Breakthrough electroneutron multi-response miniature dosimetry/spectrometry in medical accelerator.

Breakthrough multi-response miniature dosimetry/spectrometry of electroneutrons (EN) was made on surface and in-depths of whole-body polyethylene phantom under 10 cm × 10 cm electron beam of 20 MV Varian Clinac 2100C electron medical accelerator commonly applied for prostate treatment. While dosimetry/spectrometry of photoneutrons (PN) has been well characterized for decades, those of ENs lagged behind due to very low EN reaction cross section and lack of sensitive neutron dosimeters/spectrometers meeting neutron dosimetry requirements. Recently, Sohrabi "miniature neutron dosimeter/spectrometer" and "Stripe polycarbonate dosimeter" have broken this barrier and determined seven EN ambient dose equivalent (ENDE) (µSv.Gy-1) responses from electron beam and from albedo ENs including beam thermal (21 ± 2.63), albedo thermal (43 ± 3.70), total thermal (64 ± 6.33), total epithermal (32 ± 3.90), total fast (112.00), total thermal + epithermal (l96 ± 10), and total thermal + epithermal + fast (208 ± 10.23) ENs. Having seven ENDE responses of this study and seven PNDE responses of previous study with the same accelerator obtained at identical conditions by the same principle author provided the opportunity to compare the two sets of responses. The PNDE (µSv.Gy-1) responses have comparatively higher values and 22.60 times at isocenter which provide for the first time breakthrough ENDE responses not yet reported in any studies before worldwide.

CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT.

Objective.In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (i.e.bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs. In this study, we test the two hypotheses that intra-fraction radiographs are more similar to CBCT-DRRs than CT-DRRs, and that intra-fraction radiographs are more similar to DRRs from algorithms incorporating physical models of OBI components than DRRs from algorithms omitting these models.Approach.DRRs were generated from CBCT and CT image sets collected from 20 patients undergoing pancreas stereotactic body radiotherapy. CBCT-DRRs and CT-DRRs were generated replicating the treatment position of patients and the OBI geometry during intra-fraction radiograph acquisition. To investigate whether the modelling of physical OBI components influenced radiograph-DRR similarity, four DRR algorithms were applied for the generation of CBCT-DRRs and CT-DRRs, incorporating and omitting different combinations of OBI component models. The four DRR algorithms were: a traditional DRR algorithm, a DRR algorithm with source-spectrum modelling, a DRR algorithm with source-spectrum and detector modelling, and a DRR algorithm with source-spectrum, detector and patient material modelling. Similarity between radiographs and matched DRRs was quantified using Pearson's correlation and Czekanowski's index, calculated on a per-image basis. Distributions of correlations and indexes were compared to test each of the hypotheses. Distribution differences were determined to be statistically significant when Wilcoxon's signed rank test and the Kolmogorov-Smirnov two sample test returnedp≤ 0.05 for both tests.Main results.Intra-fraction radiographs were more similar to CBCT-DRRs than CT-DRRs for both metrics across all algorithms, with allp≤ 0.007. Source-spectrum modelling improved radiograph-DRR similarity for both metrics, with allp< 10-6. OBI detector modelling and patient material modelling did not influence radiograph-DRR similarity for either metric.Significance.Generating DRRs from pre-treatment CBCT-DRRs is feasible, and incorporating CBCT-DRRs into markerless target-tracking methods may promote improved target-tracking accuracies. Incorporating source-spectrum modelling into a treatment planning system's DRR algorithms may reinforce the safe treatment of cancer patients by aiding in patient alignment.

Reflective optical imaging for scattering medium using chaotic laser.

Significance: Optical imaging is a non-invasive imaging technology that utilizes near-infrared light, allows for the image reconstruction of optical properties like diffuse and absorption coefficients within the tissue. A recent trend is to use signal processing techniques or new light sources and expanding its application. Aim: We aim to develop the reflective optical imaging using the chaotic correlation technology with chaotic laser and optimize the quality and spatial resolution of reflective optical imaging. Approach: Scattering medium was measured using reflective configuration in different inhomogeneous regions to evaluate the performance of the imaging system. The accuracy of the recovered optical properties was investigated. The reconstruction errors of absorption coefficients and geometric centers were analyzed, and the feature metrics of the reconstructed images were evaluated. Results: We showed how chaotic correlation technology can be utilized for information extraction and image reconstruction. This means that a higher signal-to-noise ratio and image reconstruction of inhomogeneous phantoms under different scenarios successfully were achieved. Conclusions: This work highlights that the peak values of correlation of chaotic exhibit smaller reconstruction error and better reconstruction performance in optical imaging compared with reflective optical imaging with the continuous wave laser.

Complex Spatial Illumination Scheme Optimization of Backscattering Mueller Matrix Polarimetry for Tissue Imaging and Biosensing.

Polarization imaging and sensing techniques have shown great potential for biomedical and clinical applications. As a novel optical biosensing technology, Mueller matrix polarimetry can provide abundant microstructural information of tissue samples. However, polarimetric aberrations, which lead to inaccurate characterization of polarization properties, can be induced by uneven biomedical sample surfaces while measuring Mueller matrices with complex spatial illuminations. In this study, we analyze the detailed features of complex spatial illumination-induced aberrations by measuring the backscattering Mueller matrices of experimental phantom and tissue samples. We obtain the aberrations under different spatial illumination schemes in Mueller matrix imaging. Furthermore, we give the corresponding suggestions for selecting appropriate illumination schemes to extract specific polarization properties, and then provide strategies to alleviate polarimetric aberrations by adjusting the incident and detection angles in Mueller matrix imaging. The optimized scheme gives critical criteria for the spatial illumination scheme selection of non-collinear backscattering Mueller matrix measurements, which can be helpful for the further development of quantitative tissue polarimetric imaging and biosensing.

Three-Dimensional Visualization of Shunt Valves with Photon Counting CT and Comparison to Traditional X-ray in a Simple Phantom Model.

This study introduces an application of innovative medical technology, Photon Counting Computer Tomography (PC CT) with novel detectors, for the assessment of shunt valves. PC CT technology offers enhanced visualization capabilities, especially for small structures, and opens up new possibilities for detailed three-dimensional imaging. Shunt valves are implanted under the skin and redirect excess cerebrospinal fluid, for example, to the abdominal cavity through a catheter. They play a vital role in regulating cerebrospinal fluid drainage in various pathologies, which can lead to hydrocephalus. Accurate imaging of shunt valves is essential to assess the rate of drainage, as their precise adjustment is a requirement for optimal patient care. This study focused on two adjustable shunt valves, the proGAV 2.0® and M. blue® (manufactured by Miethke, Potsdam, Germany). A comprehensive comparative analysis of PC CT and traditional X-ray techniques was conducted to explore this cutting-edge technology and it demonstrated that routine PC CT can efficiently assess shunt valves' adjustments. This technology shows promise in enhancing the accurate management of shunt valves used in settings where head scans are already frequently required, such as in the treatment of hydrocephalus.

Widefield functional speckle-correlation optical scattering mesoscopy toward hemodynamic imaging.

Speckle-correlation optical scattering imaging (SCOSI) has shown the potential for non-invasive biomedical diagnostic applications, which directly utilizes the scattering patterns to reconstruct the deep and non-line-of-sight objects. However, the course of the translation of this technique to preclinical biomedical imaging applications has been postponed by the following two facts: 1) the field of view of SCOSI was significantly limited by the optical memory effect, and 2) the molecular-tagged functional imaging of the biological tissues remains largely unexplored. In this work, a proof-of-concept design of the first-generation widefield functional SCOSI (WF-SCOSI) system was presented for simultaneously achieving mesoscopic mapping of fluid morphology and flow rate, which was realized by implementing the concepts of scanning synthesis and fluorescence scattering flowmetry. The ex vivo imaging results of the fluorescence-labeled large-scale blood vessel network phantom underneath the strong scatters demonstrated the effectiveness of WF-SCOSI toward non-invasive hemodynamic imaging applications.

Phantom-based analysis of variations in automatic exposure control across three mammography systems: implications for radiation dose and image quality in mammography, DBT, and CEM.

BACKGROUND: Automatic exposure control (AEC) plays a crucial role in mammography by determining the exposure conditions needed to achieve specific image quality based on the absorption characteristics of compressed breasts. This study aimed to characterize the behavior of AEC for digital mammography (DM), digital breast tomosynthesis (DBT), and low-energy (LE) and high-energy (HE) acquisitions used in contrast-enhanced mammography (CEM) for three mammography systems from two manufacturers. METHODS: Using phantoms simulating various breast thicknesses, 363 studies were acquired using all available AEC modes 165 DM, 132 DBT, and 66 LE-CEM and HE-CEM. AEC behaviors were compared across systems and modalities to assess the impact of different technical components and manufacturers' strategies on the resulting mean glandular doses (MGDs) and image quality metrics such as contrast-to-noise ratio (CNR). RESULTS: For all systems and modalities, AEC increased MGD for increasing phantom thicknesses and decreased CNR. The median MGD values (interquartile ranges) were 1.135 mGy (0.772-1.668) for DM, 1.257 mGy (0.971-1.863) for DBT, 1.280 mGy (0.937-1.878) for LE-CEM, and 0.630 mGy (0.397-0.713) for HE-CEM. Medians CNRs were 14.2 (7.8-20.2) for DM, 4.91 (2.58-7.20) for a single projection in DBT, 11.9 (8.0-18.2) for LE-CEM, and 5.2 (3.6-9.2) for HE-CEM. AECs showed high repeatability, with variations lower than 5% for all modes in DM, DBT, and CEM. CONCLUSIONS: The study revealed substantial differences in AEC behavior between systems, modalities, and AEC modes, influenced by technical components and manufacturers' strategies, with potential implications in radiation dose and image quality in clinical settings. RELEVANCE STATEMENT: The study emphasized the central role of automatic exposure control in DM, DBT, and CEM acquisitions and the great variability in dose and image quality among manufacturers and between modalities. Caution is needed when generalizing conclusions about differences across mammography modalities. KEY POINTS: • AEC plays a crucial role in DM, DBT, and CEM. • AEC determines the "optimal" exposure conditions needed to achieve specific image quality. • The study revealed substantial differences in AEC behavior, influenced by differences in technical components and strategies.

Chemical shift-encoded MRI with compressed sensing combined with parallel imaging for proton density fat fraction measurement of the lumbar vertebral bone marrow.

We aimed to investigate the accuracy of proton density fat fraction (PDFF) measurement of the lumbar vertebral bone marrow using chemical shift-encoded magnetic resonance imaging (CSE-MRI) with compressed sensing combined with parallel imaging (CSPI). This study recruited a commercially available phantom, and 43 patients. Fully sampled data without CSPI and under-sampled data with CSPI acceleration factors of 2.4, 3.6, and 4.8 were acquired using a 1.5T imaging system. The relationships between PDFF measurements obtained with the no-CSPI acquisition and those obtained with each CSPI acquisition were assessed using Pearson correlation coefficient (r), linear regression analyses, and Bland-Altman analysis. The intra- and inter-observer variabilities of the PDFF measurements were evaluated using the intraclass correlation coefficient. PDFF measurements obtained with all acquisitions showed a significant correlation and strong agreement with the reference PDFF measurement of the phantom. PDFF measurements obtained using CSE-MRI with and without CSPI were positively correlated (all acquisitions: r = 0.99; P < .001). The mean bias was -0.31% to -0.17% with 95% limits of agreement within ±2.02%. The intra- and inter-observer agreements were excellent (intraclass correlation coefficient: 0.988 and 0.981, respectively). A strong agreement and positive correlation were observed between the PDFF measurements obtained using CSE-MRI with and without CSPI. PDFF measurement of the lumbar vertebral bone marrow using CSE-MRI with CSPI can be acquired with a maximum reduction of approximately 75% in the acquisition time compared with a fully sampled acquisition.

Investigation of the accuracy of a portable109Cd XRF system for the measurement of iron in skin.

We have previously reported the design of a portable109Cd x-ray fluorescence (XRF) system to measure iron levels in the skin of patients with either iron overload disease, such as thalassemia, or iron deficiency disease, such as anemia. In phantom studies, the system was found to have a detection limit of 1.35µg Fe per g of tissue for a dose of 1.1 mSv. However, the system must provide accurate as well as precise measurements of iron levels in the skin in order to be suitable for human studies. The accuracy of the system has been explored using several methods. First, the iron concentrations of ten pigskin samples were assessed using both the portable XRF system and ICP-MS, and the results were compared. Overall, it was found that XRF and ICP-MS reported average values for iron in skin that were comparable to within uncertainties. The mean difference between the two methodologies was not significant, 2.5 ± 4.6µg Fe per g. On this basis, the system could be considered accurate. However, ICP-MS measurements reported a wider range of values than XRF, with two individual samples having ICP-MS results that were significantly elevated (p < 0.05) compared to XRF. SynchrotronµXRF maps of iron levels in pigskin were acquired on the BioXAS beam line of the Canadian Light Source. TheµXRF maps indicated two important features in the distribution of iron in pigskin. First, there were small areas of high iron concentration in the pigskin samples, that were predominantly located in the dermis and hypodermis at depths greater than 0.5 mm. Monte Carlo modelling using the EGS 5 code determined that if these iron 'hot spots' were located towards the back of the skin at depths greater than 0.5 mm, they would not be observed by XRF, but would be measured by ICP-MS. These results support a hypothesis that iron levels in the two samples that reported significantly elevated ICP-MS results compared to XRF may have had small blood vessels at the back of the skin. Second, the synchrotronµXRF maps also showed a narrow (approximately 100µm thick) layer of elevated iron at the surface of the skin. Monte Carlo models determined that, as expected, the XRF system was most sensitive to these skin layers. However, the simulations found that the XRF system, when calibrated against homogenous water-based phantoms, was found to accurately measure average iron levels in the skin of normal pigs despite the greater sensitivity to the surface layer. The Monte Carlo results further indicated that with highly elevated skin surface iron levels, the XRF system would not provide a good estimate of average skin iron levels. The XRF estimate could, with correction factors, provide a good estimate of the iron levels in the surface layers of skin. There is limited data on iron distribution in skin, especially under conditions of disease. If iron levels are elevated at the skin surface by diseases including thalassemia and hemochromatosis, this XRF device may prove to be an accurate clinical tool. However, further data are required on skin iron distributions in healthy and iron overload disease before this system can be verified to provide accurate measurements.

Smartphone-based particle tracking velocimetry for the in vitro assessment of coronary flows.

The present study adopts a smartphone-based approach for the experimental characterization of coronary flows. Technically, Particle Tracking Velocimetry (PTV) measurements were performed using a smartphone camera and a low-power continuous wave laser in realistic healthy and stenosed phantoms of left anterior descending artery with inflow Reynolds numbers approximately ranging from 20 to 200. A Lagrangian-Eulerian mapping was performed to convert Lagrangian PTV velocity data to a Eulerian grid. Eulerian velocity and vorticity data obtained from smartphone-based PTV measurements were compared with Particle Image Velocimetry (PIV) measurements performed with a smartphone-based setup and with a conventional setup based on a high-power double-pulsed laser and a CMOS camera. Smartphone-based PTV and PIV velocity flow fields substantially agreed with conventional PIV measurements, with the former characterized by lower average percentage differences than the latter. Discrepancies emerged at high flow regimes, especially at the stenosis throat, due to particle image blur generated by smartphone camera shutter speed and image acquisition frequency. In conclusion, the present findings demonstrate the feasibility of PTV measurements using a smartphone camera and a low-power light source for the in vitro characterization of cardiovascular flows for research, industrial and educational purposes, with advantages in terms of costs, safety and usability.

Spatial attention-based implicit neural representation for arbitrary reduction of MRI slice spacing.

Magnetic resonance (MR) images collected in 2D clinical protocols typically have large inter-slice spacing, resulting in high in-plane resolution and reduced through-plane resolution. Super-resolution technique can enhance the through-plane resolution of MR images to facilitate downstream visualization and computer-aided diagnosis. However, most existing works train the super-resolution network at a fixed scaling factor, which is not friendly to clinical scenes of varying inter-slice spacing in MR scanning. Inspired by the recent progress in implicit neural representation, we propose a Spatial Attention-based Implicit Neural Representation (SA-INR) network for arbitrary reduction of MR inter-slice spacing. The SA-INR aims to represent an MR image as a continuous implicit function of 3D coordinates. In this way, the SA-INR can reconstruct the MR image with arbitrary inter-slice spacing by continuously sampling the coordinates in 3D space. In particular, a local-aware spatial attention operation is introduced to model nearby voxels and their affinity more accurately in a larger receptive field. Meanwhile, to improve the computational efficiency, a gradient-guided gating mask is proposed for applying the local-aware spatial attention to selected areas only. We evaluate our method on the public HCP-1200 dataset and the clinical knee MR dataset to demonstrate its superiority over other existing methods.

Impact of improved dead time correction on the quantification accuracy of a dedicated BrainPET scanner.

OBJECTIVE: Quantitative values derived from PET brain images are of high interest for neuroscientific applications. Insufficient DT correction (DTC) can lead to a systematic bias of the output parameters obtained by a detailed analysis of the time activity curves (TACs). The DTC method currently used for the Siemens 3T MR BrainPET insert is global, i.e., differences in DT losses between detector blocks are not considered, leading to inaccurate DTC and, consequently, to inaccurate measurements masked by a bias. However, following careful evaluation with phantom measurements, a new block-pairwise DTC method has demonstrated a higher degree of accuracy compared to the global DTC method. APPROACH: Differences between the global and the block-pairwise DTC method were studied in this work by applying several radioactive tracers. We evaluated the impact on [11C]ABP688, O-(2-[18F]fluoroethyl)-L-tyrosine (FET), and [15O]H2O TACs. RESULTS: For [11C]ABP688, a relevant bias of between -0.0034 and -0.0053 ml/ (cm3 • min) was found in all studied brain regions for the volume of distribution (VT) when using the current global DTC method. For [18F]FET-PET, differences of up to 10% were observed in the tumor-to-brain ratio (TBRmax), these differences depend on the radial distance of the maximum from the PET isocenter. For [15O]H2O, differences between +4% and -7% were observed in the GM region. Average biases of -4.58%, -3.2%, and -1.2% for the regional cerebral blood flow (CBF (K1)), the rate constant k2, and the volume of distribution VT were observed, respectively. Conversely, in the white matter region, average biases of -4.9%, -7.0%, and 3.8% were observed for CBF (K1), k2, and VT, respectively. CONCLUSION: The bias introduced by the global DTC method leads to an overestimation in the studied quantitative parameters for all applications compared to the block-pairwise method. SIGNIFICANCE: The observed differences between the two DTC methods are particularly relevant for research applications in neuroscientific studies as they affect the accuracy of quantitative Brain PET images.

Phantom study of a fully automatic radioactive seed placement robot for the treatment of skull base tumours.

BACKGROUND: Interstitial brachytherapy is a form of intensive local irradiation that facilitates the effective protection of surrounding structures and the preservation of organ functions, resulting in a favourable therapeutic response. As surgical robots can perform needle placement with a high level of accuracy, our team developed a fully automatic radioactive seed placement robot, and this study aimed to evaluate the accuracy and feasibility of fully automatic radioactive seed placement for the treatment of tumours in the skull base. METHODS: A fully automatic radioactive seed placement robot was established, and 4 phantoms of skull base tumours were built for experimental validation. All the phantoms were subjected to computed tomography (CT) scans. Then, the CT data were imported into the Remebot software to design the preoperative seed placement plan. After the phantoms were fixed in place, navigation registration of the Remebot was carried out, and the automatic seed placement device was controlled to complete the needle insertion and particle placement operations. After all of the seeds were implanted in the 4 phantoms, postoperative image scanning was performed, and the results were verified via image fusion. RESULTS: A total of 120 seeds were implanted in 4 phantoms. The average error of seed placement was (2.51 ± 1.44) mm. CONCLUSION: This study presents an innovative, fully automated radioactive particle implantation system utilizing the Remebot device, which can successfully complete automated localization, needle insertion, and radioactive particle implantation procedures for skull base tumours. The phantom experiments showed the robotic system to be reliable, stable, efficient and safe. However, further research on the needle-soft tissue interaction and deformation mechanism of needle puncture is still needed.

Computational peptide discovery with a genetic programming approach.

The development of peptides for therapeutic targets or biomarkers for disease diagnosis is a challenging task in protein engineering. Current approaches are tedious, often time-consuming and require complex laboratory data due to the vast search spaces that need to be considered. In silico methods can accelerate research and substantially reduce costs. Evolutionary algorithms are a promising approach for exploring large search spaces and can facilitate the discovery of new peptides. This study presents the development and use of a new variant of the genetic-programming-based POET algorithm, called POET Regex , where individuals are represented by a list of regular expressions. This algorithm was trained on a small curated dataset and employed to generate new peptides improving the sensitivity of peptides in magnetic resonance imaging with chemical exchange saturation transfer (CEST). The resulting model achieves a performance gain of 20% over the initial POET models and is able to predict a candidate peptide with a 58% performance increase compared to the gold-standard peptide. By combining the power of genetic programming with the flexibility of regular expressions, new peptide targets were identified that improve the sensitivity of detection by CEST. This approach provides a promising research direction for the efficient identification of peptides with therapeutic or diagnostic potential.

[Research Photon Energy Spectrum of Medical Linear Accelerator by Monte Carlo Method].

Objective: The distribution of the photon energy spectrum in isocenter plane of the medical linear accelerator and the influence of secondary collimator on the photon energy spectrum are studied. Methods Use the BEAMnrc program to simulate the transmission of the 6 MeV electrons and photons in 5 cm×5 cm,10 cm×10 cm,15 cm×15 cm and 20 cm×20 cm fields in treatment head of the medical linear accelerator, where a phase space file was set up at the isocenter plane to record the particle information passing through this plane. The BEAMdp program is used to analyze the phase space file, in order to obtain the distribution of the photon energy spectrum in isocenter plane and the influence of secondary collimator on the photon energy spectrum. Results: By analyzing the photon energy spectrum of a medical linear accelerator with a nominal energy of 6 MV, it is found that the secondary collimator has little effect on the photon energy spectrum; different fields have different photon energy spectrum distributions; the photon energy spectrum in different central regions of the same field have the same normalized distribution. Conclusion: In the dose calculation of radiation therapy, the influence of photon energy spectrum should be carefully considered.

A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions.

This work presents a deep learning approach for rapid and accurate muscle water T2 with subject-specific fat T2 calibration using multi-spin-echo acquisitions. This method addresses the computational limitations of conventional bi-component Extended Phase Graph fitting methods (nonlinear-least-squares and dictionary-based) by leveraging fully connected neural networks for fast processing with minimal computational resources. We validated the approach through in vivo experiments using two different MRI vendors. The results showed strong agreement of our deep learning approach with reference methods, summarized by Lin's concordance correlation coefficients ranging from 0.89 to 0.97. Further, the deep learning method achieved a significant computational time improvement, processing data 116 and 33 times faster than the nonlinear least squares and dictionary methods, respectively. In conclusion, the proposed approach demonstrated significant time and resource efficiency improvements over conventional methods while maintaining similar accuracy. This methodology makes the processing of water T2 data faster and easier for the user and will facilitate the utilization of the use of a quantitative water T2 map of muscle in clinical and research studies.

Two-view topogram-based anatomy-guided CT reconstruction for prospective risk minimization.

To facilitate a prospective estimation of the effective dose of an CT scan prior to the actual scanning in order to use sophisticated patient risk minimizing methods, a prospective spatial dose estimation and the known anatomical structures are required. To this end, a CT reconstruction method is required to reconstruct CT volumes from as few projections as possible, i.e. by using the topograms, with anatomical structures as correct as possible. In this work, an optimized CT reconstruction model based on a generative adversarial network (GAN) is proposed. The GAN is trained to reconstruct 3D volumes from an anterior-posterior and a lateral CT projection. To enhance anatomical structures, a pre-trained organ segmentation network and the 3D perceptual loss are applied during the training phase, so that the model can then generate both organ-enhanced CT volume and organ segmentation masks. The proposed method can reconstruct CT volumes with PSNR of 26.49, RMSE of 196.17, and SSIM of 0.64, compared to 26.21, 201.55 and 0.63 using the baseline method. In terms of the anatomical structure, the proposed method effectively enhances the organ shapes and boundaries and allows for a straight-forward identification of the relevant anatomical structures. We note that conventional reconstruction metrics fail to indicate the enhancement of anatomical structures. In addition to such metrics, the evaluation is expanded with assessing the organ segmentation performance. The average organ dice of the proposed method is 0.71 compared with 0.63 for the baseline model, indicating the enhancement of anatomical structures.

Photoacoustic microscopy for real-time monitoring of near-infrared optical absorbers inside biological tissue.

Significance: We developed a high-speed optical-resolution photoacoustic microscopy (OR-PAM) system using a high-repetition-rate supercontinuum (SC) light source and a two-axes Galvano scanner. The OR-PAM system enabled real-time imaging of optical absorbers inside biological tissues with excellent excitation wavelength tunability. Aim: In the near-infrared (NIR) wavelength range, high-speed OR-PAM faces limitations due to the lack of wavelength-tunable light sources. Our study aimed to enable high-speed OR-PAM imaging of various optical absorbers, including NIR contrast agents, and validate the performance of high-speed OR-PAM in the detection of circulating tumor cells (CTCs). Approach: A high-repetition nanosecond pulsed SC light source was used for OR-PAM. The excitation wavelength was adjusted by bandpass filtering of broadband light pulses produced by an SC light source. Phantom and in vivo experiments were performed to detect tumor cells stained with an NIR contrast agent within flowing blood samples. Results: The newly developed high-speed OR-PAM successfully detected stained cells both in the phantom and in vivo. The phantom experiment confirmed the correlation between the tumor cell detection rate and tumor cell concentration in the blood sample. Conclusions: The high-speed OR-PAM effectively detected stained tumor cells. Combining high-speed OR-PAM with molecular probes that stain tumor cells in vivo enables in vivo CTC detection.

Multiplexed near infrared fluorescence lifetime imaging in turbid media.

Significance: Fluorescence lifetime imaging (FLI) plays a pivotal role in enhancing our understanding of biological systems, providing a valuable tool for non-invasive exploration of biomolecular and cellular dynamics, both in vitro and in vivo. Its ability to selectively target and multiplex various entities, alongside heightened sensitivity and specificity, offers rapid and cost-effective insights. Aim: Our aim is to investigate the multiplexing capabilities of near-infrared (NIR) FLI within a scattering medium that mimics biological tissues. We strive to develop a comprehensive understanding of FLI's potential for multiplexing diverse targets within a complex, tissue-like environment. Approach: We introduce an innovative Monte Carlo (MC) simulation approach that accurately describes the scattering behavior of fluorescent photons within turbid media. Applying phasor analyses, we enable the multiplexing of distinct targets within a single FLI image. Leveraging the state-of-the-art single-photon avalanche diode (SPAD) time-gated camera, SPAD512S, we conduct experimental wide-field FLI in the NIR regime. Results: Our study demonstrates the successful multiplexing of dual targets within a single FLI image, reaching a depth of 1 cm within tissue-like phantoms. Through our novel MC simulation approach and phasor analyses, we showcase the effectiveness of our methodology in overcoming the challenges posed by scattering media. Conclusions: This research underscores the potential of NIR FLI for multiplexing applications in complex biological environments. By combining advanced simulation techniques with cutting-edge experimental tools, we introduce significant results in the non-invasive exploration of biomolecular dynamics, to advance the field of FLI research.

Quantitative and qualitative evaluation of three MSCT for high resolution bone imaging.

INTRODUCTION: Strategies for achieving high resolution varies between manufacturers. In CT, the helical mode with narrow collimation has long been considered as the gold standard for high-resolution imaging. More recently, incremental modes with small dexels and focal spot, have been developed but have not been compared with helical acquisitions under optimal conditions. The aim of this work is to compare the high-resolution acquisition strategies currently proposed by recent MSCT. METHODS: Three CT systems were compared. A phantom was used to evaluate geometric accuracy, uniformity, scan slice geometry, and spatial resolution. Human dry bones were used to test different protocols on real bone architecture. A blind visual analysis was conducted by trained CT users for classifying the different acquisitions (p-values). RESULTS: All systems give satisfactory results in terms of geometric accuracy and uniformity. The in-plane MTF at 5% were respectively 13.4, 15.9 and 18.1 lp/cm. Dry-bones evaluation confirms that acquisition#3 is considered as the best. CONCLUSIONS: The incremental acquisition coupled with à small focal spot, and a high-sampling detector, overpasses the reference of low-pitch helical acquisitions for high-resolution imaging. Cortical bone, bony vessels, and tumoral matrix analysis are the very next challenges that will have to be managed to improve normal and pathologic bone imaging thanks to the availability UHR-CT systems.