Daily Cone-beam CT Images Research Articles

Comparison and Breakdown of Cost in Head and Neck Cancer Radiation Therapy and Adaptive Replanning

Head and neck cancers pose a significant challenge to radiation oncologists due to several factors, including rapid shrinkage during radiation and patient weight loss. As the target and patient anatomy change, re-simulation and re-planning are often necessary, which precipitates additional time, resources, and cost. However, the true added cost of providing adaptive replanning for head and neck cancer patients receiving radiation therapy (RT) is often unknown. We hypothesize that adaptive replanning adds significant cost to treatment, primarily driven by the additional personnel time in the replanning process. The total costs of providing standard radiation therapy and treatment with adaptive replanning for head and neck cancer were calculated using time-driven activity-based costing. We created process maps for each step from consultation to end of treatment, utilizing data that included the space, personnel involved, equipment and supplies used, and time spent. Capacity cost rates were calculated for all resources using a combination of publicly accessible cost data, financial data from our institution, and time averages for each activity obtained from personnel interviews and clinical measurements. We included the following domains in our process maps: consultation, CT simulation, treatment planning, new treatment start, daily beam treatments, weekly on-treatment visits, CT Re-simulation, treatment replanning, and new start for replanned treatment. We found that the total cost for providing standard therapy was $12,216.39 US Dollars (USD), while the total cost of adaptive replanning was $14,705.14 USD, for a relative increase in cost of 20.4%. The most expensive factor for both treatment arms was the cost of daily treatments on the linear accelerator, representing 66.1% and 53.3% of the standard and adaptive replanning, respectively. The second largest driver of cost for both was weekly on-treatment visits with a physician, representing 11.37% and 9.45% of the total cost, respectively. Of the total cost difference between standard therapy and adaptive replanning, 64% was due to personnel costs, 27.9% was due to space/equipment costs, and 8.1% was attributable to material costs. We found that adaptive replanning increased the overall cost of radiotherapy for head and neck cancers by a significant amount. The additional personnel time with resim and replanning, as well as machine time on the CT simulator are the primary reasons for this increase. In addition, use of these resources represents an opportunity cost in the clinic. Opportunities to make adaptive replanning more cost-effective include incorporation of AI tools for volume delineation and/or treatment planning to reduce personnel time, as well as using daily cone beam CT images instead of a new CT simulation, when feasible.

Planning and Treatment Recommendations for Breast Proton Therapy From a Single Center's Experience

PurposeProton therapy use for breast cancer has grown due to advantages in coverage and potentially reduced late toxicities compared with conventional radiation therapy. We aimed to provide recommendations for robustness criteria, daily imaging, and quality assurance computed tomography (QA CT) frequency for these patients. Methods and MaterialsAll patients treated for localized breast cancer at the Johns Hopkins Proton Center between November 2019 and February 2022 were eligible for inclusion. Daily shift information was extracted and examined through control charts. If an adaptive plan was used, the time to replan was recorded. Three and 5 mm setup uncertainty was used to calculate robustness. Robust evaluation of QA CTs was compared with initial robustness range for breast/chest wall and lymph node target coverage. ResultsSixty-six patients were included: 19 with intact breast, 25 with non-reconstructed chest wall, and 22 with chest wall plus expanders or implants. Sixteen percent, 13%, and 41% of breast, chest wall, and expander/implant patients had a replan. Only patients with expanders or implants required 2 adaptive plans. Daily shift data showed large variation and did not correlate with plan adaptation. Patients without adaptive plans had QA CTs with dose-volume histogram metrics within robustness more frequently than those with adaptive plans. Using 3 mm robustness for patients who did not require an adaptive plan, 91% to 100% of patients had QA CTs within robustness, while 55% to 60% of patients with an adaptive plan had QA CTs within robustness for the axilla, internal mammary nodes, and supraclavicular nodes. Five millimeter setup uncertainty did not significantly improve this. ConclusionsWe recommend using daily cone beam CT because of the large variation in daily setup with 3 mm setup uncertainty in robustness analysis. If daily cone beam CT imaging is not available, then larger setup uncertainty should be used. Two QA CTs should be conducted during treatment if the patient has expanders or implants; otherwise, one QA CT is sufficient.

Deep Learning-Based Automatic Delineation of Target Volumes and Organs at Risk of Breast Cancer for On-Line Dosimetric Evaluation

In this study, we developed a deep learning model to achieve automatic multi-target delineation on planning CT (pCT) and daily Cone-Beam CT (CBCT). To improve the image quality of the CBCT for accurate target delineation and dose calculation, we introduce an unsupervised learning model to generate the artifact-free synthetic CT (sCT) from the CBCT. The geometric and dosimetric impact of the model on planning CT (pCT) and synthetic CT (sCT) was evaluated for breast cancer adaptive radiation therapy.We retrospectively analyzed 1127 patients treated with radiotherapy after breast-conserving surgery from two medical institutions. The CBCT for patient setup acquired utilizing breath-hold guided by optical surface monitoring system was used to generate sCT with the generative adversarial network. Organs at risk (OARs) and target volumes including tumor bed (TB) and clinical target volume (CTV) for breast cancer were delineated automatically with 3D U-Net model on pCT and sCT. The automatic delineation was compared with manually delineated contours to evaluate the performance with geometric metrics, including Dice similarity coefficient (DSC) and 95% Hausdorff Distance (HD95). The treatment plan which was transferred to the sCT from the pCT was generated with the same planning parameters as the original pCT-based plan. The dosimetric evaluation was performed by a quick dose recalculation on sCT relying on gamma analysis and the dose-volume histogram (DVH) parameters. The automatically delineating CTV on sCT which was rigidly registered to pCT was compared with manually delineating CTV on pCT to obtain DSC-CTV. The relationship between the ∆D95, ∆V95 and DSC-CTV was assessed to quantify the clinical impact of the geometric changes of CTV.The range of the DSC and HD95 were 0.73-0.97, 2.22-9.36mm for pCT, 0.63-0.95, 2.30-19.57mm for sCT from institution A, 0.70-0.97, 2.10-11.43mm for pCT from institution B respectively. The quality of sCT was excellent with an average mean absolute error (MAE) of 71.58 ± 8.78HU. The mean gamma pass rate (3%/3 mm criterion) by comparing the dose on sCT with that on original pCT was 91.46 ± 4.63%. DSC-CTV down to 0.65 accounted for a variation of more than 6% of V95 and 3Gy of D95. DSC-CTV up to 0.80 accounted for a variation of less than 4% of V95 and 2Gy of D95. The mean ∆V95 of CTV was less than 6%. The mean ∆V95 of TB was more than 8%. The mean ∆D90/∆D95 of CTV and TB were less than 2Gy/4Gy, 4Gy/5Gy for all the patients. The cardiac dose difference in left breast cancer was bigger than that in right breast cancer.This study demonstrates that highly accurate multi-target delineation and dose calculation are achievable using the daily CBCT image via deep learning. The results show that dose distribution needs to be considered to evaluate the clinical impact of geometric variations to decide whether to re-plan during breast cancer radiotherapy.

A novel use for routine CBCT imaging during radiotherapy to detect COVID-19

IntroductionThoracic CT is a useful tool in the early diagnosis of patients with COVID-19. Typical appearances include patchy ground glass shadowing. Thoracic radiotherapy uses daily cone beam CT imaging (CBCT) to check for changes in patient positioning and anatomy prior to treatment through a qualitative assessment of lung appearance by radiographers. Observation of changes related to COVID-19 infection during this process may facilitate earlier testing improving patient management and staff protection. MethodsA tool was developed to create overview reports for all CBCTs for each patient throughout their treatment. Reports contain coronal maximum intensity projection (MIP's) of all CBCTs and plots of lung density over time. A single therapeutic radiographer undertook a blinded off-line audit that reviewed 150 patient datasets for tool optimisation in which medical notes were compared to image findings. This cohort included 75 patients treated during the pandemic and 75 patients treated between 2014 and 2017. The process was repeated retrospectively on a subset of the 285 thoracic radiotherapy patients treated between January–June 2020 to assess the efficiency of the tool and process. ResultsThree patients in the n = 150 optimisation cohort had confirmed COVID-19 infections during their radiotherapy. Two of these were detected by the reported image assessment process. The third case was not detected on CBCT due to minimal density changes in the visible part of the lungs.Within the retrospective cohort four patients had confirmed COVID-19 based on RT-PCR tests, three of which were retrospectively detected by the reported process. ConclusionThe preliminary results indicate that the presence of COVID-19 can be detected on CBCT by therapeutic radiographers. Implications for practiceThis process has now been extended to clinical service with daily assessments of all thoracic CBCTs. Changes noted are referred for oncologist review.

Delivery Uncertainty Estimation Using Daily Breath-Hold Cone-Beam CTs For Liver Proton Stereotactic Body Radiotherapy

To estimate for proton stereotactic body radiotherapy (SBRT) plan delivery uncertainty with daily cone-beam CT (CBCT) imaging for liver patients under breath-hold with active breath coordinator (ABC). Images from 11 liver patients previously treated with photon SBRT with ABC at our institution are used for this study. The prescribed dose for the proton SBRT plan is 75 Gy (RBE) in 5 fractions. There is a total of 11 patients with 113 setup CBCT images collected during the patient’s previous photon SBRT treatment. The planning CT and all CBCT images are imported into Raystation 9A. A CT relative linear stopping power (RLSP) curve is calibrated for CBCT and used for proton dose calculation. A four beams proton SBRT plan is optimized with the single field optimization (SFO) technique. All 113 CBCT images are registered to planning CT with bony anatomy (rib cage and vertebrae) or liver to evaluate the delivery uncertainty. The delivery dose is estimated from the proton dose calculation on each CBCT image with the same proton plan. The dose coverages for targets are evaluated for: gross tumor volume (GTV), gtv_multABC_2mmRad_5mmSI, and ptv_5mmRad_7mmSI. Liver positions under DIBH with ABC are not consistent under bony alignment as measured. The inter-fractional and intra-fractional variation of DIBH for liver are analyzed. Proton plan delivery uncertainty can dramatically reduce under well liver alignment (up to 5% prescription dose). Daily CBCT images could be potentially used to estimate proton plan delivery uncertainty for liver patients.

Initial Evaluation of a Novel Cone-Beam CT-Based Semi-Automated Online Adaptive Radiotherapy System for Head and Neck Cancer Treatment - A Timing and Automation Quality Study.

IntroductionA novel on-line adaptive radiotherapy (ART) system based on O-ring linear accelerator (LINAC) and cone-beam CT (CBCT) was evaluated for treatment and management of head & neck (H&N) cancer in an emulated environment accessed via remote desktop connection. In this on-line ART system, organs-at-risk (OARs) and target contours and radiotherapy (RT) plans are semi-automatically generated based on the patient CBCT, expediting a typically hours-long RT planning session to under half an hour. In this paper, we describe our initial experiences with the system and explore optimization strategies to expedite the process further.MethodsWe retroactively studied five patients with head and neck cancers, treated 16-35 fractions to 50-70 Gys. For each patient, on-line ART was simulated with one planning CT and three daily CBCT images taken beginning, middle, and end of treatment (tx). Key OAR (mandible, parotids, and spinal cord) and target (planning target volume (PTV) = clinical target volume (CTV) + 3 mm margin) contours were auto-generated and adjusted as needed by therapist/dosimetrist and attending physician, respectively. Duration of OAR contouring, target contouring, and plan review was recorded. Key OAR auto-contours were qualitatively rated from 1 (unacceptable) - 5 (perfect OAR delineation), and then quantitatively compared to human-adjusted “ground truth” contours via dice similarity coefficient (DSC) and 95-percentile Hausdorff distance (HD95%). Once contours were approved, adapted RT plans were auto-generated for physician review. Simulated doses to OARs and targets from the adapted plan were compared to that from the original (un-adapted) plan.ResultsMedian on-line ART planning duration in the remote emulated environment was 19 min 34 sec (range: 13 min 10 sec - 31 min 20 sec). Automated key OAR quality was satisfactory overall (98% scored ≥3; 82% ≥4), though mandible was rated lower than others (p < 0.05). Most key OARs and all targets were within 2 mm margin of human-adjusted contours, but a few parotid and spinal cord contours deviated up to 5 mm. Anatomical changes over tx course further increased auto-contour error (p < 0.05, ΔHD95% = 0.77 mm comparing start and end of tx). Further optimizing auto-contoured OAR and target quality could reduce the on-line treatment planning duration by ~5 min and ~4.5 min, respectively. Dosimetrically, adapted plan spared OARs at a rate much greater than random chance compared to the original plan (χ2 = 22.3, p << 0.001), while maintaining similar therapeutic dose to treatment target CTV (χ2 = 1.14, p > 0.05). In addition, a general decrease in accumulated OAR dose was observed with adaptation. Unsupervised adapted plans where contours were auto-generated without human review still spared OAR at a greater rate than the original plans, suggesting benefits of adaptation can be maintained even with some leniency in contour accuracy.ConclusionFeasibility of a novel, semi-automated on-line ART system for various head and neck (H&N) cancer sites was demonstrated in terms of treatment duration, dosimetric benefits, and automated contour accuracy in a remote emulator environment. Adaptive planning duration was clinically viable at 19 min and 34 sec, but further improvements in automated contour accuracy and performance improvements of plan auto-generation may reduce adaptive planning duration by up to 10 minutes.

Rectal Motion During Intensity Modulated Radiotherapy for Post-Hysterectomy Endometrial and Cervical Cancer Patients

Intensity modulated radiotherapy (IMRT) is often used in gynecologic cancer in the post-operative setting with defined volume guidelines. It delivers a highly conformal treatment, reducing normal tissue irradiation, but results in a sharp dose gradient at the treatment volume edge. Significant vaginal cuff motion can occur due to intra- and inter-fraction motion of the rectum and bladder, which may cause inadequate target coverage. There is no consensus on how to account for the effects of rectal filling on this motion. We sought to quantify inter-fraction rectal motion during the full course of IMRT treatment and to describe if rectal motion varied by week of treatment delivery or by level within the pelvis. We retrospectively reviewed thirty consecutive patients with endometrial or cervical cancer status post hysterectomy who received IMRT to the vaginal cuff and regional lymphatics. Two reviewers measured differences in rectal position between the initial planning CT and cone-beam CT (CBCT) scans obtained daily. Department policy recommended patients be treated with full bladder daily and those with significant rectal filling asked to empty their bowels. Differences were obtained for scans obtained the first day of each week of treatment and on the final treatment date for the five weeks. At each time point, reviewers quantified anterior rectal wall movement in the anterior-posterior axis at six pre-determined levels from S4-S5 superiorly to 4 cm below the inferior border of S5 inferiorly. The resulting measurements were reviewed, and any discrepancies > 2 mm were resolved by a tertiary review. The average displacement for all patients at all timepoints and pelvic landmarks was 0.36 cm posteriorly. The maximum anterior and posterior displacements of the sample population were 3.78 cm and 4.73 cm, respectively. The average displacement did not meaningfully vary by week, measuring 0.31 cm, 0.47 cm, 0.39 cm, 0.32 cm, and 0.33 cm, all posteriorly. However, greater displacement was noticed higher in the pelvis. From superior to inferior, average displacements were 0.47 cm, 0.43 cm, 0.48 cm, 0.35 cm, 0.32 cm, and 0.18 cm, all posteriorly. 95% of all displacements fell between 2.55 cm posteriorly and 1.82 cm anteriorly. No previous studies have examined rectal displacement in the anterior-posterior axis over the course of treatment and at different levels within the pelvis for cervical and endometrial cancers. Our findings indicate significant displacement exists and that pelvic IMRT planning may benefit from anterior and posterior margins above those recommended by current guidelines. At a minimum, the results support the need for daily CBCT imaging to assess rectal filling and to develop institution guidelines for managing large displacements. In addition, margin recommendations may differ based on the level within the pelvis.

Principal component analysis modeling of Head-and-Neck anatomy using daily Cone Beam-CT images.

To model Head-and-Neck anatomy from daily Cone Beam-CT (CBCT) images over the course of fractionated radiotherapy using principal component analysis (PCA). Eighteen oropharyngeal Head-and-Neck cancer patients, treated with volumetric modulated arc therapy (VMAT), were included in this retrospective study. Normal organs, including the parotid and submandibular glands, mandible, pharyngeal constrictor muscles (PCMs), and spinal cord were contoured using daily CBCT image datasets. PCA models for each organ were developed for individual patients (IP) and the entire patient cohort/population (PP). The first 10 principal components (PCs) were extracted for all models. Analysis included cumulative and individual PCs for each organ and patient, as well as the aggregate organ/patient population; comparisons were made using the root-mean-square (RMS) of the percentage predicted spatial displacement for each PC. Overall, spatial displacement prediction was achieved at the 95% confidence level (CL) for the first three to four PCs for all organs, based on IP models. For PP models, the first four PCs predicted spatial displacement at the 80%-89% CL. Differences in percentage predicted spatial displacement between mean IP models for each organ ranged from 2.8% ± 1.8% (1st PC) to 0.6% ± 0.4% (4th PC). Differences in percentage predicted spatial displacement between IP models vs the mean IP model for each organ based on the 1st PC were <12.9% ± 6.9% for all organs. Differences in percentage predicted spatial displacement between IP and PP models based on all organs and patients for the 1st and 2nd PC were <11.7% ± 2.2%. Tissue changes during fractionated radiotherapy observed on daily CBCT in patients with Head-and-Neck cancers, were modeled using PCA. In general, spatial displacement for organs-at-risk was predicted for the first 4 principal components at the 95% confidence levels (CL), for individual patient (IP) models, and at the 80%-89% CL for population-based patient (PP) models. The IP and PP models were most predictive of changes in glandular organs and pharyngeal constrictor muscles, respectively.

I093] Mr-guided radiotherapy at the LMU in Munich: Preliminary studies

Purpose The clinical introduction of an MR-guided radiotherapy unit offers great potential to improve future patient treatment but is at the same time associated with several challenges from the perspective of medical physics. Before the final implementation of an MR-Linac in our clinical environment several preliminary studies are performed to prepare the introduction of the new system into the routine patient care as well as covering medical physics related research aspects. Methods One focus of the projects is a comparison of the adaptive workflow based on daily MR and daily cone beam CT imaging. In order to mimic the MR-guided radiotherapy workflow an MR-compatible flat table top is equipped with immobilization devices for offline MR imaging in treatment position. A flexible, modular phantom is developed based on lego bricks, enabling fast distortion phantom prototyping and consequently distortion measurements. The effect of magnetic fields on dose measurements with thermoluminescent dosimeters is evaluated. Image registration methods are applied to time-resolved 4D MR and 4D CT images of patients as well as to breathing phantoms evaluating how to include 4D data into the online adaptive treatment workflow. Results The preliminary results of the projects mentioned above will be presented and discussed. This includes a comparison of CT- and MR-based internal target volume concepts as a surrogate for reproducibility of breathing motion of the patient, the first results of the 4D phantom studies and the TLD measurements in a magnetic field. Conclusions Several studies are performed at the university hospital of the LMU in Munich to pave the way for a smooth introduction of the MR-Linac into clinical routine and into research in MR-guided radiotherapy.

Deformable Image Registration and Dose Accumulation for Locally Advanced Non-Small Cell Lung Cancer, Comparing Delivered and Planned Radiotherapy Doses

Uncertainty in the radiotherapy doses actually received over the course of treatment for locally-advanced non-small cell lung cancer (LA-NSCLC) may explain, in part, low long term survival rates for these patients. This is because target and nodal dose coverage, up to this point, have been assumed constant; however disease volume and location are known to change during the course of radiation treatment. In this study, deformable registration (DIR) and dose accumulation (DA) were used to calculate the accumulated dose received over the course of treatment. These accumulated doses are then compared with the clinical treatment plan against acceptable tolerances. This single institution retrospective study randomly selected 26 patients diagnosed with LA-NSCLS receiving radical chemo-radiotherapy. 9 Patients received a dose of 60Gy/30fx and the other 17 patients received a dose of 66/33fx. The clinical delivered plan was exported into RayStation 4.5.2. Using this system's deformable image registration (DIR) tools, doses calculated on daily cone-beam CT images acquired for daily verification are deformed and mapped onto the planning CT images, thus accounting for daily treatment incorporating set-up shifts and changes in the patients anatomy. The accumulated dose delivered was then compared to the clinical treatment plan in terms of target coverage and avoidance of organs at risk. This study demonstrates successfully that, on average, the accumulated doses calculated were not statistically different from the clinical plan. Furthermore, the accumulated doses to the clinical target volumes (CTV's) for both targets and nodes are within acceptable range, illustrating that our current PTV margins are robust against anatomical changes observed during the course of radiation therapy treatment. Differences between CTV doses calculated for the clinical treatment plan compared to the accumulated plan was within 2%. The accumulated OAR doses are also maintained as compared to the clinical plan. We successfully demonstrated that DIR and DA is a useful and valued tool confirming doses received for patients receiving radiation for LA-NSCLC. We have confirmed that our PTV margins are adequate and robust from a dosimetric perspective. Given our relatively small sample size, our results may not be representative of the entire population. Further accrual would confirm our initial findings.

Quantification of Volumetric Changes Occurring During Radiation Therapy for Esophageal Cancer

Many patients undergoing radiation therapy for esophageal cancer have marked anatomic changes during their course of treatment including shrinking of the primary tumor, edematous changes of the treated esophagus, and changes in body habitus. Changes in contour, volume, and location of the esophageal tumor over the total course of radiation therapy could have a potential dosimetric impact if highly conformal treatment techniques are used. We conducted a retrospective repeated measures analysis on daily cone-beam CT imaging to quantify the magnitude of these volumetric changes. Utilizing an institutional retrospective database, fourteen patients were identified for this study. All patients were treated using a linear accelerator with integrated on-board cone beam CT imaging that allows CT imaging during the daily treatment sessions while the patient is immobilized in the treatment position. Gross tumor volumes of the primary tumor were contoured on every axial slice on the primary planning CT and the CT acquired on treatment days 1, 6,11,16,21, and 25. The changes in primary tumor volume over time were analyzed with a repeated measures ANOVA analysis. Gross tumor volumes generally decreased at an average rate of roughly 6% volume loss per week which ultimately resulted in a 23% total average reduction in volume over the total course of therapy. Analysis of variance revealed a statistically significant reduction in tumor volume occurring by cone beam CT 11 with a mean volume of 91% of original (p=0.0011 95% CI 0.89-0.98).The volumes measured on cone beam CTs taken on treatment days 16, 21, and 25 were also statistically significant (p<0.0001) with mean residual volumes of 89% (95% CI = 0.83-0.96), 83% (95% CI=0.79-0.89), and 77% of original volume (95% CI= 0.72-0.83) respectively. Statistically significant volume reductions were noted to begin by radiation treatment day 11 with meaningful dosimetric implications. These data may, therefore, be useful in the implementation of an adaptive radiation therapy planning scheme that periodically adjusts the conformal treatment plan to match these anatomic

Comparing Delivered and Planned Radiation Therapy Doses Using Deformable Image Registration and Dose Accumulation for Locally Advanced Non–small Cell Lung Cancer

There are uncertainties in radiotherapy doses received over the course of treatment for locally-advanced non-small cell lung cancer (LA-NSCLC). This may explain poor long term survival rates for these patients as target and nodal dose coverage, have been assumed constant throughout treatment. However, disease volume and location are known to change. In this study, deformable registration (DIR) and dose accumulation (DA) were used to calculate the dose delivered over the course of treatment. These delivered doses were then compared with the clinical treatment plan. This single institution, retrospective study selected 26 sequential patients diagnosed with LA-NSCLC receiving radical chemo-radiotherapy. Using RayStation 4.5.2, doses were calculated on daily cone-beam CT images acquired for daily verification were then deformed and mapped back onto the planning CT images. DA results were compared to the clinical treatment plan for both target coverage and organs at risk. Findings are summarized in Table 1. On average, DA calculations were not statistically different from the clinical plan (p<0.05). The DA to the clinical target volumes for both targets (CTV-T) and nodes (CTV-N) demonstrated that coverage remained close to that planned. The DA for OARs was also maintained as compared to the clinical plan. While, on average, delivered doses remained within our routine clinical tolerances, outliers were observed. DA for each patient indicated a small decrease of the delivered dose with respect to their clinical plan, although large variations were observed for organs at risk. We successfully demonstrated that DIR and DA can assess delivered doses to patients receiving radiotherapy for LA-NSCLC. We have confirmed that, on average, our PTV margins are adequate and robust from a dosimetric perspective. Given our LA-NSCLC sample, our results may not be representative Non-Small Cell (NSCLC) population. Although no average differences seen, outliers persist and will be the focus of future research.Abstract 3659; Table 1Planned vs Accumulated DosesROIDelivered Dose(±SD)[Min – Max]Planned Dose(±SD)[Min – Max]% change from plan/patient (±SD)[Min – Max]ProtocolD99% CTV-T95.5 ± 3.9%[88 – 102%]97 ± 3.1%[91 – 102%]-1.3 ± 1.9[-6 – 2 %]92%D99% CTV-N94.7 ± 4.8%[79 – 100%]95.8 ± 3.2%[87 – 100%]-1.3 ± 2.2[-9 – 2 %]92%Spinal canal4450 ± 691 cGy[1317 – 5378 cGy]4438 ± 276 cGy[4008 – 5110 cGy]-2.0 ± 2.1[-5 – 5 %]4500 cGyMean lung dose1465 ± 412 cGy[657 – 1911 cGy]1401 ± 390 cGy[611 – 1876 cGy]-1.4 ± 3.5[-11 – 6 %]1800 cGyV20 lung25.9 ± 7.6%[9 – 34%]26.3 ± 8.9%[9 – 45%]-0.3 ± 4.4[-6 – 12%]30%V40 heart13.4 ±13.2%[0 – 50%]14.7 ± 13.1%[0 – 49%]-10.6 ± 24[-89 – 53%]60%V40 esophagus37 ± 17%[6 – 73%]36 ± 19%[0 – 74%]-0.8 ± 8%[-10 – 28%]60% Open table in a new tab

Variations of target volume definition and daily target volume localization in stereotactic body radiotherapy for early-stage non–small cell lung cancer patients under abdominal compression

We aimed to compare gross tumor volumes (GTV) in 3-dimensional computed tomography (3DCT) simulation and daily cone beam CT (CBCT) with the internal target volume (ITV) in 4-dimensional CT (4DCT) simulation in stereotactic body radiotherapy (SBRT) treatment of patients with early-stage non–small cell lung cancer (NSCLC) under abdominal compression. We retrospectively selected 10 patients with NSCLC who received image-guided SBRT treatments under abdominal compression with daily CBCT imaging. GTVs were contoured as visible gross tumor on the planning 3DCT and daily CBCT, and ITVs were contoured using maximum intensity projection (MIP) images of the planning 4DCT. Daily CBCTs were registered with 3DCT and MIP images by matching of bony landmarks in the thoracic region to evaluate interfractional GTV position variations. Relative to MIP-based ITVs, the average 3DCT-based GTV volume was 66.3 ± 17.1% (range: 37.5% to 92.0%) (p < 0.01 in paired t-test), and the average CBCT-based GTV volume was 90.0 ± 6.7% (daily range: 75.7% to 107.1%) (p = 0.02). Based on bony anatomy matching, the center-of-mass coordinates for CBCT-based GTVs had maximum absolute shift of 2.4 mm (left-right), 7.0 mm (anterior-posterior [AP]), and 5.2 mm (superior-inferior [SI]) relative to the MIP-based ITV. CBCT-based GTVs had average overlapping ratio of 81.3 ± 11.2% (range: 45.1% to 98.9%) with the MIP-based ITV, and 57.7 ± 13.7% (range: 35.1% to 83.2%) with the 3DCT-based GTV. Even with abdominal compression, both 3DCT simulations and daily CBCT scans significantly underestimated the full range of tumor motion. In daily image-guided patient setup corrections, automatic bony anatomy-based image registration could lead to target misalignment. Soft tissue-based image registration should be performed for accurate treatment delivery.

A comparison between two clinically applied plan library strategies in adaptive radiotherapy of bladder cancer

Background and purposeThe predominant approach to clinically applied adaptive radiotherapy (ART) for bladder cancer is daily selection of treatment plans from a plan library. In this study we have compared two clinical strategies for creating multiple planning target volumes (PTV) for ART of bladder cancer. Material and methodsOnline ART delivering 60Gy in 30 fractions to the whole bladder was simulated for ten patients using two methods of creating plan libraries. In the RepeatCT method four planning CT scans were acquired at 15-min intervals, generating four CTVs with different bladder volumes. In the RepeatCBCT method one planning CT and four daily cone-beam CT images were combined using Boolean operators to form three composite CTVs. Plan selection rates and PTV volumes were evaluated, with the selected volumes averaged across 30 treatment fractions (PTVmean). ResultsThe PTVmean volume was on average 80cm3 smaller (p<0.001) in the RepeatCT method than in the RepeatCBCT method. Compared to the non-adaptive treatment, the PTVmean was reduced by 46% (range 33–53%, RepeatCT) and 36% (range 27–44%, RepeatCBCT). ConclusionsBoth methods reduced the PTVmean volume compared to the non-adaptive approach, but the reduction was larger using the strategy with repeat planning CT imaging. However, the strategy with combined CT and repeat CBCT imaging produced a more adequate range of PTV volumes.

Ultratight Margin (2-3 mm) Intensity Modulated Radiation Therapy With Daily Cone Beam CT Image Guidance Yields Excellent Locoregional Control in Head and Neck Cancer

Ultratight Margin (2-3 mm) Intensity Modulated Radiation Therapy With Daily Cone Beam CT Image Guidance Yields Excellent Locoregional Control in Head and Neck Cancer

Evaluation of Online/Offline Image Guidance/Adaptation Approaches for Prostate Cancer Radiation Therapy

To evaluate online/offline image-guided/adaptive treatment techniques for prostate cancer radiation therapy with daily cone-beam CT (CBCT) imaging. Three treatment techniques were evaluated retrospectively using daily pre- and posttreatment CBCT images on 22 prostate cancer patients. Prostate, seminal vesicles (SV), rectal wall, and bladder were delineated on all CBCT images. For each patient, a pretreatment intensity modulated radiation therapy plan with clinical target volume (CTV)=prostate+SV and planning target volume (PTV)=CTV+3mm was created. The 3 treatment techniques were as follows: (1) Daily Correction: The pretreatment intensity modulated radiation therapy plan was delivered after online CBCT imaging, and position correction; (2) Online Planning: Daily online inverse plans with 3-mm CTV-to-PTV margin were created using online CBCT images, and delivered; and (3) Hybrid Adaption: Daily Correction plus an offline adaptive inverse planning performed after the first week of treatment. The adaptive plan was delivered for all remaining 15 fractions. Treatment dose for each technique was constructed using the daily posttreatment CBCT images via deformable image registration. Evaluation was performed using treatment dose distribution in target and critical organs. Treatment equivalent uniform dose (EUD) for the CTV was within [85.6%, 100.8%] of the pretreatment planned target EUD for Daily Correction; [98.7%, 103.0%] for OnlinePlanning; and [99.2%, 103.4%] for Hybrid Adaptation. Eighteen percent of the 22 patients in Daily Correction had a target dose deficiency >5%. For rectal wall, the mean±SD of the normalized EUD was 102.6%±2.7% for Daily Correction, 99.9%±2.5% for Online Planning, and 100.6%±2.1% for Hybrid Adaptation. The mean±SD of the normalized bladder EUD was 108.7%±8.2% for Daily Correction, 92.7%±8.6% for Online Planning, and 89.4%±10.8% for Hybrid Adaptation. Both Online Planning and Hybrid Adaptation can achieve comparable target coverage and normal tissue sparing and are superior to the Daily Correction technique. The Daily Correction technique using a 3-mm target margin in the pretreatment plan is not appropriate to compensate for residual variations in CBCT image-guided prostate cancer radiation therapy.

Phantom based evaluation of CT to CBCT image registration for proton therapy dose recalculation

The ability to perform dose recalculation on the anatomy of the day is important in the context of adaptive proton therapy. The objective of this study was to investigate the use of deformable image registration (DIR) and cone beam CT (CBCT) imaging to generate the daily stopping power distribution of the patient. We investigated the deformation of the planning CT scan (pCT) onto daily CBCT images to generate a virtual CT (vCT) using a deformable phantom designed for the head and neck (H & N) region.The phantom was imaged at a planning CT scanner in planning configuration, yielding a pCT and in deformed, treatment day configuration, yielding a reference CT (refCT). The treatment day configuration was additionally scanned at a CBCT scanner. A Morphons DIR algorithm was used to generate a vCT. The accuracy of the vCT was evaluated by comparison to the refCT in terms of corresponding features as identified by an adaptive scale invariant feature transform (aSIFT) algorithm. Additionally, the vCT CT numbers were compared to those of the refCT using both profiles and regions of interest and the volumes and overlap (DICE coefficients) of various phantom structures were compared. The water equivalent thickness (WET) of the vCT, refCT and pCT were also compared to evaluate proton range differences. Proton dose distributions from the same initial fluence were calculated on the refCT, vCT and pCT and compared in terms of proton range. The method was tested on a clinical dataset using a replanning CT scan acquired close in time to a CBCT scan as reference using the WET evaluation.Results from the aSIFT investigation suggest a deformation accuracy of 2–3 mm. The use of the Morphon algorithm did not distort CT number intensity in uniform regions and WET differences between vCT and refCT were of the order of 2% of the proton range. This result was confirmed by proton dose calculations. The patient results were consistent with phantom observations. In conclusion, our phantom study suggests the vCT approach is adequate for proton dose recalculation on the basis of CBCT imaging.

SU‐E‐I‐87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction

Purpose:The aiming of this study was to extract liver structures for daily Cone beam CT (CBCT) images automatically.Methods:Datasets were collected from 50 intravenous contrast planning CT images, which were regarded as training dataset for probabilistic atlas and shape prior model construction. Firstly, probabilistic atlas and shape prior model based on sparse shape composition (SSC) were constructed by iterative deformable registration. Secondly, the artifacts and noise were removed from the daily CBCT image by an edge‐preserving filtering using total variation with L1 norm (TV‐L1). Furthermore, the initial liver region was obtained by registering the incoming CBCT image with the atlas utilizing edge‐preserving deformable registration with multi‐scale strategy, and then the initial liver region was converted to surface meshing which was registered with the shape model where the major variation of specific patient was modeled by sparse vectors. At the last stage, the shape and intensity information were incorporated into joint probabilistic model, and finally the liver structure was extracted by maximum a posteriori segmentation.Regarding the construction process, firstly the manually segmented contours were converted into meshes, and then arbitrary patient data was chosen as reference image to register with the rest of training datasets by deformable registration algorithm for constructing probabilistic atlas and prior shape model. To improve the efficiency of proposed method, the initial probabilistic atlas was used as reference image to register with other patient data for iterative construction for removing bias caused by arbitrary selection.Results:The experiment validated the accuracy of the segmentation results quantitatively by comparing with the manually ones. The volumetric overlap percentage between the automatically generated liver contours and the ground truth were on an average 88%–95% for CBCT images.Conclusion:The experiment demonstrated that liver structures of CBCT with artifacts can be extracted accurately for following adaptive radiation therapy.This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle‐aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)

SU‐C‐BRE‐05: PTV Margin Determination Based On Tumor Radiobiological Characteristics and Geometric Uncertainties Derived From Daily Cone‐ Beam CT Images

Purpose:To determine required PTV margins for ≤1% loss in mean population TCP using systematic (Σ) and random (σ) errors calculated from daily cone‐beam CT (CBCT) images of head and neck patients.Methods:Daily CBCT images were acquired for 50 head and neck patients. The CBCT image sets acquired at each fraction were registered with planning CT to obtain positional errors for each patient for each fraction. Systematic and random errors were calculated from data collected for 50 patients as described in IPEM On Target report. CTV delineation uncertainty of 2mm is added quadratically to systematic error. Assuming a spherical target volume, the dose in each voxel of target volume is summed for each fraction in the treatment by shifting the dose grid to calculate mean population TCP inclusive of geometric uncertainties using a Monte Carlo method. These simulations were repeated for the set of Σ &amp; σ in each axis for different PTV margins and drop in TCP for each margin are obtained. In order to study the effect of dose‐response curve on PTV margins, two different σα of 0.048 Gy‐1 and 0.218 Gy‐1 representing steep and shallow dose‐response curves are studied. Σ were 2.5, 2.5, 2.1 mm and σ were 0.3, 0.3 0.2 mm respectively in x, y and z axis respectively.Results:PTV margins based on tumor radiobiological characteristics are 4.8, 4.8 and 4 mm in x, y and z axis assuming 25 treatment fractions for σα 0.048 Gy‐1 (steep) and 4.2,4.2 and 2.2 for σα of 0.218 Gy‐1 (shallow). While the TCP‐based margins did not differ much in x and y axis, it is considerably smaller in z axis for shallow DRC.Conclusion:TCP based margins are substantially smaller than physical dose‐based margin recipes. This study also demonstrates the importance of considering tumor radiobiological characteristics while deriving margins.

TH‐C‐141‐11: Evaluation of MR Images as the Planning and Reference Dataset for Daily CBCT‐Based IGRT of the Prostate

Purpose: An important question rarely discussed in the CT vs. MRI simulation debate is whether MRI reference images provide an adequate image‐set to use with daily localization such as cone‐beam CT (CBCT). This study compares clinical couch shifts based on daily CBCT images to shifts measured from MR images as the reference dataset for prostate IMRT treatment. Methods: Eight patients undergoing a pilot study had MR imaging along with CT simulation with the intent of evaluating a MR‐simulation process. Patients had T1, T2 and bTFE (balanced Turbo Field Echo) sequences. The remainder of the treatment planning process continued using traditional procedures using CT. Therapists used only the CT scan as a reference for localization. Retrospectively, an observer measured shifts between daily CBCT images and MR reference images. Results: The differences in shift positions for the cohort between therapists and the observer are −0.16cm ± 0.25cm (AP), 0.04cm ± 0.19cm (SI), and — 0.01cm ± 0.14cm (LR). The mean group error for the therapists and the observer were less than 2 mm in all directions. Based on these shifts, the calculated margins for the therapists would be 0.87cm (AP), 0.65cm (SI), and 0.71cm (LR) and for the observer would be 1.1cm (AP), 0.66cm (SI), and 0.70cm (LR). For SI and LR directions both sets of margins are very close to one another. An outlier impacted the AP margin difference by 2.3mm and should be investigated further. This initial analysis suggests that each modality can be considered clinically sufficient for daily localization. Conclusion: The results of this study suggest that MR reference image‐sets can be used for daily image‐guided localization of prostate cancers with at least the same accuracy as current methods. MR simulation provides substantial soft‐tissue contrast and can improve tissue targeting in radiation oncology, as a Result further investigation is warranted.