bluuebunny/crossref_metadata_2025_split huggingface dataset:
TU‐EF‐204‐08: Dose Efficiency of Added Beam‐Shaping Filter with Varied Attenuation Levels in Lung‐Cancer Screening CT
Authors: Ma C , Yu L , Vrieze T , Leng S , Fletcher J , McCollough C 
Published: June 2015

Purpose:Added filtration such as tin filter has the potential to improve dose efficiency of x‐ray beam in lung‐cancer screening CT. However, dose efficiency with added beam filtration is highly dependent on patient attenuation level. In this phantom study, we evaluated the image quality at different tube voltages with and without added tin filter when attenuation level varies.Methods:A 30 × 20 cm anthropomorphic thorax phantom with three added extension rings were used to simulate small (S), medium (M), large (L), and extra‐large (XL) adult patients. These phantoms were scanned on a 192‐slice CT scanner (Force, Siemens) at 100 and 120kV without tin filtration, and 100 and 150 kV with tin filtration (100Sn and 150Sn), at multiple dose levels at each kV. Images were reconstructed using iterative reconstruction (ADMIRE, Siemens). Radiation dose was measured with a 0.6 cc ion chamber in the middle and peripheral areas of the phantom. Image quality was assessed using mean image noise at uniform areas in the central region and lung. Radiation dose that is required for each kV to match the noise in a routine lung‐cancer CT screening technique (120kV, 25 quality reference mAs) was calculated.Results:At each of the four phantom sizes, 100Sn had the lowest noise in both soft tissue and lung. Compared with 120 kV, 100Sn saved 39%–60% dose for the same noise, depending on phantom size. For the XL phantom (50 by 40 cm), 150Sn provided images with the least beam‐hardening artifact in peripheral region.Conclusion:For thoracic CT, added tin filtration can provide considerable dose reduction compared with 120 kV. 100Sn provides better dose efficiencies for all phantom sizes, while 150Sn provides better image quality in peripheral region for extra‐large patients.Drs.Joel G. Fletcher and Cynthia H. McCollough receive research support from Siemens Healthcare.
TU‐EF‐204‐10: A Preliminary Study Evaluating Calculation Variations of Local Noise Power Spectra for CT Simulation in Radiation Therapy
Authors: Dolly S , Chen H , Anastasio M , Mutic S , Li H 
Published: June 2015

Purpose:Local noise power spectrum (NPS) properties are significantly affected by calculation variables and CT acquisition and reconstruction parameters, but a thoughtful analysis of these effects is absent. In this study, we performed a complete analysis of the effects of calculation and imaging parameters on the NPS.Methods:The uniformity module of a Catphan phantom was scanned with a Philips Brilliance 64‐slice CT simulator using various scanning protocols. Images were reconstructed using both FBP and iDose4 reconstruction algorithms. From these images, local NPS were calculated for regions of interest (ROI) of varying locations and sizes, using four image background removal methods. Additionally, using a predetermined ground truth, NPS calculation accuracy for various calculation parameters was compared for computer simulated ROIs. A complete analysis of the effects of calculation, acquisition, and reconstruction parameters on the NPS was conducted.Results:The local NPS varied with ROI size and image background removal method, particularly at low spatial frequencies. The image subtraction method was the most accurate according to the computer simulation study, and was also the most effective at removing low frequency background components in the acquired data. However, first‐order polynomial fitting using residual sum of squares and principle component analysis provided comparable accuracy under certain situations. Similar general trends were observed when comparing the NPS for FBP to that of iDose4 while varying other calculation and scanning parameters. However, while iDose4 reduces the noise magnitude compared to FBP, this reduction is spatial‐frequency dependent, further affecting NPS variations at low spatial frequencies.Conclusion:The local NPS varies significantly depending on calculation parameters, image acquisition parameters, and reconstruction techniques. Appropriate local NPS calculation should be performed to capture spatial variations of noise; calculation methodology should be selected with consideration of image reconstruction effects and the desired purpose of CT simulation for radiotherapy tasks.
TU‐EF‐204‐11: Impact of Using Multi‐Slice Training Sets On the Performance of a Channelized Hotelling Observer in a Low‐Contrast Detection Task in CT
Authors: Favazza C , Yu L , Leng S , McCollough C 
Published: June 2015

Purpose:To investigate using multiple CT image slices from a single acquisition as independent training images for a channelized Hotelling observer (CHO) model to reduce the number of repeated scans for CHO‐based CT image quality assessment.Methods:We applied a previously validated CHO model to detect low contrast disk objects formed from cross‐sectional images of three epoxy‐resin‐based rods (diameters: 3, 5, and 9 mm; length: ∼5cm). The rods were submerged in a 35x 25 cm2 iodine‐doped water filled phantom, yielding‐15 HU object contrast. The phantom was scanned 100 times with and without the rods present. Scan and reconstruction parameters include: 5 mm slice thickness at 0.5 mm intervals, 120 kV, 480 Quality Reference mAs, and a 128‐slice scanner. The CHO's detectability index was evaluated as a function of factors related to incorporating multi‐slice image data: object misalignment along the z‐axis, inter‐slice pixel correlation, and number of unique slice locations. In each case, the CHO training set was fixed to 100 images.Results:Artificially shifting the object's center position by as much as 3 pixels in any direction relative to the Gabor channel filters had insignificant impact on object detectability. An inter‐slice pixel correlation of >∼0.2 yielded positive bias in the model's performance. Incorporating multi‐slice image data yielded slight negative bias in detectability with increasing number of slices, likely due to physical variations in the objects. However, inclusion of image data from up to 5 slice locations yielded detectability indices within measurement error of the single slice value.Conclusion:For the investigated model and task, incorporating image data from 5 different slice locations of at least 5 mm intervals into the CHO model yielded detectability indices within measurement error of the single slice value. Consequently, this methodology would Result in a 5‐fold reduction in number of image acquisitions.This project was supported by National Institutes of Health grants R01 EB017095 and U01 EB017185 from the National Institute of Biomedical Imaging and Bioengineering.
TU‐EF‐204‐12: Quantitative Evaluation of Spectral Detector CT Using Virtual Monochromatic Images: Initial Results
Authors: Duan X , Arbique G , Guild J , Dhanantwari A , Yagil Y , Anderson J 
Published: June 2015

PurposeTo evaluate the image quality and spectral information of a spectral detector CT (SDCT) scanner using virtual monochromatic (VM) energy images.MethodsThe SDCT scanner (Philips Healthcare) was equipped with a dual‐layer detector and spectral iterative reconstruction (IR), which generates conventional 80–140 kV polychromatic energy (PE) CT images using both detector layers, PE images from the low‐energy (upper) and high‐energy (lower) detector layers and VM images. A solid water phantom with iodine (2.0–20.0 mg I/ml) and calcium (50.0–600.0 mg Ca/ml) rod inserts was used to evaluate effective energy estimate (EEE) and iodine contrast to noise ratio (CNR). The EEE corresponding to an insert CT number in a PE image was calculated from a CT number fit to the VM image set. Since PE image is prone to beam‐hardening artifact EEE may underestimate the actual energy separation from two layers of the detector. A 30‐cm‐diameter water phantom was used to evaluate noise power spectrum (NPS). The phantoms were scanned at 120 and 140 kV with the same CTDIvol.ResultsThe CT number difference for contrast inserts in VM images (50–150 keV) was 1.3±6% between 120 and 140 kV scans. The difference of EEE calculated from low‐ and high‐energy detector images was 11.5 and 16.7 keV for 120 and 140 kV scans, respectively. The differences calculated from 140 and 100 kV conventional PE images were 12.8, and 20.1 keV from 140 and 80 kV conventional PE images. The iodine CNR increased monotonically with decreased keV. Compared to conventional PE images, the peak of NPS curves from VM images were shifted to lower frequency.ConclusionThe EEE results indicates that SDCT at 120 and 140 kV may have energy separation comparable to 100/140 kV and 80/140 kV dual‐kV imaging. The effects of IR on CNR and NPS require further investigation for SDCT.Author YY and AD are Philips Healthcare employees.
TU‐EF‐210‐01: HIFU, Drug Delivery, and Immunotherapy
Authors: Ferrara 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
TU‐EF‐210‐02: MRg Hyperthermia
Authors: Chopra R. 
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‐PIS‐Exhibit Hall‐1: Tools for Collecting and Analyzing Patient Dose Index Information from Imaging Equipment
Authors: Supanich Mark , Wang J. 
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‐4: How to implement a dose monitoring solution in the real world: a technical perspective
Authors: Massey 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‐PIS‐Exhibit Hall‐5: Use of the Enterprise‐wide Dose Tracking Software Radimetrics In an Academic Medical System
Authors: Goode A. 
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‐F‐BRB‐00: MRI‐Based Motion Management for RT
Authors: Cai Jing 
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‐F‐BRB‐02: Motion Artifacts and Suppression in MRI
Authors: Zhong X. 
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.