Synthetic CTs for MRI-only brain RT treatment: integration of immobilization systems.

PURPOSE: Auxiliary devices such as immobilization systems should be considered in synthetic CT (sCT)-based treatment planning (TP) for MRI-only brain radiotherapy (RT). A method for auxiliary device definition in the sCT is introduced, and its dosimetric impact on the sCT-based TP is addressed. METHODS: T1-VIBE DIXON was acquired in an RT setup. Ten datasets were retrospectively used for sCT generation. Silicone markers were used to determine the auxiliary devices' relative position. An auxiliary structure template (AST) was created in the TP system and placed manually on the MRI. Various RT mask characteristics were simulated in the sCT and investigated by recalculating the CT-based clinical plan on the sCT. The influence of auxiliary devices was investigated by creating static fields aimed at artificial planning target volumes (PTVs) in the CT and recalculated in the sCT. The dose covering 50% of the PTV (D50) deviation percentage between CT-based/recalculated plan (∆D50[%]) was evaluated. RESULTS: Defining an optimal RT mask yielded a ∆D50[%] of 0.2 ± 1.03% for the PTV and between -1.6 ± 3.4% and 1.1 ± 2.0% for OARs. Evaluating each static field, the largest ∆D50[%] was delivered by AST positioning inaccuracy (max: 3.5 ± 2.4%), followed by the RT table (max: 3.6 ± 1.2%) and the RT mask (max: 3.0 ± 0.8% [anterior], 1.6 ± 0.4% [rest]). No correlation between ∆D50[%] and beam depth was found for the sum of opposing beams, except for (45°â€¯+ 315°). CONCLUSION: This study evaluated the integration of auxiliary devices and their dosimetric influence on sCT-based TP. The AST can be easily integrated into the sCT-based TP. Further, we found that the dosimetric impact was within an acceptable range for an MRI-only workflow.

Usability of magnetic resonance images acquired at a novel low-field 0.55 T scanner for brain radiotherapy treatment planning.

Background and Purpose: Low-field magnetic resonance imaging (MRI) may offer specific advantages over high-field MRI, e.g. lower susceptibility-dependent distortions and simpler installation. The study aim was to evaluate if a novel 0.55 T MRI scanner provides sufficient image accuracy and quality for radiotherapy (RT) treatment planning. Material and methods: The geometric accuracy of images acquired at a low-field MRI scanner was evaluated in phantom measurements regarding gradient non-linearity-related distortions. Patient-induced B0-susceptibility changes were investigated via B0-field-mapping in ten volunteers. Patients were positioned in RT-setup using a 3D-printed insert for the head/neck-coil that was tested for sufficient signal-to-noise-ratio (SNR). The suitability of the MRI-system for detection of metastases was evaluated in eleven patients. In comparison to diagnostic images, acquired at ≥1.5 T, three physicians evaluated the detectability of metastases by counting them in low- and high-field-images, respectively. Results: The phantom measurements showed a high imaging fidelity after 3D-distortion-correction with (1.2 ± 0.9) mm geometric distortion in 10 cm radius from isocentre. At the edges remaining distortions were greater than at 1.5 T. The mean susceptibility-induced distortions in the head were (0.05 ± 0.05) mm and maximum 0.69 mm. SNR analysis showed that optimised positioning of RT-patients without signal loss in the head/neck-coil was possible with the RT-insert. No significant differences (p = 0.48) in detectability of metastases were found. Conclusion: The 0.55 T MRI system provided sufficiently geometrically accurate and high-resolution images that can be used for RT-planning for brain metastases. Hence, modern low-field MRI may contribute to simply access MRI for RT-planning after further investigations.

End-to-end testing for stereotactic radiotherapy including the development of a Multi-Modality phantom.

PURPOSE: A new insert for a commercially available end-to-end test phantom was designed and in-house manufactured by 3D printing. Subsequently, the insert was tested for different stereotactic radiation therapy workflows (SRS, SBRT, FSRT, and Multimet) also in comparison to the original insert. MATERIAL AND METHODS: Workflows contained imaging (MR, CT), treatment planning, positioning, and irradiation. Positioning accuracy was evaluated for non-coplanar x-ray, kV- and MV-CBCT systems, as well as surface guided radiation therapy. Dosimetric accuracy of the irradiation was measured with an ionization chamber at four different linear accelerators including dynamic tumor tracking for SBRT. RESULTS: CT parameters of the insert were within the specification. For MR images, the new insert allowed quantitative analysis of the MR distortion. Positioning accuracy of the phantom with the new insert using the imaging systems of the different linacs was < 1 mm/degree also for MV-CBCT and a non-coplanar imaging system which caused > 3 mm deviation with the original insert. Deviation of point dose values was <3% for SRS, FSRT, and SBRT for both inserts. For the Multimet plans deviations exceeded 10% because the ionization chamber was not positioned in each metastasis, but in the center of phantom and treatment plan. CONCLUSION: The in-house manufactured insert performed well in all steps of four stereotactic treatment end-to-end tests. Advantages over the commercially available alternative were seen for quantitative analysis of deformation correction in MR images, applicability for non-coplanar x-ray imaging, and dynamic tumor tracking.

Feasibility of artificial-intelligence-based synthetic computed tomography in a magnetic resonance-only radiotherapy workflow for brain radiotherapy: Two-way dose validation and 2D/2D kV-image-based positioning.

Background and purpose: Magnetic Resonance Imaging (MRI)-only workflow eliminates the MRI-computed tomography (CT) registration inaccuracy, which degrades radiotherapy (RT) treatment accuracy. For an MRI-only workflow MRI sequences need to be converted to synthetic-CT (sCT). The purpose of this study was to evaluate a commercially available artificial intelligence (AI)-based sCT generation for dose calculation and 2D/2D kV-image daily positioning for brain RT workflow. Materials and methods: T1-VIBE DIXON was acquired at the 1.5 T MRI for 26 patients in RT setup for sCTs generation. For each patient, a volumetric modulated arc therapy (VMAT) plan was optimized on the CT, then recalculated on the sCT; and vice versa. sCT-based digitally reconstructed radiographs (DRRs) were fused with stereoscopic X-ray images recorded as image guidance for clinical treatments. Dosimetric differences between planned/recalculated doses and the differences between the calculated and recorded clinical couch shift/rotation were evaluated. Results: Mean ΔD50 between planned/recalculated doses for target volumes ranged between -0.2 % and 0.2 %; mean ΔD50 and ΔD0.01ccm were -0.6 % and 1.6 % and -1.4 % and 1.0 % for organ-at-risks, respectively. Differences were tested for clinical equivalence using intervals ±2 % (dose), ±1mm (translation), and ±1° (rotation). Dose equivalence was found using ±2 % interval (p < 0.001). The median differences between lat./long./vert. couch shift between CT-based/sCT-based DRRs were 0.3 mm/0.2 mm/0.3 mm (p < 0.05); median differences between lat./long./vert. couch rotation were -1.5°/0.1°/0.1° (after improvement of RT setup: -0.4°/-0.1°/-0.4°, p < 0.05). Conclusions: This in-silico study showed that the AI-based sCT provided equivalent results to the CT for dose calculation and daily stereoscopic X-ray positioning when using an optimal RT setup during MRI acquisition.

Accuracy of MRI-CT registration in brain stereotactic radiotherapy: Impact of MRI acquisition setup and registration method.

BACKGROUND: In MR-based radiotherapy (RT), MRI images are co-registered to the planning CT to leverage MR image information for RT planning. Especially in brain stereotactic RT, where typical CTV-PTV margins are 1-2 mm, high registration accuracy is critical. Several factors influence the registration accuracy, including the acquisition setup during MR simulation and the registration methods. PURPOSE: In this work, the impact of the MRI acquisition setup and registration method was evaluated in the context of brain RT, both geometrically and dosimetrically. METHODS AND MATERIALS: MRI of 20 brain radiotherapy patients was acquired in two MRI acquisition setups (RT and diagnostic). Three different automatic registration tools provided by three treatment planning systems were used to rigidly register both MRIs and CT in addition to the clinical registration. Segmentation-based evaluation using Hausdorff Distance (HD)/Dice Similarity Coefficient and landmark-based evaluation were used as evaluation metrics. Dose-volume-histograms were evaluated for target volumes and various organs at risks. RESULTS: MRI acquisition in the RT setup provided a similar head extension as compared to the planning CT. The registration method had a more significant influence than the acquisition setup (Wilcoxon signed-rank test, p<0.05). When registering using a less optimal registration method, the RT setup improved the registration accuracy compared to the diagnostic setup (Difference: ΔMHD = 0.16 mm, ΔHDP95 = 0.64 mm, mean Euclidean distance (ΔmEuD) = 2.65 mm). Different registration methods and acquisition setups lead to the variation of the clinical DVH. Acquiring MRI in the RT setup can improve PTV and GTV coverage compared to the diagnostic setup. CONCLUSIONS: Both MRI acquisition setup and registration method influence the MRI-CT registration accuracy in brain RT patients geometrically and dosimetrically. MR-simulation in the RT setup assures optimal registration accuracy if automatic registration is impaired, and therefore recommended for brain RT.

Implementation of a dedicated 1.5 T MR scanner for radiotherapy treatment planning featuring a novel high-channel coil setup for brain imaging in treatment position.

PURPOSE: To share our experiences in implementing a dedicated magnetic resonance (MR) scanner for radiotherapy (RT) treatment planning using a novel coil setup for brain imaging in treatment position as well as to present developed core protocols with sequences specifically tuned for brain and prostate RT treatment planning. MATERIALS AND METHODS: Our novel setup consists of two large 18-channel flexible coils and a specifically designed wooden mask holder mounted on a flat tabletop overlay, which allows patients to be measured in treatment position with mask immobilization. The signal-to-noise ratio (SNR) of this setup was compared to the vendor-provided flexible coil RT setup and the standard setup for diagnostic radiology. The occurrence of motion artifacts was quantified. To develop magnetic resonance imaging (MRI) protocols, we formulated site- and disease-specific clinical objectives. RESULTS: Our novel setup showed mean SNR of 163 ± 28 anteriorly, 104 ± 23 centrally, and 78 ± 14 posteriorly compared to 84 ± 8 and 102 ± 22 anteriorly, 68 ± 6 and 95 ± 20 centrally, and 56 ± 7 and 119 ± 23 posteriorly for the vendor-provided and diagnostic setup, respectively. All differences were significant (p > 0.05). Image quality of our novel setup was judged suitable for contouring by expert-based assessment. Motion artifacts were found in 8/60 patients in the diagnostic setup, whereas none were found for patients in the RT setup. Site-specific core protocols were designed to minimize distortions while optimizing tissue contrast and 3D resolution according to indication-specific objectives. CONCLUSION: We present a novel setup for high-quality imaging in treatment position that allows use of several immobilization systems enabling MR-only workflows, which could reduce unnecessary dose and registration inaccuracies.

Magnetic resonance imaging for brain stereotactic radiotherapy : A review of requirements and pitfalls.

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.

Volumetric Regression in Brain Metastases After Stereotactic Radiotherapy: Time Course, Predictors, and Significance.

BACKGROUND: There 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. METHODS: Volumetric 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. RESULTS: Median 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. CONCLUSIONS: Volumetric 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.

Error detection using an electromagnetic tracking system in multi-catheter breast interstitial brachytherapy.

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.