Simultaneous radiosurgery for multiple brain metastases: technical overview of the UCLA experience

Purpose/objective(s) To communicate our institutional experience with single isocenter radiosurgery treatments for multiple brain metastases, including challenges with determining planning target volume (PTV) margins and resulting consequences, image-guidance translational and rotational tolerances, intra-fraction patient motion, and prescription considerations with larger PTV margins. Materials/methods Eight patient treatments with 51 targets were planned with various margins using Elements Multiple Brain Mets SRS treatment planning software (Brainlab, Munich, Germany). Forty-eight plans with 0 mm, 1 mm and 2 mm margins were created, including plans with variable margins, where targets more than 6 cm away from the isocenter were planned with larger margins. The dosimetric impact of the margins were analyzed with V5Gy, V8Gy, V10Gy, V12Gy values. Additionally, 12 patient motion data were analyzed to determine both the impact of the repositioning threshold and the distributions of the patient translational and rotational movements. Results The V5Gy, V8Gy, V10Gy, V12Gy volumes approximately doubled when margins change from 0 to 1 mm and tripled when change from 0 to 2 mm. With variable margins, the aggregated results are similar to results from plans using the lower of two margins, since only 12.2% of the targets were more than 6 cm away from the isocenter. With 0.5 mm re-positioning threshold, 57.4% of the time the patients are repositioned. Reducing the threshold to 0.25 mm results in 91.7% repositioning rate, due to limitations of the fusion algorithm and actual patient motion. The 90th percentile of translational movements in all directions is 0.7 mm, while the 90th percentile of rotational movements in all directions is 0.6 degrees. Median translations and rotations are 0.2 mm and 0.2 degrees, respectively. Conclusions Based on the data presented, we have switched our modus operandi from 2 to 1 mm PTV margins, with an eventual goal of using 0.5 and 1.0 mm variable margins when an automated margin assignment method becomes available. The 0.5 mm and 0.5 degrees repositioning thresholds are clinically appropriate with small residual patient movements.

Standardizing SPECT/CT dosimetry following radioembolization with yttrium-90 microspheres

Background Multiple post-treatment dosimetry methods are currently under investigation for Yttrium-90 ($$^{90}\hbox {Y}$$ 90 Y ) radioembolization. Within each methodology, a variety of dosimetric inputs exists that affect the final dose estimates. Understanding their effects is essential to facilitating proper dose analysis and crucial in the eventual standardization of radioembolization dosimetry. The purpose of this study is to investigate the dose differences due to different self-calibrations and mass density assignments in the non-compartmental and local deposition methods. A practical mean correction method was introduced that permits dosimetry in images where the quality is compromised by patient motion and partial volume effects. Methods Twenty-one patients underwent $$^{90}\hbox {Y}$$ 90 Y radioembolization and were imaged with SPECT/CT. Five different self-calibrations (FOV, Body, OAR, Liverlung, and Liver) were implemented and dosimetrically compared. The non-compartmental and local deposition method were used to perform dosimetry based on either nominal- or CT calibration-based mass densities. A mean correction method was derived assuming homogeneous densities. Cumulative dose volume histograms, linear regressions, boxplots, and Bland Altman plots were utilized for analysis. Results Up to 270% weighted dose difference was found between self-calibrations with mean dose differences up to 50 Gy in the liver and 23 Gy in the lungs. Between the local deposition and non-compartmental methods, the liver and lung had dose differences within 0.71 Gy and 20 Gy, respectively. The local deposition method’s nominal and CT calibration-based mass density implementations dosimetric metrics were within 1.4% in the liver and 24% in the lungs. The mean lung doses calculated with the CT method were shown to be inflated. The mean correction method demonstrated that the corrected mean doses were greater by up to $$\sim 5$$ ∼ 5 Gy in the liver and lower by up to $$\sim 12$$ ∼ 12 Gy in the lungs. Conclusions The OAR calibration may be utilized as a potentially more accurate and precise self-calibration. The non-compartmental method was found more comparable to the local deposition method in organs that were more homogeneous in mass densities. Due to the potential for inflated lung mean doses, the non-compartmental and local deposition method implemented with nominal mass densities is recommended for more consistent dosimetric results. If patient motion and partial volume effects are present in the liver, our practical correction method will calculate more representative doses in images suboptimal for dosimetry.

Robustness assessment of a novel 4D optimization approach for lung cancer radiotherapy

One of the main challenges to treatment of lung cancer with radiation therapy is the tumor motion due to respiration. Previously, a novel approach was developed to generate treatment plans which compensate for respiratory motion and its variations. The worst case method is based on combining two intensity maps from two 4D plans optimized on the two worst cases of motion variations. The worst case planning method was previously tested on simulated motion variations. The goal of this project was to further test the worst case approach on realistic patient motion variations and treatment planning data. Two approaches to combining worst case plans were investigated: the first method takes the average of the two intensity maps, and the second method takes the maximum intensity of the two intensity maps. The robustness of worst case plans was compared with ITV plans and nominal 4D plans on three different motion variation scenarios. Study 1 and 2 investigated the robustness of the worst case methods on amplitude variations and patient motion variations on simulated image data. Study 3 investigated the robustness of the worst case methods on patient motion variations using real patient image data. The average intensity worst case method was only robust to Study 3 motion variations. The maximum intensity worst case method, the margin based, and the nominal approaches were not robust to any of the motion variations. Further evaluation over a wide range of tumour sizes, motion amplitudes and variability is required to determine the clinical applicability of the worst case planning method.

Robustness assessment of a novel 4D optimization approach for lung cancer radiotherapy

One of the main challenges to treatment of lung cancer with radiation therapy is the tumor motion due to respiration. Previously, a novel approach was developed to generate treatment plans which compensate for respiratory motion and its variations. The worst case method is based on combining two intensity maps from two 4D plans optimized on the two worst cases of motion variations. The worst case planning method was previously tested on simulated motion variations. The goal of this project was to further test the worst case approach on realistic patient motion variations and treatment planning data. Two approaches to combining worst case plans were investigated: the first method takes the average of the two intensity maps, and the second method takes the maximum intensity of the two intensity maps. The robustness of worst case plans was compared with ITV plans and nominal 4D plans on three different motion variation scenarios. Study 1 and 2 investigated the robustness of the worst case methods on amplitude variations and patient motion variations on simulated image data. Study 3 investigated the robustness of the worst case methods on patient motion variations using real patient image data. The average intensity worst case method was only robust to Study 3 motion variations. The maximum intensity worst case method, the margin based, and the nominal approaches were not robust to any of the motion variations. Further evaluation over a wide range of tumour sizes, motion amplitudes and variability is required to determine the clinical applicability of the worst case planning method.

Influence of patient motion on quantitative accuracy in cardiac 15O-water positron emission tomography

Background Patient motion is a common problem during cardiac PET. The purpose of the present study was to investigate to what extent motions influence the quantitative accuracy of cardiac 15O-water PET/CT and to develop a method for automated motion detection. Method Frequency and magnitude of motion was assessed visually using data from 50 clinical 15O-water PET/CT scans. Simulations of 4 types of motions with amplitude of 5 to 20 mm were performed based on data from 10 scans. An automated motion detection algorithm was evaluated on clinical and simulated motion data. MBF and PTF of all simulated scans were compared to the original scan used as reference. Results Patient motion was detected in 68% of clinical cases by visual inspection. All observed motions were small with amplitudes less than half the LV wall thickness. A clear pattern of motion influence was seen in the simulations with a decrease of myocardial blood flow (MBF) in the region of myocardium to where the motion was directed. The perfusable tissue fraction (PTF) trended in the opposite direction. Global absolute average deviation of MBF was 3.1% ± 1.8% and 7.3% ± 6.3% for motions with maximum amplitudes of 5 and 20 mm, respectively. Automated motion detection showed a sensitivity of 90% for simulated motions ≥ 10 mm but struggled with the smaller (≤ 5 mm) simulated (sensitivity 45%) and clinical motions (accuracy 48%). Conclusion Patient motion can impair the quantitative accuracy of MBF. However, at typically occurring levels of patient motion, effects are similar to or only slightly larger than inter-observer variability, and downstream clinical effects are likely negligible.

Multi-Channel RF Supervision Module for Thermal Magnetic Resonance Based Cancer Therapy

Glioblastoma multiforme (GBM) is the most lethal and common brain tumor. Combining hyperthermia with chemotherapy and/or radiotherapy improves the survival of GBM patients. Thermal magnetic resonance (ThermalMR) is a hyperthermia variant that exploits radio frequency (RF)-induced heating to examine the role of temperature in biological systems and disease. The RF signals’ power and phase need to be supervised to manage the formation of the energy focal point, accurate thermal dose control, and safety. Patient position during treatment also needs to be monitored to ensure the efficacy of the treatment and avoid damages to healthy tissue. This work reports on a multi-channel RF signal supervision module that is capable of monitoring and regulating RF signals and detecting patient motion. System characterization was performed for a broad range of frequencies. Monte-Carlo simulations were performed to examine the impact of power and phase errors on hyperthermia performance. The supervision module’s utility was demonstrated in characterizing RF power amplifiers and being a key part of a feedback control loop regulating RF signals in heating experiments. Electromagnetic field simulations were conducted to calculate the impact of patient displacement during treatment. The supervision module was experimentally tested for detecting patient motion to a submillimeter level. To conclude, this work presents a cost-effective RF supervision module that is a key component for a hyperthermia hardware system and forms a technological basis for future ThermalMR applications.