Biomedical Physics & Engineering Express最新文献

Cherenkov radiation is emitted during x-ray irradiation in a linear accelerator (LINAC). Cherenkov light contains many short wavelength components, including ultraviolet (UV) light, which is well-known for its bactericidal effects. A similar phenomenon is probable for human cancer cells. To assess the effect of Cherenkov light on cell death in x-ray irradiation, we employed simulations and UV cell survival data. We measured the survival rates of HeLa cells exposed to 254 nm (UVC) and 310 nm (UVB) light to determine the 50% lethal dose (LD50) required to kill 50% of the cells. For other wavelengths, we utilized literature values to establish the relationship between wavelength and LD50. Due to the broad range of the Cherenkov light spectrum, we need LD50 as a function of wavelength to estimate cell survival solely from Cherenkov light. A Monte Carlo simulation was used to calculate the fluence distribution of Cherenkov light in a 300 mm³phantom comprised of soft tissue, both with and without absorption of visible light. The latter scenario is considered to be most influenced by Cherenkov light. By combining the fluence distribution and the wavelength-LD50 relationship, we determined the distribution of the survival rate. Our findings indicate that, in the absence of absorption, a radiation dose of approximately 90 Gy or greater is necessary for Cherenkov light to have any effect. As a result, the impact of Cherenkov light on cell survival can be considered negligible for typical dose of 2 Gy.

Reactive oxygen species (ROS), which are expressed at high levels in many diseases, can be scavenged by cerium oxide nanoparticles (CeO₂NPs). CeO₂NPs can cause significant cytotoxicity when administered directly to cells, but this cytotoxicity can be reduced if CeO₂NPs can be encapsulated in biocompatible polymers. In this study, CeO₂NPs were synthesized using a one-stage process, then purified, characterized, and then encapsulated into an electrospun poly-ε-caprolactone (PCL) scaffold. The direct administration of CeO₂NPs to RAW 264.7 Macrophages resulted in reduced ROS levels but lower cell viability. Conversely, the encapsulation of nanoceria in a PCL scaffold was shown to lower ROS levels and improve cell survival. The study demonstrated an effective technique for encapsulating nanoceria in PCL fiber and confirmed its biocompatibility and efficacy. This system has the potential to be utilized for developing tissue engineering scaffolds, targeted delivery of therapeutic CeO₂NPs, wound healing, and other biomedical applications.

Purpose. Precise identification of pancreatic tumors is challenging for radiotherapy planning due to the tumor's anatomical variability and poor visualization on 3D cross-sectional imaging. Low extracellular volume fraction (ECVf) correlates with poor vasculature uptake and possible necrosis or hypoxia in pancreatic tumors. This work investigates the feasibility of delineating pancreatic tumors using ECVf spatial distribution maps derived from contrast enhanced dual-energy CT (DECT).Methods and Materials. Data acquired from radiotherapy simulation of 12 pancreatic cancer patients, using a dual source DECT scanner, were analyzed. For each patient, an ECVf distribution of the pancreas was computed from the simultaneously acquired low and high energy DECT series during the late arterial contrast phase combined with the patient's hematocrit level. Volume of interest (V_ECVf) maps in ECVf distribution of pancreas were identified by applying an appropriate threshold condition and a connected components clustering algorithm. The obtained V_ECVfwas compared with the clinical gross tumor volume (GTV) using the positive predictive value (PPV), Dice similarity coefficient (DSC), mean distance to agreement (MDA) and true positive rate (TPR).Results. As a proof of concept, our hypothetical threshold condition based on the first quartile separation of the ECVf distribution to find V_ECVfof the pancreas elucidates the tumor volume within the pancreas. Notably, 7 out of 12 cases studied for V_ECVfmatched well with the GTV and the mean PPV of 0.83 ± 0.12. The mean MDA (2.83 ± 1.0) of the cases confirms that V_ECVflies within the tolerance for comparing to the pancreatic GTV. For the remaining 5 cases, the V_ECVfis substantially affected by other compounding factors, e.g., large cysts, dilate ducts, and thus did not align with the GTVs.Conclusions. This work demonstrated the promising application of the ECVf map, derived from contrast enhanced DECT, to help delineate tumor target for RT planning of pancreatic cancer.

Iron Deficiency Anemia (IDA) is the nutritional disorder that occurs when the body does not contain enough iron, an essential component of hemoglobin (Hb). The World Health Organization (WHO) estimated that IDA is the main cause of anemia in 1.62 billion cases worldwide [1]. Although IDA rarely results in death, it has significant adverse impacts on human health. During diagnosis, the hemoglobin indices show low mean corpuscular hemoglobin and mean corpuscular hemoglobin volume. On Peripheral Blood Smear (PBS) images viewed under a microscope by hematologists, IDA shows hypochromic and microcytic red cells. The purpose of the proposed research is to develop a computer-aided system that will allow hematologists to diagnose and detect diseases more accurately and quickly, therefore saving them time and effort. In order to diagnose or detect clinical disorders, non-invasive techniques like machine learning algorithms are employed. This work aims to identify IDA by utilizing the RetinaNet-Disentangled Dense Object Detector (DDOD) to localize hypochromic microcytes in PBS images. To the best of our knowledge, this is the first work using the object detection technique to detect IDA based on the Red Blood Cell (RBC) morphology. We carried out an extensive quantitative and qualitative evaluation of the model. Additionally, a comparison was made between the performance of our model and other object detection models. The results showed that our approach outperformed state-of-the-art techniques, with a mean average precision that was more than 8% higher.

This large multicenter study of 37 magnetic resonance imaging scanners aimed at characterizing, for the first time, spatial profiles of inaccuracy (namely, Δ-profiles) in apparent diffusion coefficient (ADC) values with varying acquisition plan orientation and diffusion weighting gradient direction, using a statistical approach exploiting unsupervised clustering analysis. A diffusion-weighted imaging (DWI) protocol (b-value: 0-200-400-600-800-1000 s mm^-2) with different combinations of acquisition plan orientation (axial/sagittal/coronal) and diffusion weighting gradient direction (anterior-posterior/left-right/feet-head) was acquired on a standard water phantom. For each acquisition setup, Δ-profiles along the 3 main orthogonal directions were characterized by fitting data with a second order polynomial function (ar²+ br + c). Moreover, for each Δ-profile, the maximum minus minimum of the fitting function (δ_max) was calculated. The parametersa,b,c, andδ_maxshowed some significant variations between scanner systems by different manufacturers or with different static magnetic field strengths, as well as between different acquisition/estimation setups. Unsupervised clustering analysis showed two evident clusters with significantly different values of parametera(p< 0.0001), which can be grouped by acquisition protocol/Δ-profile direction but not scanner system. The results of ∆-profiles confirm an appreciable inter-scanner variability in ADC measurement and corroborate the importance of guarantying the reliability of ADC estimations in clinical or research studies, considering for each scanner system the specific acquisition sequence in terms of acquisition plan orientation and diffusion weighting gradient direction.

Purpose.This paper introduces a deep learning method for myocardial strain analysis while also evaluating the efficacy of the method across a public and a private dataset for cardiac pathology discrimination.Methods.We measure the global and regional myocardial strain in cSAX CMR images by first identifying a ROI centered in the LV, obtaining the cardiac structures (LV, RV and Myo) and estimating the motion of the myocardium. Finally, we compute the strain for the heart coordinate system and report the global and regional strain.Results.We validated our method in two public datasets (ACDC, 80 subjects, and CMAC, 16 subjects) and a private dataset (SSC, 75 subjects), containing healthy and pathological cases (acute myocardial infarction, DCM and HCM). We measured the mean Dice coefficient and Hausdorff distance for segmentation accuracy, and the absolute end point error for motion accuracy, and we conducted a study of the discrimination power of the strain and strain rate between populations of healthy and pathological subjects. The results demonstrated that our method effectively quantifies myocardial strain and strain rate, showing distinct patterns across different cardiac conditions achieving notable statistical significance. Results also show that the method's accuracy is on par with iterative non-parametric registration methods and is also capable of estimating regional strain values.Conclusion.Our method proves to be a powerful tool for cardiac strain analysis, achieving results comparable to other state-of-the-art methods, and computational efficiency over traditional methods.

Postural balance is crucial for daily activities, relying on the coordination of sensory systems. Balance impairment, common in the elderly, is a leading cause of mortality in this population. To analyze balance, methods like postural adjustment analysis using electromyography (EMG) have been developed. With age, women tend to experience reduced mobility and greater muscle loss compared to men. However, few studies have focused on postural adjustments in women of different ages using EMG of the lower limbs during laterolateral and anteroposterior movements. This gap could reveal a decrease in muscle activation time with aging, as activation time is vital for postural adjustments. This study aimed to analyze muscle activation times in women of different ages during postural adjustments. Thirty women were divided into two groups: young and older women. A controlled biaxial force platform was used for static and dynamic balance tests while recording lower limb muscle activity using EMG. Data analysis focused on identifying muscle activation points and analyzing postural adjustment times. Results showed significant differences in muscle activation times between the two groups across various muscles and platform tilt conditions. Younger women had longer muscle activation times than older women, particularly during laterolateral platform inclinations. In anteroposterior movements, older women exhibited longer activation times compared to their laterolateral performance, with fewer differences between the groups. Overall, older women had shorter muscle activation times than younger women, suggesting a potential indicator of imbalance and increased fall risk.

Objective.While the biological effective dose (BED) has been used to estimate the damage to tumor cells in radiotherapy, BED does not consider intrafractional interruption (IFI) occurring during irradiation. We aim to develop a framework to evaluate the decrease in BED [ΔBED] and to create a plan compensating for the decrease by IFI.Approach.ΔBEDwas calculated using a model based on the microdosimetric kinetic model (MKM) for four brain tumor cases treated using a volumetric-modulated arc therapy. Four biologically compensated plans (BCPs) were created in the treatment planning system by a single-time optimization using a base plan consideringΔBEDcreated in in-house software and optimization objectives for the original clinically delivered plan to achieve a homogeneous BED distribution within the planning target volume (PTV). The BED-volume histogram was evaluated for non-compensated plan and BCP with different timepoint of interruption, a percentage of gantry rotation angle (GRA) before interruption in planned GRA,ηand duration of interruptionτ. Characteristics of the dose accumulation were analyzed for different collimator angle sets, Plan A (10°, 85°) and Plan B (45° and 315°), for the first case.Main Results.Hot spots in theΔBEDdistribution forη= 25%, 50%, and 75% were observed at superior-and-interior ends, central region, and peripheral region in PTV, respectively. These behaviors could be understood by characteristics of the MKM-based model producing maximumΔBEDat 50% of the dose accumulation.ΔBED50%ranged 4.5%-6.6%, 5.0%-7.3%, and 5.3%-7.7% forτ= 60, 90, and 120 min, respectively. Plan A showed fast dose accumulation at superior and inferior edges while slow on peripheries in the lateral dose profile. Plan B showed more homogeneous PD distributions than Plan A during irradiation.Significance.The developed framework successfully evaluated and compensated for the decreased BED distribution.

Magnetic shielding room (MSR) is one of the necessary equipment for measuring magnetocardiography (MCG) and magnetoencephalography (MEG). The traditional closed MSR only focuses on the indicators of the shielded magnetic field, and ignores the patient's feelings within the MSR. In this paper, an open-window MSR is proposed to solve the problem that patients have difficulty in communicating with the outside of closed MSR and have closed fear. The simulation results show that the size and distribution trend of the residual magnetic field in the inner working area of the MSR with shield-duct and active magnetic compensation coil is similar to that of the closed MSR. The method proposed in this paper provides a way to improve the comfort of patients in MSR for measuring MCG and MEG in humans.

Objective.This study proposes a closed-loop brain-machine interface (BMI) based on spinal cord stimulation to inhibit epileptic seizures, applying a semi-supervised machine learning approach that learns from Local Field Potential (LFP) patterns acquired on the pre-ictal (preceding the seizure) condition.Approach.LFP epochs from the hippocampus and motor cortex are band-pass filtered from 1 to 13 Hz, to obtain the time-frequency representation using the continuous Wavelet transform, and successively calculate the phase lock values (PLV). As a novelty, theZ-score-based PLV normalization using both modifiedk-means and Davies-Bouldin's measure for clustering is proposed here. Consequently, a generic seizure's detector is calibrated for detecting seizures on the normalized PLV, and enables the spinal cord stimulation for periods of 30 s in a closed-loop, while the BMI system detects seizure events. To calibrate the proposed BMI, a dataset with LFP signals recorded on five Wistar rats during basal state and epileptic crisis was used. The epileptic crisis was induced by injecting pentylenetetrazol (PTZ). Afterwards, two experiments without/with our BMI were carried out, inducing epileptic crisis by PTZ in Wistar rats.Main results.Stronger seizure events of high LFP amplitudes and long time periods were observed in the rat, when the BMI system was not used. In contrast, short-time seizure events of relative low intensity were observed in the rat, using the proposed BMI. The proposed system detected on unseen data the synchronized seizure activity in the hippocampus and motor cortex, provided stimulation appropriately, and consequently decreased seizure symptoms.Significance.Low-frequency LFP signals from the hippocampus and motor cortex, and cord spinal stimulation can be used to develop accurate closed-loop BMIs for early epileptic seizures inhibition, as an alternative treatment.