bluuebunny/crossref_metadata_2025 huggingface dataset:
SU‐C‐204‐03: DFT Calculations of the Stability of DOTA‐Based‐Radiopharmaceuticals
Authors: Khabibullin A.R. , Karolak A. , Budzevich M.M. , Woods L.M. , Martinez M.V. , McLaughlin M.L. , Morse D.L.
Published: July 2016

Purpose:

Application of the density function theory (DFT) to investigate the structural stability of complexes applied in cancer therapy consisting of the 1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetraacetic acid (DOTA) chelated to Ac225, Fr221, At217, Bi213, and Gd68 radio‐nuclei.

Methods:

The possibility to deliver a toxic payload directly to tumor cells is a highly desirable aim in targeted alpha particle therapy. The estimation of bond stability between radioactive atoms and the DOTA chelating agent is the key element in understanding the foundations of this delivery process. Thus, we adapted the Vienna Ab‐initio Simulation Package (VASP) with the projector‐augmented wave method and a plane‐wave basis set in order to study the stability and electronic properties of DOTA ligand chelated to radioactive isotopes. In order to count for the relativistic effect of radioactive isotopes we included Spin‐Orbit Coupling (SOC) in the DFT calculations. Five DOTA complex structures were represented as unit cells, each containing 58 atoms. The energy optimization was performed for all structures prior to calculations of electronic properties. Binding energies, electron localization functions as well as bond lengths between atoms were estimated.

Results:

Calculated binding energies for DOTA‐radioactive atom systems were −17.792, −5.784, −8.872, −13.305, −18.467 eV for Ac, Fr, At, Bi and Gd complexes respectively. The displacements of isotopes in DOTA cages were estimated from the variations in bond lengths, which were within 2.32–3.75 angstroms. The detailed representation of chemical bonding in all complexes was obtained with the Electron Localization Function (ELF).

Conclusion:

DOTA‐Gd, DOTA‐Ac and DOTA‐Bi were the most stable structures in the group. Inclusion of SOC had a significant role in the improvement of DFT calculation accuracy for heavy radioactive atoms. Our approach is found to be proper for the investigation of structures with DOTA‐based‐radiopharmaceuticals and will enhance our understanding of processes occurring at subatomic levels.
SU‐C‐204‐04: Irradiation of Human Cell Lines Using Various Ions
Authors: Lin Y , Tessa C , Rusek A , McMahon S , Kaminuma T , Held K
Published: July 2016

Purpose:

The purpose of this study is to investigate and quantify the biological effects of ion radiation using several human cell lines. We aim to answer the question of whether carbon ion the most ideal ion species for heavy ion radiotherapy.

Methods:

The cells were irradiated at different positions along the pristine Bragg peak of several ions with different atomic number. The biological effectiveness was evaluated using the clonogenic cell survival assay. Irradiation of three human lung cancer cell lines and a fibroblast cell line were undertaken using the charged particle beam at the NASA Space Radiation Laboratory at Brookhaven National Lab. Four mono‐energetic ion beams (carbon, oxygen, helium and lithium) were used to irradiate the cells. Water or media‐filled T25 flasks were lined up along the beam line so that the cell‐containing surfaces of the flasks were placed at a specific depth along the pristine Bragg curve. Four depths along the curve, representing entrance point, rising peak, peak and distal fall off, were selected to determine biological effectiveness. Gaf‐chromic films were placed between the flasks to monitor the irradiation as soon as it was finished.

Results:

For all ion radiations, the maximum cell killing effect occurs at either peak or distal fall off, depending on the cell lines. For instance, for the fibroblast cell line AGO1522, RBEs of 1.4, 1.2, 1.4 and 1.9 were observed at the Bragg peak for Helium, Lithium, Carbon and Oxygen ions. Comparing positions, RBEs of 0.9, 1.2, 1.4 and 1.8 were observed for carbon irradiation of AGO‐1522 cells positions corresponding to entrance, rising peak, peak and distal fall off.

Conclusion:

RBE values differ with position in the Bragg peak, ion species and cell line. Ions other than carbon may prove more effective in certain irradiation conditions and may contribute to optimized heavy ion therapy.
SU‐C‐201‐01: Core/shell and Multishell Colloidal Quantum Dots Nanodosimeters Behaviour Under Repeated MV and KV Irradiations
Authors: Delage M , Cloutier E , Lecavalier M , Lariviere D , Allen C , Beaulieu L
Published: July 2016

Purpose:

This study intends to characterize the energy dependence of the effect of radiation damage on CdSe multi‐shell (MS) (CdS/CdZnS/ZnS) and CdSe core/shell (CS)(ZnS) cQDs. It also aims to investigate irregularities resulting of pauses between subsequent irradiations.

Methods:

Radioluminescence (RL) measurements were performed with a CCD camera as dose was cumulated by the cQDs (up to 10 kGy), for beam energies 120 kVp, 220 kVp and 6 MV. Repeated expositions of 1999 MU were cumulated. Pauses between subsequent irradiations were varied from 2 to 50 minutes. cQDs photoluminescence (PL) and RL spectral stability was tracked by quantifying the position and FWHM of the luminescence peak.

Results:

Both types of cQDs showed a clear energy dependence of the RL signal decrease between the kV and the MV beams. For 1.2 kGy of dose cumulated, MS cQDs had 92% of the initial signal left at 6 MV compared to 98% at 120 kVp. The same was observed for CS cQDs: 87% at 6 MV vs 94% at 120 kVp. MS cQDs were found to have a systematic (though small, ∼1%) RL intensity recovery for pauses of 15 minutes or more, while CS cQDs maintain a stable loss regardless of the pause duration. PL and RL spectral measurements revealed a good stability (< 1% variation of the peak position and FWHM) for both types of cQDs.

Conclusion:

In all, both MS and CS cQDs have a sufficient resistance to large doses of radiation for standard radiation therapy and imaging. Since this resistance is better for lower energy, the utilization of cQDs could be optimized for low energy applications (e.g. theragnostic applications for small animal studies and others). Finally, the ionizing radiation damage mechanisms for this new type of nano‐scintillator still have to be identified properly.
SU‐C‐BRC‐01: A Monte Carlo Study of Out‐Of‐Field Doses From Cobalt‐60 Teletherapy Units Intended for Historical Correlations of Dose to Normal Tissue
Authors: Petroccia H , Olguin E , Culberson W , Bednarz B , Mendenhall N , Bolch W
Published: July 2016

Purpose:

Innovations in radiotherapy treatments, such as dynamic IMRT, VMAT, and SBRT/SRS, result in larger proportions of low‐dose regions where normal tissues are exposed to low doses levels. Low doses of radiation have been linked to secondary cancers and cardiac toxicities. The AAPM TG Committee No.158 entitled, ‘Measurements and Calculations of Doses outside the Treatment Volume from External‐Beam Radiation Therapy’, has been formed to review the dosimetry of non‐target and out‐of‐field exposures using experimental and computational approaches. Studies on historical patients can provide comprehensive information about secondary effects from out‐of‐field doses when combined with long‐term patient follow‐up, thus providing significant insight into projecting future outcomes of patients undergoing modern‐day treatments.

Methods:

We present a Monte Carlo model of a Theratron‐1000 cobalt‐60 teletherapy unit, which historically treated patients at the University of Florida, as a means of determining doses located outside the primary beam. Experimental data for a similar Theratron‐1000 was obtained at the University of Wisconsin's ADCL to benchmark the model for out‐of‐field dosimetry. An Exradin A12 ion chamber and TLD100 chips were used to measure doses in an extended water phantom to 60 cm outside the primary field at 5 and 10 cm depths.

Results:

Comparison between simulated and experimental measurements of PDDs and lateral profiles show good agreement for in‐field and out‐of‐field doses. At 10 cm away from the edge of a 6×6, 10×10, and 20×20 cm2 field, relative out‐of‐field doses were measured in the range of 0.5% to 3% of the dose measured at 5 cm depth along the CAX.

Conclusion:

Out‐of‐field doses can be as high as 90 to 180 cGy assuming historical prescription doses of 30 to 60 Gy and should be considered when correlating late effects with normal tissue dose.
SU‐C‐BRC‐04: Efficient Dose Calculation Algorithm for FFF IMRT with a Simplified Bivariate Gaussian Source Model
Authors: Li F , Park J , Barraclough B , Lu B , Li J , Liu C , Yan G
Published: July 2016

Purpose:

To develop an efficient and accurate independent dose calculation algorithm with a simplified analytical source model for the quality assurance and safe delivery of Flattening Filter Free (FFF)‐IMRT on an Elekta Versa HD.

Methods:

The source model consisted of a point source and a 2D bivariate Gaussian source, respectively modeling the primary photons and the combined effect of head scatter, monitor chamber backscatter and collimator exchange effect. The in‐air fluence was firstly calculated by back‐projecting the edges of beam defining devices onto the source plane and integrating the visible source distribution. The effect of the rounded MLC leaf end, tongue‐and‐groove and interleaf transmission was taken into account in the back‐projection. The in‐air fluence was then modified with a fourth degree polynomial modeling the cone‐shaped dose distribution of FFF beams. Planar dose distribution was obtained by convolving the in‐air fluence with a dose deposition kernel (DDK) consisting of the sum of three 2D Gaussian functions. The parameters of the source model and the DDK were commissioned using measured in‐air output factors (Sc) and cross beam profiles, respectively. A novel method was used to eliminate the volume averaging effect of ion chambers in determining the DDK. Planar dose distributions of five head‐and‐neck FFF‐IMRT plans were calculated and compared against measurements performed with a 2D diode array (MapCHECK™) to validate the accuracy of the algorithm.

Results:

The proposed source model predicted Sc for both 6MV and 10MV with an accuracy better than 0.1%. With a stringent gamma criterion (2%/2mm/local difference), the passing rate of the FFF‐IMRT dose calculation was 97.2±2.6%.

Conclusion:

The removal of the flattening filter represents a simplification of the head structure which allows the use of a simpler source model for very accurate dose calculation. The proposed algorithm offers an effective way to ensure the safe delivery of FFF‐IMRT.
SU‐C‐BRB‐05: Determining the Adequacy of Auto‐Contouring Via Probabilistic Assessment of Ensuing Treatment Plan Metrics in Comparison with Manual Contours
Authors: Nourzadeh H , Watkins W , Siebers J , Ahmad M
Published: July 2016

Purpose:

To determine if auto‐contour and manual‐contour—based plans differ when evaluated with respect to probabilistic coverage metrics and biological model endpoints for prostate IMRT.

Methods:

Manual and auto‐contours were created for 149 CT image sets acquired from 16 unique prostate patients. A single physician manually contoured all images. Auto‐contouring was completed utilizing Pinnacle's Smart Probabilistic Image Contouring Engine (SPICE). For each CT, three different 78 Gy/39 fraction 7‐beam IMRT plans are created; PD with drawn ROIs, PAS with auto‐contoured ROIs, and PM with auto‐contoured OARs with the manually drawn target. For each plan, 1000 virtual treatment simulations with different sampled systematic errors for each simulation and a different sampled random error for each fraction were performed using our in‐house GPU‐accelerated robustness analyzer tool which reports the statistical probability of achieving dose‐volume metrics, NTCP, TCP, and the probability of achieving the optimization criteria for both auto‐contoured (AS) and manually drawn (D) ROIs. Metrics are reported for all possible cross‐evaluation pairs of ROI types (AS,D) and planning scenarios (PD,PAS,PM). Bhattacharyya coefficient (BC) is calculated to measure the PDF similarities for the dose‐volume metric, NTCP, TCP, and objectives with respect to the manually drawn contour evaluated on base plan (D‐PD).

Results:

We observe high BC values (BC≥0.94) for all OAR objectives. BC values of max dose objective on CTV also signify high resemblance (BC≥0.93) between the distributions. On the other hand, BC values for CTV's D95 and Dmin objectives are small for AS‐PM, AS‐PD. NTCP distributions are similar across all evaluation pairs, while TCP distributions of AS‐PM, AS‐PD sustain variations up to %6 compared to other evaluated pairs.

Conclusion:

No significant probabilistic differences are observed in the metrics when auto‐contoured OARs are used. The prostate auto‐contour needs improvement to achieve clinically equivalent plans.
SU‐C‐BRA‐02: A Lung Tumor Autocontouring Algorithm Based On Particle Filter for Dynamic Magnetic Resonance
Authors: Bourque A , Bedwani S , Filion E , Carrier J
Published: July 2016

Purpose:

This study proposes a novel autocontouring algorithm for lung tumors based on particle filter. It is developed in the context of MR‐linac treatments and is validated on in‐vivo dynamic magnetic resonance images.

Methods:

A sequential Monte Carlo method called particle filter is combined with Otsu's thresholding technique to contour lung tumors on dynamic MR images. Four non‐small cell lung cancer (NSCLC) patients were imaged with a 1.5 T MR (MAGNETOM Aera, Siemens Healthcare, Erlangen, Germany) for one minute at a rate of 4 images per second. A pretreatment image‐processing step includes a manual contour of the tumor, the tumor's displacement, and its descriptive statistics. During treatment, the contours are automatically generated by thresholding the image in a window surrounding the center of mass of the particles. The Dice similarity coefficient (DSC), the precision, the recall, the Hausdorff distance (HD) and the difference in centroid positions (Δd) are calculated to compare with the expert's contours.

Results:

This autocontouring algorithm presents continuous adaptability and is independent of pre‐treatment training. The number of particles is proportional to the area of the tumor and increases the computational time at a rate of 2 ms for every 500 particles, whereas the contouring step adds a constant 14 ms. The contours’ comparison is obtained with a mean DSC of 0.89 to 0.91, mean precision of 0.88 to 0.92, mean recall of 0.88 to 0.95 and mean Δd of 0.6 to 2.3 mm.

Conclusion:

This work presents a new autocontouring algorithm for NSCLC patients on dynamic MR images. Combining the autocontours with a motion prediction algorithm presents a promising method for lung tumor online tracking treatments.
SU‐C‐202‐02: A Comprehensive Evaluation of Adaptive Daily Planning for Cervical Cancer HDR Brachytherapy
Authors: Meerschaert R , Nalichowski A , Burmeister J , Paul A , Miller A , Zhuang L
Published: July 2016

Purpose:

To evaluate adaptive daily planning for cervical cancer patients who underwent high‐dose‐rate intra‐cavitary brachytherapy (HDR‐ICBT).

Methods:

This study included 22 cervical cancer patients who underwent 5 fractions of HDR ICBT. Regions of interest (ROIs) including high‐risk clinical tumor volume (HR‐CTV) and organs‐at‐risk (OARs) were manually contoured on daily CT images. All patients were treated with adaptive daily plans, which involved ROI delineation and dose optimization at each treatment fraction. Single treatment plans were retrospectively generated by applying the first treatment fraction's dwell times adjusted for decay and dwell positions of the applicator to subsequent treatment fractions. Various existing similarity metrics were calculated for the ROIs to quantify interfractional organ variations. A novel similarity score (JRARM) was established, which combined both volumetric overlap metrics (DSC, JSC, and RVD) and distance metrics (ASD, MSD, and RMSD). Linear regression was performed to determine a relationship between inter‐fractional organ variations of various similarity metrics and D2cc variations from both plans. Wilcoxon Signed Rank Tests were used to assess adaptive daily plans and single plans by comparing EQD2 D2cc (α/β=3) for OARs.

Results:

For inter‐fractional organ variations, the sigmoid demonstrated the greatest variations based on the JRARM and DSC similarity metrics. Comparisons between paired ROIs showed differences in JRARM scores and DSCs at each treatment fraction. RVD, MSD, and RMSD were found to be significantly correlated to D2cc variations for bladder and sigmoid. The comparison between plans found that adaptive daily planning provided lower EQD2 D2cc of OARs than single planning, specifically for the sigmoid (p=0.015).

Conclusion:

Substantial inter‐fractional organ motion can occur during HDR‐BT, which may significantly affect D2cc of OARs. Adaptive daily planning provides improved dose sparing for OARs compared to single planning.
SU‐C‐202‐03: A Tool for Automatic Calculation of Delivered Dose Variation for Off‐Line Adaptive Therapy Using Cone Beam CT
Authors: Zhang B , Lee S , Chen S , Zhou J , Prado K , D'Souza W , Yi B
Published: July 2016

Purpose:

Monitoring the delivered dose is an important task for the adaptive radiotherapy (ART) and for determining time to re‐plan. A software tool which enables automatic delivered dose calculation using cone‐beam CT (CBCT) has been developed and tested.

Methods:

The tool consists of four components: a CBCT Colleting Module (CCM), a Plan Registration Moduel (PRM), a Dose Calculation Module (DCM), and an Evaluation and Action Module (EAM). The CCM is triggered periodically (e.g. every 1:00 AM) to search for newly acquired CBCTs of patients of interest and then export the DICOM files of the images and related registrations defined in ARIA followed by triggering the PRM. The PRM imports the DICOM images and registrations, links the CBCTs to the related treatment plan of the patient in the planning system (RayStation V4.5, RaySearch, Stockholm, Sweden). A pre‐determined CT‐to‐density table is automatically generated for dose calculation. Current version of the DCM uses a rigid registration which regards the treatment isocenter of the CBCT to be the isocenter of the treatment plan. Then it starts the dose calculation automatically. The AEM evaluates the plan using pre‐determined plan evaluation parameters: PTV dose‐volume metrics and critical organ doses. The tool has been tested for 10 patients.

Results:

Automatic plans are generated and saved in the order of the treatment dates of the Adaptive Planning module of the RayStation planning system, without any manual intervention. Once the CTV dose deviates more than 3%, both email and page alerts are sent to the physician and the physicist of the patient so that one can look the case closely.

Conclusion:

The tool is capable to perform automatic dose tracking and to alert clinicians when an action is needed. It is clinically useful for off‐line adaptive therapy to catch any gross error. Practical way of determining alarming level for OAR is under development.
SU‐C‐202‐05: Pilot Study of Online Treatment Evaluation and Adaptive Re‐Planning for Laryngeal SBRT
Authors: Mao W , Liu C , Zhong H , Rozario T , Lu W , Gu X , Yan Y , Jia X , Sumer B , Schwartz D
Published: July 2016

Purpose:

We have instigated a phase I trial of 5‐fraction stereotactic body radiotherapy (SBRT) for advanced‐stage laryngeal cancer. We conducted this pilot dosimetric study to confirm the potential utility of online adaptive re‐planning to preserve treatment quality.

Methods:

Ten cases of larynx cancer were evaluated. Baseline and daily SBRT treatment plans were generated per trial protocol. Daily volumetric images were acquired prior to every fraction of treatment. Reference simulation CT images were deformably registered to daily volumetric images using Eclipse. Planning contours were then deformably propagated to daily images. Reference SBRT plans were directly copied to calculate delivered dose distributions on deformed reference CT images. In‐house software platform has been developed to calculate cumulative dose over a course of treatment in four steps: 1) deforming delivered dose grid to reference CT images using deformation information exported from Eclipse; 2) generating tetrahedrons using deformed dose grid as vertices; 3) resampling dose to a high resolution within every tetrahedron; 4) calculating dose‐volume histograms. Our inhouse software was benchmarked with a commercial software, Mirada.

Results:

In all ten cases including 49 fractions of treatments, delivered daily doses were completely evaluated and treatment could be re‐planned within 10 minutes. Prescription dose coverage of PTV was less than intended in 53% of fractions of treatment (mean: 94%, range: 84%–98%) while minimum coverage of CTV and GTV was 94% and 97%, respectively. Maximum bystander point dose limits to arytenoids, parotids, and spinal cord remained respected in all cases, although variances in carotid artery doses were observed in a minority of cases.

Conclusion:

Although GTV and CTV coverage is preserved by in‐room 3D image guidance of larynx SBRT, PTV coverage can vary significantly from intended plans. Online adaptive treatment evaluation and re‐planning is potentially necessary and our procedure is clinically applicable to fully preserve treatment quality.

This project is supported by CPRIT Individual Investigator Research Award RP150386.
SU‐C‐202‐07: Protocol and Hardware for Improved Flood Field Calibration of TrueBeam FFF Cine Imaging
Authors: Adamson J , Faught A , Yin F
Published: July 2016

Purpose:

Flattening filter free photon energies are commonly used for high dose treatments such as SBRT, where localization accuracy is essential. Often, MV cine imaging may be employed to verify correct localization. TrueBeam Electronic Portal Imaging Devices (EPIDs) equipped with the 40×30cm2 Image Detection Unit (IDU) are prone to image saturation at the image center especially for higher dose rates. While saturation often does not occur for cine imaging during treatment because the beam is attenuated by the patient, the flood field calibration is affected when the standard calibration procedure is followed. Here we describe the hardware and protocol to achieve improved image quality for this model of TrueBeam EPID.

Methods:

A stainless steel filter of uniform thickness was designed to have sufficient attenuation to avoid panel saturation for both 6XFFF and 10XFFF at the maximum dose rates (1400 MU/min & 2400 MU/min, respectively). The cine imaging flood field calibration was then acquired with the filter in place for the FFF energies under the standard calibration geometry (SDD=150cm). Image quality during MV cine was assessed with & without the modified flood field calibration using a low contrast resolution phantom and an anthropomorphic phantom.

Results:

When the flood field is acquired using the standard procedure (no filter in place), a pixel gain artifact is clearly present in the image center (r=3cm for 10XFFF at 2400 MU/min) which appears similar to and may be mis‐attributed to panel saturation in the subject image. The artifact obscured all low contrast inserts at the image center and was also visible on the anthropomorphic phantom. Using the filter for flood field calibration eliminated the artifact.

Conclusion:

Use of a modified flood field calibration procedure improves image quality for cine MV imaging with TrueBeams equipped with the 40×30cm2 IDU.
SU‐C‐207A‐06: On‐Line Beam Range Verification with Multiple Scanning Particle Beams: Initial Feasibility Study with Simulations
Authors: Zhong Y , Sun X , Lu W , Jia X , Wang J , Shao Y
Published: July 2016

Purpose:

To investigate the feasibility and requirement for intra‐fraction on‐line multiple scanning particle beam range verifications (BRVs) with in‐situ PET imaging, which is beyond the current single‐beam BRV with extra factors that will affect the BR measurement accuracy, such as beam diameter, separation between beams, and different image counts at different BRV positions.

Methods:

We simulated a 110‐MeV proton beam with 5‐mm diameter irradiating a uniform PMMA phantom by GATE simulation, which generated nuclear interaction‐induced positrons. In this preliminary study, we simply duplicated these positrons and placed them next to the initial protons to approximately mimic the two spatially separated positron distributions produced by two beams parallel to each other but with different beam ranges. These positrons were then imaged by a PET (∼2‐mm resolution, 10% sensitivity, 320×320×128 mm^3 FOV) with different acquisition times. We calculated the positron activity ranges (ARs) from reconstructed PET images and compared them with the corresponding ARs of original positron distributions.

Results:

Without further image data processing and correction, the preliminary study show the errors between the measured and original ARs varied from 0.2 mm to 2.3 mm as center‐to‐center separations and range differences were in the range of 8–12 mm and 2–8 mm respectively, indicating the accuracy of AR measurement strongly depends on the beam separations and range differences. In addition, it is feasible to achieve ≤ 1.0‐mm accuracy for both beams with 1‐min PET acquisition and 12 mm beam separation.

Conclusion:

This study shows that the overlap between the positron distributions from multiple scanning beams can significantly impact the accuracy of BRVs of distributed particle beams and need to be further addressed beyond the established method of single‐beam BRV, but it also indicates the feasibility to achieve accurate on‐line multi‐beam BRV with further improved method.
SU‐C‐206‐01: Impact of Charge Sharing Effect On Sub‐Pitch Resolution for CZT‐Based Photon Counting CT Systems
Authors: Zheng X , Cheng Z , Deen J , Peng H , Xing L
Published: July 2016

Purposes:

Photon counting CT is a new imaging technology that can provide tissue composition information such as calcium/iodine content quantification. Cadmium zinc telluride CZT is considered a good candidate the photon counting CT due to its relatively high atomic number and band gap. One potential challenge is the degradation of both spatial and energy resolution as the fine electrode pitch is deployed (<50 µm). We investigated the extent of charge sharing effect as functions of gap width, bias voltage and depth‐of‐interaction (DOI).

Methods:

The initial electron cloud size and diffusion process were modeled analytically. The valid range of charge sharing effect refers to the range over which both signals of adjacent electrodes are above the triggering threshold (10% of the amplitude of 60keV X‐ray photons). The intensity ratios of output in three regions (I1/I2/I3: left pixel, gap area and right pixel) were calculated. With Gaussian white noises modeled (a SNR of 5 based upon the preliminary experiments), the sub‐pitch resolution as a function of the spatial position in‐between two pixels was studied.

Results:

The valid range of charge sharing increases linearly with depth‐of‐interaction (DOI) but decreases with gap width and bias voltage. For a 1.5mm thickness CZT detector (pitch: 50µm, bias: 400 V), the range increase from ∼90µm up to ∼110µm. Such an increase can be attributed to a longer travel distance and the associated electron cloud broadening. The achievable sub‐pitch resolution is in the range of ∼10–30µm.

Conclusion:

The preliminary results demonstrate that sub‐pixel spatial resolution can be achieved using the ratio of amplitudes of two neighboring pixels. Such ratio may also be used to correct charge loss and help improve energy resolution of a CZT detector. The impact of characteristic X‐rays hitting adjacent pixels (i.e., multiple interaction) on charge sharing is currently being investigated.
SU‐C‐206‐03: Metal Artifact Reduction in X‐Ray Computed Tomography Based On Local Anatomical Similarity
Authors: Dong X , Yang X , Rosenfield J , Elder E , Dhabaan A
Published: July 2016

Purpose:

Metal implants such as orthopedic hardware and dental fillings cause severe bright and dark streaking in reconstructed CT images. These artifacts decrease image contrast and degrade HU accuracy, leading to inaccuracies in target delineation and dose calculation. Additionally, such artifacts negatively impact patient set‐up in image guided radiation therapy (IGRT). In this work, we propose a novel method for metal artifact reduction which utilizes the anatomical similarity between neighboring CT slices.

Methods:

Neighboring CT slices show similar anatomy. Based on this anatomical similarity, the proposed method replaces corrupted CT pixels with pixels from adjacent, artifact‐free slices. A gamma map, which is the weighted summation of relative HU error and distance error, is calculated for each pixel in the artifact‐corrupted CT image. The minimum value in each pixel's gamma map is used to identify a pixel from the adjacent CT slice to replace the corresponding artifact‐corrupted pixel. This replacement only occurs if the minimum value in a particular pixel's gamma map is larger than a threshold. The proposed method was evaluated with clinical images.

Results:

Highly attenuating dental fillings and hip implants cause severe streaking artifacts on CT images. The proposed method eliminates the dark and bright streaking and improves the implant delineation and visibility. In particular, the image non‐uniformity in the central region of interest was reduced from 1.88 and 1.01 to 0.28 and 0.35, respectively. Further, the mean CT HU error was reduced from 328 HU and 460 HU to 60 HU and 36 HU, respectively.

Conclusions:

The proposed metal artifact reduction method replaces corrupted image pixels with pixels from neighboring slices that are free of metal artifacts. This method proved capable of suppressing streaking artifacts, improving HU accuracy and image detectability.
SU‐C‐206‐05: Pixel‐Wise Calculation of Noise Statistics On Iterative CT Reconstruction from a Single Scan
Authors: Wang T , Zhu L
Published: July 2016

Purpose:

As iterative CT reconstruction continues to advance, the spatial distributions of noise standard deviation (STD) and accurate noise power spectrum (NPS) on reconstructed CT images become more important for method evaluation ans algorithm parameters settings. Using data of a single scan, we propose a practical method for pixel‐wise noise statistics calculation on iterative CT reconstruction image, which enables accurate calculation of noise STD for each pixel and NPS without stationary noise assumption.

Methods:

We first iteratively reconstruct a CT image using existing reconstruction algorithm. Noise perturbation is then simulated on the raw projection data based on the estimated noise statistics, and the iterative reconstruction continues to generate a different CT image. The above process is repeated on the same projection data but with different noise perturbations, until a sufficient number (32 in our implementations) of different noisy reconstruction images are generated. Pixel‐wise calculations of noise STD and NPS are finally performed on the entire stack of noisy images.

Results:

We have evaluated our method via simulation studies on a clinical head‐and‐neck CT image, using two iterative reconstruction algorithms: penalized weighted least‐square (PWLS) and total‐variation (TV) regularization. 128 sets of simulated noisy sinogram are used to generate ground‐truths of noise STD and NPS. Using only one set noisy sinogram, the proposed method accurately calculates noise STD map, with a correlation of 94% and 95% for PWLS and TV methods, respectively, compared with the ground‐truth. The relative root‐mean‐square error of 1D‐NPS for proposed method are 1.5% and 3.4% for PWLS and TV methods, respectively, while those for conventional method (averaging NPS of sub‐ROIs in ROI of one image) are 9.0% and 12.9%.

Conclusion:

The proposed method accurately calculates noise STD for each pixel and NPS without stationary noise assumption on iteratively reconstructed CT image, with no requirements of repeated CT scans.

Research reported in this abstract was supported by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R21EB019597.
SU‐C‐209‐01: Validation of the Simulated Detectability Metric (G‐ROD) Using the Experimental Generalized Measured Relative Object Detectability Metric (GM‐ROD)
Authors: Russ M , Ionita C , Bednarek D , Rudin S
Published: July 2016

Purpose:

The Generalized Relative Object Detectability (G‐ROD) family of ideal observer metrics are a well‐characterized set of task‐based metrics used for quantitatively comparing imaging systems that include the detector, focal spot geometry and scatter characteristics on the basis of system abilities in imaging a given simulated object. The G‐ROD metric takes the integral over spatial frequencies of the Fourier transform of a simulated object function weighted with the detector generalized DQE (GDQE), divided by the comparable integral for another detector. When a measured image of an actual object is used, the generalized measured‐ROD (GM‐ROD) metric can compare detector systems without explicitly determining detector MTF. In this work, the results of simulated and measured ROD calculations for the same object are compared for the first time.

Methods:

G‐ROD calculations were performed to compare a high resolution microangiographic fluoroscopic (MAF) detector to a flat panel detector (FPD) using 5mm segments of simulated copper wires of varying diameter (d=0.05–0.6mm) as the object function for three different focal spot sizes at two magnifications. A GM‐ROD experiment with similar parameters was performed to compare the same detector system using three actual 5mm copper wires (d=0.113mm,0.238mm,0.558mm) imaged under identical but simulated conditions used in G‐ROD calculations to determine the agreement between simulated and experimentally obtained results.

Results:

The G‐ROD and GM‐ROD calculations examined relative detector system imaging performance. The GM‐ROD results for all three different sized wires imaged with low magnification and a small focal spot size were 2.1, 1.38, and 1.1, respectively, and the G‐ROD results for the same calculation was 1.81, 1.3, and 1.07, corresponding to percent deviations of 13%, 5.8%, and 2.7%.

Conclusion:

These results indicate experimental validation of the simulated metric results.

Partial support from NIH grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp.
SU‐C‐209‐02: 3D Fluoroscopic Image Generation From Patient‐Specific 4DCBCT‐Based Motion Models Derived From Clinical Patient Images
Authors: Dhou S , Ionascu D , Cai W , Hurwitz M , Williams C , Lewis J
Published: July 2016

Purpose:

We develop a method to generate time varying volumetric images (3D fluoroscopic images) using patient‐specific motion models derived from four‐dimensional cone‐beam CT (4DCBCT).

Methods:

Motion models are derived by selecting one 4DCBCT phase as a reference image, and registering the remaining images to it. Principal component analysis (PCA) is performed on the resultant displacement vector fields (DVFs) to create a reduced set of PCA eigenvectors that capture the majority of respiratory motion. 3D fluoroscopic images are generated by optimizing the weights of the PCA eigenvectors iteratively through comparison of measured cone‐beam projections and simulated projections generated from the motion model. This method was applied to images from five lung‐cancer patients. The spatial accuracy of this method is evaluated by comparing landmark positions in the 3D fluoroscopic images to manually defined ground truth positions in the patient cone‐beam projections.

Results:

4DCBCT motion models were shown to accurately generate 3D fluoroscopic images when the patient cone‐beam projections contained clearly visible structures moving with respiration (e.g., the diaphragm). When no moving anatomical structure was clearly visible in the projections, the 3D fluoroscopic images generated did not capture breathing deformations, and reverted to the reference image. For the subset of 3D fluoroscopic images generated from projections with visibly moving anatomy, the average tumor localization error and the 95th percentile were 1.6 mm and 3.1 mm respectively.

Conclusion:

This study showed that 4DCBCT‐based 3D fluoroscopic images can accurately capture respiratory deformations in a patient dataset, so long as the cone‐beam projections used contain visible structures that move with respiration. For clinical implementation of 3D fluoroscopic imaging for treatment verification, an imaging field of view (FOV) that contains visible structures moving with respiration should be selected. If no other appropriate structures are visible, the images should include the diaphragm.

This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc, Palo Alto, CA.
SU‐C‐209‐04: Calculation of Two‐Material Tissue Parameterizations for Dual‐Energy Imaging
Authors: Jennings R
Published: July 2016

Purpose:

The characterization of the energy dependences of tissue attenuation coefficients is fundamental in dual‐energy imaging. It has been posited that a two‐parameter model is both necessary and sufficient to describe these dependences for tissues of medical interest in the diagnostic energy range. In one approach the two parameters are the weighting factors for the energy‐dependent linear attenuation coefficients of two distinct materials. This is commonly known as the basis material decomposition method. The purpose of this work is to describe and evaluate a method for determining these weighting factors for user‐selected basis materials and tissues of interest.

Methods:

The method essentially says that the linear attenuation coefficient of the tissue of interest is equal, to a good approximation, to the weighted sum of the coefficients of two other distinct materials. The weights can be obtained from the resulting equation, evaluated at two different energies. Not all pairs of energies produce weights that yield accurate results. The method for finding a quasi‐optimal pair of weights is described.

Results:

The method has been applied to a variety of combinations of tissue of interest and materials chosen to represent it. In most instances, the accuracy of the match is of the order of a few tenths of one percent over a large energy range. Even for combinations that might be expected to give poor results, water represented by PMMA and aluminum for example, the maximum deviations are of the order of one percent.

Conclusion:

The method produces characterizations that are at least as good as, and usually better than, the accuracy of x‐ray measurements obtainable with reasonable patient doses and currently available hardware. The results also show that many different materials are reasonable choices for basis materials. The software used for this study is available on GitHub.
SU‐C‐207B‐03: A Geometrical Constrained Chan‐Vese Based Tumor Segmentation Scheme for PET
Authors: Chen L , Zhou Z , Wang J
Published: July 2016

Purpose:

Accurate segmentation of tumor in PET is challenging when part of tumor is connected with normal organs/tissues with no difference in intensity. Conventional segmentation methods, such as thresholding or region growing, cannot generate satisfactory results in this case. We proposed a geometrical constrained Chan‐Vese based scheme to segment tumor in PET for this special case by considering the similarity between two adjacent slices.

Methods:

The proposed scheme performs segmentation in a slice‐by‐slice fashion where an accurate segmentation of one slice is used as the guidance for segmentation of rest slices. For a slice that the tumor is not directly connected to organs/tissues with similar intensity values, a conventional clustering‐based segmentation method under user's guidance is used to obtain an exact tumor contour. This is set as the initial contour and the Chan‐Vese algorithm is applied for segmenting the tumor in the next adjacent slice by adding constraints of tumor size, position and shape information. This procedure is repeated until the last slice of PET containing tumor. The proposed geometrical constrained Chan‐Vese based algorithm was implemented in Matlab and its performance was tested on several cervical cancer patients where cervix and bladder are connected with similar activity values. The positive predictive values (PPV) are calculated to characterize the segmentation accuracy of the proposed scheme.

Results:

Tumors were accurately segmented by the proposed method even when they are connected with bladder in the image with no difference in intensity. The average PPVs were 0.9571±0.0355 and 0.9894±0.0271 for 17 slices and 11 slices of PET from two patients, respectively.

Conclusion:

We have developed a new scheme to segment tumor in PET images for the special case that the tumor is quite similar to or connected to normal organs/tissues in the image. The proposed scheme can provide a reliable way for segmenting tumors.
SU‐C‐207B‐04: Automated Segmentation of Pectoral Muscle in MR Images of Dense Breasts
Authors: Verburg E , de Waard SN , Veldhuis WB , van Gils CH , Gilhuijs KGA
Published: July 2016

Purpose:

To develop and evaluate a fully automated method for segmentation of the pectoral muscle boundary in Magnetic Resonance Imaging (MRI) of dense breasts.

Methods:

Segmentation of the pectoral muscle is an important part of automatic breast image analysis methods. Current methods for segmenting the pectoral muscle in breast MRI have difficulties delineating the muscle border correctly in breasts with a large proportion of fibroglandular tissue (i.e., dense breasts). Hence, an automated method based on dynamic programming was developed, incorporating heuristics aimed at shape, location and gradient features.To assess the method, the pectoral muscle was segmented in 91 randomly selected participants (mean age 56.6 years, range 49.5–75.2 years) from a large MRI screening trial in women with dense breasts (ACR BI‐RADS category 4). Each MR dataset consisted of 178 or 179 T1‐weighted images with voxel size 0.64 × 0.64 × 1.00 mm3. All images (n=16,287) were reviewed and scored by a radiologist. In contrast to volume overlap coefficients, such as DICE, the radiologist detected deviations in the segmented muscle border and determined whether the result would impact the ability to accurately determine the volume of fibroglandular tissue and detection of breast lesions.

Results:

According to the radiologist's scores, 95.5% of the slices did not mask breast tissue in such way that it could affect detection of breast lesions or volume measurements. In 13.1% of the slices a deviation in the segmented muscle border was present which would not impact breast lesion detection. In 70 datasets (78%) at least 95% of the slices were segmented in such a way it would not affect detection of breast lesions, and in 60 (66%) datasets this was 100%.

Conclusion:

Dynamic programming with dedicated heuristics shows promising potential to segment the pectoral muscle in women with dense breasts.
SU‐C‐207B‐06: Comparison of Registration Methods for Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy
Authors: Riyahi S , Choi W , Bhooshan N , Tan S , Zhang H , Lu W
Published: July 2016

Purpose:

To compare linear and deformable registration methods for evaluation of tumor response to Chemoradiation therapy (CRT) in patients with esophageal cancer.

Methods:

Linear and multi‐resolution BSpline deformable registration were performed on Pre‐Post‐CRT CT/PET images of 20 patients with esophageal cancer. For both registration methods, we registered CT using Mean Square Error (MSE) metric, however to register PET we used transformation obtained using Mutual Information (MI) from the same CT due to being multi‐modality. Similarity of Warped‐CT/PET was quantitatively evaluated using Normalized Mutual Information and plausibility of DF was assessed using inverse consistency Error. To evaluate tumor response four groups of tumor features were examined: (1) Conventional PET/CT e.g. SUV, diameter (2) Clinical parameters e.g. TNM stage, histology (3)spatial‐temporal PET features that describe intensity, texture and geometry of tumor (4)all features combined. Dominant features were identified using 10‐fold cross‐validation and Support Vector Machine (SVM) was deployed for tumor response prediction while the accuracy was evaluated by ROC Area Under Curve (AUC).

Results:

Average and standard deviation of Normalized mutual information for deformable registration using MSE was 0.2±0.054 and for linear registration was 0.1±0.026, showing higher NMI for deformable registration. Likewise for MI metric, deformable registration had 0.13±0.035 comparing to linear counterpart with 0.12±0.037. Inverse consistency error for deformable registration for MSE metric was 4.65±2.49 and for linear was 1.32±2.3 showing smaller value for linear registration. The same conclusion was obtained for MI in terms of inverse consistency error. AUC for both linear and deformable registration was 1 showing no absolute difference in terms of response evaluation.

Conclusion:

Deformable registration showed better NMI comparing to linear registration, however inverse consistency of transformation was lower in linear registration. We do not expect to see significant difference when warping PET images using deformable or linear registration.

This work was supported in part by the National Cancer Institute Grants R01CA172638.
SU‐D‐204‐04: Correlations Between Dosimetric Indices and Follow‐Up Data for Salivary Glands Six Months After Radiation Therapy for Head and Neck Cancer
Authors: Chera B , Price A , Kostich M , Amdur R , Mendenhall W , Sheets N , Green R , Marks L , Das S , Mavroidis P
Published: July 2016

Purpose:

To investigate the correlation between different dosimetric indices of salivary glands (as separate or combined structures) to patient‐reported dry mouth 6 months post radiotherapy using the novel patient reported outcome version of the CTCAE (PRO‐CTCAE).

Methods:

Forty‐three patients with oropharyngeal squamous cell carcinoma were treated on a prospective multi‐institutional study. All patients received de‐intensified 60 Gy intensity modulated radiotherapy. Dosimetric constraints were used for the salivary glands (e.g. mean dose to the contralateral‐parotid < 26 Gy). We investigated correlations of individual patient dosimetric data of the parotid and submandibular glands (as separate or combined structures) to their self‐reported 6 month post‐treatment dry mouth responses. Moderate dry mouth responses were most prevalent and were used as the clinical endpoint indicating response. The correlation of Dmean, Dmax and a range of dosevolume (VD) points were assessed through the area under the Receiver Operating Characteristic curve (ROC) and Odds Ratios (OR).

Results:

Patients reporting non/mild dry mouth response (N=22) had average Dmean = 19.6 ± 6.2Gy to the contralateral‐parotid compared to an average Dmean = 28.0 ± 8.3Gy and an AUC = 0.758 for the patients reporting moderate/severe/very severe dry mouth (N=21). Analysis of the range of VD's for patients who had reported dry mouth showed that for the contralateral‐parotid the indices V18 through V22 had the highest area under the curves (AUC) (0.762 – 0.772) compared to a more traditional dosimetric index V30, which had an AUC = 0.732. The highest AUC was observed for the combination of contralateral parotid and contralateral submandibular glands, for which V16 through V28 had AUC = 0.801 – 0.834.

Conclusion:

Patients who report moderate/severe/very severe dry mouth 6 months post radiotherapy had on average higher Dmean. The V16‐V28 of the combination of the contralateral glands showed the highest correlation with the clinical endpoint.