bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐G‐12A‐01: Quantitative Imaging Metrology: What Should Be Assessed and How?
Authors: Giger M , Petrick N , Obuchowski N , Kinahan P 
Published: July 2014

The first two symposia in the Quantitative Imaging Track focused on 1) the introduction of quantitative imaging (QI) challenges and opportunities, and QI efforts of agencies and organizations such as the RSNA, NCI, FDA, and NIST, and 2) the techniques, applications, and challenges of QI, with specific examples from CT, PET/CT, and MR. This third symposium in the QI Track will focus on metrology and its importance in successfully advancing the QI field. While the specific focus will be on QI, many of the concepts presented are more broadly applicable to many areas of medical physics research and applications. As such, the topics discussed should be of interest to medical physicists involved in imaging as well as therapy. The first talk of the session will focus on the introduction to metrology and why it is critically important in QI. The second talk will focus on appropriate methods for technical performance assessment. The third talk will address statistically valid methods for algorithm comparison, a common problem not only in QI but also in other areas of medical physics. The final talk in the session will address strategies for publication of results that will allow statistically valid meta‐analyses, which is critical for combining results of individual studies with typically small sample sizes in a manner that can best inform decisions and advance the field.Learning Objectives:

Understand the importance of metrology in the QI efforts.
Understand appropriate methods for technical performance assessment.
Understand methods for comparing algorithms with or without reference data (i.e., “ground truth”).
Understand the challenges and importance of reporting results in a manner that allows for statistically valid meta‐analyses.
MO‐H‐19A‐01: FEATURED PRESENTATION – Treatment Planning Tool for Radiotherapy with Very High‐Energy Electron Beams
Authors: Bazalova M , Qu B , Hynning E , Hardemark B , Palma B , Loo B , Maxim P 
Published: July 2014

Purpose:To develop a tool for treatment planning optimization for fast radiotherapy delivered with very high‐energy electron beams (VHEE) and to compare VHEE plans to state‐of‐the‐art plans for challenging pelvis and H' N cases.Methods:Treatment planning for radiotherapy delivered with VHEE scanning pencil beams was performed by integrating EGSnrc Monte Carlo (MC) dose calculations with spot scanning optimization run in a research version of RayStation. A Matlab GUI for MC beamlet generation was developed, in which treatment parameters such as the pencil beam size and spacing, energy and number of beams can be selected. Treatment planning study for H' N and pelvis cases was performed and the effect of treatment parameters on the delivered dose distributions was evaluated and compared to the clinical treatment plans. The pelvis case with a 691cm3 PTV was treated with 2‐arc 15MV VMAT and the H' N case with four PTVs with total volume of 531cm3 was treated with 4‐arc 6MV VMAT.Results:Most studied VHEE plans outperformed VMAT plans. The best pelvis 80MeV VHEE plan with 25 beams resulted in 12% body dose sparing and 8% sparing to the bowel and right femur compared to the VMAT plan. The 100MeV plan was superior to the 150MeV plan. Mixing 100 and 150MeV improved dose sparing to the bladder by 7% compared to either plan. Plans with 16 and 36 beams did not significantly affect the dose distributions compared to 25 beam plans. The best H' N 100MeV VHEE plan decreased mean doses to the brainstem, chiasm, and both globes by 10‐42% compared to the VMAT plan.Conclusion:The pelvis and H' N cases suggested that sixteen 100MeV beams might be sufficient specifications of a novel VHEE treatment machine. However, optimum machine parameters will be determined with the presented VHEE treatment‐planning tool for a large number of clinical cases.BW Loo and P Maxim received research support from RaySearch Laboratories. E Hynning and B Hardemark are employees of RaySearch Laboratories.
MO‐H‐19A‐02: Investigation of Modulated Electron Arc (MeArc) Therapy for the Treatment of Scalp Tumors
Authors: Eldib A , Jin L , Martin J , Li J , Chibani O , Galloway T , Ma C 
Published: July 2014

Purpose:Electron arc therapy has long been proposed as the most suitable technique for the treatment of superficial tumors that follow circularly curved surfaces. However it was challenged by unsuitability of the conventional applicators and the lack of adequate 3‐D dose calculation tools for arc electron beams in the treatment planning systems (TPS). Now with the availability of an electron specific multi‐leaf collimator (eMLC) and an in‐house Monte Carlo (MC) based TPS, we were motivated to investigate more advanced modulated electron arc (MeARC) therapy and its beneficial outcome.Methods:We initiated the study by a film measurement conducted in a head and neck phantom, where we delivered electron arcs in a step and shoot manner using the light field as a guide to avoid fields abutments. This step was done to insure enough clearance for the arcs with eMLC. MCBEAM and MCPLAN MC codes were used for the treatment head simulation and phantom dose calculation, respectively. Treatment plans were generated for targets drawn in real patient CTs and head and neck phantom. We utilized beams eye view available from a commercial planning system to create beamlets having same isocenter and adjoined at the scalp surface. Then dose‐deposition coefficients from those beamlets were calculated for all electron energies using MCPLAN. An in‐house optimization code was then used to find the optimum weights needed from individual beamlets.Results:MeARC showed a nicely tailored dose distribution around the circular curved target on the scalp. Some hot spots were noticed and could be attributed to fields abutment problem owing to the bulging nature of electron profiles. Brain dose was shown to be at lower levels compared to photon treatment.Conclusion:MeARC was shown to be a promising modality for treating scalp cases and could be beneficial to all superficial tumors with a circular curvature.
TU‐A‐9A‐03: Development and Verification of a Forward Model That Assists in Iterative Post‐Processing Algorithms Used to Reduce Blur in Compton Backscatter Imaging Systems
Authors: Juneja B , Gilland D , Hintenlang D , Doxsee K , Bova F 
Published: July 2014

Purpose:In Compton Backscatter Imaging (CBI), the source and detector reside on the same side of the patient. We previously demonstrated the applicability of CBI systems for medical purposes using an industrial system. To assist in post‐processing images from a CBI system, a forward model based on radiation absorption and scatter principles has been developed.Methods:The forward model was developed in C++ using raytracing to track particles. The algorithm accepts phantoms of any size and resolution to calculate the fraction of incident photons scattered back to the detector, and can perform these calculations for any detector geometry and source specification. To validate the model, results were compared to MCNP‐X, which is a Monte Carlo based simulation software, for various combinations of source specifications, detector geometries, and phantom compositions.Results:The model verified that the backscatter signal to the detector was based on three interaction probabilities: a) attenuation of photons going into the phantom, b) Compton scatter of photons toward the detector, and c) attenuation of photons coming out of the phantom. The results from the MCNP‐X simulations and the forward model varied from 1 to 5%. This difference was less than 1% for energies higher than 30 keV, but was up to 4% for lower energies. At 50 keV, the difference was less than 1% for multiple detector widths and for both homogeneous and heterogeneous phantoms.Conclusion:As part of the optimization of a medical CBI system, an efficient and accurate forward model was constructed in C++ to estimate the output of CBI system. The model characterized individual components contributing to CBI output and increased computational efficiency over Monte Carlo simulations. It is now used in the development of novel post‐processing algorithms that reduce image blur by reversing undesired contribution from outside the region of interest.
TU‐A‐9A‐05: First Experimental Demonstration of the Anisotropic Detection Principle in X‐Ray Fluorescence Computed Tomography
Authors: Ahmad M , Bazalova M , Fahrig R , Xing L 
Published: July 2014

Purpose:To improve the sensitivity of X‐ray fluorescence computed tomography (XFCT) for in vivo molecular imaging. Is the maximum sensitivity achieved with an isotropic (4π) detector configuration? We prove that this is not necessarily true, and that a greater sensitivity is possible with anisotropic detector configuration.Methods:An XFCT imaging system was constructed consisting of 1) a collimated pencil beam x‐ray source using a fluoroscopy grade x‐ray tube; 2) a CdTe x‐ray photon counting detector to detect fluorescent x‐rays; and 3) a rotation/translation stage for tomographic imaging. We created a 6.5‐cm diameter water phantom with 2‐cm inserts of low gold concentration (0.25%–1%) to simulate tumors targeted by gold nano‐particles. The placement of x‐ray fluorescence detector were chosen to minimize scatter x‐rays. XFCT imaging was performed at three different detector positions (60°, 90°, 145°) to determine the impact of forward‐scatter, side‐scatter, and back‐scatter on imaging performance. The three data sets were also combined to estimate the imaging performance with an isotropic detector.Results:The highest imaging performance was achieved when the XF detector was in the backscatter 145° configuration. The signal‐to‐noise ratio (SNR) was 5.5 for the 0.25% gold concentration compared to SNRs of 1.4, 0, and 2.4 for 60°, 90°, and combined (60°+90°+145°) datasets. Only the 145° detector arrangement alone could detect the 0.25% concentration. The imaging dose was 14 mGy for each detector arrangement experiment.Conclusion:This study experimentally proves, for the fist time, the Anisotropic Detection Principle in XF imaging, which holds that optimized anisotropic x‐ray fluorescence detection provides greater sensitivity than isotropic detection. The optimized detection arrangement was used to improve the sensitivity of the XFCT experiment. The achieved XFCT sensitivity is the highest ever for a phantom at least this large using a benchtop x‐ray source, which is an important step toward clinical XFCT molecular imaging.This work was supported by the NCI fellowship grant R25T‐CA118681 and by the NIH (1R01‐EB016777) and NIBIB (1K99‐EB016059).
TU‐A‐9A‐09: Proton Beam X‐Ray Fluorescence CT
Authors: Bazalova M , Ahmad M , Fahrig R , Xing L 
Published: July 2014

Purpose:To evaluate x‐ray fluorescence computed tomography induced with proton beams (pXFCT) for imaging of gold contrast agent.Methods:Proton‐induced x‐ray fluorescence was studied by means of Monte Carlo (MC) simulations using TOPAS, a MC code based on GEANT4. First, proton‐induced K‐shell and L‐shell fluorescence was studied as a function of proton beam energy and 1) depth in water and 2) size of contrast object. Second, pXFCT images of a 2‐cm diameter cylindrical phantom with four 5‐ mm diameter contrast vials and of a 20‐cm diameter phantom with 1‐cm diameter vials were simulated. Contrast vials were filled with water and water solutions with 1‐5% gold per weight. Proton beam energies were varied from 70‐250MeV. pXFCT sinograms were generated based on the net number of gold K‐shell or L‐shell x‐rays determined by interpolations from the neighboring 0.5keV energy bins of spectra collected with an idealized 4π detector. pXFCT images were reconstructed with filtered‐back projection, and no attenuation correction was applied.Results:Proton induced x‐ray fluorescence spectra showed very low background compared to x‐ray induced fluorescence. Proton induced L‐shell fluorescence had a higher cross‐section compared to K‐shell fluorescence. Excitation of L‐shell fluorescence was most efficient for low‐energy protons, i.e. at the Bragg peak. K‐shell fluorescence increased with increasing proton beam energy and object size. The 2% and 5% gold contrast vials were accurately reconstructed in K‐shell pXFCT images of both the 2‐cm and 20‐cm diameter phantoms. Small phantom L‐shell pXFCT image required attenuation correction and had a higher sensitivity for 70MeV protons compared to 250MeV protons. With attenuation correction, L‐shell pXFCT might be a feasible option for imaging of small size (∼2cm) objects. Imaging doses for all simulations were 5‐30cGy.Conclusion:Proton induced x‐ray fluorescence CT promises to be an alternative quantitative imaging technique to the commonly considered XFCT imaging with x‐ray beams.
TU‐A‐12A‐02: Novel Lung Ventilation Imaging with Single Energy CT After Single Inhalation of Xenon: Comparison with SPECT Ventilation Images
Authors: Negahdar M , Yamamoto T , Shultz D , Gable L , Shan X , Mittra E , Diehn M , Loo B , Maxim P 
Published: July 2014

Purpose:We propose a novel lung functional imaging method to determine the spatial distribution of xenon (Xe) gas in a single inhalation as a measure of regional ventilation. We compare Xe‐CT ventilation to single‐photon emission CT (SPECT) ventilation, which is the current clinical reference. Regional lung ventilation information may be useful for the diagnosis and monitoring of pulmonary diseases such as COPD, radiotherapy planning, and assessing the progression of toxicity after radiation therapy.Methods:In an IRB‐approved clinical study, Xe‐CT and SPECT ventilation scans were acquired for three patients including one patient with severe emphysema and two lung cancer patients treated with radiotherapy. For Xe‐ CT, we acquired two breath‐hold single energy CT images of the entire lung with inspiration of 100% O2 and a mixture of 70% Xe and 30% O2, respectively. A video biofeedback system was used to achieve reproducible breath‐holds. We used deformable image registration to align the breathhold images with each other to accurately subtract them, producing a map of the distribution of Xe as a surrogate of lung ventilation. We divided each lung into twelve parts and correlated the Hounsfield unit (HU) enhancement at each part with the SPECT ventilation count of the corresponding part of the lung.Results:The mean of the Pearson linear correlation coefficient values between the Xe‐CT and ventilation SPECT count for all three patients were 0.62 (p<0.01). The Xe‐CT image had a higher resolution than SPECT, and did not show central airway deposition artifacts that were present in the SPECT image.Conclusion:We developed a rapid, safe, clinically practical, and potentially widely accessible method for regional lung functional imaging. We demonstrated strong correlations between the Xe‐CT ventilation image and SPECT ventilation image as the clinical reference. This ongoing study will investigate more patients to confirm this finding.
TU‐A‐12A‐04: Quantitative Texture Features Calculated in Lung Tissue From CT Scans Demonstrate Consistency Between Two Databases From Different Institutions
Authors: Cunliffe A , Armato S , Castillo R , Pham N , Guerrero T , Al‐Hallaq H 
Published: July 2014

Purpose:To evaluate the consistency of computed tomography (CT) scan texture features, previously identified as stable in a healthy patient cohort, in esophageal cancer patient CT scans.Methods:116 patients receiving radiation therapy (median dose: 50.4Gy) for esophageal cancer were retrospectively identified. For each patient, diagnostic‐quality pre‐therapy (0‐183 days) and post‐therapy (5‐120 days) scans (mean voxel size: 0.8mm×0.8mm×2.5mm) and a treatment planning scan and associated dose map were collected. An average of 501 32×32‐pixel ROIs were placed randomly in the lungs of each pre‐therapy scan. ROI centers were mapped to corresponding locations in post‐therapy and planning scans using the displacement vector field output by demons deformable registration. Only ROIs with mean dose <5Gy were analyzed, as these were expected to contain minimal post‐treatment damage. 140 texture features were calculated in pre‐therapy and post‐therapy scan ROIs and compared using Bland‐Altman analysis. For each feature, the mean feature value change and the distance spanned by the 95% limits of agreement were normalized to the mean feature value, yielding normalized range of agreement (nRoA) and normalized bias (nBias). Using Wilcoxon signed rank tests, nRoA and nBias were compared with values computed previously in 27 healthy patient scans (mean voxel size: 0.67mm×0.67mm×1mm) acquired at a different institution.Results:nRoA was significantly (p<0.001) larger in cancer patients than healthy patients. Differences in nBias were not significant (p=0.23). The 20 features identified previously as having nRoA<20% for healthy patients had the lowest nRoA values in the current database, with an average increase of 5.6%.Conclusion:Despite differences in CT scanner type, scan resolution, and patient health status, the same 20 features remained stable (i.e., low variability and bias) in the absence of disease changes for databases from two institutions. Identification of these features is the first step towards quantifying radiation‐induced changes between preand post‐therapy scans.Supported, in part, by NIH Grant Nos. S10 RR021039, and P30 CA14599, the Virginia and D. K. Ludwig Fund for Cancer Research, Imaging Research Institute, Biological Sciences Division, The University of Chicago, and The Institute for Translational Medicine Pilot Award, The University of Chicago.
TU‐A‐12A‐08: Computing Longitudinal Material Changes in Bone Metastases Using Dual Energy Computed Tomography
Authors: Schmidtlein CR , Hwang S , Veeraraghavan H , Fehr D , Humm J , Deasy J 
Published: July 2014

Purpose:This study demonstrates a methodology for tracking changes in metastatic bone disease using trajectories in material basis space in serial dual energy computed tomography (DECT) studies.Methods:This study includes patients with bone metastases from breast cancer that had clinical surveillance CT scans using a General Electric CT750HD in dual energy mode. A radiologist defined regions‐of‐interested (ROI) for bone metastasis, normal bone, and marrow across the serial DECT scans. Our approach employs a Radon transform to forward‐projection the basis images, namely, water and iodine, into sinogram space. This data is then repartitioned into fat/bone and effective density/Z image pairs using assumed energy spectrums for the x‐ray energies. This approach both helps remove negative material densities and avoids adding spectrum‐hardening artifacts. These new basis data sets were then reconstructed via filtered back‐projection to create new material basis pair images. The trajectories of these pairs were then plotted in the new basis space providing a means to both visualize and quantitatively measure changes in the material properties of the tumors.Results:ROI containing radiologist defined metastatic bone disease showed well‐defined trajectories in both fat/bone and effective density/Z space. ROI that contained radiologist defined normal bone and marrow did not exhibit any discernible trajectories and were stable from scan to scan.Conclusions:The preliminary results show that changes in material composition and effective density/Z image pairs were seen primarily in metastasis and not in normal tissue. This study indicates that by using routine clinical DECT it may be possible to monitor therapy response of bone metastases because healing or worsening bone metastases change material composition of bone. Additional studies are needed to further validate these results and to test for their correlation with outcome.
TU‐A‐12A‐10: Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation
Authors: Rios E , Parmar C , Jermoumi M , Aerts H 
Published: July 2014

Purpose:Recent advances in medical imaging technologies provide opportunities to quantify the tumor phenotype throughout the course of treatment non‐invasively. The emerging field of Radiomics addresses this by converting medical images into minable data by applying a large number of quantitative imaging algorithms. Accurate tumor segmentation is one of the main challenges of Radiomics. It has been shown that semiautomatic segmentation approaches efficiently reduce inter‐observer variability as compared to the time consuming manual delineations. In this study, a semiautomatic volumetric segmentation algorithm, implemented in the free and publicly available 3D‐Slicer platform, was investigated in terms of its robustness for Radiomics features quantification.Methods:Fifty‐six 3D‐Radiomics features, quantifying phenotypic differences based on the tumor intensity, shape and texture, were extracted from the computed tomography images of twenty lung cancer patients. These Radiomics features were derived from the 3D‐tumor volumes defined by three independent observers twice using 3D‐Slicer, and compared to manual slice‐by‐slice delineations of five independent physicians in terms of intra‐class correlation coefficient (ICC) and feature range.Results:Radiomics features extracted from 3D‐Slicer segmentations had significantly higher reproducibility (ICC= 0.85 0.15, p=0.0009) compared to the features extracted from the manual segmentations (ICC= 0.77 0.17). Furthermore, the features extracted from 3D‐Slicer based segmentations, spread over significantly smaller range across observers as compared to those of the manual delineations (p= 3.819e‐07). Moreover, the features derived from 3D‐Slicer segmentations overlapped in range with those of the manual delineations, as the lower(higher) limit(s) being significantly higher(lower) for the 3D‐Slicer features (p= 0.007, p= 5.863e‐06).Conclusion:3D‐Slicer based semiautomatic segmentation significantly improves the robustness of radiomics features and thus could serve as a potential alternative to the time consuming manual segmentation process. So 3D‐Slicer can have a large application in Radiomics, and be employed for high‐throughput data mining research of medical imaging in clinical oncology.