Forecasting Responses of Seagrass Distributions to Changing Water Quality Using Monitoring Data

Extensive data sets on water quality and seagrass distributions in Florida Bay have been assembled under complementary, but independent, monitoring programs. This paper presents the landscape-scale results from these monitoring programs and outlines a method for exploring the relationships between two such data sets. Seagrass species occurrence and abundance data were used to define eight benthic habitat classes from 677 sampling locations in Florida Bay. Water quality data from 28 monitoring stations spread across the Bay were used to construct a discriminant function model that assigned a probability of a given benthic habitat class occurring for a given combination of water quality variables. Mean salinity, salinity variability, the amount of light reaching the benthos, sediment depth, and mean nutrient concentrations were important predictor variables in the discriminant function model. Using a cross-validated classification scheme, this discriminant function identified the most likely benthic habitat type as the actual habitat type in most cases. The model predicted that the distribution of benthic habitat types in Florida Bay would likely change if water quality and water delivery were changed by human engineering of freshwater discharge from the Everglades. Specifically, an increase in the seasonal delivery of freshwater to Florida Bay should cause an expansion of seagrass beds dominated by Ruppia maritima and Halodule wrightii at the expense of the Thalassia testudinum-dominated community that now occurs in northeast Florida Bay. These statistical techniques should prove useful for predicting landscape-scale changes in community composition in diverse systems where communities are in quasi-equilibrium with environmental drivers.

Estimation of Inequality Indices of the Cumulative Distribution Function

Date of Acceptance: 02/03/2015

Estimation of Inequality Indices of the Cumulative Distribution Function

Date of Acceptance: 02/03/2015

Effect of age on the prognostic value of left ventricular function in patients with acute coronary syndrome : A prospective registry study

© The European Society of Cardiology 2015. Funding The project was funded by the Sir Halley Stewart Trust. MINAP is funded by the Health Quality Improvement Partnership (HQIP).

Associação entre comprometimento motor, mobilidade e qualidade de vida em crianças com paralisia cerebral espástica, nível I, II e III do Gross Motor Function Classification System

The objective of this study was to verify the association between some mobility items of the International Classification Functionality (ICF), with the evaluations Gross Motor Function Measure (GMFM-88), 1-minute walk test (1MWT) and if the motor impairment influences the quality of life in children with Cerebral Palsy (PC), by using the Paediatric Quality of Life Inventory (PedsQL 4.0 versions for children and parents). The study included 22 children with cerebral palsy spastic, classified in levels I, II, and III on the Gross Motor Function Classification System (GMFCS), with age group of 9.9 years old. Among those who have participated, seven of them were level I, eight of them were level II and seven of them were level III. All of the children and teenagers were rated by using check list ICF (mobility item), GMFM-88, 1-minute walk test and PedsQL 4.0 questionnaires for children and parents. It was observed a strong correlation between GMFM-88 with check list ICF (mobility item), but moderate correlation between GMFM-88 and 1-minute walk test (1MWT). It was also moderate the correlation between the walking test and the check list ICF (mobility item). The correlation between PedsQl 4.0 questionnaires for children and parents was weak, as well as the correlation of both with GMFM, ICF (mobility item) and the walking test. The lack of interrelation between physical function tests and quality of life, indicates that, regardless of the severity of the motor impairment and the difficulty with mobility, children and teenagers suffering of PC spastic, functional level I, II and III GMFCS and their parents have a varied opinion regarding the perception of well being and life satisfaction.

Effects of pelvic floor muscle rehabilitation on PFM function and morphology in older women

Aims The purpose of this study was to examine the effect of a pelvic floor muscle (PFM) rehabilitation program on incontinence symptoms, PFM function, and morphology in older women with SUI. Methods Women 60 years old and older with at least weekly episodes of SUI were recruited. Participants were evaluated before and after a 12-week group PFM rehabilitation intervention. The evaluations included 3-day bladder diaries, symptom, and quality of life questionnaires, PFM function testing with dynamometry (force) and electromyography (activation) during seven tasks: rest, PFM maximum voluntary contraction (MVC), straining, rapid-repeated PFM contractions, a 60 sec sustained PFM contraction, a single cough and three repeated coughs, and sagittal MRI recorded at rest, during PFM MVCs and during straining to assess PFM morphology. Results Seventeen women (68.9 ± 5.5 years) participated. Following the intervention the frequency of urine leakage decreased and disease-specific quality of life improved significantly. PFM function improved significantly: the participants were able to perform more rapid-repeated PFM contractions; they activated their PFMs sooner when coughing and they were better able to maintain a PFM contraction between repeated coughs. Pelvic organ support improved significantly: the anorectal angle was decreased and the urethrovescial junction was higher at rest, during contraction and while straining. Conclusions This study indicated that improvements in urine leakage were produced along with improvements in PFM co-ordination (demonstrated by the increased number of rapid PFM contractions and the earlier PFM activation when coughing), motor-control, pelvic organ support.

The effect of Me2SO overexposure during cryopreservation on HOS TE85 and hMSC viability, growth and quality

With the cell therapy industry continuing to grow, the ability to preserve clinical grade cells, including mesenchymal stem cells (MSCs), whilst retaining cell viability and function remains critical for the generation of off-the-shelf therapies. Cryopreservation of MSCs, using slow freezing, is an established process at lab scale. However, the cytotoxicity of cryoprotectants, like Me2SO, raises questions about the impact of prolonged cell exposure to cryoprotectant at temperatures >0 °C during processing of large cell batches for allogenic therapies prior to rapid cooling in a controlled rate freezer or in the clinic prior to administration. Here we show that exposure of human bone marrow derived MSCs to Me2SO for ≥1 h before freezing, or after thawing, degrades membrane integrity, short-term cell attachment efficiency and alters cell immunophenotype. After 2 h's exposure to Me2SO at 37 °C post-thaw, membrane integrity dropped to ∼70% and only ∼50% of cells retained the ability to adhere to tissue culture plastic. Furthermore, only 70% of the recovered MSCs retained an immunophenotype consistent with the ISCT minimal criteria after exposure. We also saw a similar loss of membrane integrity and attachment efficiency after exposing osteoblast (HOS TE85) cells to Me2SO before, and after, cryopreservation. Overall, these results show that freezing medium exposure is a critical determinant of product quality as process scale increases. Defining and reporting cell sensitivity to freezing medium exposure, both before and after cryopreservation, enables a fair judgement of how scalable a particular cryopreservation process can be, and consequently whether the therapy has commercial feasibility.

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.

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.

Effects of pelvic floor muscle rehabilitation on PFM function and morphology in older women

Aims The purpose of this study was to examine the effect of a pelvic floor muscle (PFM) rehabilitation program on incontinence symptoms, PFM function, and morphology in older women with SUI. Methods Women 60 years old and older with at least weekly episodes of SUI were recruited. Participants were evaluated before and after a 12-week group PFM rehabilitation intervention. The evaluations included 3-day bladder diaries, symptom, and quality of life questionnaires, PFM function testing with dynamometry (force) and electromyography (activation) during seven tasks: rest, PFM maximum voluntary contraction (MVC), straining, rapid-repeated PFM contractions, a 60 sec sustained PFM contraction, a single cough and three repeated coughs, and sagittal MRI recorded at rest, during PFM MVCs and during straining to assess PFM morphology. Results Seventeen women (68.9 ± 5.5 years) participated. Following the intervention the frequency of urine leakage decreased and disease-specific quality of life improved significantly. PFM function improved significantly: the participants were able to perform more rapid-repeated PFM contractions; they activated their PFMs sooner when coughing and they were better able to maintain a PFM contraction between repeated coughs. Pelvic organ support improved significantly: the anorectal angle was decreased and the urethrovescial junction was higher at rest, during contraction and while straining. Conclusions This study indicated that improvements in urine leakage were produced along with improvements in PFM co-ordination (demonstrated by the increased number of rapid PFM contractions and the earlier PFM activation when coughing), motor-control, pelvic organ support.

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.

Visual functioning and health-related quality of life in diabetic patients about to undergo anti-vascular endothelial growth factor treatment for sight-threatening macular edema

Purpose To examine patient-reported outcome (PRO) in a selected group of Swedish patients about to receive anti-vascular endothelial growth factor (VEGF) treatment for diabetic macular edema (DME). Material and methods In this cross-sectional study, 59 patients with diabetes mellitus, who regularly visited the outpatient eye-clinics, were included. Sociodemographic and clinical data were collected and the patients completed PRO measures before starting anti-VEGF treatment. PRO measures assessed eye-specific outcomes (NEI-VFQ-25) and generic health-related quality of life (SF-36). Results The participants consisted of 30 men and 29 women (mean age, 68.5 years); 54 (92 %) patients had type 2 diabetes; Five (9%) patients had moderate or severe visual impairment; 28 (47 %) were classified as having mild visual impairment. Some of the patients reported overall problems in their daily lives, such as with social relationships, as well as problems with impaired sight as a result of reduced distance vision. Conclusions Further studies are needed to investigate PRO factors related to low perceived general health in this patient population. It is important to increase our understanding of such underlying mechanisms to promote improvements in the quality of patient care.

Quantitative evaluation of visual function 12 months after bilateral implantation of a diffractive trifocal IOL

PURPOSE: To quantitatively evaluate visual function 12 months after bilateral implantation of the Physiol FineVision® trifocal intraocular lens (IOL) and to compare these results with those obtained in the first postoperative month. METHODS: In this prospective case series, 20 eyes of 10 consecutive patients were included. Monocular and binocular, uncorrected and corrected visual acuities (distance, near, and intermediate) were measured. Metrovision® was used to test contrast sensitivity under static and dynamic conditions, both in photopic and low-mesopic settings. The same software was used for pupillometry and glare evaluation. Motion, achromatic, and chromatic contrast discrimination were tested using 2 innovative psychophysical tests. A complete ophthalmologic examination was performed preoperatively and at 1, 3, 6, and 12 months postoperatively. Psychophysical tests were performed 1 month after surgery and repeated 12 months postoperatively. RESULTS: Final distance uncorrected visual acuity (VA) was 0.00 ± 0.08 and distance corrected VA was 0.00 ± 0.05 logMAR. Distance corrected near VA was 0.00 ± 0.09 and distance corrected intermediate VA was 0.00 ± 0.06 logMAR. Glare testing, pupillometry, contrast sensitivity, motion, and chromatic and achromatic contrast discrimination did not differ significantly between the first and last visit (p>0.05) or when compared to an age-matched control group (p>0.05). CONCLUSIONS: The Physiol FineVision® trifocal IOL provided satisfactory full range of vision and quality of vision parameters 12 months after surgery. Visual acuity and psychophysical tests did not vary significantly between the first and last visit.

Parental reports of the oral health-related quality of life of children with cerebral palsy

BACKGROUND The severity of physical and mental impairments and oral problems, as well as socioeconomic factors, may have an impact on quality of life of children with cerebral palsy (CP). The aim of this research was to assess the impact of impairments and oral health conditions, adjusted by socioeconomic factors, on the Oral Health-Related Quality of Life (OHRQoL) of children with CP using their parents as proxies. METHODS Sixty children, between 6-14 years of age were selected. Their parents answered a children's OHRQoL instrument (5 domains) which combines the Parental-Caregivers Perception Questionnaire (P-CPQ) and Family Impact Scale (FIS). The severity of dental caries, type of CP, communication ability, gross motor function, seizures and socioeconomic conditions were assessed. RESULTS Considering the total score of the OHRQoL instrument, only the reduction of communication ability and dental caries severity had a negative impact on the OHRQoL (p < 0.05). Considering each domain of the instrument, the severity of the type of CP and its reduction of communication ability showed a negative impact on oral symptoms and functional limitations domains (p < 0.05). Seizures have a negative impact on oral symptoms domain (p = 0.006). The multivariate fitted model showed that the severity of dental caries, communication ability and low family income were negatively associated with the impact on OHRQoL (p = 0.001). CONCLUSIONS The severity of dental caries, communication ability, and family income are conditions strongly associated with a negative impact on OHRQoL of children with CP.

Impact of traumatic dental injuries and malocclusions on quality of life of young children

BACKGROUND The presence of traumatic dental injuries and malocclusions can have a negative impact on quality of life of young children and their parents, affecting their oral health and well-being. The aim of this study was to assess the impact of traumatic dental injuries and anterior malocclusion traits on the Oral Health-Related Quality of Life (OHRQoL) of children between 2 and 5 years-old. METHODS Parents of 260 children answered the six domains of the Early Childhood Oral Health Impact Scale (ECOHIS) on their perception of the OHRQoL (outcome). Two calibrated dentists assessed the types of traumatic dental injuries (Kappa = 0.9) and the presence of anterior malocclusion traits (Kappa = 1.0). OHRQoL was measured using the ECOHIS. Poisson regression was used to associate the type of traumatic dental injury and the presence of anterior malocclusion traits to the outcome. RESULTS The presence of anterior malocclusion traits did not show a negative impact on the overall OHRQoL mean or in each domain. Only complicated traumatic dental injuries showed a negative impact on the symptoms (p = 0.005), psychological (p = 0.029), self image/social interaction (p = 0.004) and family function (p = 0.018) domains and on the overall OHRQoL mean score (p = 0.002). The presence of complicated traumatic dental injuries showed an increased negative impact on the children's quality of life (RR = 1.89; 95% CI = 1.36, 2.63; p < 0.001). CONCLUSIONS Complicated traumatic dental injuries have a negative impact on the OHRQoL of preschool children and their parents, but anterior malocclusion traits do not.