A Neonatal Phantom for CR and DR Quality Assurance. 25 april 2008 ljrutz ncaapm 1

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1 A Neonatal Phantom for CR and DR Quality Assurance 25 april 2008 ljrutz ncaapm 1

2 Acknowledgements Research supported by an NIH STTR Grant # 2R42HD Phases 1&2 Gammex, Inc. Grantee Washington University, St. Louis, MO 25 april 2008 ljrutz ncaapm 2

3 Washington University Steven Don Pediatric Radiologist, PI Bruce Whiting Imaging Physicist, Co-investigator Parinaz Massoumzadah Imaging Physicist Glenn Fletcher Medical Physicist Charles Hildebolt Statistician Ruth Holdener Technologist Summer students 25 april 2008 ljrutz ncaapm 3

4 Participating University Investigators Duke University Don Frush Pediatric Radiologist Ehsan Samei Imaging Physicist Henry Ford Michael Flynn Imaging Physicist Oregon Health Science University Katharine Hopkins Pediatric Radiologist Paul Brown Medical Physicist 25 april 2008 ljrutz ncaapm 4

5 Gammex, Inc. R&D, Engineering & Production Staff Disclosure L. Rutz currently contracted consultant for Gammex, Inc 25 april 2008 ljrutz ncaapm 5

6 Promise of Computed Radiography Exposure Reduction High sensitivity of the image plates would allow reduced patient exposure. Retakes resulting from under and over exposures would be eliminated. CR maps the exposure to the proper gray level. Improved Image Quality Intelligent image processing would allow optimization of image information. Image processing could be customized to the preference of the radiologist. Spatial frequency enhancement would improve visibility of fine details. Contrast enhancement and selection of display parameters would optimize visualization of low contrast information. Great Appeal to Pediatric Radiologists 25 april 2008 ljrutz ncaapm 6

7 Computed radiography is different from screen/film radiography. The CR system uses a-priori knowledge of the anatomy to optimize the image. Application of gray-scale mapping and spatial frequency enhancement. Histogram analysis plays a key role in the image processing. Selection of data to be treated as anatomy. Scaling of data into proper display range. 25 april 2008 ljrutz ncaapm 7

8 Grayscale Mapping 25 april 2008 ljrutz ncaapm 8

9 Histogram Based Data Selection 25 april 2008 ljrutz ncaapm 9

10 Effect on Routine Quality Assurance Image quality assessment now includes the effects of image processing. Image processing depends on a-priori knowledge of the anatomy being imaged. Tissue attenuation characteristics. Size Expected histogram shape. 25 april 2008 ljrutz ncaapm 10

11 Semi-anthropomorphic. Stylized, does match histogram. Technical Phantoms Require test protocols More creative anthropomorphic Phantoms Hard to use more than once. 25 april 2008 ljrutz ncaapm 11

12 To test all aspects of the system, including the effect of the image processing. We need a phantom that can mimic both anatomic structure and radiographic properties of the tissue composition. To see this. You need this april 2008 ljrutz ncaapm 12

13 Solution? 25 april 2008 ljrutz ncaapm 13

14 OK, Back to the Drawing Board Bruce Lois Steve? Design a New Phantom Build a Prototype Test against Physics Requirements Test against Clinical Requirements. 25 april 2008 ljrutz ncaapm 14

15 Why build a Neonatal chest phantom Importance of CR for dose reduction in Pediatric Radiology Technical difficulty of imaging neonates with CR Small size of structures, and similar tissue attenuation characteristics, challenge the technical limits of the system. Image quality factors of resolution and signal to noise ratio are stressed in neonatal imaging. If a system tests well for neonatal imaging it should be capable of good image quality in general. 25 april 2008 ljrutz ncaapm 15

16 Requirements Histogram must mimic a real neonate at all clinically relevant beam qualities. Size, shape and structures must be close enough to real neonate to give radiologists and technologists a visual reference. Should have the ability to demonstrate image quality using clinical protocols, not test settings. Should provide a means of demonstrating the effects of changes to input and image processing parameters. There should be some imaging challenge so that image degradation or relative inferiority could be determined. 25 april 2008 ljrutz ncaapm 16

17 Creating the Physical Model Used CR images and CT scans of cadavers. established sizes and major tissue types. Used anatomical drawings, film images and reference materials to refine the structures appearances, especially the bronchial tree. 25 april 2008 ljrutz ncaapm 17

18 material density in g/cc Creating the Tissue Types Selection or creation of tissue mimicking materials. Chemical Constituents %H %C %N %O %Na %Mg %S i %P %S %C l %K %C a Total newborn cortical bone newborn 1.18 femur fetal lung adult lung newborn muscle Inner Bone CB2-50% LN LN Muscle Used published references for neonate: e.g. ICRP april 2008 ljrutz ncaapm 18

19 Computational Comparisons Predicted Transmission Fractions as a function of kvp Predicted Transmission Fractions as a function of kvp fractional transmission kvp CB2 50% newborn femur (ICRU) newborn cortical bone (ICRU) IB456 fractional transmission kvp LN450 Adult lung ICRU fetal lung Predicted Transmission Fractions as a function of kvp fractional transmission muscle newborn muscle kvp 25 april 2008 ljrutz ncaapm 19

20 Validation of Computation Muscle at 90 kvp fractional transmission Bone at 90 kvp mm Bone calc meas fractional transmission mm muscle material 90 kvp calc 90 kvp meas Lung material 90 kvp y = e x fractional transmission y = e x 25 april 2008 ljrutz ncaapm 20 mm Lung material calc meas Expon. (calc) Expon. (meas)

21 Refining the Model Lung material transmission spectra at 90 kvp photons kev lung, muscle, rib lung, muscle, rib lung, muscle, rib m us cle, air m uscle, vertebra,air unattenuated spectrum Predicted transmission comparison for selected sections of the neonatal phantom using LN450 and NNLN4 Sections are denoted as AA, BB etc to correspond to dimensions of draft drawings. Section C'C' is the cross section half way between DD and EE. The assumption is that the NNLN4 will have a physical density of added filtration Aluminum LN450 NNLN4 Muscle Bone Air Total cm^2/gm cm^2/gm cm^2/gm cm^2/gm cm^2/gm cm^2/gm t in cm t in cm t in cm t in cm t in cm t in cm lung, muscle, rib AA lung, muscle, rib BB lung, muscle, rib CC muscle,air DD muscle, vertebra C'C' april 2008 ljrutz ncaapm 21

22 Validating the Fit Early Prototypes B a c k g r o u n d M e a n Phantom 1.3 Phantom 1.3 Phantom 1.3 Phantom 1.3 Phantom 1.3 and Cadavers Green plus = grams Yellow circle = grams Red dot = grams Phantom 1.3 Phantom 1.3Phantom 1.3 S t a n d a r d D e v i a t i o n Phantom 1.3 Phantom 1.3 Phantom 1.3 Phantom 1.3 Phantom 1.3 and Cadavers Green plus = grams Yellow circle = grams Red dot = grams Phantom 1.3 Phantom 1.3 Phantom 1.3 Phantom kev kev

23 Validation: Phantom adequately represents a 1kg to 2kg neonate both anatomically and radiographically. Thirty clinical images were compared to phantom images obtained using identical technique factors at three sites on three different CR systems. The raw image data were analyzed using ImageJ. Pixel values of the whole body, right lung base, heart, liver, stomach bubble, humeral metaphysis, muscle, subcutaneous fat and pneumothorax were normalized relative to direct exposure (air) for each image. The results were plotted against the weight distribution of the patients. 25 april 2008 ljrutz ncaapm 23

24 Final Design Validation Patient 3 Region Area Mean StdDev Min Max mr Attenuation Background lead marker right lung base heart liver stomach bubble humeral metaphysis muscle subcutaneous fat pneumothorax Phantom 1.1 Region Area Mean StdDev Min Max mr Attenuation bkground t5 vertebra stomach bubble heart by t t6 rib over lung t6 rib over heart liver uner rtlung last vertebra, stom bub lung/t april 2008 ljrutz ncaapm 24

25 Validating the Fit Later versions, larger data set. Kodak Whole Body Mean Value Phantom Weight PNTX Normal RDS Fit Normal Fit PNTX Fit RDS Fit All

26 Phantom Weight (in kg)* Center Heart Thorax T3 rib Humerus Wash U OHSU Duke *based on log neonate weight and log size 25 april 2008 ljrutz ncaapm 26

27 Validating the Histogram Equivalence Whole body histograms made from clinical images. Use ImageJ. Distributions of size and technique factors. Included best approximation of thorax area to match phantom. 25 april 2008 ljrutz ncaapm 27

28 Histogram Comparisons comparison of histogram for 10 normal neonates and phantom frequency of pixel pixel value bjc_01 bjc_04 bjc_05 bjc_06 bjc_07 bjc_08 bjc_09 bjc_10 bjc_11 bjc_12 phantom_with raw rad normalized histogram comparison for 10 normal neonates and phantom bjc_01 frequency as fraction of the maximum frequency pixel value as fraction of the mean bjc_4 bjc_5 bjc_6 bjc_7 bjc_8 bjc_10 bjc_11 bjc_12 ph_04 with raw radiation

29 Nearly Final Phantom Rib, spine, clavicle and part of humerus Bronchial tree Normal Lungs: with pneumothorax Torso with heart, stomach bubble, fat layer. Hyaline Membrane Disease Lungs without pneumothorax. 25 april 2008 ljrutz ncaapm 29

30 Adding Clinical Relevance to the QA Process Simulated disease processes are used as indicators of system performance. pneumothorax for resolution. hyaline membrane disease for noise Both disease states are of particular concern in neonatal imaging. Relates quality assurance testing to diagnostic value. 25 april 2008 ljrutz ncaapm 30

31 Pneumothorax Common problem in the NICU. Signs are a lucent (black) area against the lung. Can be any size or shape, from a fine border along the edge to a balloon sized shadow. Often also shows a very fine opaque (white) line along the lung border. This is the pleural thickening line that results from the compression of the lung as the air pushes against it. Typical size of the line is on the order of 0.2 mm. 25 april 2008 ljrutz ncaapm 31

32 Pneumothorax Test Object 25 april 2008 ljrutz ncaapm 32

33 Hyaline Membrane Disease Radiologists have difficulty distinguishing between healthy and hyaline membrane disease at low exposures. ALARA is important. Attempts to avoid retakes for noise resulted in Dose Creep. Use of the HMD Lung to assess lower limit of exposure has been demonstrated. As noise limit is approached, the HMD lung texture becomes indistinguishable from the normal lung and muscle tissue. 25 april 2008 ljrutz ncaapm 33

34 Demonstration of use of the neonatal phantom to determine minimum radiation exposure. a: 1mR b: 0.25mR c: 0.1mR 25 april 2008 ljrutz ncaapm 34

35 Summary Simple and effective phantom for routine quality assurance of CR. Capable of full system assessment using clinical imaging protocols. Anticipate other applications. Teaching Acceptance Testing Evaluation of new imaging techniques, e.g. filtration, processing parameter selection. 25 april 2008 ljrutz ncaapm 35