bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐C‐12A‐04: Quantification of Hepatic Perfusion Maps From DCE MRI Using Spatial Regularization
Authors: Wang H , Cao Y 
Published: July 2014

Purpose:To reduce uncertainty in hepatic perfusion quantification from DCE‐MRI for assessing tumor and normal tissue response to RT in intrahepatic cancer.Methods:Pharmacokinetic modeling of liver DCE‐MRI estimates arterial inflow rate (ka), portal venous inflow rate (kp), central venous outflow rate (kl) and bolus arrival time delays (ta, tp) from respective arterial and portal vein input functions to tissue. The parametric images estimated by the conventional approach could exhibit large variance and severe bias. To reduce the uncertainty in the quantitative images, we incorporated the prior knowledge, the slowly spatial variation of the time delays in the liver, into the model by adding spatial regulations on the time delays. The weighting factors of regularizations were determined by Stein’s unbiased risk estimate (SURE) of the mean squared prediction error (MSPE). The regularized model was optimized by the conjugate gradient minimization and implemented on the GPU to achieve fast computation. The method was evaluated by simulated and patient DCE‐MRI data. The simulated perfusion image was generated with (k2, ka, kp) of (400, 20,100 ml/(100g min)), smooth (ta, tp) maps in a 64×64 matrix, and Gaussian random noise to have contrast‐to‐noise ratios (CNR) of 10 to 100.Results:Compared to the conventional estimation, the proposed method reduced estimate variances from 14% to 8% for k2, 38% to 9% for ka, and 14% to 10% for kp in the simulated data with 20 CNR. The SURE‐based method consistently led to the optimal weight of the regularization determined by the true MSPE on the simulation data. Regularizing time delays improved the hepatic perfusion images of the patient data.Conclusion:The improved repeatability and possible accuracy in hepatic perfusion images quantified from DCE‐MRI have the potential to increase statistical power in clinical application of the physiological images for predicting outcome of liver cancer treatment.The work was supported by NIH/NCI grant RO1CA132834.
TU‐C‐12A‐09: Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemo‐Radiotherapy Using Quantitative PET/CT Features, Clinical Parameters and Demographics
Authors: Zhang H , Tan S , Chen W , Kligerman S , Kim G , D’Souza W , Suntharalingam M , Lu W 
Published: July 2014

Purpose:To develop predictive models using quantitative PET/CT features for the evaluation of tumor response to neoadjuvant chemo‐radiotherapy (CRT) in patients with locally advanced esophageal cancer.Methods:This study included 20 patients who underwent tri‐modality therapy (CRT + surgery) and had 18F‐FDG PET/CT scans before initiation of CRT and 4‐6 weeks after completion of CRT but prior to surgery. Four groups of tumor features were examined: (1) conventional PET/CT response measures (SUVmax, tumor diameter, etc.); (2) clinical parameters (TNM stage, histology, etc.) and demographics; (3) spatial‐temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changes resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross‐validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, using cross‐validations to avoid model over‐fitting. Prediction accuracy was assessed via area under the receiver operating characteristic curve (AUC), and precision was evaluated via confidence intervals (CIs) of AUC.Results:When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). Using spatial‐temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications), significantly better than using conventional PET/CT measures or clinical parameters and demographics alone. For groups with a large number of tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than the LR model.Conclusion:The SVM model using all features including quantitative PET/CT features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer.This work was supported in part by National Cancer Institute Grant R21 CA131979 and R01 CA172638. Shan Tan was supported in part by the National Natural Science Foundation of China 60971112 and 61375018, and by Fundamental Research Funds for the Central Universities 2012QN086.
TU‐E‐BRD‐01: President’s Symposium: The Necessity of Innovation in Medical Physics
Authors: Bayouth J , Siewerdsen J , Wahl E 
Published: July 2014

This abstract will not blow you away, but speed‐painting presenter Erik Wahl will certainly make a truly unique AAPM symposium that you will not want to miss. Along with clinical director John Bayouth and scientific leader Jeff Siewerdsen, this session will highlight innovation. To avoid being button pushers and irrelevant investigators of yesterday’s science, we must innovate. This is particularly challenging in the changing landscape of declining research funding and healthcare reimbursement.But all hope is not lost, Medical Physics is a field born out of innovation. As scientists we quickly translated the man‐made and natural phenomena of radiation into a tool that could diagnose broken bones, locate foreign objects imbedded within the body, and treat a spectrum of diseases. As hyperbolae surrounding the curative powers of radiation overcame society, physicists continued their systematic pursuit of a fundamental understanding of radiation and applied their knowledge to enable the diagnostic and therapeutic power of this new tool.Health economics and the decline in research funding have put the Medical Physicist in a precarious position: how do we optimally participate in medical research and advanced patient care in the face of many competing needs? Today's diagnostic imaging and therapeutic approaches are tremendously sophisticated. Researchers and commercial vendors are producing technologies at a remarkable rate; to enable their safe and effective implementation Medical Physicists must work from a fundamental understanding of these technologies. This requires all of us, clinically practicing Medical Physicists, Researchers and Educators alike, to combine our training in scientific methods with innovation.Innovation is the key to our past, a necessity for our contemporary challenges, and critical for the future of Medical Physics. The keynote speakers for the 2014 AAPM Presidential Symposium session will address the way we approach these vitally important technologies for diagnosis and therapy into opportunities to innovate. The speed‐painting artist and lecturer Erik Wahl will finish the symposium with a fast‐paced and entertaining presentation on embracing the future by creating disruptive innovation strategies.Learning Objectives:

Identify connection between Medical Physics and Innovation.
Understand how Innovation enables Clinical Medical Physicists to implement novel technologies.
Learn how innovative Medical Physics solutions can address significant and relevant challenges in science.
Become inspired to pursue a new scientific understanding, positive change in clinical practice, and benefit to patients.
TU‐F‐BRE‐03: Application of a Novel Mass‐Density Compensation Optimization Method to Improve the Response of a Liquid‐Filled Ionization Chamber in Nonstandard Fields
Authors: Kamio Y , Bouchard H 
Published: July 2014

Purpose:To improve the response of the microLion detector (PTW 31018) in small field conditions by optimizing the density of the detector's non‐sensitive components using a novel method based on the detector's dose response function.Methods:The central values h(0,0) of the perturbation functions for the microLion detector and a volume of water equivalent to its sensitive volume were calculated using the Monte Carlo user code egs_chamber by scoring the dose absorbed by a 6 MV photon pencil beam incident on their centroids. Values of h(0,0) were plotted as a function of the density of the microLion's graphite electrode with the detector placed in the axial orientation. The optimized density was found by finding the minimal value of h(0,0).Results:A density of 1.37 g/cm3 was found to minimize the perturbation function of the microLion detector. The modified microLion's response was then evaluated in small square fields with sides in the range of 5 – 40 mm and found to be consistent with highly watere‐quivalent detectors such as a scintillating detector (Exradin W1) and a generic alanine detector in both axial and radial orientations.Conclusion:This work illustrates a novel method which can used to optimize the design of radiation detectors in small fields. This method should also work with other optimization parameters (e.g. thickness of electrode). Density‐compensated detectors have the potential to eliminate the need to evaluate nonstandard field correction factors as described by the IAEA‐AAPM formalism (Alfonso et al.) and simplify future dosimetry protocols for SRS/SBRT modalities. Finally, we also expect an improvement in the response of density‐compensated detectors for composite IMRT fields.
TU‐F‐BRE‐04: Development of a High‐Resolution EPID Based Dosimetry Strategy for Radiosurgery QA
Authors: Han B , Ding A , Xing L , Wang L 
Published: July 2014

Purpose:To systematically investigate a high spatial‐resolution (0.2mm) electronic portal imaging device (EPID) for CyberKnife (CK) based radiosurgery system quality assurance (QA).Methods:An EPID‐based dosimetric measurement technique is applied to CK output measurement and field size verification. A Monte Carlo (MC) simulated pixel‐to‐pixel EPID response specific to CK is used to convert a raw EPID‐measured image of a radiosurgery field into water‐based dose distribution. The output factors are measured using EPID for radiosurgery fields formed by fixed and variable aperture (Iris) cones. Circular fields of 5, 7.5, 10, 15, 30 and 60mm diameters are measured and compared with diode measurements. The equivalent diameters are determined by analyzing the area received dose greater than half maximum.Results:For both fixed and Iris cones, the EPID measured output factors of circular fields of 5mm to 60mm diameters are in good agreement with the radiosurgery diode measurements. The mean output differences are 1.0% and 1.5% for fixed and Iris cone respectively. The max differences are 2.2% for the 15mm fixed cone, and 1.8% for the 10mm Iris field. The equivalent diameters derived from the EPID measurements are in good agreement comparing to the water scan result with mean differences of 0.21±0.09mm and 0.02±0.22mm for fixed and Iris cone, respectively. The high detector density EPID is able to measure the whole radiation field and identify the field edge and center. Therefore, there is no need to align the detector center perfectly at field center and the setup time is greatly reduced for QA.Conclusion:The high spatial‐resolution EPID is proved to be an accurate and efficient dosimetric tool for radiosurgery QA and especially useful in Cyberknife QA for variable aperture collimators.
TU‐F‐BRF‐03: Effect of Radiation Therapy Planning Scan Registration On the Dose in Lung Cancer Patient CT Scans
Authors: Cunliffe A , Contee C , White B , Justusson J , Armato S , Malik R , Al‐Hallaq H 
Published: July 2014

Purpose:To characterize the effect of deformable registration of serial computed tomography (CT) scans on the radiation dose calculated from a treatment planning scan.Methods:Eighteen patients who received curative doses (≥60Gy, 2Gy/fraction) of photon radiation therapy for lung cancer treatment were retrospectively identified. For each patient, a diagnostic‐quality pre‐therapy (4–75 days) CT scan and a treatment planning scan with an associated dose map calculated in Pinnacle were collected. To establish baseline correspondence between scan pairs, a researcher manually identified anatomically corresponding landmark point pairs between the two scans. Pre‐therapy scans were co‐registered with planning scans (and associated dose maps) using the Plastimatch demons and Fraunhofer MEVIS deformable registration algorithms. Landmark points in each pretherapy scan were automatically mapped to the planning scan using the displacement vector field output from both registration algorithms. The absolute difference in planned dose (|ΔD|) between manually and automatically mapped landmark points was calculated. Using regression modeling, |ΔD| was modeled as a function of the distance between manually and automatically matched points (registration error, E), the dose standard deviation (SD_dose) in the eight‐pixel neighborhood, and the registration algorithm used.Results:52–92 landmark point pairs (median: 82) were identified in each patient's scans. Average |ΔD| across patients was 3.66Gy (range: 1.2–7.2Gy). |ΔD| was significantly reduced by 0.53Gy using Plastimatch demons compared with Fraunhofer MEVIS. |ΔD| increased significantly as a function of E (0.39Gy/mm) and SD_dose (2.23Gy/Gy).Conclusion:An average error of <4Gy in radiation dose was introduced when points were mapped between CT scan pairs using deformable registration. Dose differences following registration were significantly increased when the Fraunhofer MEVIS registration algorithm was used, spatial registration errors were larger, and dose gradient was higher (i.e., higher SD_dose). To our knowledge, this is the first study to directly compute dose errors following deformable registration of lung CT scans.
TU‐F‐BRF‐04: Registration of 3D Transesophageal Echocardiography and X‐Ray Fluoroscopy Using An Inverse Geometry X‐Ray System
Authors: Speidel M , Hatt C , Tomkowiak M , Funk T , Raval A 
Published: July 2014

Purpose:To develop a method for the fusion of 3D echocardiography and Scanning‐Beam Digital X‐ray (SBDX) fluoroscopy to assist with catheter device and soft tissue visualization during interventional procedures.Methods:SBDX is a technology for low‐dose inverse geometry x‐ray fluoroscopy that performs digital tomosynthesis at multiple planes in real time. In this study, transesophageal echocardiography (TEE) images were fused with SBDX images by estimating the 3D position and orientation (the “pose”) of the TEE probe within the x‐ray coordinate system and then spatially transforming the TEE image data to match this pose. An initial pose estimate was obtained through tomosynthesis‐based 3D localization of points along the probe perimeter. Position and angle estimates were then iteratively refined by comparing simulated projections of a 3D probe model against SBDX x‐ray images. Algorithm performance was quantified by imaging a TEE probe in different known orientations and locations within the x‐ray field (0‐30 degree tilt angle, up to 50 mm translation). Fused 3D TEE/SBDX imaging was demonstrated by imaging a tissue‐mimicking polyvinyl alcohol cylindrical cavity as a catheter was navigated along the cavity axis.Results:Detected changes in probe tilt angle agreed with the known changes to within 1.2 degrees. For a 50 mm translation along the source‐detector axis, the detected translation was 50.3 mm. Errors for in‐plane translations ranged from 0.1 to 0.9 mm. In a fused 3D TEE/SBDX display, the catheter device was well visualized and coincident with the device shadow in the TEE images. The TEE images portrayed phantom boundaries that were not evident under x‐ray.Conclusion:Registration of soft tissue anatomy derived from TEE imaging and device imaging from SBDX x‐ray fluoroscopy is feasible. The simultaneous 3D visualization of these two modalities may be useful in interventional procedures involving the navigation of devices to soft tissue anatomy.
TU‐F‐BRF‐08: Intensity Modulation Expanded to Spatio‐Temporal Space; IMRT Combined with Optimal Fractionation Schedule
Authors: Kim M , Saberian F , Ghate A 
Published: July 2014

Purpose:Past efforts to improve the therapeutic ratio have focused on a spatial approach where highly conformal radiation dose is given to tumors while minimizing dose to normal tissues, e.g., IMRT, VMAT, and IGRT. However, the fractionation schedule, i.e., a temporal approach to radiotherapy, has been largely overlooked so far in maximizing the therapeutic ratio. We establish a rigorous mathematical spatio‐temporal approach to systematically investigate the feasibility and potential benefits of simultaneously optimizing radiation dose distribution in space and time.Methods:Stochastic control formalism is constructed to maximize the average tumor BED by choosing an optimal radiation dose distribution for an optimal number of fractions subject to normal tissue BED constraints. Three separate simulations are run on two groups of phantom cases; 5 cases with prostate cancer and 5 cases with head‐and‐neck cancer. (1) Conventional IMRT with 70Gy/35fx for head‐and‐neck, and 81Gy/45fx for prostate, (2) IMRT is done independently from the fractionation schedule optimization (S‐model), (3) integrated spatio‐temporal approach (I‐model) where radiation intensities are simultaneously optimized for the first time ever in space and time. Final tumor BEDs from the three trials are compared in prostate and head‐and‐neck cases.Results:Numerical simulations show that final tumor BED from I‐model is 20–90% larger than conventional IMRT, and 20‐50% larger than S‐model for head‐and‐neck cancer with α/β=10 and Tdouble=2–50 days. Final tumor BED from I‐model is also 90–140% larger than conventional IMRT, and 20–30% larger than S‐model for prostate cancer with α/β=2 and Tdouble=5–80 days.Conclusion:Our spatio‐temporal optimization of radiotherapy allows an expansion of search space for the optimal treatment plans to include the temporal distribution of radiation dose in addition to the spatial distribution. Such spatio‐temporal approach shows great potential to improve the therapeutic ratio, particularly with fast growing, aggressive tumors with short doubling time and/or low α/β.
TU‐F‐17A‐08: The Relative Accuracy of 4D Dose Accumulation for Lung Radiotherapy Using Rigid Dose Projection Versus Dose Recalculation On Every Breathing Phase
Authors: Lamb J , Valdes G , Lee C , Tee S , Lee P , Robinson C , Iwamoto K , Low D 
Published: July 2014

Purpose:To investigate the accuracy of 4D dose accumulation using projection of dose calculated on the end‐exhalation, mid‐ventilation, or average intensity breathing phase CT scan, versus dose accumulation performed using full Monte Carlo dose recalculation on every breathing phase.Methods:Radiotherapy plans were analyzed for 10 patients with stage I‐II lung cancer planned using 4D‐CT. SBRT plans were optimized using the dose calculated by a commercially‐available Monte Carlo algorithm on the end‐exhalation 4D‐CT phase. 4D dose accumulations using deformable registration were performed with a commercially available tool that projected the planned dose onto every breathing phase without recalculation, as well as with a Monte Carlo recalculation of the dose on all breathing phases. The 3D planned dose (3D‐EX), the 3D dose calculated on the average intensity image (3D‐AVE), and the 4D accumulations of the dose calculated on the end‐exhalation phase CT (4D‐PR‐EX), the mid‐ventilation phase CT (4D‐PR‐MID), and the average intensity image (4D‐PR‐AVE), respectively, were compared against the accumulation of the Monte Carlo dose recalculated on every phase. Plan evaluation metrics relating to target volumes and critical structures relevant for lung SBRT were analyzed.Results:Plan evaluation metrics tabulated using 4D‐PR‐EX, 4D‐PR‐MID, and 4D‐PR‐AVE differed from those tabulated using Monte Carlo recalculation on every phase by an average of 0.14±0.70 Gy, – 0.11±0.51 Gy, and 0.00±0.62 Gy, respectively. Deviations of between 8 and 13 Gy were observed between the 4D‐MC calculations and both 3D methods for the proximal bronchial trees of 3 patients.Conclusions:4D dose accumulation using projection without re‐calculation may be sufficiently accurate compared to 4D dose accumulated from Monte Carlo recalculation on every phase, depending on institutional protocols. Use of 4D dose accumulation should be considered when evaluating normal tissue complication probabilities as well as in clinical situations where target volumes are directly inferior to mobile critical structures.
TU‐F‐17A‐09: Four‐Dimensional Cone Beam CT Ventilation Imaging Can Detect Interfraction Lung Function Variations for Locally Advanced Lung Cancer Patients
Authors: Kipritidis J , Hugo G , Weiss E , Williamson J , Keall P 
Published: July 2014

Purpose:Four‐dimensional cone beam CT ventilation imaging (4D‐CBCT VI) is a novel functional lung imaging modality requiring validation. We hypothesize that 4D‐CBCT VI satisfies a necessary condition for validity: that intrafraction variations (e.g. due to poor 4D‐CBCT image quality) are substantially different to interfraction variations (e.g. due to changes in underlying function). We perform the first comparison of intrafraction (pre/post fraction) and interfraction (week‐to‐week) 4D‐CBCT VIs for locally advanced non small cell lung cancer (LA NSCLC) patients undergoing radiation therapy.Methods:A total of 215 4D‐CBCT scans were acquired for 19 LA NSCLC patients over 4‐6 weeks of radiation therapy, including 75 pairs of pre‐/post‐fraction scans on the same day. 4D‐CBCT VIs were obtained by applying state‐of‐the‐art, B‐spline deformable image registration to obtain the Jacobian determinant of deformation between the end‐exhale and end‐inhale phases. All VIs were deformably registered to the corresponding first day scan, normalized between the 10th and 90th percentile values and cropped to the ipsilateral lung only. Intrafraction variations were assessed by computing the mean and standard deviation of voxel‐wise differences between all same‐day pairs of pre‐/post‐fraction VIs. Interfraction differences were computed between first‐day VIs and treatment weeks 2, 4 and 6 for all 19 patients. We tested the hypothesis by comparing cumulative distribution functions (CDFs) of intrafraction and interfraction ventilation differences using two‐sided Kolmogorov‐Smirnov goodness‐of‐fit tests.Results:The (mean ± std. dev.) of intrafraction differences was (−0.007 ± 0.079). Interfraction differences for weeks 2, 4 and 6 were (−0.035 ± 0.103), (−0.006 ± 0.094) and (−0.019 ± 0.127) respectively. For week 2, the changes in CDFs for intrafraction and interfraction differences approached statistical significance (p=0.099).Conclusion:We have shown that 4D‐CBCT VI can satisfy a necessary condition for validity; intrafraction variations do not limit the ability to measure interfraction variations in LA NSCLC patients.This work is supported by a Cancer Institute NSW Early Career Fellowship, an NHMRC Australia Fellowship and NIH P01CA116602.