Qualitative Accuracy Research Articles

Abstract 5692: Cross-platform detection and quantification of actionable mutations in cell-free DNA shows high concordance and correlation between next-generation sequencing and droplet digital PCR

Abstract Background: Non-invasive genotyping of cell-free DNA (cfDNA) provides physicians with the ability to identify genomic alterations, evaluate response to treatment, and uncover potential mechanisms of resistance. Here, we analyze the concordance of next-generation sequencing (NGS) and droplet digital PCR (ddPCR) in detecting and quantifying actionable mutations from cfDNA of lung, colorectal, and breast cancer patients. Methods: We studied a cohort of 221 advanced cancer cfDNA samples with completed Guardant360 digital sequencing results. Variant allele frequencies (% AFs) ranged from less than 0.2% to greater than 90% for common driver and resistance mutations. Blinded to plasma NGS results, we performed ddPCR using our validated assays for EGFR L858R, exon19 del, T790M (113 presumed lung cases); BRAF V600E, KRAS G12X (77 colorectal cases); ESR1 D538G, Y537C and PIK3CA H1047R (31 breast cases). Following unblinding, qualitative and quantitative accuracy were compared. Results: Qualitative results (Table 1) show a high concordance between NGS and ddPCR, with 98.3% (576/586) of all assays run being concordant. 9/22 of samples that had an AF below 0.4% were discordant, while only one sample above 0.4% AF was discordant. AFs calculated by NGS and ddPCR were strongly correlated by linear regression (R between 0.951 and 0.999). Notably, the slope of the ddPCR AF versus NGS AF graph for EGFR ex19del was 0.725, which improved to 0.95 with the adoption of an alternate calling method. Conclusions: This interlaboratory comparison of actionable mutations in cfDNA from lung, colorectal, and breast cancers by orthogonal genotyping platforms demonstrates a substantial concordance in detection and quantification between NGS and ddPCR. Our cross-platform study establishes the feasibility of standardization of qualitative and quantitative measurements of cfDNA-detected alterations. Table 1LungEGFR L858REGFR Ex19 delEGFR T790M(n=113)G360+G360-G360+G360-G360+G360-ddPCR+580510530ddPCR-055458456BreastESR1 Y537CESR1 D538GPIK3CA H1047R(n=31)G360+G360-G360+G360-G360+G360-ddPCR+1022020ddPCR-03009029ColorectalBRAF V600EKRAS G12X(n=78)G360+G360-G360+G360-ddPCR+220571ddPCR-055118 Citation Format: Bryan C. Ulrich, Rebecca J. Nagy, Justin I. Odegaard, Richard B. Lanman, Geoffrey R. Oxnard, Cloud P. Paweletz. Cross-platform detection and quantification of actionable mutations in cell-free DNA shows high concordance and correlation between next-generation sequencing and droplet digital PCR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5692. doi:10.1158/1538-7445.AM2017-5692

Consensus algorithm‐based approach to fundamental modeling of water pipe networks

Modeling the flow dynamics of leaks in water pipe networks is an extremely difficult problem due to the complex entangled network structure and hydraulic phenomenon. A mathematical model for leak dynamics in water pipe networks based on consensus algorithm and water hammer theory is proposed. The resulting model is a simple and linearly interconnected system even though the dynamics of water pipe networks has considerable complexity. The model is then validated using experimental data obtained from real pipe network. A comparative study demonstrates the proposed model can describe the real system with high qualitative and quantitative accuracy and it can be used to develop model‐based leak detection and location algorithm based on state estimation. To show applicability of the proposed model, we apply cooperative estimation to the developed model. The results demonstrate the consensus‐based pipe model can be potentially used for leak detection and location with state estimation. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3860–3870, 2017

Near Infrared Spectroscopy to Predict Oil Fatty Acid Content and the Kind of Research to Identify Oil Species

Research on the use of Near-infrared Spectroscopy for rapid predict oil fatty acid content, proposed a method based on fatty acid content to identify the oil species. Collect five kinds of 133 parts of edible oil data samples by Near-infrared spectroscopy. The original spectroscopy were pretreated by using standard normal variable variation and De-trending(SNV-DT), and using support vector machine regression (SVR) build quantitative models of fatty acids, using Support Vector Classification (SVC) to establish the type of oil qualitative model. Results show, Using palmitic acid, oleic acid, linoleic three kinds of fatty acids it is feasible. Three kinds of fatty acid quantitative model prediction set correlation coefficients were 95.0876%,99.8592% and 98.5951%. Quantitative - Qualitative model prediction accuracy rate of 100% set. Studies shows that Near-infrared spectroscopy can quickly predict oil fatty acid content, and discriminating oil species. This research has a strong practical and popularization value. In order to develop a kind of rapid method which predict fatty acid content and use it to identify the oil species to provide technical support.

Two strategies to engineer flexible loops for improved enzyme thermostability

Flexible sites are potential targets for engineering the stability of enzymes. Nevertheless, the success rate of the rigidifying flexible sites (RFS) strategy is still low due to a limited understanding of how to determine the best mutation candidates. In this study, two parallel strategies were applied to identify mutation candidates within the flexible loops of Escherichia coli transketolase (TK). The first was a “back to consensus mutations” approach, and the second was computational design based on ΔΔG calculations in Rosetta. Forty-nine single variants were generated and characterised experimentally. From these, three single-variants I189H, A282P, D143K were found to be more thermostable than wild-type TK. The combination of A282P with H192P, a variant constructed previously, resulted in the best all-round variant with a 3-fold improved half-life at 60 °C, 5-fold increased specific activity at 65 °C, 1.3-fold improved kcat and a Tm increased by 5 °C above that of wild type. Based on a statistical analysis of the stability changes for all variants, the qualitative prediction accuracy of the Rosetta program reached 65.3%. Both of the two strategies investigated were useful in guiding mutation candidates to flexible loops, and had the potential to be used for other enzymes.

Elastographic Evaluation of Indeterminate Breast Masses on Ultrasound.

Objective To evaluate the diagnostic accuracy of elastography for breast cancer identification in patients with indeterminate lesions on ultrasound. Methods This prospective, descriptive study included patients with indeterminate breast lesions in the ultrasound and with indication for percutaneous or surgical biopsy. The elastography was evaluated by qualitative analysis and by two methods for the semi quantitative analysis. Results We evaluated 125 female patients with 159 lesions, with a mean age of 47 years, and a range of 20-85 years. Ultrasound has shown to be a method with good sensitivity (98.1%), but with a lower specificity (40.6%). On the elastography qualitative analysis, the specificity and accuracy were of 80.2% and 81.8% respectively. The mean size of the lesions showed no difference in classification by elastography. For the semiquantitative elastography, the mean values ​​of the malignant lesions were statistically higher when compared with the subcutaneous tissue or the adjacent fibroglandular tissue. The analysis of the receiver operating characteristic (ROC) curves for these two semiquantitative methods showed that both are considered satisfactory, with an area under the curve above 0.75 and statistical significance (p < 0.0001). The best results were obtained when using the findings of combined conventional ultrasound and qualitative elastography, with 100% sensitivity and 63.2% specificity. Conclusions Elastography can be a useful complementary method, increasing the specificity and diagnostic accuracy of conventional ultrasound for the diagnosis of breast cancer in patients with indeterminate breast lesions.

Comparative of dynamic enhanced CT, MRI differential diagnosis of adrenal tumors

Objective To compare the clinical value of dynamic enhanced CT, MRI in differential diagnosis of adrenal tumors. Methods 62 patients with adrenal tumor by pathologically confirmed in our hospital were selected.All patients underwent unenhanced and dynamic enhanced CT, MRI examination.The qualitative and adrenal tumor localization diagnostic accuracy, the adrenal adenomas and non adenoma tumor clearance rate of the two methods were compared. Results The accuracy of enhanced CT positioning, qualitative examination were 96.77%, 90.57%, respectively, which were slightly higher than those of the MRI enhancement(91.94%, 86.79%), but the differences were not statistically significant (χ2=0.479, 0.376, all P>0.05).53 adrenal adenomas and 9 cases non-adenomas absolute and relative clearance rate clearance rate in enhanced CT 5 min delay time, the differences were statistically significant (t=2.962, 2.018, all P<0.05).53 cases adrenal adenomas and 9 cases non adenoma clearance of correction in the enhanced MRI delay 5min, respectively (33.41±20.17)%, (14.74±12.16)%, the difference was statistically significant (t=2.684, P<0.05). Conclusion Dynamic enhanced CT, MRI are good methods for differential diagnosis of adrenal tumors, two methods have location and qualitative diagnosis correct rate.So dynamic enhanced CT, MRI are reliable means of diagnosis of adrenal tumors. Key words: Tomography, computer; Magnetic resonance imaging; Image enhancement; Adrenal gland neoplasms

Stroke-Associated Pneumonia Risk Score: Validity in a French Stroke Unit

Stroke-associated pneumonia is a leading cause of in-hospital death and post-stroke outcome. Screening patients at high risk is one of the main challenges in acute stroke units. Several screening tests have been developed, but their feasibility and validity still remain unclear. The aim of our study was to evaluate the validity of four risk scores (Pneumonia score, A2DS2, ISAN score, and AIS-APS) in a population of ischemic stroke patients admitted in a French stroke unit. Consecutive ischemic stroke patients admitted to a stroke unit were retrospectively analyzed. Data that allowed to retrospectively calculate the different pneumonia risk scores were recorded. Sensitivity and specificity of each score were assessed for in-hospital stroke-associated pneumonia and mortality. The qualitative and quantitative accuracy and utility of each diagnostic screening test were assessed by measuring the Youden Index and the Clinical Utility Index. Complete data were available for only 1960 patients. Pneumonia was observed in 8.6% of patients. Sensitivity and specificity were, respectively, .583 and .907 for Pneumonia score, .744 and .796 for A2DS2, and .696 and .812 for ISAN score. Data were insufficient to test AIS-APS. Stroke-associated pneumonia risk scores had an excellent negative Clinical Utility Index (.77-.87) to screen for in-hospital risk of pneumonia after acute ischemic stroke. All scores might be useful and applied to screen stroke-associated pneumonia in stroke patients treated in French comprehensive stroke units.

QSAR Model of Unbound Brain-to-Plasma Partition Coefficient, Kp,uu,brain: Incorporating P-glycoprotein Efflux as a Variable.

We report development and prospective validation of a QSAR model of the unbound brain-to-plasma partition coefficient, Kp,uu,brain, based on the in-house data set of ∼1000 compounds. We discuss effects of experimental variability, explore the applicability of both regression and classification approaches, and evaluate a novel, model-within-a-model approach of including P-glycoprotein efflux prediction as an additional variable. When tested on an independent test set of 91 internal compounds, incorporation of P-glycoprotein efflux information significantly improves the model performance resulting in an R2 of 0.53, RMSE of 0.57, Spearman's Rho correlation coefficient of 0.73, and qualitative prediction accuracy of 0.8 (kappa = 0.6). In addition to improving the performance, one of the key advantages of this approach is the larger chemical space coverage provided indirectly through incorporation of the in vitro, higher throughput data set that is 4 times larger than the in vivo data set.

Development of a mathematical model and analytical solution of a coupled two-beam array with nonlinear tip forces for application to AFM

Utilising arrays of cantilevers has been identified as a method of increasing AFM sensitivity and throughput beyond the limitations of current non-contact AFM. In order to develop the technology, we investigate the change in eigenstates of arrays due to interactions that occur between cantilever tip and sample using a model of a base-coupled array of cantilevers with individual mass and stiffness properties influenced by a quadratic nonlinear force to represent tip–sample interactions. An analytical expression is developed for a coupled two-beam array utilising Multiple Scale Lindstedt–Poincare perturbation theory to assess how a selected parameter space alters the array dynamics. Experiments are carried out using a macroscale set-up to validate the developed model. We show that the model captures the eigenstates of the system with good qualitative accuracy and that the perturbation expansion performs well in both the weakly (far from surface) and strongly (near the pull-in point) nonlinear regimes. The results demonstrate that utilising changes in eigenstates due to force interactions could have significant benefits to non-contact AFM with regard to measurement sensitivity and speed.

Usefulness of combined use of contrast-enhanced ultrasound and TI-RADS classification for the differentiation of benign from malignant lesions of thyroid nodules

PurposeTo study the thyroid image reporting and data system (TI-RADS) classification and the contrast-enhanced ultrasound (CEUS) enhancement pattern of thyroid nodules, and to determine whether combined use of both methods is helpful in the diagnosis of thyroid nodules.MethodsA total of 319 thyroid nodules in 246 patients were assessed with TI-RADS, CEUS and a combination of both methods. The diagnostic performance of TI-RADS, CEUS and a combination of both methods was compared.ResultsThe accuracy in the diagnosis of thyroid nodules was 90.3 % for TI-RADS, 90.0 % for CEUS and 96.0 % for a combination of both methods respectively. A statistically significant difference was not observed in the diagnostic accuracy of CEUS and TI-RADS (P > 0.05). However, a significant difference was observed between a combination of both methods and either alone (P < 0.01). A combination of both methods showed high sensitivity, specificity and accuracy for TI-RADS classifications of 4a and 4b thyroid nodules compared with TI-RADS alone (P < 0.01) and a statistically significant difference was not observed for thyroid nodules classified as 2, 3, and 5 (P > 0.05).ConclusionsThe improved TI-RADS, when combined with CEUS, could significantly improve the diagnostic accuracy for thyroid nodules, especially for TI-RADS class-4 thyroid nodules.Key Points• TI-RADS can be used as the primary diagnostic standard for thyroid nodules• CEUS can be used as an important complement to TI-RADS• The improved TI-RADS can significantly improve the qualitative diagnostic accuracy

Solvation Structure and Concentration in Glyme-Based Sodium Electrolytes: A Combined Spectroscopic and Computational Study

The optimal salt concentration used in metal-ion energy storage devices has long focused heavily on 1 M electrolytes; however, recent evidence suggests taking a deeper look at electrolyte properties as a function of salt concentration. Toward that goal, the effect of concentration on solvation properties for a prototype sodium electrolyte is considered with potential applications for sodium-ion and sodium–air technologies. An empirical force field for sodium triflate in digylme, an electrolyte already in use with sodium–air systems, was developed from ab initio molecular dynamics simulations in conjunction with the variational force-matching method. Atomistic simulations of this electrolyte along with Fourier transform infrared (FTIR) experimental studies validate the qualitative accuracy of the model and demonstrate its transferability across different concentrations. The solvation structure and the extent of ion pairing effects in the electrolyte were considered for concentrations ranging from 0.25 to 2.0 M in the sodium salt. Ion pairing effects are seen even at dilute concentrations of 0.5 M in both simulations and experiments, with a transition from solvent-separated species to direct contact ion pairs as the concentration increased to 1.5 M. With further increase in the concentration, evidence for ion aggregation is also presented.

Detection and quantification of left-to-right shunting using transpulmonary ultrasound dilution (TPUD): a validation study in neonatal lambs.

We investigated the accuracy of left-to-right shunt detection using transpulmonary ultrasound dilution (TPUD) and compared the agreement between pulmonary over systemic blood flow (Qp/Qs) ratio measured by TPUD [Qp/Qs(tpud)] and ultrasonic flow probes [Qp/Qs(ufp)]. Seven newborn lambs under general anesthesia were connected to the TPUD monitor (COstatus™) after insertion of arterial and central venous catheters. A Gore-Tex® shunt, inserted between the descending aorta and left pulmonary artery, was intermittently opened and closed while cardiac output was varied by blood withdrawals. Flow probes were placed around the main pulmonary artery (Qufp) and the descending aorta proximal (Qpre) and distal (Qpost) to the shunt insertion. Qp/Qs(ufp) was calculated as (Qufp+Qpre-Qpost)/Qufp. Seventy-two paired measurement sessions were analyzed. Shunts were detected by TPUD with a positive predictive value of 86%, a negative predictive value of 100%, a sensitivity of 100% and a specificity of 83%. The Bland-Altman analysis comparing Qp/Qs(tpud) and Qp/Qs(ufp) showed an overall mean bias (SD) of 0.1 (0.3), limits of agreement (LOA) of ±0.6 and a percentage error of 34.8%. The qualitative diagnostic accuracy of TPUD for shunt detection is high. Modification of the algorithm seems required as shunt quantification by TPUD is accurate, but not yet very precise.

Using checklists and algorithms to improve qualitative exposure judgment accuracy

ABSTRACTMost exposure assessments are conducted without the aid of robust personal exposure data and are based instead on qualitative inputs such as education and experience, training, documentation on the process chemicals, tasks and equipment, and other information. Qualitative assessments determine whether there is any follow-up, and influence the type that occurs, such as quantitative sampling, worker training, and implementing exposure and risk management measures. Accurate qualitative exposure judgments ensure appropriate follow-up that in turn ensures appropriate exposure management. Studies suggest that qualitative judgment accuracy is low. A qualitative exposure assessment Checklist tool was developed to guide the application of a set of heuristics to aid decision making. Practicing hygienists (n = 39) and novice industrial hygienists (n = 8) were recruited for a study evaluating the influence of the Checklist on exposure judgment accuracy. Participants generated 85 pre-training judgments and 195 Checklist-guided judgments. Pre-training judgment accuracy was low (33%) and not statistically significantly different from random chance. A tendency for IHs to underestimate the true exposure was observed. Exposure judgment accuracy improved significantly (p <0.001) to 63% when aided by the Checklist. Qualitative judgments guided by the Checklist tool were categorically accurate or over-estimated the true exposure by one category 70% of the time. The overall magnitude of exposure judgment precision also improved following training. Fleiss’ κ, evaluating inter-rater agreement between novice assessors was fair to moderate (κ = 0.39). Cohen's weighted and unweighted κ were good to excellent for novice (0.77 and 0.80) and practicing IHs (0.73 and 0.89), respectively. Checklist judgment accuracy was similar to quantitative exposure judgment accuracy observed in studies of similar design using personal exposure measurements, suggesting that the tool could be useful in developing informed priors and further demonstrating its usefulness in producing accurate qualitative exposure judgments.

Evaluation of a New Motion-correction Algorithm Using On-rigid Registration in Respiratory-gated PET/CT Images of Liver Tumors.

The present study aimed to determine the qualitative and quantitative accuracy of the Q.Freeze algorithm in PET/CT images of liver tumors. A body phantom and hot spheres representing liver tumors contained 5.3 and 21.2 kBq/mL of a solution containing 18F radioactivity, respectively. The phantoms were moved in the superior-inferior direction at a motion displacement of 20 mm. Conventional respiratory-gated (RG) and Q.Freeze images were sorted into 6, 10, and 13 phase-groups. The SUVave was calculated from the background of the body phantom, and the SUVmax was determined from the hot spheres of the liver tumors. Three patients with four liver tumors were also clinically assessed by whole-body and RG PET. The RG and Q.Freeze images derived from the clinical study were also sorted into 6, 10 and 13 phase-groups. Liver signal-to-noise ratio (SNR) and SUVmax were determined from the RG and Q.Freeze clinical images. The SUVave of Q.Freeze images was the same as those derived from the body phantom using RG. The liver SNR improved with Q.Freeze, and the SUVsmax was not overestimated when Q.Freeze was applied in both the phantom and clinical studies. Q.Freeze did not degrade the liver SNR and SUVmax even though the phase number was larger. Q.Freeze delivered qualitative and quantitative motion correction than conventional RG imaging even in 10-phase groups.

Simple image intensity compensation (SIMIC) method prior to application of distortion correction algorithms in brain diffusion Tensor Magnetic Resonance Imaging: Validation test for two cost functions of distortion correction algorithms

The purpose of this study is to design a simple image intensity compensation SIMIC method prior to the application of a variety of cost functions for distortion correction in diffusion tensor imaging DTI. The synthetic dataset consists of each direction of diffusion weighted imaging DWI made by multiplication of nondiffusion weighted image b = 0 image and tensor matrices. We added the effects of patient motion and eddy current distortion using translation, rotation, scaling and shearing matrices. We calculated the b = 0 image of each direction from original DTI, inversely. A co-registration method was applied to the extracted b = 0 images of each direction based on the original b = 0 image and then, the transformation matrices were generated and the original DTI were transformed using this transformation matrix. For the DTI distortion correction, two kinds of cost functions, normalized mutual information NMI and normalized cross-correlation NCC, were used. Visual assessments and quantitative measurements were used to evaluate the results. When using the NMI as a cost function, the quantitative results showed no significant differences between NMI and NMI with SIMIC method. However, there are significant differences compared with using the NCC as a cost function. Our study showed cost function for image distortion correction with SIMIC method improved the results both quantitatively and in terms of qualitative accuracy. This method may be helpful for DTI analysis and helpful for increasing accuracy. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 328-33, 2015

Automated Carbon Dioxide Angiography for the Evaluation and Endovascular Treatment of Diabetic Patients With Critical Limb Ischemia

Purpose: To test the safety, efficacy, and diagnostic accuracy of automated carbon dioxide (CO2) angiography (ACDA) for the evaluation of diabetic patients with critical limb ischemia (CLI) and baseline renal insufficiency and compare ACDA with iodinated contrast medium (ICM) during endovascular treatment. Methods: From November 2014 to January 2015, 36 consecutive diabetic patients (mean age 74.8±5.8 years; 27 men) with stage ≥3 chronic kidney disease (CKD ≥3) and CLI underwent lower limb angiography with both CO2 and ICM followed by balloon angioplasty in a prospective single-center study. The primary outcome measure was the safety and efficacy of ACDA as the exclusive agent to guide angioplasty in this cohort. The secondary outcomes were the safety and diagnostic accuracy of ACDA injection as compared with ICM digital subtraction angiography (DSA) for invasive evaluation of these patients. Results: ACDA safely and effectively guided angioplasty in all patients without complications. Transcutaneous oxygen pressure improved from 11.8±6.3 to 58.4±7.6 mm Hg (p<0.001). There were no complications related to ACDA during diagnostic imaging and no significant changes in the estimated glomerular filtration rate from baseline to 24 hours (44.7±13.3 vs 47.0±0.8 mL/min/1.73 m2; nonsignificant). The diagnostic accuracy of CO2 was 89.8% (sensitivity 92.3%; specificity 75%; positive predictive value 95.5%; negative predictive value 63.1%). There was no statistically significant difference in the qualitative diagnostic accuracy between the media (p=0.197). Conclusion: ACDA is an accurate, safe, and effective technique that can be utilized to guide endovascular interventions in diabetics with CLI and baseline CKD ≥3. Larger multicenter randomized studies are needed to validate these results.

A Review on Motion Correction Methods in Pet/Ct Images for Detection of Cancer Cells

Summary Positron Emission Tomography (PET) is an important cancer imaging tool, both for diagnosing and staging, as well as offering predictive information based on response. PET is a nuclear medicine imaging technique which produces a three-dimensional image of functional processes in the body. While PET is commonly used to detect the tumors, especially in breast, colon, lung and for lymphoma, as well in the last decade it is verified as considerably more accurate than Computed Tomography (CT) in the distinction between benign and malignant lesions. PET is not only more accurate than conventional imaging for the assessment of therapy response, but also it is useful to detect some viable tumor cells after treatment. However, motion is a source of artifacts in the medical imaging and results in reducing the quantitative and qualitative accuracy of the image. In general during the procedure of PET scanning, a few types of motion can occur that should be corrected and compensated. Different body motions are classified as brain motion, cardiac motion and respiratory motion. In this study, some of the most important motion correction and compensation methods using PET imaging system are compared.

Joint estimation of motion and illumination change in a sequence of images

We present an algorithm that simultaneously computes optical flow and estimates illumination change from an image sequence in a unified framework. We propose an energy functional consisting of conventional optical flow energy based on Horn–Schunck method and an additional constraint that is designed to compensate for illumination changes. Any undesirable illumination change that occurs in the imaging procedure in a sequence while the optical flow is being computed is considered a nuisance factor. In contrast to the conventional optical flow algorithm based on Horn–Schunck functional, which assumes the brightness constancy constraint, our algorithm is shown to be robust with respect to temporal illumination changes in the computation of optical flows. An efficient conjugate gradient descent technique is used in the optimization procedure as a numerical scheme. The experimental results obtained from the Middlebury benchmark dataset demonstrate the robustness and the effectiveness of our algorithm. In addition, comparative analysis of our algorithm and Horn–Schunck algorithm is performed on the additional test dataset that is constructed by applying a variety of synthetic bias fields to the original image sequences in the Middlebury benchmark dataset in order to demonstrate that our algorithm outperforms the Horn–Schunck algorithm. The superior performance of the proposed method is observed in terms of both qualitative visualizations and quantitative accuracy errors when compared to Horn–Schunck optical flow algorithm that easily yields poor results in the presence of small illumination changes leading to violation of the brightness constancy constraint.

Spin-flip configuration interaction singles with exact spin-projection: Theory and applications to strongly correlated systems.

Spin-flip approaches capture static correlation with the same computational scaling as the ordinary single reference methods. Here, we extend spin-flip configuration interaction singles (SFCIS) by projecting out intrinsic spin-contamination to make it spin-complete, rather than by explicitly complementing it with spin-coupled configurations. We give a general formalism of spin-projection for SFCIS, applicable to any spin states. The proposed method is viewed as a natural unification of SFCIS and spin-projected CIS to achieve a better qualitative accuracy at a low computational cost. While our wave function ansatz is more compact than previously proposed spin-complete SF approaches, it successfully offers more general static correlation beyond biradicals without sacrificing good quantum numbers. It is also shown that our method is invariant with respect to open-shell orbital rotations, due to the uniqueness of spin-projection. We will report benchmark calculations to demonstrate its qualitative performance on strongly correlated systems, including conical intersections that appear both in ground-excited and excited-excited degeneracies.

O.12 - Determination of the influence of respiratory motion on the SUV accuracy in pulmonary lesions

Introduction and Aim: Respiratory motion results in reduction of qualitative and quantitative accuracy in PET imaging of the heart, muscles of the diaphragm, liver, spleen, pancreas and imaging of the lung area. It causes blurring of the images and thus a loss of sensitivity in lesion detection. The aim was to determine the importance of respiratory motion on SUV accuracy in pulmonary lesions through simulation of respiratory motion. Materials and Methods: The XCAT Phantom was used to assess the influence of breathing on SUV quantification in a human-like simulation model. Six spherical lesions were introduced into the lungs of the model, three in the left lung and three in the right lung. Activity concentrations assigned to the lesions were varied to create a range of different lesions: background ratios, thus creating a range of contrasts. The simulations were repeated for various lesion sizes. GATE software was used to performMonte Carlo simulations during breathing. True-, scattered-, randomand total coincidences were extracted from the simulated data and reconstructed using OPL-EM and corrected for attenuation. Results: The % trues-to-total coincidences generally followed a downward trend with a decrease in contrast. Scattered coincidences had a more significant contribution at low contrast and when the lesion was closer to the diaphragm. This was greater in 3D simulations than in 2D simulations. Random coincidences were relatively greater in the apical region than in the other lung regions, particularly at low contrast large lesions. This increased for 3D compared to 2D acquisitions. The fraction of true coincidences-to-total coincidences increased when the lesions became smaller, but the relative amount of scattered events also increased. Conclusion: Breathing plays a significant role when determining the SUV of pulmonary lesions after accounting for the size, location, and the amount of activity within the simulated lesions compared to the background activity.