bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐D‐BRB‐05: Quantum Learning for Knowledge‐Based Response‐Adaptive Radiotherapy
Authors: El Naqa I , Ten R 
Published: July 2016

Purpose:There is tremendous excitement in radiotherapy about applying data‐driven methods to develop personalized clinical decisions for real‐time response‐based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics‐inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient's characteristics and optimize outcomes.Methods:We studied 88 liver SBRT patients with 35 on non‐adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split‐course of 3+2 fractions with a month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5‐variable state represented by patient's clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision‐making to adapt at one month was considered. The MDP objective was defined by the complication‐free tumor control (P+=TCPx(1‐NTCP)). A simple regression model represented state‐action mapping. Single bit in classical MDP and a qubit of 2‐superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q‐learning and quantum searching was performed using Grover's algorithm, which applies uniform superposition over possible states and yields quadratic speed‐up.Results:Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous‐courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while the quantum approach averaged a more optimistic 0.57±0.4, but with high phase fluctuations.Conclusion:Our results demonstrate that quantum machine learning approaches provide a feasible and promising framework for real‐time and sequential clinical decision‐making in adaptive radiotherapy.
SU‐D‐BRA‐03: Analysis of Systematic Errors with 2D/3D Image Registration for Target Localization and Treatment Delivery in Stereotactic Radiosurgery
Authors: Xu H , Chetty I , Wen N 
Published: July 2016

Purpose:Determine systematic deviations between 2D/3D and 3D/3D image registrations with six degrees of freedom (6DOF) for various imaging modalities and registration algorithms on the Varian Edge Linac.Methods:The 6DOF systematic errors were assessed by comparing automated 2D/3D (kV/MV vs. CT) with 3D/3D (CBCT vs. CT) image registrations from different imaging pairs, CT slice thicknesses, couch angles, similarity measures, etc., using a Rando head and a pelvic phantom. The 2D/3D image registration accuracy was evaluated at different treatment sites (intra‐cranial and extra‐cranial) by statistically analyzing 2D/3D pre‐treatment verification against 3D/3D localization of 192 Stereotactic Radiosurgery/Stereotactic Body Radiation Therapy treatment fractions for 88 patients.Results:The systematic errors of 2D/3D image registration using kV‐kV, MV‐kV and MV‐MV image pairs using 0.8 mm slice thickness CT images were within 0.3 mm and 0.3° for translations and rotations with a 95% confidence interval (CI). No significant difference between 2D/3D and 3D/3D image registrations (P>0.05) was observed for target localization at various CT slice thicknesses ranging from 0.8 to 3 mm. Couch angles (30, 45, 60 degree) did not impact the accuracy of 2D/3D image registration. Using pattern intensity with content image filtering was recommended for 2D/3D image registration to achieve the best accuracy. For the patient study, translational error was within 2 mm and rotational error was within 0.6 degrees in terms of 95% CI for 2D/3D image registration. For intra‐cranial sites, means and std. deviations of translational errors were −0.2±0.7, 0.04±0.5, 0.1±0.4 mm for LNG, LAT, VRT directions, respectively. For extra‐cranial sites, means and std. deviations of translational errors were ‐ 0.04±1, 0.2±1, 0.1±1 mm for LNG, LAT, VRT directions, respectively. 2D/3D image registration uncertainties for intra‐cranial and extra‐cranial sites were comparable.Conclusion:The Varian Edge radiosurgery 6DOF‐based system, can perform 2D/3D image registration with high accuracy for target localization in image‐guided stereotactic radiosurgery.The work was supported by a Research Scholar Grant, RSG‐15‐137‐01‐CCE from the American Cancer Society.
SU‐D‐207A‐02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses
Authors: Yee S , Chinnaiyan P , Wloch J , Pirkola M , Yan D 
Published: July 2016

Purpose:The majority of quantitative analyses involving dynamic contrast enhanced (DCE) MRI have been performed to obtain kinetic parameters such as Ktrans and ve. Such analyses are generally performed assuming a “reversible” tissue compartment, where the tracer is assumed to be rapidly equilibrated between the plasma and tissue compartments. However, some tumor vascular environments may be more suited for a “non‐reversible” tissue compartment, where, as with FDG PET imaging, the tracer is continuously deposited into the tissue compartment (or the return back to the plasma compartment is very slow in the imaging time scale). Therefore, Patlak and Logan analyses, which represent tools for the “non‐reversible” and “reversible” modeling, respectively, were performed to better characterize the brain tumor vascular environment.Methods:A voxel‐by‐voxel analysis was performed to generate both Patlak and Logan plots in two brain tumor patients, one with grade III astrocytoma and the other with grade IV astrocytoma or glioblastoma. The slopes of plots and the r‐square were then obtained by linear fitting and compared for each voxel.Results:The 2‐dimensional scatter plots of Logan (Y‐axis) vs. Patlak slopes (X‐axis) clearly showed increased Logan slopes for glioblastoma (Figure 3A). The scatter plots of goodness‐of‐fit (Figure 3B) also suggested glioblastoma, relative to grade III astrocytoma, might consist of more voxels that are kinetically Logan‐like (i.e. rapidly equilibrated extravascular space and active vascular environment). Therefore, the enhanced Logan‐like behavior (and the Logan slope) in glioblastoma may imply an increased fraction of active vascular environment, while the enhanced Patlak‐like behavior implies the vascular environment permitting a relatively slower washout of the tracer.Conclusion:Although further verification is required, the combination of Patlak and Logan analyses in DCE MRI may be useful in characterizing the tumor vascular environment, and thus, may have implications in tumor grading and monitoring response to anti‐vascular therapy.
SU‐D‐207A‐04: Use of Gradient Echo Plural Contrast Imaging (GEPCI) in MR‐Guided Radiation Therapy: A Feasibility Study Targeting Brain Treatment
Authors: Cai B , Wen J , Rao Y , Tsien C , Huang J , Green O , Mutic S , Yablonskiy D , Gach H 
Published: July 2016

Purpose:To implement the Gradient Echo Plural Contrast Imaging(GEPCI) technique in MRI‐simulation for radiation therapy and assess the feasibility of using GEPCI images with advanced inhomogeneity correction in MRI‐guided radiotherapy for brain treatment.Methods:An optimized multigradient‐echo GRE sequence (TR=50ms;TE1=4ms;delta_TE=4ms;flip angle=300,11 Echoes) was developed to generate both structural (T1w and T2*w) and functional MRIs (field and susceptibility maps) from a single acquisition. One healthy subject (Subject1) and one post‐surgical brain cancer patient (Subject2) were scanned on a Philips Ingenia 1.5T MRI used for radiation therapy simulation. Another healthy subject (Subject3) was scanned on a 0.35T MRI‐guided radiotherapy (MR‐IGRT) system (ViewRay). A voxel spread function (VSF) was used to correct the B0 inhomogeneities caused by surgical cavities and edema for Subject2. GEPCI images and standard radiotherapy planning MRIs for this patient were compared focusing the delineation of radiotherapy target region.Results:GEPCI brain images were successfully derived from all three subjects with scan times of <7 minutes. The images derived for Subjects1&2 demonstrated that GEPCI can be applied and combined into radiotherapy MRI simulation. Despite low field, T1‐weighted and R2* images were successfully reconstructed for Subject3 and were satisfactory for contour and target delineation. The R2* distribution of grey matter (center=12,FWHM=4.5) and white matter (center=14.6, FWHM=2) demonstrated the feasibility for tissue segmentation and quantification. The voxel spread function(VSF) corrected surgical site related inhomogeneities for Subject2. R2* and quantitative susceptibility map(QSM) images for Subject2 can be used to quantitatively assess the brain structure response to radiation over the treatment course.Conclusion:We implemented the GEPCI technique in MRI‐simulation and in MR‐IGRT system for radiation therapy. The images demonstrated that it is feasible to adopt this technique in radiotherapy for structural delineation. The preliminary data also enable the opportunity for quantitative assessment of radiation response of the target region and normal tissue.
SU‐D‐207A‐07: The Effects of Inter‐Cycle Respiratory Motion Variation On Dose Accumulation in Single Fraction MR‐Guided SBRT Treatment of Renal Cell Carcinoma
Authors: Stemkens B , Glitzner M , Kontaxis C , Denis de Senneville B , Prins F , Crijns SPM , Kerkmeijer L , Lagendijk J , van den Berg CAT , Tijssen RHN 
Published: July 2016

Purpose:To assess the dose deposition in simulated single‐fraction MR‐Linac treatments of renal cell carcinoma, when inter‐cycle respiratory motion variation is taken into account using online MRI.Methods:Three motion characterization methods, with increasing complexity, were compared to evaluate the effect of inter‐cycle motion variation and drifts on the accumulated dose for an SBRT kidney MR‐Linac treatment: 1) STATIC, in which static anatomy was assumed, 2) AVG‐RESP, in which 4D‐MRI phase‐volumes were time‐weighted, based on the respiratory phase and 3) PCA, in which 3D volumes were generated using a PCA‐model, enabling the detection of inter‐cycle variations and drifts. An experimental ITV‐based kidney treatment was simulated in a 1.5T magnetic field on three volunteer datasets. For each volunteer a retrospectively sorted 4D‐MRI (ten respiratory phases) and fast 2D cine‐MR images (temporal resolution = 476ms) were acquired to simulate MR‐imaging during radiation. For each method, the high spatio‐temporal resolution 3D volumes were non‐rigidly registered to obtain deformation vector fields (DVFs). Using the DVFs, pseudo‐CTs (generated from the 4D‐MRI) were deformed and the dose was accumulated for the entire treatment. The accuracies of all methods were independently determined using an additional, orthogonal 2D‐MRI slice.Results:Motion was most accurately estimated using the PCA method, which correctly estimated drifts and inter‐cycle variations (RMSE=3.2, 2.2, 1.1mm on average for STATIC, AVG‐RESP and PCA, compared to the 2DMRI slice). Dose‐volume parameters on the ITV showed moderate changes (D99=35.2, 32.5, 33.8Gy for STATIC, AVG‐RESP and PCA). AVG‐RESP showed distinct hot/cold spots outside the ITV margin, which were more distributed for the PCA scenario, since inter‐cycle variations were not modeled by the AVG‐RESP method.Conclusion:Dose differences were observed when inter‐cycle variations were taken into account. The increased inter‐cycle randomness in motion as captured by the PCA model mitigates the local (erroneous) hotspots estimated by the AVG‐RESP method.
SU‐D‐209‐04: Raise Your Table: An Effective Way to Reduce Radiation Dose for Fluoroscopy
Authors: Huo D , Hoerner M , Toskich B , Rill L 
Published: July 2016

Purpose:Patient table height plays an important role in estimating patient skin dose for interventional radiology (IR) procedures, because the patient's skin location is dependent on the height of table. Variation in table height can lead to as much as 150% difference in skin dose for patient exams with similar air kerma meter readings. In our facility, IR procedural workflow was recently changed to require the IR physicians to confirm the patient table height before the procedure. The patient table height data was collected before and after this workflow change to validate the implementation of this practice.Methods:Table height information was analyzed for all procedures performed in three IR rooms, which were impacted by the workflow change, covering three months before and after the change (Aug 2015 to Jan 2016). In total, 442, 425, and 390 procedures were performed in these three rooms over this time period. There were no personnel or procedure assignment changes during the six‐month period of time. Statistical analysis was performed for the average table height changes before and after the workflow change.Results:For the three IR rooms investigated, after the workflow change, the average table heights were increased by 1.43 cm (p=0.004084), 0.66 cm (p=0.187089), and 1.59 cm (p=0.002193), providing a corresponding estimated skin dose savings of 6.76%, 2.94% and 7.62%, respectively. After the workflow change, the average table height was increased by 0.95 cm, 0.63 cm, 0.55 cm, 1.07 cm, 1.12 cm, and 3.36 cm for the six physicians who routinely work in these three rooms.Conclusion:Consistent improvement in table height settings has been observed for all IR rooms and all physicians following a simple workflow change. This change has led to significant patient dose savings by making physicians aware of the pre‐procedure table position.
SU‐D‐209‐05: Sensitivity of the Diagnostic Radiological Index of Protection (DRIP) to Procedural Factors in Fluoroscopy
Authors: Jones A , Pasciak A , Wagner L 
Published: July 2016

Purpose:To evaluate the sensitivity of the Diagnostic Radiological Index of Protection (DRIP) to procedural factors in fluoroscopy in an effort to determine an appropriate set of scatter‐mimicking primary beams (SMPB) to be used in measuring the DRIP.Methods:A series of clinical and factorial Monte Carlo simulations were conducted to determine the shape of the scattered X‐ray spectra incident on the operator in different clinical fluoroscopy scenarios. Two clinical evaluations studied the sensitivity of the scattered spectrum to gantry angle and patient size while technical factors were varied according to measured automatic dose rate control (ADRC) data. Factorial evaluations studied the sensitivity of the scattered spectrum to gantry angle, field of view, patient size and beam quality for constant technical factors. Average energy was the figure of merit used to condense fluence in each energy bin to a single numerical index.Results:Beam quality had the strongest influence on the scattered spectrum in fluoroscopy. Many procedural factors affected the scattered spectrum indirectly through their effects on primary beam quality through ADRC, e.g., gantry angle and patient size. Lateral C‐arm rotation, common in interventional cardiology, increased the energy of the scattered spectrum, regardless of the direction of rotation. The effect of patient size on scattered radiation depended on ADRC characteristics, patient size, and procedure type.Conclusion:The scattered spectrum striking the operator in fluoroscopy, and therefore the DRIP, is most strongly influenced by primary beam quality, particularly kV. Use cases for protective garments should be classified by typical procedural primary beam qualities, which are governed by the ADRC according to the impacts of patient size, anatomical location, and gantry angle. These results will help determine an appropriate set of SMPB to be used for measuring the DRIP.
SU‐D‐209‐06: Study On the Dose Conversion Coefficients in Pediatric Radiography with the Development of Children Voxel Phantoms
Authors: Liu Q , Zhuo W , Liu H , Liu Y , Chen T 
Published: July 2016

Purpose:Conversion coefficients of organ dose normalized to entrance skin dose (ESD) are widely used to evaluate the organ doses directly using ESD without time‐consuming dose measurement, this work aims to investigate the dose conversion coefficients in pediatric chest and abdomen radiography with the development of 5 years and 10 years old children voxel phantoms.Methods:After segmentation of organs and tissues from CT slice images of ATOM tissue‐equivalent phantoms, a 5‐year‐old and a 10‐year‐old children computational voxel phantoms were developed for Monte Carlo simulation. The organ doses and the entrance skin dose for pediatric chest postero‐anterior projection and abdominal antero‐posterior projection were simulated at the same time, and then the organ dose conversion coefficients were calculated.To verify the simulated results, dose measurement was carried out with ATOM tissue‐equivalent phantoms for 5 year chest radiography.Results:Simulated results and experimental results matched very well with each other, the result differences of all the organs covered in radiation field were below 16% for 5‐year‐old child in chest projection. I showed that the conversion coefficients of organs covered in the radiation field were much larger than organs out of the field for all the study cases, for example, the conversion coefficients of stomach, liver intestines, and pancreas are larger for abdomen radiography while conversion coefficients of lungs are larger for chest radiography.Conclusion:The voxel children phantoms were helpful to evaluate the radiation doses more accurately and efficiently. Radiation field was the essential factor that affects the organ dose, use reasonably small field should be encouraged for radiation protection.This work was supported by the National Natural Science Foundation of China(11475047)
SU‐D‐209‐07: Measure the Average Glandular Dose of a 2D+3D Breast Imaging Protocol Using GE SenoClaire Breast Tomosynthesis System
Authors: Liang Y , Dutta A 
Published: July 2016

Purpose:To measure the average glandular dose (AGD) of a 2D+3D breast imaging protocol using GE SenoClaire breast tomosynthesis system.Methods:This study used a GE SenoClaire breast tomosynthesis unit, a Gammex ACR mammography accreditation phantom, 5 cm thick PMMA phantom, an Unfors RaySafe X2 mammography detector. The breast imaging protocol includes a regular 2D CC view and a 3D MLO view at 45 degree, using AUTO mode. Both ACR phantom and PMMA phantom were scanned under AUTO mode with 10 daN compression to obtain the techniques of 2D CC view, 3D MLO view, and 3D CC view. The techniques of ACR phantom were used for the following manual scan with only RaySafe X2 detector being positioned under the same compression paddle at the same height as the ACR phantom. The detector is at 3 cm from the chest wall edge and laterally centered in the X‐ray field. Measurements were repeated with detector at 6 cm and 9 cm from the chest wall edge. The above procedure were repeated using the manual techniques of PMMA phantom. The measured entrance skin air Kerma was then converted to the AGD using twoMethods:one was listed in GE QC manual; the other was based on AAPM Report 223.Results:The AGD from 2D+3D imaging for both breasts using AUTO mode is approximately 4.25 mGy for ACR phantom and approximately 6 mGy for 5 cm thick PMMA phantom. The difference between 3D MLO view and 3D CC view is less than 2%. The difference between two methods is also less than 3%.Conclusion:The AGD of a 2D +3D breast imaging using GE SenoClaire is comparable to two regular 2D images if both are scanned using AUTO mode.
SU‐D‐207B‐01: Radiomics Feature Reproducibility From Repeat CT Scans of Patients with Rectal Cancer
Authors: Hu P , Wang J , Zhong H , Zhou Z , Shen L , Hu W , Zhang Z 
Published: July 2016

Purpose:To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer.Methods:40 rectal cancer patients were enrolled in this study, each of whom underwent two CT scans within average 8.7 days (5 days to 17 days), before any treatment was delivered. The rectal gross tumor volume (GTV) was distinguished and segmented by an experienced oncologist in both CTs. Totally, more than 2000 radiomics features were defined in this study, which were divided into four groups (I: GLCM, II: GLRLM III: Wavelet GLCM and IV: Wavelet GLRLM). For each group, five types of features were extracted (Max slice: features from the largest slice of target images, Max value: features from all slices of target images and choose the maximum value, Min value: minimum value of features for all slices, Average value: average value of features for all slices, Matrix sum: all slices of target images translate into GLCM and GLRLM matrices and superpose all matrices, then extract features from the superposed matrix). Meanwhile a LOG (Laplace of Gauss) filter with different parameters was applied to these images. Concordance correlation coefficients (CCC) and inter‐class correlation coefficients (ICC) were calculated to assess the reproducibility.Results:403 radiomics features were extracted from each type of patients’ medical images. Features of average type are the most reproducible. Different filters have little effect for radiomics features. For the average type features, 253 out of 403 features (62.8%) showed high reproducibility (ICC≥0.8), 133 out of 403 features (33.0%) showed medium reproducibility (0.8≥ICC≥0.5) and 17 out of 403 features (4.2%) showed low reproducibility (ICC≥0.5).Conclusion:The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.