Performance evaluation of PET scanners: testing of geometric arc correction by off-centre uniformity measurement

The aim of this study was to demonstrate the necessity of an off-centre uniformity measurement during performance evaluation and acceptance testing of a positron emission tomography (PET) system. To this end, the effect of different methods of geometric arc correction on image uniformity was considered. The arc correction routine of the system software of a particular PET scanner family was tested in computer simulations, phantom measurements and a patient study. Various methods of geometric arc correction – nearest neighbour interpolation, linear interpolation and cubic smoothing spline interpolation – were applied to the same data. Uniformity was evaluated both visually and quantitatively using intensity profiles and regions of interest. The arc correction routine of the PET scanner family produced significant ring artefacts and led to overestimation of tracer uptake by up to 15%. Since uniformity measurements are usually performed using a cylindrical phantom at the centre of the transverse field of view, these artefacts are not detected. In conclusion, the standards for performance evaluation of a PET scanner should be extended by inclusion of an off-centre uniformity measurement at the edge of the transverse field of view. On the basis of our comparison of different methods for geometric arc correction, we suppose that cubic smoothingspline interpolationmight improve the relation between statistical noise reduction and spatial resolution as compared with conventional linear interpolation. Received 7 July and in revised form 9 September 1999     

MRI signal intensity based B‐Spline nonrigid registration for pre‐ and intraoperative imaging during prostate brachytherapy

Purpose:

To apply an intensity‐based nonrigid registration algorithm to MRI‐guided prostate brachytherapy clinical data and to assess its accuracy.

Materials and Methods:

A nonrigid registration of preoperative MRI to intraoperative MRI images was carried out in 16 cases using a Basis‐Spline algorithm in a retrospective manner. The registration was assessed qualitatively by experts' visual inspection and quantitatively by measuring the Dice similarity coefficient (DSC) for total gland (TG), central gland (CG), and peripheral zone (PZ), the mutual information (MI) metric, and the fiducial registration error (FRE) between corresponding anatomical landmarks for both the nonrigid and a rigid registration method.

Results:

All 16 cases were successfully registered in less than 5 min. After the nonrigid registration, DSC values for TG, CG, PZ were 0.91, 0.89, 0.79, respectively, the MI metric was ?0.19 ± 0.07 and FRE presented a value of 2.3 ± 1.8 mm. All the metrics were significantly better than in the case of rigid registration, as determined by one‐sided t‐tests.

Conclusion:

The intensity‐based nonrigid registration method using clinical data was demonstrated to be feasible and showed statistically improved metrics when compare to only rigid registration. The method is a valuable tool to integrate pre‐ and intraoperative images for brachytherapy. J. Magn. Reson. Imaging 2009;30:1052–1058. © 2009 Wiley‐Liss, Inc.

     

Investigating Association Between Behavior,Corticosterone, Heart Rate,and Blood Pressure in Rats Using Surrogate Marker Evaluation Methodology

Whether a one-sided or a two-sided ρ value should be used for reporting the results of an analysis should be determined by the a priori question the investigation seeks to answer. It is concluded that one-sided ρ values are appropriate in clinical trials whose objective is to provide definitive, confirmatory evidence of efficacy of pharmaceutical compounds.     

含有周期性的时间序列中随机型缺失数据的填补方法

目的用模拟研究的方法,对含周期性的时间序列数据中随机型缺失数据进行填补,比较基于周期信息的时间序列缺失值填补法(简称周期性填补法)和spline插值填补法对缺失数据的填补效果。方法利用SAS模拟产生平稳、有周期性的时间序列数据并构造随机型缺失。分别比较相同序列长度不同缺失比例和相同缺失比例不同序列长度下,两种方法的缺失值填补效果。采用NRMSE和RMSE量化填补的误差。结果相同序列长度下,随着缺失比例的增加,两种填补方法的填补误差均增加,除缺失比例为30%的RMSE在两种方法间的差异无统计学意义外,周期性填补法的NRMSE和RMSE均小于spline填补法(P<0.05)。相同缺失比例下,序列长度较短时,两种填补方法的差异无统计学意义;序列长度较长时,周期性填补法的填补效果优于spline填补法。结论总体上,周期性填补法对含有确切周期性的时间序列中缺失数据的填补效果较好。     

Summary of Dose-Response Modeling for Developmental Toxicity Studies

Developmental toxicity studies are an important area in the field of toxicology. Endpoints measured on fetuses include weight and indicators of death and malformation. Binary indicator measures are typically summed over the litter and a discrete distribution is assumed to model the number of adversely affected fetuses. Additionally, there is noticeable variation in the litter responses within dose groups that should be taken into account when modeling. Finally, the dose-response pattern in these studies exhibits a threshold effect. The threshold dose-response model is the default model for non-carcinogenic risk assessment, according to the USEPA, and is encouraged by the agency for the use in the risk assessment process. Two statistical models are proposed to estimate dose-response pattern of data from the developmental toxicity study: the threshold model and the spline model. The models were applied to two data sets. The advantages and disadvantages of these models, potential other models, and future research possibilities will be summarized.     

A methodology for the analysis of PSA response signatures

Background and purpose

Temporal distributions in PSA levels following therapeutic intervention for prostate cancer are known to contain characteristics prognostic of disease progression. An algorithm was developed for extracting such characteristics, specifically in the context of previous observations following radiotherapy.

Material and methods

Segmented regression methods were investigated for characterising the ‘signatures’ in log(PSA) descent patterns between intervention and nadir.

Results

The segmented regression method can automatically identify and parameterise features in a PSA distribution including failure points and doubling time patterns following nadir. The method has previously been applied to the analysis of descent patterns on a large clinical data series (Radiother Oncol 2009;90:382-8). Batch-processing of data using the method for all patients in a clinical trial would establish population parameter values and ranges. Subsequent application to an individual patient’s PSA data would determine which resulting prognostic group they fall into.

Conclusions

As more complete and higher-resolution PSA progression datasets become available, techniques such as presented here will allow flexible definition of the characteristics being examined and rapid extraction of parameters for correlation with clinical progression data.     

Body surface Laplacian mapping of atrial depolarization in healthy human subjects

In the present study, we report body surface Laplacian mapping of atrial depolarization under sinus rhythm in 8 healthy male subjects. For each subject, 95 unipolar disk electrodes with inter-electrode distance of 2 cm were used to record simultaneously potential ECGs over the anterior chest. The Laplacian ECG was then estimated during the P wave using a novel spline Laplacian technique. The body surface potential map (BSPM) and body surface Laplacian map (BSLM) at different time instants or time intervals of the P wave were constructed and compared. The present results showed that the BSPMs during the P wave were characterized by the rotation of a pair of positive/negative potential distribution from right to left around the anterior torso. On the other hand, the corresponding BSLMs revealed more spatial details, including two positive activities (denoted as P1 and P2, appeared in all 8 subjects), and three negative activities (denoted as N1, N2, and N3, appeared in 7, 7, and 4 subjects, respectively). The separation of these activities and their evolving patterns were also compared and confirmed by computer simulation using a realistic geometry heart-torso model. The above findings may be directly related to the underlying activation sequence during atrial depolarization in healthy subjects, suggesting the potential clinical applications of the Laplacian ECG technique.     

State parameterization approach to the solution of optimal control problems

A direct method for solving optimal control problems by parameterizing state variables is developed. This state parameterization (SP) procedure is first formulated for a general class of problem. Next, a simpler and more efficient alternative version of the SP algorithm is developed for an important special class of problems, namely those involving systems that can be cast into a multivariable non-linear phase-variable form. The modified SP algorithm in particular avoids explicit integration of the system state and costate differential equations. The algorithm is tested on two problems which are parameterized in terms of cubic splines.     

The relationship between time to arrival of emergency medical services (EMS) and survival from out-of-hospital ventricular fibrillation cardiac arrest

Aim

We examined the relationship between time from collapse to arrival of emergency medical services (EMS) and survival to hospital discharge for out-of-hospital ventricular fibrillation cardiac arrests in order to determine meaningful interpretations of this association.

Methods

We calculated survival rates in 1-min intervals from collapse to EMS arrival. Additionally, we used logistic regression to determine the absolute probability of survival per minute of delayed EMS arrival. We created a logistic regression model with spline terms for the time variable to examine the decline in survival in intervals that are hypothesized to be physiologically relevant.

Results

The observed data showed survival declined, on average, by 3% for each minute that EMS was delayed following collapse. Survival rates did not decline appreciably if the time between collapse and arrival of EMS was 4 min or less but they declined by 5.2% per minute between 5 and 10 min. EMS arrival 11-15 min after collapse showed a less steep decline in survival of 1.9% per minute. The spline model that incorporated changes in slope in the time interval variable modeled this relationship more accurately than a model with a continuous term for time (p = 0.01).

Conclusions

The results of our analyses show that survival from out-of-hospital cardiac arrest does not decline at a constant rate following collapse. Models that incorporate changes that reflect the physiological alterations that occur following cardiac arrests are a more accurate way to describe changes in survival rates over time than models that include only a continuous term for time.     

A semiparametric approach to estimate rapid lung function decline in cystic fibrosis

PurposeDetecting the onset of rapid lung function decline is important to reduce mortality rates in cystic fibrosis (CF) and other lung diseases. The most common approach is conventional linear mixed modeling—estimating a population-level slope of lung function decline and using random effects to address serial correlation—but this ignores nonlinear features of disease progression and distinct sources of variability. The purpose of this article was to estimate patient-specific timing and degree of rapid decline while appropriately characterizing natural progression and variation in CF.MethodsWe propose longitudinal semiparametric mixed modeling and contrast it with the conventional approach, which restricts lung function (measured as forced expiratory volume in 1 second as a percentage of predicted, FEV₁%) to linear decline. Each approach is applied to clinical encounter data from the United States CF Foundation Patient Registry.ResultsTiming and degree of rapid FEV₁% decline vary across patients and as a function of key covariates. Patients experience maximal FEV₁% loss by early adulthood more severe than indicated by conventional slope analysis.ConclusionsSemiparametric mixed modeling provides a means to estimate patient-specific changes in CF disease progression and may be used to inform prognostic decisions in chronic care settings and clinical studies.