Daily Computed Tomography Images Research Articles

Reproducibility and Repeatability of Pelvic Radiomics Features with Daily Imaging on a Novel Biology-Guided Radiotherapy Machine Compared to Daily Imaging on Other Radiotherapy Delivery Systems

Radiomics features extracted from computed tomography (CT) images have the potential of being used as imaging biomarkers in diagnostic and prognostic models for prostate cancer. This study aims to evaluate reproducibility and repeatability of radiomics features using daily CT images from a novel biology-guided radiotherapy (BgRT)-capable machine compared to other daily CT imaging modalities from other radiotherapy delivery systems. We retrospectively selected thirty male patients treated to the pelvic region at our institution. Among the thirty patients, ten patients were treated on a BgRT-capable machine with daily fan-beam kilovoltage CT (kVCT) scans, ten patients were treated on a conventional Linac with daily cone-beam CT (CBCT) scans, and ten patients were treated on helical tomotherapy with daily megavoltage CT (MVCT) scans. The prostate gland and femoral heads were delineated on planning CT images and on CT images at the first treatment fraction. After all the CT images were resampled to have an identical voxel size, 107 radiomics features were calculated for the prostate and femoral heads on both the planning CT images and daily CT images. Concordance correlation coefficient (CCC) and Pearson's correlation coefficient (r) were calculated to evaluate radiomics feature reproducibility between the planning CT images and pre-treatment CT scans at the first treatment fraction. To evaluate radiomics feature repeatability with kVCT images on the BgRT-capable machine, a total of ten treatment sessions with repeat kVCT scans on the BgRT-capable machine were retrieved and radiomics features were compared between the first and the second kVCT scans. For the prostate gland volume, high concordance (CCC > 0.8) was found for 8, 6, and 0 radiomics features with the first-fraction kVCT, CBCT, and MVCT images, respectively, in relation to the planning CT images, while there was strong correlation (r > 0.8) in 38, 22, and 5 radiomics features in the kVCT, CBCT, and MVCT images, respectively, in relation to the planning CT images. For the left and right femoral heads, high concordance (CCC > 0.8) was found in no more than two radiomics features with the kVCT, CBCT, or MVCT images in relation to the planning CT images. Based on repeat kVCT scan data, 97 (90.7%) radiomics features showed high concordance (CCC > 0.8) in repeat kVCT scans with 98 (91.6%) features showing high correlation (Pearson's correlation coefficient > 0.8) for the prostate gland volume. A small number of radiomics features were found to show strong reproducibility between daily CT images on the first fraction and the planning CT images with the three IGRT CT modalities in this study. On the other hand, our results indicated that strong reproducibility was found with more radiomics features with daily kVCT images from the BgRT-capable machine compared to daily CBCT and MVCT images for the prostate gland. Strong repeatability was also found with most radiomics features in daily kVCT images.

Comparison of AI-Based Auto-Segmentation Quality with Different Daily IGRT Imaging Modalities for Adaptive Radiotherapy Treatment Planning

Modern AI-based auto-segmentation tools may be applied on daily computed tomography (CT) images in an image-guided radiotherapy course to facilitate evaluation of anatomical variations and adaptive treatment planning. However, most AI auto-segmentation models are trained with high-quality diagnostic or planning CT image data. This study aims to evaluate and compare auto-segmentation quality by an AI-based auto-segmentation system with different daily CT imaging modalities. We retrospectively retrieved daily IGRT images for sixty patients. Among them, twenty patients were treated on helical tomotherapy with daily megavoltage CT (MVCT) scans, twenty patients were treated on conventional Linacs with daily cone-beam CT (CBCT) scans, and twenty patients were treated on a biology-guided radiotherapy (BgRT)-capable machine with daily fan-beam kilovoltage CT (kVCT) scans. With each treatment modality, ten patients received daily CT scans in the pelvic region while the other ten received daily CT scans in the thoracic region. An auto-segmentation system using a convolutional neural network algorithm was trained in-house with historical treatment planning CT and contouring data to generate auto-segmentation models for the pelvic and thoracic regions, respectively. Normal organs were first delineated the auto-segmentation system on the daily CT images and then drawn by an experienced planner. A set of metrics including the dice similarity coefficient (DSC), Jaccard similarity index, and Hausdorff distance were used to evaluate the quality of the auto segmentation results compared with manual contours. The auto-segmentation contours on the kVCT images showed higher average DSC compared to those on the MVCT and CBCT images for all the major organs in both the pelvic and thoracic regions including the bladder, rectum, bowel, left and right femurs, esophagus, heart, left and right lung, and spinal cord. With the kVCT images, the average DSC ranged from 0.52±0.22 to 0.996±0.005. In the pelvic region, the largest absolute difference in DSC was observed for the bowel volume with an average DSC of 0.69±0.16, 0.49±0.27, and 0.32±0.25 for the kVCT, MVCT, and CBCT images, respectively (p-value < 0.05 with unpaired t-tests between kVCT and the other two imaging modalities); in the thoracic region, the largest absolute difference in DSC was observed for the esophagus with an average DSC of 0.63±0.16, 0.22±0.08, and 0.15±0.18 for the kVCT, MVCT, and CBCT images, respectively (p-value < 0.05 with unpaired t-tests between kVCT and the other two imaging modalities). Similar results were observed with other metrics. The AI-based auto segmentation system showed improved agreement with manual contouring when using kVCT images from the BgRT capable machine compared to MVCT or CBCT images. However, manual correction is necessary on auto-segmentation results from all imaging modalities especially for organs with limited contrast from surrounding tissues.

Predicting the daily gastrointestinal doses of stereotactic body radiation therapy for pancreatic cancer based on the shortest distance between the tumor and the gastrointestinal tract using daily computed tomography images

Objectives: We aimed to investigate whether daily computed tomography (CT) images could predict the daily gastroduodenal, small intestine, and large intestine doses of stereotactic body radiation therapy (SBRT) for pancreatic cancer based on the shortest distance between the gross tumor volume (GTV) and gastrointestinal (GI) tract. Methods: Twelve patients with pancreatic cancer received SBRT of 40 Gy in five fractions. We recalculated the reference clinical SBRT plan (PLANref) using daily CT images and calculated the shortest distance from the GTV to each GI tract. The maximum dose delivered to 0.5 cc (D0.5cc) was evaluated for each planning at-risk volume of the GI tract. Spearman’s correlation test was used to determine the association between the daily change in the shortest distance (Δshortest distance) and the ratio of ΔD0.5cc dose to D0.5cc dose in PLANref (ΔD0.5cc/PLANref) for quantitative analysis. Results: The median shortest distance in PLANref was 0 mm in the gastroduodenum (interquartile range, 0–2.7), 16.7 mm in the small intestine (10.0–23.7), and 16.7 mm in the large intestine (8.3–28.1 mm). The D0.5cc of PLANref in the gastroduodenum was &gt;30 Gy in all patients, with 10 (83.3%) having the highest dose. A significant association was found between the Δshortest distance and ΔD0.5cc/ PLANref in the small or large intestine (p &lt; 0.001) but not in the gastroduodenum (p = 0.404). Conclusions: The gastroduodenum had a higher D0.5cc and predicting the daily dose was difficult. Daily dose calculations of the GI tract are recommended for safe SBRT. Advances in knowledge: This study aimed to predict the daily doses in SBRT for pancreatic cancer from the shortest distance between the GTV and the gastrointestinal tract. Daily changes in the shortest distance can predict the daily dose to the small or large intestines, but not to the gastroduodenum.

Effectiveness of CT-image guidance in proton therapy for liver cancer and the importance of daily dose monitoring for tumors and organs at risk.

It is important to have precise image guidance throughout proton therapy in order to take advantage of the therapy's physical selectivity. We evaluated the effectiveness of computed tomography (CT)-image guidance in proton therapy for patients with hepatocellular carcinoma (HCC) by assessing daily proton dose distributions. The importance of daily CT image-guided registration and daily proton dose monitoring for tumors and organs at risk (OARs) was investigated. A retrospective analysis was conducted using 570 sets of daily CT (dCT) images throughout whole treatment fractions for 38 HCC patients who underwent passive scattering proton therapy with either a 66 cobalt gray equivalent (GyE)/10 fractions (n=19) or 76 GyE/20 fractions (n=19) protocol. The actual daily delivered dose distributions were estimated by forward calculation using the dCT sets, their corresponding treatment plans, and the recorded daily couch correction information. We then evaluated the daily changes of the dose indices D99% , V30GyE , and Dmax for the tumor volumes, non-tumorous liver, and other OARs, that is, stomach, esophagus, duodenum, colon, respectively. Contours were created for all dCT sets. We validated the efficacy of the dCT-based tumor registrations (hereafter, "tumor registration") by comparing them with the bone registration and diaphragm registration as a simulation of the treatment based on the positioning using the conventional kV X-ray imaging. The dose distributions and the indices of three registrations were obtained by simulation using the same dCT sets. In the 66 GyE/10 fractions, the daily D99% value in both the tumor and diaphragm registrations agreed with the planned value with 3%-6% (SD), and the V30GyE value for the liver agreed within ±3%; the indices in the bone registration showed greater deterioration. Nevertheless, tumor-dose deterioration occurred in all registration methods for two cases due to daily changes of body shape and respiratory condition. In the 76 GyE/20 fractions, in particular for such a treatment that the dose constraints for the OARs have to be cared in the original planning, the daily D99% in the tumor registration was superior to that in the other registration (p<0.001), indicating the effectiveness of the tumor registration. The dose constraints, set in the plan as the maximum dose for OARs (i.e., duodenum, stomach, colon, and esophagus) were maintained for 16 patients including seven treated with re-planning. For three patients, the daily Dmax increased gradually or changed randomly, resulting in an inter-fractional averaged Dmax higher than the constraints. The dose distribution would have been improved if re-planning had been conducted. The results of these retrospective analyses indicate the importance of daily dose monitoring followed by adaptive re-planning when needed. The tumor registration in proton treatment for HCC was effective to maintain the daily dose to the tumor and the dose constraints of OARs, particularly in the treatment where the maintenance for the dose constraints needs to be considered throughout the treatment. Nevertheless daily proton dose monitoring with daily CT imaging is important for more reliable and safer treatment.

Dosimetric advantages of daily adaptive strategy in IMPT for high-risk prostate cancer.

PurposeTo evaluate the dosimetric advantages of daily adaptive radiotherapy (DART) in intensity‐modulated proton therapy (IMPT) for high‐risk prostate cancer by comparing estimated doses of the conventional non‐adaptive radiotherapy (NART) that irradiates according to an original treatment plan through the entire treatment and the DART that uses an adaptive treatment plan generated by using daily CT images acquired before each treatment.MethodsTwenty‐three patients with prostate cancer were included. A treatment plan with 63 Gy (relative biological effectiveness (RBE)) in 21 fractions was generated using treatment planning computed tomography (CT) images assuming that all patients had high‐risk prostate cancer for which the clinical target volume (CTV) needs to include prostate and the seminal vesicle (SV) in our treatment protocol. Twenty‐one adaptive treatment plans for each patient (total 483 data sets) were generated using daily CT images, and dose distributions were calculated. Using a 3 mm set‐up uncertainty in the robust optimization, the doses to the CTV, prostate, SV, rectum, and bladder were compared.ResultsEstimated accumulated doses of NART and DART in the 23 patients were 60.81 ± 3.47 Gy (RBE) and 63.24 ± 1.04 Gy (RBE) for CTV D99 (p < 0.01), 62.99 ± 1.28 Gy (RBE) and 63.43 ± 1.33 Gy (RBE) for the prostate D99 (p = 0.2529), and 59.07 ± 5.19 Gy (RBE) and 63.17 ± 1.04 Gy (RBE) for SV D99 (p < 0.001). No significant differences were observed between NART and DART in the estimated accumulated dose for the rectum and bladder.ConclusionCompared with the NART, DART was shown to be a useful approach that can maintain the dose coverage to the target without increasing the dose to the organs at risk (OAR) using the 3 mm set‐up uncertainty in the robust optimization in patients with high‐risk prostate cancer.

Stability of daily rectal movement and effectiveness of replanning protocols for sparing rectal doses based on the daily CT images during proton treatment for prostate cancer.

PurposeTo evaluate the optimal period of replanning to spare the rectal dose by investigating daily rectal movements during computed tomography (CT) image‐guided proton therapy for prostate cancer.Materials and methodsTo evaluate the optimum reference period for replanning, we analyzed 1483 sets of daily CT (dCT) images acquired from 40 prostate cancer patients and measured the daily rectal movement along the anterior–posterior direction based on the simulator CT (sCT) images and dCT images. We calculated daily dose distributions based on initial plans on the sCT images and replans on the dCT images for 13 representative patients, and evaluated daily dose volume histograms (DVHs) for the prostate, seminal vesicles, and rectum.ResultsThe rectal anterior side on the dCT images around the seminal vesicles largely deviated toward the anterior side relative to the position on the reference sCT images, but the deviation decreased by referring to the dCT images and became nearly zero when we referred to the dCT images after 10‐day treatment. The daily DVH values for the prostate showed good dose coverage. For six patients showing rectal movement toward the anterior side, the daily rectal DVH (V77%) showed a 3.0 ± 1.7 cc excess from the initial plan and this excess was correlated with 9.9 ± 6.8 mm rectal movement. To identify the patients (37.5% in total) for whom the replanning on the 10th‐day and 20th‐day CT images reduced the V77% excess to 0.4 ± 1.5 cc and −0.2 ± 1.3 cc, respectively, we evaluated the accumulated mean doses with a 1.2 cc criterion.ConclusionOur data demonstrate that the daily movement of the rectal anterior side tends to move toward the anterior side, which results in a rectal overdose, and the mean of the movement gradually decreases with the passage of days. In such cases, replanning with the reference CT after 10 days is effective to spare the rectal dose.

The effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect variations in patient position and anatomy.

In vivo EPID dosimetry is meant to trigger on relevant differences between delivered and planned dose distributions and should therefore be sensitive to changes in patient position and patient anatomy. Three-dimensional (3D) EPID back-projection algorithms can use either the planning computed tomography (CT) or the daily patient anatomy as patient model for dose reconstruction. The purpose of this study is to quantify the effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect patient-related variations. Variations in patient position and patient anatomy were simulated by transforming the reference planning CT images (pCT) into synthetic daily CT images (dCT) representing a variation of a given magnitude in patient position or in patient anatomy. For each variation, synthetic in vivo EPID data were also generated to simulate the reconstruction of in vivo EPID dose distributions. Both the planning CT images and the synthetic daily CT images could be used as patient model in the reconstructions yielding and EPID reconstructed dose distributions respectively. The accuracy of and reconstructions was evaluated against absolute dose measurements made in different phantom setups, and against dose distributions calculated by the treatment planning system (TPS). The comparison was performedby γ-analysis (3% local dose/2mm). The difference in sensitivity between and reconstructions to detect variations in patient position and in patient anatomy was investigated using receiver operating characteristic analysis and the number of triggered alerts for 100 volumetric modulated arc therapy plans and 12 variations. showed good agreement with both absolute point dose measurements (<0.5%) and TPS data (γ-mean=0.52±0.11). The agreement degraded with , with the magnitude of the deviation varying with each specific case. readily detected combined 3mm translation setup errors in all directions (AUC=1.0) and combined 3° rotation setup errors around all axes (AUC=0.86) whereas showed good detectability only for 12mm translations (AUC=0.85) and 9° rotations (AUC=0.80). Conversely, manifested a higher sensitivity to patient anatomical changes resulting in AUC values of 0.92/0.95 for a 6mm patient contour expansion/contraction compared to 0.70/0.64 with . Using |ΔPTVD50 |>3% as clinical tolerance level, the percentage of alerts for 6mm changes in patient contour were 85%/27% with . With planning CT images as patient model, EPID dose reconstructions underestimate the dosimetric effects caused by errors in patient positioning and overestimate the dosimetric effects caused by changes in patient anatomy. The use of the daily patient position and anatomy as patient model for in vivo 3D EPID transit dosimetry improves the ability of the system to detect uncorrected errors in patient position and it reduces the likelihood of false positives due to patient anatomical changes.

Evaluating the benefit of PBS vs. VMAT dose distributions in terms of dosimetric sparing and robustness against inter-fraction anatomical changes for pediatric abdominal tumors

Background and purposeTo evaluate the dosimetric sparing and robustness against inter-fraction anatomical changes between photon and proton dose distributions for children with abdominal tumors. Material and methodsVolumetric modulated arc therapy (VMAT) and intensity-modulated pencil beam scanning (PBS) proton dose distributions were calculated for 20 abdominal pediatric cases (average 3, range 1–8 years). VMAT plans were based on a full-arc while PBS plans on 2–3 posterior-oblique irradiation fields. Plans were robustly optimized on a patient-specific internal target volume (ITV) using a uniform 5 mm set-up uncertainty. Additionally, for the PBS plans a ± 3% proton range uncertainty was accounted for. Fractional dose re-calculations were performed using the planning computed tomography (CT) deformably registered to the daily cone-beam CT (CBCT) images. Fractional doses were accumulated rigidly. Planned and CBCT accumulated VMAT and PBS dose distributions were compared using dose–volume histogram (DVH) parameters. ResultsSignificant better sparing of the organs at risk with a maximum reduction in the mean dose of 40% was achieved with PBS. Mean ITV DVH parameters differences between planned and CBCT accumulated dose distributions were smaller than 0.5% for both VMAT and PBS. However, the ITV coverage (V95% > 99%) was not reached for one patient for the accumulated VMAT dose distribution. ConclusionsFor pediatric patients with abdominal tumors, improved dosimetric sparing was obtained with PBS compared to VMAT. In addition, PBS delivered by posterior-oblique irradiation fields demonstrated to be robust against anatomical inter-fraction changes. Compared to PBS, daily anatomical changes proved to affect the target coverage of VMAT dose distributions to a higher extent.

Accumulation of the delivered treatment dose in volumetric modulated arc therapy with breath-hold for pancreatic cancer patients based on daily cone beam computed tomography images with limited field-of-view.

Inter-fractional changes of the daily anatomy of the patient are a source of error in radiotherapy. This effect is especially present in the abdomen, where there are daily differences in the filling of the stomach or the intestines. This study investigated the impact of inter-fractional changes of pancreatic cancer patients who underwent breath-hold volumetric modulated arc therapy on the applied dose by using deformable image registration. Deformable image registration was used to determine a displacement field which maps the computed tomography (CT) used for treatment planning onto daily breath-hold cone-beam CT images with limited field-of-view (FOV) which were acquired at the beginning of every treatment fraction. Different B-spline registration methods utilizing different metrics and regularizations were used and compared. The resulting deformed planning CT images were used to calculate the dose distributions on the anatomy of the day which can therefore be seen as a good estimation of the actually delivered dose during the treatment fractions. Additionally, the accumulated dose distribution was determined by accumulating all daily dose distributions using inverted deformation fields. The calculated dose distributions were then compared to the planned dose by comparison of dose volume histograms and dosimetric volumetric indices. Best registration results were obtained using a gradient magnitude metric and a regularization of λ=0.05. The accumulated dose distributions showed that the mean dose delivered to the clinical target volume was on median reduced by 0.61Gy after 15 fractions from the planned dose. For the organs at risk, the accumulated dose distributions were still fulfilling all clinical goals for the patient cohort used in this study. It was found that rotating and shearing motions of the tumor led to a greater reduction in the mean target dose which correlated with the proximity of the target to the spine (r=0.54, P=0.038). With the proposed method, it is possible to generate a deformed planning CT image which matches the anatomy of the day based on cone beam computed tomography images with a limited FOV and calculating the dose distribution of the day. The dosimetric impact of the inter-fractional variations was small for most patients but showed larger deviations if the tumor is located in close proximity to the spine.

Effects of organ motion on proton prostate treatments, as determined from analysis of daily CT imaging for patient positioning.

We quantified interfractional movements of the prostate, seminal vesicles (SVs), and rectum during computed tomography (CT) image-guided proton therapy for prostate cancer and studied the range variation in opposed lateral proton beams. We analyzed 375 sets of daily CT images acquired throughout the proton therapy treatment of ten patients. We analyzed daily movements of the prostate, SVs, and rectum by simulating three image-matching strategies: bone matching, prostate center (PC) matching, and prostate-rectum boundary (PRB) matching. In the PC matching, translational movements of the prostate center were corrected after bone matching. In the PRB matching, we performed PC matching and correction along the anterior-posterior direction to match the boundary between the prostate and the rectum's anterior region. In each strategy, we evaluated systematic errors (Σ) and random errors (σ) by measuring the daily movements of certain points on each anatomic structure. The average positional deviations in millimeter of each point were determined by the Van Herk formula of 2.5Σ+0.7σ. Using these positional deviations, we created planning target volumes of the prostate and SVs and analyzed the daily variation in the water equivalent length (WEL) from the skin surface to the targetalong the lateral beam directions using the density converted from the daily CT number. Based on this analysis, we designed prostate cancer treatment planning and evaluated the dose volume histograms (DVHs) for these strategies. The SVs' daily movements showed large variations over the superior-inferior direction, as did the rectum's anterior region. The average positional deviations of the prostate in the anterior, posterior, superior, inferior, and lateral sides (mm) in bone matching, PC matching, and PRB matching were (8.9, 9.8, 7.5, 3.6, 1.6), (5.6, 6.1, 3.5, 4.5, 1.9), and (8.6, 3.2, 3.5, 4.5, 1.9) (mm), respectively. Moreover, the ones of the SV tip were similarly (22.5, 15.5, 11.0, 7.6, 6.0), (11.8, 8.4, 7.8, 5.2, 6.3), and (9.9, 7.5, 7.8, 5.2, 6.3). PRB matching showed the smallest positional deviations at all portions except for the anterior portion of the prostate and was able to markedly reduce the positional deviations at the posterior portion. The averaged WEL variations at the distal and proximal sides of planning target volumes were estimated 7-9mm and 4-6mm, respectively, and showed the increasing of a few millimeters in PC and PRB matching compared to bone matching. In the treatment planning simulation, the DVH values of the rectum in PRB matching were reduced compared to those obtained with other matching strategies. The positional deviations for the prostate on the posterior side and the SVs were smaller by PRB matching than the other strategies and effectively reduced the rectal dose. 3D dose calculations indicate that PRB matching with CT image guidance may do a better job relative to other positioning methods to effectively reduce the rectal complications. The WEL variation was quite large, and the appropriate margin (approx. 10mm) must be adapted to the proton range in an initial planning to maintain the coverage of target volumes throughout entire treatment.

SU‐F‐J‐194: Development of Dose‐Based Image Guided Proton Therapy Workflow

Purpose:To implement image‐guided proton therapy (IGPT) based on daily proton dose distribution.Methods:Unlike x‐ray therapy, simple alignment based on anatomy cannot ensure proper dose coverage in proton therapy. Anatomy changes along the beam path may lead to underdosing the target, or overdosing the organ‐at‐risk (OAR). With an in‐room mobile computed tomography (CT) system, we are developing a dose‐based IGPT software tool that allows patient positioning and treatment adaption based on daily dose distributions. During an IGPT treatment, daily CT images are acquired in treatment position. After initial positioning based on rigid image registration, proton dose distribution is calculated on daily CT images. The target and OARs are automatically delineated via deformable image registration. Dose distributions are evaluated to decide if repositioning or plan adaptation is necessary in order to achieve proper coverage of the target and sparing of OARs. Besides online dose‐based image guidance, the software tool can also map daily treatment doses to the treatment planning CT images for offline adaptive treatment.Results:An in‐room helical CT system is commissioned for IGPT purposes. It produces accurate CT numbers that allow proton dose calculation. GPU‐based deformable image registration algorithms are developed and evaluated for automatic ROI‐delineation and dose mapping. The online and offline IGPT functionalities are evaluated with daily CT images of the proton patients.Conclusion:The online and offline IGPT software tool may improve the safety and quality of proton treatment by allowing dose‐based IGPT and adaptive proton treatments.Research is partially supported by Mevion Medical Systems.

SU‐F‐J‐81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy

Purpose:To compute daily dose delivered during radiotherapy, deformable registration needs to be relatively fast, automated, and accurate. The aim of this study was to evaluate the performance of commercial deformable registration software for deforming between two modalities: planning computed tomography (pCT) images acquired for treatment planning and cone beam (CB) CT images acquired prior to each fraction of prostate cancer radiotherapy.Methods:A workflow was designed using MIM Software™ that aligned and deformed pCT into daily CBCT images in two steps: (1) rigid shifts applied after daily CBCT imaging to align patient anatomy to the pCT and (2) normalized intensity‐based deformable registration to account for interfractional anatomical variations. The physician‐approved CTV and organ and risk (OAR) contours were deformed from the pCT to daily CBCT over the course of treatment. The same structures were delineated on each daily CBCT by a radiation oncologist. Dice similarity coefficient (DSC) mean and standard deviations were calculated to quantify the deformable registration quality for prostate, bladder, rectum and femoral heads.Results:To date, contour comparisons have been analyzed for 31 daily fractions of 2 of 10 of the cohort. Interim analysis shows that right and left femoral head contours demonstrate the highest agreement (DSC: 0.96±0.02) with physician contours. Additionally, deformed bladder (DSC: 0.81±0.09) and prostate (DSC: 0.80±0.07) have good agreement with physician‐defined daily contours. Rectum contours have the highest variations (DSC: 0.66±0.10) between the deformed and physician‐defined contours on daily CBCT imaging.Conclusion:For structures with relatively high contrast boundaries on CBCT, the MIM automated deformable registration provided accurate representations of the daily contours during treatment delivery. These findings will permit subsequent investigations to automate daily dose computation from CBCT. However, improved methods need to be investigated to improve deformable results for rectum contours.

Learning anatomy changes from patient populations to create artificial CT images for voxel-level validation of deformable image registration.

The purpose of this study was to develop an approach to generate artificial computed tomography (CT) images with known deformation by learning the anatomy changes in a patient population for voxel‐level validation of deformable image registration. Using a dataset of CT images representing anatomy changes during the course of radiation therapy, we selected a reference image and registered the remaining images to it, either directly or indirectly, using deformable registration. The resulting deformation vector fields (DVFs) represented the anatomy variations in that patient population. The mean deformation, computed from the DVFs, and the most prominent variations, which were captured using principal component analysis (PCA), composed an active shape model that could generate random known deformations with realistic anatomy changes based on those learned from the patient population. This approach was applied to a set of 12 head and neck patients who received intensity‐modulated radiation therapy for validation. Artificial planning CT and daily CT images were generated to simulate a patient with known anatomy changes over the course of treatment and used to validate the deformable image registration between them. These artificial CT images potentially simulated the actual patients' anatomies and also showed realistic anatomy changes between different daily CT images. They were used to successfully validate deformable image registration applied to intrapatient deformation.PACS number: 87.57.nj

Importance of Daily Computed Tomography Imaging with Accelerated Partial Breast Irradiation

Importance of Daily Computed Tomography Imaging with Accelerated Partial Breast Irradiation

Clinical Outcomes and Dosimetric Considerations Using Stereotactic Body Radiotherapy for Abdominopelvic Tumors

To present clinical outcomes, early toxicity, and dosimetric constraints for patients undergoing stereotactic body radiation therapy (SBRT) for abdominal or pelvic tumors. From May 2008 to February 2010, 47 patients with 50 lesions in proximity to hollow viscous organs at risk, including stomach, duodenum, small bowel, and colon, underwent SBRT at Mayo Clinic. Treated sites included liver (21), lymph node (14), adrenal gland (6), intramuscular (4), pancreas (3), and spleen (2). Treatment planning was performed with full body immobilization and 4-dimensional computed tomography (CT)-based planning with daily cone-beam CT or stereoscopic kV imaging for pretreatment image guidance. SBRT was delivered in 1 to 5 consecutive daily fractions in a single week. The most commonly prescribed dose was 50 Gy in 5 fractions (median 45 Gy, range: 20 to 60 Gy). Toxicities were scored by CTCAE v.3. Local failure was defined as per the Response Evaluation Criteria in Solid Tumors. Median follow-up was 12 months (range: 2 to 28 mo). Tumor responses of the 48 target lesions evaluable by Response Evaluation Criteria in Solid Tumor were complete response in 18 lesions (36%), partial response in 12 lesions (24%), stable disease in 12 lesions (24%), and progressive disease in 6 lesions (12%). Kaplan-Meier estimates of local control, overall survival, and freedom from metastasis at 6 and 12 months were 98%, 90%, and 63%, and 87%, 62%, 37%, respectively. Treatment was well-tolerated acutely without reported grade ≥3 toxicity. Five grade 3 late toxicities were reported, and 1 patient died of complications from duodenal perforation 11 months after SBRT. No dose correlation with toxicity could be established. SBRT is a practical treatment option for patients with abdominopelvic tumors. Relapse typically occurs outside treatment fields, and most patients achieve a favorable response. The dose constraints used in this cohort of patients was associated with acceptable early treatment-related toxicity.

SU‐GG‐J‐146: Evaluation of Parotid Density Changes during IMRT of Head‐And‐Neck Cancer

Purpose: To evaluate the change in parotid gland density over the course of treatment for patients who have undergone adaptive radiation therapy to the head‐and‐neck. Method and Materials: Computed tomography (CT) images from sixteen patients were analyzed to assess the change in mean parotid density and parotid volume over the course of treatment. Daily CT images were acquired for a group of patients treated with adaptive radiation therapy using a CT‐on‐rails unit. A total of 529 CT scans (∼33 fractions per patient) were analyzed. Parotid contours were deformed from the planning CT to each treatment day CT image using an in‐house deformable image registration tool. The parotid volume, and average and standard deviation in CT number (HU) were obtained for each treatment fraction. Linear regression analysis was performed with a 95% confidence interval to determine the rate and trend of parotid density change. The Pearson correlation coefficient was used to evaluate possible correlations with parotid volume and function measurements. Results: Eleven of the sixteen patients showed a steady decrease in density for both parotids over the course of treatment. Two patients showed a steady decrease only in their ipsilateral parotid. The linear regression analysis for this subset of patients (p‐value &lt;0.01) revealed an average rate of decrease of 0.30 HU/fraction (range 0.13–0.70 HU/fraction). The density reduction correlated well with parotid volume change (in 24/32 instances), and was moderately correlated with patient follow‐up saliva‐flow measurements (9 patients, correlation coefficient range 0.27–0.63) for the first two follow‐up appointments. Conclusion: The mean parotid density decreased steadily and correlated well with the volume shrinkage in most patients observed in this study. In the limited available data, the density change also correlated with saliva‐flow, which warrants future studies with a larger patient population and additional treatment parameters.

Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy

Adaptive radiation therapy (ART) is the incorporation of daily images in the radiotherapy treatment process so that the treatment plan can be evaluated and modified to maximize the amount of radiation dose to the tumor while minimizing the amount of radiation delivered to healthy tissue. Registration of planning images with daily images is thus an important component of ART. In this article, the authors report their research on multiscale registration of planning computed tomography (CT) images with daily cone beam CT (CBCT) images. The multiscale algorithm is based on the hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [Multiscale Model. Simul. 2(4), pp. 554-579 (2004)]. Registration is achieved by decomposing the images to be registered into a series of scales using the (BV, L2) decomposition and initially registering the coarsest scales of the image using a landmark-based registration algorithm. The resulting transformation is then used as a starting point to deformably register the next coarse scales with one another. This procedure is iterated at each stage using the transformation computed by the previous scale registration as the starting point for the current registration. The authors present the results of studies of rectum, head-neck, and prostate CT-CBCT registration, and validate their registration method quantitatively using synthetic results in which the exact transformations our known, and qualitatively using clinical deformations in which the exact results are not known.

Performance Evaluation of Automatic Anatomy Segmentation Algorithm on Repeat or Four-Dimensional Computed Tomography Images Using Deformable Image Registration Method

Auto-propagation of anatomic regions of interest from the planning computed tomography (CT) scan to the daily CT is an essential step in image-guided adaptive radiotherapy. The goal of this study was to quantitatively evaluate the performance of the algorithm in typical clinical applications. We had previously adopted an image intensity-based deformable registration algorithm to find the correspondence between two images. In the present study, the regions of interest delineated on the planning CT image were mapped onto daily CT or four-dimensional CT images using the same transformation. Postprocessing methods, such as boundary smoothing and modification, were used to enhance the robustness of the algorithm. Auto-propagated contours for 8 head-and-neck cancer patients with a total of 100 repeat CT scans, 1 prostate patient with 24 repeat CT scans, and 9 lung cancer patients with a total of 90 four-dimensional CT images were evaluated against physician-drawn contours and physician-modified deformed contours using the volume overlap index and mean absolute surface-to-surface distance. The deformed contours were reasonably well matched with the daily anatomy on the repeat CT images. The volume overlap index and mean absolute surface-to-surface distance was 83% and 1.3 mm, respectively, compared with the independently drawn contours. Better agreement (>97% and <0.4 mm) was achieved if the physician was only asked to correct the deformed contours. The algorithm was also robust in the presence of random noise in the image. The deformable algorithm might be an effective method to propagate the planning regions of interest to subsequent CT images of changed anatomy, although a final review by physicians is highly recommended.

Effect of anatomic motion on proton therapy dose distributions in prostate cancer treatment

To determine the dosimetric impact of interfraction anatomic movements in prostate cancer patients receiving proton therapy. For each of the 10 patients studied, 8 computed tomography (CT) scans were selected from sets of daily setup CT images that were acquired from a cohort of prostate cancer patients. The images were acquired in the treatment room using the CT-on-rails system. First, standard proton therapy and intensity-modulated radiation therapy (IMRT) plans were designed for each patient using standard modality-specific methods. The images, the proton plan, and the IMRT plan were then aligned to the eight CT images based on skin marks. The doses were recalculated on these eight CT images using beam from the standard plans. Second, the plans were redesigned and evaluated assuming a smaller clinical target volume to planning target volume margin (3 mm). The images and the corresponding plans were then realigned based on the center of volume of the prostate. Dose distributions were evaluated using isodose displays, dose-volume histograms, and target coverage. For the skin-marker alignment method, 4 of the 10 IMRT plans were deficient, whereas 3 of 10 proton plans were compromised. For the alignment method based on the center of volume of the prostate, only the proton plan for 1 patient was deficient, whereas 3 of the 10 IMRT plans were suboptimal. A comparison of passively scattered proton therapy and highly conformal IMRT plans for prostate cancer revealed that the dosimetric impact of interfractional anatomic motions was similar for both modalities.

A deformable image registration method to handle distended rectums in prostate cancer radiotherapy

In image-guided adaptive radiotherapy, it is important to have the capability to automatically and accurately delineate the rectal wall, which is a major dose-limiting organ in prostate cancer radiotherapy. As image registration is a process to find the spatial correspondence between two images, a major challenge in intensity-based deformable image registration is to deal with the situation where no correspondence exists for some objects between the two images to be registered. One example is the variation of rectal contents due to the presence and absence of bowel gas. The intensity-based deformable image registration methods alone cannot create the correct spatial transformation if there is no correspondence between the source and target images. In this study we implemented an automatic image intensity modification procedure to create artificial gas pockets in the planning computed tomography (CT) images. A diffusion-based deformable image registration algorithm was developed to use an adaptive smoothing algorithm to better handle large organ deformations. The process was tested in 15 prostate cancer cases and 30 daily CT images containing the largest distended rectums. The manually delineated rectums agreed well with the autodelineated rectums when using the image-intensity modification procedure.