CT and cone-beam CT of ablative radiation therapy for pancreatic cancer with expert organ-at-risk contours.
Ontology highlight
ABSTRACT:
SUBMITTER: Hong J
PROVIDER: S-EPMC9587208 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
Publications
CT and cone-beam CT of ablative radiation therapy for pancreatic cancer with expert organ-at-risk contours.
Hong Jun J Reyngold Marsha M Crane Christopher C Cuaron John J Hajj Carla C Mann Justin J Zinovoy Melissa M Yorke Ellen E LoCastro Eve E Apte Aditya P AP Mageras Gig G
Scientific data 20221021 1
We describe a dataset from patients who received ablative radiation therapy for locally advanced pancreatic cancer (LAPC), consisting of computed tomography (CT) and cone-beam CT (CBCT) images with physician-drawn organ-at-risk (OAR) contours. The image datasets (one CT for treatment planning and two CBCT scans at the time of treatment per patient) were collected from 40 patients. All scans were acquired with the patient in the treatment position and in a deep inspiration breath-hold state. Six ...[more]
Similar Datasets
Project description:PurposeOrgan autosegmentation efforts to date have largely been focused on adult populations, due to limited availability of pediatric training data. Pediatric patients may present additional challenges for organ segmentation. This paper describes a dataset of 359 pediatric chest-abdomen-pelvis and abdomen-pelvis Computed Tomography (CT) images with expert contours of up to 29 anatomical organ structures to aid in the evaluation and development of autosegmentation algorithms for pediatric CT imaging.Acquisition and validation methodsThe dataset collection consists of axial CT images in Digital Imaging and Communications in Medicine (DICOM) format of 180 male and 179 female pediatric chest-abdomen-pelvis or abdomen-pelvis exams acquired from one of three CT scanners at Children's Wisconsin. The datasets represent random pediatric cases based upon routine clinical indications. Subjects ranged in age from 5 days to 16 years, with a mean age of 7 years. The CT acquisition, contrast, and reconstruction protocols varied across the scanner models and patients, with specifications available in the DICOM headers. Expert contours were manually labeled for up to 29 organ structures per subject. Not all contours are available for all subjects, due to limited field of view or unreliable contouring due to high noise.Data format and usage notesThe data are available on The Cancer Imaging Archive (TCIA_ (https://www.cancerimagingarchive.net/) under the collection Pediatric-CT-SEG. The axial CT image slices for each subject are available in DICOM format. The expert contours are stored in a single DICOM RTSTRUCT file for each subject. The contour names are listed in Table 2.Potential applicationsThis dataset will enable the evaluation and development of organ autosegmentation algorithms for pediatric populations, which exhibit variations in organ shape and size across age. Automated organ segmentation from CT images has numerous applications including radiation therapy, diagnostic tasks, surgical planning, and patient-specific organ dose estimation.
| S-EPMC9090951 | biostudies-literature
Project description:PurposeWe conducted a prospective, in silico study to evaluate the feasibility of cone-beam computed tomography (CBCT)-guided stereotactic adaptive radiation therapy (CT-STAR) for the treatment of ultracentral thoracic cancers (NCT04008537). We hypothesized that CT-STAR would reduce dose to organs at risk (OARs) compared with nonadaptive stereotactic body radiation therapy (SBRT) while maintaining adequate tumor coverage.Methods and materialsPatients who were already receiving radiation therapy for ultracentral thoracic malignancies underwent 5 additional daily CBCTs on the ETHOS system as part of a prospective imaging study. These were used to simulate CT-STAR, in silico. Initial, nonadaptive plans (PI) were created based on simulation images and simulated adaptive plans (PA) were based on study CBCTs. 55 Gy/5 fractions was prescribed, with OAR constraint prioritization over PTV coverage under a strict isotoxicity approach. PI were applied to patients' anatomy of the day and compared with daily PA using dose-volume histogram metrics, with selection of superior plans for simulated delivery. Feasibility was defined as completion of the end-to-end adaptive workflow while meeting strict OAR constraints in ≥80% of fractions. CT-STAR was performed under time pressures to mimic clinical adaptive processes.ResultsSeven patients were accrued, 6 with intraparenchymal tumors and 1 with a subcarinal lymph node. CT-STAR was feasible in 34 of 35 simulated fractions. In total, 32 dose constraint violations occurred when the PI was applied to anatomy-of-the-day across 22 of 35 fractions. These violations were resolved by the PA in all but one fraction, in which the proximal bronchial tree dose was still numerically improved through adaptation. The mean difference between the planning target volume and gross total volume V100% in the PI and the PA was -0.24% (-10.40 to 9.90) and -0.62% (-11.00 to 8.00), respectively. Mean end-to-end workflow time was 28.21 minutes (18.02-50.97).ConclusionsCT-STAR widened the dosimetric therapeutic index of ultracentral thorax SBRT compared with nonadaptive SBRT. A phase 1 protocol is underway to evaluate the safety of this paradigm for patients with ultracentral early-stage NSCLC.
| S-EPMC10188549 | biostudies-literature
Project description:Cone beam CT (CBCT) in image-guided radiotherapy (IGRT) offers a tremendous advantage for treatment guidance. The associated imaging dose is a clinical concern. One unique feature of CBCT-based IGRT is that the same patient is repeatedly scanned during a treatment course, and the contents of CBCT images at different fractions are similar. The authors propose a progressive dose control (PDC) scheme to utilize this temporal correlation for imaging dose reduction.A dynamic CBCT scan protocol, as opposed to the static one in the current clinical practice, is proposed to gradually reduce the imaging dose in each treatment fraction. The CBCT image from each fraction is processed by a prior-image based nonlocal means (PINLM) module to enhance its quality. The increasing amount of prior information from previous CBCT images prevents degradation of image quality due to the reduced imaging dose. Two proof-of-principle experiments have been conducted using measured phantom data and Monte Carlo simulated patient data with deformation.In the measured phantom case, utilizing a prior image acquired at 0.4 mAs, PINLM is able to improve the image quality of a CBCT acquired at 0.2 mAs by reducing the noise level from 34.95 to 12.45 HU. In the synthetic patient case, acceptable image quality is maintained at four consecutive fractions with gradually decreasing exposure levels of 0.4, 0.1, 0.07, and 0.05 mAs. When compared with the standard low-dose protocol of 0.4 mAs for each fraction, an overall imaging dose reduction of more than 60% is achieved.PINLM-PDC is able to reduce CBCT imaging dose in IGRT utilizing the temporal correlations among the sequence of CBCT images while maintaining the quality.
| S-EPMC3669143 | biostudies-other
Project description:Quantitative cone-beam CT (CBCT) imaging is on increasing demand for high-performance image guided radiation therapy (IGRT). However, the current CBCT has poor image qualities mainly due to scatter contamination. Its current clinical application is therefore limited to patient setup based on only bony structures. To improve CBCT imaging for quantitative use, we recently proposed a correction method using planning CT (pCT) as the prior knowledge. Promising phantom results have been obtained on a tabletop CBCT system, using a correction scheme with rigid registration and without iterations. More challenges arise in clinical implementations of our method, especially because patients have large organ deformation in different scans. In this paper, we propose an improved framework to extend our method from bench to bedside by including several new components.The basic principle of our correction algorithm is to estimate the primary signals of CBCT projections via forward projection on the pCT image, and then to obtain the low-frequency errors in CBCT raw projections by subtracting the estimated primary signals and low-pass filtering. We improve the algorithm by using deformable registration to minimize the geometry difference between the pCT and the CBCT images. Since the registration performance relies on the accuracy of the CBCT image, we design an optional iterative scheme to update the CBCT image used in the registration. Large correction errors result from the mismatched objects in the pCT and the CBCT scans. Another optional step of gas pocket and couch matching is added into the framework to reduce these effects.The proposed method is evaluated on four prostate patients, of which two cases are presented in detail to investigate the method performance for a large variety of patient geometry in clinical practice. The first patient has small anatomical changes from the planning to the treatment room. Our algorithm works well even without the optional iterations and the gas pocket and couch matching. The image correction on the second patient is more challenging due to the effects of gas pockets and attenuating couch. The improved framework with all new components is used to fully evaluate the correction performance. The enhanced image quality has been evaluated using mean CT number and spatial nonuniformity (SNU) error as well as contrast improvement factor. If the pCT image is considered as the ground truth, on the four patients, the overall mean CT number error is reduced from over 300 HU to below 16 HU in the selected regions of interest (ROIs), and the SNU error is suppressed from over 18% to below 2%. The average soft-tissue contrast is improved by an average factor of 2.6.We further improve our pCT-based CBCT correction algorithm for clinical use. Superior correction performance has been demonstrated on four patient studies. By providing quantitative CBCT images, our approach significantly increases the accuracy of advanced CBCT-based clinical applications for IGRT.
| S-EPMC3321051 | biostudies-other
Project description:PurposeThe emerging online adaptive radiation therapy (OART) treatment strategy based on cone beam computed tomography allows for real-time replanning according to a patient's current anatomy. However, implementing this procedure requires a new approach across the patient's care path and monitoring of the "black box" adaptation process. This study identifies high-risk failure modes (FMs) associated with AI-driven OART and proposes an interdisciplinary workflow to mitigate potential medical errors from highly automated processes, enhance treatment efficiency, and reduce the burden on clinicians.Methods and materialsAn interdisciplinary working group was formed to identify safety concerns in each process step using failure mode and effects analysis (FMEA). Based on the FMEA results, the team designed standardized procedures and safety checklists to prevent errors and ensure successful task completion. The Risk Priority Numbers (RPNs) for the top twenty FMs were calculated before and after implementing the proposed workflow to evaluate its effectiveness. Three hundred seventy-four adaptive sessions across 5 treatment sites were performed, and each session was evaluated for treatment safety and FMEA assessment.ResultsThe OART workflow has 4 components, each with 4, 8, 13, and 4 sequentially executed tasks and safety checklists. Site-specific template preparation, which includes disease-specific physician directives and Intelligent Optimization Engine template testing, is one of the new procedures introduced. The interdisciplinary workflow significantly reduced the RPNs of the high-risk FMs, with an average decrease of 110 (maximum reduction of 305.5 and minimum reduction of 27.4).ConclusionsThis study underscores the importance of addressing high-risk FMs associated with AI-driven OART and emphasizes the significance of safety measures in its implementation. By proposing a structured interdisciplinary workflow and integrated checklists, the study provides valuable insights into ensuring the safe and efficient delivery of OART while facilitating its effective integration into clinical practice.
| S-EPMC10823112 | biostudies-literature
Project description:BackgroundTo develop a low-dose cone beam CT (LD-CBCT) reconstruction method named simultaneous algebraic reconstruction technique and dual-dictionary learning (SART-DDL) joint algorithm for image guided radiation therapy (IGRT) and evaluate its imaging quality and clinical application ability.MethodsIn this retrospective study, 62 CBCT image sets from February 2018 to July 2018 at west china hospital were randomly collected from 42 head and neck patients (mean [standard deviation] age, 49.7 [11.4] years, 12 females and 30 males). All image sets were retrospectively reconstructed by SART-DDL (resultant D-CBCT image sets) with 18% less clinical raw projections. Reconstruction quality was evaluated by quantitative parameters compared with SART and Total Variation minimization (SART-TV) joint reconstruction algorithm with paired t test. Five-grade subjective grading evaluations were done by two oncologists in a blind manner compared with clinically used Feldkamp-Davis-Kress algorithm CBCT images (resultant F-CBCT image sets) and the grading results were compared by paired Wilcoxon rank test. Registration results between D-CBCT and F-CBCT were compared. D-CBCT image geometry fidelity was tested.ResultsThe mean peak signal to noise ratio of D-CBCT was 1.7 dB higher than SART-TV reconstructions (P < .001, SART-DDL vs SART-TV, 36.36 ± 0.55 dB vs 34.68 ± 0.28 dB). All D-CBCT images were recognized as clinically acceptable without significant difference with F-CBCT in subjective grading (P > .05). In clinical registration, the maximum translational and rotational difference was 1.8 mm and 1.7 degree respectively. The horizontal, vertical and sagittal geometry fidelity of D-CBCT were acceptable.ConclusionsThe image quality, geometry fidelity and clinical application ability of D-CBCT are comparable to that of the F-CBCT for head-and-neck patients with 18% less projections by SART-DDL.
| S-EPMC7425566 | biostudies-literature
Project description:PurposeBeam angle optimization is a critical issue for modern radiotherapy (RT) and is a challenging task, especially for large body sizes and noncoplanar designs. Noncoplanar RT techniques may have dosimetric advantages but increase the risk of mechanical collision. We propose a software solution to accurately predict colliding/noncolliding configurations for coplanar and noncoplanar beams.Materials and methodsIndividualized software models for two different linear accelerators were built to simulate noncolliding gantry orientations for phantom/patient subjects. The sizes and shapes of the accelerators were delineated based on their manuals and on-site measurements. The external surfaces of the subjects were automatically contoured based on computed tomography (CT) simulations. An Alderson Radiation Therapy phantom was used to predict the accuracy of spatial collision prediction by the software. A gantry collision problem encountered by one patient during initial setup was also used to test the validity of the software. Results: In the comparison between the software estimates and on-site measurements, the noncoplanar collision angles were all predicted within a 5-degree difference in gantry position. The confusion matrix was calculated for each of the two empty accelerator models, and the accuracies were 98.7% and 97.3%. The true positive rates were 97.7% and 96.9%, while the true negative rates were 99.8% and 97.9%, respectively. For the phantom study, the collision angles were predicted within a 5-degree difference. The software successfully predicted the collision problem encountered by the breast cancer patient in the initial setup position and generated shifted coordinates that were validated to correspond to a noncolliding geometry.ConclusionThe developed software effectively and accurately predicted collisions for accelerator-only, phantom, and patient setups. This software may help prevent collisions and expand the range of spatially applicable beam angles.
| S-EPMC7991715 | biostudies-literature
Project description:Standard doses of conventionally fractionated radiation have had minimal to no impact on the survival duration of patients with locally advanced unresectable pancreatic cancer (LAPC). The use of low-dose stereotactic body radiation (SBRT) in 3- to 5-fractionshas thus far produced a modest improvement in median survival with minimal toxicity and shorter duration of treatment, but failed to produce a meaningful difference at 2 years and beyond. A much higher biologically effective dose (BED) is likely needed to achieve tumor ablation The challenge is the delivery of ablative doses near the very sensitive gastrointestinal tract. Advanced organ motion management, image guidance, and adaptive planning techniques enable delivery of ablative doses of radiation (> = 100Gy BED) when more protracted hypofractionated regimens or advanced image guidance and adaptive planning are used. This approach has resulted in encouraging improvements in survival in several studies. This review will summarize the evolution of the radiation technique over time from conventional to ablative and describe the practical aspects of delivering ablative doses near the GI tract using cone beam CT image (CBCT) guidance and online adaptive MRI guidance.
| S-EPMC6555709 | biostudies-literature
Project description:PurposeA clinical-prototype, dedicated, cone-beam breast computed tomography (CBBCT) system with offset detector is undergoing clinical evaluation at our institution. This study is to estimate the normalized glandular dose coefficients ( DgNCT ) that provide air kerma-to-mean glandular dose conversion factors using Monte Carlo simulations.Materials and methodsThe clinical prototype CBBCT system uses 49 kV x-ray spectrum with 1.39 mm 1st half-value layer thickness. Monte Carlo simulations (GATE, version 8) were performed with semi-ellipsoidal, homogeneous breasts of various fibroglandular weight fractions ( fg=0.01,0.15,0.5,1) , chest wall diameters ( d=8,10,14,18,20 cm), and chest wall to nipple length ( l=0.75d ), aligned with the axis of rotation (AOR) located at 65 cm from the focal spot to determine the DgNCT . Three geometries were considered - 40×30 -cm detector with no offset that served as reference and corresponds to a clinical CBBCT system, 30×30 -cm detector with 5 cm offset, and a 30×30 -cm detector with 10 cm offset.ResultsFor 5 cm lateral offset, the DgNCT ranged 0.177-0.574 mGy/mGy and reduction in DgNCT with respect to reference geometry was observed only for 18 cm ( 6.4%±0.23% ) and 20 cm ( 9.6%±0.22% ) diameter breasts. For the 10 cm lateral offset, the DgNCT ranged 0.221-0.581 mGy/mGy and reduction in DgNCT was observed for all breast diameters. The reduction in DgNCT was 1.4%±0.48% , 7.1%±0.13% , 17.5%±0.19% , 25.1%±0.15% , and 27.7%±0.08% for 8, 10, 14, 18, and 20 cm diameter breasts, respectively. For a given breast diameter, the reduction in DgNCT with offset-detector geometries was not dependent on fg . Numerical fits of DgNCTd,l,fg were generated for each geometry.ConclusionThe DgNCT and the numerical fit, DgNCTd,l,fg would be of benefit for current CBBCT systems using the reference geometry and for future generations using offset-detector geometry. There exists a potential for radiation dose reduction with offset-detector geometry, provided the same technique factors as the reference geometry are used, and the image quality is clinically acceptable.
| S-EPMC9007273 | biostudies-literature
Project description:This paper reports on the commissioning of an Elekta cone-beam computed tomography (CT) system at one of the first U.S. sites to install a "regular," off-the-shelf Elekta Synergy (Elekta, Stockholm, Sweden) accelerator system. We present the quality assurance (QA) procedure as a guide for other users. The commissioning had six elements: (1) system safety, (2) geometric accuracy (agreement of megavoltage and kilovoltage beam isocenters), (3) image quality, (4) registration and correction accuracy, (5) dose to patient and dosimetric stability, and (6) QA procedures. The system passed the safety tests, and agreement of the isocenters was found to be within 1 mm. Using a precisely moved skull phantom, the reconstruction and alignment algorithm was found to be accurate within 1 mm and 1 degree in each dimension. Of 12 measurement points spanning a 9x9x15-cm volume in a Rando phantom (The Phantom Laboratory, Salem, NY), the average agreement in the x, y, and z coordinates was 0.10 mm, -0.12 mm, and 0.22 mm [standard deviations (SDs): 0.21 mm, 0.55 mm, 0.21 mm; largest deviations: 0.6 mm, 1.0 mm, 0.5 mm] respectively. The larger deviation for the y component can be partly attributed to the CT slice thickness of 1 mm in that direction. Dose to the patient depends on the machine settings and patient geometry. To monitor dose consistency, air kerma (output) and half-value layer (beam quality) are measured for a typical clinical setting. Air kerma was 6.3 cGy (120 kVp, 40 mA, 40 ms per frame, 360-degree scan, S20 field of view); half value layer was 7.1 mm aluminum (120 kV, 40 mA). We suggest performing items 1, 2, and 3 monthly, and 4 and 5 annually. In addition, we devised a daily QA procedure to verify agreement of the megavoltage and kilovoltage isocenters using a simple phantom containing three small steel balls. The frequency of all checks will be reevaluated based on data collected during about 1 year.
| S-EPMC5722599 | biostudies-literature