Stability of voxel values in cone-beam computed tomography

Naitoh, Munetaka; Aimiya, Hidetoshi; Nakata, Kohei; Gotoh, Keinosuke; Ariji, Eiichiro

doi:10.1007/s11282-013-0152-2

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Pauwels et al argued that image quality degradation and artifacts can occur more in the top and bottom parts of the FOV due to the wide cone angle in some CBCT images 40 , which is consistent with our findings for the CAL_CBCT images. In the axial plane, the beam geometry of CBCT causes asymmetry in the X-ray path, leading to position-dependent differences in beam hardening and endo/exo-mass effects and a consequent difference in BMD accuracy between the central and peripheral parts of the FOV [79][80][81] . Plachtovics et al showed that the difference between the HU of MDCT and the GV of CBCT increased from the center of the FOV to the outer border within an axial slice, resulting in a decrease in the density measurement accuracy of CBCT, which is consistent with our findings for the CAL_CBCT images 82 .…”

Section: Discussionmentioning

confidence: 99%

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning

Park

Kang

Kim

et al. 2023

Sci Rep

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The bone mineral density (BMD) measurement is a direct method of estimating human bone mass for diagnosing osteoporosis, and performed to objectively evaluate bone quality before implant surgery in dental clinics. The objective of this study was to validate the accuracy and reliability of BMD measurements made using quantitative cone-beam CT (CBCT) image based on deep learning by applying the method to clinical data from actual patients. Datasets containing 7500 pairs of CT and CBCT axial slice images from 30 patients were used to train a previously developed deep-learning model (QCBCT-NET). We selected 36 volumes of interest in the CBCT images for each patient in the bone regions of potential implants sites on the maxilla and mandible. We compared the BMDs shown in the quantitative CBCT (QCBCT) images with those in the conventional CBCT (CAL_CBCT) images at the various bone sites of interest across the entire field of view (FOV) using the performance metrics of the MAE, RMSE, MAPE (mean absolute percentage error), R2 (coefficient of determination), and SEE (standard error of estimation). Compared with the ground truth (QCT) images, the accuracy of the BMD measurements from the QCBCT images showed an RMSE of 83.41 mg/cm3, MAE of 67.94 mg/cm3, and MAPE of 8.32% across all the bone sites of interest, whereas for the CAL_CBCT images, those values were 491.15 mg/cm3, 460.52 mg/cm3, and 54.29%, respectively. The linear regression between the QCBCT and QCT images showed a slope of 1.00 and a R2 of 0.85, whereas for the CAL_CBCT images, those values were 0.32 and 0.24, respectively. The overall SEE between the QCBCT images and QCT images was 81.06 mg/cm3, whereas the SEE for the CAL_CBCT images was 109.32 mg/cm3. The QCBCT images thus showed better accuracy, linearity, and uniformity than the CAL_CBCT images across the entire FOV. The BMD measurements from the quantitative CBCT images showed high accuracy, linearity, and uniformity regardless of the relative geometric positions of the bone in the potential implant site. When applied to actual patient CBCT images, the CBCT-based quantitative BMD measurement based on deep learning demonstrated high accuracy and reliability across the entire FOV.

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Section: Discussionmentioning

confidence: 99%

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning

Park

Kang

Kim

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Naitoh et al 18 reported that the voxel values changed based on the z-axis location of the radiation field, although there was no mention of the cause, and the voxel values for the median anterior region were significantly higher than those for the left and right molar regions on the axial plane. Swennen et al 19 stated that with CBCT, the voxel values of an organ depend on the location in the image volume.…”

Section: Discussionmentioning

confidence: 99%