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The New Standard of Care in Medical Imaging
Lung Nodule Identification
with iCRco CBCT
Compiled by Eddie Schultz
Goals
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To be able to identify and locate 100% of phantom lung nodules using iCRco CBCT.
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To enhance patient outcomes by assisting radiologists in lung nodule detection.
Materials
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Large “LUNGMAN” chest phantom
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This anthropomorphic chest phantom has lifelike features including synthetic bones made of epoxy resin and soft tissue structures including lungs, heart, and alveoli made of polyurethane.
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Dimensions: 43x40x48cm, chest girth of 94 cm
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Arms in the overhead position for accurate CT simulation
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Model: PH-1 Multipurpose Chest Phantom N1 “LUNGMAN”
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SN: 20K-10
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Simulated lung nodules.
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Ranging in size from 3mm-12mm in diameter and in Hounsfield Units from +100 to -800. For reference, bone has a Hounsfield unit from 200 to 1000, water has a Hounsfield unit of 0, and air has a Hounsfield unit of -1000.
iCRco Claris XT CBCT
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Equipped with state of the art software XC and utilizing cone beam CT, the Claris XT was used take CT of the chest phantom with lung nodules inserted.





Setup for Images
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Using a 2x2 CT drive mode with a pulse rate of 12fps, tube potential of 12 lung nodules of varying attenuation and size were inserted at random into the lungs and placed on the CT examination table directly between the x-ray source and panel.
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Images were taken 80 kilovolts, exposure time of 15ms, and 133 milliamperes for a mAs of 2.0.
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This was determined to be the most effective way to take images after experimenting with different drive modes, tube potential, exposure time, milliamperes, and mAs.
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This CT method also limits the amount of time the patient will be asked to hold their breath. The Claris XT is able to take all images for this drive mode in only 30 seconds.
Lung Nodule Phantom Identification
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After obtaining the CT images, one can see 100% of lung nodule phantoms with the human eye.
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The following are images of nodule phantoms from 2 different scans in order to show the methods for finding all of them.
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All twelve nodule phantoms were found on all 3 scans. They are not all displayed here. The purpose here is to show the ease in which we were able to locate them.




Slide Show
(CLICK ARROWS TO VIEW MORE IMAGES)




Lung Nodule Phantom Identification (CONTINUED)
For smaller and more challenging lung nodules, such as this one, it is helpful to see them using a multi-planar reconstruction and maximum image projection. The next slide shows a graphic of this particular lung nodule from multiple viewpoints with thicker slices to make it easier to spot.


Lung Nodule Phantom Identification (CONTINUED)
This one is also very difficult to see. This is likely due to the very low Hounsfield unit associated with this lung nodule phantom. The next slide shows a multiplanar and maximum image projection view that confirms the finding. This particular lung nodule phantom has a diameter of 5mm and a Hounsfield unit of -800.

Lung Nodule Phantom Identification (CONTINUED)
This one is also very difficult to see. This is likely due to the very low Hounsfield unit associated with this lung nodule phantom. The next slide shows a multiplanar and maximum image projection view that confirms the finding.
Lung Nodule Phantom Identification (CONTINUED)
This Nodule is exceedingly challenging to see. This is the lung nodule phantom with Hounsfield unit -800 and diameter 3. The following slide contains another video that will attempt to show the multiplanar view with maximum image projection of this nodule.
Comparison and Relevance
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In December 2013, a study titled “Optimal Dose Levels in Screening Chest CT for Unimpaired Detection and Volumetry of Lung Nodules, with and without Computer Assisted Detection at Minimal Patient Radiation” was published in PLOS ONE, a peer reviewed journal.
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This study used the exact same lung phantom that iCRco is using to located lung nodule phantoms.
This study used lung nodule phantoms ranging from 5-12mm in diameter and ranging in Hounsfield unit from -630 to +100. -
This means that the iCRco study had a broader range of nodule phantoms, including smaller nodule phantoms with lower attenuation values than those used in the 2013 study.
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The 2013 study took images using a 64-row multi-detector CT scanner Somatom Sensation 64 made by Siemens and located in Forchheim, Germany.
These are images taken by the Siemens CT in Germany for the 2013 study. The lung nodules are circled.

Results
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iCRco Claris XT is able to capture images of lung nodule phantoms of varying size and attenuation, including nodules 3mm in diameter with -800 Hounsfield units.
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All nodule phantoms can be easily seen by any person with limited skills and training.
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iCRco Claris XT can obtain these images in a very short amount of time. The patient only needs to hold their breath for 30seconds for image capture to complete.
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Nodules located near the top and bottom of the lungs are challenging to see due to the nature of our cone beam reconstruction. This challenge will be overcome as our reconstruction algorithms improve.
Moving Forward
iCRco is working with an AI company to implement an AI for detecting lung nodules. This process can be completed in 1-7 minutes, depending on computer capabilities. In its first generation, it has a 65% success rate.
Bonus AI Images


Bonus Research
iCRco’s Claris XT is also capable of identifying COVID-19. Using COVID phantom webs placed in the lungs of the phantom, we are able to locate the COVID with ease.
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Some initial radiation exposure tests have been done on the iCRco CBCT. There are still more tests to be run, but initial results have a positive outlook.
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A RaySafe X2 R/F Sensor was positions inside the chest unit (same phantom as before), this time with lungs removed.
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All tests were done with a 2x2 fast CT drive mode
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Two tests were done at 80kV with 2.0mAs (same as the tests before)
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One test was done at 100kV and 1.5mAs
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One test was done at 90kV and 1.75mAs
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To the right are the results from the RaySafe R/F Sensor

