A Guide To Personalized CT Imaging In RT
The scientific overlay is not that of the individual pictured and is not froma device of Siemens Healthineers. It was modified for better visualization.DirectDensity cookbookA guide to personalized CT imaging in orusers ofSOMATOMCT systems
DirectDensity cookbook · Foreword and ContributorsForewordRadiation oncology is experiencing growth inthe use of personalized imaging for treatmentplanning and this trend has been embraced byphysicists and physicians alike.Clinical expert users have investigated andimplemented novel image optimizationtechnologies and we are pleased to be ableto share these with you.This cookbook is intended to propagatethis information to users of DirectDensity onSOMATOM CT systems. It presents a seriesof study protocols and practical tips and tricksfrom implementation to clinical routine, so thateveryone can benefit from the clinical experts’experience. The information provided here canhelp your entire clinic to optimize workflowsand provide the best imaging possible to cancerpatients undergoing radiation therapy.We look forward to hearing your feedbackand suggestions, so that we atSiemens Healthineers can continue improvingand helping you care for your patients.Contributors2Manuel AlgaraHead of Radiation OncologyDepartment, Hospital del Mar,Universitat Autònoma,Barcelona, SpainEnric Fernández-VelillaMedical Physicist,Hospital del Mar,Barcelona, SpainNuria RodríguezRadiation Oncologist,Hospital del Mar,Universitat Pompeu Fabra,Barcelona, SpainOscar PeraMedical Physicist,Hospital del Mar,Barcelona, SpainJaume QueraMedical Physicist,Hospital del Mar,Barcelona, SpainRafael JimenezRT Supervisor,Hospital del Mar,Barcelona, SpainSoufian AudiaHead Medical Physicist,Chirec hospital group,Brussels, BelgiumTakeshi KamomaeClinical Assistant Professorand Medical Physicist,Nagoya University Hospital,Aichi, JapanMasaru NakamuraChief RadiologicalTechnologist andMedical Physicist,Aichi Medical UniversityHospital, Aichi, JapanNaoki KanedaRadiological Technologist,Aichi Medical UniversityHospital, Aichi, JapanKazuhiko NakamuraRadiological Technologistand Medical Physicist,Aichi Medical UniversityHospital, Aichi, JapanYoshitaka MinamiRadiological Technologistand Medical Physicist,Aichi Medical UniversityHospital, Aichi, JapanFiras MourtadaChief of Clinical PhysicsRadiation Oncology,ChristianaCare's Helen F. GrahamCancer Center & ResearchInstitute, Newark, USA
Content · DirectDensity cookbookContentBenefits of image optimization and its challenges in RT4Three key points about DirectDensity5Technical implementationAimStep 1: Protocol setupStep 2: Phantom setupStep 3: Acquisition for calibration phantomStep 4: Image analysisStep 5: Calibration curve evaluationStep 6: Calibration curve generationStep 7: Commissioning (TPS registration)66677881011Dosimetric evaluationAimStep 1: Series generationStep 2: Dose calculationStep 3: Dose volume histogram analysis (Dmax, Dmin, mean)Step 4: Point-to-point analysis (optional)Step 5: Check other clinical areas12121212141415DirectDensity workflow in clinical routineAimStep 1: AcquisitionStep 2: ReconstructionStep 3: Patient marking and contouringStep 4: Treatment planning171717181919Clinical cases20Conclusion233
DirectDensity cookbook · Benefits of image optimizationBenefits of image optimization and itschallenges in RTWhen performing a CT examination, the tube voltage is typically adjusted to the patient (e.g.body size, body part.) in order to maximize the image quality. In Radiation Therapy, CT imagesare transferred to the treatment planning system with two purposes, 1) contouring of target and2) dose calculation where the CT parameters – in particular tube voltage – have been calibratedto convert the image intensity to an electron density. For the first purpose,an essential factorfor CT image quality is the tube voltage expressed as the kV value. Siemens Healthineers hasdeveloped CARE kV, which allows you to automatically select optimal tube voltage and effectivetube current to provide a predefined image quality level at the technically lowest possibleradiation dose. Optimization is based on the patient-specific attenuation estimation fromtopogram data. Image quality is predefined by the quality ref. mAs value for a reference kV valuefor a standard patient. CARE kV can then adjust the actual effective mAs value depending onactual patient size and tube voltage. The objective is to obtain the same image quality as for thestandard patient. Image quality is measured based on a CNR (contrast-to-noise ratio) relevant fora certain clinical use case. For radiation treatment planning, and especially for advanced therapiessuch as SRT, the technology can help increase confidence in contouring.Attenuationdata fromtopogram70 kV80 kV100 kVClinicalusecase120 kV140 kVIdeally, the optimized kV setting suggested by CARE kV should be used in fully automated mode.However, due to the second purpose, but this would imply that the treatment planning is able toaccept any tube voltage. Even when this is possible, it is is usually very cumbersome and prone toerror due to the necessity of having multiple calibration curves. This is why Siemens Healthineershas introduced DirectDensity.Image impression at 120 kV (left) and 100 kV (right) in a brain case with the same reconstruction parameters.4
Three key points · DirectDensity cookbookThree key points about DirectDensity1. What is DirectDensity?CT images are transferred to the treatment planning system with twopurposes, 1) contouring of target and 2) dose calculation. For the secondpurpose DirectDensity is an innovative technology that potentially enablesthe use of a single calibration curve for all tube voltage and beam filtrationsettings. It is available for selected CT and PET CT systems1.2. What does DirectDensity do?DirectDensity removes the constraint of a fixed tube voltage settingand thereby enables the unconstrained use of tube voltage optimizationsuch as for obese patients (with high tube voltage for low noise imaging),breast cancer patients (with low tube voltage for good CNR), pediatric patients(with low tube voltage for good CNR). It results in high-quality optimizedimages and a standardized workflow.3. What are the potential benefits in RT?Contouring quality and consistency depends on image quality. DirectDensityremoves the constraints on optimal tube voltage adapation by allowing CAREkV or the user to choose the optimal tube voltage for each patient.Clinical kV usage after100%100%80%80%usage [%]usage [%]Clinical kV usage before60%40%20%0%7080100120Tube voltage [kV]14060%40%20%0%7080100120140Tube voltage [kV]Clinical kV usage before (left) and after (right) CARE kV implementation(Source: Based on customer usage measured with Siemens Utilization Management)1 Please contact your representative of Siemens Healthineers for further information about availability.5
DirectDensity cookbook · Technical implementationTechnical implementationAimThe goal of this step is to define the scan protocols for algorithm validation.With the setup (example from Hospital Del Mar, Barcelona, Spain), the following five protocolswere adapted to the DirectDensity (DD) workflow:1) Brain 2) Head and Neck 3) Breast 4) Abdomen 5) ProstateStep 1: Protocol setupClinical areaDefault protocolParameters to be changed Important remarksBrainRT Brain1st recon: I30 / Br3812nd recon: F30 / Sd40 (DD)Head and NeckBreastAbdomenProstateRT HeadNeckRT BreastRT AbdomenRT PelvisTips: CARE kVCARE Dose4D:2 YesCARE kV(semi mode/manual kV)1st recon: I30 / Br382nd recon: F30 / Sd40 (DD)CARE Dose4D: Yes1st recon: I30 / Br382nd recon: F30 / Sd40 (DD)CARE Dose4D: Yes1st recon: I30 / Br382nd recon: F30 / Sd40 (DD)CARE Dose4D: Yes1st recon: I30 / Br382nd recon: F30 / Sd40 (DD)CARE Dose4D: YesCARE kV(semi mode/manual kV)CARE kV(semi mode/manual kV)CARE kV(semi mode/manual kV)CARE kV(semi mode/manual kV) CARE kV is a dose-saving mechanism that guarantees a predefined image quality.Semi mode or manual kV is required in order to evaluate CT values for different tube voltages.SOMATOM go. platformSOMATOM Definition AS Open/Confidence/Drive“off”CARE Dose4D off and manual kV and mAs selection“manual kV”CARE Dose4D on and CARE kV similar to “semi” mode of SOMARIS/7“full”CARE Dose4D on and CARE kV similar to “auto” mode of SOMARIS/7"full" doesn't allow you to select tube voltage to change. After the evaluation is complete,CARE kV may be set to full auto mode.162 econstruction kernels may vary based on software versions.R C ARE Dose4D is an automatic exposure control based on attenuation of the projection in real time.
Technical implementation · DirectDensity cookbookStep 2: Phantom scan setupThe aim of this step is to find out whether the DirectDensity algorithm provides a calibrationcurve proportional to electron density regardless of the acquisition conditions. To do this,the Advanced Electron Density Phantom from Sun Nuclear was used. Acquisitions are performedusing both the small and the large phantom (this allows you to check how the patientthickness affects the Hounsfield units). The complete set of images acquired for calibrationis composed of four series for each tube voltage setting with two different reconstructions(standard reconstruction and DirectDensity reconstruction) for two different phantoms(small and large phantom).Calibration phantomVarious calibration phantoms are available on themarket. We used the Advanced Electron Density Phantomfrom Sun Nuclear, featuring Gammex technology1 toevaluate DirectDensity for this cookbook.The features of this phantom are as follows: Adherence to ICRU-44 and ICRP material performance Expanded phantom size for wide-beam systems thatcan be used for CBCT as this phantom is thicker thanthe previous version Inserts include Air, LN-300 Lung, LN-450 Lung, HEGeneral Adipose, HE Breast 50:50, HE Solid Water,Water, HE Brain, HE Liver, HE Inner Bone, 30% CaCO3,50% CaCO3, HE Cortical BoneStep 3: Acquisition for calibration phantom1) Place a Gammex phantom the large(Advanced Electron Density Phantom) on the table.2) Adjust the position of the phantom to thecenter of the bore and align it with the scan axis(use gantry lasers and markings or distinctfeatures of the phantom).3) Select the RT Abdomen protocol.4) Set up scan and make sure that the scan rangeis centered on the phantom.5) Perform repeated scans for all the tube voltages(e.g., 80 kV, 100 kV, 120 kV, and 140 kV).6) Repeat all the scans with the large phantom for:- Breast protocol,- Prostate protocol.7) Repeat all the scans with the small phantom for:- Head and Neck protocol,- Brain protocol.1Positioning of the Advanced ElectronDensity Phantom from Sun Nuclear ammex is a wholly owned subsidiary of Sun Nuclear Corporation. The Advanced Electron Density Phantom, Model 1467,Gis Siemens PN GA805810.7
DirectDensity cookbook · Technical implementationStep 4: Image analysis1) Open the series in the TPS to measure CT values.2) Use the middle slice position of the Advanced Electron Density Phantom.3) A 2 cm ROI is used on the center of each rod(make sure that the ROI does not cover the edge of the rod).Image analysis using the large phantom (Breast, Abdomen, and Pelvis) and the small phantom (Brain and Head andNeck). The edge of the inserted material must be avoided, otherwise it introduces uncertainty to the CT values due toovershoot (orange arrows).Step 5: Calibration curve evaluation1) Open Microsoft Excel, or an equivalent program. Enter your measured values into a table1.2) The CT values for different materials using RT Abdomen and the large phantom are shownin the table below.3) Calibration curves at different kV settings with and without DirectDensity are created as below.4) Repeat this step for the different protocols (e.g. use the small phantom for the Brain protocol).Phantom certificateCT value with standard reconstructionCT value with y80 kV(HU)80 0 Lung0.2890.279-698.6-704.6-705.8-705.6LN-450 Lung0.4620.447-532.2-538.3-539.9HE General Adipose0.9620.951-83.1-73.5HE Breast 50:500.9830.969-46.7HE Solid Water1.0220.998Water1.000HE BrainMaterial120 kV140 2539.135.033.431.929.626.729.429.0HE Liver1.0811.05466.063.161.159.850.249.753.553.2HE Inner 68.930% 259.750% 9463.8HE Cortical 6.9797.818100 kV(HU)120 kV(HU)140 kV(HU)100 kV hese steps may also be achieved with RapidCHECK software from Sun Nuclear. Use RapidCHECK with the Advanced ElectronTDensity Phantom to automatically locate and identify the material of each rod, and to streamline the CT-to-Electron Densitytable report.
Technical implementation · DirectDensity cookbookElectron density relative to waterFigure 1A: Calibration curves for RT Abdomen protocol with large phantomwith standard reconstruction1.880 kV1.6100 kV1.4120 kV1.2140 kV1.00.80.60.40.20.0-1,00001,0002,000CT Value [HU]Electron density relative to waterFigure 1B: Calibration curves with DirectDensity1.880 kV1.6100 kV1.4120 kV1.2140 kV1.00.80.60.40.20.0-1,000-50005001,000CT value9
DirectDensity cookbook · Technical implementationStep 6: Calibration curve generation by averaging CT values obtained fordifferent tube voltagesCalculate the average DirectDensity value by averaging the CT values obtained for differenttube voltages for each material. In the example below, we took the average of all four protocols(Breast, Prostate with large phantom, and Head and Neck and Brain with small phantom).Phantom sity80 kV DDimagevalue100 kV DDimagevalue120 kV DDimagevalue140 kV DDimagevalueAverageDirectDensityimage value0.000-993.8-995.4-995.8-996.8-995.5LN-300 Lung0.2890.279-697.2-702.9-703.9-703.6-701.9LN-450 Lung0.4620.447-531.5-537.5-538.9-538.7-536.7HE E Breast 50:500.9830.969-46.3-40.1-36.1-33.2-38.9HE Solid 22.43.52.0HE Brain1.0511.02529.626.729.429.028.7HE Liver1.0811.05450.249.753.553.251.7HE Inner Bone1.2141.164166.8171.8170.9168.9169.630% CaCO31.3321.268245.0255.6260.0259.7255.150% CaCO31.5591.462462.6468.7466.9463.8465.5HE Cortical Bone 1.9241.774812.8816.9806.9797.8808.6
Technical implementation · DirectDensity cookbookStep 7: Commissioning (TPS1 registration)Calibration curve examples from Hospital Del Mar (left) and Nagoya University Hospital (right):The curve should be almost a straight line.1) Log in to the TPS with an administrator (physicist) account2) Go to calibration curve registration(e.g., Eclipse, beam configuration Beam data CT calibration)3) Enter corresponding pairs of average DirectDensity image value and relative electron/physicaldensity values (use air, LN-300 and 450, General Adipose, Breast 50:50, Liquid Water, Brain,Liver, Inner Bone, 30% CaCO3, 50% CaCO3, and Cortical Bone; enter CT value and relativedensity accordingly (see example above))4) Extrapolation of the relative density to 6.0 might be optional (otherwise high-density singlepixel can trigger a warning message that must be accepted every time)25) Check calibration curve – the line should be almost straight (see examples, left)6) Save the calibration curveTips for handling metal implants:1) iMAR (iterative metal artifact reduction) is recommended to minimize metal artifactsin order to improve the certainty of dose calculation and contouring2) Beam placement should not overlap with metal implants3) To avoid warning messages due to high density, please insert 29768 for physical density(19.32 g/cm3)2Using Eclipse from Varian Medical Systems. Procedures may vary depending on the software versions or different TPS systems.Non-natural materials, for example metals and contrast agents like iodine, will decrease accuracy and – as with conventional CTimages – can potentially lead to image artifacts.1 2 11
DirectDensity cookbook · Dosimetric evaluationDosimetric evaluationAimOn Figures (1A, 1B), we showed that varying the acquisition kV has almost no influence on thecalibration curve when the DirectDensity reconstruction kernel is used. Before implementing inclinical routine, we recommend preliminary evaluation with a few clinical cases (e.g., four mostimportant cancer sites, two cases each) in order to double check the dosimetric impact.Step 1: Series generation1) Head and Neck scan with CARE kVwith full mode (in this case, 100 kV)12) Reconstruct two series, one with the standardreconstruction kernel, one with the DirectDensitykernel. If there are predefined scan protocols(see technical implementation step), two adequatereconstructions should already be defined. Referencedata: 100 kV standard reconstruction.Comparison data: 100 kV with DirectDensity.3) Export the two series to the TPS. In the TPS, makesure that the correct imaging device is selected (sothat the TPS uses the appropriate calibration curve).100 kV with DirectDensity (left),and without (right)Step 2: Dose calculation1) Open the images in the TPS with standardreconstruction.2) Contour organs at risk (OAR) and target.3) Copy the contours to the DirectDensityreconstruction.4) Calculate dose on standard reconstruction usingAnisotropic Analytical Algorithm (AAA)2 afteroptimizing a plan or setting some beams3.5) Copy the plan and assign to the correspondingDirectDensity datasets.1212100 kV with DirectDensity (left),and without (right)I f 120 kV is required as reference, repeat the scan with 120 kV, and add reconstruction accordingly. Using Eclipse (Varian Medical Systems).
Dosimetric evaluation · DirectDensity cookbook6) Calculate the new plan on the DirectDensity images and compare the dose with thereference plan (see example above)Tip: Please make sure that the corresponding calibrationcurve is selected when performing dose calculation. For simple analysis, the monitor units (MU) should beequal for both plans.13
DirectDensity cookbook · Dosimetric evaluationStep 3: Dose-volume histograms (DVH) for maximum dose (Dmax),minimum dose (Dmin), and mean doseThe purpose of this step is to compare the DVH dose plan for standard reconstruction andDirectDensity reconstruction. We recommend comparing the Dmax, Dmin, and mean dosefor each volume.DVH comparison between DirectDensity reconstruction and standard reconstruction for following structures.Red PTVPink CervelDose comparison in terms of Dmax, Dmin, and mean dose for each volume.Step 4: Voxel-by-voxel evaluation of dose distributions (optional)For further evaluation, dose distributions of the plans based on the standard reconstructionand the DirectDensity reconstruction can be compared voxel by voxel. For example, youcan use a dose difference frequency histogram. It provides a visualization of the distributionof dose differences between the two plans, as well as the mean and standard deviationof those differences. Within our evaluation, the DirectDensity-based plan shows a goodalignment with the standard/conventional plan.2,000Frequency1,5001,0005000-2 -1.6 -1.2 -0.8 -0.400.4 0.8 1.2 1.6Dose difference (%)142Tips:For voxel-by-voxel evaluation, dosedistributions usually have to be exportedfrom the TPS (usually in DICOM format)and then processed via suitable third-partyapplications capable of reading DICOMimage data (e.g., ImageJ, MATLAB, Python/scipy-stack/pydicom, R). Be aware of anyparameters such as dose-scaling factors;they can be found in the DICOM header.
Dosimetric evaluation · DirectDensity cookbookStep 5: Check other clinical areas.After look
Hospital, Aichi, Japan Naoki Kaneda Radiological Technologist, Aichi Medical University Hospital, Aichi, Japan Jaume Quera Medical Physicist, Hospital del Mar, Barcelona, Spain 2 DirectDensity cookbook · Foreword and Contributors
Reserved/Personalized License Plates-Application For VLIC-4.420 Original Date: 09/28/1990 Revision Date: 07/15/2017 Personalized Plate Policy Violations Create Personalized Message Relinquish Personalized/Reserved Plates Governor Series and Low Number License Plates Customer Requirements-Original/Reissue Front Counter CSR-Original/Reissue
ii. personalized medicine from a regulatory perspective 5 1. defining personalized medicine 5 2. fda's unique role and responsibilities in personalized medicine 11 iii. driving toward and responding to scientific advances 14 1. building the infrastructure to support personalized medicine 16 2. recent organizational efforts 20 iv.
Expanding the Frontiers of Personalized Medicine 9 PART III Evidence Development Despite the extraordinary pace of technological progress in personalized medicine, payers and providers rightly demand evidence demonstrating that personalized medical interventions can be integrated into health systems in ways that deliver both clinical and
"Personalized learning is a way to actually enact the pedagogy we believe in and that kids thrive in," said Tavenner, the founder of Sum-mit Public Schools, a California-based charter network that operates about a dozen of its own personalized-learning schools while licensing its personalized-learning software to hun-dreds of others.
Personalized Learning Visioning Tool Anyone interested in implementing personalized learning, including states, districts, schools, and individuals. Create consensus around the vision for personalized learning in your community; create draft communications to share with your community. Help create, refine, clarify, or communicate your vision for
Personalized learning. There is no single, universally agreed-upon definition of personalized learning (Pane, et al., 2017). That said, the. Aurora Institute's definition succinctly and powerfully incorporates many ideas common to various definitions: Personalized learning is "tailoring learning for each student's strengths, needs and
work/products (Beading, Candles, Carving, Food Products, Soap, Weaving, etc.) ⃝I understand that if my work contains Indigenous visual representation that it is a reflection of the Indigenous culture of my native region. ⃝To the best of my knowledge, my work/products fall within Craft Council standards and expectations with respect to
akuntansi musyarakah (sak no 106) Ayat tentang Musyarakah (Q.S. 39; 29) لًََّز ãَ åِاَ óِ îَخظَْ ó Þَْ ë Þٍجُزَِ ß ا äًَّ àَط لًَّجُرَ íَ åَ îظُِ Ûاَش
