bluuebunny/crossref_metadata_2025 huggingface dataset:
WE‐EF‐303‐11: Activity Distributions of Positron‐Emitting‐Isotopes Activated by Modulated Spot‐Scanning Particle Beams
Authors: Hsi W , Deng Y , Sun L , Li Y , Huang Z , Sheng Y , Zhao J , Zhao F
Published: June 2015

Purpose:

To present the characteristics of positron‐emitting‐isotope (PEI) activity distributions on homogeneous and CIRS thorax phantoms irradiated by modulated spot‐scanning carbon‐ions and protons in Siemens IONTRIS system.

Methods and Materials:

Cylindrical homogeneous wax was irradiated by carbon‐ions and protons of 10cm uniform square field with single‐energy‐layer ranges of 7cm, 16cm and 29cm. Images of PEI distributions were acquired over a period of 30 minutes at 10 minutes after each irradiation. Optimized uniform biological‐equivalent doses of carbon‐ions over a 5.0cm spherical target was delivered to CIRS phantom. Doses with range shifts in depths from 1mm to 6mm were also calculated and delivered to evaluate the accuracy of measuring activated PEI distributions.

Results:

Activated PEI distribution on homogeneous phantoms showed sharper peak near distal edge with flatter distribution toward proximal depth by carbon‐ions than by protons. For depths near at Bragg‐peak, penetration‐depth spreading for energies from 10MeV/u to 60 MeV/u are from 0.4mm to 10.3mm, and 1.2mm to 30.4mm for projectile‐fragments by carbon‐ions and target‐fragments by protons, respectively. For depths proximal to Bragg‐peak, target‐fragments for both carbon‐ions and protons had minimal energy dependence in depth. For complex dose distributions delivered to CIRS thorax phantom, similar PEI peak‐like distributions were still observed for carbon‐ions. And, the changes at locations and edges of measured PEI peak were correlated within 0.5mm of shifted ranges. Mean activities over 5.0cm spherical target were similar for CISR phantom irradiated by doses with various range shifts.

Conclusions:

Peak‐like PEI distributions by carbon‐ions with good correlation to distal edges in both homogeneous and CIRS thorax phantoms present the potential for the in‐vivo range verification while additional efforts is needed for protons. Due to flat distributions for depths at 6mm proximal to distal edges, mean activity at target might be used for in‐vivo dose verification of target.
WE‐EF‐207‐01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task‐Driven Imaging for Cone‐Beam CT in Interventional Guidance
Authors: Gang G , Stayman J , Ouadah S , Ehtiati T , Siewerdsen J
Published: June 2015

Purpose:

This work introduces a task‐driven imaging framework that utilizes a patient‐specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task‐based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view‐dependent reconstruction kernel in filtered‐backprojection reconstruction and non‐circular orbit design in model‐based reconstruction.

Methods:

The system model is based on a cascaded systems analysis of cone‐beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and a wide range of imaging parameters. Detectability index for a non‐prewhitening observer model is used as the objective function in a task‐driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient‐based optimization of reconstruction kernel. The non‐circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task‐driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit.

Results:

The task‐driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non‐circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil.

Conclusion:

The task‐driven imaging framework leverages a knowledge of the imaging task within a patient‐specific anatomical model to optimize image acquisition and reconstruction techniques, thereby improving imaging performance beyond that achievable with conventional approaches.

2R01‐CA‐112163; R01‐EB‐017226; U01‐EB‐018758; Siemens Healthcare (Forcheim, Germany)
WE‐EF‐207‐10: Striped Ratio Grids: A New Concept for Scatter Estimation
Authors: Hsieh S
Published: June 2015

Purpose:

To propose a new method for estimating scatter in x‐ray imaging. We propose the “striped ratio grid,” an anti‐scatter grid with alternating stripes of high scatter rejection (attained, for example, by high grid ratio) and low scatter rejection. To minimize artifacts, stripes are oriented parallel to the direction of the ramp filter. Signal discontinuities at the boundaries between stripes provide information on local scatter content, although these discontinuities are contaminated by variation in primary radiation.

Methods:

We emulated a striped ratio grid by imaging phantoms with two sequential CT scans, one with and one without a conventional grid, and processed them together to mimic a striped ratio grid. Two phantoms were scanned with the emulated striped ratio grid and compared with a conventional anti‐scatter grid and a fan‐beam acquisition, which served as ground truth. A nonlinear image processing algorithm was developed to mitigate the problem of primary variation.

Results:

The emulated striped ratio grid reduced scatter more effectively than the conventional grid alone. Contrast is thereby improved in projection imaging. In CT imaging, cupping is markedly reduced. Artifacts introduced by the striped ratio grid appear to be minimal.

Conclusion:

Striped ratio grids could be a simple and effective evolution of conventional anti‐scatter grids. Unlike several other approaches currently under investigation for scatter management, striped ratio grids require minimal computation, little new hardware (at least for systems which already use removable grids) and impose few assumptions on the nature of the object being scanned.
WE‐EF‐210‐00: Advances in Ultrasound Imaging Technology
Authors: Zagzebski James
Published: June 2015

Recent advances in ultrasound‐related technologies have had a significant impact on enhancing image quality as well as offering new approaches for quantitative ultrasonic imaging and therapeutic applications. The presentations associated with this session will provide an overview of advances in ultrasound image formation, the development of using nanoparticles for therapeutic ultrasound applications, as well as approaches for assessing the intrinsic viscoelastic properties of tissue and methods for monitoring tissue response to therapy.

Learning Objectives:

Develop a general understanding of new technologies associated with enhanced ultrasound image formation and volume imaging.

Develop an understanding of new ultrasound‐based technologies for quantitative assessment of intrinsic tissue properties.

Develop an understanding of novel approaches for ultrasound‐mediated non‐invasive therapeutic applications.

Dr. Rao is an employee of Siemens Ultrasound
WE‐EF‐210‐04: Viscoelastic Response (VisR) Ultrasound for Noninvasively Assessing the Viscoelastic Properties of Tissue
Authors: Gallippi C.
Published: June 2015

Recent advances in ultrasound‐related technologies have had a significant impact on enhancing image quality as well as offering new approaches for quantitative ultrasonic imaging and therapeutic applications. The presentations associated with this session will provide an overview of advances in ultrasound image formation, the development of using nanoparticles for therapeutic ultrasound applications, as well as approaches for assessing the intrinsic viscoelastic properties of tissue and methods for monitoring tissue response to therapy.

Learning Objectives:

Develop a general understanding of new technologies associated with enhanced ultrasound image formation and volume imaging.

Develop an understanding of new ultrasound‐based technologies for quantitative assessment of intrinsic tissue properties.

Develop an understanding of novel approaches for ultrasound‐mediated non‐invasive therapeutic applications.

Dr. Rao is an employee of Siemens Ultrasound
WE‐F‐BRB‐01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge
Authors: Gabriel P.
Published: June 2015

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3‐dimensional dose distribution and its relation to the critical anatomy.

This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients.

Learning Objectives:

Understand the role of standard terminologies, ontologies and data organization in oncology

Understand methods to capture clinical toxicity and outcomes in a clinical setting

Understand opportunities to learn from clinical data and its application to treatment planning

Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented
WE‐F‐BRB‐03: Inclusion of Data‐Driven Risk Predictions in Radiation Treatment Planning in the Context of a Local Level Learning Health System
Authors: McNutt T.
Published: June 2015

Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3‐dimensional dose distribution and its relation to the critical anatomy.

This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients.

Learning Objectives:

Understand the role of standard terminologies, ontologies and data organization in oncology

Understand methods to capture clinical toxicity and outcomes in a clinical setting

Understand opportunities to learn from clinical data and its application to treatment planning

Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented
WE‐G‐304‐00: It Can't Happen to Me! ‐ My Position Has Been Terminated, Now What?
Authors: Starkschall George
Published: June 2015

In the past few years, several high‐profile medical physicists found their positions terminated. It is a fact that no medical physics job is a sinecure, and that individuals can be terminated through no fault of their own. Medical physicists need to be prepared for such an occurrence. Termination provisions in an employment contract, whether individually negotiated or as part of an employee manual, are important, and also generally overlooked when one is going into a new job. Coupled with the fact that most states are “at‐will,” that makes for a tough position for any physicist who finds his/her position terminated.

In this course, a medical physicist who is also a practicing attorney will start the discussion with a description of the various types of employment situations and employment agreements. This will be followed by two high‐profile medical physicists who had their positions terminated in recent years, who will describe their experiences, including answering such questions as

How much time were you given before termination was effective?

Did you have any foreshadowing of what was coming?

How did you deal with the termination?

Given hindsight, what would you have done differently to mitigate the effects of your termination?

During job interviews, are there ways to open closets to find the skeletons?

What advice would you give medical physicists if faced with a similar situation?

What can you negotiate in a termination agreement?

What kinds of termination agreements could be presented?

The symposium will conclude with a panel discussion.

Learning Objectives:

Identify the various types of employment contracts with an emphasis on termination provisions.

Recognize the implications of non‐compete clauses in employment contracts.

Recognize the possibility of termination of employment.

Identify ways to recognize possibly poor employment situations

Identify steps that one could take to mitigate the effects of termination.
WE‐G‐BRD‐06: Volumetric Cine MRI (VC‐MRI) Estimated Based On Prior Knowledge for On‐Board Target Localization
Authors: Harris W , Yin F , Cai J , Zhang Y , Ren L
Published: June 2015

Purpose:

To develop a technique to generate on‐board VC‐MRI using patient prior 4D‐MRI, motion modeling and on‐board 2D‐cine MRI for real‐time 3D target verification of liver and lung radiotherapy.

Methods:

The end‐expiration phase images of a 4D‐MRI acquired during patient simulation are used as patient prior images. Principal component analysis (PCA) is used to extract 3 major respiratory deformation patterns from the Deformation Field Maps (DFMs) generated between end‐expiration phase and all other phases. On‐board 2D‐cine MRI images are acquired in the axial view. The on‐board VC‐MRI at any instant is considered as a deformation of the prior MRI at the end‐expiration phase. The DFM is represented as a linear combination of the 3 major deformation patterns. The coefficients of the deformation patterns are solved by matching the corresponding 2D slice of the estimated VC‐MRI with the acquired single 2D‐cine MRI. The method was evaluated using both XCAT (a computerized patient model) simulation of lung cancer patients and MRI data from a real liver cancer patient. The 3D‐MRI at every phase except end‐expiration phase was used to simulate the ground‐truth on‐board VC‐MRI at different instances, and the center‐tumor slice was selected to simulate the on‐board 2D‐cine images.

Results:

Image subtraction of ground truth with estimated on‐board VC‐MRI shows fewer differences than image subtraction of ground truth with prior image. Excellent agreement between profiles was achieved. The normalized cross correlation coefficients between the estimated and ground‐truth in the axial, coronal and sagittal views for each time step were >= 0.982, 0.905, 0.961 for XCAT data and >= 0.998, 0.911, 0.9541 for patient data. For XCAT data, the maximum‐Volume‐Percent‐Difference between ground‐truth and estimated tumor volumes was 1.6% and the maximum‐Center‐of‐Mass‐Shift was 0.9 mm.

Conclusion:

Preliminary studies demonstrated the feasibility to estimate real‐time VC‐MRI for on‐board target localization before or during radiotherapy treatments.

National Institutes of Health Grant No. R01‐CA184173; Varian Medical System
WE‐G‐BRB‐04: Leveraging Innovation to Design Future Clinical Trials
Authors: Michalski J.
Published: June 2015

Over the past 20 years the NIH has funded individual grants, program projects grants, and clinical trials which have been instrumental in advancing patient care. The ways that each grant mechanism lends itself to the different phases of translating research into clinical practice will be described. Major technological innovations, such as IMRT and proton therapy, have been advanced with R01‐type and P01‐type funding and will be discussed. Similarly, the role of program project grants in identifying and addressing key hypotheses on the potential of 3D conformal therapy, normal tissue‐guided dose escalation and motion management will be described. An overview will be provided regarding how these technological innovations have been applied to multi‐institutional NIH‐sponsored trials. Finally, the panel will discuss regarding which research questions should be funded by the NIH to inspire the next advances in radiation therapy.

Learning Objectives:

Understand the different funding mechanisms of the NIH

Learn about research advances that have led to innovation in delivery

Review achievements due to NIH‐funded program project grants in radiotherapy over the past 20 years

Understand example advances achieved with multi‐institutional clinical trials

NIH
WE‐G‐BRA‐08: Failure Modes and Effects Analysis (FMEA) for Gamma Knife Radiosurgery
Authors: Xu Y , Bhatnagar J , Bednarz G , Flickinger J , Arai Y , Vacsulka J , Feng W , Monaco E , Niranjan A , Lunsford L Dade , Huq M Saiful
Published: June 2015

Purpose:

To perform a failure modes and effects analysis (FMEA) study for Gamma Knife (GK) radiosurgery processes at our institution based on our experience with the treatment of more than 13,000 patients.

Methods:

A team consisting of medical physicists, nurses, radiation oncologists, neurosurgeons at the University of Pittsburgh Medical Center and an external physicist expert was formed for the FMEA study. A process tree and a failure mode table were created for the GK procedures using the Leksell GK Perfexion and 4C units. Three scores for the probability of occurrence (O), the severity (S), and the probability of no detection (D) for failure modes were assigned to each failure mode by each professional on a scale from 1 to 10. The risk priority number (RPN) for each failure mode was then calculated (RPN = OxSxD) as the average scores from all data sets collected.

Results:

The established process tree for GK radiosurgery consists of 10 sub‐processes and 53 steps, including a sub‐process for frame placement and 11 steps that are directly related to the frame‐based nature of the GK radiosurgery. Out of the 86 failure modes identified, 40 failure modes are GK specific, caused by the potential for inappropriate use of the radiosurgery head frame, the imaging fiducial boxes, the GK helmets and plugs, and the GammaPlan treatment planning system. The other 46 failure modes are associated with the registration, imaging, image transfer, contouring processes that are common for all radiation therapy techniques. The failure modes with the highest hazard scores are related to imperfect frame adaptor attachment, bad fiducial box assembly, overlooked target areas, inaccurate previous treatment information and excessive patient movement during MRI scan.

Conclusion:

The implementation of the FMEA approach for Gamma Knife radiosurgery enabled deeper understanding of the overall process among all professionals involved in the care of the patient and helped identify potential weaknesses in the overall process.
WE‐G‐303‐01: Physical Bases for Gold Nanoparticle Applications in Radiation Oncology and X‐Ray Imaging
Authors: Cho S.
Published: June 2015

Over the last decade, there has been a growing interest in applying nanotechnology to cancer detection, treatment, and treatment monitoring. Advances in nanotechnology have enabled the fabrication of nanoparticles from various materials with different shapes and sizes. Nanoparticles can be accumulated preferentially within tumors by either “passive targeting” through a phenomenon typically known as “enhanced permeability and retention” or “active targeting” in which nanoparticles are conjugated with antibodies or peptides directed against tumor and/or stromal markers. The tumor specificity of nanoparticles in conjunction with their unique physicochemical properties offers many novel strategies for cancer treatment and detection. For example, notable approaches in the radiation oncology setting include the use of gold nanoparticles for radiation response modulation of tumor or normal tissue and thermal ablation or hyperthermia treatment of tumors. Some of these approaches are currently being tested either on humans or on animals and, very likely, will become the clinical reality in the near future. Various computational and experimental techniques have also been applied to address unique research issues associated with nanoparticles and may become the standard tools for future investigations and clinical translations. Therefore, both clinicians and researchers may need to be properly educated about the basic principles as well as the promise of nanoparticle‐based applications with regard to the future of cancer diagnostics and therapeutics.

This symposium will familiarize the audience with the potential applications of nanoparticles in oncologic imaging and therapy using specific illustrative examples. The audience will be properly oriented by these illustrative examples to the multiple avenues for collaborative research amongst interdisciplinary teams of physicists, clinicians, engineers, chemists, and biologists in industry and academia.

Learning Objectives:

Understand the physical bases of gold nanoparticle applications for radiosensitization and x‐ray fluorescence imaging

Understand the parameters that define gold nanoparticle‐mediated radiosensitization in biological systems

Understand the potential of magnetic nanoparticle characterization of the microenvironment

Understand the various strategies for radiolabeling of nanoparticles and their applications

S.C. and S.K. acknowledge support from MD Anderson Cancer Center, NIH (R01CA155446 and P30CA16672) and DoD (W81XWH‐12‐1‐0198); J.W. acknowledges support from NIH (U54CA151662‐01); W.C. acknowledges support from the University of Wisconsin‐Madison, NIH (R01CA169365, P30CA014520, and T32CA009206), DoD (W81XWH‐11‐1‐0644 and W81XWH‐11‐1‐0648), and ACS (125246‐RSG‐13‐099‐01‐CCE).
WE‐G‐204‐03: Photon‐Counting Hexagonal Pixel Array CdTe Detector: Optimal Resampling to Square Pixels
Authors: Shrestha S , Vedantham S , Karellas A , Bellazzini R , Spandre G , Brez A
Published: June 2015

Purpose:

Detectors with hexagonal pixels require resampling to square pixels for distortion‐free display of acquired images. In this work, the presampling modulation transfer function (MTF) of a hexagonal pixel array photon‐counting CdTe detector for region‐of‐interest fluoroscopy was measured and the optimal square pixel size for resampling was determined.

Methods:

A 0.65mm thick CdTe Schottky sensor capable of concurrently acquiring up to 3 energy‐windowed images was operated in a single energy‐window mode to include ≥10 KeV photons. The detector had hexagonal pixels with apothem of 30 microns resulting in pixel spacing of 60 and 51.96 microns along the two orthogonal directions. Images of a tungsten edge test device acquired under IEC RQA5 conditions were double Hough transformed to identify the edge and numerically differentiated. The presampling MTF was determined from the finely sampled line spread function that accounted for the hexagonal sampling. The optimal square pixel size was determined in two ways; the square pixel size for which the aperture function evaluated at the Nyquist frequencies along the two orthogonal directions matched that from the hexagonal pixel aperture functions, and the square pixel size for which the mean absolute difference between the square and hexagonal aperture functions was minimized over all frequencies up to the Nyquist limit.

Results:

Evaluation of the aperture functions over the entire frequency range resulted in square pixel size of 53 microns with less than 2% difference from the hexagonal pixel. Evaluation of the aperture functions at Nyquist frequencies alone resulted in 54 microns square pixels. For the photon‐counting CdTe detector and after resampling to 53 microns square pixels using quadratic interpolation, the presampling MTF at Nyquist frequency of 9.434 cycles/mm along the two directions were 0.501 and 0.507.

Conclusion:

Hexagonal pixel array photon‐counting CdTe detector after resampling to square pixels provides high‐resolution imaging suitable for fluoroscopy.
WE‐G‐204‐08: Optimized Digital Radiographic Technique for Lost Surgical Devices/Needle Identification
Authors: Gorman A , Seabrook G , Brakken A , Dubois M , Marn C , Wilson C , Jacobson D , Liu Y
Published: June 2015

Purpose:

Small surgical devices and needles are used in many surgical procedures. Conventionally, an x‐ray film is taken to identify missing devices/needles if post procedure count is incorrect. There is no data to indicate smallest surgical devices/needles that can be identified with digital radiography (DR), and its optimized acquisition technique.

Methods:

In this study, the DR equipment used is a Canon RadPro mobile with CXDI‐70c wireless DR plate, and the same DR plate on a fixed Siemens Multix unit. Small surgical devices and needles tested include Rubber Shod, Bulldog, Fogarty Hydrogrip, and needles with sizes 3‐0 C‐T1 through 8‐0 BV175‐6. They are imaged with PMMA block phantoms with thickness of 2–8 inch, and an abdomen phantom. Various DR techniques are used. Images are reviewed on the portable x‐ray acquisition display, a clinical workstation, and a diagnostic workstation.

Results:

all small surgical devices and needles are visible in portable DR images with 2–8 inch of PMMA. However, when they are imaged with the abdomen phantom plus 2 inch of PMMA, needles smaller than 9.3 mm length can not be visualized at the optimized technique of 81 kV and 16 mAs. There is no significant difference in visualization with various techniques, or between mobile and fixed radiography unit. However, there is noticeable difference in visualizing the smallest needle on a diagnostic reading workstation compared to the acquisition display on a portable x‐ray unit.

Conclusion:

DR images should be reviewed on a diagnostic reading workstation. Using optimized DR techniques, the smallest needle that can be identified on all phantom studies is 9.3 mm. Sample DR images of various small surgical devices/needles available on diagnostic workstation for comparison may improve their identification. Further in vivo study is needed to confirm the optimized digital radiography technique for identification of lost small surgical devices and needles.
WE‐G‐207‐02: Full Sequential Projection Onto Convex Sets (FS‐POCS) for X‐Ray CT Reconstruction
Authors: Liu L , Han Y , Jin M
Published: June 2015

Purpose:

To develop an iterative reconstruction method for X‐ray CT, in which the reconstruction can quickly converge to the desired solution with much reduced projection views.

Methods:

The reconstruction is formulated as a convex feasibility problem, i.e. the solution is an intersection of three convex sets: 1) data fidelity (DF) set – the L2 norm of the difference of observed projections and those from the reconstructed image is no greater than an error bound; 2) non‐negativity of image voxels (NN) set; and 3) piecewise constant (PC) set ‐ the total variation (TV) of the reconstructed image is no greater than an upper bound. The solution can be found by applying projection onto convex sets (POCS) sequentially for these three convex sets. Specifically, the algebraic reconstruction technique and setting negative voxels as zero are used for projection onto the DF and NN sets, respectively, while the projection onto the PC set is achieved by solving a standard Rudin, Osher, and Fatemi (ROF) model. The proposed method is named as full sequential POCS (FS‐POCS), which is tested using the Shepp‐Logan phantom and the Catphan600 phantom and compared with two similar algorithms, TV‐POCS and CP‐TV.

Results:

Using the Shepp‐Logan phantom, the root mean square error (RMSE) of reconstructed images changing along with the number of iterations is used as the convergence measurement. In general, FS‐ POCS converges faster than TV‐POCS and CP‐TV, especially with fewer projection views. FS‐POCS can also achieve accurate reconstruction of cone‐beam CT of the Catphan600 phantom using only 54 views, comparable to that of FDK using 364 views.

Conclusion:

We developed an efficient iterative reconstruction for sparse‐view CT using full sequential POCS. The simulation and physical phantom data demonstrated the computational efficiency and effectiveness of FS‐POCS.
WE‐G‐207‐04: Non‐Local Total‐Variation (NLTV) Combined with Reweighted L1‐Norm for Compressed Sensing Based CT Reconstruction
Authors: Kim H , Chen J , Pouliot J
Published: June 2015

Purpose:

Compressed sensing (CS) has been used for CT (4DCT/CBCT) reconstruction with few projections to reduce dose of radiation. Total‐variation (TV) in L1‐minimization (min.) with local information is the prevalent technique in CS, while it can be prone to noise. To address the problem, this work proposes to apply a new image processing technique, called non‐local TV (NLTV), to CS based CT reconstruction, and incorporate reweighted L1‐norm into it for more precise reconstruction.

Methods:

TV minimizes intensity variations by considering two local neighboring voxels, which can be prone to noise, possibly damaging the reconstructed CT image. NLTV, contrarily, utilizes more global information by computing a weight function of current voxel relative to surrounding search area. In fact, it might be challenging to obtain an optimal solution due to difficulty in defining the weight function with appropriate parameters. Introducing reweighted L1‐min., designed for approximation to ideal L0‐min., can reduce the dependence on defining the weight function, therefore improving accuracy of the solution. This work implemented the NLTV combined with reweighted L1‐min. by Split Bregman Iterative method. For evaluation, a noisy digital phantom and a pelvic CT images are employed to compare the quality of images reconstructed by TV, NLTV and reweighted NLTV.

Results:

In both cases, conventional and reweighted NLTV outperform TV min. in signal‐to‐noise ratio (SNR) and root‐mean squared errors of the reconstructed images. Relative to conventional NLTV, NLTV with reweighted L1‐norm was able to slightly improve SNR, while greatly increasing the contrast between tissues due to additional iterative reweighting process.

Conclusion:

NLTV min. can provide more precise compressed sensing based CT image reconstruction by incorporating the reweighted L1‐norm, while maintaining greater robustness to the noise effect than TV min.
WE‐G‐207‐05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis
Authors: Lee J , Nishikawa R , Reiser I , Boone J
Published: June 2015

Purpose:

Segmentation quality can affect quantitative image feature analysis. The objective of this study is to examine the relationship between computed tomography (CT) image quality, segmentation performance, and quantitative image feature analysis.

Methods:

A total of 90 pathology proven breast lesions in 87 dedicated breast CT images were considered. An iterative image reconstruction (IIR) algorithm was used to obtain CT images with different quality. With different combinations of 4 variables in the algorithm, this study obtained a total of 28 different qualities of CT images. Two imaging tasks/objectives were considered: 1) segmentation and 2) classification of the lesion as benign or malignant. Twenty‐three image features were extracted after segmentation using a semi‐automated algorithm and 5 of them were selected via a feature selection technique. Logistic regression was trained and tested using leave‐one‐out‐cross‐validation and its area under the ROC curve (AUC) was recorded. The standard deviation of a homogeneous portion and the gradient of a parenchymal portion of an example breast were used as an estimate of image noise and sharpness. The DICE coefficient was computed using a radiologist's drawing on the lesion. Mean DICE and AUC were used as performance metrics for each of the 28 reconstructions. The relationship between segmentation and classification performance under different reconstructions were compared. Distributions (median, 95% confidence interval) of DICE and AUC for each reconstruction were also compared.

Results:

Moderate correlation (Pearson's rho = 0.43, p‐value = 0.02) between DICE and AUC values was found. However, the variation between DICE and AUC values for each reconstruction increased as the image sharpness increased. There was a combination of IIR parameters that resulted in the best segmentation with the worst classification performance.

Conclusion:

There are certain images that yield better segmentation or classification performance. The best segmentation Result does not necessarily lead to the best classification Result.

This work has been supported in part by grants from the NIH R21‐EB015053. R Nishikawa is receives royalties form Hologic, Inc.
WE‐G‐207‐07: Iterative CT Shading Correction Method with No Prior Information
Authors: Wu P , Mao T , Xie S , Sheng K , Niu T
Published: June 2015

Purpose:

Shading artifacts are caused by scatter contamination, beam hardening effects and other non‐ideal imaging condition. Our Purpose is to propose a novel and general correction framework to eliminate low‐frequency shading artifacts in CT imaging (e.g., cone‐beam CT, low‐kVp CT) without relying on prior information.

Methods:

Our method applies general knowledge of the relatively uniform CT number distribution in one tissue component. Image segmentation is applied to construct template image where each structure is filled with the same CT number of that specific tissue. By subtracting the ideal template from CT image, the residual from various error sources are generated. Since the forward projection is an integration process, the non‐continuous low‐frequency shading artifacts in the image become continuous and low‐frequency signals in the line integral. Residual image is thus forward projected and its line integral is filtered using Savitzky‐Golay filter to estimate the error. A compensation map is reconstructed on the error using standard FDK algorithm and added to the original image to obtain the shading corrected one. Since the segmentation is not accurate on shaded CT image, the proposed scheme is iterated until the variation of residual image is minimized.

Results:

The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT angiography scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4.

Conclusion:

We propose an effective iterative algorithm for shading correction in CT imaging. Being different from existing algorithms, our method is only assisted by general anatomical and physical information in CT imaging without relying on prior knowledge. Our method is thus practical and attractive as a general solution to CT shading correction.

This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.
WE‐G‐207‐09: A Practical Bowtie Ring Artifact Correction Algorithm for Cone‐Beam CT
Authors: Wu P , Mao T , Xie S , Sheng K , Niu T , Niu T
Published: June 2015

Purpose:

Shaded ring artifact in cone‐beam CT (CBCT) is caused by scatter contamination from bowtie‐modulated primary beam and presents a unique ring pattern in CBCT image. Previous shading correction methods, which suppress the artifact as conventional scatter correction in projection domain, are complicated due to the non‐trivial scatter estimation. In this work, we propose a practical and readily implementable algorithm to correct for the severe shaded ring in CBCT without relying on prior information and directly in image domain.

Methods:

Due to the correlation between the ring pattern and bowtie modulator, an initial bowtie mask was reconstructed from bowtie‐modulated air‐scan projections as if they were acquired from a flat‐field exposure penetrating the bowtie modulator. The shape of the bowtie mask matches well with that of the shaded ring in CBCT, while its intensity needs to be scaled to fully compensate for the shading ring. To find a correct scaling factor, we start from the anatomical knowledge that the same tissue has comparable CT number. This knowledge indicates a sharp peak in histogram of that specific tissue. One way to achieve this goal is to maximize the peak value of the histogram of that tissue. The above concept is formulated as a mathematical optimization problem which is solved using a standard Simplex method. The shaded ring artifact in CBCT is finally corrected for by adding a scaled bowtie mask.

Results:

The proposed method is evaluated on one pelvis patient. Severe shaded ring artifact is greatly suppressed. Our method reduces the CT number error from >200 HU to be ∼50 HU, and increases the spatial uniformity by 1.3 times.

Conclusion:

We propose a practical image‐domain algorithm for shaded ring artifact correction in CBCT. It is computationally efficient and does not rely on prior knowledge. It is thus attractive for clinical use.

This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.
WE‐G‐201‐02: Image Quality Characteristics of Handheld Medical Image Viewing Devices
Authors: Badano A.
Published: June 2015

Many health care organizations are adopting mobile applications for patient care. These tools can provide the opportunity for improvements in timely access to patient images. With new possibilities for patient image viewing, it is sensible to take a closer look at what handheld devices might provide and how they are being used.

Three speakers: a radiologist, an imaging research scientist, and a clinical medical physicist provide input into different aspects of image viewing on handheld devices.

1. Patrick Luetmer, M.D., Radiologist

Provides a radiologist's perspective of how mobile technologies best fit into patient care workflows, including how patient image viewing is done differently on a mobile platform compared to a PACS workstation and what types of decisions are being made from handheld devices.

2. Aldo Badano, Ph.D., Imaging Research Scientist

Provides an overview of technological properties of handheld devices and describes how image viewing with handheld devices impacts the image information that is visible under ideal and clinical conditions.

3. Dr. Alisa Walz‐Flannigan, Ph.D., Clinical Medical Physicist

Provides an overview of different strategies for setup and quality control as relevant for handheld devices.

This session is related to the ongoing work of Task Group No. 260 “Considerations for the Use of Handheld Devices for Viewing Medical Images”.

Learning Objectives:

To understand how mobile devices for image viewing are being used to enhance patient care

To understand how technological properties of various mobile devices combine with device usage to impact the information visible in a medical image

To gain awareness of different options for configuring and testing handheld devices for medical image viewing

Dr. Aldo Badano has the following: Cooperative Research and Development Agreement (CRADA #123‐07) with BARCO.
WE‐G‐201‐04: Panel Discussion
Authors: Walz‐Flannigan A.
Published: June 2015

Many health care organizations are adopting mobile applications for patient care. These tools can provide the opportunity for improvements in timely access to patient images. With new possibilities for patient image viewing, it is sensible to take a closer look at what handheld devices might provide and how they are being used.

Three speakers: a radiologist, an imaging research scientist, and a clinical medical physicist provide input into different aspects of image viewing on handheld devices.

1. Patrick Luetmer, M.D., Radiologist

Provides a radiologist's perspective of how mobile technologies best fit into patient care workflows, including how patient image viewing is done differently on a mobile platform compared to a PACS workstation and what types of decisions are being made from handheld devices.

2. Aldo Badano, Ph.D., Imaging Research Scientist

Provides an overview of technological properties of handheld devices and describes how image viewing with handheld devices impacts the image information that is visible under ideal and clinical conditions.

3. Dr. Alisa Walz‐Flannigan, Ph.D., Clinical Medical Physicist

Provides an overview of different strategies for setup and quality control as relevant for handheld devices.

This session is related to the ongoing work of Task Group No. 260 “Considerations for the Use of Handheld Devices for Viewing Medical Images”.

Learning Objectives:

To understand how mobile devices for image viewing are being used to enhance patient care

To understand how technological properties of various mobile devices combine with device usage to impact the information visible in a medical image

To gain awareness of different options for configuring and testing handheld devices for medical image viewing

Dr. Aldo Badano has the following: Cooperative Research and Development Agreement (CRADA #123‐07) with BARCO.
WE‐G‐210‐03: Mammographically Configured, Automated Ultrasound: Methods and Potential Applications
Authors: Carson P.
Published: June 2015

This session focuses on recent developments in breast ultrasound imaging, covering clinical practice as well as clinical and pre‐clinical research. Current status of ultrasound screening will be reviewed, followed by discussions of emerging technologies at various stages of regulatory and technical development. The session strives to provide the attendee with a view of a continuum of imaging advances starting with the present and spanning the near and long term future.

Learning Objectives:

Understand current state of ultrasound screening for breast cancer

Learn about current availability of whole breast ultrasound

Appreciate the current barriers to stronger adoption of screening ultrasound

Learn about attempts to drive adoption of screening ultrasound (e.g. breast density laws)

Learn about ultrasound tomography as an emerging technique for breast imaging

Learn about the regulatory status of emerging techniques such as ultrasound tomography

Learn about the developmental status of combined 3‐D ultrasound and Mammography systems

Learn about photo‐acoustic imaging and its potential future role in breast imaging
WE‐G‐210‐04: Photoacoustic Computed Tomography with Applications to Breast Imaging
Authors: Anastasio M.
Published: June 2015

This session focuses on recent developments in breast ultrasound imaging, covering clinical practice as well as clinical and pre‐clinical research. Current status of ultrasound screening will be reviewed, followed by discussions of emerging technologies at various stages of regulatory and technical development. The session strives to provide the attendee with a view of a continuum of imaging advances starting with the present and spanning the near and long term future.

Learning Objectives:

Understand current state of ultrasound screening for breast cancer

Learn about current availability of whole breast ultrasound

Appreciate the current barriers to stronger adoption of screening ultrasound

Learn about attempts to drive adoption of screening ultrasound (e.g. breast density laws)

Learn about ultrasound tomography as an emerging technique for breast imaging

Learn about the regulatory status of emerging techniques such as ultrasound tomography

Learn about the developmental status of combined 3‐D ultrasound and Mammography systems

Learn about photo‐acoustic imaging and its potential future role in breast imaging
TH‐AB‐304‐01: Dose‐Volume Relations for Late Rectal Bleeding in 1001 Patients From Five Prostate Cancer Cohorts
Authors: Thor M , Jackson A , Steineck G , Zelefsky M , Karlsdottir A , Hoyer M , Liu M , Nasser N , Petersen S , Moiseenko V , Deasy J
Published: June 2015

Purpose:

Normal tissue complications following radiotherapy (RT) are commonly estimated from single institutions, limiting generalizability of critical dose‐volume thresholds. In this study we use data from five cohorts/institutions to explore dose‐volume relations for late rectal bleeding (LRB) after RT for prostate cancer.

Methods:

The investigated cohorts included 1001 patients treated with various RT techniques for prostate cancer (922 3DCRT, 211 image‐guided RT, and 79 intensity‐modulated RT patients) to 70–86 Gy@2Gy/fraction in 1991–2007. The rectum extended from the recto‐sigmoid flexure to the anal canal, and the median (range) follow‐up for LRB was 58 (4–259) months. Rectal cross sectional area, length, and volume were compared between LRB and non‐ LRB patients (Mann‐Whitney‐test). The ability of dose metrics to predict moderate‐to‐severe LRB (prevalence: 14%) was investigated on univariate analysis, UVA, (Spearman's Rho (Rs) and p‐values calculated as medians from 10 0000 Bootstrap‐resamples). Dose‐volume metrics significantly predicting LRB on UVA (p≤0.05) were considered for multivariate logistic regression, MVA, following removal of correlated metrics (Pearson's correlation, Pr ≥0.85).

Results:

Patients with LRB had significantly (p<0.01) smaller and shorter rectums than non‐LRB patients (48 vs. 68 cm3 and 6 vs. 7 cm, respectively). On UVA, the relative volumes receiving 5–20 Gy, V5–V20 (Rs=0.05–0.07), V40–V65 (Rs=0.05–0.11), the minimum dose to the hottest 20–55% volumes, D20‐D55 and D100 (Rs=0.06–0.09), and mean dose (Rs=0.05) significantly (p<0.03) predicted LRB. Within a range of correlated dose metrics (Pr=0.86–0.98), the metric showing the strongest relationship with LRB was considered for MVA together with the other dose metrics, length and volume. The length, V50, mean dose, and D35% remained significant (p<0.01) predictors for LRB on MVA, MVALRB=5.2*V50+6.1*D35+9.2*mean dose+0.2*length.

Conclusion:

Our findings (>1000 patients) suggest that shorter rectums and intermediate to high doses predict LRB. The wide range of prescribed doses and treatment techniques applied support generalizability of our results to other prostate cancer cohorts.