Characterisation of the UK high energy proton research beamline for high and ultra-high dose rate (FLASH) irradiation.

Objective. This work sets out the capabilities of the high energy proton research beamline developed in the Christie proton therapy centre for Ultra-High Dose Rate (UHDR) irradiation and FLASH experiments. It also characterises the lower limits of UHDR operation for this Pencil Beam Scanning (PBS) proton hardware.Approach. Energy dependent nozzle transmission was measured using a Faraday Cup beam collector. Spot size was measured at the reference plane using a 2D scintillation detector. Integrated depth doses (IDDs) were measured. EBT3 Gafchromic film was used to compare UHDR and conventional dose rate spots. Our beam monitor calibration methodolgy for UHDR is described. A microDiamond detector was used to determine dose rates at zref. Instantaneous depth dose rates were calculated for 70-245 MeV. PBS dose rate distributions were calculated using Folkerts and Van der Water definitions.Main results. Transmission of 7.05 ± 0.1% is achieveable corresponding to a peak instantaneous dose rate of 112.7 Gy s-1. Beam parameters are comparable in conventional and UHDR mode with a spot size ofσx= 4.6 mm,σy= 6.6 mm. Dead time in the beam monitoring electonics warrants a beam current dependent MU correction in the present configuration. Fast beam scanning of 26.4 m s-1(X) and 12.1 m s-1(Y) allows PBS dose rates of the order tens of Grays per second.Significance. UHDR delivery is possible for small field sizes and high energies enabling research into the FLASH effect with PBS protons at our facility. To our knowledge this is also the first thorough characterisation of UHDR irradiation using the hardware of this clinical accelerator at energies less than 250 MeV. The data set out in this publication can be used for designing experiments at this UK research facility and inform the possible future clinical translation of UHDR PBS proton therapy.

Assessing Equity of Access to Proton Beam Therapy: A Literature Review.

Proton beam therapy (PBT) is one of the most advanced radiotherapy technologies, with growing evidence to support its use in specific clinical scenarios and exponential growth of demand and capacity worldwide over the past few decades. However, geographical inequalities persist in the distribution of PBT centres, which translate into variations in access and use of this technology. The aim of this work was to look at the factors that contribute to these inequalities, to help raise awareness among stakeholders, governments and policy makers. A literature search was conducted using the Population, Intervention, Comparison, Outcomes (PICO) criteria. The same search strategy was run in Embase and Medline and identified 242 records, which were screened for manual review. Of these, 24 were deemed relevant and were included in this analysis. Most of the 24 publications included in this review originated from the USA (22/24) and involved paediatric patients, teenagers and young adults (61% for children and/or teenagers and young adults versus 39% for adults). The most reported indicator of disparity was socioeconomic status (16/24), followed by geographical location (13/24). All the studies evaluated in this review showed disparities in the access to PBT. As paediatric patients make up a significant proportion of the PBT-eligible patients, equity of access to PBT also raises ethical considerations. Therefore, further research is needed into the equity of access to PBT to reduce the care gap.

An Update to the Malthus Model for Radiotherapy Utilisation in England.

AIMS: The Malthus Programme predicts national and local radiotherapy demand by combining cancer incidence data with decision trees detailing the indications, and appropriate dose fractionation, for radiotherapy. Since the last model update in 2017, technological advancements and the COVID-19 pandemic have led to increasing hypofractionation of radiotherapy schedules. Indications for radiotherapy have also evolved, particularly in the context of oligometastatic disease. Here we present a brief update on the model for 2021. We have updated the decision trees for breast, prostate, lung and head and neck cancers, and incorporated recent cancer incidence data into our model, generating a current estimate of fraction demand for these four cancer sites across England. MATERIALS AND METHODS: The decision tree update was based on evidence from practice-changing randomised controlled trials, published guidelines, audit data and expert opinion. Site- and stage-specific incidence data were taken from the National Disease Registration Service. We used the updated model to estimate the proportion of patients who would receive radiotherapy (appropriate rate of radiotherapy) and the fraction demand per million population at a national and Clinical Commissioning Group level in 2021. RESULTS: The total predicted fraction demand has decreased by 11.4% across all four cancer sites in our new model, compared with the 2017 version. This reduction can be explained primarily by greater use of hypofractionated treatments (including stereotactic ablative radiotherapy) and a shift towards earlier stage presentation. The only large change in appropriate rate of radiotherapy was an absolute decrease of 3% for lung cancer. CONCLUSIONS: Compared with our previous model, the current version predicts a reduction in fraction demand across England. This is driven principally by hypofractionation of radiotherapy regimens, using technology that requires increasingly complex planning. Treatment complexity and local service factors need to be taken into account when translating fraction burden into linear accelerator demand or throughput.

Variations in Demand across England for the Magnetic Resonance-Linac Technology, Simulated Utilising Local-level Demographic and Cancer Data in the Malthus Project.

AIMS: Cancer incidence varies across England, which affects the local-level demand for treatments. The magnetic resonance-linac (MR-linac) is a new radiotherapy technology that combines imaging and treatment. Here we model the demand and demand variations for the MR-linac across England. MATERIALS AND METHODS: Initial clinical indications were provided by the MR-linac consortium and introduced into the Malthus radiotherapy clinical decision trees. The Malthus model contains Clinical Commissioning Group (CCG) population, cancer incidence and stage presentation data (for lung and prostate) and simulated the demand for the MR-linac for all CCGs and Radiotherapy Operational Delivery Networks (RODN) across England. RESULTS: Based on the initial target clinical indications, the MR-linac could service 16% of England's fraction burden. The simulated fractions/million population demand/annum varies between 3000 and 10 600 fractions/million at the CCG level. Focussing only on the cancer population, the simulated fractions/1000 cancer cases demand/annum ranges from 1028 to 1195 fractions/1000 cases. If a national average for fractions/million demand was then used, at the RODN level, the variation from actual annual demand ranges from an overestimation of 8400 fractions to an underestimation of 5800 fractions. When using the national average fractions/1000 cases, the RODN demand varies from an overestimation of 3200 fractions to an underestimation of 3000 fractions. CONCLUSIONS: Planning cancer services is complex due to regional variations in cancer burden. The variations in simulated demand of the MR-linac highlight the requirement to use local-level data when planning to introduce a new technology.

Determining the parameter space for effective oxygen depletion for FLASH radiation therapy.

There has been a recent revival of interest in the FLASH effect, after experiments have shown normal tissue sparing capabilities of ultra-high-dose-rate radiation with no compromise on tumour growth restraint. A model has been developed to investigate the relative importance of a number of fundamental parameters considered to be involved in the oxygen depletion paradigm of induced radioresistance. An example eight-dimensional parameter space demonstrates the conditions under which radiation may induce sufficient depletion of oxygen for a diffusion-limited hypoxic cellular response. Initial results support experimental evidence that FLASH sparing is only achieved for dose rates on the order of tens of Gy s-1or higher, for a sufficiently high dose, and only for tissue that is slightly hypoxic at the time of radiation. We show that the FLASH effect is the result of a number of biological, radiochemical and delivery parameters. Also, the threshold dose for a FLASH effect occurring would be more prominent when the parameterisation was optimised to produce the maximum effect. The model provides a framework for further FLASH-related investigation and experimental design. An understanding of the mechanistic interactions producing an optimised FLASH effect is essential for its translation into clinical practice.

Evaluating very high energy electron RBE from nanodosimetric pBR322 plasmid DNA damage.

This paper presents the first plasmid DNA irradiations carried out with Very High Energy Electrons (VHEE) over 100-200 MeV at the CLEAR user facility at CERN to determine the Relative Biological Effectiveness (RBE) of VHEE. DNA damage yields were measured in dry and aqueous environments to determine that ~ 99% of total DNA breaks were caused by indirect effects, consistent with other published measurements for protons and photons. Double-Strand Break (DSB) yield was used as the biological endpoint for RBE calculation, with values found to be consistent with established radiotherapy modalities. Similarities in physical damage between VHEE and conventional modalities gives confidence that biological effects of VHEE will also be similar-key for clinical implementation. Damage yields were used as a baseline for track structure simulations of VHEE plasmid irradiation using GEANT4-DNA. Current models for DSB yield have shown reasonable agreement with experimental values. The growing interest in FLASH radiotherapy motivated a study into DSB yield variation with dose rate following VHEE irradiation. No significant variations were observed between conventional and FLASH dose rate irradiations, indicating that no FLASH effect is seen under these conditions.

Inter- and intra-fractional stability of rectal gas in pelvic cancer patients during MRIgRT.

PURPOSE: Due to the electron return effect (ERE) during magnetic resonance imaging guided radiotherapy (MRIgRT), rectal gas during pelvic treatments can result in hot spots of over-dosage in the rectal wall. Determining the clinical impact of this effect on rectal toxicity requires estimation of the amount and mobility (and stability) of rectal gas during treatment. We therefore investigated the amount of rectal gas and local inter- and intra-fractional changes of rectal gas in pelvic cancer patients. METHODS: To estimate the volume of gas present at treatment planning, the rectal gas contents in the planning computed tomography (CT) scans of 124 bladder, 70 cervical and 2180 prostate cancer patients were calculated. To estimate inter- and intra-fractional variations in rectal gas, 174 and 131 T2-w MRIs for six cervical and eleven bladder cancer patients were used. These scans were acquired during four scan-sessions (~20-25 min each) at various time-points. Additionally, 258 T2-w MRIs of the first five prostate cancer patients treated using MRIgRT at our center, acquired during each fraction, were analyzed. Rectums were delineated on all scans. The area of gas within the rectum delineations was identified on each MRI slice using thresholding techniques. The area of gas on each slice of the rectum was used to calculate the inter- and intra-fractional group mean, systematic and random variations along the length of the rectum. The cumulative dose perturbation as a result of the gas was estimated. Two approaches were explored: accounting or not accounting for the gas at the start of the scan-session. RESULTS: Intra-fractional variations in rectal gas are small compared to the absolute volume of rectal gas detected for all patient groups. That is, rectal gas is likely to remain stable for periods of 20-25 min. Larger volumes of gas and larger variations in gas volume were observed in bladder cancer patients compared with cervical and prostate cancer patients. For all patients, local cumulative dose perturbations per beam over an entire treatment in the order of 60 % were estimated when gas had not been accounted for in the daily adaption. The calculated dose perturbation over the whole treatment was dramatically reduced in all patients when accounting for the gas in the daily set-up image. CONCLUSION: Rectal gas in pelvic cancer patients is likely to remain stable over the course of an MRIgRT fraction, and also likely to reappear in the same location in multiple fractions, and can therefore result in clinically relevant over-dosage in the rectal wall. The over-dosage is reduced when accounting for gas in the daily adaption.

Experimental verification the electron return effect around spherical air cavities for the MR-Linac using Monte Carlo calculation.

PURPOSE: Dose deposition around unplanned air cavities during magnetic resonance-guided radiotherapy (MRgRT) is influenced by the electron return effect (ERE). This is clinically relevant for gas forming close to or inside organs at risk (OARs) that lie in the path of a single beam, for example, intestinal track during pelvic treatment. This work aims to verify Monte Carlo calculations that predict the dosimetric effects of ERE around air cavities. For this, we use GafChromic EBT3 film inside poly-methyl methacrylate (PMMA) -air phantoms. METHOD: Four PMMA phantoms were produced. Three of the phantoms contained centrally located spherical air cavities (0.5, 3.5, 7.5 cm diameter), and one phantom contained no air. The phantoms were split to sandwich GafChromic EBT3 film in the center. The phantoms were irradiated on an Elekta Unity system using a single 10 × 10 cm2 7-MV photon beam under the influence of a 1.5-T transverse magnetic field. The measurements were replicated using the Elekta Monaco treatment planning system (TPS). Gamma analysis with pass criteria 3%/3 mm was used to compare the measured and calculated dose distributions. We also consider 3%/2 mm, 2%/3 mm, and 2%/2 mm pass criteria for interest. RESULTS: The gamma analysis showed that >95% of the points agreed between the TPS-calculated and measured dose distributions, using 3%/3 mm criteria. The phantom containing the largest air cavity had the lowest agreement, with most of the disagreeing points lying inside the air cavity (dose to air region). CONCLUSIONS: The dose effects due to ERE around spherical air cavities are being calculated in the TPS with sufficient accuracy for clinical use.

In Silico Models of DNA Damage and Repair in Proton Treatment Planning: A Proof of Concept.

There is strong in vitro cell survival evidence that the relative biological effectiveness (RBE) of protons is variable, with dependence on factors such as linear energy transfer (LET) and dose. This is coupled with the growing in vivo evidence, from post-treatment image change analysis, of a variable RBE. Despite this, a constant RBE of 1.1 is still applied as a standard in proton therapy. However, there is a building clinical interest in incorporating a variable RBE. Recently, correlations summarising Monte Carlo-based mechanistic models of DNA damage and repair with absorbed dose and LET have been published as the Manchester mechanistic (MM) model. These correlations offer an alternative path to variable RBE compared to the more standard phenomenological models. In this proof of concept work, these correlations have been extended to acquire RBE-weighted dose distributions and calculated, along with other RBE models, on a treatment plan. The phenomenological and mechanistic models for RBE have been shown to produce comparable results with some differences in magnitude and relative distribution. The mechanistic model found a large RBE for misrepair, which phenomenological models are unable to do. The potential of the MM model to predict multiple endpoints presents a clear advantage over phenomenological models.

Mechanistic modelling supports entwined rather than exclusively competitive DNA double-strand break repair pathway.

Following radiation induced DNA damage, several repair pathways are activated to help preserve genome integrity. Double Strand Breaks (DSBs), which are highly toxic, have specified repair pathways to address them. The main repair pathways used to resolve DSBs are Non-Homologous End Joining (NHEJ) and Homologous Recombination (HR). Cell cycle phase determines the availability of HR, but the repair choice between pathways in the G2 phases where both HR and NHEJ can operate is not clearly understood. This study compares several in silico models of repair choice to experimental data published in the literature, each model representing a different possible scenario describing how repair choice takes place. Competitive only scenarios, where initial protein recruitment determines repair choice, are unable to fit the literature data. In contrast, the scenario which uses a more entwined relationship between NHEJ and HR, incorporating protein co-localisation and RNF138-dependent removal of the Ku/DNA-PK complex, is better able to predict levels of repair similar to the experimental data. Furthermore, this study concludes that co-localisation of the Mre11-Rad50-Nbs1 (MRN) complexes, with initial NHEJ proteins must be modeled to accurately depict repair choice.

Clinically relevant nanodosimetric simulation of DNA damage complexity from photons and protons.

Relative Biological Effectiveness (RBE), the ratio of doses between radiation modalities to produce the same biological endpoint, is a controversial and important topic in proton therapy. A number of phenomenological models incorporate variable RBE as a function of Linear Energy Transfer (LET), though a lack of mechanistic description limits their applicability. In this work we take a different approach, using a track structure model employing fundamental physics and chemistry to make predictions of proton and photon induced DNA damage, the first step in the mechanism of radiation-induced cell death. We apply this model to a proton therapy clinical case showing, for the first time, predictions of DNA damage on a patient treatment plan. Our model predictions are for an idealised cell and are applied to an ependymoma case, at this stage without any cell specific parameters. By comparing to similar predictions for photons, we present a voxel-wise RBE of DNA damage complexity. This RBE of damage complexity shows similar trends to the expected RBE for cell kill, implying that damage complexity is an important factor in DNA repair and therefore biological effect.

A New Standard DNA Damage (SDD) Data Format.

Our understanding of radiation-induced cellular damage has greatly improved over the past few decades. Despite this progress, there are still many obstacles to fully understand how radiation interacts with biologically relevant cellular components, such as DNA, to cause observable end points such as cell killing. Damage in DNA is identified as a major route of cell killing. One hurdle when modeling biological effects is the difficulty in directly comparing results generated by members of different research groups. Multiple Monte Carlo codes have been developed to simulate damage induction at the DNA scale, while at the same time various groups have developed models that describe DNA repair processes with varying levels of detail. These repair models are intrinsically linked to the damage model employed in their development, making it difficult to disentangle systematic effects in either part of the modeling chain. These modeling chains typically consist of track-structure Monte Carlo simulations of the physical interactions creating direct damages to DNA, followed by simulations of the production and initial reactions of chemical species causing so-called "indirect" damages. After the induction of DNA damage, DNA repair models combine the simulated damage patterns with biological models to determine the biological consequences of the damage. To date, the effect of the environment, such as molecular oxygen (normoxic vs. hypoxic), has been poorly considered. We propose a new standard DNA damage (SDD) data format to unify the interface between the simulation of damage induction in DNA and the biological modeling of DNA repair processes, and introduce the effect of the environment (molecular oxygen or other compounds) as a flexible parameter. Such a standard greatly facilitates inter-model comparisons, providing an ideal environment to tease out model assumptions and identify persistent, underlying mechanisms. Through inter-model comparisons, this unified standard has the potential to greatly advance our understanding of the underlying mechanisms of radiation-induced DNA damage and the resulting observable biological effects when radiation parameters and/or environmental conditions change.

Mathematical Modelling for Patient Selection in Proton Therapy.

Proton beam therapy (PBT) is still relatively new in cancer treatment and the clinical evidence base is relatively sparse. Mathematical modelling offers assistance when selecting patients for PBT and predicting the demand for service. Discrete event simulation, normal tissue complication probability, quality-adjusted life-years and Markov Chain models are all mathematical and statistical modelling techniques currently used but none is dominant. As new evidence and outcome data become available from PBT, comprehensive models will emerge that are less dependent on the specific technologies of radiotherapy planning and delivery.

In Silico Non-Homologous End Joining Following Ion Induced DNA Double Strand Breaks Predicts That Repair Fidelity Depends on Break Density.

This work uses Monte Carlo simulations to investigate the dependence of residual and misrepaired double strand breaks (DSBs) at 24 hours on the initial damage pattern created during ion therapy. We present results from a nanometric DNA damage simulation coupled to a mechanistic model of Non-Homologous End Joining, capable of predicting the position, complexity, and repair of DSBs. The initial damage pattern is scored by calculating the average number of DSBs within 70 nm from every DSB. We show that this local DSB density, referred to as the cluster density, can linearly predict misrepair regardless of ion species. The models predict that the fraction of residual DSBs is constant, with 7.3% of DSBs left unrepaired following 24 hours of repair. Through simulation over a range of doses and linear energy transfer (LET) we derive simple correlations capable of predicting residual and misrepaired DSBs. These equations are applicable to ion therapy treatment planning where both dose and LET are scored. This is demonstrated by applying the correlations to an example of a clinical proton spread out Bragg peak. Here we see a considerable biological effect past the distal edge, dominated by residual DSBs.

Nanodosimetric Simulation of Direct Ion-Induced DNA Damage Using Different Chromatin Geometry Models.

Monte Carlo based simulation has proven useful in investigating the effect of proton-induced DNA damage and the processes through which this damage occurs. Clustering of ionizations within a small volume can be related to DNA damage through the principles of nanodosimetry. For simulation, it is standard to construct a small volume of water and determine spatial clusters. More recently, realistic DNA geometries have been used, tracking energy depositions within DNA backbone volumes. Traditionally a chromatin fiber is built within the simulation and identically replicated throughout a cell nucleus, representing the cell in interphase. However, the in vivo geometry of the chromatin fiber is still unknown within the literature, with many proposed models. In this work, the Geant4-DNA toolkit was used to build three chromatin models: the solenoid, zig-zag and cross-linked geometries. All fibers were built to the same chromatin density of 4.2 nucleosomes/11 nm. The fibers were then irradiated with protons (LET 5-80 keV/µm) or alpha particles (LET 63-226 keV/µm). Nanodosimetric parameters were scored for each fiber after each LET and used as a comparator among the models. Statistically significant differences were observed in the double-strand break backbone size distributions among the models, although nonsignificant differences were noted among the nanodosimetric parameters. From the data presented in this article, we conclude that selection of the solenoid, zig-zag or cross-linked chromatin model does not significantly affect the calculated nanodosimetric parameters. This allows for a simulation-based cell model to make use of any of these chromatin models for the scoring of direct ion-induced DNA damage.

Consensus Paper: Cerebellum and Emotion.

Over the past three decades, insights into the role of the cerebellum in emotional processing have substantially increased. Indeed, methodological refinements in cerebellar lesion studies and major technological advancements in the field of neuroscience are in particular responsible to an exponential growth of knowledge on the topic. It is timely to review the available data and to critically evaluate the current status of the role of the cerebellum in emotion and related domains. The main aim of this article is to present an overview of current facts and ongoing debates relating to clinical, neuroimaging, and neurophysiological findings on the role of the cerebellum in key aspects of emotion. Experts in the field of cerebellar research discuss the range of cerebellar contributions to emotion in nine topics. Topics include the role of the cerebellum in perception and recognition, forwarding and encoding of emotional information, and the experience and regulation of emotional states in relation to motor, cognitive, and social behaviors. In addition, perspectives including cerebellar involvement in emotional learning, pain, emotional aspects of speech, and neuropsychiatric aspects of the cerebellum in mood disorders are briefly discussed. Results of this consensus paper illustrate how theory and empirical research have converged to produce a composite picture of brain topography, physiology, and function that establishes the role of the cerebellum in many aspects of emotional processing.

Automatic cell detection in bright-field microscopy for microbeam irradiation studies.

Automatic cell detection in bright-field illumination microscopy is challenging due to cells' inherent optical properties. Applications including individual cell microbeam irradiation demand minimisation of additional cell stressing factors, so contrast-enhancing fluorescence microscopy should be avoided. Additionally, the use of optically non-homogeneous substrates amplifies the problem. This research focuses on the design of a method for automatic cell detection on polypropylene substrate, suitable for microbeam irradiation. In order to fulfil the relative requirements, the Harris corner detector was employed to detect apparent cellular features. These features-corners were clustered based on a dual-clustering technique according to the density of their distribution across the image. Weighted centroids were extracted from the clusters of corners and constituted the targets for irradiation. The proposed method identified more than 88% of the 1,738 V79 Chinese hamster cells examined. Moreover, a processing time of 2.6 s per image fulfilled the requirements for a near real-time cell detection-irradiation system.

Investigation of gold nanoparticle radiosensitization mechanisms using a free radical scavenger and protons of different energies.

Gold nanoparticles (GNPs) have been shown to sensitize cancer cells to x-ray radiation, particularly at kV energies where photoelectric interactions dominate and the high atomic number of gold makes a large difference to x-ray absorption. Protons have a high cross-section for gold at a large range of relevant clinical energies, and so potentially could be used with GNPs for increased therapeutic effect.Here, we investigate the contribution of secondary electron emission to cancer cell radiosensitization and investigate how this parameter is affected by proton energy and a free radical scavenger. We simulate the emission from a realistic cell phantom containing GNPs after traversal by protons and x-rays with different energies. We find that with a range of proton energies (1-250 MeV) there is a small increase in secondaries compared to a much larger increase with x-rays. Secondary electrons are known to produce toxic free radicals. Using a cancer cell line in vitro we find that a free radical scavenger has no protective effect on cells containing GNPs irradiated with 3 MeV protons, while it does protect against cells irradiated with x-rays. We conclude that GNP generated free radicals are a major cause of radiosensitization and that there is likely to be much less dose enhancement effect with clinical proton beams compared to x-rays.

Influence of the nucleus area distribution on the survival fraction after charged particles broad beam irradiation.

It is well known that broad beam irradiation with heavy ions leads to variation in the number of hit(s) received by each cell as the distribution of particles follows the Poisson statistics. Although the nucleus area will determine the number of hit(s) received for a given dose, variation amongst its irradiated cell population is generally not considered. In this work, we investigate the effect of the nucleus area's distribution on the survival fraction. More specifically, this work aims to explain the deviation, or tail, which might be observed in the survival fraction at high irradiation doses. For this purpose, the nucleus area distribution was added to the beam Poisson statistics and the Linear-Quadratic model in order to fit the experimental data. As shown in this study, nucleus size variation, and the associated Poisson statistics, can lead to an upward survival trend after broad beam irradiation. The influence of the distribution parameters (mean area and standard deviation) was studied using a normal distribution, along with the Linear-Quadratic model parameters (α and ß). Finally, the model proposed here was successfully tested to the survival fraction of LN18 cells irradiated with a 85 keV µm(- 1) carbon ion broad beam for which the distribution in the area of the nucleus had been determined.

Elevations in serum muscle enzyme activities in racehorses due to unaccustomed exercise and training.

Hereditary muscular disease is well described in racehorses, yet little is known about traumatic muscle disease associated with unaccustomed exercise or training. The objective of the study was to compare sedentary horses, racehorses undergoing training for the first time (unaccustomed exercise), and experienced racehorses during a training season (accustomed exercise) to investigate the effect of exercise and training on serum muscle enzyme activities and other variables. Horses were sampled prior to exercise for serum activities of aspartate amino transferase (AST), creatine kinase and other variables γ glutamyl transferase (GGT) and serum amyloid A (SAA) in a three-part study. Serum activities of AST and GGT were higher in fit racehorses (n=47) compared with sedentary horses (n=57) at a single time point (P<0.05). The monthly serum activity of AST in two-year-old racehorses (n=10) increased from month 1 to 4 of unaccustomed training (P<0.05). The serum activities of AST and GGT in three-year-old racehorses (n=12) previously accustomed to exercise sampled fortnightly to monthly showed a linear increase (P<0.05) with cumulative training days over the seven months of training, but showed minimal increase during the first four months of accustomed training. SAA was weakly correlated to cumulative training days. In conclusion, AST activity was increased by unaccustomed exercise and cumulative training stress in the racehorse. GGT appeared to be correlated to cumulative training load. Mild to moderate elevations in serum AST in racehorses may be associated with cumulative muscle damage from training or trauma associated with unaccustomed exercise.