Data-driven gated positron emission tomography/computed tomography for radiotherapy.

Purpose: Software-based data-driven gated (DDG) positron emission tomography/computed tomography (PET/CT) has replaced hardware-based 4D PET/CT. The purpose of this article was to review DDG PET/CT, which could improve the accuracy of treatment response assessment, tumor motion evaluation, and target tumor contouring with whole-body (WB) PET/CT for radiotherapy (RT). Material and methods: This review covered the topics of 4D PET/CT with hardware gating, advancements in PET instrumentation, DDG PET, DDG CT, and DDG PET/CT based on a systematic literature review. It included a discussion of the large axial field-of-view (AFOV) PET detector and a review of the clinical results of DDG PET and DDG PET/CT. Results: DDG PET matched or outperformed 4D PET with hardware gating. DDG CT was more compatible with DDG PET than 4D CT, which required hardware gating. DDG CT could replace 4D CT for RT. DDG PET and DDG CT for DDG PET/CT can be incorporated in a WB PET/CT of less than 15 min scan time on a PET/CT scanner of at least 25 cm AFOV PET detector. Conclusions: DDG PET/CT could correct the misregistration and tumor motion artifacts in a WB PET/CT and provide the quantitative PET and tumor motion information of a registered PET/CT for RT.

Treatment of Central Nervous System Tumors on Combination MR-Linear Accelerators: Review of Current Practice and Future Directions.

Magnetic resonance imaging (MRI) provides excellent visualization of central nervous system (CNS) tumors due to its superior soft tissue contrast. Magnetic resonance-guided radiotherapy (MRgRT) has historically been limited to use in the initial treatment planning stage due to cost and feasibility. MRI-guided linear accelerators (MRLs) allow clinicians to visualize tumors and organs at risk (OARs) directly before and during treatment, a process known as online MRgRT. This novel system permits adaptive treatment planning based on anatomical changes to ensure accurate dose delivery to the tumor while minimizing unnecessary toxicity to healthy tissue. These advancements are critical to treatment adaptation in the brain and spinal cord, where both preliminary MRI and daily CT guidance have typically had limited benefit. In this narrative review, we investigate the application of online MRgRT in the treatment of various CNS malignancies and any relevant ongoing clinical trials. Imaging of glioblastoma patients has shown significant changes in the gross tumor volume over a standard course of chemoradiotherapy. The use of adaptive online MRgRT in these patients demonstrated reduced target volumes with cavity shrinkage and a resulting reduction in radiation dose to uninvolved tissue. Dosimetric feasibility studies have shown MRL-guided stereotactic radiotherapy (SRT) for intracranial and spine tumors to have potential dosimetric advantages and reduced morbidity compared with conventional linear accelerators. Similarly, dosimetric feasibility studies have shown promise in hippocampal avoidance whole brain radiotherapy (HA-WBRT). Next, we explore the potential of MRL-based multiparametric MRI (mpMRI) and genomically informed radiotherapy to treat CNS disease with cutting-edge precision. Lastly, we explore the challenges of treating CNS malignancies and special limitations MRL systems face.

Development and evaluation of ultrasound image tracking technology based on Mask R-CNN applied to respiratory motion compensation system.

Background: For respiration induced tumor displacement during a radiation therapy, a common method to prevent the extra radiation is image-guided radiation therapy. Moreover, mask region-based convolutional neural networks (Mask R-CNN) is one of the state-of-the-art (SOTA) object detection frameworks capable of conducting object classification, localization, and pixel-level instance segmentation. Methods: We developed a novel ultrasound image tracking technology based on Mask R-CNN for stable tracking of the detected diaphragm motion and applied to the respiratory motion compensation system (RMCS). For training Mask R-CNN, 1800 ultrasonic images of the human diaphragm are collected. Subsequently, an ultrasonic image tracking algorithm was developed to compute the mean pixel coordinates of the diaphragm detected by Mask R-CNN. These calculated coordinates are then utilized by the RMCS for compensation purposes. The tracking similarity verification experiment of mask ultrasonic imaging tracking algorithm (M-UITA) is performed. Results: The correlation between the input signal and the signal tracked by M-UITA was evaluated during the experiment. The average discrete Fréchet distance was less than 4 mm. Subsequently, a respiratory displacement compensation experiment was conducted. The proposed method was compared to UITA, and the compensation rates of three different respiratory signals were calculated and compared. The experimental results showed that the proposed method achieved a 6.22% improvement in compensation rate compared to UITA. Conclusions: This study introduces a novel method called M-UITA, which offers high tracking precision and excellent stability for monitoring diaphragm movement. Additionally, it eliminates the need for manual parameter adjustments during operation, which is an added advantage.

Extracting lung contour deformation features with deep learning for internal target motion tracking: a preliminary study.

Objective. To propose lung contour deformation features (LCDFs) as a surrogate to estimate the thoracic internal target motion, and to report their performance by correlating with the changing body using a cascade ensemble model (CEM). LCDFs, correlated to the respiration driver, are employed without patient-specific motion data sampling and additional training before treatment.Approach. LCDFs are extracted by matching lung contours via an encoder-decoder deep learning model. CEM estimates LCDFs from the currently captured body, and then uses the estimated LCDFs to track internal target motion. The accuracy of the proposed LCDFs and CEM were evaluated using 48 targets' motion data, and compared with other published methods.Main results. LCDFs estimated the internal targets with a localization error of 2.6 ± 1.0 mm (average ± standard deviation). CEM reached a localization error of 4.7 ± 0.9 mm and a real-time performance of 256.9 ± 6.0 ms. With no internal anatomy knowledge, they achieved a small accuracy difference (of 0.34∼1.10 mm for LCDFs and of 0.43∼1.75 mm for CEM at the 95% confidence level) with a patient-specific lung biomechanical model and the deformable image registration models.Significance. The results demonstrated the effectiveness of LCDFs and CEM on tracking target motion. LCDFs and CEM are non-invasive, and require no patient-specific training before treatment. They show potential for broad applications.

A comprehensive quality assurance program for four-dimensional computed tomography in radiotherapy.

This study aimed to develop and validate a comprehensive, reproducible and automatic 4DCT Quality Assurance (QA) workflow (QAMotion) that evaluates image accuracy across various regular and irregular breathing patterns. Volume and amplitude deviations, CT number accuracy, and spatial integrity were used as evaluation metrics. For repeatability tests, tolerances were respected with a mean CT number deviation < 10 HU, volume deviation < 2% and diameter and amplitude deviation < 2 mm except for irregular amplitude curves for which an amplitude deviation up to 6 mm was measured. QAMotion was able to flag image artefacts for our clinical 4DCT system.

High-speed low-noise optical respiratory monitoring for spot scanning proton therapy.

PURPOSE: To investigate a novel optical markerless respiratory sensor for surface guided spot scanning proton therapy and to measure its main technical characteristics. METHODS: The main characteristics of the respiratory sensor including sensitivity, linearity, noise, signal-to-noise, and time delay were measured using a dynamic phantom and electrical measuring equipment on a laboratory stand. The respiratory signals of free breathing and deep-inspiration breath-hold patterns were acquired for various distances with a volunteer. A comparative analysis of this sensor with existing commercially available and experimental respiratory monitoring systems was carried out based on several criteria including principle of operation, patient contact, application to proton therapy, distance range, accuracy (noise, signal-to-noise ratio), and time delay (sampling rate). RESULTS: The sensor provides optical respiratory monitoring of the chest surface over a distance range of 0.4-1.2 m with the RMS noise of 0.03-0.60 mm, SNR of 40-15 dB (for motion with peak-to-peak of 10 mm), and time delay of 1.2 ± 0.2 ms. CONCLUSIONS: The investigated optical respiratory sensor was found to be appropriate to use in surface guided spot scanning proton therapy. This sensor combined with a fast respiratory signal processing algorithm may provide accurate beam control and a fast response in patients' irregular breathing movements. A careful study of correlation between the respiratory signal and 4DCT data of tumor position will be required before clinical implementation.

Stereotactic Magnetic Resonance-Guided Adaptive and Non-Adaptive Radiotherapy on Combination MR-Linear Accelerators: Current Practice and Future Directions.

Stereotactic body radiotherapy (SBRT) is an effective radiation therapy technique that has allowed for shorter treatment courses, as compared to conventionally dosed radiation therapy. As its name implies, SBRT relies on daily image guidance to ensure that each fraction targets a tumor, instead of healthy tissue. Magnetic resonance imaging (MRI) offers improved soft-tissue visualization, allowing for better tumor and normal tissue delineation. MR-guided RT (MRgRT) has traditionally been defined by the use of offline MRI to aid in defining the RT volumes during the initial planning stages in order to ensure accurate tumor targeting while sparing critical normal tissues. However, the ViewRay MRIdian and Elekta Unity have improved upon and revolutionized the MRgRT by creating a combined MRI and linear accelerator (MRL), allowing MRgRT to incorporate online MRI in RT. MRL-based MR-guided SBRT (MRgSBRT) represents a novel solution to deliver higher doses to larger volumes of gross disease, regardless of the proximity of at-risk organs due to the (1) superior soft-tissue visualization for patient positioning, (2) real-time continuous intrafraction assessment of internal structures, and (3) daily online adaptive replanning. Stereotactic MR-guided adaptive radiation therapy (SMART) has enabled the safe delivery of ablative doses to tumors adjacent to radiosensitive tissues throughout the body. Although it is still a relatively new RT technique, SMART has demonstrated significant opportunities to improve disease control and reduce toxicity. In this review, we included the current clinical applications and the active prospective trials related to SMART. We highlighted the most impactful clinical studies at various tumor sites. In addition, we explored how MRL-based multiparametric MRI could potentially synergize with SMART to significantly change the current treatment paradigm and to improve personalized cancer care.

Machine learning for predicting accuracy of lung and liver tumor motion tracking using radiomic features.

Background: Internal tumor motion is commonly predicted using external respiratory signals. However, the internal/external correlation is complex and patient-specific. The purpose of this study was to develop various models based on the radiomic features of computed tomography (CT) images to predict the accuracy of tumor motion tracking using external surrogates and to find accurate and reliable tracking algorithms. Methods: Images obtained from a total of 108 and 71 patients pathologically diagnosed with lung and liver cancers, respectively, were examined. Real-time position monitoring motion was fitted to tumor motion, and samples with fitting errors greater than 2 mm were considered positive. Radiomic features were extracted from internal target volumes of average intensity projections, and cross-validation least absolute shrinkage and selection operator (LassoCV) was used to conduct feature selection. Based on the radiomic features, a total of 26 separate models (13 for the lung and 13 for the liver) were trained and tested. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to assess performance. Relative standard deviation was used to assess stability. Results: Thirty-three and 22 radiomic features were selected for the lung and liver, respectively. For the lung, the AUC varied from 0.848 (decision tree) to 0.941 [support vector classifier (SVC), logistic regression]; sensitivity varied from 0.723 (extreme gradient boosting) to 0.848 [linear support vector classifier (linearSVC)]; specificity varied from 0.834 (gaussian naive bayes) to 0.936 [multilayer perceptron (MLP), wide and deep (W&D)]; and MLP and W&D had better performance and stability than the median. For the liver, the AUC varied from 0.677 [light gradient boosting machine (Light)] to 0.892 (logistic regression); sensitivity varied from 0.717 (W&D) to 0.862 (MLP); specificity varied from 0.566 (Light) to 0.829 (linearSVC); and logistic regression, MLP, and SVC had better performance and stability than the median. Conclusions: Respiratory-sensitive radiomic features extracted from CT images of lung and liver tumors were proved to contain sufficient information to establish an external/internal motion relationship. We developed a rapid and accurate method based on radiomics to classify the accuracy of monitoring a patient's external surface for lung and liver tumor tracking. Several machine learning algorithms-in particular, MLP-demonstrated excellent classification performance and stability.

Intrafraction tumor motion monitoring and dose reconstruction for liver pencil beam scanning proton therapy.

Background: Pencil beam scanning (PBS) proton therapy can provide highly conformal target dose distributions and healthy tissue sparing. However, proton therapy of hepatocellular carcinoma (HCC) is prone to dosimetrical uncertainties induced by respiratory motion. This study aims to develop intra-treatment tumor motion monitoring during respiratory gated proton therapy and combine it with motion-including dose reconstruction to estimate the delivered tumor doses for individual HCC treatment fractions. Methods: Three HCC-patients were planned to receive 58 GyRBE (n=2) or 67.5 GyRBE (n=1) of exhale respiratory gated PBS proton therapy in 15 fractions. The treatment planning was based on the exhale phase of a 4-dimensional CT scan. Daily setup was based on cone-beam CT (CBCT) imaging of three implanted fiducial markers. An external marker block (RPM) on the patient's abdomen was used for exhale gating in free breathing. This study was based on 5 fractions (patient 1), 1 fraction (patient 2) and 6 fractions (patient 3) where a post-treatment control CBCT was available. After treatment, segmented 2D marker positions in the post-treatment CBCT projections provided the estimated 3D motion trajectory during the CBCT by a probability-based method. An external-internal correlation model (ECM) that estimated the tumor motion from the RPM motion was built from the synchronized RPM signal and marker motion in the CBCT. The ECM was then used to estimate intra-treatment tumor motion. Finally, the motion-including CTV dose was estimated using a dose reconstruction method that emulates tumor motion in beam's eye view as lateral spot shifts and in-depth motion as changes in the proton beam energy. The CTV homogeneity index (HI) The CTV homogeneity index (HI) was calculated as D 2 %  -  D 98 % D 50 %   × 100 % . Results: The tumor position during spot delivery had a root-mean-square error of 1.3 mm in left-right, 2.8 mm in cranio-caudal and 1.7 mm in anterior-posterior directions compared to the planned position. On average, the CTV HI was larger than planned by 3.7%-points (range: 1.0-6.6%-points) for individual fractions and by 0.7%-points (range: 0.3-1.1%-points) for the average dose of 5 or 6 fractions. Conclusions: A method to estimate internal tumor motion and reconstruct the motion-including fraction dose for PBS proton therapy of HCC was developed and demonstrated successfully clinically.

Real-time motion monitoring using orthogonal cine MRI during MR-guided adaptive radiation therapy for abdominal tumors on 1.5T MR-Linac.

BACKGROUND: Real-time motion monitoring (RTMM) is necessary for accurate motion management of intrafraction motions during radiation therapy (RT). PURPOSE: Building upon a previous study, this work develops and tests an improved RTMM technique based on real-time orthogonal cine magnetic resonance imaging (MRI) acquired during magnetic resonance-guided adaptive RT (MRgART) for abdominal tumors on MR-Linac. METHODS: A motion monitoring research package (MMRP) was developed and tested for RTMM based on template rigid registration between beam-on real-time orthogonal cine MRI and pre-beam daily reference 3D-MRI (baseline). The MRI data acquired under free-breathing during the routine MRgART on a 1.5T MR-Linac for 18 patients with abdominal malignancies of 8 liver, 4 adrenal glands (renal fossa), and 6 pancreas cases were used to evaluate the MMRP package. For each patient, a 3D mid-position image derived from an in-house daily 4D-MRI was used to define a target mask or a surrogate sub-region encompassing the target. Additionally, an exploratory case reviewed for an MRI dataset of a healthy volunteer acquired under both free-breathing and deep inspiration breath-hold (DIBH) was used to test how effectively the RTMM using the MMRP can address through-plane motion (TPM). For all cases, the 2D T2/T1-weighted cine MRIs were captured with a temporal resolution of 200 ms interleaved between coronal and sagittal orientations. Manually delineated contours on the cine frames were used as the ground-truth motion. Common visible vessels and segments of target boundaries in proximity to the target were used as anatomical landmarks for reproducible delineations on both the 3D and the cine MRI images. Standard deviation of the error (SDE) between the ground-truth and the measured target motion from the MMRP package were analyzed to evaluate the RTMM accuracy. The maximum target motion (MTM) was measured on the 4D-MRI for all cases during free-breathing. RESULTS: The mean (range) centroid motions for the 13 abdominal tumor cases were 7.69 (4.71-11.15), 1.73 (0.81-3.05), and 2.71 (1.45-3.93) mm with an overall accuracy of <2 mm in the superior-inferior (SI), the left-right (LR), and the anterior-posterior (AP) directions, respectively. The mean (range) of the MTM from the 4D-MRI was 7.38 (2-11) mm in the SI direction, smaller than the monitored motion of centroid, demonstrating the importance of the real-time motion capture. For the remaining patient cases, the ground-truth delineation was challenging under free-breathing due to the target deformation and the large TPM in the AP direction, the implant-induced image artifacts, and/or the suboptimal image plane selection. These cases were evaluated based on visual assessment. For the healthy volunteer, the TPM of the target was significant under free-breathing which degraded the RTMM accuracy. RTMM accuracy of <2 mm was achieved under DIBH, indicating DIBH is an effective method to address large TPM. CONCLUSIONS: We have successfully developed and tested the use of a template-based registration method for an accurate RTMM of abdominal targets during MRgART on a 1.5T MR-Linac without using injected contrast agents or radio-opaque implants. DIBH may be used to effectively reduce or eliminate TPM of abdominal targets during RTMM.

Quantification of Lung Tumor Motion and Optimization of Treatment.

Background: Mobility of lung tumors is induced by respiration and causes inadequate dose coverage. Objective: This study quantified lung tumor motion, velocity, and stability for small (≤5 cm) and large (>5 cm) tumors to adapt radiation therapy techniques for lung cancer patients. Material and Methods: In this retrospective study, 70 patients with lung cancer were included that 50 and 20 patients had a small and large gross tumor volume (GTV). To quantify the tumor motion and velocity in the upper lobe (UL) and lower lobe (LL) for the central region (CR) and a peripheral region (PR), the GTV was contoured in all ten respiratory phases, using 4D-CT. Results: The amplitude of tumor motion was greater in the LL, with motion in the superior-inferior (SI) direction compared to the UL, with an elliptical motion for small and large tumors. Tumor motion was greater in the CR, rather than in the PR, by 63% and 49% in the UL compared to 50% and 38% in the LL, for the left and right lung. The maximum tumor velocity for a small GTV was 44.1 mm/s in the LL (CR), decreased to 4 mm/s for both ULs (PR), and a large GTV ranged from 0.4 to 9.4 mm/s. Conclusion: The tumor motion and velocity depend on the tumor localization and the greater motion was in the CR for both lobes due to heart contribution. The tumor velocity and stability can help select the best technique for motion management during radiation therapy.

Reduction of intrafraction pancreas motion using an abdominal corset compatible with proton therapy and MRI.

Background and purpose: Motion mitigation is of crucial importance in particle therapy (PT) of patients with abdominal tumors to ensure high-precision irradiation. Magnetic resonance imaging (MRI) is an excellent modality for target volume delineation and motion estimation of mobile soft-tissue tumors. Thus, the aims of this study were to develop an MRI- and PT-compatible abdominal compression device, to investigate its effect on pancreas motion reduction, and to evaluate patient tolerability and acceptance. Materials and methods: In a prospective clinical study, 16 patients with abdominal tumors received an individualized polyethylene-based abdominal corset. Pancreas motion was analyzed using time- and phase resolved MRI scans (orthogonal 2D-cine and 4D MRI) with and without compression by the corset. The pancreas was manually segmented in each MRI data set and the population-averaged center-of-mass motion in inferior-superior (IS), anterior-posterior (AP) and left-right (LR) directions was determined. A questionnaire was developed to investigate the level of patient acceptance of the corset, which the patients completed after acquisition of the planning computed tomography (CT) and MRI scans. Results: The corset was found to reduce pancreas motion predominantly in IS direction by on average 47 % - 51 % as found in the 2D-cine and 4D MRI data, respectively, while motion in the AP and LR direction was not significantly reduced. Most patients reported no discomfort when wearing the corset. Conclusion: An MRI- and PT-compatible individualized abdominal corset was presented, which substantially reduced breathing-induced pancreas motion and can be safely applied with no additional discomfort for the patients. The corset has been successfully integrated into our in-house clinical workflow for PT of tumors of the upper abdomen.

The dosimetric error due to uncorrected tumor rotation during real-time adaptive prostate stereotactic body radiation therapy.

BACKGROUND: During prostate stereotactic body radiation therapy (SBRT), prostate tumor translational motion may deteriorate the planned dose distribution. Most of the major advances in motion management to date have focused on correcting this one aspect of the tumor motion, translation. However, large prostate rotation up to 30° has been measured. As the technological innovation evolves toward delivering increasingly precise radiotherapy, it is important to quantify the clinical benefit of translational and rotational motion correction over translational motion correction alone. PURPOSE: The purpose of this work was to quantify the dosimetric impact of intrafractional dynamic rotation of the prostate measured with a six degrees-of-freedom tumor motion monitoring technology. METHODS: The delivered dose was reconstructed including (a) translational and rotational motion and (b) only translational motion of the tumor for 32 prostate cancer patients recruited on a 5-fraction prostate SBRT clinical trial. Patients on the trial received 7.25 Gy in a treatment fraction. A 5 mm clinical target volume (CTV) to planning target volume (PTV) margin was applied in all directions except the posterior direction where a 3 mm expansion was used. Prostate intrafractional translational motion was managed using a gating strategy, and any translation above the gating threshold was corrected by applying an equivalent couch shift. The residual translational motion is denoted as T r e s $T_{res}$ . Prostate intrafractional rotational motion R u n c o r r $R_{uncorr}$ was recorded but not corrected. The dose differences from the planned dose due to T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ , ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) and due to T r e s $T_{res}$ alone, ΔD( T r e s $T_{res}$ ), were then determined for CTV D98, PTV D95, bladder V6Gy, and rectum V6Gy. The residual dose error due to uncorrected rotation, R u n c o r r $R_{uncorr}$ was then quantified: Δ D R e s i d u a l $\Delta D_{Residual}$ = ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) - ΔD( T res ${T}_{\textit{res}}$ ). RESULTS: Fractional data analysis shows that the dose differences from the plan (both ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) and ΔD( T r e s $T_{res}$ )) for CTV D98 was less than 5% in all treatment fractions. ΔD( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) was larger than 5% in one fraction for PTV D95, in one fraction for bladder V6Gy, and in five fractions for rectum V6Gy. Uncorrected rotation, R u n c o r r $R_{uncorr}$ induced residual dose error, Δ D R e s i d u a l $\Delta D_{Residual}$ , resulted in less dose to CTV and PTV in 43% and 59% treatment fractions, respectively, and more dose to bladder and rectum in 51% and 53% treatment fractions, respectively. The cumulative dose over five fractions, ∑D( T r e s $T_{res}$ + R u n c o r r $R_{uncorr}$ ) and ∑D( T r e s $T_{res}$ ), was always within 5% of the planned dose for all four structures for every patient. CONCLUSIONS: The dosimetric impact of tumor rotation on a large prostate cancer patient cohort was quantified in this study. These results suggest that the standard 3-5 mm CTV-PTV margin was sufficient to account for the intrafraction prostate rotation observed for this cohort of patients, provided an appropriate gating threshold was applied to correct for translational motion. Residual dose errors due to uncorrected prostate rotation were small in magnitude, which may be corrected using different treatment adaptation strategies to further improve the dosimetric accuracy.

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 ( M P ¯ ), 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 θ X , θ Y and θ Z around the three coordinate axes were 0.88, 1.24 and 1.12, respectively. (|r|>0.4) was obtainted between Y -Z , Y - θ Z , Z -θ Z and θ X - θ Y . 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.

Association Between Internal Organ/Liver Tumor and External Surface Motion From Cine MR Images on an MRI-Linac.

Purposes/Objectives: Historically, motion correlation between internal tumor and external surrogates have been based on limited sets of X-ray or magnetic resonance (MR) images. With the recent clinical implementation of MR-guided linear accelerators, a vast quantity of continuous planar real-time MR imaging data is acquired. In this study, information was extracted from MR cine imaging during liver cancer treatments to establish associations between internal tumor/diaphragm and external surface/skin movement. Methods and Materials: This retrospective study used 305,644 MR image frames acquired over 118 treatment/imaging sessions of the first 23 liver cancer patients treated on an MRI-linac. 9 features were automatically determined on each MR image frame: Lung_Area, the posterior (Dia_Post), dome (Dia_Dome), and anterior (Dia_Ant) points of a diaphragmatic curve and the diaphragm curve point (Dia_Max), the chest (Chest) and the belly (Belly) skin points experiencing the maximum motion ranges; the superior-interior (SI) and posterior-anterior (PA) positions of a target. For every session, correlation analyses were performed twice among the 9 features: 1) over a breath-hold (BH) set and 2) on a pseudo free-breathing (PFB) generated by removing breath-holding frames. Results: 303,123 frames of images were successfully analyzed. For BH set analysis, correlation coefficients were as follows: 0.94 ± 0.07 between any two features among Dia_Post, Dia_Dome, Dia_Max, and Lung_Area; 0.95 ± 0.06 between SI and any feature among Dia_Post, Dia_Dome, Dia_Max, or Lung_Area; 0.76 ± 0.29 between SI and Belly (with 50% of correlations ≥ 0.87). The PFB set had 142,862 frames of images. For this set, correlation coefficients were 0.96 ± 0.06 between any two features among Dia_Post, Dia_Dome, Dia_Max, and Lung_Area; 0.95 ± 0.06 between SI and any feature among Dia_Post, Dia_Dome, Dia_Max, or Lung_Area; 0.80 ± 0.26 between SI and Belly (with 50% of correlations ≥ 0.91). Conclusion: Diaphragmatic motion as assessed by cine MR imaging is highly correlated with liver tumor motion. Belly vertical motion is highly correlated with liver tumor longitudinal motion in approximately half of the cases. More detailed analyses of those cases displaying weak correlations are in progress.

Stability and Reliability of Enhanced External-Internal Motion Correlation via Dynamic Phase-Shift Corrections Over 30-min Timeframe for Respiratory-Gated Radiotherapy.

To assess the stability of patient-specific phase shifts between external- and internal-respiratory motion waveforms, the reliability of enhanced external-internal correlation with phase-shift correction, and the feasibility of guiding respiratory-gated radiotherapy (RGRT) over 30 min. In this clinical feasibility investigation, external bellows and internal-navigator waveforms were simultaneously and prospectively acquired along with two four-dimensional magnetic resonance imaging (4DMRI) scans (6-15 m each) with 15-20 m intervals in 10 volunteers. A bellows was placed 5 cm inferior to the xiphoid to monitor abdominal motion, and an MR navigator was used to track the diaphragmatic motion. The mean phase-domain (MPD) method was applied, which combines three individual phase-calculating methods: phase-space oval fitting, principal component analysis, and analytic signal analysis, weighted by the reciprocal of their residual errors (RE) excluding outliers (RE >2σ). The time-domain cross-correlation (TCC) analysis was applied for comparison. Dynamic phase-shift correction was performed based on the phase shift detected on the fly within two 10 s moving datasets. Simulating bellows-triggered gating, the median and 95% confidence interval for the navigator's position at beam-on/beam-off and %harm (percentage of beam-on time outside the safety margin) were calculated. Averaged across all subjects, the mean phase shifts are found indistinguishable (p > .05) between scan 1 (55˚ ± 9˚) and scan 2 (59˚ ± 11˚). Using the MPD method the averaged correlation increases from 0.56 ± 0.22 to 0.85 ± 0.11 for scan 1 and from 0.47 ± 0.30 to 0.84 ± 0.08 for scan 2. The TCC correction results in similar results. After phase-shift correction, the number of cases that were suitable for amplitude gating (with <10%harm) increased from 2 to 17 out of 20 cases. A patient-specific, stable phase-shift between the external and internal motions was observed and corrected using the MPD and TCC methods, producing long-lasting enhanced motion correlation over 30m. Phase-shift correction offers a feasible strategy for improving the accuracy of tumor-motion prediction during RGRT.

Correlation of Optical Surface Respiratory Motion Signal and Internal Lung and Liver Tumor Motion: A Retrospective Single-Center Observational Study.

Purpose: Surface-guided radiation therapy (SGRT) application has limitations. This study aimed to explore the relationship between patient characteristics and their external/internal correlation to qualitatively assess the external/internal correlation in a particular patient. Methods: Liver and lung cancer patients treated with radiotherapy in our institution were retrospectively analyzed. The external/internal correlation were calculated with Spearman correlation coefficient (SCC) and SCC after support vector regression (SVR) fitting (SCCsvr). The relationship between the external/internal correlation and magnitudes of motion of the tumor and external marker (Ai, Ae), tumor volume Vt, patient age, gender, and tumor location were explored. Results: The external/internal motions of liver and lung cancer patients were strongly correlated in the S-I direction, with mean SCCsvr values of 0.913 and 0.813. The correlation coefficients between the external/internal correlations and the patients' characteristics (Ai, Ae, Vt, and age) were all smaller than 0.5; Ai, Ae and liver tumor volumes were positively correlated with the strength of the external/internal correlation, while lung tumor volumes and patient age were negative. The external/internal correlations in males and females were roughly equal, and the external/internal correlations in patients with peripheral lung cancers were stronger than those in patients with central lung cancers. Conclusion: The external/internal correlation shows great individual differences. The effects of Ai, Ae, Vt, and age are weakly to moderately correlated. Our results suggest the necessity of individualized assessment of patient's external/internal motion correlation prior to the application of SGRT technique for breath motion monitoring.

Stereotactic Ablative Radiotherapy Using CALYPSO® Extracranial Tracking for Intrafractional Tumor Motion Management-A New Potential Local Treatment for Unresectable Locally Advanced Pancreatic Cancer? Results from a Retrospective Study.

(1) Background: The aim of this study was to evaluate the efficacy and safety of SABR for LAPC using Calypso® Extracranial Tracking for intrafractional, fiducial-based motion management, to present this motion management technique, as there are yet no published data on usage of Calypso® during SABR for LAPC, and to report on our clinical outcomes. (2) Methods: Fifty-four patients were treated with SABR in one, three, or five fractions, receiving median BED10 = 112.5 Gy. Thirty-eight patients received systemic treatment. End points were OS, FFLP, PFS, and toxicity. Actuarial survival analysis and univariate analysis were investigated. (3) Results: Median follow-up was 20 months. Median OS was 24 months. One-year FFLP and one-year OS were 100% and 90.7%, respectively. Median PFS was 18 months, and one-year PFS was 72.2%. Twenty-five patients (46.3%) were alive at the time of analysis, and both median FU and OS for this subgroup were 26 months. No acute/late toxicity > G2 was reported. (4) Conclusions: SABR for LAPC using Calypso® presented as an effective and safe treatment and could be a promising local therapeutic option with very acceptable toxicity, either as a single treatment or in a multimodality regimen. Dose escalation to the tumor combined with systemic treatment could yield better clinical outcomes.

A novel bone suppression algorithm in intensity-based 2D/3D image registration for real-time tumor motion monitoring: Development and phantom-based validation.

BACKGROUND: Real-time tumor motion monitoring (TMM) is a crucial process for intra-fractional respiration management in lung cancer radiotherapy. Since the tumor can be partly or fully located behind the ribs, the TMM is challenging. PURPOSE: The aim of this work was to develop a bone suppression (BS) algorithm designed for real-time 2D/3D marker-less TMM to increase the visibility of the tumor when overlapping with bony structures and consequently to improve the accuracy of TMM. METHOD: A BS method was implemented in the in-house developed software for ultrafast intensity-based 2D/3D tumor registration (Fast Image-based Registration [FIRE]). The method operates on both, digitally reconstructed radiograph (DRR) and intra-fractional X-ray images. The bony structures are derived from computed tomography data by thresholding during ray-casting, and the resulting bone DRR is subtracted from intra-fractional X-ray images to obtain a soft-tissue-only image for subsequent tumor registration. The accuracy of TMM utilizing BS was evaluated within a retrospective phantom study with nine different 3D-printed tumor phantoms placed in the in-house developed Advanced Radiation DOSimetry (ARDOS) breathing phantom. A 24 mm craniocaudal tumor motion, including rib eclipses, was simulated, and X-ray images were acquired on the Elekta Versa HD Linac in the lateral and posterior-anterior directions. An error assessment for BS images was evaluated with respect to the ground truth tumor position. RESULTS: A total error (root mean square error) of 0.87 ± 0.23 mm and 1.03 ± 0.26 mm was found for posterior-anterior and lateral imaging; the mean time for BS was 8.03 ± 1.54 ms. Without utilizing BS, TMM failed in all X-ray images since the registration algorithm focused on the rib position due to the predominant intensity of this tissue within DRR and X-ray images. CONCLUSION: The BS algorithm developed and implemented improved the accuracy, robustness, and stability of real-time TMM in lung cancer in a phantom study, even in the case of rib interlude where normal tumor registration fails.

Real-time marker-less tumor tracking with TOF PET:in silicofeasibility study.

Purpose.Although positron emission tomography (PET) can provide a functional image of static tumors for RT guidance, it's conventionally very challenging for PET to track a moving tumor in real-time with a multiple frame/s sampling rate. In this study, we developed a novel method to enable PET based three-dimension (3D) real-time marker-less tumor tracking (RMTT) and demonstrated its feasibility with a simulation study.Methods.For each line-of-response (LOR) acquired, its positron-electron annihilation position is calculated based on the time difference between the two gamma interactions detected by the TOF PET detectors. The accumulation of these annihilation positions from data acquired within a single sampling frame forms a coarsely measured 3D distribution of positron-emitter radiotracer uptakes of the lung tumor and other organs and tissues (background). With clinically relevant tumor size and sufficient differential radiotracer uptake concentrations between the tumor and background, the high-uptake tumor can be differentiated from the surrounding low-uptake background in the measured distribution of radiotracer uptakes. With a volume-of-interest (VOI) that closely encloses the tumor, the count-weighted centroid of the annihilation positions within the VOI can be calculated as the tumor position. All these data processes can be conducted online. The feasibility of the new method was investigated with a simulated cardiac-torso digital phantom and stationary dual-panel TOF PET detectors to track a 28 mm diameter lung tumor with a 4:1 tumor-to-background18FDG activity concentration ratio.Results.The initial study shows TOF PET based RMTT can achieve <2.0 mm tumor tracking accuracy with 5 frame s-1sampling rate under the simulated conditions. In comparison, using reconstructed PET images to track a similar size tumor would require >30 s acquisition time to achieve the same tracking accuracy.Conclusion.With the demonstrated feasibility, the new method may enable TOF PET based RMTT for practical RT applications.