bluuebunny/crossref_metadata_2025_split huggingface dataset:
WE‐F‐201‐00: Practical Guidelines for Commissioning Advanced Brachytherapy Dose Calculation Algorithms
Authors: Mourtada Firas , Richardson Susan 
Published: June 2015

With the recent introduction of heterogeneity correction algorithms for brachytherapy, the AAPM community is still unclear on how to commission and implement these into clinical practice. The recently‐published AAPM TG‐186 report discusses important issues for clinical implementation of these algorithms. A charge of the AAPM‐ESTRO‐ABG Working Group on MBDCA in Brachytherapy (WGMBDCA) is the development of a set of well‐defined test case plans, available as references in the software commissioning process to be performed by clinical end‐users. In this practical medical physics course, specific examples on how to perform the commissioning process are presented, as well as descriptions of the clinical impact from recent literature reporting comparisons of TG‐43 and heterogeneity‐based dosimetry.Learning Objectives:

Identify key clinical applications needing advanced dose calculation in brachytherapy.
Review TG‐186 and WGMBDCA guidelines, commission process, and dosimetry benchmarks.
Evaluate clinical cases using commercially available systems and compare to TG‐43 dosimetry
WE‐F‐201‐01: Identify Key Clinical Applications Needing Advanced Dose Calculation in Brachytherapy
Authors: Fulkerson R. 
Published: June 2015

With the recent introduction of heterogeneity correction algorithms for brachytherapy, the AAPM community is still unclear on how to commission and implement these into clinical practice. The recently‐published AAPM TG‐186 report discusses important issues for clinical implementation of these algorithms. A charge of the AAPM‐ESTRO‐ABG Working Group on MBDCA in Brachytherapy (WGMBDCA) is the development of a set of well‐defined test case plans, available as references in the software commissioning process to be performed by clinical end‐users. In this practical medical physics course, specific examples on how to perform the commissioning process are presented, as well as descriptions of the clinical impact from recent literature reporting comparisons of TG‐43 and heterogeneity‐based dosimetry.Learning Objectives:

Identify key clinical applications needing advanced dose calculation in brachytherapy.
Review TG‐186 and WGMBDCA guidelines, commission process, and dosimetry benchmarks.
Evaluate clinical cases using commercially available systems and compare to TG‐43 dosimetry
WE‐F‐201‐02: Review TG‐186 and WGMBDCA Guidelines, Commission Process, and Dosimetry Benchmarks
Authors: Rivard M. 
Published: June 2015

With the recent introduction of heterogeneity correction algorithms for brachytherapy, the AAPM community is still unclear on how to commission and implement these into clinical practice. The recently‐published AAPM TG‐186 report discusses important issues for clinical implementation of these algorithms. A charge of the AAPM‐ESTRO‐ABG Working Group on MBDCA in Brachytherapy (WGMBDCA) is the development of a set of well‐defined test case plans, available as references in the software commissioning process to be performed by clinical end‐users. In this practical medical physics course, specific examples on how to perform the commissioning process are presented, as well as descriptions of the clinical impact from recent literature reporting comparisons of TG‐43 and heterogeneity‐based dosimetry.Learning Objectives:

Identify key clinical applications needing advanced dose calculation in brachytherapy.
Review TG‐186 and WGMBDCA guidelines, commission process, and dosimetry benchmarks.
Evaluate clinical cases using commercially available systems and compare to TG‐43 dosimetry
WE‐G‐304‐03: My Personal Experience
Authors: Curran B. 
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 asHow 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‐01: A Data‐Driven 4D‐MRI Motion Model to Estimate Full Field‐Of‐View Abdominal Motion From 2D Image Navigators During MR‐Linac Treatment
Authors: Stemkens B , Tijssen RHN , de Senneville B Denis , Lagendijk JJW , van den Berg CAT 
Published: June 2015

Purpose:To estimate full field‐of‐view abdominal respiratory motion from fast 2D image navigators using a 4D‐MRI based motion model. This will allow for radiation dose accumulation mapping during MR‐Linac treatment.Methods:Experiments were conducted on a Philips Ingenia 1.5T MRI. First, a retrospectively ordered 4D‐MRI was constructed using 3D transient‐bSSFP with radial in‐plane sampling. Motion fields were calculated through 3D non‐rigid registration. From these motion fields a PCA‐based abdominal motion model was constructed and used to warp a 3D reference volume to fast 2D cine‐MR image navigators that can be used for real‐time tracking. To test this procedure, a time‐series consisting of two interleaved orthogonal slices (sagittal and coronal), positioned on the pancreas or kidneys, were acquired for 1m38s (dynamic scan‐time=0.196ms), during normal, shallow, or deep breathing. The coronal slices were used to update the optimal weights for the first two PCA components, in order to warp the 3D reference image and construct a dynamic 4D‐MRI time‐series. The interleaved sagittal slices served as an independent measure to test the model's accuracy and fit. Spatial maps of the root‐mean‐squared error (RMSE) and histograms of the motion differences within the pancreas and kidneys were used to evaluate the method.Results:Cranio‐caudal motion was accurately calculated within the pancreas using the model for normal and shallow breathing with an RMSE of 1.6mm and 1.5mm and a histogram median and standard deviation below 0.2 and 1.7mm, respectively. For deep‐breathing an underestimation of the inhale amplitude was observed (RMSE=4.1mm). Respiratory‐induced antero‐posterior and lateral motion were correctly mapped (RMSE=0.6/0.5mm). Kidney motion demonstrated good motion estimation with RMSE‐values of 0.95 and 2.4mm for the right and left kidney, respectively.Conclusion:We have demonstrated a method that can calculate dynamic 3D abdominal motion in a large volume, while acquiring real‐time cine‐MR images for MR‐guided radiotherapy.
WE‐G‐BRD‐02: Characterizing Information Loss in a Sparse‐Sampling‐Based Dynamic MRI Sequence (k‐T BLAST) for Lung Motion Monitoring
Authors: Arai T , Nofiele J , Sawant A 
Published: June 2015

Purpose:Rapid MRI is an attractive, non‐ionizing tool for soft‐tissue‐based monitoring of respiratory motion in thoracic and abdominal radiotherapy. One big challenge is to achieve high temporal resolution while maintaining adequate spatial resolution. K‐t BLAST, sparse‐sampling and reconstruction sequence based on a‐priori information represents a potential solution. In this work, we investigated how much “true” motion information is lost as a‐priori information is progressively added for faster imaging.Methods:Lung tumor motions in superior‐inferior direction obtained from ten individuals were replayed into an in‐house, MRI‐compatible, programmable motion platform (50Hz refresh and 100microns precision). Six water‐filled 1.5ml tubes were placed on it as fiducial markers. Dynamic marker motion within a coronal slice (FOV: 32×32cm2, resolution: 0.67×0.67mm2, slice‐thickness: 5mm) was collected on 3.0T body scanner (Ingenia, Philips). Balanced‐FFE (TE/TR: 1.3ms/2.5ms, flip‐angle: 40degrees) was used in conjunction with k‐t BLAST. Each motion was repeated four times as four k‐t acceleration factors 1, 2, 5, and 16 (corresponding frame rates were 2.5, 4.7, 9.8, and 19.1Hz, respectively) were compared. For each image set, one average motion trajectory was computed from six marker displacements. Root mean square error (RMS) was used as a metric of spatial accuracy where measured trajectories were compared to original data.Results:Tumor motion was approximately 10mm. The mean(standard deviation) of respiratory rates over ten patients was 0.28(0.06)Hz. Cumulative distributions of tumor motion frequency spectra (0–25Hz) obtained from the patients showed that 90% of motion fell on 3.88Hz or less. Therefore, the frame rate must be a double or higher for accurate monitoring. The RMS errors over patients for k‐t factors of 1, 2, 5, and 16 were.10(.04),.17(.04), .21(.06) and.26(.06)mm, respectively.Conclusions:K‐t factor of 5 or higher can cover the high frequency component of tumor respiratory motion, while the estimated error of spatial accuracy was approximately.2mm.
WE‐G‐BRD‐03: Real‐Time Tumor Motion Tracking in Low Field Cine‐MR Images
Authors: Wan H , Pless R , Parikh P 
Published: June 2015

Purpose:ViewRay's MRIdian system acquires cine‐MR images during treatment, allowing for real‐time visualization of the tumor without additional dose. We propose a novel method for tracking the tumor target on these cine‐MR images in real‐time.Methods:9 patients with mobile abdominal tumors (3 stomach, 1 pancreas, 1 adrenal, 2 mesenteric, 2 peritoneal) were imaged on ViewRay (0.3T, open‐bore; TrueFISP). Sagittal slice cine‐MR images (3.5×3.5mm pixels) were acquired at 4 frames per second. A 25‐second training period was used to collect 100 images during normal breathing. PCA was used to bin the images using the first 2 eigenvalues. Manual contouring of the target was performed on the first eigenimage. The mean eigenvalues in each bin were used to reconstruct 15 images, on which template matching was used to locate the target. A linear fit of the pixel locations was used to create the motion model. For each subsequently acquired image, the 2‐component PCA model was inverted and the values plugged into the motion model to get the corresponding pixel location. Finally, this location and the user‐drawn contour were used as the initialization for an active contouring algorithm to refine the edges of the tracked target. 100 images for each patient were manually contoured and used as the gold standard for comparison using the Dice similarity coefficient (DSC) and the modified Hausdorff distance (MHD).Results:The mean DSC is 0.87±0.09 and MHD is 2.6±0.9mm, which is less than the pixel size. The algorithm takes 100ms per image using Matlab, and is therefore more than fast enough for real‐time use.Conclusion:We have developed a robust method for real‐time tumor motion tracking in low‐resolution, low‐field cine‐MR images. We foresee our method being used for automated gating and dosimetric measurement purposes with the ViewRay system.
WE‐G‐BRD‐04: BEST IN PHYSICS (JOINT IMAGING‐THERAPY): An Integrated Model‐Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy
Authors: Chen H , Dolly S , Victoria J , Anastasio M , Ruan S , Low D , Li H , Wooten H , Dempsey J , Gay H , Mutic S , Thorstad W , Li H 
Published: June 2015

Purpose:In‐treatment dynamic cine images, provided by the first commercially available MRI‐guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model‐based approach to automatically delineate and analyze moving structures from on‐board cine images.Methods:The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target‐to‐be‐tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face‐jaw, and face‐jaw‐palate) was first built from a set of manually delineated shapes using principal component analysis. An integrated model‐fitting algorithm was then employed to align the statistical shapes to the first to‐be‐detected cine frame, and multi‐feature level‐set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach.Results:The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency.Conclusion:We proposed the integrated computational approach, which for the first time allows to automatically identify the H&N upper airway and quantify in‐treatment H&N internal motion in real‐time. This approach can be applied to track other structures’ motion, and provide guidance on patient‐specific prediction of intra‐/inter‐fractional structure displacements.
WE‐G‐BRD‐07: Automated MR Image Standardization and Auto‐Contouring Strategy for MRI‐Based Adaptive Brachytherapy for Cervix Cancer
Authors: Saleh H Al , Erickson B , Paulson E 
Published: June 2015

Purpose:MRI‐based adaptive brachytherapy (ABT) is an emerging treatment modality for patients with gynecological tumors. However, MR image intensity non‐uniformities (IINU) can vary from fraction to fraction, complicating image interpretation and auto‐contouring accuracy. We demonstrate here an automated MR image standardization and auto‐contouring strategy for MRI‐based ABT of cervix cancer.Methods:MR image standardization consisted of: 1) IINU correction using the MNI N3 algorithm, 2) noise filtering using anisotropic diffusion, and 3) signal intensity normalization using the volumetric median. This post‐processing chain was implemented as a series of custom Matlab and Java extensions in MIM (v6.4.5, MIM Software) and was applied to 3D T2 SPACE images of six patients undergoing MRI‐based ABT at 3T. Coefficients of variation (CV=σ/µ) were calculated for both original and standardized images and compared using Mann‐Whitney tests. Patient‐specific cumulative MR atlases of bladder, rectum, and sigmoid contours were constructed throughout ABT, using original and standardized MR images from all previous ABT fractions. Auto‐contouring was performed in MIM two ways: 1) best‐match of one atlas image to the daily MR image, 2) multi‐match of all previous fraction atlas images to the daily MR image. Dice's Similarity Coefficients (DSCs) were calculated for auto‐generated contours relative to reference contours for both original and standardized MR images and compared using Mann‐Whitney tests.Results:Significant improvements in CV were detected following MR image standardization (p=0.0043), demonstrating an improvement in MR image uniformity. DSCs consistently increased for auto‐contoured bladder, rectum, and sigmoid following MR image standardization, with the highest DSCs detected when the combination of MR image standardization and multi‐match cumulative atlas‐based auto‐contouring was utilized.Conclusion:MR image standardization significantly improves MR image uniformity. The combination of MR image standardization and multi‐match cumulative atlas‐based auto‐contouring produced the highest DSCs and is a promising strategy for MRI‐based ABT for cervix cancer.
WE‐G‐BRB‐00: NIH‐Funded Research: Instrumental in the Pursuit of Clinical Trials and Technological Innovations
Authors: Moran Jean 
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‐BRB‐01: The Importance of NIH Funding in Innovation in Radiation Therapy
Authors: Deye 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‐BRB‐02: The Role of Program Project Grants in Study of 3D Conformal Therapy, Dose Escalation and Motion Management
Authors: Fraass B. 
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‐303‐03: Advances in in Vivo Magnetic NanoparticleSensing
Authors: Weaver J. 
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).