One size does not fit all: Factors associated with increased frequency of radiation overexposure alerts based on fixed-alert thresholds

ObjectivesQuantify the expected rate of CT radiation dose alerts for three body regions using accepted radiation dose benchmarks and assess key determinants of alert frequency.MethodsThis IRB-approved retrospective cohort study evaluated consecutive CT examinations performed between July and December 2013 within an academic medical system. CTDI_vol x-ray tube output metrics were compared to the body-region-specific benchmark levels, Achievable Doses (AD), Diagnostic Reference Levels (DRL), and Dose Notification Values (DNV). A logistic regression model for the simulated alerts was fit as a function of the independent predictors: scanner, body region, gender, weight, and age.ResultsFor 17,000 exams, the proportion of events triggering alerts increased with patient weight. Significant covariates were scanner, body region, patient weight and patient age (all p < 0.0001). Odds of alert generation for the AD, DRL, and DNV benchmarks increased by 7.6%, 6.6% and 2.9% per kilogram, respectively, and by 0.8%, 1.1% and −2.7% per year of age (all p < 0.0001). Compared to the most highly optimized scanner, odds of alert generation varied by a factor of 595 for AD, 1126 for DRL, and 13 for DNV.ConclusionAlert frequency was significantly correlated with weight, age, body region and scanner. Controllable factors include scanner functionality and associated protocol optimization. Patient factors driving alert frequency are predominantly weight, and to a lesser degree, age. Size-agnostic fixed dose thresholds can frequently produce false positive alerts in appropriately performed exams of large patients, while missing opportunities to identify outlier scans of higher-than-expected dose in small patients.     

低剂量胸部CT自动管电流调节技术在超重体型患者检查中的可行性研究

目的：探讨16层螺旋CT自动管电流调节技术（CAREDose4D）在超重体型患者检查中的可行性。方法：收集行胸部CT检查的超重体型患者（BMI值于24-27．9之间）100例,扫描分低剂量组（A组）和常规剂量组（B组）,其中A组扫描运用CAREDose4D技术自动调节管电流;B组扫描运用常规剂量管电流为70mAs扫描。扫描完成后记录加权CT剂量指数（CTDlvol）、有效mAs值、剂量长度乘积（DLP）,计算出有效剂量（ED）及剂量减低比值（DR）,并比较两组的剂量及图像质量。结果：与B组相比,A组常规扫描辐射剂量显著降低,差异有显著统计学意义（P〈0．01）,A组剂量减低比值（DR）降低约20．84％,而图像质量无明显下降,不影响诊断,在主动脉弓上4cm（肺尖）层面A组图像质量优于B组,差异有统计学意义（x^2=8．442,P=0．015）。结论：自动管电流调节技术既可以减少患者的辐射剂量,对待超重体型患者个体化、人性化,又不影响影像诊断,是一项有价值的检查方法。     

Detecting and cleaning outliers for robust estimation of variogram models in insect count data

Outlier detection and cleaning procedures were evaluated to estimate mathematical restricted variogram models with discrete insect population count data. Because variogram modeling is significantly affected by outliers, methods to detect and clean outliers from data sets are critical for proper variogram modeling. In this study, we examined spatial data in the form of discrete measurements of insect counts on a rectangular grid. Two well-known insect pest population data were analyzed; one data set was the western flower thrips, Frankliniella occidentalis (Pergande) on greenhouse cucumbers and the other was the greenhouse whitefly, Trialeurodes vaporariorum (Westwood) on greenhouse cherry tomatoes. A spatial additive outlier model was constructed to detect outliers in both the isolated and patchy spatial distributions of outliers, and the outliers were cleaned with the neighboring median cleaner. To analyze the effect of outliers, we compared the relative nugget effects of data cleaned of outliers and data still containing outliers after transformation. In addition, the correlation coefficients between the actual and predicted values were compared using the leave-one-out cross-validation method with data cleaned of outliers and non-cleaned data after unbiased back transformation. The outlier detection and cleaning procedure improved geostatistical analysis, particularly by reducing the nugget effect, which greatly impacts the prediction variance of kriging. Consequently, the outlier detection and cleaning procedures used here improved the results of geostatistical analysis with highly skewed and extremely fluctuating data, such as insect counts.     

Combined PET/CT for IMRT treatment planning of NSCLC: Contrast-enhanced CT images for Monte Carlo dose calculation

PurposeCombined PET/CT imaging has been proposed as an integral part of radiotherapy treatment planning (TP). Contrast-enhanced CT (ceCT) images are frequently acquired as part of the PET/CT examination to support target delineation. The aim of this dosimetric planning study was to investigate the error introduced by using a ceCT for intensity modulated radiotherapy (IMRT) TP with Monte Carlo dose calculation for non-small cell lung cancer (NSCLC).Material and methodsNine patients with NSCLC prior to chemo-RT were included in this retrospective study. For each patient non-enhanced, low-dose CT (neCT), ceCT and [¹⁸F]-FDG-PET emission data were acquired within a single examination. Manual contouring and TP were performed on the ceCT. An additional set of independent target volumes was auto-segmented in PET images. Dose distributions were recalculated on the neCT. Differences in dosimetric parameters were evaluated.ResultsDose differences in PTV and lungs were small for all patients. The maximum difference in all PTVs when using ceCT images for dose calculation was ?2.1%, whereas the mean difference was less than ?1.7%. Maximum differences in the lungs ranged from ?1.8% to 2.1% (mean: ?0.1%). In four patients an underestimation of the maximum spinal cord dose between 2% and 3.2% was observed, but treatment plans remained clinically acceptable.ConclusionsMonte Carlo based IMRT planning for NSCLC patients using ceCT allows for correct dose calculation. A direct comparison to neCT-based treatment plans revealed only small dose differences. Therefore, ceCT-based TP is clinically safe as long as the maximum acceptable dose to organs at risk is not approached.     

Practical radiation dosimetry across a variety of CBCT devices in Radiology

Cone beam technology is becoming more prominent in Radiology. In our hospital we have an extremity CT, an O-arm and a number of C-arms offering 3D capabilities. Each of these modalities use cone beam CT (CBCT) technology to image the area of interest in one single rotation. Traditional CTDI metrics for radiation dosimetry in CT depend on narrow beam geometry. The relevance of the CTDI as a dose indicator for cone beam scanning is contentious due to underestimation of dose lying outside the standard 100 mm chamber length and CTDI phantoms being of insufficient length.In an attempt to better quantify dose from cone beam scanning, alternative methodologies have been developed which attempt to counter the limitations of CTDI methodologies. In this comparison study we utilised the CBCT methodologies outlined in (i) IAEA Report 5, (ii) EFOMP’s protocol on QC in CBCT and (iii) conventional CTDI measurement and tested them on various CBCT systems used in Radiology. These methods were chosen as they use equipment that is typically available to a diagnostic imaging physicist.We determine that the EFOMP protocol and the conventional CTDI method produce the best estimate of the radiation output for quality control purposes. Our conclusion is that the EFOMP protocol is the fastest and easiest method to measure a CBCT metric but it is not always accessible. For the systems in our hospital we will adopt the EFOMP protocol for open systems (C-arms) and perform CTDI_Vol measurements using conventional techniques on enclosed systems (O-arm and extremity CT).     

Detection of outlier residues for improving interface prediction in protein heterocomplexes

Sequence-based understanding and identification of protein binding interfaces is a challenging research topic due to the complexity in protein systems and the imbalanced distribution between interface and noninterface residues. This paper presents an outlier detection idea to address the redundancy problem in protein interaction data. The cleaned training data are then used for improving the prediction performance. We use three novel measures to describe the extent a residue is considered as an outlier in comparison to the other residues: the distance of a residue instance from the center instance of all residue instances of the same class label (Dist), the probability of the class label of the residue instance (PCL), and the importance of within-class and between-class (IWB) residue instances. Outlier scores are computed by integrating the three factors; instances with a sufficiently large score are treated as outliers and removed. The data sets without outliers are taken as input for a support vector machine (SVM) ensemble. The proposed SVM ensemble trained on input data without outliers performs better than that with outliers. Our method is also more accurate than many literature methods on benchmark data sets. From our empirical studies, we found that some outlier interface residues are truly near to noninterface regions, and some outlier noninterface residues are close to interface regions.     

Detecting outliers in a univariate time series dataset using unsupervised combined statistical methods: A case study on surface water temperature

The surface water temperature is a vital ecological and climate variable, and its monitoring is critical. An extensive sensor network measures the ocean, but outliers pervade the monitoring data due to the sudden change in the water surface level. No single algorithm can identify the outlier efficiently. Hence, this work aims to propose and evaluate the performance of three statistical-based outlier detection algorithms for the water surface temperature: 1) the Standard Z-Score method, 2) the Modified Z-Score coupled with decomposition, and 3) the Exponential Moving Average with the Coupled Modified Z-Score and decomposition. A threshold was set to flag the outlier values. The models' performance was evaluated using the F-score method. Results showed that an increase in outlier detection might reduce the precision of identifying the actual outlier. Based on the results, the Exponential Moving Average with the Modified Z-Score gave the highest F-score value (= 0.83) compared to the other two individual methods. Therefore, this proposed algorithm is recommended to detect outliers efficiently in large surface water temperature datasets.     

Image quality for radiotherapy CT simulators with different scanner bore size

PurposeWe compare image quality parameters derived from phantom images taken on three commercially available radiotherapy CT simulators. To make an unbiased evaluation, we assured images were obtained with the same surface dose measured using XR-QA2 model GafChromic™ film placed at the imaging phantom surface for all three CT-simulators.MethodsRadiotherapy CT simulators GE LS 16, Philips Brilliance Big Bore, and Toshiba Aquilion LB were compared in terms of spatial resolution, low contrast detectability, image uniformity, and contrast to noise ratio using CATPHAN-504 phantom, scanned with Head and Pelvis protocols. Dose was measured at phantom surface, with CT scans repeated until doses on all scanners were within 2%.ResultsIn terms of spatial resolution, the GE simulator appears slightly better, while Philips CT images are superior in terms of SNR for both scanning protocols. The CNR results show that Philips CT images appear to be better, except for high Z material, while Toshiba appears to fit in between the two simulators.ConclusionsWhile the image quality parameters for three RT CT simulators show comparable results, the scanner bore size is of vital importance in various radiotherapy applications. Since the image quality is a function of a large number of confounding parameters, any loss in image quality due to scanner bore size could be compensated by the appropriate choice of scanning parameters, including the exposure and by balancing between the additional imaging dose to the patient and high image quality required in highly conformal RT techniques.     

Monte Carlo simulation of the dose distribution of ICRP adult reference computational phantoms for acquisitions with a 320 detector-row cone-beam CT scanner

PurposeThe purpose of this study was to develop and validate a Monte Carlo (MC) simulation tool for patient dose assessment for a 320 detector-row CT scanner, based on the recommendations of International Commission on Radiological Protection (ICRP). Additionally, the simulation was applied on four clinical acquisition protocols, with and without automatic tube current modulation (TCM).MethodsThe MC simulation was based on EGS4 code and was developed specifically for a 320 detector-row cone-beam CT scanner. The ICRP adult reference phantoms were used as patient models. Dose measurements were performed free-in-air and also in four CTDI phantoms: 150 mm and 350 mm long CT head and CT body phantoms. The MC program was validated by comparing simulations results with these actual measurements acquired under the same conditions. The measurements agreed with the simulations across all conditions within 5%. Patient dose assessment was performed for four clinical axial acquisitions using the ICRP adult reference phantoms, one of them using TCM.ResultsThe results were nearly always lower than those obtained from other dose calculator tools or published in other studies, which were obtained using mathematical phantoms in different CT systems. For the protocol with TCM organ doses were reduced by between 28 and 36%, compared to the results obtained using a fixed mA value.ConclusionsThe developed simulation program provides a useful tool for assessing doses in a 320 detector-row cone-beam CT scanner using ICRP adult reference computational phantoms and is ready to be applied to more complex protocols.     

Can AFLP genome scans detect small islands of differentiation? The case of shell sculpture variation in the periwinkle Echinolittorina hawaiiensis

Genome scans have identified candidate regions of the genome undergoing selection in a wide variety of organisms, yet have rarely been applied to broadly dispersing marine organisms experiencing divergent selection pressures, where high recombination rates can reduce the extent of linkage disequilibrium (LD) and the ability to detect genomic regions under selection. The broadly dispersing periwinkle Echinolittorina hawaiiensis exhibits a heritable shell sculpture polymorphism that is correlated with environmental variation. To elucidate the genetic basis of phenotypic variation, a genome scan using over 1000 AFLP loci was conducted on smooth and sculptured snails from divergent habitats at four replicate sites. Approximately 5% of loci were identified as outliers with Dfdist, whereas no outliers were identified by BayeScan. Closer examination of the Dfdist outliers supported the conclusion that these loci were false positives. These results highlight the importance of controlling for Type I error using multiple outlier detection approaches, multitest corrections and replicate population comparisons. Assuming shell phenotypes have a genetic basis, our failure to detect outliers suggests that the life history of the target species needs to be considered when designing a genome scan.     

Noise properties of reconstructed images in a kilo-voltage on-board imaging system with iterative reconstruction techniques: A phantom study

X-ray computed tomography (CT) images obtained with a kilo-voltage (kV) on-board imaging (OBI) system improve the accuracy of patient setup and treatment planning. The use of iterative reconstruction techniques (IRTs) for CT imaging can also reduce radiation dose compared to analytic reconstruction techniques. Despite these improvements, the image quality varies with IRTs, and the noise structure of reconstructed images can be distorted by IRTs. In this study, the noise properties and spatial resolution of the images reconstructed by IRTs were evaluated in terms of conventional noise metrics, high-order statistics, noise spectral density (NSD) and modulation transfer function (MTF) at different radiation doses. A kV OBI system mounted on a Varian Trilogy machine and a CATPHAN600 phantom were used to obtain projections, and the projections were reconstructed by Feldkamp (FDK), algebraic reconstruction technique (ART), maximum-likelihood expectation–maximization (MLEM) and total variation (TV) minimization algorithms. The reconstructed images were compared according to mean, standard deviation, skewness, kurtosis, NSD and MTF at different radiation doses. The results demonstrated that the noise properties and spatial resolution of reconstructed images depend on the type of IRT and the radiation dose. The noise structures are altered by IRTs and can be characterized by high-order statistics and NSD, as well as conventional noise metrics. In conclusion, high-order statistics and NSD should be considered in order to provide detailed information for the images reconstructed by IRTs. Also, trade-off among noise properties, spatial resolution and contrast is important to optimize image quality obtained using IRTs.     

Dosimetric impact of 4DCT artifact in carbon-ion scanning beam treatment: Worst case analysis in lung and liver treatments

IntroductionWe evaluated the impact of 4DCT artifacts on carbon-ion pencil beam scanning dose distributions in lung and liver treatment.Methods & materials4DCT was performed in 20 liver and lung patients using area-detector CT (original 4DCT). 4DCT acquisition by multi-detector row CT was simulated using original 4DCT by selecting other phases randomly (plus/minus 20% phases). Since tumor position can move over the respiratory range in original 4DCT, mid-exhalation was set as reference phase. Total prescribed dose of 60 Gy (RBE) was delivered to the clinical target volume (CTV). Reference dose distribution was calculated with the original CT, and actual dose distributions were calculated with treatment planning parameters optimized using the simulated CT (simulated dose). Dose distribution was calculated by substituting these parameters into the original CT.ResultsFor liver cases, CTV-D95 and CTV-Dmin values for the reference dose were 97.6 ± 0.5% and 89.8 ± 0.6% of prescribed dose, respectively. Values for the simulated dose were significantly degraded, to 88.6 ± 14.0% and 46.3 ± 26.7%, respectively. Dose assessment results for lung cases were 84.8 ± 12.8% and 58.0 ± 24.5% for the simulated dose, showing significant degradation over the reference dose of 95.1 ± 1.5% and 87.0 ± 2.2%, respectively.Conclusions4DCT image quality should be closely checked to minimize degradation of dose conformation due to 4DCT artifacts. Medical staff should pay particular attention to checking the quality of 4DCT images as a function of respiratory phase, because it is difficult to recognize 4DCT artifact on a single phase in some cases     

Assessment of the variation in CT scanner performance (image quality and Hounsfield units) with scan parameters,for image optimisation in radiotherapy treatment planning

PurposeTo define a method and investigate how the adjustment of scan parameters affected the image quality and Hounsfield units (HUs) on a CT scanner used for radiotherapy treatment planning. A lack of similar investigations in the literature may be a contributing factor in the apparent reluctance to optimise radiotherapy CT protocols.MethodA Catphan phantom was used to assess how image quality on a Toshiba Aquilion LB scanner changed with scan parameters. Acquisition and reconstruction field-of-view (FOV), collimation, image slice thickness, effective mAs per rotation and reconstruction algorithm were varied. Changes were assessed for HUs of different materials, high contrast spatial resolution (HCSR), contrast-noise ratio (CNR), HU uniformity, scan direction low contrast and CT dose-index.ResultsCNR and HCSR varied most with reconstruction algorithm, reconstruction FOV and effective mAs. Collimation, but not image slice width, had a significant effect on CT dose-index with narrower collimation giving higher doses. Dose increased with effective mAs. Highest HU differences were seen when changing reconstruction algorithm: 56 HU for densities close to water and 117 HU for bone-like materials. Acquisition FOV affected the HUs but reconstruction FOV and effective mAs did not.ConclusionsAll the scan parameters investigated affected the image quality metrics. Reconstruction algorithm, reconstruction FOV, collimation and effective mAs were most important. Reconstruction algorithm and acquisition FOV had significant effect on HU. The methodology is applicable to radiotherapy CT scanners when investigating image quality optimisation, prior to assessing the impact of scan protocol changes on clinical CT images and treatment plans.     

Was Rodney Ledward a statistical outlier? Retrospective analysis using routine hospital data to identify gynaecologists' performance

Objectives To investigate whether routinely collected data from hospital episode statistics could be used to identify the gynaecologist Rodney Ledward, who was suspended in 1966 and was the subject of the Ritchie inquiry into quality and practice within the NHS.Design A mixed scanning approach was used to identify seven variables from hospital episode statistics that were likely to be associated with potentially poor performance. A blinded multivariate analysis was undertaken to determine the distance (known as the Mahalanobis distance) in the seven indicator multidimensional space that each consultant was from the average consultant in each year. The change in Mahalanobis distance over time was also investigated by using a mixed effects model.Setting NHS hospital trusts in two English regions, in the five years from 1991-2 to 1995-6.Population Gynaecology consultants (n = 143) and their hospital episode statistics data.Main outcome measure Whether Ledward was a statistical outlier at the 95% level.Results The proportion of consultants who were outliers in any one year (at the 95% significance level) ranged from 9% to 20%. Ledward appeared as an outlier in three of the five years. Our mixed effects (multi-year) model identified nine high outlier consultants, including Ledward.Conclusion It was possible to identify Ledward as an outlier by using hospital episode statistics data. Although our method found other outlier consultants, we strongly caution that these outliers should not be overinterpreted as indicative of “poor” performance. Instead, a scientific search for a credible explanation should be undertaken, but this was outside the remit of our study. The set of indicators used means that cancer specialists, for example, are likely to have high values for several indicators, and the approach needs to be refined to deal with case mix variation. Even after allowing for that, the interpretation of outlier status is still as yet unclear. Further prospective evaluation of our method is warranted, but our overall approach may be potentially useful in other settings, especially where performance entails several indicator variables.     

An Integrated Approach for Identifying Wrongly Labelled Samples When Performing Classification in Microarray Data

Background

Using hybrid approach for gene selection and classification is common as results obtained are generally better than performing the two tasks independently. Yet, for some microarray datasets, both classification accuracy and stability of gene sets obtained still have rooms for improvement. This may be due to the presence of samples with wrong class labels (i.e. outliers). Outlier detection algorithms proposed so far are either not suitable for microarray data, or only solve the outlier detection problem on their own.

Results

We tackle the outlier detection problem based on a previously proposed Multiple-Filter-Multiple-Wrapper (MFMW) model, which was demonstrated to yield promising results when compared to other hybrid approaches (Leung and Hung, 2010). To incorporate outlier detection and overcome limitations of the existing MFMW model, three new features are introduced in our proposed MFMW-outlier approach: 1) an unbiased external Leave-One-Out Cross-Validation framework is developed to replace internal cross-validation in the previous MFMW model; 2) wrongly labeled samples are identified within the MFMW-outlier model; and 3) a stable set of genes is selected using an L1-norm SVM that removes any redundant genes present. Six binary-class microarray datasets were tested. Comparing with outlier detection studies on the same datasets, MFMW-outlier could detect all the outliers found in the original paper (for which the data was provided for analysis), and the genes selected after outlier removal were proven to have biological relevance. We also compared MFMW-outlier with PRAPIV (Zhang et al., 2006) based on same synthetic datasets. MFMW-outlier gave better average precision and recall values on three different settings. Lastly, artificially flipped microarray datasets were created by removing our detected outliers and flipping some of the remaining samples'' labels. Almost all the ‘wrong’ (artificially flipped) samples were detected, suggesting that MFMW-outlier was sufficiently powerful to detect outliers in high-dimensional microarray datasets.     

The use of out-of-plane high Z patient shielding for fetal dose reduction in computed tomography: Literature review and comparison with Monte-Carlo calculations of an alternative optimisation technique

When performing CT examinations on pregnant patients, great effort should be dedicated towards optimising the exposure of the mother and the conceptus. For this purpose, many radiology departments use high-Z garments to be wrapped around the patient's lower abdomen for out-of-plane organ shielding to protect the fetus. To assess their current protection efficiency, we performed a literature review and compared the efficiencies mentioned in the literature to Monte-Carlo calculations of CT protocols for which the overall scan length was reduced. We found 11 relevant articles, all of them reporting uterus exposure due to CT imaging performed for exclusion of pulmonary embolism, one of the leading causes of peripartum deaths in western countries. Uterus doses ranged between 60 and 660 µGy per examination, and relative dose reductions to the uterus due to high-Z garments were between 20 and 56%. Calculations showed that reducing the scan length by one to three centimetres could potentially reduce uterus dose up to 24% for chest imaging, and even 47% for upper abdominal imaging. These dose reductions were in the order of those achieved by high-Z garments. However, using the latter may negatively influence the diagnostic image quality and even interfere with the automatic exposure control system thus increasing patient dose if positioned in the primary beam, for example in the overranging length in helical acquisition. We conclude that efforts should be concentrated on positioning the patient correctly in the gantry and optimising protocol parameters, rather than using high-Z garments for out-of-plane uterus shielding.     

Characterization of X-ray Dose in Murine Animals Using microCT,a New Low-Dose Detector and nanoDot Dosimeters

Background

Dose continues to be an area of concern in preclinical imaging studies, especially for those imaging disease progression in longitudinal studies. To our knowledge, this work is the first to characterize and assess dose from the Inveon CT imaging platform using nanoDot dosimeters. This work is also the first to characterize a new low-dose configuration available for this platform.

Methodology/Principal Findings

nanoDot dosimeters from Landauer, Inc. were surgically implanted into 15 wild type mice. Two nanoDots were placed in each animal: one just under the skin behind the spine and the other located centrally within the abdomen. A manufacturer-recommended CT protocol was created with 1 projection per degree of rotation acquired over 360 degrees. For best comparison of the low dose and standard configurations, noise characteristics of the reconstructed images were used to match the acquisition protocol parameters. Results for all dose measurements showed the average dose delivered to the abdomen to be 13.8 cGy±0.74 and 0.97 cGy±0.05 for standard and low dose configurations respectively. Skin measurements of dose averaged 15.99 cGy±0.72 and 1.18 cGy±0.06. For both groups, the standard deviation to mean was less than 5.6%. The maximum dose received for the abdomen was 15.12 cGy and 0.97 cGy while the maximum dose for the skin was 17.3 cGy and 1.32 cGy. Control dosimeters were used for each group to validate that no unwanted additional radiation was present to bias the results.

Conclusions/Significance

This study shows that the Inveon CT platform is suitable for imaging mice both for single and longitudinal studies. Use of low-dose detector hardware results in significant reductions in dose to subjects with a >12x (90%) reduction in delivered dose. Installation of this hardware on another in vivo microCT platform resulted in dose reductions of over 9x (89%).     

A multi‐metric fish index to assess the environmental condition of estuaries

The development of a multi‐metric fish index, the Estuarine Fish Community Index (EFCI), for assessing estuarine environments is described. The index comprises 14 metrics or measures that represent four broad fish community attributes: species diversity and composition, species abundance, nursery function and trophic integrity. The individual metrics were evaluated using data that were collected on a South African estuary that was degraded and in which rehabilitation measures were implemented. The evaluation suggested that the selected metrics adequately measure the condition of separate but related components of estuarine fish communities and that these reflect environmental condition. Reference conditions and metric thresholds were derived from fish community data collected during an extensive national study. The final multi‐metric index was then constructed and evaluated. The EFCI combines both structural and functional attributes of estuarine fish communities and integrates these to provide both a robust and sensitive method for assessing the ecological condition of estuarine systems. It is also an effective communication tool for converting ecological information into an easily understood format for managers, policy makers and the general public.