bluuebunny/crossref_metadata_2025 huggingface dataset:
TU‐CD‐BRB‐08: Radiomic Analysis of FDG‐PET Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated with SBRT
Authors: Cui Y , Song J , Pollom E , Shirato H , Chang D , Koong A , Li R
Published: June 2015

Purpose:

This study aims to identify novel prognostic imaging biomarkers in locally advanced pancreatic cancer (LAPC) using quantitative, high‐throughput image analysis.

Methods:

86 patients with LAPC receiving chemotherapy followed by SBRT were retrospectively studied. All patients had a baseline FDG‐PET scan prior to SBRT. For each patient, we extracted 435 PET imaging features of five types: statistical, morphological, textural, histogram, and wavelet. These features went through redundancy checks, robustness analysis, as well as a prescreening process based on their concordance indices with respect to the relevant outcomes. We then performed principle component analysis on the remaining features (number ranged from 10 to 16), and fitted a Cox proportional hazard regression model using the first 3 principle components. Kaplan‐Meier analysis was used to assess the ability to distinguish high versus low‐risk patients separated by median predicted survival. To avoid overfitting, all evaluations were based on leave‐one‐out cross validation (LOOCV), in which each holdout patient was assigned to a risk group according to the model obtained from a separate training set.

Results:

For predicting overall survival (OS), the most dominant imaging features were wavelet coefficients. There was a statistically significant difference in OS between patients with predicted high and low‐risk based on LOOCV (hazard ratio: 2.26, p<0.001). Similar imaging features were also strongly associated with local progression‐free survival (LPFS) (hazard ratio: 1.53, p=0.026) on LOOCV. In comparison, neither SUVmax nor TLG was associated with LPFS (p=0.103, p=0.433) (Table 1). Results for progression‐free survival and distant progression‐free survival showed similar trends.

Conclusion:

Radiomic analysis identified novel imaging features that showed improved prognostic value over conventional methods. These features characterize the degree of intra‐tumor heterogeneity reflected on FDG‐PET images, and their biological underpinnings warrant further investigation. If validated in large, prospective cohorts, this method could be used to stratify patients based on individualized risk.
TU‐CD‐BRA‐04: Evaluation of An Atlas‐Based Segmentation Method for Prostate and Peripheral Zone Regions On MRI
Authors: Nelson AS , Piper J , Curry K , Swallen A , Padgett K , Pollack A , Stoyanova RS
Published: June 2015

Purpose:

Prostate MRI plays an important role in diagnosis, biopsy guidance, and therapy planning for prostate cancer. Prostate MRI contours can be used to aid in image fusion for ultrasound biopsy guidance and delivery of radiation. Our goal in this study is to evaluate an automatic atlas‐based segmentation method for generating prostate and peripheral zone (PZ) contours on MRI.

Methods:

T2‐weighted MRIs were acquired on 3T‐Discovery MR750 System (GE, Milwaukee). The Volumes of Interest (VOIs): prostate and PZ were outlined by an expert radiation oncologist and used to create an atlas library for atlas‐based segmentation. The atlas‐segmentation accuracy was evaluated using a leave‐one‐out analysis. The method involved automatically finding the atlas subject that best matched the test subject followed by a normalized intensity‐based free‐form deformable registration of the atlas subject to the test subject. The prostate and PZ contours were transformed to the test subject using the same deformation. For each test subject the three best matches were used and the final contour was combined using Majority Vote. The atlas‐segmentation process was fully automatic. Dice similarity coefficients (DSC) and mean Hausdorff values were used for comparison.

Results:

VOIs contours were available for 28 subjects. For the prostate, the atlas‐based segmentation method resulted in an average DSC of 0.88+/−0.08 and a mean Hausdorff distance of 1.1+/−0.9mm. The number of patients (#) in DSC ranges are as follows: 0.60–0.69(1), 0.70–0.79(2), 0.80–0.89(13), >0.89(11). For the PZ, the average DSC was 0.72+/−0.17 and average Hausdorff of 0.9+/−0.9mm. The number of patients (#) in DSC ranges are as follows: <0.60(4), 0.60–0.69(6), 0.70–0.79(7), 0.80–0.89(9), >0.89(1).

Conclusion:

The MRI atlas‐based segmentation method achieved good results for both the whole prostate and PZ compared to expert defined VOIs. The technique is fast, fully automatic, and has the potential to provide significant time savings for prostate VOI definition.

AS Nelson and J Piper are partial owners of MIM Software, Inc. AS Nelson, J Piper, K Curry, and A Swallen are current employees at MIM Software, Inc.
TU‐CD‐BRA‐05: Atlas Selection for Multi‐Atlas‐Based Image Segmentation Using Surrogate Modeling
Authors: Zhao T , Ruan D
Published: June 2015

Purpose:

The growing size and heterogeneity in training atlas necessitates sophisticated schemes to identify only the most relevant atlases for the specific multi‐atlas‐based image segmentation problem. This study aims to develop a model to infer the inaccessible oracle geometric relevance metric from surrogate image similarity metrics, and based on such model, provide guidance to atlas selection in multi‐atlas‐based image segmentation.

Methods:

We relate the oracle geometric relevance metric in label space to the surrogate metric in image space, by a monotonically non‐decreasing function with additive random perturbations. Subsequently, a surrogate's ability to prognosticate the oracle order for atlas subset selection is quantified probabilistically. Finally, important insights and guidance are provided for the design of fusion set size, balancing the competing demands to include the most relevant atlases and to exclude the most irrelevant ones. A systematic solution is derived based on an optimization framework. Model verification and performance assessment is performed based on clinical prostate MR images.

Results:

The proposed surrogate model was exemplified by a linear map with normally distributed perturbation, and verified with several commonly‐used surrogates, including MSD, NCC and (N)MI. The derived behaviors of different surrogates in atlas selection and their corresponding performance in ultimate label estimate were validated. The performance of NCC and (N)MI was similarly superior to MSD, with a 10% higher atlas selection probability and a segmentation performance increase in DSC by 0.10 with the first and third quartiles of (0.83, 0.89), compared to (0.81, 0.89). The derived optimal fusion set size, valued at 7/8/8/7 for MSD/NCC/MI/NMI, agreed well with the appropriate range [4, 9] from empirical observation.

Conclusion:

This work has developed an efficacious probabilistic model to characterize the image‐based surrogate metric on atlas selection. Analytical insights lead to valid guiding principles on fusion set size design.
TU‐CD‐BRA‐08: Single‐Energy Computed Tomography‐Based Pulmonary Perfusion Imaging: Proof‐Of‐Principle in a Canine Model
Authors: Yamamoto T , Kent M , Wisner E , Fujita Y , Boone J
Published: June 2015

Purpose:

Pulmonary perfusion imaging has provided significant insights into pulmonary diseases, and can be useful in radiotherapy. The purpose of this study was to prospectively establish proof‐of‐principle in a canine model for single‐energy CT‐based perfusion imaging, which has the potential for widespread clinical implementation.

Methods:

Single‐energy CT perfusion imaging is based on: (1) acquisition of inspiratory breath‐hold CT scans before and after intravenous injection of iodinated contrast medium, (2) deformable image registration (DIR) of the two CT image data sets, and (3) subtraction of the pre‐contrast image from post‐contrast image, yielding a map of Hounsfield unit (HU) enhancement. These subtraction image data sets hypothetically represent perfused blood volume, a surrogate for perfusion. In an IACUC‐approved clinical trial, we acquired pre‐ and post‐contrast CT scans in the prone posture for six anesthetized, mechanically‐ventilated dogs. The elastix algorithm was used for DIR. The registration accuracy was quantified using the target registration errors (TREs) for 50 pulmonary landmarks in each dog. The gradient of HU enhancement between gravity‐dependent (ventral) and non‐dependent (dorsal) regions was evaluated to quantify the known effect of gravity, i.e., greater perfusion in ventral regions.

Results:

The lung volume difference between the two scans was 4.3±3.5% on average (range 0.3%–10.1%). DIR demonstrated an average TRE of 0.7±1.0 mm. HU enhancement in lung parenchyma was 34±10 HU on average and varied considerably between individual dogs, indicating the need for improvement of the contrast injection protocol. HU enhancement in ventral (gravity‐dependent) regions was found to be greater than in dorsal regions. A population average ventral‐to‐dorsal gradient of HU enhancement was strong (R2=0.94) and statistically significant (p<0.01).

Conclusion:

This canine study demonstrated relatively accurate DIR and a strong ventral‐to‐dorsal gradient of HU enhancement, providing proof‐of‐principle for single‐energy CT pulmonary perfusion imaging. This ongoing study will enroll more dogs and investigate the physiological significance.

This study was supported by a Philips Healthcare/Radiological Society of North America (RSNA) Research Seed Grant (RSD1458).
TU‐CD‐BRA‐10: Hybridized Deformable Registration Framework for Contrast‐Enhanced Dedicated Breast CT
Authors: Gazi P , Boone J
Published: June 2015

Purpose:

Utilization of contrast enhancement in dedicated breast CT (bCT) has been reported to be a reliable metric in determining the conspicuity of malignant breast lesions. In this study, we have designed and developed a framework of image segmentation and registration to align the structure of pre‐ and post‐contrast breast CT image.

Methods:

An iterative two‐means clustering method was used in image segmentation. The image segmentation algorithm results in segmenting the breast CT image to skin, adipose, fibroglandular and contrast‐enhanced lesions. These results are used in image registration method. A deformable image registration method code‐named Intensity Difference Adaptive Demons (IDAD) was developed based on the Demons image registration. Within the developed framework, the deformation field forces are calculated considering the contrast enhancement levels in the bCT image voxels. The performance of the developed framework was evaluated using mathematical simulations and patient breast CT images.

Results:

The proposed method outperformed conventional affine and other Demons variations for serial pre‐contrast and post‐contrast breast CT image alignment. In simulation studies, IDAD exhibited 1–11% improvement in Normalized Cross Correlation (NCC) compared to the conventional Demons approach with the improvement increasing with lesion size and contrast enhancement levels. Registration error measured by Target Registration Error (TRE) shows only submillimeter mismatches between the concordant anatomical target points in all patient studies. The implementation of the presented hybridized framework was implemented based on a parallel processing architecture, resulting in rapid execution time for the iterative segmentation and intensity‐adaptive registration techniques.

Conclusion:

Characterization of contrast‐enhanced lesions is improved using IDAD. Spatial subtraction of the aligned images yields useful diagnostic information with respect to lesion morphology.
TU‐CD‐BRA‐11: Application of Bone Suppression Technique to Inspiratory/expiratory Chest Radiography
Authors: Tanaka R , Sanada S , Sakuta K , Kawashima H , Kishitani Y
Published: June 2015

Purpose:

The bone suppression technique based on advanced image processing can suppress the conspicuity of bones on chest radiographs, creating soft tissue images normally obtained by the dual‐energy subtraction technique. This study was performed to investigate the usefulness of bone suppression technique in quantitative analysis of pulmonary function in inspiratory/expiratory chest radiography.

Methods:

Commercial bone suppression image processing software (ClearRead; Riverain Technologies) was applied to paired inspiratory/expiratory chest radiographs of 107 patients (normal, 33; abnormal, 74) to create corresponding bone suppression images. The abnormal subjects had been diagnosed with pulmonary diseases, such as pneumothorax, pneumonia, emphysema, asthma, and lung cancer. After recognition of the lung area, the vectors of respiratory displacement were measured in all local lung areas using a cross‐correlation technique. The measured displacement in each area was visualized as displacement color maps. The distribution pattern of respiratory displacement was assessed by comparison with the findings of lung scintigraphy.

Results:

Respiratory displacement of pulmonary markings (soft tissues) was able to be quantified separately from the rib movements on bone suppression images. The resulting displacement map showed a left‐right symmetric distribution increasing from the lung apex to the bottom region of the lung in many cases. However, patients with ventilatory impairments showed a nonuniform distribution caused by decreased displacement of pulmonary markings, which were confirmed to correspond to area with ventilatory impairments found on the lung scintigrams.

Conclusion:

The bone suppression technique was useful for quantitative analysis of respiratory displacement of pulmonary markings without any interruption of the rib shadows. Abnormal areas could be detected as decreased displacement of pulmonary markings. Inspiratory/expiratory chest radiography combined with the bone suppression technique has potential for predicting local lung function on the basis of dynamic analysis of pulmonary markings.

This work was partially supported by Nakatani Foundation, Grant‐in‐aid for Scientific Research (C) of Ministry of Education, Culture, Sports, Science and Technology, JAPAN (Grant number : 24601007), and Nakatani Foundation, Mitsubishi Foundation, and the he Mitani Foundation for Research and Development. Yasushi Kishitani is a staff of TOYO corporation.
TU‐CD‐303‐00: In Memoriam of Warren Sinclair: Physics Applications for New Radiobiology
Authors: Chang Sha
Published: June 2015

The Medical Physics and Radiation Protection communities lost one of their true pioneers in May, 2014 with the passing of Warren K. Sinclair, Ph.D. He received his Doctorate in Physics at the University of London, U.K. He was a fellow of the Institute of Physics and a Certified Health Physicist. After a number of posts at Hospitals and Universities in the U.K. and New Zealand, he became the Head, Physics Department at the M.D. Anderson Hospital, Houston, TX. He held a number of academic physics positions with the University of Texas, Austin at the main campus and at the Postgraduate School of Medicine, Houston. He later served as a Senior Biophysicist, Division Director, and then Associate Laboratory Director for Biomedical Division Director, and then Associate Laboratory Director for Biomedical and Environmental Research at the Argonne National Laboratory, IL. He had additional academic appointments at the University of California, Berkeley; Northern Illinois University; the University of Illinois (Chicago Circle Campus); and the University of Chicago.

Warren was a charter member of the AAPM and a leader in many communities: President of the AAPM from 1960 to 1961 and the Journal Editor from 1964 to 1969, the 2nd President of the NCRP from 1977 to 1991, and the President of the Radiation Research Society from 1978 to 1979. His many awards included the William D. Coolidge Award in 1986. Even this barely scratches the surface of the many other organizations he served with and influenced including the ICRP, IOP, RSNA, SNM, and UNSCEAR. His research interests resulted in publications from 1948 to the 1990s in many aspects (physical and biological) of radiotherapy and the effects of ionizing radiation in general, leading to early definitions of RBE values for megavoltage radiotherapy as well as contributing to the development of the modern framework for radiation protection worldwide.

Warren was not a retiring person and even after moving to NCRP President Emeritus status continued to provide advice and comments on publications and to mentor others until the time of his passing. Sadly, Warren's long‐time wife Joy passed away in December, 2014 but he is survived by his son Bruce and daughter Roslyn, 2 grandchildren and 4 great‐grandchildren.
TU‐CD‐303‐05: Unveiling Tumor Heterogeneity by Molecular Imaging
Authors: Jeraj R.
Published: June 2015

Recent advances in cancer research have shed new light on the complex processes of how therapeutic radiation initiates changes at cellular, tissue, and system levels that may lead to clinical effects. These new advances may transform the way we use radiation to combat certain types of cancers. For the past two decades many technological advancements in radiation therapy have been largely based on the hypothesis that direct radiation‐induced DNA double strand breaks cause cell death and thus tumor control and normal tissue damage. However, new insights have elucidated that in addition to causing cellular DNA damage, localized therapeutic radiation also initiates cascades of complex downstream biological responses in tissue that extend far beyond where therapeutic radiation dose is directly deposited. For instance, studies show that irradiated dying tumor cells release tumor antigens that can lead the immune system to a systemic anti‐cancer attack throughout the body of cancer patient; targeted irradiation to solid tumor also increases the migration of tumor cells already in bloodstream, the seeds of potential metastasis. Some of the new insights may explain the long ago discovered but still unexplained non‐localized radiation effects (bystander effect and abscopal effect) and the efficacy of spatially fractionated radiation therapy (microbeam radiation therapy and GRID therapy) where many “hot” and “cold” spots are intentionally created throughout the treatment volume. Better understanding of the mechanisms behind the non‐localized radiation effects creates tremendous opportunities to develop new and integrated cancer treatment strategies that are based on radiotherapy, immunology, and chemotherapy. However, in the multidisciplinary effort to advance new radiobiology, there are also tremendous challenges including a lack of multidisciplinary researchers and imaging technologies for the microscopic radiation‐induced responses.

A better grasp of the essence of these advances in cancer biology research will give medical physicists a new perspective in daily clinical physics practice and in future radiation therapy technological development. Furthermore, academic medical physics should continue to be an integral part of the multidisciplinary cancer research community, harnessing our newly acquired understanding of radiation effects, and developing novel cost‐effective treatment strategies to better combat cancer.

Learning Objectives:

Understand that localized radiation can lead to non‐localized secondary effects such as radiation‐induced immune response, bystander effect, and abscopal effect.

Understand that the non‐localized radiation effects may be harnessed to improve cancer treatment.

Learn examples of physics participation in multidisciplinary research to advance cancer biology.

Recognize the challenges and possibilities of physics applications in cancer research.

Chang: NIH 5RC2CA148487‐02 and 1U54CA151652‐01

Graves: IDEA award (19IB‐0106) from the California Breast Cancer Research Program (CBCRP), and by NIH P01 CA67166
TU‐CD‐204‐01: CT Noise Power Sectrum for Filtered Backprojection and Iterative Reconstruction
Authors: Dong F.
Published: June 2015

For practicing medical physicists, CT image quality assessment is, in general, limited to the ones required by ACR and based on the axial images, such as CT number uniformity, image noise, contrast‐to‐noise ratio (CNR), and high contrast resolution. However, with more advanced technologies introduced by CT vendors, just assessing these basic image quality metrics may not be enough. Noise power spectrum (NPS), characterizing the signal noise component at each spatial frequency, is a powerful tool to predict the CT performance related to lesion detectability and noise texture. The quality of coronal and sagittal reformatted images is, in a large part, determined by the slice profile. How to accurately assess the slice profile is important for clinical medical physicists but not well recognized.

Automatic tube current modulation (ATCM) has been adopted by major CT manufacturers, to maintain image quality across the scan range. The way how ATMC works varies significantly among vendors. A “standard” method is needed to evaluate the performance of this critical dose‐saving and image quality improvement technique. As dual energy CT becomes more readily available for routine clinical use, the need of image quality assessment metrics unique to the dual energy CT mode is becoming urgent.

The session will facilitate the discussion of NPS and its application in the evaluation of FBP and iterative reconstruction. This session will also present the methods to measure the slice profile and characterize the performance of ATCM. The last part of this session will focus on the physics of CT dual energy mode, as well as unique image quality metrics to evaluate the performance of the dual energy mode.

Learning Objectives:

Be familiar with procedures on how to correctly compute CT noise power spectrum

Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction

Understand CT slice profile and how to accurately measure it

Be familiar with ATCM from major CT vendors and how to evaluate its performance

Understand different hardware approaches for dual energy CT

Be familiar with image quality metrics relevant to dual energy mode

Schmidt: Employee of Siemens Healthcare

Fan: Employee of GE Healthcare
TU‐CD‐204‐02: Measuring CT Slice Profile and Characterizing Automatic Tube Current Modulation
Authors: Fan J.
Published: June 2015

For practicing medical physicists, CT image quality assessment is, in general, limited to the ones required by ACR and based on the axial images, such as CT number uniformity, image noise, contrast‐to‐noise ratio (CNR), and high contrast resolution. However, with more advanced technologies introduced by CT vendors, just assessing these basic image quality metrics may not be enough. Noise power spectrum (NPS), characterizing the signal noise component at each spatial frequency, is a powerful tool to predict the CT performance related to lesion detectability and noise texture. The quality of coronal and sagittal reformatted images is, in a large part, determined by the slice profile. How to accurately assess the slice profile is important for clinical medical physicists but not well recognized.

Automatic tube current modulation (ATCM) has been adopted by major CT manufacturers, to maintain image quality across the scan range. The way how ATMC works varies significantly among vendors. A “standard” method is needed to evaluate the performance of this critical dose‐saving and image quality improvement technique. As dual energy CT becomes more readily available for routine clinical use, the need of image quality assessment metrics unique to the dual energy CT mode is becoming urgent.

The session will facilitate the discussion of NPS and its application in the evaluation of FBP and iterative reconstruction. This session will also present the methods to measure the slice profile and characterize the performance of ATCM. The last part of this session will focus on the physics of CT dual energy mode, as well as unique image quality metrics to evaluate the performance of the dual energy mode.

Learning Objectives:

Be familiar with procedures on how to correctly compute CT noise power spectrum

Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction

Understand CT slice profile and how to accurately measure it

Be familiar with ATCM from major CT vendors and how to evaluate its performance

Understand different hardware approaches for dual energy CT

Be familiar with image quality metrics relevant to dual energy mode

Schmidt: Employee of Siemens Healthcare

Fan: Employee of GE Healthcare
TU‐CD‐204‐03: Dual Energy CT Physics, Hardware and Image Quality Assessment
Authors: Schmidt B.
Published: June 2015

For practicing medical physicists, CT image quality assessment is, in general, limited to the ones required by ACR and based on the axial images, such as CT number uniformity, image noise, contrast‐to‐noise ratio (CNR), and high contrast resolution. However, with more advanced technologies introduced by CT vendors, just assessing these basic image quality metrics may not be enough. Noise power spectrum (NPS), characterizing the signal noise component at each spatial frequency, is a powerful tool to predict the CT performance related to lesion detectability and noise texture. The quality of coronal and sagittal reformatted images is, in a large part, determined by the slice profile. How to accurately assess the slice profile is important for clinical medical physicists but not well recognized.

Automatic tube current modulation (ATCM) has been adopted by major CT manufacturers, to maintain image quality across the scan range. The way how ATMC works varies significantly among vendors. A “standard” method is needed to evaluate the performance of this critical dose‐saving and image quality improvement technique. As dual energy CT becomes more readily available for routine clinical use, the need of image quality assessment metrics unique to the dual energy CT mode is becoming urgent.

The session will facilitate the discussion of NPS and its application in the evaluation of FBP and iterative reconstruction. This session will also present the methods to measure the slice profile and characterize the performance of ATCM. The last part of this session will focus on the physics of CT dual energy mode, as well as unique image quality metrics to evaluate the performance of the dual energy mode.

Learning Objectives:

Be familiar with procedures on how to correctly compute CT noise power spectrum

Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction

Understand CT slice profile and how to accurately measure it

Be familiar with ATCM from major CT vendors and how to evaluate its performance

Understand different hardware approaches for dual energy CT

Be familiar with image quality metrics relevant to dual energy mode

Schmidt: Employee of Siemens Healthcare

Fan: Employee of GE Healthcare
TU‐CD‐207‐01: Characterization of Breast Tissue Composition Using Spectral Mammography
Authors: Ding H , Cho H , Kumar N , Sennung D , Ng A Lam , Molloi S
Published: June 2015

Purpose:

To investigate the feasibility of characterizing the chemical composition of breast tissue, in terms of water and lipid, by using spectral mammography in simulation and postmortem studies.

Methods:

Analytical simulations were performed to obtain low‐ and high‐energy signals of breast tissue based on previously reported water, lipid, and protein contents. Dual‐energy decomposition was used to characterize the simulated breast tissue into water and lipid basis materials and the measured water density was compared to the known value. In experimental studies, postmortem breasts were imaged with a spectral mammography system based on a scanning multi‐slit Si strip photon‐counting detector. Low‐ and high‐energy images were acquired simultaneously from a single exposure by sorting the recorded photons into the corresponding energy bins. Dual‐energy material decomposition of the low‐ and high‐energy images yielded individual pixel measurements of breast tissue composition in terms of water and lipid thicknesses. After imaging, each postmortem breast was chemically decomposed into water, lipid and protein. The water density calculated from chemical analysis was used as the reference gold standard. Correlation of the water density measurements between spectral mammography and chemical analysis was analyzed using linear regression.

Results:

Both simulation and postmortem studies showed good linear correlation between the decomposed water thickness using spectral mammography and chemical analysis. The slope of the linear fitting function in the simulation and postmortem studies were 1.15 and 1.21, respectively.

Conclusion:

The results indicate that breast tissue composition, in terms of water and lipid, can be accurately measured using spectral mammography. Quantitative breast tissue composition can potentially be used to stratify patients according to their breast cancer risk.
TU‐CD‐207‐02: Quantification of Breast Lesion Compositions Using Low‐Dose Spectral Mammography: A Feasibility Study
Authors: Cho H , Ding H , Sennung D , Kumar N , Molloi S
Published: June 2015

Purpose:

To investigate the feasibility of measuring breast lesion composition with spectral mammography using physical phantoms and bovine tissue.

Methods:

Phantom images were acquired with a spectral mammography system with a silicon‐strip based photon‐counting detector. Plastic water and adipose‐equivalent phantoms were used to calibrate the system for dual‐energy material decomposition. The calibration phantom was constructed in range of 2–8 cm thickness and water densities in the range of 0% to 100%. A non‐linear rational fitting function was used to calibrate the imaging system. The phantom studies were performed with uniform background phantom and non‐uniform background phantom. The breast lesion phantoms (2 cm in diameter and 0.5 cm in thickness) were made with water densities ranging from 0 to 100%. The lesion phantoms were placed in different positions and depths on the phantoms to investigate the accuracy of the measurement under various conditions. The plastic water content of the lesion was measured by subtracting the total decomposed plastic water signal from a surrounding 2.5 mm thick border outside the lesion. In addition, bovine tissue samples composed of 80 % lean were imaged as background for the simulated lesion phantoms.

Results:

The thickness of measured and known water contents was compared. The rootmean‐square (RMS) errors in water thickness measurements were 0.01 cm for the uniform background phantom, 0.04 cm for non‐uniform background phantom, and 0.03 cm for 80% lean bovine tissue background.

Conclusion:

The results indicate that the proposed technique using spectral mammography can be used to accurately characterize breast lesion compositions.
TU‐EF‐204‐02: Hiigh Quality and Sub‐MSv Cerebral CT Perfusion Imaging
Authors: Li Ke , Niu Kai , Wu Yijing , Chen Guang‐Hong
Published: June 2015

Purpose:

CT Perfusion (CTP) imaging is of great importance in acute ischemic stroke management due to its potential to detect hypoperfused yet salvageable tissue and distinguish it from definitely unsalvageable tissue. However, current CTP imaging suffers from poor image quality and high radiation dose (up to 5 mSv). The purpose of this work was to demonstrate that technical innovations such as Prior Image Constrained Compressed Sensing (PICCS) have the potential to address these challenges and achieve high quality and sub‐mSv CTP imaging.

Methods:

(1) A spatial‐temporal 4D cascaded system model was developed to indentify the bottlenecks in the current CTP technology; (2) A task‐based framework was developed to optimize the CTP system parameters; (3) Guided by (1) and (2), PICCS was customized for the reconstruction of CTP source images. Digital anthropomorphic perfusion phantoms, animal studies, and preliminary human subject studies were used to validate and evaluate the potentials of using these innovations to advance the CTP technology.

Results:

The 4D cascaded model was validated in both phantom and canine stroke models. Based upon this cascaded model, it has been discovered that, as long as the spatial resolution and noise properties of the 4D source CT images are given, the 3D MTF and NPS of the final CTP maps can be analytically derived for a given set of processing methods and parameters. The cascaded model analysis also identified that the most critical technical factor in CTP is how to acquire and reconstruct high quality source images; it has very little to do with the denoising techniques often used after parametric perfusion calculations. This explained why PICCS resulted in a five‐fold dose reduction or substantial improvement in image quality.

Conclusion:

Technical innovations generated promising results towards achieving high quality and sub‐mSv CTP imaging for reliable and safe assessment of acute ischemic strokes.

K. Li, K. Niu, Y. Wu: Nothing to disclose. G.‐H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.
TU‐EF‐204‐03: Task‐Based KV and MAs Optimization for Radiation Dose Reduction in CT: From FBP to Statistical Model‐Based Iterative Reconstruction (MBIR)
Authors: Gomez‐Cardona D , Li K , Lubner M G , Pickhardt P J , Chen G‐H
Published: June 2015

Purpose:

The introduction of the highly nonlinear MBIR algorithm to clinical CT systems has made CNR an invalid metric for kV optimization. The purpose of this work was to develop a task‐based framework to unify kV and mAs optimization for both FBP‐ and MBIR‐based CT systems.

Methods:

The kV‐mAs optimization was formulated as a constrained minimization problem: to select kV and mAs to minimize dose under the constraint of maintaining the detection performance as clinically prescribed. To experimentally solve this optimization problem, exhaustive measurements of detectability index (d’) for a hepatic lesion detection task were performed at 15 different mA levels and 4 kV levels using an anthropomorphic phantom. The measured d’ values were used to generate an iso‐detectability map; similarly, dose levels recorded at different kV‐mAs combinations were used to generate an iso‐dose map. The iso‐detectability map was overlaid on top of the iso‐dose map so that for a prescribed detectability level d’, the optimal kV‐mA can be determined from the crossing between the d’ contour and the dose contour that corresponds to the minimum dose.

Results:

Taking d’=16 as an example: the kV‐mAs combinations on the measured iso‐d’ line of MBIR are 80–150 (3.8), 100–140 (6.6), 120–150 (11.3), and 140–160 (17.2), where values in the parentheses are measured dose values. As a Result, the optimal kV was 80 and optimal mA was 150. In comparison, the optimal kV and mA for FBP were 100 and 500, which corresponded to a dose level of 24 mGy. Results of in vivo animal experiments were consistent with the phantom results.

Conclusion:

A new method to optimize kV and mAs selection has been developed. This method is applicable to both linear and nonlinear CT systems such as those using MBIR. Additional dose savings can be achieved by combining MBIR with this method.

This work was partially supported by an NIH grant R01CA169331 and GE Healthcare. K. Li, D. Gomez‐Cardona, M. G. Lubner: Nothing to disclose. P. J. Pickhardt: Co‐founder, VirtuoCTC, LLC Stockholder, Cellectar Biosciences, Inc. G.‐H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.
TU‐EF‐210‐00: Therapeutic Strategies and Image Guidance
Authors: Payne Allison
Published: June 2015

The use of therapeutic ultrasound to provide targeted therapy is an active research area that has a broad application scope. The invited talks in this session will address currently implemented strategies and protocols for both hyperthermia and ablation applications using therapeutic ultrasound. The role of both ultrasound and MRI in the monitoring and assessment of these therapies will be explored in both pre‐clinical and clinical applications.

Katherine Ferrara: High Intensity Focused Ultrasound, Drug Delivery, and Immunotherapy

Rajiv Chopra: Translating Localized Doxorubicin Delivery to Pediatric Oncology using MRI‐guided HIFU

Elisa Konofagou: Real‐time Ablation Monitoring and Lesion Quantification using Harmonic Motion Imaging

Keyvan Farahani: AAPM Task Groups in Interventional Ultrasound Imaging and Therapy

Learning Objectives:

Understand the role of ultrasound in localized drug delivery and the effects of immunotherapy when used in conjunction with ultrasound therapy.

Understand potential targeted drug delivery clinical applications including pediatric oncology.

Understand the technical requirements for performing targeted drug delivery.

Understand how radiation‐force approaches can be used to both monitor and assess high intensity focused ultrasound ablation therapy.

Understand the role of AAPM task groups in ultrasound imaging and therapies.

Chopra: Funding from Cancer Prevention and Research Initiative of Texas (CPRIT), Award R1308 Evelyn and M.R. Hudson Foundation; Research Support from Research Contract with Philips Healthcare; COI are Co‐founder of FUS Instruments Inc

Ferrara: Supported by NIH, UCDavis and California (CIRM and BHCE)

Farahani: In‐kind research support from Philips Healthcare
TU‐EF‐210‐04: AAPM Task Groups in Interventional Ultrasound Imaging and Therapy
Authors: Farahani K.
Published: June 2015

The use of therapeutic ultrasound to provide targeted therapy is an active research area that has a broad application scope. The invited talks in this session will address currently implemented strategies and protocols for both hyperthermia and ablation applications using therapeutic ultrasound. The role of both ultrasound and MRI in the monitoring and assessment of these therapies will be explored in both pre‐clinical and clinical applications.

Katherine Ferrara: High Intensity Focused Ultrasound, Drug Delivery, and Immunotherapy

Rajiv Chopra: Translating Localized Doxorubicin Delivery to Pediatric Oncology using MRI‐guided HIFU

Elisa Konofagou: Real‐time Ablation Monitoring and Lesion Quantification using Harmonic Motion Imaging

Keyvan Farahani: AAPM Task Groups in Interventional Ultrasound Imaging and Therapy

Learning Objectives:

Understand the role of ultrasound in localized drug delivery and the effects of immunotherapy when used in conjunction with ultrasound therapy.

Understand potential targeted drug delivery clinical applications including pediatric oncology.

Understand the technical requirements for performing targeted drug delivery.

Understand how radiation‐force approaches can be used to both monitor and assess high intensity focused ultrasound ablation therapy.

Understand the role of AAPM task groups in ultrasound imaging and therapies.

Chopra: Funding from Cancer Prevention and Research Initiative of Texas (CPRIT), Award R1308 Evelyn and M.R. Hudson Foundation; Research Support from Research Contract with Philips Healthcare; COI are Co‐founder of FUS Instruments Inc

Ferrara: Supported by NIH, UCDavis and California (CIRM and BHCE)

Farahani: In‐kind research support from Philips Healthcare
TU‐F‐BRB‐03: Clinical Implementation of MR‐Based Motion Management
Authors: Glide‐Hurst C.
Published: June 2015

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.

Learning Objectives:

Discuss the need of MR‐based motion management for improving patient care in radiotherapy.

Understand MR techniques for motion imaging and tumor motion characterization.

Understand the current state of the art and future steps for clinical integration.

Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.
TU‐PIS‐Exhibit Hall‐2: How to Move Beyond Dose Monitoring to Imaging Performance Utilization
Authors: Valencia D.
Published: June 2015

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.

Learning Objectives:

Discuss the need of MR‐based motion management for improving patient care in radiotherapy.

Understand MR techniques for motion imaging and tumor motion characterization.

Understand the current state of the art and future steps for clinical integration.

Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.
TU‐PIS‐Exhibit Hall‐3: Simultaneous tracking of patient and real time staff dose to optimize interventional workflow
Authors: Boon S.
Published: June 2015

The current clinical standard of organ respiratory imaging, 4D‐CT, is fundamentally limited by poor soft‐tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose‐volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft‐tissue contrast. MRI‐based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR‐based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D‐MRI and MRI hybrid treatment machines (i.e. MR‐linac or MR‐Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI‐based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR‐based motion management methods and technologies, the state‐of‐the‐art concerning MRI development and clinical application and the barriers to more widespread adoption.

Learning Objectives:

Discuss the need of MR‐based motion management for improving patient care in radiotherapy.

Understand MR techniques for motion imaging and tumor motion characterization.

Understand the current state of the art and future steps for clinical integration.

Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.
TU‐G‐304‐00: New Member Symposium
Authors: Keener Justin
Published: June 2015

As a new member of AAPM, it's easy to feel overwhelmed by the size and complexity of the association and to be unaware of the benefits and opportunities available to members. At this year's AAPM Annual Meeting in Anaheim, we will host a New Member Symposium where you can learn more about the organization, member resources, opportunities to get involved, and about topics of particular interest to new professionals. We encourage you to take advantage of this great opportunity to learn valuable information and to grow your professional network.

Following an introduction from Dr. John Boone, AAPM President; Justin Keener, Chair of the New Professional Subcommittee, will speak on, “Physics of the AAPM.” Next will be Dr. George Sherouse sharing invaluable information in his talk, “Things You Won't Be Able to Say Somebody Should've Told You.”

Registered attendees will receive a raffle ticket. Enter to win a complimentary registration for the 2016 Annual Meeting in Washington, DC!

In addition, all new members who register for the Symposium will receive a drink ticket, good for one complimentary soda or beer served after the New Member Symposium during the social with Committee Chairs from 4 AAPM Councils: Science, Education, Professional and Administrative.

Get your picture taken!!! There will be a photographer there to take pictures for your profile in the AAPM directory.

The New Member Symposium is a (free) ticket option when you register online for the Annual Meeting. We hope that you will plan to attend.