HU Numbers Research Articles

Development of a 3D printed phantom for commissioning and quality assurance of multiple brain targets stereotactic radiosurgery

Single plan techniques for multiple brain targets (MBT) stereotactic radiosurgery (SRS) are now routine. Patient specific quality assurance (QA) for MBT poses challenges due to the limited capabilities of existing QA tools which necessitates several plan redeliveries. This study sought to develop an SRS QA phantom that enables flexible MBT patient specific QA in a single delivery, along with complex SRS commissioning. PLA marble and PLA StoneFil materials were selected based on the literature and previous research conducted in our department. The HU numbers were investigated to determine the appropriate percentage infill for skull and soft-tissue equivalence. A Prusa MK3S printer in conjunction with the above-mentioned filaments were used to print the SRS QA phantom. Quality control (QC) was performed on the printed skull, film inserts and plugs for point dose measurements. EBT3 film and point dose measurements were performed using a CC04 ionisation chamber. QC demonstrated that the SRS QA phantom transverse, coronal and sagittal film planes were orthogonal within 0.5°. HU numbers for the skull, film inserts and plugs were 858 ± 20 and 35 ± 12 respectively. Point and EBT3 film dose measurements were within 2.5% and 3%/2 mm 95% gamma pass rate, respectively except one Gross Tumour Volume (GTV) that had a slightly lower gamma pass rate. Dose distributions to five GTVs were measured with EBT3 film in a single plan delivery on CyberKnife. In conclusion, an SRS QA phantom was designed, and 3D printed and its use for performing complex MBT patient specific QA in a single delivery was demonstrated.

An anthropomorphic 3D printed inhomogeneity thorax phantom slab for SBRT commissioning and quality assurance.

Anthropomorphic phantoms with tissue equivalency are required in radiotherapy for quality assurance of imaging and dosimetric processes used in radiotherapy treatments. Commercial phantoms are expensive and provide limited approximation to patient geometry and tissue equivalency. In this study, a 5cm thick anthropomorphic thoracic slab phantom was designed and 3D printed using models exported from a CT dataset to demonstrate the feasibility of manufacturing anthropomorphic 3D printed phantoms onsite in a clinical radiotherapy department. The 3D printed phantom was manufactured with polylactic acid with an in-fill density of 80% to simulate tissue density and 26% to simulate lung density. A common radio-opacifier, barium sulfate (BaSO4), was added 6% w/w to an epoxy resin mixture to simulate similar HU numbers for bone equivalency. A half-cylindrical shape was cropped away from the spine region to allow insertion of the bone equivalent mixture. Two Gafchromic™ EBT3 film strips were inserted into the 3D printed phantom to measure the delivery of two stereotactic radiotherapy plans targeting lung and bone lesions respectively. Results were analysed within SNC Patient with a low dose threshold of 10% and a gamma criterion of 3%/2mm and 5%/1mm. The resulting gamma pass rate across both criterions for lung and bone were ≥ 95% and approximately 85% respectively. Results shows that a cost-effective anthropomorphic 3D printed phantom with realistic heterogeneity simulation can be fabricated in departments with access a suitable 3D printer, which can be used for performing commissioning and quality assurance for stereotactic type radiotherapy to lesions in the presence of heterogeneity.

An abdominal phantom with anthropomorphic organ motion and multimodal imaging contrast for MR-guided radiotherapy

Purpose. Improvements in image-guided radiotherapy (IGRT) enable accurate and precise treatment of moving tumors in the abdomen while simultaneously sparing healthy tissue. However, the lack of validation tools for newly developed MR-guided radiotherapy hybrid devices such as the MR-Linac is an open issue. This study presents a custom developed abdominal phantom with respiratory organ motion and multimodal imaging contrast to perform end-to-end tests for IGRT treatment planning scenarios. Methods. The abdominal phantom contains deformable and anatomically shaped liver and kidney models made of Ni-DTPA and KCl-doped agarose mixtures that can be reproducibly positioned within the phantom. Organ models are wrapped in foil to avoid ion exchange with the surrounding agarose and to provide stable T1 and T2 relaxation times as well as HU numbers. Breathing motion is realized by a diaphragm connected to an actuator that is hydraulically controlled via a programmable logic controller. With this system, artificial and patient-specific breathing patterns can be carried out. In 1.5 T magnetic resonance imaging (MRI), diaphragm, liver and kidney motion was measured and compared to the breathing motion of a healthy male volunteer for different breathing amplitudes including shallow, normal and deep breathing. Results. The constructed abdominal phantom demonstrated organ-equivalent intensity values in CT as well as in MRI. T1-weighted (T1w) and T2-weighted (T2w) relaxation times for 1.5 T and CT numbers were 552.9 ms, 48.2 ms and 48.8 HU (liver) as well as 950.42 ms, 79 ms and 28.2 HU (kidney), respectively. These values were stable for more than six months. Extracted breathing motion from a healthy volunteer revealed a liver to diaphragm motion ratio (LDMR) of 64.4% and a kidney to diaphragm motion ratio (KDMR) of 30.7%. Well-comparable values were obtained for the phantom (LDMR: 65.5%, KDMR: 27.5%). Conclusions. The abdominal phantom demonstrated anthropomorphic T1 and T2 relaxation times as well as HU numbers and physiological motion pattern in MRI and CT. This allows for wide use in the validation of IGRT including MRgRT.

Development of a stereoscopic CT metal artifact management algorithm using gantry angle tilts for head and neck patients.

Dental amalgams are a common source of artifacts in head and neck (HN) images. Commercial artifact reduction techniques have been offered, but are substantially ineffectual at reducing artifacts from dental amalgams, can produce additional artifacts, provide inaccurate HU information, or require extensive computation time, and thus offer limited clinically utility. The goal of this work was to define and validate a novel algorithm and provide a phantom‐based testing as proof of principle. An initial clinical comparison to a vendor's current solution was also performed. The algorithm uses two‐angled CT scans in order to generate a single image set with minimal artifacts posterior to the metal implants. The algorithm was evaluated using a phantom simulating a HN patient with dental fillings. Baseline (no artifacts) geometrical measurements of the phantom were taken in the anterior–posterior, left–right, and superior–inferior directions and compared to the metal‐corrected images using our algorithm to evaluate possible distortion from application of the algorithm. Mean HU numbers were also compared between the baseline scan and corrected image sets. A similar analysis was performed on the vendor's algorithm for comparison. The algorithm developed in this work successfully preserved the image geometry and HU and corrected the CT metal artifacts in the region posterior to the metal. The average total distortion for all gantry angles in the AP, LR, and SI directions was 0.17, 0.12, and 0.14 mm, respectively. The HU measurements showed significant consistency throughout the different reconstructed images when compared to the baseline image sets. The vendor's algorithm also showed no geometrical distortion but performed inferiorly in the HU number analysis compared to our technique. Our novel metal artifact management algorithm, using CT gantry angle tilts, provides a promising technique for clinical management of metal artifacts from dental amalgam.

73 Impact of iMAR® algorithm (Siemens) and extended field of view reconstruction on HU numbers accuracy and dose calculation in radiotherapy treatment plans

Introduction.Definition AS64 CT (Siemens) provides an artifact reduction algorithm (iMAR®) which allows to reconstruct the missing data considering the material type which created the artifact. This correction can modify the image by changing the volumes and the HU numbers. The diameter of the scan field of view is only 50 cm long. It’s then possible to reconstruct an extended field of view when the patient size is larger. Uncertainty on HU numbers is 50 HU when the field of view diameter is extended to 65 cm. Beyond this diameter, Siemens doesn’t ensure their accuracy. These options are particularly interesting for radiotherapy. The aim of this study is to determine the influence of these algorithms on HU numbers, volumes and dose calculation.

Assessing lung function using contrast-enhanced dual-energy computed tomography for potential applications in radiation therapy.

There is an increasing interest in the evaluation of lung function from physiological images in radiation therapy treatment planning to reduce the extent of postradiation toxicities. The purpose of this work was to retrieve reliable functional information from contrast-enhanced dual-energy computed tomography (DECT) for new applications in radiation therapy. The functional information obtained by DECT is also compared with other methods using single-energy CT (SECT) and single-photon emission computed tomography (SPECT) with CT. The differential function between left and right lung, as well as between lobes is computed for all methods. Five lung cancer patients were retrospectively selected for this study; each underwent a SPECT/CT scan and a contrast-injected DECT scan, using 100 and 140 Sn kVp. The DECT images are postprocessed into iodine concentration maps, which are further used to determine the perfused blood volume. These maps are calculated in two steps: (a) a DECT stoichiometric calibration adapted to the presence of iodine and followed by (b) a two-material decomposition technique. The functional information from SECT is assumed proportional to the HU numbers from a mixed CT image. The functional data from SPECT/CT are considered proportional to the number of counts. A radiation oncologist segmented the entire lung volume into five lobes on both mixed CT images and low-dose CT images from SPECT/CT to allow a regional comparison. The differential function for each subvolume is computed relative to the entire lung volume. The differential function per lobe derived from SPECT/CT correlates strongly with DECT (Pearson's coefficient r = 0.91) and moderately with SECT (r = 0.46). The differential function for the left lung shows a mean difference of 7% between SPECT/CT and DECT; and 17% between SPECT/CT and SECT. The presence of nonfunctional areas, such as localized emphysema or a lung tumor, is reflected by an intensity drop in the iodine concentration maps. Functional dose volume histograms (fDVH) are also generated for two patients as a proof of concept. The extraction of iodine concentration maps from a contrast-enhanced DECT scan is achieved to compute the differential function for each lung subvolume and good agreement is found in respect to SPECT/CT. One promising avenue in radiation therapy is to include such functional information during treatment planning dose optimization to spare functional lung tissues.

Use of Synthetic CT for Magnetic Resonance–Only Based External Beam Pelvic Radiation Therapy of Cervical Cancer

The superiority of T2 MRI over CT for cervical cancer tumor delineation is established by GEC-ESTRO. With the emergence of integrated MRI/LINAC technology, MR-only pelvic radiation needs to be studied in the definitive treatment of cervical cancer. In this study, we evaluate the impact of MR on pelvic targets and organs at risk (OARs) demarcation and dose distribution. Eight patients treated for cervical cancer staged FIGO IIA2 to IIIB for which a supine CT simulation and supine MRI of pelvis was performed were reviewed. All patient data was de-identified in accordance with institutional IRB requirements. Diagnostic MR Images were acquired on a 1.5T scanner. The MR images were manually co-registered with CT using Velocity software. CT body was segmented into 3 tissue types known as Dixon map: bone, fat, muscle/organs, by thresholding of CT number, and assigned HU numbers of 300, -100, and 0, respectively, to generate synCT. Treatment planning from CT was recalculated on the synCTs. Contouring of the CTV was performed by a radiologist on CT and T2MR to ensure accuracy. OARs were contoured on both CT and registered T2-weighted MR images. Four-field box conformal 3D-CRT planning to 45 Gy was used for plan generation. Treatment plans from CT was recalculated on the synCTs using same beam arrangements and monitor units. Dosimetric statistical analysis of the targets and OARs was performed using t-test with an alpha of 0.05. The volumetric difference between CT-CTV (mean 292.70 cm3, range 68.40-1139.90 cm3) and MR-CTV (mean 88.96 cm3, range 30.30-331.70 cm3) was not statistically significant (SS) (p=0.06). The mean D99 for CT and MR uterocervix was 45.32 and 44.99 Gy, respectively, and V100 for CT and MR uterocervix was 226.00 and 176.96, respectively, with no statistical difference between D99 or V100 for CT and MRI uterocervix (p=0.26 and 0.24, respectively). All dosimetric data can be found in Table 1 demonstrating non-significant difference on max doses for all OARs.Abstract 3614; Table 1Mean dosimetry metrics and statistical analysis using student's T-test comparing CT to MRICT CTVMRCTVCT UtcxMRUtcxCT BladMR BladCT RectMR RectCT L FHMRL FHCT R FHMR R FHMean Vol cm3292.790.0292.7238.3Mean Max dose Gy47.747.747.947.341.642.340.242.2t-Test P-Value0.060.240.360.060.750.26 Open table in a new tab The use of MRI for external beam planning provides optimal tumor visualization, providing potential clinical impact by improving target coverage. Our findings suggest that defining the CTV on MRI may be more accurate given the inherent MR advantage for pelvic organ visualization. The average CTV volume was smaller on MRI, which could ultimately lead to improved OAR sparing and reduced toxicities. We feel that this small pilot study warrants further investigation in order to fully evaluate the advantage of MR only based external beam planning for cervical cancer.

SU‐F‐T‐489: 4‐Years Experience of QA in TomoTherapy MVCT: What Do We Look Out For?

Purpose:To evaluate the QA results of TomoTherapy MVCT from March 2012 to February 2016, and to identify issues that may affect consistency in HU numbers and reconstructed treatment dose in MVCT.Methods:Monthly QA was performed on our TomoHD system. Phantom with rod inserts of various mass densities was imaged in MVCT and compared to baseline to evaluate HU number consistency. To evaluate treatment dose reconstructed by delivered sinogram and MVCT, a treatment plan was designed on a humanoid skull phantom. The phantom was imaged with MVCT and treatment plan was delivered to obtain the sinogram. The dose reconstructed with the Planned Adaptive software was compared to the dose in the original plan. The QA tolerance for HU numbers was ±30 HU, and ±2% for discrepancy between original plan dose and reconstructed dose. Tolerances were referenced to AAPM TG148.Results:Several technical modifications or maintenance activities to the system have been identified which affected QAResults:1) Upgrade in console system software which added a weekly HU calibration procedure; 2) Linac or MLC replacement leading to change in Accelerator Output Machine (AOM) parameters; 3) Upgrade in planning system algorithm affecting MVCT dose reconstruction. These events caused abrupt changes in QA results especially for the reconstructed dose. In the past 9 months, when no such modifications were done to the system, reconstructed dose was consistent with maximum deviation from baseline less than 0.6%. The HU number deviated less than 5HU.Conclusion:Routine QA is essential for MVCT, especially if the MVCT is used for daily dose reconstruction to monitor delivered dose to patients. Several technical events which may affect consistency of this are software changes, linac or MLC replacement. QA results reflected changes which justify re‐calibration or system adjustment. In normal circumstances, the system should be relatively stable and quarterly QA may be sufficient.

SU‐F‐T‐407: Artifact Reduction with Dual Energy Or IMAR: Who's Winning?

Purpose:The purpose of this abstract was to evaluate the performance of commercial strategies for artifact reduction in radiation oncology settings. The iterative metal artifact reduction (Siemens iMAR) algorithm and monoenergetic virtual datasets reconstructed from dual energy scans are compared side‐by‐side in their ability to image in the presence of metal inserts.Methods:A CIRS ATOM Dosimetry Verification Phantom was scanned with and without a metal insert on a SOMATOM Definition AS dual energy scanner. Images with the metal insert were reconstructed with (a) a tradition single energy CT scan with the iMAR option implemented, using different artifact reduction settings and (b) a monoenergetic scan calculated from dual energy scans by recovering differences in the energy‐dependence of the attenuation coefficients of different materials and then creating a virtual monoenergetic scan from these coefficients. The iMAR and monoenergetic scans were then compared with the metal‐free scan to assess changes in HU numbers and noise within a region around the metal insert.Results:Both the iMAR and dual energy scans reduced artifacts produced by the metal insert. However the iMAR results are dependent of the selected algorithm settings, with a mean HU difference ranging from 0.65 to 90.40 for different options. The mean differences without the iMAR correction were 38.74. When using the dual energy scan, the mean differences were 4.53, that is however attributed to increased noise and not artifacts, as the dual energy scan had the lowest skewness (2.52) compared to the iMAR scans (ranging from 3.90 to 4.88) and the lowest kurtosis (5.72 for dual energy, range of 18.19 to 27.36 for iMAR).Conclusion:Both approaches accurately recovered HU numbers, however the dual energy method provided smaller residual artifacts.

SU‐F‐J‐212: Enabling Conventional Cone Beam CT with the Capability of Dual Energy Imaging Using a Simple Add‐On Beam Modifier

Purpose:In searching for a robust, efficient and cost‐effective dual energy cone beam CT (DECBCT) solution for various radiation oncology applications, in particularly for improved proton dose planning/replanning accuracy and DE‐CBCT guided radiation therapy, we investigate a novel energy modulation scheme using a beam modifier placed between the source and patient and optimize its geometric configuration for routine clinical use.Methods:The study was performed using a Hitachi CBCT scanner and the tube voltage was set at 125 kVp. The higher energy beam was obtained by filtering the incident utilizing a beam modulation layer (material: copper, thickness: 1.8 mm). To avoid the need for double scans (one with and one without the energy modulator), the modulation layer was configured to cover only the half of the X‐ray beam so that two sets of sinograms corresponding low and high energies were collected after a single gantry rotation of 360 deg. The average high energy and low energy HU numbers (HUhigh and HUlow) were derived for pixels in a defined region‐of‐interest, respectively.Results:The beam modifier increased the threshold of the energy spectrum from ∼20 keV up to ∼50 keV. Two complete sets of images were obtained with good alignment between the high energy and low‐energy cases without any artifact observed (Fig. 2). The HUlow/HUhigh is ∼0/0 (water), ∼394/238 (brain), ∼1283/1085 (cortical bone) and ∼3000/1800 (titanium).Conclusion:The feasibility of the proposed DECT implementation using a beam modifier has been demonstrated. Compared to the existing DECT solutions, the proposed scheme is much more cost‐effective and requires minimum hardware modification. The work lays foundation for us to study the quantification of HU values to derive material density images and atomic number (and electron density) of substances.

Investigation of CT numbers correction of kilo-voltage cone-beam CT images for accurate dose calculation

Objective To study CT numbers correction of kilo-voltage cone-beam CT(KV-CBCT)images for dose calculation. Method Aligning the CBCT images with plan CT images, then obtain the background scatter by subtracting CT images from CBCT images. The background scatter is then processed by low-pass filter. The final CBCT images are acquired by subtracting the background scatter from the raw CBCT. KV-CBCT images of Catphan600 phantom and four patients with pelvic tumors were obtained with the linac-integrated CBCT system. The CBCT images were modified to correct the CT numbers. Finally, compare HU numbers between corrected CBCT and planning CT by paired T test. Evaluate the image quality and accuracy of dose calculation of the modified CBCT images. Results The proposed method reduces the artifacts of CBCT images significantly. The differences of CT numbers were 232 HU, 89 HU, 29 HU and 66 HU for air, fat, muscle and femoral head between CT and CBCT respectively(P = 0. 39,0. 66,0. 59,1).The differences of CT numbers between CT and CBCT was reduced to within 5 HU. And the error of dose calculation with corrected CBCT images was within 2%. Conclusions The CT numbers of corrected CBCT are similar with plan CT images and dose calculations based on the modified CBCT show good agreement with plan CT. Key words: Tomography, X-ray computed, cone-beam; CT numbers regulate; Dose calculation

MO‐E‐17A‐05: Individualized Patient Dosimetry in CT Using the Patient Dose (PATDOSE) Algorithm

Purpose:Radiation dose to the patient undergoing a CT examination has been the focus of many recent studies. While CTDIvol and SSDE‐based methods are important tools for patient dose management, the CT image data provides important information with respect to CT dose and its distribution. Coupled with the known geometry and output factors (kV, mAs, pitch, etc.) of the CT scanner, the CT dataset can be used directly for computing absorbed dose.Methods:The HU numbers in a patient's CT data set can be converted to linear attenuation coefficients (LACs) with some assumptions. With this (PAT‐DOSE) method, which is not Monte Carlo‐based, the primary and scatter dose are computed separately. The primary dose is computed directly from the geometry of the scanner, x‐ray spectrum, and the known patient LACs. Once the primary dose has been computed to all voxels in the patient, the scatter dose algorithm redistributes a fraction of the absorbed primary dose (based on the HU number of each source voxel), and the methods here invoke both tissue attenuation and absorption and solid angle geometry. The scatter dose algorithm can be run N times to include Nth‐scatter redistribution. PAT‐DOSE was deployed using simple PMMA phantoms, to validate its performance against Monte Carlo‐derived dose distributions.Results:Comparison between PAT‐DOSE and MCNPX primary dose distributions showed excellent agreement for several scan lengths. The 1st‐scatter dose distributions showed relatively higher‐amplitude, long‐range scatter tails for the PAT‐DOSE algorithm then for MCNPX simulations.Conclusion:The PAT‐DOSE algorithm provides a fast, deterministic assessment of the 3‐D dose distribution in CT, making use of scanner geometry and the patient image data set. The preliminary implementation of the algorithm produces accurate primary dose distributions however achieving scatter distribution agreement is more challenging. Addressing the polyenergetic x‐ray spectrum and spatially dependent scatter fractions will improve algorithm accuracy.Funding Support: UC Davis Clinical and Translational Science Center (CTSC) Award; NIH IMSD Student Fellowship; Saxon Student FellowshipDisclosure: PATENT Royalties from Samsung for dosimetry algorithm

SU-E-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU values were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken ofmore » the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation treatment planning accuracy.« less

WE-G-217BCD-07: Implementation and Evaluation of Helical On-Board CBCT and Exact Image Reconstruction.

Longitudinal coverage of CBCT, which is 17 cm for head scan and 15.5 cm for body scan, is not enough to cover the entire PTV for over 90% of head/neck and gastrointestinal/genitourinary/gynecologic patients if lymph nodes are involved. Helical CBCT, which was accomplished using external beam LINAC in its research mode, is one promising way to extend the CBCT longitudinal coverage. Aim of this study is to compare Katsevich's exact algorithm with traditional FDK algorithm for helical CBCT image reconstruction. CBCT projection raw data were acquired on a TrueBeam LINAC machine (Varian Medical Systems) in the research mode in helical trajectories that encompass a 360 degree rotation, 25 cm pitch, 100 kVp, 80 mA, and 25 ms, with a Catphan 600. Reconstruction was done with Katsevich's exact and FDK approximate algorithms. Scatter correction, beam-hardening correction, and non-uniform gantry angle correction, are performed on projection data to reduce artifacts and noise. Image qualities (CT number accuracy, uniformity, SNR) were evaluated and compared between the reconstruction algorithms. Images reconstructed by Katsevich's algorithm show better qualities, compared to ones by FDK algorithm and HU numbers have higher uniformity and accuracy. The HU-density calibration curve closely conforms to the manufacturer recommended values. The level of noise computed as the standard deviation in the phantom uniform region is 28.07 for the Katsevich algorithm, compared to 44.64 for the FDK algorithm. Katsevich's exact reconstruction algorithm provided better image qualities than FDK for helical CBCT scans. This result will very useful for our ongoing investigation of helical CBCT, which would lead to improvement of CBCT longitudinal coverage of PTV and would be essential for future image-guided adaptive radiation therapy applications. Varian Research Agreement with Washington University in St. Louis.

SU-E-T-146: Uncertainty of Stopping Powers of Tissue Equivalent Materials in Uniformly Scanned Proton Beam

Purpose: To quantify uncertainties associated with the extraction of CT HU to stopping power conversion curve for tissue equivalent materials in uniformly scanned (US)proton beams. Methods and Materials: The Philips Gemini TF Big Bore PET/CT scanner at the Hampton University Proton Therapy Institute (HUPTI), was used to extract the HU numbers for several tissue equivalent materials in the CIRS M062 phantom. Protonstopping power for each material was extracted by measuring the range change with and without the material, in a USproton beam pristine Bragg peak, and comparing to its physical thickness. The in‐beam measurements were performed using a Multilayer Ionization Chamber device (IBA Dosimetry, Zebra). Data were analyzed using both IBA OmniPro Incline and an in‐house software analysis package. Several proton beam energies were used: 143 MeV, 175 MeV, and 210 MeV. For each material and energy the difference between measured and predicted value of the stopping power was quantified. Results: The difference between measured and calculated stopping power with proton energy was found to be within 1–2.5 percent. The upper value of this variation was added to the machine specific systematic error of the CT HU number and quantified as the uncertainty of the CT HU to protonstopping power conversion curve. It was added to the total uncertainties (proton range and lateral profile), when PTV margins were implemented in the TPS. Conclusions: The relative linear stopping powers of 9 different tissue equivalent materials were measured using a range of uniformly scanned proton beam energies. These values were compared with predicted stopping powers calculated using current prescriptions and quantified as uncertainties of the CT HU to protonstopping power calibration curve. This work supports the accuracy of the protonstopping power implementation in the TPS and implicit the accuracy of patient treatment at HUPTI.

SU‐C‐110‐05: Analysis of Intra‐ and Inter‐Fractional Range Variations to Fiducials in Proton Radiotherapy of Liver Tumors

Purpose: To quantify radiological pathlength variations to fiducials in proton beam treatment of liver tumors. Methods: Serial 4DCT scans of 10 patients with primary liver tumors were analyzed. The water equivalent pathlength (WEL) was quantified from entrance surface to radio‐opaque clips 1) for different respiratory phases 2) for serial 4DCT scans 3) for each treatment angle (typically AP or PA and a single lateral field) 4) for different immobilization methods. WEL measurements to fiducials is well defined, Vs range to the distal surface of a deformably registered target, but results in fewer measurements (typically 3 clips). A statistical analysis of the mean range variations and spread is performed. Results: AP range at T50 to clips is reproducible from day to day with a mean variation of 1.8mm, SD 1.3mm. Lateral field range variations from day to day at T50 were 1.3mm SD 2.6mm. Range variations at inhale were more variable, with AP T00 mean WEL variation of 3.5mm SD 4.4mm and lateral mean variations of 3.2mm SD 1.7mm. An 8mm lateral range variation was observed in one patient. Range variation during respiration was also studied. The mean AP and lateral range variation was 3mm SD 2.4 and 4.1 mm SD 2.1mm. A 13mm variation was observed in one patient, and attributed to clip motion during respiration without significant change in the entrance surface. Conclusions: Several sources of range uncertainty are routinely included in treatment range determination for proton therapy. These include uncertainties in CT HU numbers, relative stopping powers of tissues, compensator misalignment, etc. Organ motion is explicitly taken into account in the aperture plane, but not in the beam direction. This study elucidates the magnitude and causes of range variations to well defined points. Inclusion of this uncertainty should be considered in determining treatment range.The project described was supported by Award Number P01CA021239 from the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health.

TU‐D‐AUD‐06: Cone Beam CT Number Correction Method for Accurate EBRT Dose Calculations

Purpose: Benchmark a method for correcting CBCT Hounsfield numbers in support of accurate dose calculations. Method and Materials: Cone beam CT (CBCT) and Fan Beam CT (FBCT) scans of three phantoms: Head, Thorax and large solid water cylindrical ‘pelvic’ phantom are acquired under identical setup conditions. CBCT images are then modified by a step‐function correction method, descretizing the Hounsfield units to five discrete CT numbers for the thorax, three discrete CT numbers for HN and Pelvic anatomies. The groups include the three main ranges of 0 HU for gas/air, 1000 HU for water/muscle and 2000 HU for bone. The FBCT, CBCT and corrected CBCT scans for each body site surrogate (HN, lung and pelvis) are used to compute EBRT plans consisting of an IMRT HN, SBRT lung and a prostate IMRT plan, respectively. The CBCT and corrected CBCT plans are paired with the corresponding FBCT‐based plans to perform comparisons using dose difference analyses, DTA analyses and gamma‐analyses. The criteria used are 0.2cm for DTA, 2.0% of maximum dose for dose difference and 1.0 for gamma. Results: Compared with raw CBCT‐based plan, this correction method reduces gamma by about 0.2, reduces DTA by about 0.1 cm and reduces dose difference by about 1% for lung and pelvis. The passing rate of gamma, DTA and dose difference also improved significantly. For HN, with and without correction both give excellent results, which may be due to the fact that the HU numbers or raw CBCT is much closer to those of FBCT for HN than those for lung and pelvis. Conclusion: The HU correction method presented herein effectively improves the accuracy of dose calculation for CBCT‐based treatment plan, supporting CBCT as a viable imaging modality for accurate EBRT dose calculations.

Wooden Foreign Bodies in CT

CT findings in 2 patients with a wooden foreign body in the orbital region soft tissue, and a series of CT measurements of wooden elements are presented. The wooden foreign bodies presented low HU numbers in CT and were initially interpreted as a gas collection. Different species of trees presented a large spectrum of densities, varying from the -550 HU of pine up to the +289 HU of ebony. The density of a spruce plank increased along with water-logging from -470 HU to -86 HU in 4 weeks, and peak enhancement up to 106 HU was found in the layer closest to the surface. It was concluded that a wooden foreign body in soft tissues may present CT patterns simulating materials as different as a gas bubble or a bone fragment.

Wooden Foreign Bodies in CT

CT findings in 2 patients with a wooden foreign body in the orbital region soft tissue, and a series of CT measurements of wooden elements are presented. The wooden foreign bodies presented low HU numbers in CT and were initially interpreted as a gas collection. Different species of trees presented a large spectrum of densities, varying from the −550 HU of pine up to the +289 HU of ebony. The density of a spruce plank increased along with water-logging from −470 HU to −86 HU in 4 weeks, and peak enhancement up to 106 HU was found in the layer closest to the surface. It was concluded that a wooden foreign body in soft tissues may present CT patterns simulating materials as different as a gas bubble or a bone fragment.

Wooden Foreign Bodies in CT

CT findings in 2 patients with a wooden foreign body in the orbital region soft tissue, and a series of CT measurements of wooden elements are presented. The wooden foreign bodies presented low HU numbers in CT and were initially interpreted as a gas collection. Different species of trees presented a large spectrum of densities, varying from the -550 HU of pine up to the +289 HU of ebony. The density of a spruce plank increased along with water-logging from -470 HU to -86 HU in 4 weeks, and peak enhancement up to 106 HU was found in the layer closest to the surface. It was concluded that a wooden foreign body in soft tissues may present CT patterns simulating materials as different as a gas bubble or a bone fragment.