Resection and brain brachytherapy with permanent iodine-125 sources for brain metastasis.

OBJECTIVE Stereotactic radiosurgery (SRS) with or without whole-brain radiotherapy can be used to achieve local control (> 90%) for small brain metastases after resection. However, many brain metastases are unsuitable for SRS because of their size or previous treatment, and whole-brain radiotherapy is associated with significant neurocognitive morbidity. The purpose of this study was to investigate the efficacy and toxicity of surgery and iodine-125 (125I) brachytherapy for brain metastases. METHODS A total of 95 consecutive patients treated for 105 brain metastases at a single institution between September 1997 and July 2013 were identified for this analysis retrospectively. Each patient underwent MRI followed by craniotomy with resection of metastasis and placement of 125I sources as permanent implants. The patients were followed with serial surveillance MRIs. The relationships among local control, overall survival, and necrosis were estimated by using the Kaplan-Meier method and compared with results of log-rank tests and multivariate regression models. RESULTS The median age at surgery was 59 years (range 29.9-81.6 years), 53% of the lesions had been treated previously, and the median preoperative metastasis volume was 13.5 cm3 (range 0.21-76.2 cm3). Gross-total resection was achieved in 81% of the cases. The median number of 125I sources implanted per cavity was 28 (range 4-93), and the median activity was 0.73 mCi (range 0.34-1.3 mCi) per source. A total of 476 brain MRIs were analyzed (median MRIs per patient 3; range 0-22). Metastasis size was the strongest predictor of cavity volume and shrinkage (p < 0.0001). Multivariable regression modeling failed to predict the likelihood of local progression or necrosis according to metastasis volume, cavity volume, or the rate of cavity remodeling regardless of source activity or previous SRS. The median clinical follow-up time in living patients was 14.4 months (range 0.02-13.6 years), and crude local control was 90%. Median overall survival extended from 2.1 months in the shortest quartile to 62.3 months in the longest quartile (p < 0.0001). The overall risk of necrosis was 15% and increased significantly for lesions with a history of previous SRS (p < 0.05). CONCLUSIONS Therapeutic options for patients with large or recurrent brain metastases are limited. Data from this study suggest that resection with permanent 125I brachytherapy is an effective strategy for achieving local control of brain metastasis. Although metastasis volume significantly influences resection cavity size and remodeling, volumetric parameters do not seem to influence local control or necrosis. With careful patient selection, this treatment regimen is associated with minimal toxicity and can result in long-term survival for some patients. ▪ CLASSIFICATION OF EVIDENCE Type of question: therapeutic; study design: retrospective case series; evidence: Class IV.

Cardiac position sensitivity study in the electrocardiographic forward problem using stochastic collocation and boundary element methods.

The electrocardiogram (ECG) is ubiquitously employed as a diagnostic and monitoring tool for patients experiencing cardiac distress and/or disease. It is widely known that changes in heart position resulting from, for example, posture of the patient (sitting, standing, lying) and respiration significantly affect the body-surface potentials; however, few studies have quantitatively and systematically evaluated the effects of heart displacement on the ECG. The goal of this study was to evaluate the impact of positional changes of the heart on the ECG in the specific clinical setting of myocardial ischemia. To carry out the necessary comprehensive sensitivity analysis, we applied a relatively novel and highly efficient statistical approach, the generalized polynomial chaos-stochastic collocation method, to a boundary element formulation of the electrocardiographic forward problem, and we drove these simulations with measured epicardial potentials from whole-heart experiments. Results of the analysis identified regions on the body-surface where the potentials were especially sensitive to realistic heart motion. The standard deviation (STD) of ST-segment voltage changes caused by the apex of a normal heart, swinging forward and backward or side-to-side was approximately 0.2 mV. Variations were even larger, 0.3 mV, for a heart exhibiting elevated ischemic potentials. These variations could be large enough to mask or to mimic signs of ischemia in the ECG. Our results suggest possible modifications to ECG protocols that could reduce the diagnostic error related to postural changes in patients possibly suffering from myocardial ischemia.

Incorporating patient breathing variability into a stochastic model of dose deposition for stereotactic body radiation therapy.

Hypo-fractionated stereotactic body radiation therapy (SBRT) employs precisely-conforming high-level radiation dose delivery to improve tumor control probabilities and sparing of healthy tissue. However, the delivery precision and conformity of SBRT renders dose accumulation particularly susceptible to organ motion, and respiratory-induced motion in the abdomen may result in significant displacement of lesion targets during the breathing cycle. Given the maturity of the technology, sensitivity of dose deposition to respiratory-induced organ motion represents a significant factor in observed discrepancies between predictive treatment plan indicators and clinical patient outcome statistics and one of the major outstanding unsolved problems in SBRT. Techniques intended to compensate for respiratory-induced organ motion have been investigated, but very few have yet reached clinical practice. To improve SBRT, it is necessary to overcome the challenge that uncertainties in dose deposition due to organ motion present. This requires incorporating an accurate prediction of the effects of the random nature of the respiratory process on SBRT dose deposition for improved treatment planning and delivery of SBRT. We introduce a means of characterizing the underlying day-to-day variability of patient breathing and calculate the resulting stochasticity in dose accumulation.

Application of stochastic finite element methods to study the sensitivity of ECG forward modeling to organ conductivity.

Because numerical simulation parameters may significantly influence the accuracy of the results, evaluating the sensitivity of simulation results to variations in parameters is essential. Although the field of sensitivity analysis is well developed, systematic application of such methods to complex biological models is limited due to the associated high computational costs and the substantial technical challenges for implementation. In the specific case of the forward problem in electrocardiography, the lack of robust, feasible, and comprehensive sensitivity analysis has left many aspects of the problem unresolved and subject to empirical and intuitive evaluation rather than sound, quantitative investigation. In this study, we have developed a systematic, stochastic approach to the analysis of sensitivity of the forward problem of electrocardiography to the parameter of inhomogeneous tissue conductivity. We apply this approach to a two-dimensional, inhomogeneous, geometric model of a slice through the human thorax. We assigned probability density functions for various organ conductivities and applied stochastic finite elements based on the generalized polynomial chaos-stochastic Galerkin (gPC-SG) method to obtain the standard deviation of the resulting stochastic torso potentials. This method utilizes a spectral representation of the stochastic process to obtain numerically accurate stochastic solutions in a fraction of the time required when employing classic Monte Carlo methods. We have shown that a systematic study of sensitivity is not only easily feasible with the gPC-SG approach but can also provide valuable insight into characteristics of the specific simulation.

Stochastic Markovian modeling of electrophysiology of ion channels: reconstruction of standard deviations in macroscopic currents.

Markovian models of ion channels have proven useful in the reconstruction of experimental data and prediction of cellular electrophysiology. We present the stochastic Galerkin method as an alternative to Monte Carlo and other stochastic methods for assessing the impact of uncertain rate coefficients on the predictions of Markovian ion channel models. We extend and study two different ion channel models: a simple model with only a single open and a closed state and a detailed model of the cardiac rapidly activating delayed rectifier potassium current. We demonstrate the efficacy of stochastic Galerkin methods for computing solutions to systems with random model parameters. Our studies illustrate the characteristic changes in distributions of state transitions and electrical currents through ion channels due to random rate coefficients. Furthermore, the studies indicate the applicability of the stochastic Galerkin technique for uncertainty and sensitivity analysis of bio-mathematical models.