Popple, Richard A.

OBJECTIVE Stereotactic radiosurgery (SRS) is an effective treatment for refractory tremor. However, the lack of reliable patient-specific targeting biomarkers leads to varying outcomes. Although connectomic-based targeting is commonly used in deep brain stimulation, its application in SRS is limited. This study aimed to develop a new targeting approach by using patient-specific structural connectivity to improve outcomes after SRS. METHODS The authors performed a retrospective study of patients in a prospective trial for frameless virtual-cone SRS on a linear accelerator for essential tremor or tremor-dominant Parkinson disease. The primary endpoint was percentage improvement in Fahn-Tolosa-Marin tremor rating scale scores contralateral to the treatment side. Probabilistic tractography assessed connectivity from each thalamic voxel to the primary motor cortex (M1), primary sensory cortex (S1), and supplemental motor area/premotor cortex (SMA/PMC). Group-level comparisons were conducted to evaluate the relationship between the sweet spot for maximum contralateral tremor improvement and areas maximally connected to M1, S1, and SMA/PMC. Multiple regression analysis assessed the relationship between the lesion centerpoint coordinates and the maximally connected voxel to M1, S1, and SMA/PMC at the individual level. RESULTS The analysis included 27 patients with a mean follow-up of 17.9 ± 11.1 months. The sweet spot for maximal contralateral tremor improvement at the group level was in the region most connected to M1 cortex. Smaller y-distances (anterior-posterior) from the lesion center to the M1 maximally connected voxel significantly correlated with tremor improvement at the single-subject level (p < 0.001). However, the authors found no significant correlation between the lesion y-coordinate and the maximally connected voxel to SMA/PMC and S1, nor between the x-distances from the lesions to the SMA/PMC, M1, and S1 voxels (p > 0.07). CONCLUSIONS This study demonstrates that patient-specific connectivity between the treatment target and M1 correlates with treatment outcomes. The authors’ approach provides a practical targeting method for SRS thalamotomy for tremor.

The term Big Data has come to encompass a number of concepts and uses within medicine. This paper lays out the relevance and application of large collections of data in the radiation oncology community. We describe the potential importance and uses in clinical practice. The important concepts are then described and how they have been or could be implemented are discussed. Impediments to progress in the collection and use of sufficient quantities of data are also described. Finally, recommendations for how the community can move forward to achieve the potential of big data in radiation oncology are provided.

The purpose of this study was to evaluate the accuracy and calculation speed of electron dose distributions calculated by the Eclipse electron Monte Carlo (eMC) algorithm for use with bolus electron conformal therapy (ECT). The recent commercial availability of bolus ECT technology requires further validation of the eMC dose calculation algorithm. eMC‐calculated electron dose distributions for bolus ECT have been compared to previously measured TLD‐dose points throughout patient‐based cylindrical phantoms (retromolar trigone and nose), whose axial cross sections were based on the mid‐PTV (planning treatment volume) CT anatomy. The phantoms consisted of SR4 muscle substitute, SR4 bone substitute, and air. The treatment plans were imported into the Eclipse treatment planning system, and electron dose distributions calculated using 1% and statistical uncertainties. The accuracy of the dose calculations using moderate smoothing and no smoothing were evaluated. Dose differences (eMC‐calculated less measured dose) were evaluated in terms of absolute dose difference, where 100% equals the given dose, as well as distance to agreement (DTA). Dose calculations were also evaluated for calculation speed. Results from the eMC for the retromolar trigone phantom using 1% statistical uncertainty without smoothing showed calculated dose at of the measured TLD‐dose points was within 3% dose difference or 3 mm DTA of the measured value. The average dose difference was , and the net standard deviation was 2.32%. Differences as large as 3.7% occurred immediately distal to the mandible bone. Results for the nose phantom, using 1% statistical uncertainty without smoothing, showed calculated dose at of the measured TLD‐dose points within 3% dose difference or 3 mm DTA. The average dose difference was 1.08%, and the net standard deviation was 3.17%. Differences as large as 10% occurred lateral to the nasal air cavities. Including smoothing had insignificant effects on the accuracy of the retromolar trigone phantom calculations, but reduced the accuracy of the nose phantom calculations in the high‐gradient dose areas. Dose calculation times with 1% statistical uncertainty for the retromolar trigone and nose treatment plans were 30 s and 24 s, respectively, using 16 processors (Intel Xeon E5‐2690, 2.9 GHz) on a framework agent server (FAS). In comparison, the eMC was significantly more accurate than the pencil beam algorithm (PBA). The eMC has comparable accuracy to the pencil beam redefinition algorithm (PBRA) used for bolus ECT planning and has acceptably low dose calculation times. The eMC accuracy decreased when smoothing was used in high‐gradient dose regions. The eMC accuracy was consistent with that previously reported for accuracy of the eMC electron dose algorithm and shows that the algorithm is suitable for clinical implementation of bolus ECT.PACS number(s): 87.55.kd