Due to its superior soft tissue contrast, magnetic resonance imaging (MRI) is essential for many radiotherapy treatment indications. This is especially true for treatment planning in intracranial tumors, where MRI has a long-standing history for target delineation in clinical practice. Despite its routine use, care has to be taken when selecting and acquiring MRI studies for the purpose of radiotherapy treatment planning. Requirements on MRI are particularly demanding for intracranial stereotactic radiotherapy, where accurate imaging has a critical role in treatment success. However, MR images acquired for routine radiological assessment are frequently unsuitable for high-precision stereotactic radiotherapy as the requirements for imaging are significantly different for radiotherapy planning and diagnostic radiology. To assure that optimal imaging is used for treatment planning, the radiation oncologist needs proper knowledge of the most important requirements concerning the use of MRI in brain stereotactic radiotherapy. In the present review, we summarize and discuss the most relevant issues when using MR images for target volume delineation in intracranial stereotactic radiotherapy.

BackgroundThere is insufficient understanding of the natural course of volumetric regression in brain metastases after stereotactic radiotherapy (SRT) and optimal volumetric criteria for the assessment of response and progression in radiotherapy clinical trials for brain metastases are currently unknown.MethodsVolumetric analysis via whole-tumor segmentation in contrast-enhanced 1 mm³-isotropic T1-Mprage sequences before SRT and during follow-up. A total of 3,145 MRI studies of 419 brain metastases from 189 patients were segmented. Progression was defined using a volumetric extension of the RANO-BM criteria. A subset of 205 metastases without progression/radionecrosis during their entire follow-up of at least 3 months was used to study the natural course of volumetric regression after SRT. Predictors for volumetric regression were investigated. A second subset of 179 metastases was used to investigate the prognostic significance of volumetric response at 3 months (defined as ≥20% and ≥65% volume reduction, respectively) for subsequent local control.ResultsMedian relative metastasis volume post-SRT was 66.9% at 6 weeks, 38.6% at 3 months, 17.7% at 6 months, 2.7% at 12 months and 0.0% at 24 months. Radioresistant histology and FSRT vs. SRS were associated with reduced tumor regression for all time points. In multivariate linear regression, radiosensitive histology (p=0.006) was the only significant predictor for metastasis regression at 3 months. Volumetric regression ≥20% at 3 months post-SRT was the only significant prognostic factor for subsequent control in multivariate analysis (HR 0.63, p=0.023), whereas regression ≥65% was no significant predictor.ConclusionsVolumetric regression post-SRT does not occur at a constant rate but is most pronounced in the first 6 weeks to 3 months. Despite decreasing over time, volumetric regression continues beyond 6 months post-radiotherapy and may lead to complete resolution of controlled lesions by 24 months. Radioresistant histology is associated with slower regression. We found that a cutoff of ≥20% regression for the volumetric definition of response at 3 months post-SRT was predictive for subsequent control whereas the currently proposed definition of ≥65% was not. These results have implications for standardized volumetric criteria in future radiotherapy trials for brain metastases.

The hybrid treatment delivery system (HTDS) has been proposed as a possible option for a quality assurance in the multi-catheter interstitial brachytherapy for breast cancer patients. The system, which consists out of a prototype afterloader with an integrated electromagnetic tracking (EMT) sensor and an EMT system, allows the automatic measurement of implanted catheters. To test the feasibility of the system for error detection, possible treatment planning errors and treatment delivery errors were simulated. Planning errors such as an incorrect offset value, an incorrect indexer length, tip/connector end swaps, and partial swaps, and; treatment delivery errors such as catheter shifts and catheter connection swaps were manually simulated using phantoms. An in-house Matlab routine was used to assess geometrical deviations between the dwell positions defined based on CT and EMT measurement. Additionally, the influence of implant motion on the detection ability of the system was assessed. An algorithm for the detection and specification of errors based on the error simulation results was developed. At the University Hospital Erlangen, a patient study is ongoing, where errors in patient data were analyzed using the proposed algorithm. All simulated planning errors were detected. Catheter connection swaps can be detected 100% of the time. A shift detection rate of  >97% was observed for shifts larger than 1.1 mm, both in the static and the motion measurements. Catheter reconstruction uncertainties and catheter shifts  <2 mm were found to be the most common treatment planning and delivery errors in patient data. HTDS proved to be a reliable method for error detection.

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