Introduction:
Cone-beam CT (CBCT) is an imaging system which offers three-dimensional (3D), multiplanar images and has many advantages over computed tomography (CT) including shorter acquisition times for the resolution desired in dentistry, lower radiation dose to the patient, reasonable price and higher spatial resolution but CBCT scanners are unable to display actual Hounsfield units (HU) similar to medical CT. In CT scan, to show the image that represents the density of the tissue Hounsfield Unit is proportional to the degree of x-ray attenuation and it is allocated to each pixel. In CBCT systems displayed gray levels are arbitrary and so variable, so the derived density provided less than meaningful data and the ability to assess the density or quality of bone is limited. The purpose of the present study was to present a clinical study demonstrating a method to derive Hounsfield units from gray levels in cone beam CT (CBCT).
Materials and Methods:
For the evaluation of CBCT gray values, a new versatile quality control tool of dental Cone- Beam CT, Pro-Dent CT mk II phantom, which consists of a main PMMA cylinder that houses modules with different test objects was used. Four CBCT devices were used for the scanning of the phantom: CS8100, CS9300(Carestream Health, New York, NY), New Tom GIANO (Quantitative Radiology, Verona, Italy), Vatech Pax-i3D (Hwaseong-si, Gyeonggi-do, Korea). The reconstructed data were exported as Digital Imaging and Communications in Medicine (DICOM) and analyzed with On Demand 3DH by Cybermed, Seoul, Korea and ImageJ as an image processing toolkit. The relationship between gray levels and linear attenuation coefficients in various kV and mA was investigated.
Results:
The results indicated a strong linear relationship between the gray scales in CBCT and HU in CT using the standard definition HU = (µmaterial – µwater)/(µwater) × 1000. This made it possible to calculate Hounsfield units from the measured gray levels. Uncertainty in determining effective energies for each of CBCT systems resulted in unrealistic effective energies and significant variability of calculated CT numbers. Linear regression (0.802<R2<0.981) from gray levels directly to Hounsfield units at specified energies resulted in greater consistency. Conclusion:
Considering the fact that CBCT gray levels are inaccurate to rely upon for decisions on implant placement. HU can be derived from the gray levels in dental CBCT scanners using linear attenuation coefficients as an intermediate step. This study presented a method to convert gray levels in CBCT imaging into meaningful HU. Establishment of meaningful HU for CBCT will open new possibilities for clinicians in implant planning, diagnosis, surgical interventions, treatment planning, 2D and 3D reconstruction of images.