Characteristics of Acute Cartilage Response After Mechanical Loading in Patients with Early-Mild Knee Osteoarthritis.

This study determined whether the acute cartilage response, assessed by cartilage thickness and echo intensity, differs between patients with early-mild knee osteoarthritis (OA) and healthy controls. We recruited 56 women aged ≥ 50 years with Kellgren-Lawrence (KL) grade ≤ 2 (age, 70.6 ± 7.4 years; height, 153.7 ± 5.2 cm; weight, 51.9 ± 8.2 kg). Based on KL grades and knee symptoms, the participants were classified into control (KL ≤ 1, asymptomatic, n = 27) and early-mild knee OA groups (KL 1 and symptomatic, KL 2, n = 29). Medial femoral cartilage thickness and echo intensity were assessed using ultrasonographic B-mode images before and after treadmill walking (15 min, 3.3 km/h). To investigate the acute cartilage response, repeated-measures analysis of covariance (groups × time) with adjusted age, external knee moment impulse, steps during treadmill walking, and cartilage thickness at pre-walking was performed. A significant interaction was found at the tibiofemoral joint; after walking, the cartilage thickness was significantly decreased in the early-mild knee OA group compared to the control group (p = 0.002). At the patellofemoral joint, a significant main effect of time was observed, but no interaction was detected (p = 0.802). No changes in cartilage echo intensity at either the tibiofemoral or patellofemoral joints, and no interactions were noted (p = 0.295 and p = 0.063). As acute cartilage response after walking, the thickness of the medial tibiofemoral joint in the early-mild knee OA was significantly reduced than that in the control group. Thus, greater acute deformation after walking might be a feature found in patients with early-mild knee OA.

Age-related change in gait efficacy and predictors of its decline: A 3-year longitudinal study.

AIM: This study aimed to calculate the minimal clinically important difference (MCID) for a modified Gait Efficacy Scale (mGES) over 3 years and to clarify the predictors of mGES decline. METHODS: In total, 87 community-dwelling older adults were enrolled in this 3-year longitudinal study. The mGES, fall history and physical function (chair stand frequency, open-eyes one-leg stand, open-close stepping test, walking speed, walking endurance [shuttle stamina walk test] and physical activity) were assessed at baseline. After a 3-year follow-up period, the mGES and Global Rating of Change Scale were assessed. The MCID was calculated using anchor-based methods, with the Global Rating of Change Scale as an anchor. The participants were classified into the decline and keep groups based on whether the changes in the mGES were greater than the MCID. A logistic regression analysis was conducted using the mGES as the dependent variable and physical characteristics, fall history, and physical function as independent variables. RESULTS: The MCID for the mGES over 3 years was -7.38 points. A logistic regression analysis identified low open-close stepping (odds ratio, 0.87; 95% confidence interval, 0.782-0.985; P = 0.027) and the shuttle stamina walk test (odds ratio, 0.974; 95% confidence interval, 0.949-1.000; P = 0.049) as predictors of the mGES decline. CONCLUSION: These findings suggest that a change of 7.38 points in the mGES was clinically significant and that poor agility and walking endurance can predict future decline in the mGES. Geriatr Gerontol Int 2024; 24: 90-94.

Understanding muscle coordination during gait based on muscle synergy and its association with symptoms in patients with knee osteoarthritis.

OBJECTIVE: We aimed to investigate the muscle coordination differences between a control group and patients with mild and severe knee osteoarthritis (KOA) using muscle synergy analysis and determine whether muscle coordination was associated with symptoms of KOA. METHOD: Fifty-three women with medial KOA and 19 control patients participated in the study. The gait analyses and muscle activity measurements of seven lower limb muscles were assessed using a motion capture system and electromyography. Gait speed and knee adduction moment impulse were calculated. The spatiotemporal components of muscle synergy were extracted using non-negative matrix factorization, and the dynamic motor control index during walking (walk-DMC) was computed. The number of muscle synergy and their spatiotemporal components were compared among the mild KOA, severe KOA, and control groups. Moreover, the association between KOA symptoms with walk-DMC and other gait parameters was evaluated using multi-linear regression analysis. RESULTS: The number of muscle synergies was lower in mild and severe KOA compared with those in the control group. In synergy 1, the weightings of biceps femoris and gluteus medius in severe KOA were higher than that in the control group. In synergy 3, the weightings of higher tibial anterior and lower gastrocnemius lateralis were confirmed in the mild KOA group. Regression analysis showed that the walk-DMC was independently associated with knee-related symptoms of KOA after adjusting for the covariates. CONCLUSIONS: Muscle coordination was altered in patients with KOA. The correlation between muscle coordination and KOA may be attributed to the knee-related symptoms. Key points • Patients with knee osteoarthritis (OA) experienced a deterioration in muscle coordination when walking. • Loss of muscle coordination was associated with severe knee-related symptoms in knee OA. • Considering muscle coordination as a knee OA symptom-related factor may provide improved treatment.

Driver's Cognitive Function Estimation Using Daily Driving Data.

Driving assistance systems that support drivers by adapting to driver characteristics can provide appropriate feedback and prevent traffic accidents. Cognitive function is helpful information for such systems to assist older drivers, and automatic estimation of drivers' cognitive function enables systems to utilize this information without being burdensome to these drivers. Therefore, this study aims to estimate drivers' cognitive function from daily driving data. We focus on modeling the scores of Trail Making Test (A) and (B) as measures of cognitive function, which indicate general cognitive ability. The main challenge is learning the generalized mapping function to the cognitive status from driving behavioral features extracted from the different driving routes of each driver. To address this problem, the proposed method focuses on particular driving scenarios in which differences in cognitive function can be observed. We evaluate the performance of the proposed model and the effectiveness of driving scenario information. Experimental results show that the results of Trail Making Tests (A) and (B) can be estimated with Spearman rank correlation coefficients of r = 0.34 and 0.48, respectively. In addition, the proposed method makes it easier to analyze the relationships between driving behaviors and cognitive function by comparing driving behaviors (e.g., steering angle velocity) in specific driving scenarios (e.g., intersections).

Dementia Scale Classification with Sequential Model from Sleep Activity Data.

Dementia, a disorder caused by brain diseases, has been found to influence the sleep patterns of patients. The finding indicates that monitoring sleep activity is helpful to detect the change in cognitive status. With this in mind, the aim of this study is to explore the possibility to develop a machine learning model for classifying the scores of dementia screening tests based on sleep activity data which could be recorded with less burden for participants. In this study, We collected sleep activity data from 124 elderly patients with varying cognitive states, including heart rate, respiratory rate and depth of sleep, using a single sensor. The score of Mini Mental State Estimation (MMSE) cognitive test is used to determine the level of cognitive states. First, we conducted a statistical analysis of the measured sleep activity data to find specific features observed in people with low-MMSE scores. Second, we utilized an efficient sequence model for capturing time-series changes in sleep activity for binary classification of the dementia scale to detect such low-MMSE people. Our findings revealed significant distinctions in sleep patterns between high and low cognitive status groups, and in the classification task, a maximum macro F1 score of 0.67 was achieved using LSTM models. Our results suggest the validity of using sleep activity data for the prediction of dementia classification.

Ultrasonographic echo intensity in the medial femoral cartilage is enhanced prior to cartilage thinning in women with early mild knee osteoarthritis.

PURPOSE: We aimed to determine whether altered cartilage echo intensity is associated with knee osteoarthritis (OA) severity and whether the alteration occurs before thinning of the femoral cartilage in knee OA. METHODS: The medial femoral cartilage thickness and echo intensity of 118 women aged ≥ 50 years were assessed using an ultrasound imaging device. Based on the Kellgren-Lawrence (KL) grade and knee symptoms, participants were classified into five groups: control (asymptomatic grades 0-1), early OA (symptomatic grade 1), grade 2, grade 3, and grade 4. Analysis of covariance, with adjusted age and height, and the Sidak post hoc test were used to assess the differences in cartilage thickness and echo intensity in knees with varying OA severity. RESULTS: The echo intensity on longitudinal images, equivalent to the tibiofemoral weight-bearing surface, was significantly higher in the grade 2 group than that in the control group (p = 0.049). However, no significant difference was noted in cartilage thickness (n.s.). In the grades 3 and 4 groups, cartilage thickness became thinner as OA progressed (p < 0.001 and p < 0.001, respectively). However, the cartilage echo intensity was not significantly enhanced compared with that of the grade 2 group (n.s.). There were no significant differences in the cartilage thickness and echo intensity between the early OA and control groups on the longitudinal images (n.s.). CONCLUSIONS: The echo intensity of the medial femoral cartilage was high in patients with KL grade 2, without decreased thickness. Our findings suggested that higher echo intensity is a feature of early cartilage degeneration in mild knee OA. Further studies are needed to establish this feature as a useful screening parameter of early cartilage degeneration in knee OA. LEVEL OF EVIDENCE: Level III.

A higher intramuscular fat in vastus medialis is associated with functional disabilities and symptoms in early stage of knee osteoarthritis: a case-control study.

BACKGROUND: The characteristics of muscle degeneration in individual quadriceps in early knee osteoarthritis (OA) and the association of muscle quantity and quality on knee dysfunction remain unclear. This study aimed to clarify the characteristics of muscle degeneration in individual quadriceps muscles in early knee OA and elucidate the association of muscle volume and intramuscular adipose tissue (intraMAT) with knee dysfunction, including functional disabilities, symptoms, and joint morphology. METHODS: Fifty participants were categorized into early knee OA and healthy control groups. 3.0 T magnetic resonance imaging (MRI) using T1-weighted and Dixon methods and 3D SPACE in the thigh muscle and knee joint regions was performed. Quadriceps muscle volume, intraMAT, and whole-organ MRI score (WORMS) were assessed. The Knee Society Score (KSS) was used to evaluate functional disabilities and knee symptoms. Univariate analysis of variance was conducted with covariates to clarify the differences in muscle volume and intraMAT between the two groups. Multiple linear regression analyses were performed using the KSS function and symptom subcategories and WORMS as dependent variables and muscle volume, intraMAT, and the presence of early knee OA as independent variables, such as potential confounders. RESULTS: The quadriceps intraMAT, especially in the vastus medialis (VM), was significantly higher in patients with early knee OA than in healthy controls. The VM intraMAT, not muscle volume, was significantly associated with KSS function [B = - 3.47; 95% confidence interval [CI], - 5.24 to - 1.71; p < 0.001] and symptom scores [B = - 0.63; 95% CI, - 1.09 to - 0.17; p = 0.008], but not with WORMS. CONCLUSION: These findings suggest that higher VM intraMAT is characteristic of quadriceps muscle degeneration in early knee OA and its increase is associated with functional disabilities and symptoms.

Assessment of fore-, mid-, and rear-foot alignment and their association with knee symptoms and function in patients with knee osteoarthritis.

OBJECTIVE: Hallux valgus, flatfoot, and rearfoot eversion are well-known major complications of knee osteoarthritis (OA). However, there is no consensus on the association between these foot malalignments and knee symptoms or function. Thus, this study aimed to examine the association between foot alignment and knee symptoms or function in patients with knee OA. METHODS: Female patients aged ≥ 50 years with symptomatic knee OA participated in this study. Knee symptoms and function were assessed using the Knee Society Scoring System (KSS). Hallux valgus, navicular/foot ratio, and leg heel alignment were used as the forefoot, midfoot, and rearfoot alignment indices, respectively. The navicular/foot ratio was defined as the ratio of the navicular height to the total foot length. We performed multiple linear regression analysis to examine the associations between foot alignment and knee symptoms or function. RESULTS: Seventy-eight participants participated our study. KSS symptom score was significantly associated with navicular/foot ratio (regression coefficient [ß], -0.30; 95% confidence interval [CI], -109.2 to -20.5; P = 0.005), knee extensor strength (ß, 0.32; 95% CI, 0.02 to 0.09; P = 0.004), and age (ß, 0.24; 95% CI, 0.01 to 0.32; P = 0.036). KSS function score was not associated with foot alignments but with knee extensor strength (ß, 0.40; 95% CI, 0.10 to 0.33; P = 0.001) and body mass index (ß, -0.35; 95% CI, -2.82 to -0.66; P = 0.002). CONCLUSIONS: Knee symptoms were significantly associated with midfoot alignment in patients with medial knee OA. This suggests that lower navicular height in patients with medial knee OA may relate with the alleviation of knee symptoms. Key Points • In patients with medial knee OA, midfoot alignment was significantly associated with knee symptoms in patients with medial knee OA; however, knee function was not associated with foot alignment. • Lower navicular height in patients with medial knee OA may relate with the alleviation of knee symptoms.

Hydration status and running performance during cool and hot training sessions in rugby union forwards and backs.

BACKGROUND: Rugby showed a high incidence of exertional heatstroke. Different physiques and running performances between the forward and back players (FW and BK) may result in different heatstroke risks. This study aimed to compare the hydration status, running performance, and perceived heatstroke symptoms (PHS) between cool and hot environment training (HT and CT) in university rugby union FW and BK. METHODS: Thirteen university rugby players (seven forwards and six backs) participated in this study. During both conditions, players were allowed to drink water and sports drink, and the amount of fluid intake was recorded. Body mass was measured pre- and post-training, and weight loss was calculated. Sweat loss was calculated based on body mass and fluid intake. During training, running performance was measured using GPS. The presence of PHS was assessed using a questionnaire administered after training. RESULTS: Fluid intake and sweat loss were higher in the HT as opposed to the CT, and FW showed higher fluid intake and dehydration than BK. However, there were no significant differences in weight loss observed during data collection. Running distance per minute and maximum speed were higher in BK than in FW, but there was no significant difference between conditions. Although a significant weight loss was not observed between conditions, the number of PHS was higher in the HT. CONCLUSIONS: Although BK had a higher running distance and maximum speed than FW during training, a higher cycle of fluid intake and sweat loss was observed in the FW than that in the BK.

Enhanced echo intensity in vastus medialis is associated with worsening of functional disabilities and symptoms in patients with knee osteoarthritis: a 3 years longitudinal study.

Patients with knee osteoarthritis (OA) experience muscle quality loss, and is characterized by the enhanced echo intensity (EI) of the vastus medialis (VM) muscles and a high extracellular water-to-intracellular water (ECW/ICW) ratio of the thigh. This study aimed to elucidate the association between muscle degeneration and the worsening of functional disabilities and symptoms in patients with KOA over 3 years duration. Thirty-three patients with KOA who completed follow-up over 3 years were included in the analysis. The knee scoring system (KSS) was used to evaluate the functional abilities and symptoms. Based on the 3 years change in KSS scores, patients were classified into progressive or non-progressive groups. Muscle thickness (MT) and EI of the VM were determined using ultrasonography. The ECW/ICW ratio was measured using segmental-bioelectrical impedance spectroscopy. Multivariable logistic regression analyses were conducted with the groups as the dependent variables and VM-MT, VM-EI, and ECW/ICW ratio at baseline as independent variables, including potential confounders. Thirteen (39.4%) patients showed progressive features. VM-EI at baseline was significantly associated with the progression of functional disabilities (adjusted odds ratio [OR] 1.24; 95% confidence interval [CI] 1.03 - 1.50) and symptoms (adjusted OR 1.13; 95% CI 1.01 - 1.25). Enhanced VM-EI was associated with the worsening of functional disabilities and symptoms in patients with KOA over a period of 3 years. Therefore, the assessment of VM-EI using ultrasonography is a useful indicator for predicting the future worsening of KOA.

Machine Learning Algorithm to Predict Worsening of Flexion Range of Motion After Total Knee Arthroplasty.

Background: Predicting the worsening of flexion range of motion (ROM) during the course post-total knee arthroplasty (TKA) is clinically meaningful. This study aimed to create a model that could predict the worsening of knee flexion ROM during the TKA course using a machine learning algorithm and to examine its accuracy and predictive variables. Methods: Altogether, 344 patients (508 knees) who underwent TKA were enrolled. Knee flexion ROM worsening was defined as ROM decrease of ≥10° between 1 month and 6 months post-TKA. A predictive model for worsening was investigated using 31 variables obtained retrospectively. 5 data sets were created using stratified 5-fold cross-validation. Total data (n = 508) were randomly divided into training (n = 407) and test (n = 101) data. On each data set, 5 machine learning algorithms (logistic regression, support vector machine, multilayer perceptron, decision tree, and random forest) were applied; the optimal algorithm was decided. Then, variables extracted using recursive feature elimination were combined; by combination, random forest models were created and compared. The accuracy rate and area under the curve were calculated. Finally, the importance of variables was calculated for the most accurate model. Results: The knees were classified into the worsening (n = 124) and nonworsening (n = 384) groups. The random forest model with 3 variables had the highest accuracy rate, 0.86 (area under the curve, 0.72). These variables (importance) were joint-line change (1.000), postoperative femoral-tibial angle (0.887), and hemoglobin A1c (0.468). Conclusions: The random forest model with the above variables is useful for predicting the worsening of knee flexion ROM during the course post-TKA.

Geant4-DNA simulation of the pre-chemical stage of water radiolysis and its impact on initial radiochemical yields.

This paper demonstrates the impact of the pre-chemical stage, especially the dissociation scheme and the associated probabilities, on water radiolysis simulation using the Geant4-DNA Monte Carlo track structure simulation toolkit. The models and parameters provided by TRACs have been collected and implemented into Geant4-DNA. In order to evaluate their influence on water radiolysis simulation, the radiochemical yields (G-values) are evaluated as a function of time and LET using the "chem6" Geant4-DNA example, and they are compared with published experimental and calculated data. The new pre-chemical models lead to a better agreement with literature data than the default pre-chemical models of Geant4-DNA, especially for OH radicals and H2O2. The revised chemistry constructor "G4EmDNAChemistry_option3" is available in Geant4-DNA version 10.7.

Quantitative estimation of track segment yields of water radiolysis species under heavy ions around Bragg peak energies using Geant4-DNA.

We evaluate the track segment yield G' of typical water radiolysis products (eaq-, ·OH and H2O2) under heavy ions (He, C and Fe ions) using a Monte Carlo simulation code in the Geant4-DNA. Furthermore, we reproduce experimental results of ·OH of He and C ions around the Bragg peak energies (< 6 MeV/u). In the relatively high energy region (e.g., > 10 MeV/u), the simulation results using Geant4-DNA have agreed with experimental results. However, the G-values of water radiolysis species have not been properly evaluated around the Bragg peak energies, at which high ionizing density can be expected. Around the Bragg peak energy, dense continuous secondary products are generated, so that it is necessary to simulate the radical-radical reaction more accurately. To do so, we added the role of secondary products formed by irradiation. Consequently, our simulation results are in good agreement with experimental results and previous simulations not only in the high-energy region but also around the Bragg peak. Several future issues are also discussed regarding the roles of fragmentation and multi-ionization to realize more realistic simulations.

Assessment of DNA damage with an adapted independent reaction time approach implemented in Geant4-DNA for the simulation of diffusion-controlled reactions between radio-induced reactive species and a chromatin fiber.

PURPOSE: Simulation of indirect damage originating from the attack of free radical species produced by ionizing radiation on biological molecules based on the independent pair approximation is investigated in this work. In addition, a new approach, relying on the independent pair approximation that is at the origin of the independent reaction time (IRT) method, is proposed in the chemical stage of Geant4-DNA. METHODS: This new approach has been designed to respect the current Geant4-DNA chemistry framework while proposing a variant IRT method. Based on the synchronous algorithm, this implementation allows us to access the information concerning the position of radicals and may make it more convenient for biological damage simulations. Estimates of the evolution of free species as well as biological hits in a segment of DNA chromatin fiber in Geant4-DNA were compared for the dynamic time step approach of the step-by-step (SBS) method, currently used in Geant4-DNA, and this newly implemented IRT. RESULTS: Results show a gain in computation time of a factor of 30 for high LET particle tracks with a better than 10% agreement on the number of DNA hits between the value obtained with the IRT method as implemented in this work and the SBS method currently available in Geant4-DNA. CONCLUSION: Offering in Geant4-DNA more efficient methods for the chemical step based on the IRT method is a task in progress. For the calculation of biological damage, information on the position of chemical species is a crucial point. This can be achieved using the method presented in this paper.

Independent reaction times method in Geant4-DNA: Implementation and performance.

PURPOSE: The simulation of individual particle tracks and the chemical stage following water radiolysis in biological tissue is an effective means of improving our knowledge of the physico-chemical contribution to the biological effect of ionizing radiation. However, the step-by-step simulation of the reaction kinetics of radiolytic species is the most time-consuming task in Monte Carlo track-structure simulations, with long simulation times that are an impediment to research. In this work, we present the implementation of the independent reaction times (IRT) method in Geant4-DNA Monte Carlo toolkit to improve the computational efficiency of calculating G-values, defined as the number of chemical species created or lost per 100 eV of deposited energy. METHODS: The computational efficiency of IRT, as implemented, is compared to that from available Geant4-DNA step-by-step simulations for electrons, protons and alpha particles covering a wide range of linear energy transfer (LET). The accuracy of both methods is verified using published measured data from fast electron irradiations for • OH and e aq - for time-dependent G-values. For IRT, simulations in the presence of scavengers irradiated by cobalt-60 γ-ray and 2 MeV protons are compared with measured data for different scavenging capacities. In addition, a qualitative assessment comparing measured LET-dependent G-values with Geant4-DNA calculations in pure liquid water is presented. RESULTS: The IRT improved the computational efficiency by three orders of magnitude relative to the step-by-step method while differences in G-values by 3.9% at 1 µs were found. At 7 ps, • OH and e aq - yields calculated with IRT differed from recent published measured data by 5% ± 4% and 2% ± 4%, respectively. At 1 µs, differences were 9% ± 5% and 6% ± 7% for • OH and e aq - , respectively. Uncertainties are one standard deviation. Finally, G-values at different scavenging capacities and LET-dependent G-values reproduced the behavior of measurements for all radiation qualities. CONCLUSION: The comprehensive validation of the Geant4-DNA capabilities to accurately simulate the chemistry following water radiolysis is an ongoing work. The implementation presented in this work is a necessary step to facilitate performing such a task.

Evaluation of early radiation DNA damage in a fractal cell nucleus model using Geant4-DNA.

The advancement of multidisciplinary research fields dealing with ionising radiation induced biological damage - radiobiology, radiation physics, radiation protection and, in particular, medical physics - requires a clear mechanistic understanding of how cellular damage is induced by ionising radiation. Monte Carlo (MC) simulations provide a promising approach for the mechanistic simulation of radiation transport and radiation chemistry, towards the in silico simulation of early biological damage. We have recently developed a fully integrated MC simulation that calculates early single strand breaks (SSBs) and double strand breaks (DSBs) in a fractal chromatin based human cell nucleus model. The results of this simulation are almost equivalent to past MC simulations when considering direct/indirect strand break fraction, DSB yields and fragment distribution. The simulation results agree with experimental data on DSB yields within 13.6% on average and fragment distributions agree within an average of 34.8%.

MPEXS-DNA, a new GPU-based Monte Carlo simulator for track structures and radiation chemistry at subcellular scale.

PURPOSE: Track structure simulation codes can accurately reproduce the stochastic nature of particle-matter interactions in order to evaluate quantitatively radiation damage in biological cells such as DNA strand breaks and base damage. Such simulations handle large numbers of secondary charged particles and molecular species created in the irradiated medium. Every particle and molecular species are tracked step-by-step using a Monte Carlo method to calculate energy loss patterns and spatial distributions of molecular species inside a cell nucleus with high spatial accuracy. The Geant4-DNA extension of the Geant4 general-purpose Monte Carlo simulation toolkit allows for such track structure simulations and can be run on CPUs. However, long execution times have been observed for the simulation of DNA damage in cells. We present in this work an improvement of the computing performance of such simulations using ultraparallel processing on a graphical processing unit (GPU). METHODS: A new Monte Carlo simulator named MPEXS-DNA, allowing high computing performance by using a GPU, has been developed for track structure and radiolysis simulations at the subcellular scale. MPEXS-DNA physics and chemical processes are based on Geant4-DNA processes available in Geant4 version 10.02 p03. We have reimplemented the Geant4-DNA process codes of the physics stage (electromagnetic processes of charged particles) and the chemical stage (diffusion and chemical reactions for molecular species) for microdosimetry simulation by using the CUDA language. MPEXS-DNA can calculate a distribution of energy loss in the irradiated medium caused by charged particles and also simulate production, diffusion, and chemical interactions of molecular species from water radiolysis to quantitatively assess initial damage to DNA. The validation of MPEXS-DNA physics and chemical simulations was performed by comparing various types of distributions, namely the radial dose distributions for the physics stage, and the G-value profiles for each chemical product and their linear energy transfer dependency for the chemical stage, to existing experimental data and simulation results obtained by other simulation codes, including PARTRAC. RESULTS: For physics validation, radial dose distributions calculated by MPEXS-DNA are consistent with experimental data and numerical simulations. For chemistry validation, MPEXS-DNA can also reproduce G-value profiles for each molecular species with the same tendency as existing experimental data. MPEXS-DNA also agrees with simulations by PARTRAC reasonably well. However, we have confirmed that there are slight discrepancies in G-value profiles calculated by MPEXS-DNA for molecular species such as H2 and H2 O2 when compared to experimental data and PARTRAC simulations. The differences in G-value profiles between MPEXS-DNA and PARTRAC are caused by the different chemical reactions considered. MPEXS-DNA can drastically boost the computing performance of track structure and radiolysis simulations. By using NVIDIA's GPU devices adopting the Volta architecture, MPEXS-DNA has achieved speedup factors up to 2900 against Geant4-DNA simulations with a single CPU core. CONCLUSION: The MPEXS-DNA Monte Carlo simulation achieves similar accuracy to Monte Carlo simulations performed using other codes such as Geant4-DNA and PARTRAC, and its predictions are consistent with experimental data. Notably, MPEXS-DNA allows calculations that are, at maximum, 2900 times faster than conventional simulations using a CPU.

Geant4-DNA track-structure simulations for gold nanoparticles: The importance of electron discrete models in nanometer volumes.

PURPOSE: Gold nanoparticles (GNPs) are known to enhance the absorbed dose in their vicinity following photon-based irradiation. To investigate the therapeutic effectiveness of GNPs, previous Monte Carlo simulation studies have explored GNP dose enhancement using mostly condensed-history models. However, in general, such models are suitable for macroscopic volumes and for electron energies above a few hundred electron volts. We have recently developed, for the Geant4-DNA extension of the Geant4 Monte Carlo simulation toolkit, discrete physics models for electron transport in gold which include the description of the full atomic de-excitation cascade. These models allow event-by-event simulation of electron tracks in gold down to 10 eV. The present work describes how such specialized physics models impact simulation-based studies on GNP-radioenhancement in a context of x-ray radiotherapy. METHODS: The new discrete physics models are compared to the Geant4 Penelope and Livermore condensed-history models, which are being widely used for simulation-based NP radioenhancement studies. An ad hoc Geant4 simulation application has been developed to calculate the absorbed dose in liquid water around a GNP and its radioenhancement, caused by secondary particles emitted from the GNP itself, when irradiated with a monoenergetic electron beam. The effect of the new physics models is also quantified in the calculation of secondary particle spectra, when originating in the GNP and when exiting from it. RESULTS: The new physics models show similar backscattering coefficients with the existing Geant4 Livermore and Penelope models in large volumes for 100 keV incident electrons. However, in submicron sized volumes, only the discrete models describe the high backscattering that should still be present around GNPs at these length scales. Sizeable differences (mostly above a factor of 2) are also found in the radial distribution of absorbed dose and secondary particles between the new and the existing Geant4 models. The degree to which these differences are due to intrinsic limitations of the condensed-history models or to differences in the underling scattering cross sections requires further investigation. CONCLUSIONS: Improved physics models for gold are necessary to better model the impact of GNPs in radiotherapy via Monte Carlo simulations. We implemented discrete electron transport models for gold in Geant4 that is applicable down to 10 eV including the modeling of the full de-excitation cascade. It is demonstrated that the new model has a significant positive impact on particle transport simulations in gold volumes with submicron dimensions compared to the existing Livermore and Penelope condensed-history models of Geant4.