bluuebunny/crossref_metadata_2025_split huggingface dataset:
MO‐F‐CAMPUS‐J‐04: Tissue Segmentation‐Based MR Electron Density Mapping Method for MR‐Only Radiation Treatment Planning of Brain
Authors: Yu H , Lee Y , Ruschin M , Karam I , Sahgal A 
Published: June 2015

Purpose:Automatically derive electron density of tissues using MR images and generate a pseudo‐CT for MR‐only treatment planning of brain tumours.Methods:20 stereotactic radiosurgery (SRS) patients’ T1‐weighted MR images and CT images were retrospectively acquired. First, a semi‐automated tissue segmentation algorithm was developed to differentiate tissues with similar MR intensities and large differences in electron densities. The method started with approximately 12 slices of manually contoured spatial regions containing sinuses and airways, then air, bone, brain, cerebrospinal fluid (CSF) and eyes were automatically segmented using edge detection and anatomical information including location, shape, tissue uniformity and relative intensity distribution. Next, soft tissues ‐ muscle and fat were segmented based on their relative intensity histogram. Finally, intensities of voxels in each segmented tissue were mapped into their electron density range to generate pseudo‐CT by linearly fitting their relative intensity histograms. Co‐registered CT was used as a ground truth. The bone segmentations of pseudo‐CT were compared with those of co‐registered CT obtained by using a 300HU threshold. The average distances between voxels on external edges of the skull of pseudo‐CT and CT in three axial, coronal and sagittal slices with the largest width of skull were calculated. The mean absolute electron density (in Hounsfield unit) difference of voxels in each segmented tissues was calculated.Results:The average of distances between voxels on external skull from pseudo‐CT and CT were 0.6±1.1mm (mean±1SD). The mean absolute electron density differences for bone, brain, CSF, muscle and fat are 78±114 HU, and 21±8 HU, 14±29 HU, 57±37 HU, and 31±63 HU, respectively.Conclusion:The semi‐automated MR electron density mapping technique was developed using T1‐weighted MR images. The generated pseudo‐CT is comparable to that of CT in terms of anatomical position of tissues and similarity of electron density assignment. This method can allow MR‐only treatment planning.
MO‐F‐CAMPUS‐I‐01: Accuracy of Radiologists Interpretation of Mammographic Breast Density
Authors: Vedantham S , Shi L , Karellas A , O'Connell A 
Published: June 2015

Purpose:Several commercial and non‐commercial software and techniques are available for determining breast density from mammograms. However, where mandated by law the breast density information communicated to the subject/patient is based on radiologist's interpretation of breast density from mammograms. Several studies have reported on the concordance among radiologists in interpreting mammographic breast density. In this work, we investigated the accuracy of radiologist's interpretation of breast density.Methods:Volumetric breast density (VBD) determined from 134 unilateral dedicated breast CT scans from 134 subjects was considered the truth. An MQSA‐qualified study radiologist with more than 20 years of breast imaging experience reviewed the DICOM “for presentation” standard 2‐view mammograms of the corresponding breasts and assigned BIRADS breast density categories. For statistical analysis, the breast density categories were dichotomized in two ways; fatty vs. dense breasts where “fatty” corresponds to BIRADS breast density categories A/B, and “dense” corresponds to BIRADS breast density categories C/D, and extremely dense vs. fatty to heterogeneously dense breasts, where extremely dense corresponds to BIRADS breast density category D and BIRADS breast density categories A through C were grouped as fatty to heterogeneously dense breasts. Logistic regression models (SAS 9.3) were used to determine the association between radiologist's interpretation of breast density and VBD from breast CT, from which the area under the ROC (AUC) was determined.Results:Both logistic regression models were statistically significant (Likelihood Ratio test, p<0.0001). The accuracy (AUC) of the study radiologist for classification of fatty vs. dense breasts was 88.4% (95% CI: 83–94%) and for classification of extremely dense breast was 94.3% (95% CI: 90–98%).Conclusion:The accuracy of the radiologist in classifying dense and extremely dense breasts is high. Considering the variability in VBD estimates from commercial software, the breast density information communicated to the patient should be based on radiologist's interpretation.This work was supported in part by NIH R21 CA176470 and R21 CA134128. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or NCI.
MO‐F‐CAMPUS‐I‐03: Tissue Equivalent Material Phantom to Test and Optimize Coherent Scatter Imaging for Tumor Classification
Authors: Albanese K , Morris R , Lakshmanan M , Greenberg J , Kapadia A 
Published: June 2015

Purpose:To accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x‐ray scatter imaging system.Methods:A breast phantom has been designed to assess the capability of coded aperture coherent x‐ray scatter imaging system to classify different types of breast tissue (adipose, fibroglandular, tumor). The tissue‐equivalent phantom was modeled as a hollow plastic cylinder containing multiple cylindrical and spherical inserts that can be positioned, rearranged, or removed to model different breast geometries. Each enclosure can be filled with a tissue‐equivalent material and excised human tumors. In this study, beef and lard, placed inside 2‐mm diameter plastic Nalgene containers, were used as surrogates for fibroglandular and adipose tissue, respectively. The phantom was imaged at 125 kVp, 40 mA for 10 seconds each with a 1‐mm pencil beam. The raw data were reconstructed using a model‐based reconstruction algorithm and yielded the location and form factor, or momentum transfer (q) spectrum of the materials that were imaged. The measured material form factors were then compared to the ground truth measurements acquired by x‐ray diffraction (XRD) imaging.Results:The tissue equivalent phantom was found to accurately model different types of breast tissue by qualitatively comparing our measured form factors to those of adipose and fibroglandular tissue from literature. Our imaging system has been able to define the location and composition of the various materials in the phantom.Conclusion:This work introduces a new tissue equivalent phantom for testing and optimization of our coherent scatter imaging system for material classification. In future studies, the phantom will enable the use of a variety of materials including excised human tissue specimens in evaluating and optimizing our imaging system using pencil‐ and fan‐beam geometries.United States Department of Homeland Security Duke University Medical Center ‐ Department of Radiology Carl E Ravin Advanced Imaging Laboratories Duke University Medical Physics Graduate Program
MO‐F‐CAMPUS‐I‐05: The Total Internal Reflection Based Elastography Method for Tissue Elasticity Quantification and Characterization
Authors: Lee J 
Published: June 2015

Purpose:Diagnosing early formation of tumors or lumps, particularly those caused by cancer, has been a problem. Our goal is to develop a simple and easy to use system that can document the properties of palpable lumps in soft tissue using noninvasive technique.Methods:The tactile sensor we propose comprises of an elastic optical waveguide unit, a high resolution CCD camera unit, a LED light source unit, and a laptop computer. The sensing element is formed on poly dimethylsiloxane (PDMS) and is illuminated along its four edges by LED light sources. The tactile sensor operates on the principle of total internal reflection (TIR) within an optical waveguide. The light directed into the waveguide remains within it due to the TIR generated, since the waveguide is surrounded by air having a lower refractive index than the waveguide. When an object adheres to the waveguide and compresses, the contact area of the waveguide deforms and causes the light to scatter.Results:To validate the proposed method, three patients presented with a lesion that was initially detected by another modality (mammography, ultrasound, or manual palpation). When performing the sensor scans, the doctor already knew where the lesions were located. For each lesion, 10 tactile images were obtained and the estimated parameters were averaged. Regarding the hardness estimation of the lesions, malignant breast lesion of the patient 1 had increased Young's modulus (146 kPa), compared to benign lesions (97 kPa and 103 kPa, patient 2 and 3). The elasticity information was correlated with the malignancy data from the pathology reports. The minimum and maximum relative errors are 1.1% and 11.72%. The mean error is 5.07% with 3.39% standard deviation.Conclusion:In this paper, a tactile elasticity imaging sensor using the total internal reflection principle is designed and experimentally evaluated.
MO‐F‐CAMPUS‐T‐03: Continuous Dose Delivery with Gamma Knife Perfexion
Authors: Ghobadi  , Aleman D , Li W , Chung C , Jaffray D 
Published: June 2015

Purpose:We propose continuous dose delivery techniques for stereotactic treatments delivered by Gamma Knife Perfexion using inverse treatment planning system that can be applied to various tumour sites in the brain. We test the accuracy of the plans on Perfexion's planning system (GammaPlan) to ensure the obtained plans are viable. This approach introduces continuous dose delivery for Perefxion, as opposed to the currently employed step‐and‐shoot approaches, for different tumour sites. Additionally, this is the first realization of automated inverse planning on GammaPlan.Methods:The inverse planning approach is divided into two steps of identifying a quality path inside the target, and finding the best collimator composition for the path. To find a path, we select strategic regions inside the target volume and find a path that visits each region exactly once. This path is then passed to a mathematical model which finds the best combination of collimators and their durations. The mathematical model minimizes the dose spillage to the surrounding tissues while ensuring the prescribed dose is delivered to the target(s). Organs‐at‐risk and their corresponding allowable doses can also be added to the model to protect adjacent organs.Results:We test this approach on various tumour sizes and sites. The quality of the obtained treatment plans are comparable or better than forward plans and inverse plans that use step‐ and‐shoot technique. The conformity indices in the obtained continuous dose delivery plans are similar to those of forward plans while the beam‐on time is improved on average (see Table 1 in supporting document).Conclusion:We employ inverse planning for continuous dose delivery in Perfexion for brain tumours. The quality of the obtained plans is similar to forward and inverse plans that use conventional step‐and‐shoot technique. We tested the inverse plans on GammaPlan to verify clinical relevance.This research was partially supported by Elekta, Sweden (vendor of Gamma Knife Perfexion).
MO‐F‐CAMPUS‐T‐04: Development and Evaluation of a Knowledge‐Based Model for Treatment Planning of Lung Cancer Patients Using Stereotactic Body Radiotherapy (SBRT)
Authors: Snyder K , Kim J , Reding A , Fraser C , Lu S , Gordon J , Ajlouni M , Movsas B , Chetty I 
Published: June 2015

Purpose:To describe the development of a knowledge‐based treatment planning model for lung cancer patients treated with SBRT, and to evaluate the model performance and applicability to different planning techniques and tumor locations.Methods:105 lung SBRT plans previously treated at our institution were included in the development of the model using Varian's RapidPlan DVH estimation algorithm. The model was trained with a combination of IMRT, VMAT, and 3D–CRT techniques. Tumor locations encompassed lesions located centrally vs peripherally (43:62), upper vs lower (62:43), and anterior vs posterior lobes (60:45). The model performance was validated with 25 cases independent of the training set, for both IMRT and VMAT. Model generated plans were created with only one optimization and no planner intervention. The original, general model was also divided into four separate models according to tumor location. The model was also applied using different beam templates to further improve workflow. Dose differences to targets and organs‐at‐risk were evaluated.Results:IMRT and VMAT RapidPlan generated plans were comparable to clinical plans with respect to target coverage and several OARs. Spinal cord dose was lowered in the model‐based plans by 1Gy compared to the clinical plans, p=0.008. Splitting the model according to tumor location resulted in insignificant differences in DVH estimation. The peripheral model decreased esophagus dose to the central lesions by 0.5Gy compared to the original model, p=0.025, and the posterior model increased dose to the spinal cord by 1Gy compared to the anterior model, p=0.001. All template beam plans met OAR criteria, with 1Gy increases noted in maximum heart dose for the 9‐field plans, p=0.04.Conclusion:A RapidPlan knowledge‐based model for lung SBRT produces comparable results to clinical plans, with increased consistency and greater efficiency. The model encompasses both IMRT and VMAT techniques, differing tumor locations, and beam arrangements.Research supported in part by a grant from Varian Medical Systems, Palo Alto CA.
MO‐F‐CAMPUS‐J‐01: A Novel and Efficient Daily QA Program for Both Modern Linear Accelerator and Optical Surface Motion Systems
Authors: Peng J , McDonald D , Ashenafi M , Koch N , Fugal M , Vanek K 
Published: June 2015

Purpose:The camera‐based optical surface monitoring system(OSMS) is a standard motion‐tracking system for TrueBeam™ machine. Daily quality assurance(DQA) procedures for the TrueBeam and OSMS systems currently require multiple phantoms and test sequences. Machine Performance Check(MPC) uses the IsoCal™ phantom to test geometric and dosimetric aspects, and has been validated for routine TrueBeam DQA. This work examines the novel use of MPC to simultaneously conduct DQA of OSMS,utilizing one phantom and test sequence for QA of both the TrueBeam and OSMS systems.Methods:TrueBeam with 6 degree‐of‐freedom(6DOF) couch, MPC and OSMS were installed. The therapists routinely use MPC with the IsoCal phantom to verify geometric and dosimetric parameters with an automated sequence of varying gantry and collimator angles, MLC positions, and couch translations and rotations as the DQA for TrueBeam. A surface outline of the IsoCal phantom, generated from a CT dataset, was imported to OSMS and used to monitor the position of the phantom at isocenter and to track its movement up to 5cm/10°(yaw) and rotation in pitch and roll up to 3° in real time during the automated MPC sequence. Motion of the phantom throughout the MPC routine was compared to the couch position shown by the digital readout.Results:The coincidence of isocenter, as determined by OSMS, and TrueBeam radiation isocenter was within ±0.8mm/±0.8° in three axes. Between OSMS and TrueBeam 6DOF couch, the mean couch relative shifts/angles were within ±0.7mm/±0.8° for each axis. Reported pitch and roll values were within ±0.4mm/±0.4°. The total measurement time for each DQA session took approximately 5 minutes.Conclusion:Use of the IsoCal phantom and MPC for simultaneous DQA of TrueBeam and OSMS increases QA efficiency and reduces complexity. OSMS isocenter position and motion‐tracking capability in 6DOF were verified in real‐time and were found to be within 1mm of the expected value.
MO‐F‐CAMPUS‐J‐03: Evaluation and Use of Cubic Phantoms for Daily IGRT QA Process with TrueBeam 6DoF Couch
Authors: Ito S , de los Santos L Fong , Cutsinger S McCauley 
Published: June 2015

Purpose:To improve efficiency and efficacy of Daily IGRT QA process and to prepare for Varian TrueBeam 6DoF couch implementationMethods:MIMI phantom from Standard Imaging was compared to PentaGuide phantom from Modus Medical in order to replace and update our daily IGRT QA process. The following metrics were used as our evaluation criteria: contrast structures, predefined shift mark, TG‐142 compliance, support for 6DoF and ease of use. To improve process compliance, daily IGRT QA set up and process, an acrylic in‐house baseplates with known offsets were designed. New Daily IGRT QA protocol for 3DoF and 6DoF systems was developed and implemented into our practice. The selected phantom was used for the commissioning of Varian TrueBeam 6DoF couches and test the reproducibility and accuracy of 2D/2D and 3D/3D matching and localization processes. Baseline and tolerances for Daily IGRT QA for 6DoF couch were determined.Results:Based on our evaluation criteria, the MIMI phantom fit best our QA processes and matching goals. Comprehensive daily IGRT QA which includes CBCT 3D automatic registration, couch positioning, coincidence of kV/MV isocenters, image quality, and laser alignment were accurately and efficiently validated using the MIMI phantom and the setup baseplate with Varian TrueBeam and EX systems with 3DoF and 6DoF couches. Also, the use of MIMI phantom and setup baseplate was found to be a useful and effective tool for the commissioning of the Varian TrueBeam 6DoF couches.Conclusion:Implementation of MIMI phantom improved our Daily IGRT QA process by eliminating the use multiple phantoms which resulted in 40% Daily IGRT QA time reduction. Feedback from therapists has been positive and 100% compliance to new protocol has been achieved with minimal training. MIMI phantom was used to test the stability of the couch and to set baseline for Daily QA target and tolerance values.
MO‐F‐CAMPUS‐I‐01: EIT Imaging to Monitor Human Salivary Gland Functionality: A Feasibility Study
Authors: Kohli K , Karvat A , Liu J , Krishnan K 
Published: June 2015

Purpose:Clinically, there exists a need to develop a non‐invasive technique for monitoring salivary activity. In this study, we investigate the feasibility of a using the electrical conductivity information from Electrical Impedance Tomography (EIT) to monitor salivary flow activity.Methods:To acquire EIT data, eight Ag/AgCl ECG electrodes were placed around the mandible of the subject. An EIT scan was obtained by injecting current at 50 KHz, 0.4 mA through each pair of electrodes and recording voltage across other electrode pairs. The functional conductivity image was obtained through reconstruction of the voltage data, using Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS) in Matlab. In using EIDORS, forward solution was obtained using a user‐defined finite element model shape and inverse solution was obtained using one‐step Gaussian solver. EIT scans of volunteer research team members were acquired for three different physiological states: pre‐stimulation, stimulation and post‐stimulation. For pre‐stimulation phase, data were collected in intervals of 5 minutes for 15 minutes. The salivary glands were then stimulated in the subject using lemon and the data were collected immediately. Post‐stimulation data were collected at 4 different timings after stimulation.Results:Variations were observed in the electrical conductivity patterns near parotid regions between the pre‐ and post‐stimulation stages. The three images acquired during the 15 minute pre‐stimulation phase showed no major changes in the conductivity. Immediately after stimulation, electrical conductivity increased near parotid regions and 15 minutes later slowly returned to pre‐stimulation level.Conclusion:In the present study involving human subjects, the change in electrical conductivity pattern shown in the EIT images, acquired at different times with and without stimulation of salivary glands, appeared to be consistent with the change in salivary gland activity. The conductivity changes imaged through EIT are potentially useful for the purpose of salivary monitoring.
MO‐F‐CAMPUS‐I‐02: Stability Investigation of a Gamma Fitting Algorithm for Angiographic Parametric Imaging at Low X‐Ray Exposures Using a Patient Specific Neurovascular Phantom
Authors: Balasubramoniam A , Bednarek D , Rudin S , Ionita C 
Published: June 2015

Purpose:To analyze the stability of a Gamma fitting algorithm based on digital subtraction angiography sequences, at different exposure, hence noise levels.Methods:Starting with a patient CT volume, we built a 3D printed neurovascular phantom which contained a complete Circle of Willis with major arteries and five aneurysms. We placed the phantom in a 15 cm water bath and connected it to a flow loop containing a peristaltic pump which simulated physiological relevant flow conditions. We injected 10 ml contrast boluses using an automatic contrast injector at a rate of 10 ml/sec. Digital Subtraction Angiography images were acquired at 30 frames/sec and processed with a gamma fitting based algorithm, to yield parametric maps of: Mean transit time (MTT), Time‐to‐Peak (TTP), Bolus Arrival Time (BAT). Starting with the optimal exposure parameters selected by the x‐ray system automatic exposure control, while keeping the same kV, we lowered the mA and exposure per frame in four steps until we reached the minimum value allowed by the system. We analyzed the variation of the MTT, TTP and BAT for various artery signal to noise ratios using four ROIs.Results:The peak (maximum opacification) SNRs for full dose and minimum dose were: 35 and 13 for 4 mm arteries and 18 and 7 for 2 mm arteries. The parameters standard deviation expressed as a percent fraction of the value measured at the full dose value, were: MTT=2.4%, BAT=0.5% and TTP=1.9% for 4 mm vessels and MTT=3.7%, BAT=5.4% and TTP=6.3% for 2 mm vessels.Conclusion:Despite a significant decrease of the peak SNR the algorithm performed very well displaying variations less than 6.3% of the ideal conditions. Partial Support: NIH grant R01EB002873 and Toshiba Medical Systems Corp.Partial Support: NIH grant R01EB002873 and Toshiba Medical Systems Corp.