Search

Radiopharmaceutical therapy (RPT) continues to demonstrate tremendous potential in improving the therapeutic gains in radiation therapy by specifically delivering radiation to tumors that can be well assessed in terms of dosimetry and imaging. Dosimetry in external beam radiation therapy is standard practice. This is not the case, however, in RPT. This NRG (acronym formed from the first letter of the 3 original groups: National Surgical Adjuvant Breast and Bowel Project, the Radiation Therapy Oncology Group, and the Gynecologic Oncology Group)-National Cancer Institute Working Group review describes some of the challenges to improving RPT. The main priorities for advancing the field include (1) developing and adopting best practice guidelines for incorporating patient-specific dosimetry for RPT that can be used at both large clinics with substantial resources and more modest clinics that have limited resources, (2) establishing and improving strategies for introducing new radiopharmaceuticals for clinical investigation, (3) developing approaches to address the radiophobia that is associated with the administration of radioactivity for cancer therapy, and (4) solving the financial and logistical issues of expertise and training in the developing field of RPT.

Background: Recent studies have shown a clear relationship between absorbed dose and tumor response to treatment after hepatic radioembolization. These findings help to create more personalized treatment planning and dosimetry. However, crucial to this goal is the ability to predict the dose distribution prior to treatment. The microsphere distribution is ultimately determined by (i) the hepatic vasculature and the resulting blood flow dynamics and (ii) the catheter position. Purpose: To show that pretreatment, intra‐procedural imaging of blood flow patterns, as quantified by catheter‐directed intra‐arterial contrast enhancement, correlate with posttreatment microsphere accumulation and, consequently, absorbed dose. Materials and methods: Patients who participated in a clinical trial (NCT01177007) and for whom both a pretreatment dual‐phase contrast‐enhanced cone‐beam CT (CBCT) and a posttreatment 90Y PET/CT scan were available were included in this retrospective study. Tumors and perfused volumes were manually delineated on the CBCT by an experienced radiologist. The mean, sum, and standard deviation of the voxels in each volume were recorded. The delineations were transferred to the PET‐based absorbed dose maps by coregistration of the corresponding CTs. Linear multiple regression was used to correlate pretreatment CBCT enhancement to posttreatment 90Y PET/CT‐based absorbed dose in each region. Leave‐one‐out cross‐validation and Bland–Altman analyses were performed on the predicted versus measured absorbed doses. Results: Nine patients, with a total of 23 tumors were included. All presented with hepatocellular carcinoma (HCC). Visually, all patients had a clear correspondence between CBCT enhancement and absorbed dose. The correlation between CBCT enhancement and posttherapy absorbed tumor dose based was strong (R2 = 0.91), and moderate for the non‐tumor liver tissue (R2 = 0.61). Limits of agreement were approximately ±55 Gray for tumor tissue. Conclusion: There is a linear relationship between pretreatment blood dynamics in HCC tumors and posttreatment absorbed dose, which, if shown to be generalizable, allows for pretreatment tumor absorbed dose prediction. [ABSTRACT FROM AUTHOR]

Background: Pediatric molecular imaging requires a balance between administering an activity that will yield sufficient diagnostic image quality while maintaining patient radiation exposure at acceptable levels. In current clinical practice, this balance is arrived at by the current North American Consensus Guidelines in which patient weight is used to recommend the administered activity (AA). Purpose: We have previously demonstrated that girth (waist circumference at the level of the kidneys) is better at equalizing image quality than patient weight for pediatric Tc‐99m DMSA renal function imaging. However, the correlation between image quality (IQ), AA, and patient girth has not been rigorously and systematically developed. In this work, we generate a series of curves showing the tradeoff between AA and IQ as a function of patient girth, providing the data for standards bodies to develop the next generation of dosing guideline for pediatric DMSA SPECT. Methods: An anthropomorphic phantom series that included variations in age (5, 10, and 15 years), gender (M, F), local body morphometry (5, 10, 50, 90, and 95th girth percentiles), and kidney size (±15% standard size), was used to generate realistic SPECT projections. A fixed and clinically challenging defect‐to‐organ volume percentage (0.49% of renal cortex value) was used to model a focal defect with zero uptake (i.e., full local loss of renal function). Task‐based IQ assessment methods were used to rigorously measure IQ in terms of renal perfusion defect detectability. This assessment was performed at multiple count levels (corresponding to various AAs) for groups of patients that had similar girths and defect sizes. Receiver‐operating characteristics (ROC) analysis was applied; the area under the ROC curve (AUC) was used as a figure‐of‐merit for task performance. Curves showing the tradeoff between AUC and AA were generated for these groups of phantoms. Results: Overall, the girth‐based dosing method suggested different amounts of AA compared to weight‐based dosing for the phantoms that had a relatively large body weight but a small girth or phantoms with relatively small bodyweight but large girth. Reductions of AA to 62.9% compared to weight‐based dosing guidelines can potentially be realized while maintaining a baseline (AUC = 0.80) IQ for certain 15‐year‐olds who have a relatively small girth and large defect size. Note that the task‐based IQ results are heavily dependent on the simulated defect size for the defect detection task and the appropriate AUC value must be decided by the physicians for this diagnostic task. These results are based purely on simulation and are subject to future clinical validation. Conclusions: The study provides simulation‐based IQ‐AA data for a girth‐based dosing method for pediatric renal SPECT, suggesting that patient waist circumference at the level of kidneys should be considered in selecting the AA needed to achieve an acceptable IQ. This data may be useful for standards bodies to develop girth‐based dosing guidelines. [ABSTRACT FROM AUTHOR]

In order to describe multiclass classification performance, several figures of merit (FOM) have been proposed. Among the earliest and most widely known of these is the three-class Hotelling trace (3-HT). The goal of this paper is to present theoretical and empirical data demonstrating the failure of 3-HT as a measure of three-class task performance. To help do this, we contrast it to a newly proposed three-class FOM, the volume under the three-class receiver operating characteristic (ROC) surface (VUS). The VUS is obtained from a decision theory based three-class ROC analysis method which has been proved to extend the decision theoretic, linear discriminant analysis (LDA), and psychophysical foundations of binary ROC analysis to a three-class paradigm. We demonstrate empirically that the VUS and 3-HT do not have a monotonic relationship in general when describing three-class task performance. Numerical experiments demonstrated that the VUS provided reasonable results, while the 3-HT failed to distinguish between the case where all objects could be perfectly classified from the case where only one pair of the classes could be perfectly classified. We have provided theoretical explanations of this failure of 3-HT. The significance of this work goes beyond merely demonstrating the problems of the 3-HT, it demonstrates that a FOM that is mathematically correct and has a strong theoretical basis can provide results that violate a common sense understanding of three-class task performance. This fact raises the question of 'how to evaluate a classification performance evaluation method?' We believe the answer to this question lies in the theoretical foundations of binary ROC analysis. We have thus contrasted the two FOMs in terms of three fundamental theories underlying binary ROC analysis: decision theory, binary linear discriminant analysis, and the equivalence of two psychophysical classification procedures. These theoretical investigations demonstrated the importance of extending and unifying all the fundamental theories of binary classification in the development of a three-class FOM; violating one of theses fundamental binary classification theories may, as it did for the L-HT, provide predictions of three-class task performance that do not agree with a common sense understanding of three-class task performance. Index Terms--L-class Hotelling trace, L-class linear discriminant analysis, receiver operating characteristic (ROC) analysis, three-class classification.

The diagnosis of cardiac disease using dual-isotope myocardial perfusion SPECT (MPS) is based on the defect status in both stress and rest images, and can be modeled as a three-class task of classifying patients as having no, reversible, or fixed perfusion defects. Simultaneous acquisition protocols for dual-isotope MPS imaging have gained much interest due to their advantages including perfect registration of the [sup.201]T1 and [sup.99m]Tc images in space and time, increased patient comfort, and higher clinical throughput. As a result of simultaneous acquisition, however, crosstalk contamination, where photons emitted by one isotope contribute to the image of the other isotope, degrades image quality. Minimizing the crosstalk is important in obtaining the best possible image quality. One way to minimize the crosstalk is to optimize the injected activity of the two isotopes by considering the three-class nature of the diagnostic problem. To effectively do so, we have previously developed a three-class receiver operating characteristic (ROC) analysis methodology that extends and unifies the decision theoretic, linear discriminant analysis, and psychophysical foundations of binary ROC analysis in a three-class paradigm. In this work, we applied the proposed three-class ROC methodology to the assessment of the image quality of simultaneous dual-isotope MPS imaging techniques and the determination of the optimal injected activity combination. In addition to this application, the rapid development of diagnostic imaging techniques has produced an increasing number of clinical diagnostic tasks that involve not only disease detection, but also disease characterization and are thus multiclass tasks. This paper provides a practical example of the application of the proposed three-class ROC analysis methodology to medical problems. Index Terms--Dual-isotope myocardial perfusion SPECT (MPS), simultaneous acquisition, task-based image quality assessment, three-class Hotelling observer, three-class receiver operating characteristic (ROC) analysis.

The ideal observer (IO) employs complete knowledge of the available data statistics and sets an upper limit on observer performance on a binary classification task. However, the IO test statistic cannot be calculated analytically, except for cases where object statistics are extremely simple. Kupinski et al. have developed a Markov chain Monte Carlo (MCMC) based technique to compute the IO test statistic for, in principle, arbitrarily complex objects and imaging systems. In this work, we applied MCMC to estimate the IO test statistic in the context of myocardial perfusion SPECT (MPS). We modeled the imaging system using an analytic SPECT projector with attenuation, distant-dependent detector-response modeling and Poisson noise statistics. The object is a family of parameterized torso phantoms with variable geometric and organ uptake parameters. To accelerate the imaging simulation process and thus enable the MCMC IO estimation, we used discretized anatomic parameters and continuous uptake parameters in defining the objects. The imaging process simulation was modeled by precomputing projections for each organ for a finite number of discretely-parameterized anatomic parameters and taking linear combinations of the organ projections based on continuous sampling of the organ uptake parameters. The proposed method greatly reduces the computational burden and allows MCMC IO estimation for a realistic MPS imaging simulation. We validated the proposed IO estimation technique by estimating IO test statistics for a large number of input objects. The properties of the first- and second-order statistics of the IO test statistics estimated using the MCMC IO estimation technique agreed well with theoretical predictions. Further, as expected, the IO had better performance, as measured by the receiver operating characteristic (ROC) curve, than the Hotelling observer. This method is developed for SPECT imaging. However, it can be adapted to any linear imaging system. Index Terms--Ideal observer, Markov chain Monte Carlo (MCMC).

Previously, we have proposed a method for three-class receiver operating characteristic (ROC) analysis based on decision theory. In this method, the volume under a three-class ROC surface (VUS) serves as a figure-of-merit (FOM) and measures three-class task performance. The proposed three-class ROC analysis method was demonstrated to be optimal under decision theory according to several decision criteria. Further, an optimal three-class linear observer was proposed to simultaneously maximize the signal-to-noise ratio (SNR) between the test statistics of each pair of the classes provided certain data linearity condition. Applicability of this three-class ROC analysis method would be further enhanced by the development of an intuitive meaning of the VUS and a more general method to calculate the VUS that provides an estimate of its standard error. In this paper, we investigated the general meaning and usage of VUS as a FOM for three-class classification task performance. We showed that the VUS value, which is obtained from a rating procedure, equals the percent correct in a corresponding categorization procedure for continuous rating data. The significance of this relationship goes beyond providing another theoretical basis for three-class ROC analysis--it enables statistical analysis of the VUS value. Based on this relationship, we developed and we reviewed the current status of the proposed three-class ROC analysis methodology, and concluded that it extends and unifies decision theoretic, linear discriminant analysis, and psychophys-ical foundations of binary ROC analysis in a three-class paradigm. Index Terms--Ideal observer, receiver operating characteristic (ROC) analysis, three-class classification.

Estimating the residence times in tumor and normal organs is an essential part of treatment planning for radioimmunotherapy (RIT). This estimation is usually done using a conjugate view whole body scan time series and planar processing. This method has logistical and cost advantages compared to 3-D imaging methods such as Single photon emission computed tomography (SPECT), but, because it does not provide information about the 3-D distribution of activity, it is difficult to fully compensate for effects such as attenuation and background and overlapping activity. Incomplete compensation for these effects reduces the accuracy of the residence time estimates. In this work we compare residence times estimates obtained using planar methods to those from methods based on quantitative SPECT (QSPECT) reconstructions. We have previously developed QSPECT methods that provide compensation for attenuation, scatter, collimator-detector response, and partial volume effects. In this study we compared the use of residence time estimation methods using QSPECT to planar methods. The evaluation was done using the realistic NCAT phantom with organ time activities that model [sup.111]In ibritumomab tiuxetan. Projection data were obtained using Monte Carlo simulations (MCS) that realistically model the image formation process including penetration and scatter in the collimator-detector system. These projection data were used to evaluate the accuracy of residence time estimation using a time series of QSPECT studies, a single QSPECT study combined with planar scans and the planar scans alone. The errors in the residence time estimates were

Rotating multisegment slant-hole (RMSSH) single photon emission computed tomography (SPECT) is suitable for detecting small and low-contrast breast lesions since it has much higher detection efficiency than conventional SPECT with a parallel-hole collimator and can image the breast at a closer distance. Our RMSSH SPECT reconstruction extends a previous rotation-shear transformation-based method to include nonuniform attenuation and collimator-detector response (CDR) compensation. To evaluate our reconstruction method, we performed two phantom simulation studies with 1) an isolated breast and 2) a breast phantom attached to the body torso. The reconstructed RMSSH SPECT images with attenuation and CDR compensation showed improved quantitative accuracy and less image artifacts than without. To evaluate the clinical efficacy of RMSSH SPECT mammography, we used a simulation study to compare with planar scintimammography in terms of the signal-to-noise ratio (SNR) value of a breast lesion. The RMSSH SPECT reconstruction images showed higher SNR value than the planar scintimammography images and even more so as we applied compensation for attenuation and collimator detector response. We conclude that attenuation and CDR compensation provide RMSSH SPECT mammography images with improved quality and quantitative accuracy.

Many attempts have been made to develop an optimal linear observer for classifying multiclass data. Most approaches either do not have a definite description of optimality or have regions of ambiguity in decision making. In this paper, we derive a threeclass Hotelling observer (3-HO), inspired by the ideal observer that results from a decision theoretic solution to the three-class classification problem. Assuming the data vectors follow multivariate Gaussian distributions with equal covariance matrices for the three classes, it is shown that two two-class Hoteiling templates construct a 3-HO which has the same performance as the three-class ideal observer (3-IO). We show that, without the Gaussian and equal covariance assumptions, the 3-HO is still applicable when the twoclass Hotelling templates of each pair of the classes satisfy a certain linear relationship. In this case, the 3-HO simultaneously maximizes the signal-to-noise (SNR) of the test statistics between each pair of the classes. In conclusion, we developed a three-class linear mathematical observer that uses first- and second-order ensemble data statistics. This mathematical observer, which has clearly defined optimality for several data statistics conditions and has decision rules that have no ambiguous decision regions, is potentially useful in the optimization and evaluation of imaging techniques for performing three-class diagnostic tasks. Index Terms--Three-class classification, three-class Hotelling observer (HO), three-class receiver operating characteristic (ROC) analysis.

Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the 'general' three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems. Index Terms--Ideal observer, three-class classification, three-class receiver operating characteristic (ROC).

Receiver operating characteristic (ROC) analysis is well established in the evaluation of systems involving binary classification tasks. However, medical tests often require distinguishing among more than two diagnostic alternatives. The goal of this work was to develop an ROC analysis method for three-class classification tasks. Based on decision theory, we developed a method for three-class ROC analysis. In this method, the objects were classified by making the decision that provided the maximal utility relative to the other two. By making assumptions about the magnitudes of the relative utilities of incorrect decisions, we found a decision model that maximized the expected utility of the decisions when using log-likelihood ratios as decision variables. This decision model consists of a two-dimensional decision plane with log likelihood ratios as the axes and a decision structure that separates the plane into three regions. Moving the decision structure over the decision plane, which corresponds to moving the decision threshold in two-class ROC analysis, and computing the true class 1, 2, and 3 fractions defined a three-class ROC surface. We have shown that the resulting three-class ROC surface shares many features with the two-class ROC curve; i.e., using the log likelihood ratios as the decision variables results in maximal expected utility of the decisions, and the optimal operating point for a given diagnostic setting (set of relative utilities and disease prevalences) lies on the surface. The volume under the three-class surface (VUS) serves as a figure-of-merit to evaluate different data acquisition systems or image processing and reconstruction methods when the assumed utility constraints are relevant. Index Terms--Ideal observers, ROC analysis, three-class classification.

In [sup.201]T1/[sup.99m]Tc dual-isotope simultaneous-acquisition (DISA) myocardial imaging, crosstalk due to Tc photons results in significant contamination of the T1 data. The objective of this work is to seek the acquisition parameters (i.e., energy window width and center) that have the optimal tradeoff between minimizing the crosstalk and maximizing the detection efficiency. The optimization criterion was based on maximizing an ideal observer signal-to-noise ratio (SNR) for the myocardial defect detection task using single-isotope and DISA projection images acquired from a torso phantom. For single-isotope images, the optimal energy windows (width/center: 26 keV/75 keV and 28 keV/165 keV for [sup.201]T1, 30 keV/142 keV for [sup.99m]Tc) are wider than typical windows. For DISA imaging, the optimal windows varied with the [sup.99m]Tc to [sup.201]T1 activity ratio and are thus likely to depend on the uptake ratio in each patient. Using the optimal ratio 2.25-2.75 (148 MBq [sup.201]T1 and 333-407 MBq [sup.99m]Tc) with the corresponding optimal windows (22 keV/72 keV, 24 keV/167 keV, and 24 keV/140 keV) gives [sup.201]T1 images with substantially increased SNRs as well as [sup.99m]Tc images with SNRs same as those of 370 MBq [sup.99m]Tc-only images. However, without the addition of crosstalk compensation, the use of the optimal activity and energy windows alone is likely not sufficient to restore the DISA TI SNR to that of TI-only image. Index Terms--Listmode, optimization, simultaneous dual-isotope imaging, [sup.99m]TC, [sup.201]T1.