bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐E‐J‐180: Monitoring Thermochemical Ablation Using Fast Chemical Shift Magnetic Resonance Imaging
Authors: MacLellan C , Maier F , Cressman E , Stafford R 
Published: July 2014

Purpose:To investigate the feasibility of using fast chemical shift imaging (fCSI) to directly image the chemical species associated with exothermic acid/base reactions during thermochemical ablation (TCA) injections.Methods:Five different mixtures of 10M acetic acid and 10M sodium hydroxide representing pure reagents, partial neutralization, and complete neutralization (1:0, 3:1, 1:1, 1:3, 0:1) were prepared in 15mL centrifuge tubes to assess impact on fCSI. An MR spectroscopy (MRS) acquisition provided corroborative data. An fCSI acquisition used a multi gradient echo acquisition (n=16) with autoregressive moving average model based spectral estimation. The acquisition was repeated 8 times with shifted echo trains to effectively increase the number of echoes per k‐space line to 128 and the spectral bandwidth from 2.82 ppm to 22.7 ppm. The T1 of each sample was measured using inversion recovery FSE.Results:The 1H chemical shift of acetate measured via MRS was 2.65 ppm and 2.40 ppm to 2.87 ppm (mean=2.63 ppm) on fCSI, with 2.8 ppm expected. The difference between the chemical shift of water and acetate within the same sample and the T1 in each sample increase with the concentration of acetate ion and range from 2.82ppm to 3.90 ppm and 323ms to 1743ms, respectively.Conclusion:In this work we evaluated a fCSI acquisition for measuring the MR parameters of acid and base solutions that have been investigated for use in TCA. The importance of shimming the main magnetic field was highlighted by the variation in the position of the acetate peak in the fCSI acquisition. The changes in the chemical shift difference between water and acetate and T1 relaxation suggest a dependence on acetate ion concentration that may be useful and must be accounted for in the monitoring of these procedures.
SU‐E‐J‐181: Magnetic Resonance Image‐Guided Radiation Therapy Workflow: Initial Clinical Experience
Authors: Green O , Kashani R , Santanam L , Hand T , Steele C , Victoria J , Wooten H , Li H , Rodriguez V , Hu Y , Mutic S 
Published: July 2014

Purpose:The aims of this work are to describe the workflow and initial clinical experience treating patients with an MRI‐guided radiotherapy (MRIGRT) system.Methods:Patient treatments with a novel MR‐IGRT system started at our institution in mid‐January. The system consists of an on‐board 0.35‐T MRI, with IMRT‐capable delivery via doubly‐focused MLCs on three 6 0 Co heads. In addition to volumetric MR‐imaging, real‐time planar imaging is performed during treatment. So far, eleven patients started treatment (six finished), ranging from bladder to lung SBRT. While the system is capable of online adaptive radiotherapy and gating, a conventional workflow was used to start, consisting of volumetric imaging for patient setup using visible tumor, evaluation of tumor motion outside of PTV on cine images, and real‐time imaging. Workflow times were collected and evaluated to increase efficiency and evaluate feasibility of adding the adaptive and gating features while maintaining a reasonable patient throughput.Results:For the first month, physicians attended every fraction to provide guidance on identifying the tumor and an acceptable level of positioning and anatomical deviation. Average total treatment times (including setup) were reduced from 55 to 45 min after physician presence was no longer required and the therapists had learned to align patients based on soft‐tissue imaging. Presently, the source strengths were at half maximum (7.7K Ci each), therefore beam‐on times will be reduced after source replacement. Current patient load is 10 per day, with increase to 25 anticipated in the near future.Conclusion:On‐board, real‐time MRI‐guided RT has been incorporated into clinical use. Treatment times were kept to reasonable lengths while including volumetric imaging, previews of tumor movement, and physician evaluation. Workflow and timing is being continuously evaluated to increase efficiency. In near future, adaptive and gating capabilities of the system will be implemented.
SU‐E‐J‐192: Verification of 4D‐MRI Internal Target Volume Using Cine MRI
Authors: Lafata K , Czito B , Palta M , Bashir M , Yin F , Cai J 
Published: July 2014

Purpose:To investigate the accuracy of 4D‐MRI in determining the Internal Target Volume (ITV) used in radiation oncology treatment planning of liver cancers. Cine MRI is used as the standard baseline in establishing the feasibility and accuracy of 4D‐MRI tumor motion within the liver.Methods:IRB approval was obtained for this retrospective study. Analysis was performed on MR images from four patients receiving external beam radiation therapy for liver cancer at our institution. Eligible patients received both Cine and 4D‐MRI scans before treatment. Cine images were acquired sagittally in real time at a slice bisecting the tumor, while 4D images were acquired volumetrically. Cine MR DICOM headers were manipulated such that each respiratory frame was assigned a unique slice location. This approach permitted the treatment planning system (Eclipse, Varian Medical Systems) to recognize a complete respiratory cycle as a “volume”, where the gross tumor was contoured temporally. Software was developed to calculate the union of all frame contours in the structure set, resulting in the corresponding plane of the ITV projecting through the middle of the tumor, defined as the Internal Target Area (ITA). This was repeated for 4D‐MRI, at the corresponding slice location, allowing a direct comparison of ITAs obtained from each modality.Results:Four patients have been analyzed. ITAs contoured from 4D‐MRI correlate with contours from Cine MRI. The mean error of 4D values relative to Cine values is 7.67 +/− 2.55 %. No single ITA contoured from 4D‐MRI demonstrated more than 10.5 % error compared to its Cine MRI counterpart.Conclusion:Motion management is a significant aspect of treatment planning within dynamic environments such as the liver, where diaphragmatic and cardiac activity influence plan accuracy. This small pilot study suggests that 4D‐MRI based ITA measurements agree with Cine MRI based measurements, an important step towards clinical implementation.NIH 1R21CA165384‐01A1
SU‐E‐J‐193: Feasibility of MRI‐Only Based IMRT Planning for Pancreatic Cancer
Authors: Prior P , Botros M , Chen X , Paulson E , Erickson B , Li X 
Published: July 2014

Purpose:With the increasing use of MRI simulation and the advent of MRI‐guided delivery, it is desirable to use MRI only for treatment planning. In this study, we assess the dosimetric difference between MRI‐ and CTbased IMRT planning for pancreatic cancer.Methods:Planning CTs and MRIs acquired for a representative pancreatic cancer patient were used. MRI‐based planning utilized forced relative electron density (rED) assignment of organ specific values from IRCU report 46, where rED = 1.029 for PTV and a rED = 1.036 for non‐specified tissue (NST). Six IMRT plans were generated with clinical dose‐volume (DV) constraints using a research Monaco planning system employing Monte Carlo dose calculation with optional perpendicular magnetic field (MF) of 1.5T. The following five plans were generated and compared with the planning CT: 1.) CT plan with MF and dose recalculation without optimization; 2.) MRI (T2) plan with target and OARs redrawn based on MRI, forced rED, no MF, and recalculation without optimization; 3.) Similar as in 2 but with MF; 4.) MRI plan with MF but without optimization; and 5.) Similar as in 4 but with optimization.Results:Generally, noticeable differences in PTV point doses and DV parameters (DVPs) between the CT‐and MRI‐based plans with and without the MF were observed. These differences between the optimized plans were generally small, mostly within 2%. Larger differences were observed in point doses and mean doses for certain OARs between the CT and MRI plan, mostly due to differences between image acquisition times.Conclusion:MRI only based IMRT planning for pancreatic cancer is feasible. The differences observed between the optimized CT and MRI plans with or without the MF were practically negligible if excluding the differences between MRI and CT defined structures.
SU‐E‐J‐197: A Moving Least Squares Approach for Computing Spatially Accurate Transformations That Satisfy Strict Physiologic Constraints
Authors: Castillo E , Castillo R , Fuentes D , Guerrero T 
Published: July 2014

Purpose:To efficiently compute a physiologically realistic spatial transformation from a sparse point cloud of displacement estimates using Moving Least Squares (MLS) and any combination of upper bound, lower bound, or equality constraints placed on the Jacobian. Whereas diffeomorphic deformable image registration (DIR) requires the transformation's Jacobian determinant to be positive, within the context of thoracic CT, a more appropriate constraint is to require positive Jacobian values that reflect a strictly contracting volume (inhale to exhale DIR) or expanding volume (exhale to inhale DIR).Methods:Jacobian constraints manifest as nonlinear inequality constraints that considerably complicate DIR computation. However, MLS defines a spatial transformation from a sparse point cloud of estimated displacements and provides simple analytic derivative estimates for all voxel locations. Given displacement estimates from automated block matching algorithm, an optimal MLS spatial transformation is determined by computing the minimal perturbation to the displacement data required to yield an MLS transformation that satisfies the Jacobian constraints.Results:Five publicly available (cases 6‐10 from www.dir‐lab.com) inhale/exhale thoracic CT image pairs each with 300 landmarks (for DIR validation) were registered by first obtaining a sparse point cloud of displacement estimates via block matching. Two MLS transformations were then computed, one with no Jacobian constraints and the other with strict contraction Jacobian constraints. Both MLS fields achieved similarly low average millimeter error on all five cases (between 1.16 – 1.26). However, the constrained MLS yielded a strict contraction (all Jacobian values between 0 and 1) while the unconstrained MLS resulted in regions of expansion (Jacobian values larger than 1) despite registering from inhale to exhale.Conclusion:The proposed MLS approach is capable of producing Jacobian constrained transformations without degrading spatial accuracy. Though applied to block match estimates, the approach can be employed in conjunction with displacement estimates from any DIR algorithm.
SU‐E‐J‐199: Evaluation of Motion Tracking Effects On Stereotactic Body Radiotherapy of Abdominal Targets
Authors: Monterroso M , Dogan N , Yang Y 
Published: July 2014

Purpose:To evaluate the effects of respiratory motion on the delivered dose distribution of CyberKnife motion tracking‐based stereotactic body radiotherapy (SBRT) of abdominal targets.Methods:Four patients (two pancreas and two liver, and all with 4DCT scans) were retrospectively evaluated. A plan (3D plan) using CyberKnife Synchrony was optimized on the end‐exhale phase in the CyberKnife's MultiPlan treatment planning system (TPS), with 40Gy prescribed in 5 fractions. A 4D plan was then created following the 4D planning utility in the MultiPlan TPS, by recalculating dose from the 3D plan beams on all 4DCT phases, with the same prescribed isodose line. The other seven phases of the 4DCT were then deformably registered to the end‐exhale phase for 4D dose summation. Doses to the target and organs at risk (OAR) were compared between 3D and 4D plans for each patient. The mean and maximum doses to duodenum, liver, spinal cord and kidneys, and doses to 5cc of duodenum, 700cc of liver, 0.25cc of spinal cord and 200cc of kidneys were used.Results:Target coverage in the 4D plans was about 1% higher for two patients and about 9% lower in the other two. OAR dose differences between 3D and 4D varied among structures, with doses as much as 8.26Gy lower or as much as 5.41Gy higher observed in the 4D plans.Conclusion:The delivered dose can be significantly different from the planned dose for both the target and OAR close to the target, which is caused by the relative geometry change while the beams chase the moving target. Studies will be performed on more patients in the future. The differences of motion tracking versus passive motion management with the use of internal target volumes will also be investigated.
SU‐E‐J‐208: Fast and Accurate Auto‐Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy
Authors: Gupta V , Wang Y , Romero A , Myronenko A , Jordan P , Heijmen B , Hoogeman M 
Published: July 2014

Purpose:Various studies have demonstrated that online adaptive radiotherapy by real‐time re‐optimization of the treatment plan can improve organs‐at‐risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto‐segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto‐segmentation method that uses fully automated non‐rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans.Methods:OARs were manually contoured by an expert panel to obtain ground truth contours for repeat CT scans (3 per patient) of 10 patients. For the non‐rigid alignment, we used a new non‐rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto‐segmentation, we compared the propagated and ground truth contours using two widely used metrics‐ Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto‐segmentation.Results:For all organs, the auto‐segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively.Conclusion:Based on the achieved accuracy and computational time we conclude that the investigated auto‐segmentation method overcomes an important hurdle to the clinical implementation of online adaptive radiotherapy.Partial funding for this work was provided by Accuray Incorporated as part of a research collaboration with Erasmus MC Cancer Institute.
SU‐E‐J‐212: Identifying Bones From MRI: A Dictionary Learnign and Sparse Regression Approach
Authors: Ruan D , Yang Y , Cao M , Hu P , Low D 
Published: July 2014

Purpose:To develop an efficient and robust scheme to identify bony anatomy based on MRI‐only simulation images.Methods:MRI offers important soft tissue contrast and functional information, yet its lack of correlation to electron‐density has placed it as an auxiliary modality to CT in radiotherapy simulation and adaptation. An effective scheme to identify bony anatomy is an important first step towards MR‐only simulation/treatment paradigm and would satisfy most practical purposes. We utilize a UTE acquisition sequence to achieve visibility of the bone. By contrast to manual + bulk or registration‐to identify bones, we propose a novel learning‐based approach for improved robustness to MR artefacts and environmental changes. Specifically, local information is encoded with MR image patch, and the corresponding label is extracted (during training) from simulation CT aligned to the UTE. Within each class (bone vs. nonbone), an overcomplete dictionary is learned so that typical patches within the proper class can be represented as a sparse combination of the dictionary entries. For testing, an acquired UTE‐MRI is divided to patches using a sliding scheme, where each patch is sparsely regressed against both bone and nonbone dictionaries, and subsequently claimed to be associated with the class with the smaller residual.Results:The proposed method has been applied to the pilot site of brain imaging and it has showed general good performance, with dice similarity coefficient of greater than 0.9 in a crossvalidation study using 4 datasets. Importantly, it is robust towards consistent foreign objects (e.g., headset) and the artefacts relates to Gibbs and field heterogeneity.Conclusion:A learning perspective has been developed for inferring bone structures based on UTE MRI. The imaging setting is subject to minimal motion effects and the post‐processing is efficient. The improved efficiency and robustness enables a first translation to MR‐only routine. The scheme generalizes to multiple tissue classes.
SU‐E‐J‐273: Simulation of the Radiation Response of Hypoxic Tumors
Authors: Espinoza I , Peschke P , Karger C 
Published: July 2014

Purpose:In radiotherapy, it is important to predict the response of tumour to irradiation prior to the treatment. Mathematical modelling of tumour control probability (TCP) based on the dose distribution, medical imaging and other biological information may help to improve this prediction and to optimize the treatment plan. The aim of this work is to develop an image based 3D multiscale radiobiological model, which describes the growth and the response to radiotherapy of hypoxic tumors.Methods:The computer model is based on voxels, containing tumour, normal (including capillary) and dead cells. Killing of tumour cells due to irradiation is calculated by the Linear Quadratic Model (extended for hypoxia), and the proliferation and resorption of cells are modelled by exponential laws. The initial shape of the tumours is taken from CT images and the initial vascular and cell density information from PET and/or MR images. Including the fractionation regime and the physical dose distribution of the radiation treatment, the model simulates the spatial‐temporal evolution of the tumor. Additionally, the dose distribution may be biologically optimized.Results:The model describes the appearance of hypoxia during tumour growth and the reoxygenation processes during radiotherapy. Among other parameters, the TCP is calculated for different dose distributions. The results are in accordance with published results.Conclusion:The simulation model may contribute to the understanding of the influence of biological parameters on tumor response during treatment, and specifically on TCP. It may be used to implement dose‐painting approaches. Experimental and clinical validation is needed.This study is supported by a grant from the Ministry of Education of Chile, Programa Mece Educacion Superior (2).
SU‐E‐T‐06: A Comparison of IMRT Treatment of Esophageal Carcinoma in Elekta‐Precise and Varian23EX Linac
Authors: Bai W , Fan X , qiu r , Qiao X , Zhang R 
Published: July 2014

Purpose:To compare and analyze the characteristics of static intensity‐modulated radiotherapy (IMRT) plans designed on Elekta and Varian Linac in different esophageal cancer(EC), exploring advantages and disadvantages of different vendor Linac, thus can be better serve for clinical.Methods:Twenty‐four patients with EC were selected, including 6 cases located in the cervical, upper, middle and the lower thorax, respectively. Two IMRT plans were generated with the Oncentra planning system: in Elekta and Varian Linac, prescription dose of 60Gy in 30 fractions to the PTV. We examined the dose‐volume histogram parameters of PTV and the organs at risk (OAR) such as lungs, spinal cord and heart, and additional Monitor units(MU), treatment time, Homogeneity index(HI), Conformity index(CI) and Gamma index comparisons were performed.Results:All plans resulted in abundant dose coverage of PTV for EC of different locations. The doses to PTV, HI and OAR in Elekta plans were not statistically different in comparison with Varian plans, with the following exceptions: in cervical, upper and lower thoracic EC the PTV's CI, and in middle thorax EC PTV's D2, D50, V105 and PTV‐average were better in Elekta plans than in Varian plans. In the cervical, upper and the middle thorax EC, treatment time were significantly decreased in Varian plans as against Elekta plans, while in the lower thoracic EC treatment time were no striking difference. MUs and gamma index were similar between the two Linac plans.Conclusion:For the the middle thorax EC Varian plans is better than Elekta plans, not only in treatment time but in the PTV dose; while for the lower thorax EC Elekta plans is the first choice for better CI; for the other part of the EC usually Elekta plans can increase the CI, while Varian plans can reduce treatment time, can be selected according to the actual situation of the patient treatment.
SU‐E‐T‐08: A Convolution Model for Head Scatter Fluence in the Intensity Modulated Field
Authors: Chen M , Mo X , Chen Y , Parnell D , Key S , Olivera G , Galmarini W , Lu W 
Published: July 2014

Purpose:To efficiently calculate the head scatter fluence for an arbitrary intensity‐modulated field with any source distribution using the source occlusion model.Method:The source occlusion model with focal and extra focal radiation (Jaffray et al, 1993) can be used to account for LINAC head scatter. In the model, the fluence map of any field shape at any point can be calculated via integration of the source distribution within the visible range, as confined by each segment, using the detector eye's view. A 2D integration would be required for each segment and each fluence plane point, which is time‐consuming, as an intensity‐modulated field contains typically tens to hundreds of segments. In this work, we prove that the superposition of the segmental integrations is equivalent to a simple convolution regardless of what the source distribution is. In fact, for each point, the detector eye's view of the field shape can be represented as a function with the origin defined at the point's pinhole reflection through the center of the collimator plane. We were thus able to reduce hundreds of source plane integration to one convolution. We calculated the fluence map for various 3D and IMRT beams and various extra‐focal source distributions using both the segmental integration approach and the convolution approach and compared the computation time and fluence map results of both approaches.Results:The fluence maps calculated using the convolution approach were the same as those calculated using the segmental approach, except for rounding errors (<0.1%). While it took considerably longer time to calculate all segmental integrations, the fluence map calculation using the convolution approach took only ∼1/3 of the time for typical IMRT fields with ∼100 segments.Conclusions:The convolution approach for head scatter fluence calculation is fast and accurate and can be used to enhance the online process.