Estimating intrafraction tumor motion during fiducial-based liver stereotactic radiotherapy via an iterative closest point (ICP) algorithm

Accuracy of robotic radiosurgery in renal cell carcinoma

PURPOSE

Although emerging clinical evidence supports robotic radiosurgery as a highly effective treatment option for renal cell carcinoma (RCC) less than 4 cm in diameter, delivery uncertainties and associated target volume margins have not been studied in detail. We assess intrafraction tumor motion patterns and accuracy of robotic radiosurgery in renal tumors with real-time respiratory tracking to optimize treatment margins.

METHODS

Delivery log files from 165 consecutive treatments of RCC were retrospectively analyzed. Five components were considered for planning target volume (PTV) margin estimation: (a) The model error from the correlation model between patient breath and tumor motion, (b) the prediction error from an algorithm predicting the patient breathing pattern, (c) the targeting error from the treatment robot, (d) the inherent total accuracy of the system for respiratory motion tracking, and (e) the margin required to cover potential target rotation, simulated with PTV rotations up to 10°.

RESULTS

The median tumor motion was 10.5 mm, 2.4 mm and 4.4 mm in the superior-inferior, left-right, and anterior-posterior directions, respectively. The root of the sum of squares of all contributions to the system's inaccuracy results in a minimum PTV margin of 4.3 mm, 2.6 mm and 3.0 mm in the superior-inferior, left-right and anterior-posterior directions, respectively, assuming optimal fiducial position and neglecting target deformation.

CONCLUSIONS

We have assessed kidney motion and derived PTV margins for the treatment of RCC with robotic radiosurgery, which helps to deliver renal treatments in a more consistent manner and potentially further improve outcomes.

A markerless beam's eye view tumor tracking algorithm based on unsupervised deformable registration learning framework of VoxelMorph in medical image with partial data

PURPOSE

To propose an unsupervised deformable registration learning framework-based markerless beam's eye view (BEV) tumor tracking algorithm for the inferior quality megavolt (MV) images with occlusion and deformation.

METHODS

Quality assurance (QA) plans for thorax phantom were delivered to the linear accelerator with artificially treatment offsets. Electronic portal imaging device (EPID) images (682 in total) and corresponding digitally reconstructed radiograph (DRR) were gathered as the moving and fixed image pairs, which were randomly divided into training and testing set in a ratio of 0.7:0.3 to train a non-rigid registration model with Voxelmorph. Simultaneously, 533 pairs of patient images from 21 lung tumor plans were acquired for tumor tracking investigation to offer quantifiable tumor motion data. Tracking error and image similarity measures were employed to evaluate the algorithm's accuracy.

RESULTS

The tracking algorithm can handle image registration with non-rigid deformation and losses ranging from 10 % to 80 %. The tracking errors in the phantom study were below 3 mm in about 86.8 % of cases, and below 2 mm in about 80 % of cases. The normalized mutual information (NMI) changes from 1.182 ± 0.024 to 1.198 ± 0.024 (p < 0.005). The patient target had an average translation of 3.784 mm and a maximum comprehensive displacement value of 7.455 mm. NMI of patient images changes from 1.209 ± 0.027 to 1.217 ± 0.026 (p < 0.005), indicating the presence of non-negligible non-rigid deformation.

CONCLUSIONS

The study provides a robust markerless tumor tracking algorithm for multi-modal, partial data and inferior quality image processing.

Quantifying 6D tumor motion and calculating PTV margins during liver stereotactic radiotherapy with fiducial tracking

Objective

Our study aims to estimate intra-fraction six-dimensional (6D) tumor motion with rotational correction and the related correlations between motions of different degrees of freedom (DoF), as well as quantify sufficient anisotropic clinical target volume (CTV) to planning target volume (PTV) margins during stereotactic body radiotherapy (SBRT) of liver cancer with fiducial tracking technique.

Methods

A cohort of 12 patients who were implanted with 3 or 4 golden markers were included in this study, and 495 orthogonal kilovoltage (kV) pairs of images acquired during the first fraction were used to extract the spacial position of each golden marker. Translational and rotational motions of tumor were calculated based on the marker coordinates by using an iterative closest point (ICP) algorithm. Moreover, the Pearson product-moment correlation coefficients (r) were applied to quantify the correlations between motions with different degrees of freedom (DoFs). The population mean displacement (MP¯), systematic error (Σ) and random error (σ) were obtained to calculate PTV margins based on published recipes.

Results

The mean translational variability of tumors were 0.56, 1.24 and 3.38 mm in the left-right (LR, X), anterior-posterior (AP, Y), and superior-inferior (SI, Z) directions, respectively. The average rotational angles θX , θY and θZ around the three coordinate axes were 0.88, 1.24 and 1.12, respectively. (|r|&gt;0.4) was obtainted between Y -Z , Y - θZ , Z -θZ and θX - θY . The PTV margins calculated based on 13 published recipes in X, Y, and Z directions were 1.08, 2.26 and 5.42 mm, and the 95% confidence interval (CI) of them were (0.88,1.28), (1.99,2.53) and (4.78,6.05), respectively.

Conclusions

The maximum translational motion was in SI direction, and the largest correlation coefficient of Y-Z was obtained. We recommend margins of 2, 3 and 7 mm in LR, AP and SI directions, respectively.

Analysis of the amplitude changes and baseline shifts of respiratory motion using intra-fractional CBCT in liver stereotactic body radiation therapy

PURPOSE

Using intra-fractional cone-beam CT (CBCT) to evaluate the amplitude changes and baseline shifts of respiratory motion in liver stereotactic body radiation therapy (SBRT).

METHODS

The amplitude changes and baseline shifts of respiratory motion for 24 liver patients were evaluated by the four-dimensional (4D) CT, inter- and intra-fractional CBCT. The difference of the average liver position errors among all treatment fractions and the 4D CT representthe baseline shifts. According to the baseline shifts, the ITV to PTV margin was recalculated and the plan was re-designed to compare the dosimetric variation.

RESULTS

The systematic and random errors of the baseline shifts for intra-fractional CBCT in the left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions were 0.99/1.60 mm, 2.03/2.46 mm, and 1.02/2.07 mm, respectively. The new ITV to PTV margins should be 4.0 mm, 7.0 mm, and 4.0 mm, respectively. The amplitude change of motion between the 4D CT and the intra-fractional CBCT was 1.03 ± 4.35 mm, with 31% of fractions exceeding 5 mm. To achieve the same dose coverage of the new PTV, the D_mean, V50, V40, V30, V25 of normal liver and maximum dose of the duodenum were significantly different.

CONCLUSIONS

Significant amplitude changes and baseline shifts of motion occurred during dose delivery compared with those in 4D CT. Using the ITV to PTV margin of 4.0 mm (LR), 7.0 mm (SI), and 4.0 mm (AP) can ensure the target dose coverage and keep the dose constrain of normal tissues at an acceptable level.

A systematic review and meta-analysis of liver tumor position variability during SBRT using various motion management and IGRT strategies

PURPOSE

To suggest PTV margins for liver SBRT with different motion management strategies based on a systematic review and meta-analysis.

METHODS

In accordance with Preferred-Reporting-Items-for-Systematic-Reviews-and-Meta-Analyses (PRISMA), a systematic review in PubMed, Embase and Medline databases was performed for liver tumor position variability. From an initial 533 studies published before October 2020, 36 studies were categorized as 18 free-breathing (FB; n_patients = 401), 9 abdominal compression (AC; n_patients = 145) and 9 breath-hold (BH; n_patients = 126). A meta-analysis was performed on inter- and intra-fraction position variability to report weighted-mean with 95% confidence interval (CI₉₅) in superior-inferior (SI), left-right (LR) and anterior-posterior (AP) directions. Furthermore, weighted-mean ITV margins were computed for FB (n_studies = 15, n_patients = 373) and AC (n_studies = 6, n_patients = 97) and PTV margins were computed for FB (n_studies = 6, n_patients = 95), AC (n_studies = 7, n_patients = 106) and BH (n_studies = 8, n_patients = 133).

RESULTS

The FB weighted-mean intra-fraction variability, ITV margins and weighted-standard-deviation in mm were SI-9.7, CI₉₅ = 9.3-10.1, 13.5 ± 4.9; LR-5.4, CI₉₅ = 5.3-5.6, 7.3 ± 7.9; and AP-4.2, CI₉₅ = 4.0-4.4, 6.3 ± 7.6. The inter-fraction-based results were SI-4.7, CI₉₅ = 4.3-5.1, 5.7 ± 1.7; LR-1.4, CI₉₅ = 1.1-1.6, 3.6 ± 2.7; and AP-2.8, CI₉₅ = 2.5-3.1, 4.8 ± 2.1. For AC intra-fraction results in mm were SI-1.8, CI₉₅ = 1.6-2.0, 2.6 ± 1.2; LR-0.7, CI₉₅ = 0.6-0.8, 1.7 ± 1.5; and AP-0.9, CI₉₅ = 0.8-1.0, 1.9 ± 1.7. The inter-fraction results were SI-2.6, CI₉₅ = 2.3-3.0, 5.2 ± 2.9; LR-1.9, CI₉₅ = 1.7-2.1, 4.0 ± 2.2; and AP-2.9, CI₉₅ = 2.5-3.2, 5.8 ± 2.7. For BH the inter-fraction variability, and the weighted-mean PTV margins and weighted-standard-deviation in mm were SI-2.4, CI₉₅ = 2.1-2.7, 5.6 ± 2.9; LR-1.8, CI₉₅ = 1.3-2.2, 5.5 ± 1.7; and AP-1.4; CI₉₅ = 1.2-1.7, 6.1 ± 2.1.

CONCLUSION

Our meta-analysis suggests a symmetric weighted-mean PTV margin of 6 mm might be appropriate for BH. For AC and FB, asymmetric PTV margins (weighted-mean margin of 4 mm (AP), 6 mm (SI/LR)) might be appropriate. For FB, if larger (>ITV margin) intra-fraction variability observed, the additional intra- and inter-fraction variability should be accounted in the PTV margin.

The status of medical physics in radiotherapy in China

PURPOSE

To present an overview of the status of medical physics in radiotherapy in China, including facilities and devices, occupation, education, research, etc. MATERIALS AND METHODS: The information about medical physics in clinics was obtained from the 9-th nationwide survey conducted by the China Society for Radiation Oncology in 2019. The data of medical physics in education and research was collected from the publications of the official and professional organizations.

RESULTS

By 2019, there were 1463 hospitals or institutes registered to practice radiotherapy and the number of accelerators per million population was 1.5. There were 4172 medical physicists working in clinics of radiation oncology. The ratio between the numbers of radiation oncologists and medical physicists is 3.51. Approximately, 95% of medical physicists have an undergraduate or graduate degrees in nuclear physics and biomedical engineering. 86% of medical physicists have certificates issued by the Chinese Society of Medical Physics. There has been a fast growth of publications by authors from mainland of China in the top international medical physics and radiotherapy journals since 2018.

CONCLUSIONS

Demand for medical physicists in radiotherapy increased quickly in the past decade. The distribution of radiotherapy facilities in China became more balanced. High quality continuing education and training programs for medical physicists are deficient in most areas. The role of medical physicists in the clinic has not been clearly defined and their contributions have not been fully recognized by the community.

Validation of a 4D-MRI guided liver stereotactic body radiation therapy strategy for implementation on the MR-linac

Purpose. Accurate tumor localization for image-guided liver stereotactic body radiation therapy (SBRT) is challenging due to respiratory motion and poor tumor visibility on conventional x-ray based images. Novel integrated MRI and radiotherapy systems enable direct in-room tumor visualization, potentially increasing treatment accuracy. As these systems currently do not provide a 4D image-guided radiotherapy strategy, we developed a 4D-MRI guided liver SBRT workflow and validated all steps for implementation on the Unity MR-linac.Materials and Methods. The proposed workflow consists of five steps: (1) acquisition of a daily 4D-MRI scan, (2) 4D-MRI to mid-position planning-CT rigid tumor registration, (3) calculation of daily tumor midP misalignment, (4) plan adaptation using adapt-to-position (ATP) with segment-weights optimization and (5) adapted plan delivery. The workflow was first validated in a motion phantom, performing regular motion at different baselines (±5 to ±10 mm) and patient-derived respiratory signals with varying degrees of irregularity. 4D-MRI derived respiratory signals and 4D-MRI to planning CT registrations were compared to the phantom input, and gamma and dose-area-histogram analyses were performed on the delivered dose distributions on film. Additionally, 4D-MRI to CT registration performance was evaluated in patient images using the full-circle method (transitivity analysis). Plan adaption was further analyzedin-silicoby creating adapted treatment plans for 15 patients with oligometastatic liver disease.Results. Phantom trajectories could be reliably extracted from 4D-MRI scans and 4D-MRI to CT registration showed submillimeter accuracy. The DAH-analysis demonstrated excellent coverage of the dose evaluation structures GTV and GTV_TD. The median daily rigid 4D-MRI to midP-CT registration precision in patient images was <2 mm. The ATP strategy restored the target dose without increased exposure to the OARs and plan quality was independent from 3D shift distance in the range of 1-26 mm.Conclusions. The proposed 4D-MRI guided strategy showed excellent performance in all workflow tests in preparation of the clinical introduction on the Unity MR-linac.

Quantification of Intrafraction and Interfraction Tumor Motion Amplitude and Prediction Error for Different Liver Tumor Trajectories in Cyberknife Synchrony Tracking

PURPOSE

To research the fiducial-based, real-time tracking intrafraction (during the fraction [intra-]) and interfraction (between fractions [inter-]) tumor respiration amplitude, motion trajectory, and prediction error and quantify their relationships for different types of motion trajectories during Cyberknife-based stereotactic ablation radiotherapy.

METHODS AND MATERIALS

Twelve patients with liver tumors were treated using a Cyberknife system, and 58 fractions were involved in this study. Real-time target motion tracking data were extracted and transformed from the robot coordinate system into the patient coordinate system by the rotation matrix. Only the time sessions of the beam on were studied according to the data information generated from the Cyberknife motion tracking system. The motion correlation model between the external marker signal and internal fiducial position was built to present the type of motion trajectory.

RESULTS

Using the correlation model as a function of external marker signal and internal fiducial position, we knew 4 motion trajectories mainly existed for liver cancer patients as follows: perfect linearity (group I), simple linearity (group II), hysteresis (group III), and area respiratory (group IV) patterns. More than half of the patients had a linear breathing trajectory. Analyzing all patients together, the intra-amplitudes were slightly less than those of the inter-amplitudes. The amplitude from large to small was in the superior-inferior, left-right and anterior-posterior directions, regardless of inter- and intra-amplitudes. Then, patients with a larger peak-to-peak have a larger standard deviation of amplitude and a larger amplitude in all fractions/sessions. The prediction errors of the linear motion trajectory were generally less than 1 mm. The prediction errors of the regular hysteresis breathing model were smaller than those of the irregular hysteresis model. Scattered breathing would result in a larger tracking error, such as the area respiratory trajectory. It was logical that prediction errors were larger for patients who showed much variation in their breathing amplitude.

CONCLUSIONS

This paper showed that the liver motion trajectory model included perfect linearity, sample linearity, hysteresis, and area. The linear motion trajectory presented the minimum tracking error and the best stability, and the hysteresis and area trajectory were the worst. Therefore, breathing management, including respiration training, control, and evaluation of motion trajectory in all directions, was significantly necessary during liver SABR treatment.

Image quality of 4D in-treatment CBCT acquired during lung SBRT using FFF beam: a phantom study

Background

Rotational beam delivery enables concurrent acquisition of cone-beam CT (CBCT), thereby facilitating further geometric verification of patient setup during radiation treatment. However, it is challenging to acquire CBCT during stereotactic body radiation therapy (SBRT) using flattening-filter free X-ray beams, in which a high radiation dose is delivered. This study presents quantitative evaluation results of the image quality in four-dimensional (4D) in-treatment CBCT acquired during SBRT delivery.

Methods

The impact of megavoltage (MV) scatter and acquisition parameters on the image quality was evaluated using Catphan 503 and XSight lung tracking phantoms. The in-treatment CBCT images of the phantoms were acquired while delivering 16 SBRT plans. The uniformity, contrast, and contrast-to-noise ratio (CNR) of the in-treatment CBCT images were calculated and compared to those of CBCT images acquired without SBRT delivery. Furthermore, the localizing accuracy of the moving target in the XSight lung phantom was evaluated for 10 respiratory phases.

Results

The CNR of the 3D-reconstucted Catphan CBCT images was reduced from 6.3 to 2.6 due to the effect of MV treatment scatter. Both for the Catphan and XSight phantoms, the CBCT image quality was affected by the tube current and monitor units (MUs) of the treatment plan. The lung target in the XSight tracking phantom was most visible for extreme phases; the mean CNRs of the lung target in the in-treatment CBCT images (with 40 mA tube current) across the SBRT plans were 3.2 for the end-of-exhalation phase and 3.0 for the end-of-inhalation phase. The lung target was localized with sub-millimeter accuracy for the extreme respiratory phases.

Conclusions

Full-arc acquisition with an increased tube current (e.g. 40 mA) is recommended to compensate for degradation in the CBCT image quality due to unflattened MV beam scatter. Acquiring in-treatment CBCT with a high-MU treatment beam is also suggested to improve the resulting CBCT image quality.