bluuebunny/crossref_metadata_2025_split huggingface dataset:
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 1U54CA151652‐01Graves: 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 HealthcareFan: 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 HealthcareFan: 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 HealthcareFan: 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 ImmunotherapyRajiv Chopra: Translating Localized Doxorubicin Delivery to Pediatric Oncology using MRI‐guided HIFUElisa Konofagou: Real‐time Ablation Monitoring and Lesion Quantification using Harmonic Motion ImagingKeyvan Farahani: AAPM Task Groups in Interventional Ultrasound Imaging and TherapyLearning 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 IncFerrara: 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 ImmunotherapyRajiv Chopra: Translating Localized Doxorubicin Delivery to Pediatric Oncology using MRI‐guided HIFUElisa Konofagou: Real‐time Ablation Monitoring and Lesion Quantification using Harmonic Motion ImagingKeyvan Farahani: AAPM Task Groups in Interventional Ultrasound Imaging and TherapyLearning 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 IncFerrara: Supported by NIH, UCDavis and California (CIRM and BHCE)Farahani: In‐kind research support from Philips Healthcare