Theoretical design of an absorption hologram-based sensor for dose quantification in daylight photodynamic therapy.

Daylight photodynamic therapy (D-PDT) is an effective and almost painless treatment for many skin conditions, where successful treatment relies on daylight activation of a topical photosensitizer. Optimization of D-PDT requires accurate assessment of light dose received. There is a requirement for a small-area sensor that can be placed adjacent to the treatment site to facilitate accurate dose quantification. Here, a novel, to the best of our knowledge, configuration for a D-PDT dose sensor, consisting of a holographic absorption grating fabricated in a photosensitive film, is presented. Theoretical modeling of the sensor's response (i.e., change in grating diffraction efficiency due to change in grating absorption modulation, α1, on exposure to daylight) was conducted using Kogelnik's coupled-wave theory. The influence of the different grating parameters (initial film absorption, thickness, spatial frequency, and reconstruction wavelength) on the sensor response was examined and revealed that the initial absorption and grating thickness values have a large impact on both the magnitude and rate of the D-PDT sensor response. The optimum design for an absorption grating-based D-PDT sensor is described.

Development of a focal lesion phantom with clinically relevant lesion characteristics for image quality evaluation of breast ultrasound scanners.

PURPOSE: Contrast-detail (C-D) and anechoic-target (A-T) detectability are measures of an ultrasound scanner's ability to image lesions of varying contrast and size from background tissue and, as such, they are important tools for grading the imaging capabilities of ultrasound scanners. The objective of this study was to develop a range of contrast- and anechoic-detail phantoms with clinically relevant lesions, of various contrast and sizes, for performance testing of breast ultrasound equipment. METHODS: Tissue mimicking materials that represent the acoustic properties of breast fibroglandular tissue were produced and moulded to construct a range of C-D and A-T phantoms. Two phantom designs were produced, containing cylindrical and spherical targets. Both phantom types were constructed with contrast targets covering the range anechoic, -1, -2, -3 and -4 dB, with lesion diameters of 1-4 mm, positioned at four clinically relevant depths (10, 25, 40 and 55 mm). An image analysis program was developed to objectively analyse the lesion images and to determine the lesion-signal-noise-ratio (LSNR). RESULTS: Both phantoms were used to evaluate the performance of a breast ultrasound scanner. The use of cylindrical phantoms led to an artificially higher image quality performance compared with the more clinically relevant spherical lesion phantom, thus indicating the importance of using the appropriate targets in ultrasound phantoms. CONCLUSION: The spherical lesion phantoms, coupled with the quantitative metric of LSNR, provides a comprehensive approach for performance and quality control testing, as well as the evaluation of advanced ultrasound imaging modes and technologies.

Diagnostic accuracy of SUVmax in predicting malignancy of supraclavicular lymph nodes from primary oesophageal cancer.

PURPOSE: To determine the diagnostic accuracy and optimum cut-off value of SUVmax on PET to predict malignancy of supraclavicular lymph nodes (SCLNs) in patients with oesophageal carcinoma. MATERIAL AND METHODS: All diagnosed cases of oesophageal cancer were retrospectively reviewed (2010-2016). Patients that had a confirmed diagnosis of oesophageal cancer with avid SCLNs on staging PET were included in the study. 33 SCLNs that subsequently underwent ultrasound guided biopsy for staging were analysed. The maximum uptake values (SUVmax) of the SCLNs and primary tumours were measured. A receiver operating characteristic (ROC) analysis was performed to determine the optimum cut off of SUVmax in predicting malignancy. RESULTS: 24/33 PET-detected SCLNs were malignant. ROC analysis identified the best nodal SUVmax cut-off to be 3.0. The diagnostic accuracy of PET was 76.0 % (sensitivity = 78.9 %, specificity = 66.6 %). For SCLNs with SUVmax > 3.0, PET showed a positive predictor value of 88.2 %; for SCLNs < 3.0, PET showed a negative predictor value of 50 %. The median SUVmax of pathologically negative and positive nodes were 2.8 (range 1.8-6.0) and 5.3 (range 1.9-13.4). The median primary tumour SUVmax was 13.8 (range 3.7-30.0). The SUVmax of metastatic lymph nodes were significant higher than those of benign lesions (p < 0.05). CONCLUSION: Our study revealed an accuracy rate of 76 % for PET detected SCLNs in patients with oesophageal carcinoma. For SCLNs with SUVmax > 3.0, PET had a high PPV (88 %), which can minimize the need for further diagnostic tests.

Socio-Economic Status and MultiOriginal morbidity - Fact or Fiction?

BACKGROUND: Areas of low socio-economic status (SES) have a disproportionate number of emergency medical admissions; we quantitate the profile of multi-morbidity related to SES. METHODS: We developed a logistic multiple variable regression model, based on over 15 years of hospital data, to examine the effect of socio-demography on hospital outcomes. RESULTS: Admissions from low SES cohort were a decade younger, and had a shorter hospital stay, and lower 30-day episode mortality outcome. The number of morbidities was equivalent between groups, but the more disadvantaged were more likely to have a respiratory diagnosis or diabetes. CONCLUSION: Low SES emergency admissions present > 10 yr. earlier than the high SES population; their equivalent multimorbidity, despite a lower age, could reflect accelerated disease progression.

The Problems with Risk Prediction during an Emergency Medical Admission Using Laboratory Data - Evidence from Potassium.

BACKGROUND: The prediction of clinical outcomes using biochemical markers is an important tool. METHODS: We calculated a risk score for all emergency admissions 2002-2017. We related potassium and mortality in a multivariable fractional polynomial model. We investigated the potassium distribution and relationship of potassium to mortality over time. RESULTS: There were 106,586 admissions in 54,928 patients. Mortality was higher for those with an admission potassium above the median - 6.1% vs 4.6% (p<0.001), OR 1.07 (95%CI: 1.06, 1.09). There was a progressive increase in mortality from the lowest - 8.9% (95%CI: 8.3%, 9.4%) to highest potassium decile - 14.2% (95%CI: 13.5%, 14.8%). The frequency of admission hypokalaemia and the mortality at any given potassium decreased over time. CONCLUSION: Admission potassium predicts mortality.

Mortality outcomes and emergency department wait times - the paradox in the capacity limited sytem.

BACKGROUND: There is concern that undue ED wait times may result in adverse outcomes. METHODS: We studied 30-day in-hospital mortality (2002-2017) for all medical admissions (106,586 episodes; 54,928 patients) focusing on clinical risk profile. RESULTS: Comparing 2002-09 vs. 2010-17, median ED waits > 6 hours (hr) increased 10h (95% CI: 8,13) to 15h (95% CI: 9,19). 30-day mortality declined 6.2% to 4.9%- (RRR- 20.8%/ NNT- 78). 30-day-mortality by ED wait: - < 4hr 6.6% (95% CI: 6.3%, 6.9%), 4-8hr 4.8% (95% CI: 4.6%, 5.0%), 8-12hr 4.3% (95% CI: 4.1%, 4.5%) or >=12hr 4.2% (95% CI: 3.9%, 4.5%). CONCLUSION: Admissions with shorter waits are overrepresented with high clinical acuity. Higher Risk Score patient with extended wait times had worse clinical outcomes.

Improved mortality outcomes over time for weekend emergency medical admissions.

BACKGROUND: Multiple studies have suggested an association between weekend hospital admissions and mortality. These have been limited by potential residual confounders and a lack of explanation of causation. AIM: We previously attributed adverse weekend outcomes to higher acuity; we have re-examined this question for all emergency medical admissions to our institution from 2002 to 2014. METHODS: We divided admissions by a weekday or weekend (Friday to Sunday) hospital arrival. We utilised a multivariate logistic regression model, to determine whether the latter was independently predictive of 30-day in-hospital mortality. RESULTS: There were 82,368 admissions in 44,628 patients over the 13-year period. Of admissions, 37.4% occurred at the weekend. The Acute Illness Severity Score, the Charlson Co-morbidity Index and the Chronic Disabling Disease Score were similar by a weekday or weekend admission. The multivariable logistic regression showed no increase in 30-day in-hospital mortality for weekend admissions, odds ratio 1.07 (95% confidence interval 0.98 to 1.16) (p = 0.11). Since the inception of the AMAU, the per patient mortality for a weekend admission has declined from 13.5% in 2002 to 4.4% in 2014. This represents a relative risk reduction of 67.9% with a number needed to treat of 10.8. Outcomes improved similarly for weekday and weekend admissions. CONCLUSION: No increase in 30-day in-hospital mortality for weekend admissions was found in this study. There has been a substantial reduction in mortality for both weekday and weekend admissions over time.

Survival analysis of weekend emergency medical admissions.

BACKGROUND: We previously reported weekend emergency admissions to have a higher mortality; we have now examined the time profile of deaths, by weekday or weekend admission, in all emergency medical patients admitted between 2002 and 2014. METHODS: We divided admissions by a weekday or weekend (After 17.00 Friday-Sunday) hospital arrival. We examined survival following an admission using Cox proportional hazard models and Kaplan-Meier time to event analysis. RESULTS: In total 82 368 admissions were recorded in 44, 628 patients. Weekend admissions had an increased mortality of 5.0% (95% CI 4.7, 5.4) compared with weekday admissions of 4.5% (95% CI 4.3, 4.7) ( P = 0.007). The univariate adjusted Odds Ratio (OR) of death for a weekend admission was significantly increased OR = 1.15 (95% CI 1.05, 1.24) ( P = 0.001). Mortality following an admission declined exponentially over time with a long tail, ∼25% of deaths occurred after day 28. Only 11.4% of deaths occurred on the weekend of the admission. Survival curves showed no mortality difference at 28 days ( P = 0.21) but a difference at 90 days ( P = 0.05). The higher mortality for a weekend admission was attributable to late deaths in the cohort with an extended stay; compared with weekday, these weekend admissions were more likely to be older and have greater co-morbidity. CONCLUSION: Survival rates following a weekend or weekday admission were similar out to 28 days. The higher overall mortality for weekend admissions is due to divergence in survival between 28 and 90 days. Most deaths in weekend admissions occurred when the hospital was fully staffed.

Interaction of Broadband Access and Education Levels in Determining the Rate of Emergency Medical Admissions.

Background We examined the effect of broadband access, educational status and their interaction on local population health. Methods We calculated the annual admission incidence rates for each small area population unit within our hospital catchment, relating quintiles of broadband access to two groups a) full time education to primary level (less than or equal to 15 years) and b) full time education to tertiary level (>18 years). Univariate and multivariable risk estimates were calculated, using truncated Poisson regression. Results 82,368 admissions in 44,628 patients were included. Broadband access was a linear predictor of the admission incidence rate with decreases from Q1 (least access) 50.8 (95%CI 30.2 to 71.4) to Q5 (highest access) 17.9 (95%CI 13.4 to 22.4). Areas with greater numbers educated only to primary level were more influenced by broadband access. Conclusion Broadband access is a predictor of the emergency medical admission rate; this effect is modulated by the baseline education level.

Age and the economics of an emergency medical admission-what factors determine costs?

BACKGROUND: The ageing of the population may be anticipated to increase demand on hospital resources. We have investigated the relationship between hospital episode costs and age profile in a single centre. METHODS: All Emergency Medical admissions (33 732 episodes) to an Irish hospital over a 6-year period, categorized into three age groups, were evaluated against total hospital episode costs. Univariate and adjusted incidence rate ratios (IRRs) were calculated using zero truncated Poisson regression. RESULTS: The total hospital episode cost increased with age ( P < 0.001). The multi-variable Poisson regression model demonstrated that the most important drivers of overall costs were Acute Illness Severity-IRR 1.36 (95% CI: 1.30, 1.41), Sepsis Status -1.46 (95% CI: 1.42, 1.51) and Chronic Disabling Disease Score -1.25 (95% CI: 1.22, 1.27) and the Age Group as exemplified for those 85 years IRR 1.23 (95% CI: 1.15, 1.32). CONCLUSION: Total hospital episode costs are a product of clinical complexity with contributions from the Acute Illness Severity, Co-Morbidity, Chronic Disabling Disease Score and Sepsis Status. However age is also an important contributor and an increasing patient age profile will have a predictable impact on total hospital episode costs.

Radiology imaging delays as independent predictors of length of hospital stay for emergency medical admissions.

AIM: To investigate the extent to which the time to completion for computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound could be shown to influence the length of stay and costs incurred while in hospital, while accounting for patient acuity. MATERIALS AND METHODS: All emergency admissions, totalling 25,326 imaging investigations between 2010-2014 were evaluated. The 50(th), 75(th), and 90(th) centiles of completion times for each imaging type was entered into a multivariable truncated Poisson regression model predicting the length of hospital stay. Estimates of risk (odds or incidence rate ratios [IRRs]) of the regressors were adjusted for acute illness severity, Charlson comorbidity index, chronic disabling disease score, and sepsis status. Quantile regression analysis was used to examine the impact of imaging on total hospital costs. RESULTS: For all imaging examinations, longer hospital lengths of stay were shown to be related to delays in imaging time. Increased delays in CT and MRI were shown to be associated with increased hospital episode costs, while ultrasound did not independently predict increased hospital costs. The magnitude of the effect of imaging delays on episode costs were equivalent to some measures of illness severity. CONCLUSION: CT, MRI, and ultrasound are undertaken in patients with differing clinical complexity; however, even with adjustment for complexity, the time delay in a more expeditious radiological service could potentially shorten the hospital episode and reduce costs.

Influence of social deprivation, overcrowding and family structure on emergency medical admission rates.

BACKGROUND: Patients from deprived backgrounds have a higher in-patient mortality following emergency medical admission. AIM: To evaluate the influence of Deprivation Index, overcrowding and family structure on hospital admission rates. DESIGN: Retrospective cohort study. METHODS: All emergency medical admissions from 2002 to 2013 were evaluated. Based on address, each patient was allocated to an electoral division, whose small area population statistics were available from census data. Patients were categorized by quintile of Deprivation Index, overcrowding and family structure, and these were evaluated against hospital admission rate, calculated as rate/1000 population. Univariate and multivariable risk estimates (Odds Ratios or Incidence Rate Ratios) were calculated, using logistic or zero truncated Poisson regression as appropriate. RESULTS: There were 66 861 admissions in 36 214 patients over the 12-year study period. Deprivation Index quintile independently predicted the admission rate, with rates of Q1 12.0 (95% CI 11.8-12.2), Q2 19.5 (95% CI 19.3-19.6), Q3 33.7 (95% CI 33.3-34.0), Q4 31.4 (95% CI 31.2-31.6) and Q5 38.1 (95% CI 37.7-38.5). Similarly the proportions of families with children <15 years old, was an independent predictor of the admission rate with rates of Q1 20.8 (95% CI 20.4-21.1), Q2 23.0 (95% CI 22.7-23.3), Q3 32.2 (95% CI 31.9-32.5), Q4 32.4 (95% CI 32.2-32.7) and Q5 37.2 (95% CI 36.6-37.8). The proportion of families with children ≥15-years old was also predictive but quintile of overcrowding was only predictive in the univarate model. CONCLUSION: Deprivation Index and family structure strongly predict emergency medical hospital admission rates.

Social deprivation and the rate of emergency medical admission for older persons.

BACKGROUND: Deprivation Status increases the annual admission incidence of emergency medical admissions; the extent to which deprivation influences the admission of older persons is less well known. AIM: To examine whether deprivation within a hospital catchment area influences emergency medical admissions for the elderly population. DESIGN: The relationship between Deprivation Status, Dependency Ratio (population proportion of non-working age (<15 or ≥65 years) and age for all emergency admissions (82 368 episodes of 44 628 patients), over a 13-year period, were examined and ranked by quintile. METHODS: Univariate and multi-variable risk estimates (incidence rate ratios) were calculated, using truncated Poisson regression. RESULTS: The Dependency Ratio and the Deprivation index independently predicted the annual incidence rate of medical emergencies; however, when calculated for older persons, the corresponding incidence rate ratios showed a falling trend with increasing Deprivation Status-Q2 0.51 (95% confidence interval [CI]: 0.50, 0.52), Q3 0.59 (95% CI: 0.58, 0.60), Q4 0.51 (95% CI: 0.50, 0.52) and Q5 0.37 (95% CI: 0.36, 0.38). Thus, with increasing Deprivation Status, the proportion of total admission from the ≥65-year cohort fell substantially. CONCLUSION: The admission incidence rate for emergency medical patients is strongly influenced by the catchment area Deprivation Status. However, because of its greater impact on the younger population, increasing deprivation alters the ratio of younger to older persons as a proportion of total emergency admissions.

Chronic disabling disease--impact on outcomes and costs in emergency medical admissions.

BACKGROUND: Chronic disabling disease is present in nearly 90% of emergency medical admissions. We have examined its impact on outcomes and costs in one institution, using a database of episodes collected prospectively over 12 years. METHODS: All emergency admissions (66,933 episodes; 36,271 patients) to St James' Hospital over a 12-year period (2002-13) were evaluated in relation to 30-day in-hospital mortality, length of stay (LOS) and hospital costs. Predictor variables (identified univariately) were entered into a multi-variable logistic regression model to predict 30-day in-hospital mortality. The data were also modelled as count data (absolute LOS, total cost) using zero-truncated Poisson regression. RESULTS: Acute illness severity was the best independent predictor of mortality; chronic disabling disease was an independent predictor (P < 0.001) for patients with 4+ disabling conditions. Age, adjusted for other predictors, was only independently predictive of mortality for patient 85+ years. Chronic disabling disease was an independent predictor of LOS increasing linearly with incidence rate ratios of 1.35 (95% CI: 1.29, 1.42), 1.59 (95% CI: 1.51, 1.66), 1.73 (95% CI: 1.65, 1.83) and 1.74 (95% CI: 1.65, 1.84) for those with 1, 2, 3 or 4+ disabling conditions, respectively. Age, as a predictor of LOS was strongly correlated with the presence of disabling disease. Chronic disabling disease independently predicted costs non-linearly; those with 2 or more disabling conditions had particularly high total hospital costs. CONCLUSION: Chronic disabling disease is an independent predictor of hospital LOS and costs in unselected emergency admissions; adjusted for illness severity, it is only a mortality predictor for those with multiple disabling conditions.

Does admission via an acute medical unit influence hospital mortality? 12 years' experience in a large Dublin hospital.

BACKGROUND: Following an emergency medical admission, patients may be admitted an acute medical assessment unit (AMAU) or directly into a ward. An AMAU provides a structured environment for their initial assessment and treatment. METHODS: All emergency admissions (66,933 episodes in 36,271 patients) to an Irish hospital over an 12-year period (2002-2013) were studied with 30-day in-hospital mortality as the outcome measure. Univariate Odds Ratios, by initial patient allocation, and the fully adjusted Odds Ratios were calculated, using a validated logistic regression model. RESULTS: Patients, by design, were intended to be admitted initially to the AMAU (<= 5 day stay). Capacity constraints dictated that only 39.8% of patients were so admitted; the remainder bypassed the AMAU to a ward (60.2%). All patients remained under the care of the admitting consultant/team. We computed the risk profile for each group, using a multiple variable validated model of 30-day in-hospital mortality; the model indicated the same risk profile between these groups. The univariate OR of an in-hospital death by day 30 for a patient initially allocated to the AMAU, compared with an initial ward allocation was 0.76 (95% CI: 0.71, 0.82- p<0.001). The fully adjusted risk for patients was 0.67 (95% CI: 0.62, 0.73- p<0.001). CONCLUSION: Patients, with equivalent mortality risk, allocated initially to AMAU or a more traditional ward, appeared to have substantially different outcomes.

The novel application of Benford's second order analysis for monitoring radiation output in interventional radiology.

Benford's law is an empirical observation which predicts the expected frequency of digits in naturally occurring datasets spanning multiple orders of magnitude, with the law having been most successfully applied as an audit tool in accountancy. This study investigated the sensitivity of the technique in identifying system output changes using simulated changes in interventional radiology Dose-Area-Product (DAP) data, with any deviations from Benford's distribution identified using z-statistics. The radiation output for interventional radiology X-ray equipment is monitored annually during quality control testing; however, for a considerable portion of the year an increased output of the system, potentially caused by engineering adjustments or spontaneous system faults may go unnoticed, leading to a potential increase in the radiation dose to patients. In normal operation recorded examination radiation outputs vary over multiple orders of magnitude rendering the application of normal statistics ineffective for detecting systematic changes in the output. In this work, the annual DAP datasets complied with Benford's first order law for first, second and combinations of the first and second digits. Further, a continuous 'rolling' second order technique was devised for trending simulated changes over shorter timescales. This distribution analysis, the first employment of the method for radiation output trending, detected significant changes simulated on the original data, proving the technique useful in this case. The potential is demonstrated for implementation of this novel analysis for monitoring and identifying change in suitable datasets for the purpose of system process control.

An audit of a hospital-based Doppler ultrasound quality control protocol using a commercial string Doppler phantom.

Results from a four-year audit of a Doppler quality assurance (QA) program using a commercially available Doppler string phantom are presented. The suitability of the phantom was firstly determined and modifications were made to improve the reliability and quality of the measurements. QA of Doppler ultrasound equipment is very important as data obtained from these systems is used in patient management. It was found that if the braided-silk filament of the Doppler phantom was exchanged with an O-ring rubber filament and the velocity range below 50 cm/s was avoided for Doppler quality control (QC) measurements, then the maximum velocity accuracy (MVA) error and intrinsic spectral broadening (ISB) results obtained using this device had a repeatability of 18 ± 3.3% and 19 ± 3.5%, respectively. A consistent overestimation of the MVA of between 12% and 56% was found for each of the tested ultrasound systems. Of more concern was the variation of the overestimation within each respective transducer category: MVA errors of the linear, curvilinear and phased array probes were in the range 12.3-20.8%, 32.3-53.8% and 27-40.7%, respectively. There is a dearth of QA data for Doppler ultrasound; it would be beneficial if a multicentre longitudinal study was carried out using the same Doppler ultrasound test object to evaluate sensitivity to deterioration in performance measurements.

The effects of fatty deposits on the accuracy of the Fibroscan® liver transient elastography ultrasound system.

A new generation of ultrasound transient elastography (TE) systems have emerged which exploit the well-known correlation between the liver's pathological and mechanical properties through measurements of the Young's elastic modulus; however, little work has been carried out to examine the effect that fatty deposits may have on the TE measurement accuracy. An investigation was carried out on the effects on the measurement accuracy of a TE ultrasound system, the Fibroscan®, caused by overlaying fat layers of varying thickness on healthy liver-mimicking phantoms, simulating in vivo conditions for obese patients. Furthermore, a steatosis effect similar to that in non-alcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD) was simulated to investigate its effect on the TE system. A range of novel elastography fat-mimicking materials were developed using 6-10 wt% poly(vinyl alcohol) cryogel capable of achieving a range of acoustic velocities (1482-1530 m s(-1)) and attenuation coefficients (0.4-1 dB MHz(-1) cm(-1)) for simulating different liver states. Laboratory-based acoustic velocities and attenuation coefficients were measured while the Young's modulus was established through a gold standard compression testing method. A significant variation of the Young's elastic modulus was measured in healthy phantoms with overlaying fat layers of thicknesses exceeding 45 mm, impinging on the scanners region of interest, overestimating the compression tested values by up to 11 kPa in some cases. Furthermore, Fibroscan® measurements of the steatosis phantoms showed a consistent overestimation (∼54%), which strongly suggests that the speed of sound mismatch between that of liver tissue and that assumed by the scanner is responsible for the high clinical cut-offs established in the case of ALD and NAFLD.

Modelling temporal trends of 137Cs and 99Tc concentrations in Fucus vesiculosus from the eastern Irish coastline.

Time series of 137Cs and 99Tc activity concentrations in the brown seaweed Fucus vesiculosus and seawater, gathered at three locations on the eastern Irish coastline during the period 1988-2008, have been modelled using a novel approach incorporating a variable uptake rate in the seaweed. Seasonal variations in the time series, identified using spectral analysis, were incorporated into the model which was used to determine transfer kinetic parameters and to predict 137Cs and 99Tc concentrations in seaweed, as influenced by levels in ambient seawater. An optimisation method combining evolutionary and grid search minimisation techniques was adopted to determine the best values for the model parameters, from which concentration factors (CF) and biological half-lives (tb1/2) for 137Cs and 99Tc in F. vesiculosus were calculated. CF values of 170-179 and 1.1×105 l kg(-1) (dry weight) were obtained for 137Cs and 99Tc, respectively, while the corresponding tb1/2 values were 39-47 and 32 days, respectively.

Modelling the biological half-life and seasonality of ¹4C in Fucus vesiculosus from the east coast of Ireland: implications for the estimation of future trends.

Radiocarbon levels were recorded in Fucus vesiculosus samples collected on a monthly basis over a three-year period at a site on the east coast of Ireland. The resulting data was analysed using a numerical model which estimates the transit times from the Sellafield plant to the sampling location, and the mean availability time of ¹4C in seaweed. With the inclusion of a model parameter allowing for seasonal variability in uptake by the Fucus, good correlation was observed between the predicted and measured concentrations. Future temporal trends of ¹4C Fucus concentrations along the eastern Irish coastline were modelled with the application of three possible prospective discharge scenarios, predicting ¹4C Fucus concentrations to reduce to ambient background levels within 2.5-years of discharges being set to zero. Such projections may prove helpful in assessing the consequences of discharge management and policy making in the context of the OSPAR convention.