Uncorrected Data Research Articles

Evaluation of the Compatibility of TRMM Satellite Data with Precipitation Observation Data

The availability of hydrological data is one of the challenges associated with developing water infrastructure in different areas. This led to the TRMM (Tropical Precipitation Measurement Mission) design by NASA, which involves using satellite weather monitoring technology to monitor and analyze tropical precipitation in different parts of the world. Therefore, this validation study was conducted to compare TRMM precipitation data with observed precipitation to determine its application as an alternate source of hydrological data. The Kuranji watershed was selected as the study site due to the availability of suitable data. Moreover, the validation analyses applied include the Root Mean Squared Error (RMSE), Nash-Sutcliffe Efficiency (NSE), Coefficient Correlation (R), and Relative Error (RE). These used two calculation forms: one for the uncorrected data and another for the corrected data. The results showed that the best-adjusted data validation from the Gunung Nago station in 2016 was recorded to be RMSE = 62,298, NSE = 0.044, R = 0.902, and RE = 11,328. The closeness of the R-value to one implies that the corrected TRMM data outperforms the uncorrected ones. Therefore, it was generally concluded that the TRMM data matches the observed precipitation data and can be used for hydrological study in the Kuranji watershed

Self-supervised denoising of projection data for low-dose cone-beam CT.

Convolutional neural networks(CNNs) have shown promising results in image denoising tasks. While most existing CNN-based methods depend on supervised learning by directly mapping noisy inputs to clean targets, high-quality references are often unavailable for interventional radiology such as cone-beam computed tomography(CBCT). In this paper, we propose a novel self-supervised learning method that reduces noise in projections acquired by ordinary CBCTscans. With a network that partially blinds input, we are able to train the denoising model by mapping the partially blinded projections to the original projections. Additionally, we incorporate noise-to-noise learning into the self-supervised learning by mapping the adjacent projections to the original projections. With standard image reconstruction methods such as FDK-type algorithms, we can reconstruct high-quality CBCT images from the projections denoised by our projection-domain denoising method. In the head phantom study, we measure peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) values of the proposed method along with the other denoising methods and uncorrected low-dose CBCT data for a quantitative comparison both in projection and image domains. The PSNR and SSIM values of our self-supervised denoising approach are 27.08 and 0.839, whereas those of uncorrected CBCT images are 15.68 and 0.103, respectively. In the retrospective study, we assess the quality of interventional patient CBCT images to evaluate the projection-domain and image-domain denoising methods. Both qualitative and quantitative results indicate that our approach can effectively produce high-quality CBCT images with low-dose projections in the absence of duplicate clean or noisyreferences. Our self-supervised learning strategy is capable of restoring anatomical information while efficiently removing noise in CBCT projection data.

Quantifying and correcting for speed and stride frequency effects on running mechanics in fatiguing outdoor running.

Measuring impact-related quantities in running is of interest to improve the running technique. Many quantities are typically measured in a controlled laboratory setting, even though most runners run in uncontrolled outdoor environments. While monitoring running mechanics in an uncontrolled environment, a decrease in speed or stride frequency can mask fatigue-related changes in running mechanics. Hence, this study aimed to quantify and correct the subject-specific effects of running speed and stride frequency on changes in impact-related running mechanics during a fatiguing outdoor run. Seven runners ran a competitive marathon while peak tibial acceleration and knee angles were measured with inertial measurement units. Running speed was measured through sports watches. Median values over segments of 25 strides throughout the marathon were computed and used to create subject-specific multiple linear regression models. These models predicted peak tibial acceleration, knee angles at initial contact, and maximum stance phase knee flexion based on running speed and stride frequency. Data were corrected for individual speed and stride frequency effects during the marathon. The speed and stride frequency corrected and uncorrected data were divided into ten stages to investigate the effect of marathon stage on mechanical quantities. This study showed that running speed and stride frequency explained, on average, 20%-30% of the variance in peak tibial acceleration, knee angles at initial contact, and maximum stance phase knee angles while running in an uncontrolled setting. Regression coefficients for speed and stride frequency varied strongly between subjects. Speed and stride frequency corrected peak tibial acceleration, and maximum stance phase knee flexion increased throughout the marathon. At the same time, uncorrected maximum stance phase knee angles showed no significant differences between marathon stages due to a decrease in running speed. Hence, subject-specific effects of changes in speed and stride frequency influence the interpretation of running mechanics and are relevant when monitoring, or comparing the gait pattern between runs in uncontrolled environments.

Chorus Wave Properties From Van Allen Probes: Quantifying the Impact of the Sheath Corrected Electric Field

AbstractA sheath impedance model has recently been developed to describe how the variable coupling impedance between the Van Allen Probes instrumentation and the ambient plasma affects both the amplitude and phase of electric field wave measurements. Here, the impact of this sheath correction on measured chorus wave properties, including electric field wave power and the Poynting vector, is directly quantified. It is found that the sheath‐corrected electric field wave power is typically between two and nine times larger than the uncorrected measurement, depending on wave frequency. The sheath correction typically increases the Poynting flux by a factor of ∼2, and causes the polar angle of the Poynting vector to switch hemisphere from parallel to anti‐parallel propagation in ∼2% of cases. The uncorrected data exhibit significant deviations from the theoretically predicted relationship between the wave vector and the Poynting vector whereas this relationship is well‐reproduced with the sheath‐corrected observations.

Benchmarking integration of single-cell differential expression

Integration of single-cell RNA sequencing data between different samples has been a major challenge for analyzing cell populations. However, strategies to integrate differential expression analysis of single-cell data remain underinvestigated. Here, we benchmark 46 workflows for differential expression analysis of single-cell data with multiple batches. We show that batch effects, sequencing depth and data sparsity substantially impact their performances. Notably, we find that the use of batch-corrected data rarely improves the analysis for sparse data, whereas batch covariate modeling improves the analysis for substantial batch effects. We show that for low depth data, single-cell techniques based on zero-inflation model deteriorate the performance, whereas the analysis of uncorrected data using limmatrend, Wilcoxon test and fixed effects model performs well. We suggest several high-performance methods under different conditions based on various simulation and real data analyses. Additionally, we demonstrate that differential expression analysis for a specific cell type outperforms that of large-scale bulk sample data in prioritizing disease-related genes.

The first aerial survey to estimate abundance of humpback whales (Megaptera novaeangliae) in the breeding ground off Brazil (Breeding Stock A)

In the Southern Hemisphere, humpback whales (Megaptera novaeangliae) were heavily exploited from both coastal stations and in pelagic waters in all major ocean basins. About 200,000 whales were taken after 1900, causing declines of populations to small percentages of their pre-exploitation levels. The study presented here aimed to investigate humpback whale abundance in the Brazilian coastal breeding ground, in order to provide information to support further analysis of the population recovery. Between 25 August and 2 September 2001, a fixed wing, flat window, aircraft was used to survey transect lines along the northern limit of Bahia State (12°10’S), to the southern limit of Espírito Santo State (20°42’S). All on-effort sightings were recorded and abundance was estimated according to standard distance sampling methodology (Burnham et al., 1980; Buckland et al., 1993). Group sizes of humpback whales ranged between 1-5 and the mean group size was 1.52 (±0.06). The model that best fitted the perpendicular distance data, based on the minimum Akaike Information Criterion, was the hazard rate model. The population size estimated using uncorrected data was 1,493 (CV=0.21) whales. Surface time was used to correct the estimates for gˆ(0), resulting in a correction factor of 0.67 (±0.15). The corrected analysis for each block and combined result, increased the population size estimate to 2,229 (CV=0.31) individuals. The data from this study could be used to identify new areas appropriate for whalewatching, to monitor the status and dynamics of the humpback whale population off the Brazilian coast and to provide information for the establishment of new protected areas.

Jet fragmentation properties with CMS open-data

The CMS collaboration has made some of their data public, making it possible for external users to perform physics analysis using real data. In this work, we report the measurement of jet properties such as fragmentation function, and the average multiplicity distribution of leptons and charged hadrons within the jets, all of them produced in pp collisions at = 7 TeV. We show that by implementing high energy cuts, the uncorrected experimental data approaches the behavior of corrected data, facilitating the use of open-data for simple analysis. The analysis is restricted in pseudorapidity and energy of the jets to: ∣η Jet∣ < 2.1 and E Jet > 120 GeV respectively. For the study we used the anti − K T algorithm applied to four samples of 2011 CMS open-data, to explore the possible differences obtained by using different trigger conditions, and the results are compared with predictions from the Pythia 8 event generator.

Comparison of the Pharmacokinetics, Bioequivalence and Safety of Aqueous Progesterone Formulation Administered as either Intramuscular or Subcutaneous Injection versus Oil-based Progesterone Formulation Administered as Intramuscular Injection: A Randomised Study

Introduction: Progesterone is the treatment of choice for support of the luteal phase of controlled ovarian stimulation cycles in women undergoing an Assisted Reproductive Technology (ART) treatment. Available progesterone preparations include oral, vaginal and oil-based Intramuscular (i.m.) formulations. Oral formulation has poor bioavailability whereas vaginal formulations cause side-effects such as vaginal discharge and/ or local irritation. Oil-based progesterone formulations for i.m. use are associated with discomfort and pain at the injection site. Hence, a novel aqueous-based progesterone formulation for i.m./Subcutaneous (s.c.) was developed to avoid the local tolerability issues of the existing parenteral formulations. Aim: To assess single-dose Pharmacokinetics (PK) and relative bioavailability of i.m. (test-1; T1) or s.c. (test-2; T2) administration of novel aqueous progesterone formulation with i.m. (reference; R) administration of oil-based progesterone formulation. Materials and Methods: In this open-label, three-sequence, three-period, single-dose, cross-over study, 51 healthy human postmenopausal female subjects between 45 to 65 years of age were included. The study was conducted at Lambda Therapeutic Research Limited, Ahmedabad, Gujarat, India, between 21 May 2018 to 06 July 2018. Subjects were randomised to a single 25 mg dose of T1, T2 or R in three-periods (Period-I: T1, R, T2; Period-II: T2, T1, R; Period-III: R, T2, T1) with ≥18 days washout period. Blood samples were collected at prespecified time points in each period and analysed using validated liquid chromatography with tandem mass spectrometry. PK parameters {maximum plasma concentration (Cmax), time to reach Cmax (Tmax), area under the plasma concentration vs. time curve (AUC0-t), AUC from time 0 to ∞ (AUC0-∞), plasma half-life (t1/2)} were calculated from the plasma concentration vs. time profile by non compartmental model. The total study duration was about 47 days (11 hours prior to the drug administration in Period-I until the last ambulatory sample in Period-III). All patients provided written informed consent form and an approval from the Conscience-Independent Ethics Committee (CIEC) was taken. Descriptive statistics were calculated and reported for PK parameters for baseline corrected and uncorrected data. Results: Of 72 screened patients, 51 patients were included for the PK and statistical analysis. The mean±SD age of the patients was 55.1±4.67 years. The baseline corrected PK data shows that in T1, T2 and R arms, mean (range) Tmax were 1.00 (0.50– 1.75), 1.00 (0.75–1.75) and 8.00 hours (1.00–12.00), mean±SD t ½ (h) were 15.43±5.81, 15.27±6.68 and 19.80±6.35; mean±SD Cmax (ng/mL) were 101.91±73.07, 51.67±14.81 and 18.89±7.89, and mean±SD AUC0-t (ng/mL) were 385.10±89.29, 349.63±64.41 and 371.50±56.25, respectively. Similarly, the AUC0-∞ was also comparable in all three arms. The baseline uncorrected data were also in line with baseline corrected data. For AUC0-t and AUC0-∞, 90% CIs were 98.44-107.06% and 97.96-106.15%, respectively, for T1/R ratio, and 90.01-97.90 and 89.90-97.42, respectively, for T2/R ratio. Six Adverse Events (AEs) in four subjects were reported. All AEs were mild in nature and there were no deaths, significant or serious AEs reported. Overall, all the treatments were well-tolerated without any new safety concerns. Conclusion: Novel aqueous progesterone formulation i.m./s.c was bioequivalent with oil-based progesterone formulation i.m. with respect to AUC. The s.c. administration of aqueous progesterone formulation could offer a convenient alternative to the i.m. oil-based progesterone formulation for luteal phase support to patients undergoing ART treatments

Enhancing drought resilience and energy security through complementing hydro by offshore wind power—The case of Brazil

During atypical droughts, power systems with a heavy reliance on hydropower risk increased greenhouse gas emissions if they are balanced with fossil-fired generation. This work investigates the role of offshore wind energy in reducing the vulnerability of power systems dependent on such hydrological patterns, thereby eliminating this emission increase, using Brazil as a case study. Offshore wind potential and its complementarity with hydro resources are addressed by considering bias-corrected reanalysis data. Then, a cost-minimizing model is built to analyze the effect of integrating wind farms (considering bottom-fixed and floating structures and distance to shore) into the existing power system in Brazil. Applying a lower, median, and upper bias correction factor, potentials are reduced by 8%–44% compared to uncorrected data. Irrespective of systematic bias, the findings indicate a high complementarity between Northeastern wind regimes and most hydropower basins. The share of offshore wind energy grows in scenarios with reduced costs, but wind farms are part of the optimal system even with the current costs. With increasing wind power capacity, dynamic dispatch changes, and natural gas no longer plays a role in the dry season as it currently does, but only in the rainy season on a significantly reduced scale. Existing reservoirs support the integration of offshore wind farms into highly renewable scenarios, but they are insufficient in a complete fossil fuel phaseout, where other electricity storage must be deployed to help balance the system. Yet, power systems in the scenarios with large wind capacity have less stored hydropower in the dry season than in the current system, while they store more in the rainy season, implying a reduced risk of empty reservoirs. The Brazilian power system with offshore wind farms can eliminate 54.4 Mton CO2eq/year (97% of current power sector emissions) without additional electricity storage.

Correction and Accuracy of PurpleAir PM2.5 Measurements for Extreme Wildfire Smoke.

PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries for real-time air quality information, particularly during wildfire smoke episodes. Uncorrected PurpleAir data can be biased and may exhibit a nonlinear response at extreme smoke concentrations (>300 µg/m3). This bias and nonlinearity result in a disagreement with the traditional ambient monitoring network, leading to the public’s confusion during smoke episodes. These sensors must be evaluated during smoke-impacted times and then corrected for bias, to ensure that accurate data are reported. The nearby public PurpleAir sensor and monitor pairs were identified during the summer of 2020 and were used to supplement the data from collocated pairs to develop an extended U.S.-wide correction for high concentrations. We evaluated several correction schemes to identify an optimal correction, using the previously developed U.S.-wide correction, up to 300 µg/m3, transitioning to a quadradic fit above 400 µg/m3. The correction reduces the bias at each air quality index (AQI) breakpoint; most ambient collocations that were studied met the Environmental Protection Agency’s (EPA) performance targets (twelve of the thirteen ambient sensors met the EPA’s targets) and some smoke-impacted sites (5 out of 15 met the EPA’s performance targets in terms of the 1-h averages). This correction can also be used to improve the comparability of PurpleAir sensor data with regulatory-grade monitors when they are collectively analyzed or shown together on public information websites; the methods developed in this paper can also be used to correct future air-sensor types. The PurpleAir network is already filling in spatial and temporal gaps in the regulatory monitoring network and providing valuable air-quality information during smoke episodes.

Validation of a drift-corrected 3D MR temperature imaging sequence for breast MR-guided focused ultrasound treatments

Real-time temperature monitoring is critical to the success of thermally ablative therapies. This work validates a 3D thermometry sequence with k-space field drift correction designed for use in magnetic resonance-guided focused ultrasound treatments for breast cancer. Fiberoptic probes were embedded in tissue-mimicking phantoms, and temperature change measurements from the probes were compared with the magnetic resonance temperature imaging measurements following heating with focused ultrasound. Precision and accuracy of measurements were also evaluated in free-breathing healthy volunteers (N = 3) under a non-heating condition.MR temperature measurements agreed closely with those of fiberoptic probes, with a 95% confidence interval of measurement difference from −2.0 °C to 1.4 °C. Field drift-corrected measurements in vivo had a precision of 1.1 ± 0.7 °C and were accurate within 1.3 ± 0.9 °C across the three volunteers. The field drift correction method improved precision and accuracy by an average of 46 and 42%, respectively, when compared to the uncorrected data. This temperature imaging sequence can provide accurate measurements of temperature change in aqueous tissues in the breast and support the use of this sequence in clinical investigations of focused ultrasound treatments for breast cancer.

Investigating the Impact of the Spatiotemporal Bias Correction of Precipitation in CMIP6 Climate Models on Drought Assessments

Precipitation of future climate models is critical for the assessments of future drought but contains large systematic biases over the Tibetan Plateau. Although the common precipitation bias correction method, quantile mapping has achieved remarkable results in terms of temporal bias correction, it does not consider the spatial distribution of bias. Furthermore, the extent to which precipitation bias affects drought estimation remains unclear. In our study, we take the Qinghai–Tibet Plateau (QHTP) as the case study and quantify the impact of corrected precipitation bias for seven Coupled Model Intercomparison Project Phase 6 (CMIP6) models on drought assessment in historical and future scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). To improve the accuracy of drought prediction, potential evapotranspiration (PET) was also corrected. Firstly, the histogram matching-quantile mapping (HQ) algorithm considering spatial correction is established to correct precipitation and PET. Then, we quantified the effects of precipitation and potential evapotranspiration correction on the change of drought intensity, and finally analyzed the spatiotemporal trends of precipitation, PET, and SPEI over the QHTP in the future. The results show that the HQ method can effectively improve the simulation ability of the model, especially the simulation accuracy of the ensemble model. After correction, the average annual total precipitation (TP) declined by 64.262% in 99.952% of QHTP, the average PET increased in 11.902% of the area and decreased in 88.098% of the area, while the intensity of the drought in 81.331% of the area increased by 2.875% and the 18.669% area decreased by 1.139%. Therefore, the uncorrected simulation data overestimated the future increase trend in precipitation and underestimated the future decrease trend in SPEI. The trend of HQ-corrected TP increased by 3.730 mm/10a, 7.190 mm/10a, and 12.790 mm/10a, and the trend of SPEI (TP and PET corrected) decreased by 0.143/100a, 0.397/100a, and 0.675/100a, respectively. Therefore, quantifying the changing relationship between precipitation bias correction and drought assessments is useful for understanding regional climate change.

On the Consistency of the Bottle and CTD Profile Data

Abstract Nansen bottle casts served as the main oceanographic instrumentation type for more than a century since the establishing of the technique in the late 1890s. Between the end of the 1960s and the end of the 1990s Nansen cast technique has been gradually replaced by electronic sensor profilers (CTD). Both instrumentation types are considered as the most accurate among other oceanographic instruments and are often used as the unbiased reference. We conducted a comprehensive investigation of the consistency of the temperature data from Nansen casts and CTD profilers analyzing the quasi-collocated bottle and CTD data between the 1960s and the 1990s when both instrumentation types overlap. We found that Nansen casts tend to overestimate the sample depth with reversing mercury-in-glass thermometer temperatures being on average slightly lower compared to CTD data. Respectively, depth and temperature corrections are provided. Further, we estimated the ocean heat content changes between 1955 and 1990 using (along with all other instrumentation types) corrected and uncorrected Nansen cast data. These calculations show that for the upper 2 km layer the global average warming trend for this time period increases from 0.20 ± 0.05 W m−2 for the uncorrected data to 0.28 ± 0.06 W m−2 for the corrected data at the 90% confidence level. Finally, we suggest that the Nansen bottle cast profiles be put into a separate instrumentation group within the World Ocean Database.

Glial activation may mediate Alzheimer’s disease progression

AbstractBackgroundGlial activation may precede regional tau progression through Braak stages in Alzheimer’s Disease (AD)[1]. However, the role of glial activity in the temporal progression of AD is not well characterized.MethodNineteen controls and 22 patients with clinical diagnosis of MCI or AD underwent [18F]florbetaben, [18F]MK‐6240, and [11C]PBR28 PET to measure β‐amyloid, tau, and TSPO (a glial biomarker). Standard uptake value ratios and corrected gray matter volume (%GM) were calculated from prefrontal, temporal, and parietal regions to create composite AD‐centric measures for β‐amyloid, TSPO, and neurodegeneration. Braak‐specific gray matter volumes were used to measure tau and neurodegeneration in early (I/II), middle (III/IV) and late (V/VI) Braak regions. Tau and TSPO were measured with (‐PVC) and without partial volume correction. Correlation analyses were performed between TSPO and β‐amyloid, tau, and MMSE scores. Mediation analyses explored the effect of TSPO in the steps along a proposed model for AD progression (Fig 1).ResultGreater TSPO‐PVC was associated with greater β‐amyloid (std.β=0.38, p=0.015), and with greater tau‐PVC in middle (std.β=0.45, p=0.004) and late Braak regions (std.β=0.50, p=0.002, Fig 2), even after controlling for %GM. Greater TSPO‐PVC was associated with lower MMSE score (std.β=‐0.53, p=0.006). Similar results were observed for uncorrected PET data. TSPO‐PVC mediated the relationship between tau‐PVC in early Braak regions and tau‐PVC in middle Braak regions (indirect effect=0.118, p=0.017) and the relationship between tau‐PVC in middle Braak regions and neurodegeneration in middle Braak regions (indirect effect=‐0.255, p=0.027). TSPO‐PVC mediated the relationship between neurodegeneration and impaired MMSE performance for early (indirect effect=0.233, p=0.021) and middle Braak regions (indirect effect=0.204, p=0.029), and between neurodegeneration and impaired Trails B performance for early (indirect effect=0.283, p=0.009) and middle Braak regions (indirect effect=0.228, p=0.017).ConclusionTSPO is related to β‐amyloid burden, tau pathology in middle and late Braak regions, and cognitive impairment in a manner independent of neurodegeneration. Our results suggest that glial activity impacts the progression of tau pathology from early to middle Braak regions and influences the relationship between neurodegeneration and cognitive impairment in these same regions.Reference: 1. Pascoal, T.A., et al. Microglial activation and tau propagate jointly across Braak stages. Nat Med 27, 1592–1599(2021).

Multidecadal Trend Analysis of Armenian Mountainous Grassland and Its Relationship to Climate Change Using Multi-Sensor NDVI Time-Series

This paper presents a comprehensive analysis of links between satellite-measured vegetation vigor and climate variables in Armenian mountain grassland ecosystems in the years 1984–2018. NDVI is derived from MODIS and LANDSAT data, temperature and precipitation data are from meteorological stations. Two study sites were selected, representing arid and semi-arid grassland vegetation types, respectively. Various trend estimators including Mann–Kendall (MK) and derivatives were combined for vegetation change analysis at different time scales. Results suggest that temperature and precipitation had negative and positive impacts on vegetation growth, respectively, in both areas. NDVI-to-precipitation correlation was significant but with an apparent time-lag effect that was further investigated. No significant general changes were observed in vegetation along the observed period. Further comparisons between results from corrected and uncorrected data led us to conclude that MODIS and LANDSAT data with BRDF, topographic and atmospheric corrections applied are best suited for analyzing relationships between NDVI and climatic factors for the 2000–2018 period in grassland at a very local scale; however, in the absence of correction tools and information, uncorrected data can still provide meaningful results. Future refinements will include removal of anthropogenic impact, and deeper investigation of time-lag effects of climatic factors on vegetation dynamics.

Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short distance channels.

.Significance: Functional near-infrared spectroscopy (fNIRS) is a promising tool for neurofeedback (NFB) or brain–computer interfaces (BCIs). However, fNIRS signals are typically highly contaminated by systemic activity (SA) artifacts, and, if not properly corrected, NFB or BCIs run the risk of being based on noise instead of brain activity. This risk can likely be reduced by correcting for SA, in particular when short-distance channels (SDCs) are available. Literature comparing correction methods with and without SDCs is still sparse, specifically comparisons considering single trials are lacking.Aim: This study aimed at comparing the performance of SA correction methods with and without SDCs.Approach: Semisimulated and real motor task data of healthy older adults were used. Correction methods without SDCs included a simple and a more advanced spatial filter. Correction methods with SDCs included a regression approach considering only the closest SDC and two GLM-based methods, one including all eight SDCs and one using only two a priori selected SDCs as regressors. All methods were compared with data uncorrected for SA and correction performance was assessed with quality measures quantifying signal improvement and spatial specificity at single trial level.Results: All correction methods were found to improve signal quality and enhance spatial specificity as compared with the uncorrected data. Methods with SDCs usually outperformed methods without SDCs. Correction methods without SDCs tended to overcorrect the data. However, the exact pattern of results and the degree of differences observable between correction methods varied between semisimulated and real data, and also between quality measures.Conclusions: Overall, results confirmed that both and are affected by SA and that correction methods with SDCs outperform methods without SDCs. Nonetheless, improvements in signal quality can also be achieved without SDCs and should therefore be given priority over not correcting for SA.

Towards accurate partial volume correction in 99mTc oncology SPECT: perturbation for case-specific resolution estimation

BackgroundCurrently, there is no consensus on the optimal partial volume correction (PVC) algorithm for oncology imaging. Several existing PVC methods require knowledge of the reconstructed resolution, usually as the point spread function (PSF)—often assumed to be spatially invariant. However, this is not the case for SPECT imaging. This work aimed to assess the accuracy of SPECT quantification when PVC is applied using a case-specific PSF.MethodsSimulations of SPECT ^{99{mathrm{m}}}Tc imaging were performed for a range of activity distributions, including those replicating typical clinical oncology studies. Gaussian PSFs in reconstructed images were estimated using perturbation with a small point source. Estimates of the PSF were made in situations which could be encountered in a patient study, including; different positions in the field of view, different lesion shapes, sizes and contrasts, noise-free and noisy data. Ground truth images were convolved with the perturbation-estimated PSF, and with a PSF reflecting the resolution at the centre of the field of view. Both were compared with reconstructed images and the root-mean-square error calculated to assess the accuracy of the estimated PSF. PVC was applied using Single Target Correction, incorporating the perturbation-estimated PSF. Corrected regional mean values were assessed for quantitative accuracy.ResultsPerturbation-estimated PSF values demonstrated dependence on the position in the Field of View and the number of OSEM iterations. A lower root mean squared error was observed when convolution of the ground truth image was performed with the perturbation-estimated PSF, compared with convolution using a different PSF. Regional mean values following PVC using the perturbation-estimated PSF were more accurate than uncorrected data, or data corrected with PVC using an unsuitable PSF. This was the case for both simple and anthropomorphic phantoms. For the simple phantom, regional mean values were within 0.7% of the ground truth values. Accuracy improved after 5 or more OSEM iterations (10 subsets). For the anthropomorphic phantoms, post-correction regional mean values were within 1.6% of the ground truth values for noise-free uniform lesions.ConclusionPerturbation using a simulated point source could potentially improve quantitative SPECT accuracy via the application of PVC, provided that sufficient reconstruction iterations are used.

Comparison of safety and efficacy of silicone hydrogel contact Lens-assisted CXL and accelerated CXL in keratoconus patients with thin corneas.

To evaluate the efficacy and safety of silicone hydrogel contact lens-assisted corneal cross-linking (CL-CXL) and compare 12-month visual and topographic outcomes with accelerated CXL using hypo-osmolar riboflavin (A-CXL) in keratoconus patients with thin corneas (below 400 μm with epithelium). This retrospective study included 27 eyes of 27 keratoconus patients who underwent CL-CXL (n = 14) or A-CXL (n = 13). Uncorrected and corrected distance visual acuity (UDVA and CDVA) and data obtained from corneal topography were analyzed at baseline and again at 6- and 12-month follow-ups. Corneal demarcation line depth (DLD) was measured at one month, and changes in the corneal endothelial cell density (ECD) at 12 months were also assessed. Mean UDVA improved significantly in both groups at 12 months (all p < 0.05). Maximum keratometry (K-max) decreased by 1.04 ± 1.90 D in the CL-CXL group and by 0.87 ± 1.89 D in the A-CXL group at 12 months, which was not statistically significant (all p>0.05). Total corneal higher-order aberrations (HOAs) analysis showed a significant improvement in only the CL-CXL group at 12 months (p = 0.041). Average DLD was 227.18 ± 65.60 μm in the CL-CXL group and 245.30 ± 66.84 μm in the A-CXL group (p = 0.275). No significant change in ECD was found in either group (all p>0.05). Mean changes in UDVA, CDVA, K-max, K-mean, HOAs, and ECD were not statistically significant between the groups (all p>0.05). Silicone hydrogel CL-assisted CXL seems as effective as A-CXL in halting keratoconus progression in thin corneas with no side effects during the one-year follow-up period.

On the influences of the continental shelf bathymetry correction in Prydz Bay, East Antarctica

The bathymetry around Antarctica can govern the shelf sea circulations and play a key role in conditioning water masses. In Prydz Bay, the Prydz Bay Gyre and coastal currents are also determined by the continental shelf topography. However, due to the paucity of beam echo sounding data, the bathymetric datasets in Prydz Bay still have large uncertainties. With the aid of in situ hydrographic observations, this study focuses on the correction of an up-to-date bathymetric dataset and the resultant influences on the shelf circulation and the basal melting of the ice shelves. The corrected bathymetry mainly improves the biased shallow representations in the uncorrected bathymetric data set, with a maximum change of ~500 m deepening in the eastern flank of Prydz Bay. Sensitivity numerical experiments show that the bathymetric corrections in Prydz Bay have a significant impact on the circulation pattern and onshore warm water intrusions. In addition, the corrected bathymetry markedly decreases the heat transport towards the calving front of the Amery Ice Shelf. The onshore heat transport reduces by ~22.18% from ~5.23×1013 J s-1 to ~4.07×1013 J s-1 over the outer shelf. Over the inner shelf, the heat transport towards the Amery Ice Shelf reduces by ~18.15% from ~5.95×1013 J s-1 to ~4.87×1013 J s-1. Consequently, the temporally and spatially averaged basal melting rate of the Amery Ice Shelf reduces by ~13.04% from ~0.69 m yr-1 to ~0.60 m yr-1.

Evaluation of 18F-flutemetamol amyloid PET image analysis parameters on the effect of verubecestat on brain amlyoid load in Alzheimer's disease.

The BACE inhibitor verubecestat was previously found to reduce amyloid load as assessed by 18F-flutemetamol positron emission tomography (PET) composite cortical standard uptake value ratio (SUVr) in patients with mild-to-moderate Alzheimer's disease (AD) in a substudy of the EPOCH trial. Here, we report on additional analyses relevant to the EPOCH PET data, to help inform on the use of PET for assessing amlyloid load in AD clinical trials. The analyses addressed (1) identification of an optimal 18F-flutemetamol reference region, (2) determination of the threshold to characterize the magnitude of the longitudinal change, and (3) the impact of partial volume correction (PVC). Pons and subcortical white matter were evaluated as reference regions. The SUVr cutoffs and final reference region choice were determined using 162 18F-flutemetamol PET scans from the AIBL dataset. 18F-flutemetamol SUVrs were computed at baseline and at Week 78 in EPOCH participants who received verubecestat 12mg (n = 14), 40mg (n = 20), or placebo (n = 20). Drug effects on amyloid load were computed using either Meltzer (MZ), or symmetric geometric transfer matrix (SGTM) PVC and compared to uncorrected data. The optimal subcortical white matter and pons SUVr cutoffs were determined to be 0.69 and 0.62, respectively. The effect size to detect longitudinal change was higher for subcortical white matter (1.20) than pons (0.45). Hence, subcortical white matter was used as the reference region for the EPOCH PET substudy. In EPOCH, uncorrected baseline SUVr values correlated strongly with MZ PVC (r2 = 0.94) and SGTM PVC (r2 = 0.92) baseline SUVr values, and PVC did not provide improvement for evaluating treatment effects on amyloid load at Week 78. No change from baseline was observed in the placebo group at Week 78, whereas a 0.02 and a 0.04 decrease in SUVr were observed in the 12mg and 40mg arms, with the latter representing a 22% reduction in the amyloid load above the detection threshold. Treatment-related 18F-flutemetamol longitudinal changes in AD clinical trials can be quantified using a subcortical white matter reference region without PVC. clinicaltrials.gov NCT01739348.