Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Automated Assessment of Image Quality and Dose Attributes in Clinical CT Images

Computed tomography (CT) is a valuable technology to the healthcare enterprise as evidenced by the more than 70 million CT exams performed every year. As a result, CT has become the largest contributor to population doses amongst all medical imaging modalities that utilize man-made ionizing radiation. Acknowledging the fact that ionizing radiation poses a health risk, there exists the need to strike a balance between diagnostic benefit and radiation dose. Thus, to ensure that CT scanners are optimally used in the clinic, an understanding and characterization of image quality and radiation dose are essential.

The state-of-the-art in both image quality characterization and radiation dose estimation in CT are dependent on phantom based measurements reflective of systems and protocols. For image quality characterization, measurements are performed on inserts imbedded in static phantoms and the results are ascribed to clinical CT images. However, the key objective for image quality assessment should be its quantification in clinical images; that is the only characterization of image quality that clinically matters as it is most directly related to the actual quality of clinical images. Moreover, for dose estimation, phantom based dose metrics, such as CT dose index (CTDI) and size specific dose estimates (SSDE), are measured by the scanner and referenced as an indicator for radiation exposure. However, CTDI and SSDE are surrogates for dose, rather than dose per-se.

Currently there are several software packages that track the CTDI and SSDE associated with individual CT examinations. This is primarily the result of two causes. The first is due to bureaucracies and governments pressuring clinics and hospitals to monitor the radiation exposure to individuals in our society. The second is due to the personal concerns of patients who are curious about the health risks associated with the ionizing radiation exposure they receive as a result of their diagnostic procedures.

An idea that resonates with clinical imaging physicists is that patients come to the clinic to acquire quality images so they can receive a proper diagnosis, not to be exposed to ionizing radiation. Thus, while it is important to monitor the dose to patients undergoing CT examinations, it is equally, if not more important to monitor the image quality of the clinical images generated by the CT scanners throughout the hospital.

The purposes of the work presented in this thesis are threefold: (1) to develop and validate a fully automated technique to measure spatial resolution in clinical CT images, (2) to develop and validate a fully automated technique to measure image contrast in clinical CT images, and (3) to develop a fully automated technique to estimate radiation dose (not surrogates for dose) from a variety of clinical CT protocols.

Prospective Estimation of Radiation Dose and Image Quality for Optimized CT Performance

X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

Responsiveness and clinical utility of the geriatric self-efficacy index for urinary incontinence

OBJECTIVES: To report on the responsiveness testing and clinical utility of the 12-item Geriatric Self-Efficacy Index for Urinary Incontinence (GSE-UI). DESIGN: Prospective cohort study. SETTING: Six urinary incontinence (UI) outpatient clinics in Quebec, Canada. PARTICIPANTS: Community-dwelling incontinent adults aged 65 and older. MEASUREMENTS: The abridged 12-item GSE-UI, measuring older adults' level of confidence for preventing urine loss, was administered to all new consecutive incontinent patients 1 week before their initial clinic visit, at baseline, and 3 months posttreatment. At follow-up, a positive rating of improvement in UI was ascertained from patients and their physicians using the Patient's and Clinician's Global Impression of Improvement scales, respectively. Responsiveness of the GSE-UI was calculated using Guyatt's change index. Its clinical utility was determined using receiver operating curves. RESULTS: Eighty-nine of 228 eligible patients (39.0%) participated (mean age 72.6+5.8, range 65–90). At 3-month follow-up, 22.5% of patients were very much better, and 41.6% were a little or much better. Guyatt's change index was 2.6 for patients who changed by a clinically meaningful amount and 1.5 for patients having experienced any level of improvement. An improvement of 14 points on the 12-item GSE-UI had a sensitivity of 75.1% and a specificity of 78.2% for detecting clinically meaningful changes in UI status. Mean GSE-UI scores varied according to improvement status (P<.001) and correlated with changes in quality-of-life scores (r=0.7, P<.001) and reductions in UI episodes (r=0.4, P=.004). CONCLUSION: The GSE-UI is responsive and clinically useful.

Mobilizing capacity of environmental information: the importance of quality journalism to achieve proenvironmental attitudes

Citizens say they are very concerned about the environment, and they know the role they play in their deterioration; but there is a gap between this proclaimed interest and the mobilization against environmental problems. Several news published between 2010 and 2011 about the Spanish energy policy and Doñana have economic and social aspects, that sometimes are confused with environmental aspects. It is worthy of study, therefore, to analyze how the press reflects that citizen interest; and how a critical issue as the quality of the information can influence the attitude of citizens in issues related to the environment. If the journalistic practice does not meet quality its function, it will condition the social participation.

Some Remarks on Quality in Interpreting, Interpreting Modes and the Interpreter’s Role

Quality in interpreting is a hotly debated issue whose complexity is determined by a mix of factors. In this article I analyze it in the light of the role played by interpreters, stressing how the constraints imposed by the different interpreting modes, the different roles actually played by professionals (who become more or less visible, even within the same assignment) and the expectations they generate require the adoption of a flexible perspective when it comes to identifying and assessing quality criteria and drafting professional codes that are open enough to adjust to diverse communicative settings and to the dynamic character of quality.

Extracting Patterns from Educational Traces via Clustering and Associated Quality Metrics

Clustering algorithms, pattern mining techniques and associated quality metrics emerged as reliable methods for modeling learners’ performance, comprehension and interaction in given educational scenarios. The specificity of available data such as missing values, extreme values or outliers, creates a challenge to extract significant user models from an educational perspective. In this paper we introduce a pattern detection mechanism with-in our data analytics tool based on k-means clustering and on SSE, silhouette, Dunn index and Xi-Beni index quality metrics. Experiments performed on a dataset obtained from our online e-learning platform show that the extracted interaction patterns were representative in classifying learners. Furthermore, the performed monitoring activities created a strong basis for generating automatic feedback to learners in terms of their course participation, while relying on their previous performance. In addition, our analysis introduces automatic triggers that highlight learners who will potentially fail the course, enabling tutors to take timely actions.

The influence of socio-demographic, psychological and knowledge-related variables alongside perceived cooking and food skills abilities in the prediction of diet quality in adults: a nationally representative cross-sectional study

Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

Development of an instrument measuring the quality of residential care facilities for older people

Aims. To validate the Swedish version of the Sheffield Care Environment Assessment Matrix (S-SCEAM). The instrument’s items measure environmental elements important for supporting the needs of older people, and conceptualized within eight domains. Methods. Item relevance was assessed by a group of experts and measured using content validity index (CVI). Test-retest and inter-rater reliability tests were performed.  The domain structure was assessed by the inter-rater agreement of a second group of experts, and measured using Fleiss kappa. Results. All items attained a CVI above 0.78, the suggested criteria for excellent content validity. Test-retest reliability showed high stability (96% and 95% for two independent raters respectively), and inter-rater reliability demonstrated high levels of agreement (95% and 94% on two separate rating occasions). Kappa values were very good for test-retest (κ = 0.903 and 0.869) and inter-rater reliability (κ = 0.851 and 0.832). Domain structure was good,  Fleiss’ kappa was 0.63 (range 0.45 to 0.75).    Conclusion. The S-SCEAM of 210 items and eight domains showed good content validity and construct validity. The instrument is suggested for use in measuring of the quality of the physical environment in residential care facilities for older persons.

Impact of oral diseases and disorders on oral health-related quality of life of preschool children

BACKGROUND The presence of oral diseases and disorders can produce an impact on the quality of life of preschool children and their parents, affecting their oral health and well-being. However, socioeconomic factors could confound this association, but it has not been yet tested at this age. OBJECTIVE To assess the impact of early childhood caries (ECC), traumatic dental injuries (TDI) and malocclusions on the oral health-related quality of life (OHRQoL) of children between 2 and 5 years of age adjusted by socioeconomic factors. METHODS Parents of 260 children answered the Early Childhood Oral Health Impact Scale (ECOHIS) (six domains) on their perception of the children's OHRQoL and socioeconomic conditions. Two calibrated dentists (κ>0.8) examined the severity of ECC according to dmft index, and children were categorized into: 0=caries free; 1-5=low severity; ≥6=high severity. TDI and malocclusions were examined according to Andreasen & Andreasen (1994) classification and for the presence or absence of three anterior malocclusion traits (AMT), respectively. OHRQoL was measured through ECOHIS domain and total scores, and poisson regression was used to associate the different factors with the outcome. RESULTS In each domain and overall ECOHIS scores, the severity of ECC showed a negative impact on OHRQoL (P<0.001). TDI and AMT did not show a negative impact on OHRQoL nor in each domain (P>0.05). The increase in the child's age, higher household crowding, lower family income and mother working out of home were significantly associated with OHRQoL (P<0.05). The multivariate adjusted model showed that the high severity of ECC (RR=3.81; 95% CI=2.66, 5.46; P<0.001) was associated with greater negative impact on OHRQoL, while high family income was a protective factor for OHRQoL (RR=0.93; 95% CI=0.87, 0.99; P<0.001). CONCLUSIONS The severity of ECC and a lower family income had a negative impact on the OHRQoL of preschool children and their parents.

A cross-sectional study assessing the association between online ratings and structural and quality of care measures : results from two German physician rating websites

BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.

The Relationship of Diet Quality and Blood Serum Lipid Levels in a Population at High Risk for Diabetes: The Strong Heart Family Study

Thesis (Master's)--University of Washington, 2016-08

Health-related quality of life in portuguese SLE patients: an outcome measure independent of disease activity and cumulative damage

PURPOSE: To evaluate quality of life in Portuguese patients with Systemic Lupus Erithematosus (SLE) and its correlation with disease activity and cumulative damage. METHODS: We included consecutive SLE patients, fulfilling the 1997 ACR Classification Criteria for SLE and followed at the Rheumatology Department of the University Hospital of Coimbra, Portugal at time of visit to the outpatient clinic. Quality of life was evaluated using the patient self-assessment questionnaire Medical Outcomes Survey Short Form-36 (SF-36) (validated Portuguese version). The consulting rheumatologist fulfilled the SLE associated indexes for cumulative damage (Systemic Lupus International Collaborating Clinics- Damage Index: SLICC/ACR-DI) and disease activity (Systemic Lupus Erythematosus Disease Activity Index: SLEDAI 2000). Correlation between SLEDAI and SLICC and SF-36 was tested with the Spearman Coefficient. Significant level considered was 0.05. RESULTS: The study included 133 SLE patients (90.2% female, mean age - 40.7 years, mean disease duration - 8.7 years). Most patients presented low disease activity (mean SLEDAI = 4.23) and limited cumulative damage (mean SLICC = 0.76). Despite that, SF-36 mean scores were below 70% in all eight domains of the index. Physical function domains showed lower scores than mental function domains. The QoL in this group of patients is significantly impaired when compared with the reference Portuguese population (p<0.05 in all domains). There was no correlation between clinical activity or cumulative damage and quality of life. CONCLUSION: QoL is significantly compromised in this group of SLE patients, but not related with disease activity or damage. These findings suggest that disease activity, cumulative damage and QoL are independent outcome measures and should all be used to assess the full impact of disease in SLE patients.

Variation in composition of macro-benthic invertebrates as an indication of water quality status in three bays in Lake Victoria

Knowledge of how biota can be used to monitor ecosystem health and assess impacts by human alterations such as land use and management measures taken at different spatial scales is critical for improving the ecological quality of aquatic ecosystems. This knowledge in Uganda is very limited or unavailable yet it is needed to better understand the relationship between environmental factors at different spatial scales, assemblage structure and taxon richness of aquatic ecosystems. In this study, benthic invertebrate community patterns were sampled between June 2001 and April 2002 and analysed in relation to water quality and catchment land use patterns from three shallow near-shore bays characterized by three major land uses patterns: urban (Murchison Bay); semi-urban (Fielding Bay); rural (Hannington Bay). Variations in density and guild composition of benthic macro-invertebrates communities were evaluated using GIS techniques along an urban-rural gradient of land use and differences in community composition were related to dissolved oxygen and conductivity variation. Based on numerical abundance and tolerance values, Hilsenhoff's Biotic Index ofthe invertebrates was determined in order to evaluate the relative importance of water quality in the three bays. Murchison Bay supported a relatively taxa-poor invertebrate assemblage mainly comprising stenotopic and eurytopic populations of pollution-tolerant groups such as worms and Chironomus sp. with an overall depression in species diversity. On the contrary, the communities in Fielding and Hannington bays were quite similar and supported distinct and diverse assemblages including pollution-intolerant forms such as Ephemeroptera (mayflies), Odonata (dragonflies). The Hilsenhoff Biotic Index in Murchison Bay was 6.53. (indicating poor water quality) compared to 6.34 for Fielding Bay and 5.78 for Hannington Bay (both indicating fair water quality). The characterization of maximum taxa richness balanced among taxa groups with good representation of intolerant individuals in Hannington Bay relative to Fielding and Murchison bays concludes that the bay is the cleanest in terms of water quality. Contrary, the dominance of few taxa with many tolerant iqdividuals present in Murchison Bay indicates that the bay is degraded in terms of water quality. These result are ofimportance when planning conservation and management measures, implementing large-scale biomonitoring programs, and predicting how human alterations (e.g nutrient loading) affect water ecosystems. Therefore, analysis of water quality in relation to macro-invertebrate community composition patterns as bio-indicators can lead to further understanding of their responses to environmental manipulations and perturbations.

Biofloc contribution to antioxidant defence status, lipid nutrition and reproductive performance of broodstock of the shrimp Litopenaeus stylirostris: Consequences for the quality of eggs and larvae

The aim of this study was to determine biofloc contributions to the antioxidant status and lipid nutrition of broodstock of Litopenaeus stylirostris in relationship with their reproductive performance and the health of larvae produced. Shrimp broodstock reared with Biofloc technology (BFT) compared to Clear water (CW) exhibited a higher health status with (i) a better final survival rate during the reproduction period (52.6% in CW against 79.8% in BFT); (ii) higher glutathione level (GSH) and total antioxidant status (TAS), reduced oxidized/reduced glutathione ratio and a higher spawning rate and frequency as well as higher gonado-somatic index and number of spawned eggs. Finally, larvae from broodstock from BFT exhibited higher survival rates at the Zoe 2 (+ 37%) and Post Larvae 1 (+ 51%) stages when compared with those from females from CW treatment. The improved reproductive performance of the broodstock and higher larvae survival rate resulting from BFT treatment may be linked to the dietary supplement obtained by the shrimp from natural productivity during BFT rearing. Indeed, our study confirms that biofloc particulates represent a potential source of dietary glutathione and a significant source of lipids, particularly essential phospholipids and n-3 highly unsaturated fatty acids (HUFA) for shrimps. Thus, broodstock from BFT treatment accumulated phospholipids, n-3 HUFA and arachidonic acid, which are necessary for vitellogenesis, embryogenesis and pre-feeding larval development. The predominant essential fatty acids, arachidonic acid (ARA), eicopentaeonic acid (EPA) and docosahexaenoic acid (DHA), had levels in the eggs that were, respectively, 2.5, 2.8 and 3 fold higher for BFT compared to the CW treatment. Statement of Relevance Today, the influence of biofloc technology on shrimp broodstock is not enough described and no information was available on the larvae quality. Moreover, two key pieces of new information emerge from the present study. Firstly, biofloc is a source of further dietary lipids that can act as energetic substrates, but also as a source of phospholipids and essential fatty acids necessary to sustain reproduction, embryonic and larval development. Second, improving the reproduction of the broodstock also leads to an improvement in the quality of the larvae. We think that our research is new and important to increase knowledge on biofloc topic. We believe the paper will contribute to the development of more efficient and therefore more sustainable systems.