Browsing by Subject "SBRT"
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Item Open Access A Collimator Setting Optimization Algorithm for Dual-arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy(2019) Li, XinyiPurpose: To develop an automatic collimator setting optimization algorithm to improve dosimetric quality of pancreas Volumetric Modulated Arc Therapy (VMAT) plans for Stereotactic Body Radiation Therapy (SBRT).
Methods: Fifty-five pancreas SBRT cases were retrospectively studied. Different from the conventional practice of initializing collimator settings manually, the proposed algorithm simultaneously optimizes the collimator angles and jaw positions which are customized to the patient geometry. This algorithm includes two key steps: an iterative optimization algorithm via simulated annealing that generates a set of collimator settings candidates, and a scoring system that choose the final collimator settings based on organs-at-risk (OARs) sparing criteria and dose prescription. The scoring system penalizes 3 factors: 1) jaw opening ratio on Y direction to X direction; 2) unmodulated MLC area within the jaw aperture in a dynamic MLC sequence; 3) OAR shielding capability by MLC with MLC aperture control constraints. For validation, the other 16 pancreas SBRT cases were analyzed. Two dual-arc plans were generated for each validation case, an optimized plan (Planopt) and a conventional plan (Planconv). Each plan was generated by a same set of auxiliary planning structures and dose-volume-histogram (DVH) constraints in inverse optimization. Dosimetric results were analyzed and compared. All results were tested by Wilcoxon signed-rank tests.
Results: Both plan groups had no statistical differences in target dose coverage V95% (p=0.84) and Root Conformity Index (p=0.30). Mean doses of OARs were improved or comparable. In comparison with Planconv, Planopt reduced maximum dose (D0.03cc) to stomach (-49.5cGy, p=0.03), duodenum (-63.5cGy, p<0.01), and bowel (-62.5cGy, p=0.01). Planopt also showed lower modulation complexity score (p=0.02), which implies its higher modulation complexity of the dynamic MLC sequence.
Conclusions: The proposed collimator settings optimization algorithm successfully improved dosimetric performance for dual-arc VMAT plans in pancreas SBRT. The proposed algorithm was demonstrated with great clinical feasibility and readiness.
Item Open Access A current perspective on stereotactic body radiation therapy for pancreatic cancer.(Onco Targets Ther, 2016) Hong, Julian C; Czito, Brian G; Willett, Christopher G; Palta, ManishaPancreatic cancer is a formidable malignancy with poor outcomes. The majority of patients are unable to undergo resection, which remains the only potentially curative treatment option. The management of locally advanced (unresectable) pancreatic cancer is controversial; however, treatment with either chemotherapy or chemoradiation is associated with high rates of local tumor progression and metastases development, resulting in low survival rates. An emerging local modality is stereotactic body radiation therapy (SBRT), which uses image-guided, conformal, high-dose radiation. SBRT has demonstrated promising local control rates and resultant quality of life with acceptable rates of toxicity. Over the past decade, increasing clinical experience and data have supported SBRT as a local treatment modality. Nevertheless, additional research is required to further evaluate the role of SBRT and improve upon the persistently poor outcomes associated with pancreatic cancer. This review discusses the existing clinical experience and technical implementation of SBRT for pancreatic cancer and highlights the directions for ongoing and future studies.Item Open Access Application of TG-218 to SRS and SBRT Pre-Treatment Patient Specific QA(2020) Xia, YuqingAbstract
Purpose: Updated recommendations for pre-treatment QA of patient-specific intensity modulated radiation therapy (IMRT) and Volumetric modulated arc therapy (VMAT) quality assurance (QA) were recently published by the AAPM task group TG-218. While the traditionally most common QA analysis is to use a Gamma index with dose & spatial analysis criteria of 3% & 3mm, respectively, TG-218 recommends a tighter spatial tolerance of 2mm for standard IMRT QA, and that even tighter tolerances should be considered for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). Our purpose is to report our experience with applying the TG-218 recommendations to a large clinical SRS and SBRT program. In addition, a new SRS technique was recently developed at Duke, called Conformal Arc Informed Volumetric Modulated Arc Therapy (CAVMAT), which is designed to be less sensitive to configuration and delivery errors. We measured the agreement of CAVMAT for pre-treatment QA and compared it to the current standard (VMAT) to evaluate whether CAVMAT is more robust to delivery errors than VMAT.
Methods: We re-analyzed the pre-treatment QA with respect to the TG-218 recommendations. For Portal Dosimetry (Varian Medical Systems, Palo Alto, CA), this included IMRT brain (n=25) and SBRT / hypofractionated image guided radiotherapy (HIGRT) cases that utilize flattened photon beams (n=18). For Delta4 (ScandiDos, Madison, WI) this included single target SRS (n=24), multiple target SRS (n=25), SBRT cases using VMAT (n=74), and SBRT cases using IMRT with FFF photons (n=23). For ArcCHECK (Sun Nuclear, Melbourne, FL)), we take 25 single target VMAT SRS cases and 25 multiple target VMAT SRS cases. For SRS MapCHECK(Sun Nuclear, Melboume, FL), we analyze 10 multiple target VMAT SRS cases with 16 targets. A Gamma analysis was performed with 6 spatial/dose criteria combinations: 3%/3mm, 3%/2mm, 3%/1mm, 2%/1mm, 4%/1mm, 5%/1mm. We then calculated the TG-218 action limit and tolerance limit per plan type and compared to the “universal” TG-218 action limit of 90% having a Gamma <1.
To compare CAVMAT and VMAT, log file analysis and pre-treatment QA was performed for 10 patients with 20 plans (10 VMAT, 10 CAVMAT) with 46 targets in total. 10 VMAT plans were re-planned using CAVMAT, and the dosimetric effect due to treatment delivery errors was quantified for V6Gy, V12Gy, and V16Gy of healthy brain along with the maximum, average and minimum doses of each target. Gamma analysis of VMAT and CAVMAT plans was performed using Delta4 and SRS MapCHECK with 3% / 1mm, 2% / 1mm, 1% / 1mm criteria to assess the agreement during patient specific quality assurance.
Result: For Portal Dosimetry QA of IMRT brain and SBRT/HIGRT using a 3%/1mm criteria, the TG-218 action limit was 99.68, and 90.14, respectively; with 3.68% and 3.68% of cases failing the universal 90% criteria. For Delta4 QA of single target SRS, multiple target SRS, and SBRT IMRT with FFF using a 3%/1mm criteria, the TG-218 action limit was 93.64, 97.12, and 92.01, respectively; with 0%, 0%, and 0% of cases failing the universal 90% criteria. For Delta4 QA of SBRT VMAT using a 4%/1mm criteria, the TG-218 action limit was 94.47, with 100% passing. For ArcCHECK QA of single target and multiple target SRS VMAT using a 3%/2mm criteria, the TG-218 action limit was 98.06 and 96.59 respectively, with 100% passing. For SRS MapCHECK QA of multiple target SRS VMAT cases using 3%1mm criteria, the TG-218 action limit was 99.24 with 100% passing.
The average increase in V6Gy, V12Gy, V16Gy due to treatment delivery errors as quantified using the trajectory logfile was 0.94 ± 1.43, 0.90 ± 1.38%, and 1.23 ± 1.54% respectively for VMAT, and 0.035 ± 0.14%, 0.14 ± 0.18%, and 0.28 ± 0.24% for CAVMAT. The average change to target maximum, average, and minimum dose due to delivery errors was 0.53 ± 0.46%, 0.52 ± 0.46%, and 0.53 ± 0.56%, for VMAT, and 0.16 0.18%, 0.11 0.08%, and 0.03 0.24% for CAVMAT. There was no significant difference in magnitude of MLC discrepancies during delivery for VMAT and CAVMAT. For Gamma analysis with strict 1% / 1mm criteria, the average passing rate of VMAT gamma analysis is 94.53 ± 4.42%, while that of CAVMAT is 99.28 ± 1.74%.
Conclusion: For most QA devices, spatial tolerance of pre-treatment QA for SRS/SBRT can be tightened to 1mm while still maintaining an in-control QA process. The gamma criteria to 3%/1mm for all SRS cases and SBRT with IMRT and transitioning to a 4%1mm criteria for SBRT with VMAT have a spatial tolerance that is appropriate for the radiotherapy technique while not resulting in an excessive false positive failure rate. The CAVMAT treatment planning technique resulted in superior gamma analysis passing rate for each gamma analysis criteria.
Item Embargo CBCT image enhancement for improving accuracy of radiomics analysis and soft tissue target localization(2023) Zhang, ZeyuCone-beam computed tomography (CBCT) is one of the most commonly used image modalities in radiation therapy. It provides valuable information for target localization and outcome prediction throughout treatment courses. However, CBCT images suffer from various artifacts caused by scattering, beam hardening, undersampling, system hardware instability, and motions of the patient, which severely degrade the CBCT image quality. In addition, CBCT images have extremely poor soft-tissue contrast, making it almost impossible to accurately localize tumors in the soft tissue, such as liver tumors.
This dissertation presents the improvements of CBCT image quality for better outcome prediction and target localization by developing the deep learning and finite element based image enhancement model.
A deep learning based CBCT image enhancement model was developed to improve the radiomic feature accuracy. The model was trained based on 4D CBCT of ten patients and tested on three patients with different tumor sizes. The results show that 4D CBCT image quality can substantially affect the accuracy of the radiomic features, and the degree of impact is feature-dependent. The deep learning model was able to enhance the anatomical details and edge information in the 4D-CBCT as well as removing other image artifacts. This enhancement of image quality resulted in reduced errors for most radiomic
features. The average reduction of radiomics errors for 3 patients are 20.0%, 31.4%, 36.7%, 50.0%, 33.6% and 11.3% for histogram, GLCM, GLRLM, GLSZM, NGTDM and Wavelet features. And the error reduction was more significant for patients with larger tumors. To further improve the results, a patient-specific based training model has been developed. The model was trained based on the augmentation dataset of a single patient and tested on the different 4D CBCT of the same patient. Compared with a group-based model, the patient-specific training model further improved the accuracy of radiomic features, especially for features with large errors in the group-based model. For example, the 3D whole-body and ROI loss-based patient-specific model reduces the errors of the first-order median feature by 83.67%, the wavelet LLL feature maximum by 91.98%, and the wavelet HLL skewness feature by 15.0% on average for the four patients tested.
In addition, a patient-specific deep learning model is proposed to generate synthetic magnetic resonance imaging (MRI) from CBCT to improve tumor localization. A key innovation is using patient-specific CBCT-MRI image pairs to train a deep learning model to generate synthetic MRI from CBCT. Specifically, patient planning CT was deformably registered to prior MRI, and then used to simulate CBCT with simulated projections and Feldkamp, Davis, and Kress reconstruction. These CBCT-MRI images were augmented using translations and rotations to generate enough patient-specific training data. A U-Net-based deep learning model was developed and trained to generate synthetic MRI from CBCT in the liver, and then tested on a different CBCT dataset.
Synthetic MRIs were quantitatively evaluated against ground-truth MRI. On average, the synthetic MRI achieved 28.01, 0.025, and 0.929 for peak signal-to-noise ratio, mean square error, and structural similarity index, respectively, outperforming CBCT images on the three patients tested. To further improve the robustness of synthetic MRI generation, we developed an organ specific biomechanical model. This model registers the pretreatment MRI images to onboard CBCT images based on the organ contours, and combines the MRI organ with CBCT body to the generate hybrid MRI/CBCT. 48 registration cases were performed, which includes 18 Monte Carlo simulated cases and 30 real patient cases. We identified tumor landmarks of hybrid MRI/CBCT, onboard CBCT and planning CT, and calculated errors of landmark locations of two CBCT images. The errors were calculated based on the landmark differences of two CBCT images and ground truth planning CT. The results show that the tumor landmark localization accuracy around tumor is improved by 54.2 ± 22.2 %.
Item Open Access Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.(Frontiers in artificial intelligence, 2020-01) Wang, Wentao; Sheng, Yang; Wang, Chunhao; Zhang, Jiahan; Li, Xinyi; Palta, Manisha; Czito, Brian; Willett, Christopher G; Wu, Qiuwen; Ge, Yaorong; Yin, Fang-Fang; Wu, Q JackiePurpose: Treatment planning for pancreas stereotactic body radiation therapy (SBRT) is a difficult and time-consuming task. In this study, we aim to develop a novel deep learning framework to generate clinical-quality plans by direct prediction of fluence maps from patient anatomy using convolutional neural networks (CNNs). Materials and Methods: Our proposed framework utilizes two CNNs to predict intensity-modulated radiation therapy fluence maps and generate deliverable plans: (1) Field-dose CNN predicts field-dose distributions in the region of interest using planning images and structure contours; (2) a fluence map CNN predicts the final fluence map per beam using the predicted field dose projected onto the beam's eye view. The predicted fluence maps were subsequently imported into the treatment planning system for leaf sequencing and final dose calculation (model-predicted plans). One hundred patients previously treated with pancreas SBRT were included in this retrospective study, and they were split into 85 training cases and 15 test cases. For each network, 10% of training data were randomly selected for model validation. Nine-beam benchmark plans with standardized target prescription and organ-at-risk constraints were planned by experienced clinical physicists and used as the gold standard to train the model. Model-predicted plans were compared with benchmark plans in terms of dosimetric endpoints, fluence map deliverability, and total monitor units. Results: The average time for fluence-map prediction per patient was 7.1 s. Comparing model-predicted plans with benchmark plans, target mean dose, maximum dose (0.1 cc), and D95% absolute differences in percentages of prescription were 0.1, 3.9, and 2.1%, respectively; organ-at-risk mean dose and maximum dose (0.1 cc) absolute differences were 0.2 and 4.4%, respectively. The predicted plans had fluence map gamma indices (97.69 ± 0.96% vs. 98.14 ± 0.74%) and total monitor units (2,122 ± 281 vs. 2,265 ± 373) that were comparable to the benchmark plans. Conclusions: We develop a novel deep learning framework for pancreas SBRT planning, which predicts a fluence map for each beam and can, therefore, bypass the lengthy inverse optimization process. The proposed framework could potentially change the paradigm of treatment planning by harnessing the power of deep learning to generate clinically deliverable plans in seconds.Item Open Access Investigation of Patient Positioning Accuracy in Lung Stereotactic Body Radiation Therapy(2013) Turner, KathrynPurpose: It has been shown that patients' irregular breathing can cause variation in the delineation of the internal target volume (ITV) and affect the accuracy of four dimensional computed tomography (4DCT) and cone-beam computed tomography (CBCT) images. Therefore, it is expected that the variations induced by irregular breathing will also affect image registration between the two images. This study aims to test a new method of ITV delineation, which involves using the gross tumor volume (GTV) in conjunction with the maximum intensity projection (MIP) generated from the 4DCT, rather than just the MIP itself. Additionally, this study aims to quantitatively assess breathing irregularity induced error in CBCT-based patient positioning in lung SBRT and correlate the error with a measure of breathing variability.
Methods and Materials: For testing the new method of ITV delineation, the Computerized Imaging Reference Systems (CIRS) Dynamic Thorax Phantom Model 008A (CIRS, Norfolk, VA) with CIRS motion control software was used to model 4 irregular patient respiratory profiles and one regular respiratory profile (sine wave) with a 3 cm tumor insert. A 3D-CT and repeated 4D-CT scans were performed on a 4-slice clinical scanner (Lightspeed, GE, WI). The RPM system (Varian, Palo Alto, CA) was used to track the respiratory profiles. GTV was contoured on 3D-CT, and ITV was contoured on each MIP (ITVMIP) using a consistent lung window by the same person. The new method of creating ITV was to combine the GTV and ITVMIP, namely ITVCOMB. To evaluate which ITV is more accurate, ITVCOMB and ITVMIP were compared to a "ground truth" ITV (ITVGT) which was generated by combining the three ITVMIPs. To investigate the error in image registration between the CBCT and 4DCT, the 4D extended cardiac-torso (XCAT) digital phantom was used to generate 10-phase 4DCTand CBCT images using in-house developed simulation programs. Images were generated using the same clinical-based parameters for various respiratory profiles (one regular sinusoidal and 10 irregular) and tumor sizes (1 cm, 2 cm, 3 cm). Maximum intensity projection (MIP) and average intensity projection (AIP) images were generated from 4DCT images The internal target volumes (ITVs) were contoured by the same user with the same window/level in Eclipse. Image registrations were performed between CBCT and AIP images by matching the target as in the clinic, for each respiratory profile and tumor size. Error of registration was determined as the difference between the manual CBCT-to-AIP registration and the known registration between the two. Variability of the respiratory profiles was measured, and a correlation between the error and breathing irregularity was investigated. Additionally, variation in ITV volumes among AIP, MIP, and CBCT images were examined.
Results: When examining the volumes for the ITV delineation study, for the regular profile, both ITVMIP (27.25 cm3) and ITVCOMB (28.12cm3) were comparable to ITVGT (27.25 cm3). For irregular profiles, the mean absolute difference between ITVCOMB and ITVGT (6.3%±4.9) was significantly (p-value=0.0078) smaller than that between ITVMIP and ITVGT (18.1%±12.3). A total of 33 registrations were performed to investigate error in image registration. As expected, negligible errors of registration were found for the regular respiratory profile at all tumor sizes: the median (± SD) error was 0.50 (± 0.73) mm, 0.20 (± 0.17) mm, and 0.40 (± 0.22) mm in the medial-lateral (ML), anterior-posterior (AP), and superior-inferior (SI) direction, respectively. For the irregular respiratory profiles and all tumor sizes combined, maximum error of registration was 1.2 mm, 2.6 mm, and 7.4 mm in the ML, AP, and SI direction, respectively. Median errors were found small in ML and AP directions (the median (± SD) error was 0.50 (± 0.21) mm and 0.50 (± 0.71) mm respectively), primarily due to small motion in these two directions. Median error in the SI direction was found non-trivial (the median (± SD) error was 1.90 (± 1.55) mm).
Conclusions: The results suggest that combining GTV of the 3D-CT with the ITV of the MIP is more accurate than the ITV of the MIP alone, and thus would be a simple method to reduce breathing irregularity induced errors in ITV delineation for treatment planning of lung cancer. Errors could occur during CBCT-to-AIP registration in lung SBRT when patient's breathing is irregular, especially in the SI direction. The error is largely induced by breathing irregularity and could not be overcome by perfecting manual matching, and it should be considered when determining the ITV to PTV margin. Differences in ITV volumes for AIP-MIP were seen to be minimal. However, significant differences in ITV volumes for MIP-CBCT were observed. Further studies of clinically minimizing such uncertainties are desirable.
Item Open Access Physics and Treatment Planning Considerations for Multifocal Radiosurgery and SBRT(2017) Trager, Michael AdamPurpose:
A new development in linac-based intracranial stereotactic radiosurgery (SRS) and extracranial stereotactic body radiation therapy (SBRT) is treatment of multiple targets using single isocenter volumetric modulated arc therapy (VMAT) technique, dramatically reducing treatment time while maintaining high target conformality and steep dose gradients between targets and surrounding organs at risk (OAR). In VMAT, the gantry rotates around the patient while continuously delivering radiation. Throughout the VMAT arc, the beam is modulated based on an inverse optimization algorithm in order to spare organs at risk. Single isocenter multi-target VMAT has already been implemented for intracranial SRS and is increasingly used for extracranial SBRT treatments. Despite the increasing popularity of this technique, certain inherent clinically meaningful challenges warrant further investigation. Specifically, single isocenter, multifocal SRS and SBRT can result in small volumes targets with a large off-axis distance from the treatment isocenter. Consequently, angular errors in the collimator, patient support assembly (PSA), or gantry could have an increased impact on target coverage, warranting a re-evaluation of routine linear accelerator QA tolerance recommendations in TG-142. Also, questions have arisen regarding the ability of clinical dose calculation algorithms to calculate dose accurately for these cases at large off-axis distances. Specifically, it is questionable whether or not the MLC model used is sophisticated enough to accurately model the dose off axis. This is of concern because the MLC leaves have different dimensions outside of the HD region, but the dosimetric-leaf-gap model used is the same for both regions. Applying the single isocenter technique to extracranial SBRT of oligometastases introduces additional unique challenges that must be addressed. These include greater intra and inter-fractional setup uncertainties, and dosimetric interplay since immobilization is more difficult and internal motion is non-negligible. The purpose of this thesis is to explore these specific physics and treatment planning considerations for single isocenter multi-target intracranial radiosurgery and extracranial SBRT.
Materials and Methods:
Intracranial SRS
For single isocenter multifocal stereotactic radiosurgery, we evaluated potential dose deviations from mechanical errors in PSA, collimator, and gantry angle within the tolerance recommended by TG-142 for radiosurgery machines. Systematic errors in PSA, collimator, and gantry angle were introduced at the recommended tolerance levels into both multifocal SRS plans and traditional single target SRS using dynamic conformal arcs, and the resulting dosimetric effect were quantified within the treatment planning system. In addition, we quantified the accuracy of the treatment planning system dose calculation algorithm for targets located at large off-axis distances with 3D Slicer analysis software. The dose distribution from the treatment planning system was compared to the distribution measured using a high-resolution 3D dosimetry system (PRESAGE®/Optical-CT). Comparisons were made using DVH and gamma analysis (criteria: 2mm/3%, 3mm/3%, and 3mm/5%). DVH comparisons included a shell analysis in which we compared the dose from 2mm within the target to the target’s surface, the surface to 2mm outside the target, and 2mm to 4mm outside the target for both the plan and the dosimeter.
Extracranial SBRT
For applying the single isocenter multifocal technique to extracranial oligometastases, we propose a treatment method that addresses intra and inter-fractional motion as well as dosimetric interplay. The developed technique uses a Single Isocenter with Distinct Optimizations (SIDO) in which all Volumetric Modulated Arc Therapy (VMAT) fields share an isocenter but each field treats only one target. When necessary, setup uncertainties from rotations and deformations are mitigated by applying a couch translation between VMAT arcs, and interplay is minimized using dynamic conformal arcs (DCAs) as the starting point for inverse optimization. We evaluated this planning technique using relevant dose indices including conformity index, gradient index and modulation factor.
Results:
Intracranial SRS
Induced errors at TG-142 tolerance levels showed the greatest change in multifocal SRS target coverage for collimator and gantry rotations, while minimal change in coverage was noted for errors in PSA rotation. For single isocenter cases, the largest dose discrepancies were a result of 1° errors in the collimator and gantry angles, specifically with respect to the volume of the PTV receiving the prescription dose. These errors caused up to 33% and 18% deviations, respectively, to the volume of the PTV receiving the prescription dose with mean deviations of 5% and 2%, respectively. When the collimator and gantry errors in single isocenter plans were reduced to 0.5°, the discrepancies in the volume of the PTV receiving the prescription dose were reduced to a max value of <5% for the gantry and collimator with mean values of approximately 1%. For 1° errors in DCA plans, however, deviations to the volume of the PTV receiving the prescription dose did not exceed 5% for the collimator, couch, or gantry and similar results were seen in all other dosimetric indices investigated.
A preliminary analysis of the Eclipse dose calculation algorithm in comparison to actual dose delivered to targets shows agreement with 89.46%, 94.87%, and 96.39% of voxels having a passing gamma index with criteria of 2mm/3%, 3mm/3%, and 3mm/5% respectively (distance from isocenter ranged from 0-10cm). Targets within 8cm of the isocenter showed less than 2% discrepancy between the plan and measurement with respect to the percent of the target receiving the prescription dose. The target at 10cm from the isocenter, however, had a 15% discrepancy between the plan and measurement with respect to the percent of the target receiving the prescription dose and therefore warrants further investigation.
Extracranial SBRT
As the distance between targets increases, the probability for requiring a second translation between treatment arcs also increases. Assuming a margin of 5mm and considering six lung and five liver patient cases, a second translational shift would be required 0%, ~10%, and ~25% of the time for target separations of 5cm, 10cm, and 15cm respectively.
For greater than 3cm separation between targets in extracranial SBRT, SIDO and SIDO with DCA have an average conformity index of 0.862, and 0.864 respectively, which is comparable to the average conformity of traditional multifocal treatment techniques at these target separations of 0.901. When separation between PTVs is less than 3cm, however, traditional single isocenter VMAT has superior conformity with a mean value of 0.875, as opposed to 0.772 and 0.782 for SIDO and SIDO with DCA respectively; and decreasing conformity with decreasing target separation. SIDO with DCA had superior GI over all other planning techniques for almost all cases with a mean value of 7.31 across all target separations. SIDO with DCA even performed better than the DCA technique with a mean GI of 7.43 across all target separations, which was assumed to be the best method for obtaining a desirable GI. SIDO with DCA had a comparable MF to the DCA plans and was closer to 1 than all other planning techniques. The mean MF values across all target separations for SIDO with DCA and DCA were 1.17 and 0.83 respectively.
Conclusions:
Intracranial SRS
Institutions utilizing a single isocenter VMAT technique for multifocal disease should pay careful attention to the angular mechanical tolerances in designing a robust and complete QA program, especially with respect to the collimator and gantry recommended tolerances. We recommend reducing collimator and gantry tolerances from 1.0° to 0.5° to decrease the potential magnitude of deviations between the planning and delivered dose distributions. The PRESAGE®/Optical-CT 3D dosimetry system verified the accuracy of the Eclipse dose calculation algorithm to within 2% for targets located up to 8cm from the isocenter. Further investigation is required for more distal targets, as they did not have sufficient agreement.
Extracranial SBRT
A single isocenter approach for SBRT treatment of extracranial oligometastases may be feasible using the proposed SIDO and SIDO with DCA treatment planning techniques. SIDO for extracranial oligometastases allows flexibility to mitigate spatial uncertainties from rotation and deformation, and has comparable dosimetry to traditional VMAT with low modulation when inverse optimization begins with DCAs. These advantages make SIDO beneficial for target separations of greater than 3cm, however, for target separations less than 3cm a traditional single isocenter technique is more appropriate.
Item Open Access Pre-treatment Radiomics Models for Clinical Outcomes in Early-stage Non-Small Cell Lung Cancer (NSCLC)(2021) Shaffer, NathanLung cancer in accounts for 13% of all new cancer diagnoses and is the leading cause of cancer mortality in the United States (Bogart, 2017, Howlader, 2020). Non-small cell lung cancer (NSCLC) in particular, accounts for 80-85% of lung cancer diagnoses and is estimated to cause more than 130,000 deaths this year (American Cancer Society, 2021). Currently, the standard of care for early-stage NSCLC is surgery, with stereotactic body radiation therapy (SBRT) is becoming more accepted as the primary treatment option for patients who are medically inoperable. It remains controversial as to which method is optimal for marginal surgical patients, but it has been shown that SBRT and sublobar resection provide similar local tumor control rates and clinical outcomes in stage I NSCLC (Ackerson, 2018).The goal of this research work was to develop pre-treatment radiomic models for surgical NSCLC patients to predict cancer recurrence. This was done by investigating two specific aims. The first was to (1.) build radiomic models based on pre-treatment CT images from surgical patients and evaluate their performance in predicting cancer recurrence and the second was to (2.) build radiomic models based on pre-treatment CT images from surgical patients and evaluate their performance in predicting cancer recurrence. Radiomic features were extracted from the contoured GTV’s from pre-treatment CT scans of surgical and SBRT patients. To investigate the first aim, multivariate models were trained and tested on only surgical patients to find associations between the extracted features and each clinical outcome. To investigate the second aim, these models were first trained on surgical data and tested on SBRT data to investigate the generalizability of each model across treatment modalities. Next, models were trained and tested on a pooled dataset to investigate potential associations of radiomic features with cancer recurrence independent of treatment. Models were evaluated by creating ROC curves and calculating the area under these curves (AUC’s). Models trained and tested on surgical patients showed a stronger association between radiomic features and non-local failure (maximum AUC of 0.82 ± 0.04) and a poor association with local failure (maximum AUC of 0.57 ± 0.04). This may suggest that radiomic features have limited value in predicting local recurrence since the GTV which is used in calculating these features is no longer in the body post-treatment. Despite this, it is difficult to draw strong conclusions based on the variability in the image parameters of surgical patients, such as slice thickness and x-ray tube current, which have been shown to affect feature values (Midya, 2018, Kim, 2019). This is supported by the degraded performance in these models when SBRT data was introduced, further increasing image variability.
Item Open Access Radiomic feature variability on cone-beam CT images for lung SBRT(2018) Geng, RuiqiThis study aims to (1) investigate methodology for harmonization of radiomics features between planning CT and on-board CBCT and establish a workflow to harmonize images taken from different scanning protocols and over the course of radiotherapy treatments using normalization, and (2) examine feature variability of longitudinal cone-beam CT radiomics for 3 different fractionation schemes and a time-point during treatment indicative of early treatment response.
All CBCT images acquired over the course of lung SBRT for each patient were registered with corresponding planning CT. A volume-of-interest (VOI) in a homogeneous soft-tissue region that would not change over the course of radiotherapy was selected on the planning CT. The VOI was applied to all CBCT images of the same patient taken at different days. The first CBCT was normalized to the planning CT using the ratio of their respective mean VOI pixel values. Subsequent CBCT images were normalized using the ratio of that CBCT’s mean VOI pixel value to the first CBCT’s mean VOI pixel value. Forty-three features characterizing image intensity and morphology in fine and coarse textures were extracted from the planning CT, all original CBCT images, and all normalized CBCT images. T-test on extracted features from CBCT images with and without normalization indicates the effect of normalization on the distribution of various features. Mutual information between the planning CT and the first CBCT with and without normalization was calculated to assess the effectiveness of normalization on harmonizing radiomics features.
Of 72 NSCLC patients treated with lung SBRT, 18 received 15-18 Gy / fraction for 3 fractions; 36 received 12-12.5 Gy / fraction for 4 fractions; 18 received 8-10 Gy / fraction for 5 fractions. We studied 7 sets of CBCT images from the same treatment fraction as a ‘test-retest’ baseline to study the additional daily CBCT images. Fifty-five gray level intensity and textural features were extracted from the CBCT images. Test-retest images were used to determine the smallest detectable change (C=1.96*SD) indicating significant variation with a 95% confidence level. Here, the significance of feature variation depended on the choice of a minimum number of patients for which a feature changed more than ’C’. Analysis of which features change at which moment during treatment with different fractionation schemes was used to investigate a time-point indicative of early tumor response.
T-test on planning CT and CBCT images of the 72 patients indicated that normalization with a soft tissue VOI reduced the number of features with significant variation (p<0.05) by 55%. Following lung SBRT, 30 features changed significantly for at least 10% of all patients. For patients treated with 3 fractions, 49 features changed at Fraction 2, and 49 at Fraction 3; there was 100% overlap between features at both fractions. For patients treated with 4 fractions, 45, 45, and 48 features changed at Fraction 2-4 respectively; there was 92% overlap between features at Fraction 2 and the remaining fractions. For patients treated with 5 fractions, 12, 18, 14, and 25 features changed at Fraction 2-5; there was 36%, 48%, and 48% overlap between features at Fraction 2-4 and the remaining fractions respectively.
Normalization can potentially harmonize radiomics features on both planning CT and on-board CBCT. Feature variability depends on the selection of normalization VOI and extraction VOI. Significant changes in gray level radiomic features were observed over the course of lung SBRT. Different fractionation schemes corresponded to different patterns of feature variation. Higher fractional dose corresponded to a larger number of variable features and high overlap of variable features at an earlier time-point.
Item Open Access Spine SBRT With Halcyon™: Plan Quality, Modulation Complexity, Delivery Accuracy, and Speed.(Frontiers in Oncology, 2019-01) Petroccia, Heather M; Malajovich, Irina; Barsky, Andrew R; Ghiam, Alireza Fotouhi; Jones, Joshua; Wang, Chunhao; Zou, Wei; Teo, Boon-Keng Kevin; Dong, Lei; Metz, James M; Li, TaoranPurpose: Spine SBRT requires treatment plans with steep dose gradients and tight limits to the cord maximal dose. A new dual-layer staggered 1-cm MLC in Halcyon™ treatment platform has improved leakage, speed, and DLG compared to 120-Millennium (0.5-cm) and High-Definition (0.25-cm) MLCs in the TrueBeam platform. Halcyon™ 2.0 with SX2 MLC modulates fluence with the upper and lower MLCs, while in Halcyon™ 1.0 with SX1 only the lower MLC modulates the fluence and the upper MLC functions as a back-up jaw. We investigated the effects of four MLC designs on plan quality for spine SBRT treatments. Methods: 15 patients previously treated at our institution were re-planned according to the NRG-BR-002 guidelines with a prescription of 3,000 cGy in 3 fractions, 6xFFF, 800 MU/min, and 3-arc VMAT technique. Planning objectives were adjusted manually by an experienced planner to generate optimal plans and kept the same for different MLCs within the same platform. Results: All treatment plans were able to achieve adequate target coverage while meeting NRG-BR002 dosimetric constraints. Planning parameters were evaluated including: conformity index, homogeneity index, gradient measure, and global point dose maximum. Delivery accuracy, modulation complexity, and delivery time were also analyzed for all MLCs. Conclusion: The Halcyon™ dual-layer MLC can generate comparable and clinically equivalent spine SBRT plans to TrueBeam plans with less rapid dose fall-off and lower conformity. MLC width leaf can impact maximum dose to organs at risk and plan quality, but does not cause limitations in achieving acceptable plans for spine SBRT treatments.Item Open Access Tumor Motion Analysis Using Cine-MV in Lung Stereotatic Radiation Therapy(2012) Zhang, FanProbabilistic planning is an evolving approach for tumor motion management in which reproducibility of probability distribution function (PDF) of tumor motion is critical yet unclear. Aim of the first study is to evaluate the reproducibility of tumor motion PDF in stereotactic body radiation therapy (SBRT) using cine megavoltage (MV) images. External surrogate is used clinically in 4DCT imaging and radiation treatments for respiratory motion monitoring. However, studies have shown questionable correlation between external surrogate motion and internal tumor motion. Thus, Aim of the second study is to evaluate the correlation of external surrogate motion and internal tumor motion from a statistical point of view.
20 lung cancer patients who underwent SBRT treatment using 3D conformal technique were included in our study. During simulation, 4DCT scan assisted with RPM system was done. Cine MV images acquired during treatments were collected to extract tumor motion trajectories. For each patient, tumor motion PDFn was generated using 3 "usable" beams for each fraction. Patients without at least 3 "usable" beams were excluded. PDFn reproducibility (Rn) was calculated using the Dice Coefficient between PDFn to a "ground-truth" PDF (PDFg). The mean of Rn (Rm) was calculated for each patient and correlated to mean tumor motion rang (Am). Change of Rm during the course of SBRT treatments was also evaluated.
Thirteen patients were kept for further analysis. The tumor motion PDF during the treatments can be determined using cine MV images. The reproducibility of lung tumor motion PDF decreased exponentially as the tumor motion range increased and also decreased slightly throughout the course of treatments.
For each of thirteen patients, tumor motion range, tumor motion "ground-truth" PDFg (PDFMV), and tumor motion variability VMV were calculated using the cine-MV images. Similarly, surrogate motion range (RMV), surrogate PDF (PDFRPM), and surrogate variability (VRPM) were calculated using motion trajectory of the reflective marker. Correlation between and RRPM, and between VMV and VRPM, and between similarity of PDFMV and PDFRPM and RMV were determined.
No correlations were found in motion range and variability between the external surrogate (RPM) and the internal lung tumor motion. High PDF similarity, with a mean (±standard deviation) of 0.83(±0.1) was found between RPM and internal lung tumor motion, but no correlation exists between this PDF similarity and tumor motion range.
Item Open Access Using Genetically Engineered Mouse Models to Dissect the Critical Cellular Target of Radiation Therapy(2018) Castle, Katherine DelandApproximately half of all cancer patients will receive radiation as part of their treatment regimen in either a palliative or curative setting. Conventionally, radiation therapy has been administered to patients in small 1.8-2 Gy daily fractions over the span of 1 to 2 months. However, advances in treatment planning and radiation delivery methods have enabled tumors to be irradiated with a small number of large radiation doses between 15 and 24 Gy. This innovative radiation delivery method has been employed for the treatment of various cancers, resulting in improved rates of local control. However, the mechanism mediating enhanced tumor eradication with high dose radiation therapy remains elusive. Some studies have suggested that the tumor vasculature is functionally damaged or destroyed following high doses of radiation, resulting in a second wave of tumor cell killing due to the depletion of nutrients. Other studies suggest that although high doses of radiation may disrupt the tumor vasculature, this phenotype is not a critical regulator of the enhanced rates of local control obtained with high dose radiation therapy. A better understanding of the mechanisms by which high radiation dose per fraction improves the efficacy of radiation therapy will help to develop strategies to improve patient outcomes.
To dissect the critical cellular target(s) of radiation therapy that regulates tumor response, we utilized genetically engineered mouse models of soft tissue sarcoma, non-small cell lung cancer, and brainstem glioma to manipulate the radiosensitivity of various cellular compartments. Dual recombinase technology enabled the deletion of the DNA damage response gene Atm in tumor endothelial cells. In primary sarcomas, radiosensitization of the tumor vasculature by disruption of ATM signaling resulted in improved tumor growth delay, but not rates of local control in response to radiation. The radiosensitization of endothelial cells did not improve tumor radiation responses in primary models of lung cancer and brainstem glioma. In stark contrast, deletion of Atm within the tumor parenchymal cells specifically resulted in improved radiation therapy outcomes in all three mouse models. Interestingly, loss of Atm was only able to improve tumor outcome after radiotherapy in brainstem gliomas lacking p53 which has potential significance for the translation of ATM inhibitors into the clinic. Together, these results identify tumor parenchymal cells, rather than endothelial cells, as the critical targets that promote tumor response to radiation therapy.