Dataset Information

A novel region-growing based semi-automatic segmentation protocol for three-dimensional condylar reconstruction using cone beam computed tomography (CBCT).

ABSTRACT:

Objective

To present and validate a semi-automatic segmentation protocol to enable an accurate 3D reconstruction of the mandibular condyles using cone beam computed tomography (CBCT).

Materials and methods

Approval from the regional medical ethics review board was obtained for this study. Bilateral mandibular condyles in ten CBCT datasets of patients were segmented using the currently proposed semi-automatic segmentation protocol. This segmentation protocol combined 3D region-growing and local thresholding algorithms. The segmentation of a total of twenty condyles was performed by two observers. The Dice-coefficient and distance map calculations were used to evaluate the accuracy and reproducibility of the segmented and 3D rendered condyles.

Results

The mean inter-observer Dice-coefficient was 0.98 (range [0.95-0.99]). An average 90th percentile distance of 0.32 mm was found, indicating an excellent inter-observer similarity of the segmented and 3D rendered condyles. No systematic errors were observed in the currently proposed segmentation protocol.

Conclusion

The novel semi-automated segmentation protocol is an accurate and reproducible tool to segment and render condyles in 3D. The implementation of this protocol in the clinical practice allows the CBCT to be used as an imaging modality for the quantitative analysis of condylar morphology.

SUBMITTER: Xi T

PROVIDER: S-EPMC4234209 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

A novel region-growing based semi-automatic segmentation protocol for three-dimensional condylar reconstruction using cone beam computed tomography (CBCT).

Xi Tong T Schreurs Ruud R Heerink Wout J WJ Bergé Stefaan J SJ Maal Thomas J J TJ

PloS one 20141117 11

<h4>Objective</h4>To present and validate a semi-automatic segmentation protocol to enable an accurate 3D reconstruction of the mandibular condyles using cone beam computed tomography (CBCT).<h4>Materials and methods</h4>Approval from the regional medical ethics review board was obtained for this study. Bilateral mandibular condyles in ten CBCT datasets of patients were segmented using the currently proposed semi-automatic segmentation protocol. This segmentation protocol combined 3D region-grow ...[more]

PMID: 25401954

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Project description:BackgroundMotion-compensated (MoCo) reconstruction shows great promise in improving four-dimensional cone-beam computed tomography (4D-CBCT) image quality. MoCo reconstruction for a 4D-CBCT could be more accurate using motion information at the CBCT imaging time than that obtained from previous 4D-CT scans. However, such data-driven approaches are hampered by the quality of initial 4D-CBCT images used for motion modeling.PurposeThis study aims to develop a deep-learning method to generate high-quality motion models for MoCo reconstruction to improve the quality of final 4D-CBCT images.MethodsA 3D artifact-reduction convolutional neural network (CNN) was proposed to improve conventional phase-correlated Feldkamp-Davis-Kress (PCF) reconstructions by reducing undersampling-induced streaking artifacts while maintaining motion information. The CNN-generated artifact-mitigated 4D-CBCT images (CNN enhanced) were then used to build a motion model which was used by MoCo reconstruction (CNN+MoCo). The proposed procedure was evaluated using in-vivo patient datasets, an extended cardiac-torso (XCAT) phantom, and the public SPARE challenge datasets. The quality of reconstructed images for XCAT phantom and SPARE datasets was quantitatively assessed using root-mean-square-error (RMSE) and normalized cross-correlation (NCC).ResultsThe trained CNN effectively reduced the streaking artifacts of PCF CBCT images for all datasets. More detailed structures can be recovered using the proposed CNN+MoCo reconstruction procedure. XCAT phantom experiments showed that the accuracy of estimated motion model using CNN enhanced images was greatly improved over PCF. CNN+MoCo showed lower RMSE and higher NCC compared to PCF, CNN enhanced and conventional MoCo. For the SPARE datasets, the average (± standard deviation) RMSE in mm-1 for body region of PCF, CNN enhanced, conventional MoCo and CNN+MoCo were 0.0040 ± 0.0009, 0.0029 ± 0.0002, 0.0024 ± 0.0003 and 0.0021 ± 0.0003. Corresponding NCC were 0.84 ± 0.05, 0.91 ± 0.05, 0.91 ± 0.05 and 0.93 ± 0.04.ConclusionsCNN-based artifact reduction can substantially reduce the artifacts in the initial 4D-CBCT images. The improved images could be used to enhance the motion modeling and ultimately improve the quality of the final 4D-CBCT images reconstructed using MoCo.

Project description:BackgroundA correct understanding of the mandibular condyle morphology may help clinicians judge the normal range of morphological variations of asymptomatic patients or the pathological conditions correctly. Hence, the aim of the present study was to evaluate the status of condyle cortication and condyle morphology, and to investigate the relationship between the development of the condylar cortex and the changes of condyle morphology.MethodsThe present study was an observational study. A total of 1,010 temporomandibular joint (TMJ) cone-beam computed tomography (CBCT) images were collected retrospectively. The mandibular condyle morphology was observed in axial (concave, convex, plane and others for anterior and posterior facets), coronal (plane, convex, angled and round for superior facet) and sagittal (round and plane for superior facet) views, and the condylar cortication was grouped into three types (undeveloped, developing and developed). Analytical statistics were performed to detect a relationship between the cortication status and morphology of the condyles.ResultsFor males and females, the mean age was 15.11±2.71 and 14.25±2.60 years (for condylar bone without cortication), 19.45±3.92 and 18.65±3.45 years (with developing cortical bone), 23.63±3.36 and 23.86±3.73 years (with developed cortical bone), respectively. The condyle morphology with a plane form in the anterior aspect, a convex form in the posterior aspect, a convex form in the coronal view and a round form in the sagittal view was the most often recorded condyle morphologies (13.2%). After the cortical bone of condyle completely forms, the plane form was significantly increased in the superior surface in both sagittal and coronal views.ConclusionsThe condylar shape gradually changes with growth and development of the condyle bone cortex. The more mature the bone cortex is, the higher the probability that the condyle will have an uneven shape, which may mean that the condyle morphology may change due to remodeling during growth and development.

Project description:Background To evaluate the effects of dose to tumors and organs at risk (OARs) on inter-fractional anatomic changes. Methods We evaluated nine patients with cervical cancer treated with intensity-modulated radiotherapy (IMRT) (45 Gy in 25 fractions) using kV cone-beam computed tomography (CBCT) image guidance once or twice a week before treatment. For each patient, the original plan on the computed tomography (CT) image was copied to merged images, and then the fractional doses were calculated. Subsequently, deformable accumulated doses were obtained by summing the fractional absolute doses into a single dose in MIM Maestro software. The volume changes in the target and OARs were compared between the original CT and merged CBCT images, and the differences in the fractional and accumulated doses were also evaluated. Results Sixty-nine merged CBCT images were obtained and analyzed in this study. For the target areas, the volume changes in the clinical target volume (CTV) and planning target volume (PTV) reached −18.05% and −24.11% at most, respectively. The fractional D2% of the CTV and PTV was generally higher than the original plans, and the accumulated deviations were 2.27%±0.82% (P<0.01) and 2.42%±1.28% (P<0.01), respectively. The fractional D98% of the PTV was underdosed up to 18.28% for 78% of patients, and the accumulated deviations were −2.06% to −17.29% (P<0.05). For the OARs, the bladder volume changes were the most dramatic, reducing up to 93.60%. The fractional Dmean and D2cc of the bladder were generally higher than the original plans, and there were significant differences in their accumulated values (P<0.05). There was no obvious trend of rectal volume change with −69.65% to 74.20%. The rectum Dmean and D2cc of the accumulated were not significantly different from the planned dose (P>0.05). Conclusions For patients with cervical cancer, the changes in bladder and rectal volume were greater than in the target volume. Although the volume changes in the bladder and rectum had no significant effect on D98% of the CTV and PTV, they had a significant effect on their own D2cc and the D2% of the CTV and PTV. More attention should be paid to the volume changes in the bladder and rectum in clinical work.

Dataset Information

A novel region-growing based semi-automatic segmentation protocol for three-dimensional condylar reconstruction using cone beam computed tomography (CBCT).

Objective

Materials and methods

Results

Conclusion

Publications

A novel region-growing based semi-automatic segmentation protocol for three-dimensional condylar reconstruction using cone beam computed tomography (CBCT).

Similar Datasets

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