigate the possibility of assessing hypoxia by simultaneously detecting positronium lifetime and the positronium decay rate ratio. We introduce two distinct quantum sensing approaches. Method 1 utilizes the correlation between oxygen concentration and ortho-positronium (o-Ps) decay rates, relying on the simultaneous measurement of the mean o-Ps lifetime ($τ_{\mathrm{oPs}}$) and the $3γ$-to-$2γ$ annihilation rate ratio of o-Ps ($R_{\mathrm{oPs-3γ/2γ}}$). Method 2 introduces a novel hypothesis: that the degree of QE is sensitive to the relative contribution of annihilation mechanisms (pick-off vs. conversion), which in turn depends on oxygen concentration. We derive a formula for partial pressure of oxygen ($p\mathrm{O}_2$) as a function of $R_{\mathrm{oPs-3γ/2γ}}$ and $τ_{\mathrm{oPs}}$ and estimate the measurement accuracy required for these parameters - and for the degree of QE - to sense in-vivo oxygen pressure in the range between hypoxic and physoxic conditions. Theoretical models and quantitative estimates for $R_{\mathrm{oPs-3γ/2γ}}$, $τ_{\mathrm{oPs}}$ and for the degree of QE ($C_{\mathrm{QE}}$ ) as a function of $p\mathrm{O}_2$ are provided for water, isopropanol, cyclohexane, isooctane, and adipose tissue. In particular, applying the formulas derived under the working hypothesis that in pick-off process the photons are not entangled, we estimated that for $p\mathrm{O}_2 = 0$, the degree of quantum entanglement $C_{\mathrm{QE}}$ is equal to 0.890 for adipose, 0.886 for isopropanol, 0.867 for water, 0.818 for cyclohexane, and 0.784 for isooctane.

Purpose: To create modular solutions for interactive real-time MRI using reconstruction algorithms implemented in BART. Methods: A new protocol for streaming of multidimensional arrays is presented and integrated into BART. The new functionality is demonstrated using examples for cardiac interactive real-time MRI based on radial FLASH, where iterative reconstruction is combined with advanced features such as dynamic coil compression and gradient-delay orrection. We analyze the latency of the reconstruction and measure end-to-end latency of the full imaging process. Results: Reconstruction pipelines with iterative reconstruction and advanced functionality were built in a modular way using scripting. Latency measurements demonstrate latency sufficient for interactive real-time MRI, on the order of 30 ms for BART processing and network transfer time, or 200 ms for end-to-end latency including acquisition, vendor processing, and display. Conclusion: With the new streaming capabilities, real-time reconstruction pipelines can be assembled using BART in a flexible way, enabling rapid prototyping of advanced applications such as interactive real-time MRI.