Software Measurement Research Articles

Machine learning volumetry of ischemic brain lesions on CT after thrombectomy-prospective diagnostic accuracy study in ischemic stroke patients.

Ischemic lesion volume (ILV) is an important radiological predictor of functional outcome in patients with anterior circulation stroke. Our aim was to assess the agreement between automated ILV measurements on NCCT using the Brainomix software and manual ILV measurements on diffusion-weighted imaging (DWI). This was a prospective single-center observational study of patients with CT angiography (CTA) proven anterior circulation occlusion treated with endovascular thrombectomy (May 2018 to May 2019). NCCT ILV was measured automatically by the Brainomix software. DWI ILV was measured manually. The McNemar's test was used to test sensitivity and specificity. The Somer's delta was used to test the differences between concordant and discordant ASPECTS regions. The Bland-Altman plot was calculated to compare the differences between Brainomix and DWI ILVs. Forty-five patients were included. Median Brainomix ILV was 23ml (interquartile range [IQR], 15-39ml), and median DWI ILV was 11.5ml (IQR, 7-32ml) in the TICI 2b-3 group. In the TICI 0-2a, the NCCT ILV was 39ml (IQR, 18-62ml) and DWI ILV was 30 (IQR, 11-105ml). The DWI ILVs in patients with good clinical outcome (mRS 0-2) was significantly lower compared with patients with mRS ≥ 3 (10mL vs 59mL, p = 0.002). Similar trend was observed for Brainomix ILV measurements (21mL vs 39mL, p = 0.012). There was a high correlation and accuracy in the detection of follow-up ischemic changes in particular ASPECTS regions. NCCT ILV measured automatically by the Brainomix software might be considered a valuable radiological outcome measure.

Measuring Emotional Responses to Negative Commercials: A Comparison of Two Methods

We compare two alternative measures for assessing people’s emotional reactions to political stimuli: the traditional self-report measure and facial expression analysis. We recruited participants to take part in a study examining reactions to a set of negative political commercials aired during the 2018 elections. We compare people’s self-reporting of their emotional reactions to negative political advertisements with their expressed emotion, according to the facial expression analysis. We find the discriminant validity of the facial expression analysis is higher than the self-report measure. Second, the self-report and facial expression measures of emotion have little convergent validity: we fail to find a consistent and strong positive correlation between the self-report and facial software measures of the same emotion and the same political advertisement. Third, the facial software measure has better predictive validity than the self-report measure, generating better predictions for the three dependent variables examined: changes in political interest, changes in people’s confidence in elected officials, and people’s assessment of the tone of the senate campaign.

MP42-03 HUMAN VS MACHINE: COMPARISON OF MANUAL VERSUS AUTOMATED SOFTWARE CT MEASUREMENTS OF STONE PHANTOMS

You have accessJournal of UrologyImaging/Radiology: Uroradiology II (MP42)1 Apr 2020MP42-03 HUMAN VS MACHINE: COMPARISON OF MANUAL VERSUS AUTOMATED SOFTWARE CT MEASUREMENTS OF STONE PHANTOMS Andrew M. Harris, Morgan N. Cash, Leslie M. Peard*, Mohamed M. Issa, James T. Lee, Jason R. Bylund, Amul A. Bhalodi, and John R. Bell Andrew M. HarrisAndrew M. Harris More articles by this author , Morgan N. CashMorgan N. Cash More articles by this author , Leslie M. Peard*Leslie M. Peard* More articles by this author , Mohamed M. IssaMohamed M. Issa More articles by this author , James T. LeeJames T. Lee More articles by this author , Jason R. BylundJason R. Bylund More articles by this author , Amul A. BhalodiAmul A. Bhalodi More articles by this author , and John R. BellJohn R. Bell More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000891.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Given the significance of stone size management of urolithiasis, obtaining accurate and precise measurements is paramount. We compared software and manual stone length and volume measurements to actual measurements of stone phantoms. METHODS: Seventeen unique stone phantoms were created in a variety of shapes and sizes using BegoStone Plus. Stone length, width, and height were measured with electronic calipers. Stone volume was measured using volume of displacement in water. Stone phantoms were placed in saline and imaged with computed tomography (CT). The CT images were uploaded into post-processing software, which analyzed the stones for maximum length and volume. Two urologists assessed the imaged stones for length, width and height and were blinded to the software measurements. Stone volume was calculated using the ellipsoid formula 0.52 x length x width x height. RESULTS: The stone phantoms ranged in length from 5.5mm to 63mm with volumes of 40mm3 to 16,000mm3. The software had the closest approximation to the actual stone length with a median percent error of 6.2% (IQR 3.1%-9.4%). Readers 1 and 2 had median percent errors of 5.7% (IQR 3.7%-14.1%) and 7.8% (IQR 2.1%-17.2%) respectively. Reader 1 and 2 both differed from the software with median percent differences of 16% (IQR 8.6%-22.4%) and 17.1% (IQR 5.2%-28.4%). The readers had a median percent difference from each other of 4.1% (IQR 3%-6.6%). None of the length measurements by the software or the human readers differed significantly from the actual stone phantoms (P>0.610). The percent errors with regards to volume for the software, reader 1 and reader 2 compared to actual stone volume were 20% (IQR 14.2%-30%), 18% (IQR 5.2%-39.8%), 24.1% (IQR 10.2%-33.2%), respectively. Reader 1 and 2 differed from the software with median percent differences of 33.1% (IQR 21.7%-59.5%) and 26.3% (IQR 15%-48%), respectively. The readers had a median percent difference from each other of 17.3% (IQR 7.5%-32.5%). None of the measurements by the software or the human readers differed significantly from the actual stone phantom volume (P>0.697). CONCLUSIONS: Software measurements approximated the actual measurements for the stone phantoms while eliminating interobserver variability. Using post-processing software to measure urinary stones appears to be as accurate as human readers, but with greater precision. Source of Funding: None © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e603-e604 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andrew M. Harris More articles by this author Morgan N. Cash More articles by this author Leslie M. Peard* More articles by this author Mohamed M. Issa More articles by this author James T. Lee More articles by this author Jason R. Bylund More articles by this author Amul A. Bhalodi More articles by this author John R. Bell More articles by this author Expand All Advertisement PDF downloadLoading ...

Association of T-wave amplitude on electrocardiogram with left ventricular ejection fraction in children with dilated cardiomyopathy

To study the association of T-wave amplitude on electrocardiogram (ECG) with left ventricular ejection fraction (LVEF) in children with dilated cardiomyopathy. A retrospective analysis was performed for the clinical data of 44 children who were diagnosed with dilated cardiomyopathy from May 2009 to June 2018. According to LVEF, they were divided into two groups: LVEF ≥50% group (n=26) and LVEF <50% group (n=18). After treatment, 25 children were followed up for 3-42 months (mean 14±9 months). The Guangdong Zhongshan SR-1000A ECG Automatic Analyzer was used to obtain the 12-lead body surface ECG results in the supine position. T-wave amplitude on ECG was evaluated by software and manual measurement. Compared with the LVEF ≥50% group, the LVEF <50% group had a significant reduction in the T-wave amplitude in leads II, V4, V5 and V6 (P<0.05). The increased-LVEF group (an increase in LVEF > 5% after treatment) had a significant increase in the T-wave amplitude in leads aVR, V5, and V6 after treatment (P<0.05), while the unchanged-LVEF group (an increase in LVEF ≤ 5% after treatment) had a significant reduction in the T-wave amplitude in lead aVR after treatment (P<0.05). The receiver operating characteristic curve analysis showed that the T-wave amplitude in leads II, V4, V5 and V6 had a certain value in predicting LVEF <50% in children with dilated cardiomyopathy (P<0.05). A combination of T-wave amplitude of ≤0.20 mV in lead II, ≤0.40 mV in lead V4, and ≤0.30 mV in leads V5 and V6 had a sensitivity of 88.2% and specificity of 76.0% in the predication of LVEF <50% in children with dilated cardiomyopathy. T-wave amplitude on ECG can be used as the indexes for the evaluation of the left ventricular systolic function in children with dilated cardiomyopathy.

PSM 기반의 ISO 26262 개발 단계 별 기능 안전성 및 신뢰성 확보를 위한 측정지표 수립에 관한 연구

PSM 기반의 ISO 26262 개발 단계 별 기능 안전성 및 신뢰성 확보를 위한 측정지표 수립에 관한 연구

Estimation of dynamic SNP-heritability with Bayesian Gaussian process models

MotivationImproved DNA technology has made it practical to estimate single-nucleotide polymorphism (SNP)-heritability among distantly related individuals with unknown relationships. For growth- and development-related traits, it is meaningful to base SNP-heritability estimation on longitudinal data due to the time-dependency of the process. However, only few statistical methods have been developed so far for estimating dynamic SNP-heritability and quantifying its full uncertainty.ResultsWe introduce a completely tuning-free Bayesian Gaussian process (GP)-based approach for estimating dynamic variance components and heritability as their function. For parameter estimation, we use a modern Markov Chain Monte Carlo method which allows full uncertainty quantification. Several datasets are analysed and our results clearly illustrate that the 95% credible intervals of the proposed joint estimation method (which ‘borrows strength’ from adjacent time points) are significantly narrower than of a two-stage baseline method that first estimates the variance components at each time point independently and then performs smoothing. We compare the method with a random regression model using MTG2 and BLUPF90 software and quantitative measures indicate superior performance of our method. Results are presented for simulated and real data with up to 1000 time points. Finally, we demonstrate scalability of the proposed method for simulated data with tens of thousands of individuals.Availability and implementationThe C++ implementation dynBGP and simulated data are available in GitHub: https://github.com/aarjas/dynBGP. The programmes can be run in R. Real datasets are available in QTL archive: https://phenome.jax.org/centers/QTLA.Supplementary information Supplementary data are available at Bioinformatics online.

Investigation of predictability and influence factors of the achieved lenticule thickness in small incision lenticule extraction

BackgroundTo evaluate the differences between the predicted and achieved lenticule thickness (ΔLT) after small incision lenticule extraction (SMILE) surgery and investigate relationships between ΔLT and predicted lenticule thickness in SMILE.MethodsA total of 184 eyes from 184 consecutive patients who underwent SMILE were included in this prospective study. One eye for each patient was randomly selected and included for statistical analysis. To achieve emmetropia, nomogram adds 10% correction of spherical refractive. An ultrasound pachymetry measurement and Scheimpflug camera corneal topography were obtained before and at 3 months after SMILE. The achieved lenticule thickness was calculated by comparing the preoperative examinations with postoperative examinations using ultrasound pachymetry and Pentacam software measurements. The pupil center and corneal vertex were selected as the 2 locations for measurement calculation on Pentacam. Analysis of variance (ANOVA) was performed to compare mean pachymetry values using different instruments. Linear regression analyses were performed between the VisuMax readout lenticule thicknesses and the measured maximum corneal change, between ΔLT and predicted lenticule thickness.ResultsOn average, the achieved lenticule thickness measured with ultrasound pachymetry was 13.02 ± 8.87 μm thinner than the predicted lenticule thickness. The proportion of ΔLT in predicted values is 11.9% (ultrasound) and about 15% (Pentacam). Linear regression analysis showed significant relationships between the predicted and each achieved lenticule thickness. Each ΔLT was significantly related to predicted lenticule thickness (ultrasound: R2 = 0.242; pupil center from Pentacam: R2 = 0.230).ConclusionsAn overestimation of achieved lenticule thickness was evident in this study which may exclude eligible SMILE patient. Also, our results showed that 10% increase of spherical refractive correction in the nomogram is appropriate. Furthermore, clinicians should subtract 10% of the predicted lenticule thickness to calculate the residual corneal stroma bed thickness.

PERBEDAAN SIGNAL TO NOISE RATIO (SNR) ANTARA SEKUENS PDW_SPAIR (SPECTRAL ADIABATIC INVERSION RECOVERY) DENGAN SEKUENS PDW_FATSAT(FAT SATURATION) PADA PEMERIKSAAN MRI KNEE JOINT POTONGAN SAGITAL

Background : In some cases, an MRI exam have difficulty distinguishing fat and soft tissue around. Fat is often a source of problems in MRI, because fat around many anatomical structures, but not well constrained. Spair and Fatsat is a technique used to suppress the fat signal. Signal To Noise Ratio (SNR) is an influential factor in a lot of quality MRI image. This study aims to determine the difference in value SNR between sequences PDW_SPAIR and PDW_Fatsat MRI Knee Joint Pieces Sagittal.&#x0D; Method : This research is a quantitative study with an experimental approach. Data were collected from November to December 2016 at the Radiology Siloam Hospital Lippo Village. Data taken from the examination using MRI Knee Joint PDW_SPAIR sequences and PDW_Fatsat on 10 probandus. Data was analyzed using software measurement ROI (Region Of Interest) in the organs of articular cartilage, anterior cruciate ligament, posterior cruciate ligament and Meniscus. then calculated the value of SNR, SNR values ​​are tested with Shapiro Wilk normality test and showed normal distribution of data is then performed statistical tests using paired T test to determine whether or not there is a difference of the two sequences.&#x0D; Result : Research show that there are differences between the sequences PDW_SPAIR SNR with PDW_Fatsat MRI Knee joint with a p value of 0.000 (p &lt;0.05). When viewed from the mean value of the sequence PDW_SPAIR MRI Knee joint sagittal slice generate value SNR better than PDW_Fatsat sequences with a mean of 42.10 PDW_SPAIR and a mean value of 35.14 PDW_Fatsat.&#x0D; Conclusion: There is a difference Signal to Noise Ratio (SNR) between PDW_SPAIR (Spectral Adiabatic Inversion Recovery) sequence with PDW_Fatsat (Fat Saturation) sequence in examination of MRI Knee Joint Sagital Pieces with a significance level of p-value 0,000 (p&lt;0,05). PDW_SPAIR sequence is an optimal value for Signal to Noise Ratio (SNR)in examination of MRI Knee Joint sagital pieces

AutoCellRow (ACR) – A new tool for the automatic quantification of cell radial files in conifer images

Quantitative wood anatomy (QWA) is a growing field of dendrochronology that allows obtaining a large number of parameters as the number, size and spatial arrangement of cellular elements, elements that highlight the adjustments of trees to their environment. In this work, we presented the free/libre open-source software AutoCellRow (ACR), a ready-to-use tool for automatic QWA in conifers. The ACR analyzes radial files of cells on cross-sections views of tree rings and provides automatic measurements of different cell parameters (e.g., lumen radial diameter, double cell wall thickness and cell radial diameter) for each cell along the selected radial file. The ACR measurements are based on high performed image analysis of xylem cells. The accuracy of the software measurements was tested in cross-sections of five conifer species from a semi-arid area of southern Siberia, and compared with measurements obtained by a semiautomatic tool. Our results suggested high accuracy in the ACR cell traits measurements, facilitating and speeding the analysis of quantitative wood anatomy in conifers over radial files of cells.

Study of a linear actuator with a hybrid core using sensorless position control

In this paper, a study of a tubular linear actuator with a hybrid core is presented. Through a finite-element analysis software and force measurements, it is shown that, by using a hybrid core combining a permanent magnet and a ferromagnetic material, a higher force density can be achieved in relation of that achieved by using a ferromagnetic core alone. Also, by keeping the ferromagnetic part, the sensorless detection of the core position is possible. A simple position control strategy is proposed, using the inductance variation to indirectly detect the position of the core, in which the duty cycle of the PWM voltage is changed to compensate variations of position or load force. In order to experimentally test the linear motor with hybrid core and the proposed control strategy, a prototype and a control circuit were built. The experimental results clearly demonstrate the advantages and applicability of the hybrid core in linear actuators.

Literature review on Functional Requirements for Function Point Analysis in Mobile Game

Functional size measurement has been widely used as the effort prediction method for software project over the past decades. Despite the success in predicting the cost, time requirement, and staff resources utilizing the amount of functionality delivered by a system, the method still needs to be improved further especially in dealing with mobile application characteristics. In the domain of mobile game application, the functional features can be challenging to identify wholly due to various application platforms, diversity of game genre, and complex game scenario. This paper presents a literature review concerning the functional requirements of the mobile game. The review includes the process of defining the research question, search strategy, and selection of study. Fifty-three articles were found in the academic libraries, and only 30 relevant studies were selected for the review. This literature review aims to provide researchers and practitioners in software measurement and gaming technology with an overview of common functional characteristics in the mobile game, which can be integrated into the functional size measurement method.

Recovering Android Bad Smells from Android Applications

The demand for Android mobile software applications is continuously increasing with the evolution of technology and new enriching features to make the life of people easy and comfortable. The mobile-based software applications are frequently updated as compared to other web and desktop applications. Due to these frequent updating cycles, the developers sometimes make changes in a rush which leads to poor design choices known as antipatterns or code bad smells. Code bad smells degrade the performance of applications and make evolution difficult. The recovery of bad smells from mobile software applications is still at infancy but it is a very important research realm that requires the attention of researchers and practitioners. The results of recovery may be used for comprehension, maintenance, reengineering, evolution and refactoring of these applications. Most state-of-the-art approaches focused on the detection of code bad smells from object-oriented applications and they target only a few code smells. We present a novel approach supplemented with tool support to recover 25 Android code bad smells from Android-specific software applications. We evaluate our approach by performing experiments on 4 open source and 3 industrial Android-specific software applications and measure accuracy using standard metrics.

Oxford Cobbometer Versus Computer Assisted-Software for Measurement of Cobb Angle in Adolescent Idiopathic Scoliosis.

ObjectiveThe objective was to compare Cobb angle measurements performed using an Oxford Cobbmeter and digital computer software (Surgimap) in a series of 83 adolescent idiopathic scoliosis (AIS) patients. MethodsTwo independent observers measured the Cobb angles for 123 curves on 83 consecutive long radiographs of patients with AIS using both Oxford Cobbmeter and digital computer software (Surgimap). The measurements were repeated a week. Curves were classified according to the severity into mild, moderate, and severe. The results were statistically analyzed for intraobserver and interobserver reliability ResultsThe mean Cobb angle was 48.12° ± 19.75° (range, 10.54°–110.76°). Globally the results of curve measurements were comparable between and within both observers using both methods, with small mean differences. According to intraclass correlation coefficient, there was high inter- and intraobserver high agreement for both methods. All readings were > 0.9. There was a good interobserver (κ = 0.745, 0.693) and a very good interobserver agreement (κ = 0.810, 0.804) for both methods for curve classification. However, poor agreement was observed as regards to the measurement time, being less with Oxford Cobbometer. ConclusionThe results of this study indicate that the Surgimap digital computer software measurement is an equivalent measuring tool to the Oxford Cobbmeter in Cobb angle measurement. Both have high intra and interobserver agreement for measurement and for curve classification, with small measurement differences. Oxford Cobbmeter is advantageous in being quicker, and therefore it is the method of choice for manual measurement, where PACS (patient archiving and communication system) or digital system is not available.

Radiological measurement of pelvic fractures using a pelvic deformity measurement software program

BackgroundIt is difficult for the surgeon to measure pelvic displacement in the closed reduction operation for unstable pelvic fracture. We therefore developed a pelvic deformity measurement software program based on standardized radiographs. The objectives of the present study were to evaluate the inter-observer reliability of the program for measuring specific fracture types on preoperative pelvic films and to assess the validity of the measurement software program by comparing it with a gold standard.MethodsTwenty-five patients diagnosed with AO/OTA type B or C pelvic fractures with the unilateral pelvis fractured and dislocated were included in this study. Four separate observers repeatedly determined the translational and rotational patterns and outcomes using the software program and hand measurement, and calculated the displacement using computed tomography (CT) coupled with a three-dimensional (3D) CT model. The validity of the measurement software was calculated by assessing the consistency between the software measurements and the gold standard. Additionally, inter-observer reliability was assessed for the software. The software was also applied in preliminary clinical practice for closed reduction procedures.ResultsThe overall inter-observer reliabilities of the software program, CT coupled with 3D reconstruction, and hand measurements were high, with kappa values of 0.956, 0.958, and 0.853, respectively. The software showed validity similar to that of CT coupled with 3D reconstruction (0.939 vs. 0.969), and better than that of hand measurement (0.939 vs. 0.858). A preliminary clinical application demonstrated that the software is effective for guiding closed reduction of pelvic fractures.ConclusionsOur newly established pelvic deformity measurement program is a reliable and accurate tool for analyzing pelvic displacement patterns and can be used for guidance of closed reduction and planning of the reduction pathway.Level of evidenceIII

Makine Öğrenmesi ve Biyoenformatik Uygulamalarının Yüksek Başarımlı Hesaplama Sistemlerindeki Performans Analizi

Nowadays, it is becoming increasingly important to use the most efficient and most suitable computational resources for algorithmic tools that extract meaningful information from big data and make smart decisions. In this paper, a comparative analysis is provided for performance measurements of various machine learning and bioinformatics software including scikit-learn, Tensorflow, WEKA, libSVM, ThunderSVM, GMTK, PSI-BLAST, and HHblits with big data applications on different high performance computer systems and workstations. The programs are executed in a wide range of conditions such as single-core central processing unit (CPU), multi-core CPU, and graphical processing unit (GPU) depending on the availability of implementation. The optimum number of CPU cores are obtained for selected software. It is found that the running times depend on many factors including the CPU/GPU version, available RAM, the number of CPU cores allocated, and the algorithm used. If parallel implementations are available for a given software, the best running times are typically obtained by GPU, followed by multi-core CPU, and single-core CPU. Though there is no best system that performs better than others in all applications studied, it is anticipated that the results obtained will help researchers and practitioners to select the most appropriate computational resources for their machine learning and bioinformatics projects.

DXOMARK Objective Video Quality Measurements

Video capture is becoming more and more widespread. The technical advances of consumer devices have led to improved video quality and to a variety of new use cases presented by social media and artificial intelligence applications. Device manufacturers and users alike need to be able to compare different cameras. These devices may be smartphones, automotive components, surveillance equipment, DSLRs, drones, action cameras, etc. While quality standards and measurement protocols exist for still images, there is still a need of measurement protocols for video quality. These need to include parts that are non-trivially adapted from photo protocols, particularly concerning the temporal aspects. This article presents a comprehensive hardware and software measurement protocol for the objective evaluation of the whole video acquisition and encoding pipeline, as well as its experimental validation.

Assessing Risk Among Correctional Community Probation Populations: Predicting Reoffense With Mobile Neurocognitive Assessment Software.

We seek to address current limitations of forensic risk assessments by introducing the first mobile, self-scoring, risk assessment software that relies on neurocognitive testing to predict reoffense. This assessment, run entirely on a tablet, measures decision-making via a suite of neurocognitive tests in less than 30 minutes. The software measures several cognitive and decision-making traits of the user, including impulsivity, empathy, aggression, and several other traits linked to reoffending. Our analysis measured whether this assessment successfully predicted recidivism by testing probationers in a large urban city (Houston, TX, United States) from 2017 to 2019. To determine predictive validity, we used machine learning to yield cross-validated receiver–operator characteristics. Results gave a recidivism prediction value of 0.70, making it comparable to commonly used risk assessments. This novel approach diverges from traditional self-reporting, interview-based, and criminal-records-based approaches, and can also add a protective layer against bias, while strengthening model accuracy in predicting reoffense. In addition, subjectivity is eliminated and time-consuming administrative efforts are reduced. With continued data collection, this approach opens the possibility of identifying different levels of recidivism risk, by crime type, for any age, or gender, and seeks to steer individuals appropriately toward rehabilitative programs. Suggestions for future research directions are provided.

P755 Aortic valve area calculation by 3D transesophageal echocardiography: new insights in severity grading of aortic stenosis

Abstract Background Aortic stenosis (AS) grading is mainly based on aortic valve area (AVA) calculation by 2D transthoracic echocardiography (2D-TTE), using continuity equation (CE). However, 2D-TTE shows several limits, mainly due to left ventricular outflow tract (LOVT) underestimation. Different 3D imaging modalities have been proposed to overcome 2D-TTE limitations, including 3D transesophageal echocardiography manual and software measurements (3D-TEEm and 3D-TEEs) and multidetector computed tomography (MDCT). The AVA cut-off value generally used to define severe AS has been established and validated by outcome studies in which AVA was measured by 2D-TTE. This cut-off value cannot be directly extrapolated to the 3D-TEE combined approach that systematically measures larger LVOT compared with 2D-TTE. Purpose.To evaluate the diagnostic accuracy of 3D transesophageal echocardiography manual and software measurements (3D-TEEm and 3D-TEEs) in AS grading, compared with multidetector computed tomography (MDCT) as gold standard, and to identify a new cut-off for AS severity assessment. Methods 218 patients (81 ± 5.4 years, 54% male) with symptomatic normal-flow AS underwent 2D-TTE, 3D-TTEm, 3D-TEEs and MDCT within the same hospitalization. 3D-TEE LVOT reconstruction was performed manually and with semi-automated software (EchoPAC version 201). 3D-TEEm, 3D-TEEs and MDCT LVOT areas were combined with 2D-TTE Doppler parameters to calculate AVA by CE. Using Doppler parameters (Vmax &amp;gt;4 m/s and MPG &amp;gt;40 mmHg) to define AS severity, a receiving-operating curve (ROC) was calculated for AVA obtained with different 3D imaging modalities. Results There was a good correlation between both 3D-TEEm and 3D-TEEs and MDCT measurements (r = 0.800 and r = 0.814, respectively) and excellent agreement between 3D-TEEm and 3D-TEEs with minimum bias. 2D-TTE significantly underestimated AVA compared to 3D-TEEm, 3D-TEEs and MDCT. On the other hand, both 3D-TEEm and 3D-TEEs underestimated AVA compared to MDCT (mean AVA difference = 0.13 and =0.06 cm2, respectively). ROC curve analysis demonstrated 91% sensibility and 34% specificity for 2D-TTE AVA using a cut-off of 1 cm2 (AUC 0.732). For 3D-TEEm and 3D-TEEs, a 1 cm2cut-off resulted in 74% sensibility and 59% specificity, while a 1.2 cm2cut-off resulted in 91% sensibility and 31% specificity (AUC 0.715). MDCT showed 59% sensibility and 70% specificity using a 1 cm2 cut-off and 83% sensibility and 45% specificity using a 1.2 cm2 cut-off (AUC 0.708). Conclusion 3D-TEE represents a valuable tool for AS grading using a combined approach incorporating 3D LVOT measurements and 2D Doppler parameters in the CE. Both 3D-TEEm and 3D-TEEs AVA measurements demonstrated good correlation with MDCT and excellent reproducibility. 3D-TEE measurements underestimate AVA compared to MDCT. Given the multiparametric assessment of AS severity, a 1.2 cm2 AVA cut-off could be considered to define AS severity with emerging 3D imaging modalities.

P300 Reappraisal of aortic stenosis severity grading inconsistencies using 3D aortic valve area

Abstract Funding Acknowledgements no fundings Background Different 3D imaging modalities have been proposed to overcome the limitations in aortic stenosis (AS) grading derived from underestimation of left ventricular outflow tract (LVOT) area by 2D transthoracic echocardiography (2D-TTE). Transesophageal echocardiography manual and software measurements (3D-TEEm and 3D-TEEs) and multidetector computed tomography (MDCT) have been recently been shown as valuable tools for AS grading using a combined approach incorporating 3D LVOT measurements and 2D Doppler parameters in the continuity equation (CE). This approach results particularly useful in cases of 2D-TTE grading inconsistence. As all these 3D imaging modalities provide larger AVA compared to 2D-TTE, we have recently proposed a 1.2 cm2 AVA cut-off could to define AS severity with 3D-TEE and MDCT. Purpose To compare AVA measurements with 3D-TEEm and 3D-TEEs using MDCT as gold standard in order to assess inconsistencies and evaluate the impact of a 1.2 cm2 AVA cut-off on AS severity grading. Methods 288 patients (80 ± 11 years, 52.4% male) with symptomatic AS underwent 2D-TTE, 3D-TTEm, 3D-TEEs and MDCT within the same hospitalization. 3D-TEE LVOT reconstruction was performed manually and with semi-automated software (EchoPAC version 201). 3D-TEEm, 3D-TEEs and MDCT LVOT areas were combined with 2D-TTE Doppler parameters to calculate AVA by CE. The grading of AS was reassessed in patients with low flow-low gradient AS using a 1.2 cm2 cut-off for severity. Results Patients were classified according to flow state (stroke volume index ≥35 ml/m2 or &amp;lt;35 ml/m2) and mean pressure gradient (MPG ≥40 mmHg or &amp;lt;40 mmHg) into 4 groups: normal flow-high gradient (NF-HG; n 173, 60%), normal flow-low gradient (NF-LG; n 45, 15.5%), low flow-high gradient (LF-HG; n 39, 13.5%), and low flow-low gradient (LF-LG; n 31, 11%) AS. Among patients classified as LF-LG AS, 95%, 55%, 29% and 55% of cases were classified as severe by 2D-TTE, 3D-TEEm, 3D-TEEs and MDCT respectively using a 1.0 cm2 AVA cut-off. When the proposed severity AVA cut-off of 1.2 cm2 was applied using 3D imaging modalities, the proportion of severe AS significantly increased to 84% (p = 0.012) (3D-TEEm), 52% (p = 0.046) (3D-TEEs) and 71% (p &amp;lt; 0.001) (MDCT) respectively. Conclusion The use of a 1.2 cm2 AVA cut-off for 3D-TEE and MDCT significantly reduces the number of cases of inconsistently graded AS, increasing the proportion of patients with severe AS.

Leaf area estimation of Anacardium humile

Abstract The Anacardium humile A. St.- Hil. fruit tree has productive potential, being their fruits appreciated in the Cerrado region for having characteristic flavor, however, this species is still exploited in an extractive way, being necessary studies for its domestication. The aim of this work was to estimate the leaf area of Anacardium humile. One hundred leaves were collected in the biological collection from a genetic resources field and evaluated for length, width and fresh weight, and scanned at resolution of 300 dpi to determine the leaf area with the aid of the ImageJ image analysis program. Subsequently, a leaf disc with a diameter of 22.27 mm was detached at the basal portion of each leaf, in which the fresh weight of the discs was obtained. Data were submitted to descriptive analysis and the relationship among the features explained by Pearson’s correlation with the software Rbio. The data were also subjected to regression analysis to explain the relationship between leaf area and measurements of width, length and leaf weight, and to fit the proper statistical model with the software Origin. It was concluded that leaf area can be determined by image analysis software and linear measurements are correlated to leaf area.