RESUMO
BACKGROUND: The RefleXion X1 is a novel radiotherapy delivery system on a ring gantry equipped with fan-beam kV-CT and PET imaging subsystems. The day-to-day scanning variability of radiomics features must be evaluated before any attempt to utilize radiomics features. PURPOSE: This study aims to characterize the repeatability and reproducibility of radiomic features produced by the RefleXion X1 kV-CT. MATERIALS AND METHODS: The Credence Cartridge Radiomics (CCR) phantom includes six cartridges of varied materials. It was scanned 10 times on the RefleXion X1 kVCT imaging subsystem over a 3-month period using the two most frequently used scanning protocols (BMS and BMF). Fifty-five radiomic features were extracted for each ROI on each CT scan and analyzed using LifeX software. The coefficient of variation (COV) was computed to evaluate the repeatability. Intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) were used to evaluate the repeatability and reproducibility of the scanned images using 0.9 as the threshold. This process is repeated on a GE PET-CT scanner using several built-in protocols as a comparison. RESULTS: On average, 87% of the features on both scan protocols on the RefleXion X1 kVCT imaging subsystem can be considered repeatable as they met COV < 10% criteria. On GE PET-CT, this number is similar at 86%. When we tighten the criteria to COV <5%, the RefleXion X1 kVCT imaging subsystem showed much better repeatability with 81% of features on average whereas GE PET-CT showed only 73.5% on average. About 91% and 89% of the features with ICC > 0.9 respectively for BMS and BMF protocols on RefleXion X1. On the other hand, the percentage of features with ICC > 0.9 on GE PET-CT ranges from 67% to 82%. The RefleXion X1 kVCT imaging subsystem showed excellent intra-scanner reproducibility between the scanning protocols much better than the GE PET CT scanner. For the inter-scanner reproducibility, the percentage of features with CCC > 0.9 ranged from 49% to 80%. between X1 and GE PET-CT scanning protocols. CONCLUSIONS: Clinically useful CT radiomic features produced by the RefleXion X1 kVCT imaging subsystem are reproducible and stable over time, demonstrating its utility as a quantitative imaging platform.
Assuntos
Processamento de Imagem Assistida por Computador , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Reprodutibilidade dos Testes , Processamento de Imagem Assistida por Computador/métodos , Tomografia Computadorizada por Raios X/métodos , Tomografia por Emissão de Pósitrons , Imagens de FantasmasRESUMO
Geometric and nomenclature errors are commonly encountered in automated treatment planning. We describe a novel algorithm to extract organ geometry relationships from patient structure DICOM data to construct a database that can be used to detect organ contour inaccuracies including relational and naming errors. Twenty-five sets of head and neck patients' treatment plan data (CT, structures) were retrospectively retrieved from our institution. For each dataset, various organs were contoured and verified by experienced physicians. The relative position and orientation between organs were extracted from each patient and the data were used to construct an organ relationship database model. The model was tested using a dataset originating from an in-house organ renaming software that often-introduced organ contour naming mismatches. As part of the validation test, the renamed organs relative positions were compared with the database model to identify mismatches. Within the forty head and neck patients, we extracted the geometric relationship between 201 organ pairs. The average number of unique types of organ pairs (for example, left parotid with left eye is one type of organ pair) stored in the database was 12. Fifteen head and neck structure sets automatically renamed using our in-house organ renaming tool was used as validation data. All of the 30 random assigned wrong name labels present in these structure sets were identified using the established organ geometry relationship database. We successfully constructed a head and neck organ geometry relationship database and validated it in a contour naming quality assurance process. This novel scheme can be expanded to the entire body and shows a great potential in automatic plan physics QA procedure. It should be one essential QA step in an autonomous treatment planning process.
Assuntos
Neoplasias de Cabeça e Pescoço , Planejamento da Radioterapia Assistida por Computador , Neoplasias de Cabeça e Pescoço/diagnóstico por imagem , Neoplasias de Cabeça e Pescoço/radioterapia , Humanos , Pescoço , Glândula Parótida , Planejamento da Radioterapia Assistida por Computador/métodos , Estudos Retrospectivos , SoftwareRESUMO
PURPOSE: To present a clinical case in which real-time intratreatment imaging identified an multileaf collimator (MLC) leaf to be consistently deviating from its programmed and logged position by >1 mm. METHODS: An EPID-based exit-fluence dosimetry system designed to prevent gross delivery errors was used to capture cine during treatment images. The author serendipitously visually identified a suspected MLC leaf displacement that was not otherwise detected. The leaf position as recorded on the EPID images was measured and log-files were analyzed for the treatment in question, the prior day's treatment, and for daily MLC test patterns acquired on those treatment days. Additional standard test patterns were used to quantify the leaf position. RESULTS: Whereas the log-file reported no difference between planned and recorded positions, image-based measurements showed the leaf to be 1.3 ± 0.1 mm medial from the planned position. This offset was confirmed with the test pattern irradiations. CONCLUSIONS: It has been clinically observed that log-file derived leaf positions can differ from their actual position by >1 mm, and therefore cannot be considered to be the actual leaf positions. This cautions the use of log-based methods for MLC or patient quality assurance without independent confirmation of log integrity. Frequent verification of MLC positions through independent means is a necessary precondition to trust log-file records. Intratreatment EPID imaging provides a method to capture departures from MLC planned positions.
RESUMO
PURPOSE: Respiration-induced intrafraction target motion is a concern in liver cancer radiotherapy, especially in stereotactic body radiotherapy (SBRT), and therefore, verification of its motion is necessary. An effective means to localize the liver cancer is to insert metal fiducial markers to or near the tumor with simultaneous imaging using cone-beam computed tomography (CBCT). Utilizing the fiducial markers, the authors have demonstrated a method to generate breath-induced motion signal of liver for reconstructing 4D digital tomosynthesis (4DDTS) and 4DCBCT images based on phasewise and/or amplitudewise sorting of projection data. METHODS: The marker extraction algorithm is based on template matching of a prior known marker image and has been coded to optimally extract marker positions in CBCT projections from the On-Board Imager (Varian Medical Systems, Palo Alto, CA). To validate the algorithm, multiple projection images of moving thorax phantom and five patient cases were examined. Upon extraction of the motion signals from the markers, 4D image sorting and image reconstructions were subsequently performed. In the case of incomplete signals due to projections with missing markers, the authors have implemented signal profiling to replace the missing portion. RESULTS: The proposed marker extraction algorithm was shown to be very robust and accurate in the phantom and patient cases examined. The maximum discrepancy of the algorithm predicted marker location versus operator selected location was < 1.2 mm, with the overall average of 0.51 +/- 0.15 mm, for 500 projections. The resulting 4DDTS and 4DCBCT images showed clear reduction in motion-induced blur of the markers and the anatomy for an effective image guidance. The signal profiling method was useful in replacing missing signals. CONCLUSIONS: The authors have successfully demonstrated that motion tracking of fiducial markers and the subsequent 4D reconstruction of CBCT and DTS are possible. Due to the significant reduction in motion-induced image blur, it is anticipated that such technology will be useful in image-guided liver SBRT treatments.