937 resultados para Receiver operating characteristics curves (ROC)


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Dose reduction in digital panoramic radiography was studied. Intentional underexposure was performed with the Orthophos DS while six different human mandibles were radiographed. Exposure settings were 69 kV/15 mA (standard), 64 kV/16 mA, and 60 kV/16 mA. Standardized spherical defects, each either 1 or 1.25 mm in diameter, were simulated in 288 of 432 images, and seven observers decided whether defects were present or not. Areas under the receiver operating characteristics curves were calculated. They showed no significant differences in the detectability of the 1-mm defect at 69, 64, or 60 kV. For the 1.25-mm defect, no difference was found between the 69 and 60 kV images, but a statistically significant different detectability was found for 64 kV images in comparison with both 69 and 60 kV images. A dose reduction of up to 43% was ascertained with a Pedo-RT-Humanoid phantom when panoramic radiography was performed at 60 kV/16 mA. The conclusion is that with the Orthophos DS, it seems possible to reduce the dose rate of x-rays without loss of diagnostic quality in the case of radiolucent changes.

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OBJECTIVE The objective of this study was to assess the discriminative power of dual-energy computed tomography (DECT) versus single-energy CT (SECT) to distinguish between ferromagnetic and non-ferromagnetic ballistic projectiles to improve safety regarding magnetic resonance (MR) imaging studies in patients with retained projectiles. MATERIALS AND METHODS Twenty-seven ballistic projectiles including 25 bullets (diameter, 3-15 mm) and 2 shotgun pellets (2 mm each) were examined in an anthropomorphic chest phantom using 128-section dual-source CT. Data acquisition was performed with tube voltages set at 80, 100, 120, and 140 kV(p). Two readers independently assessed CT numbers of the projectile's core on images reconstructed with an extended CT scale. Dual-energy indices (DEIs) were calculated from both 80-/140-kV(p) and 100-/140-kV(p) pairs; receiver operating characteristics curves were fitted to assess ferromagnetic properties by means of CT numbers and DEI. RESULTS Nine (33%) of the projectiles were ferromagnetic; 18 were nonferromagnetic (67%). Interreader and intrareader correlations of CT number measurements were excellent (intraclass correlation coefficients, >0.906; P<0.001). The DEI calculated from both 80/140 and 100/140 kV(p) were significantly (P<0.05) different between the ferromagnetic and non-ferromagnetic projectiles. The area under the curve (AUC) was 0.75 and 0.8 for the tube voltage pairs of 80/140 and 100/140 kV(p) (P<0.05; 95% confidence interval, 0.57-0.94 and 0.62-0.97, respectively) to differentiate between the ferromagnetic and non-ferromagnetic ballistic projectiles; which increased to 0.83 and 0.85 when shotgun pellets were excluded from the analysis. The AUC for SECT was 0.69 and 0.73 (80 and 100 kV[p], respectively). CONCLUSIONS Measurements of DECT combined with an extended CT scale allow for the discrimination of projectiles with non-ferromagnetic from those with ferromagnetic properties in an anthropomorphic chest phantom with a higher AUC compared with SECT. This study indicates that DECT may have the potential to contribute to MR safety and allow for MR imaging of patients with retained projectiles. However, further studies are necessary before this concept may be used to triage clinical patients before MR.

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The main objective of this study was to determine the external validity of a clinical prediction rule developed by the European Multicenter Study on Human Spinal Cord Injury (EM-SCI) to predict the ambulation outcomes 12 months after traumatic spinal cord injury. Data from the North American Clinical Trials Network (NACTN) data registry with approximately 500 SCI cases were used for this validity study. The predictive accuracy of the EM-SCI prognostic model was evaluated using calibration and discrimination based on 231 NACTN cases. The area under the receiver-operating-characteristics curve (ROC) curve was 0.927 (95% CI 0.894 – 0.959) for the EM-SCI model when applied to NACTN population. This is lower than the AUC of 0.956 (95% CI 0.936 – 0.976) reported for the EM-SCI population, but suggests that the EM-SCI clinical prediction rule distinguished well between those patients in the NACTN population who were able to achieve independent ambulation and those who did not achieve independent ambulation. The calibration curve suggests that higher the prediction score is, the better the probability of walking with the best prediction for AIS D patients. In conclusion, the EM-SCI clinical prediction rule was determined to be generalizable to the adult NACTN SCI population.^

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Background: The use of sagittal abdominal diameter (SAD) has been proposed for screening cardio-metabolic risk factors; however, its accuracy can be influenced by the choice of thresholds values. Aim: To determine the SAD threshold values for cardio-metabolic risk factors in Mexican adults; to assess whether parallel and serial SAD testing can improve waist circumference (WC) sensitivity and specificity; and to analyze the effect of considering SAD along with WC and body mass index (BMI) in detecting cardio-metabolic risk. Methods: This cross-sectional study was conducted during 2012-2014 in Northeast Mexico (n = 269). Data on anthropometric, clinical, and biochemical measurements were collected. Sex-adjusted receiver-operating characteristic curves (ROC) were obtained using hypertension, dysglycemia, dyslipidemia and insulin resistance as individual outcomes and metabolic syndrome as a composite outcome. Age-adjusted odds ratios and 95% confidence intervals (CI) were estimated using logistic regression. Results: The threshold value for SAD with acceptable combination of sensitivity and specificity was 24.6 cm in men and 22.5 cm in women. Parallel SAD testing improved WC sensitivity and serial testing improved WC specificity. The co-occurrence of high WC/high SAD increased the risk for insulin resistance by 2.4-fold (95% CI: 1.1-5.3), high BMI/high SAD by 4.3-fold (95% CI: 1.7-11.9) and SAD alone by 2.2-fold (95% CI: 1.2.-4.2). Conclusions: The use of SAD together with traditional obesity indices such as WC and BMI has advantages over using either of these indices alone. SAD may be a powerful screening tool for interventions for high-risk individuals.

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Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.

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Abstract Objective: To assess the cutoff values established by ROC curves to classify18F-NaF uptake as normal or malignant. Materials and Methods: PET/CT images were acquired 1 hour after administration of 185 MBq of18F-NaF. Volumes of interest (VOIs) were drawn on three regions of the skeleton as follows: proximal right humerus diaphysis (HD), proximal right femoral diaphysis (FD) and first vertebral body (VB1), in a total of 254 patients, totalling 762 VOIs. The uptake in the VOIs was classified as normal or malignant on the basis of the radiopharmaceutical distribution pattern and of the CT images. A total of 675 volumes were classified as normal and 52 were classified as malignant. Thirty-five VOIs classified as indeterminate or nonmalignant lesions were excluded from analysis. The standardized uptake value (SUV) measured on the VOIs were plotted on an ROC curve for each one of the three regions. The area under the ROC (AUC) as well as the best cutoff SUVs to classify the VOIs were calculated. The best cutoff values were established as the ones with higher result of the sum of sensitivity and specificity. Results: The AUCs were 0.933, 0.889 and 0.975 for UD, FD and VB1, respectively. The best SUV cutoffs were 9.0 (sensitivity: 73%; specificity: 99%), 8.4 (sensitivity: 79%; specificity: 94%) and 21.0 (sensitivity: 93%; specificity: 95%) for UD, FD and VB1, respectively. Conclusion: The best cutoff value varies according to bone region of analysis and it is not possible to establish one value for the whole body.

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Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this paper, we consider the case of imprecise environments, where little may be known about these factors and they may well vary significantly when the system is applied. Specifically, the use of precision-recall analysis is investigated and compared to the more well known performance measures such as error-rate and the receiver operating characteristic (ROC). We argue that while ROC analysis is invariant to variations in class priors, this invariance in fact hides an important factor of the evaluation in imprecise environments. Therefore, we develop a generalised precision-recall analysis methodology in which variation due to prior class probabilities is incorporated into a multi-way analysis of variance (ANOVA). The increased sensitivity and reliability of this approach is demonstrated in a remote sensing application.

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On the basis of convolutional (Hamming) version of recent Neural Network Assembly Memory Model (NNAMM) for intact two-layer autoassociative Hopfield network optimal receiver operating characteristics (ROCs) have been derived analytically. A method of taking into account explicitly a priori probabilities of alternative hypotheses on the structure of information initiating memory trace retrieval and modified ROCs (mROCs, a posteriori probabilities of correct recall vs. false alarm probability) are introduced. The comparison of empirical and calculated ROCs (or mROCs) demonstrates that they coincide quantitatively and in this way intensities of cues used in appropriate experiments may be estimated. It has been found that basic ROC properties which are one of experimental findings underpinning dual-process models of recognition memory can be explained within our one-factor NNAMM.

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Purpose - The study evaluates the pre- and post-training lesion localisation ability of a group of novice observers. Parallels are drawn with the performance of inexperienced radiographers taking part in preliminary clinical evaluation (PCE) and ‘red-dot’ systems, operating within radiography practice. Materials and methods - Thirty-four novice observers searched 92 images for simulated lesions. Pre-training and post-training evaluations were completed following the free-response the receiver operating characteristic (FROC) method. Training consisted of observer performance methodology, the characteristics of the simulated lesions and information on lesion frequency. Jackknife alternative FROC (JAFROC) and highest rating inferred ROC analyses were performed to evaluate performance difference on lesion-based and case-based decisions. The significance level of the test was set at 0.05 to control the probability of Type I error. Results - JAFROC analysis (F(3,33) = 26.34, p < 0.0001) and highest-rating inferred ROC analysis (F(3,33) = 10.65, p = 0.0026) revealed a statistically significant difference in lesion detection performance. The JAFROC figure-of-merit was 0.563 (95% CI 0.512,0.614) pre-training and 0.677 (95% CI 0.639,0.715) post-training. Highest rating inferred ROC figure-of-merit was 0.728 (95% CI 0.701,0.755) pre-training and 0.772 (95% CI 0.750,0.793) post-training. Conclusions - This study has demonstrated that novice observer performance can improve significantly. This study design may have relevance in the assessment of inexperienced radiographers taking part in PCE or commenting scheme for trauma.

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Dissertação de mestrado em Bioinformática

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Objectif: Évaluer l'efficacité du dépistage de l’hypertension gestationnelle par les caractéristiques démographiques maternelles, les biomarqueurs sériques et le Doppler de l'artère utérine au premier et au deuxième trimestre de grossesse. Élaborer des modèles prédictifs de l’hypertension gestationnelle fondées sur ces paramètres. Methods: Il s'agit d'une étude prospective de cohorte incluant 598 femmes nullipares. Le Doppler utérin a été étudié par échographie transabdominale entre 11 +0 à 13 +6 semaines (1er trimestre) et entre 17 +0 à 21 +6 semaines (2e trimestre). Tous les échantillons de sérum pour la mesure de plusieurs biomarqueurs placentaires ont été recueillis au 1er trimestre. Les caractéristiques démographiques maternelles ont été enregistrées en même temps. Des courbes ROC et les valeurs prédictives ont été utilisés pour analyser la puissance prédictive des paramètres ci-dessus. Différentes combinaisons et leurs modèles de régression logistique ont été également analysés. Résultats: Parmi 598 femmes, on a observé 20 pré-éclampsies (3,3%), 7 pré-éclampsies précoces (1,2%), 52 cas d’hypertension gestationnelle (8,7%) , 10 cas d’hypertension gestationnelle avant 37 semaines (1,7%). L’index de pulsatilité des artères utérines au 2e trimestre est le meilleur prédicteur. En analyse de régression logistique multivariée, la meilleure valeur prédictive au 1er et au 2e trimestre a été obtenue pour la prévision de la pré-éclampsie précoce. Le dépistage combiné a montré des résultats nettement meilleurs comparés avec les paramètres maternels ou Doppler seuls. Conclusion: Comme seul marqueur, le Doppler utérin du deuxième trimestre a la meilleure prédictive pour l'hypertension, la naissance prématurée et la restriction de croissance. La combinaison des caractéristiques démographiques maternelles, des biomarqueurs sériques maternels et du Doppler utérin améliore l'efficacité du dépistage, en particulier pour la pré-éclampsie nécessitant un accouchement prématuré.

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Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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[EN] OBJECTIVES: To assess the usefulness of clinical findings, nerve conduction studies and ultrasonography performed by a rheumatologist to predict success in patients with idiopathic carpal tunnel syndrome (CTS) undergoing median nerve release. METHODS: Ninety consecutive patients with CTS (112 wrists) completed a specific CTS questionnaire and underwent physical examination and nerve conduction studies. Ultrasound examination was performed by a rheumatologist who was blind to any patient's data. Outcome variables were improvement >25% in symptoms of the CTS questionnaire and patient's overall satisfaction (5-point Likert scale) at 3 months postoperatively. Success was defined as improvement in both outcome variables. Receiver operating characteristics (ROC) curves and logistic regression analyses were used to assess the best predictive combination of preoperative findings. RESULTS: Success was achieved in 63% of the operated wrists. Utility parameters and area under the ROC curve (AUC) for individual findings was poor, ranging from 0.481 of the nerve conduction study to 0.634 of the cross-sectional area at tunnel outlet. Logistic regression identified the preoperative US parameters as the best predictive variables for success after 3 months. The best predictive combination (AUC=0.708) included a negative Phalen maneuver, plus absence of thenar atrophy, plus less than moderately abnormalities on nerve conduction studies plus a large maximal cross-sectional area along the tunnel by ultrasonography. CONCLUSION: Although cross-sectional area of the median nerve was the only predictor of success after three months of surgical release, isolated preoperative findings are not reliable predictors of success in patients with idiopathic CTS. A combination of findings that include ultrasound improves prediction.

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Critically ill and injured patients require pain relief and sedation to reduce the body's stress response and to facilitate painful diagnostic and therapeutic procedures. Presently, the level of sedation and analgesia is guided by the use of clinical scores which can be unreliable. There is therefore, a need for an objective measure of sedation and analgesia. The Bispectral Index (BIS) and Patient State Index (PSI) were recently introduced into clinical practice as objective measures of the depth of analgesia and sedation. ^ Aim. To compare the different measures of sedation and analgesia (BIS and PSI) to the standard and commonly used modified Ramsay Score (MRS) and determine if the monitors can be used interchangeably. ^ Methods. MRS, BIS and PSI values were obtained in 50 postoperative cardiac surgery patients requiring analgesia and sedation from June to December 2004. The MRS, BIS and PSI values were assessed hourly for up to 6-h by a single observer. ^ The relationship between BIS and PSI values were explored using scatter plots and correlation between MRS, BIS and PSI was determined using Spearman's correlation coefficient. Intra-class correlation (ICC) was used to determine the inter-rater reliability of MRS, BIS and PSI. Kappa statistics was used to further evaluate the agreement between BIS and PSI at light, moderate and deep levels of sedation. ^ Results. There was a positive correlation between BIS and PSI values (Rho = 0.731, p<0.001). Intra-class correlation between BIS and PSI was 0.58, MRS and BIS 0.43 and MRS and PSI 0.27. Using Kappa statistics, agreement between MRS and BIS was 0.35 (95% CI: 0.27–0.43) and for MRS and PSI was 0.21 (95% CI: 0.15–0.28). The kappa statistic for BIS and PSI was 0.45 (95% CI: 0.37–0.52). Receiver operating characteristics (ROC) curves constructed to detect undersedation indicated an area under the curve (AUC) of 0.91 (95% CI = 0.87 to 0.94) for the BIS and 0.84 (95% CI = 0.79 to 0.88) for the PSI. For detection of oversedation, AUC for the BIS was 0.89 (95% CI = 0.84 to 0.92) and 0.80 (95% CI = 0.75 to 0.85) for the PSI. ^ Conclusions. There is a statistically significant positive correlation between the BIS and PSI but poor correlation and poor test agreement between the MRS and BIS as well as MRS and PSI. Both the BIS and PSI demonstrated a high level of prediction for undersedation and oversedation; however, the BIS and PSI can not be considered interchangeable monitors of sedation. ^