Validation of a novel imaging approach using multi-slice CT and cone-beam CT to follow-up on condylar remodeling after bimaxillary surgery

Nicolielo, Laura Ferreira Pinheiro; Dessel, Jeroen Van; Shaheen, Eman; Letelier, Carolina; Codari, Marina; Politis, Constantinus; Lambrichts, Ivo; Jacobs, Reinhilde

doi:10.1038/ijos.2017.22

Cited by 25 publications

(18 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The next direction of further study may be to increase accuracy of the segmentation for anatomical areas with low density. Fully automatic segmentation of selected anatomical areas especially condyles would be important tool to increase the evaluation of treatment or postoperative follow-up [35,36].…”

Section: Discussionmentioning

confidence: 99%

Automatic Method for Bone Segmentation in Cone Beam Computed Tomography Data Set

Vaitiekūnas

Jegelevičius

Sakalauskas³

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

Due to technical aspects of Cone Beam Computed Tomography (CBCT), the automatic methods for bone segmentation are not widely used in the clinical practice of endodontics, orthodontics, oral and maxillofacial surgery. The aim of this study was to evaluate method’s accuracy for bone segmentation in CBCT data sets. The sliding three dimensional (3D) window, histogram filter and Otsu’s method were used to implement the automatic segmentation. The results of automatic segmentation were compared with the results of segmentation performed by an experienced oral and maxillofacial surgeon. Twenty patients and their forty CBCT data sets were used in this study (20 preoperative and 20 postoperative). Intraclass Correlation Coefficients (ICC) were calculated to prove the reliability of surgeon segmentations. ICC was 0.958 with 95% confidence interval [0.896 ... 0.983] in preoperative data sets and 0.931 with 95% confidence interval [0.836 ... 0.972] in postoperative data sets. Three basic metrics were used in order to evaluate the accuracy of the automatic method—Dice Similarity Coefficient (DSC), Root Mean Square (RMS), Average Distance Error (ADE) of surfaces mismatch and additional metric in order to evaluate computation time of segmentation was used. The mean value of preoperative DSC was 0.921, postoperative—0.911, the mean value of preoperative RMS was 0.559 mm, postoperative—0.647 mm, the ADE value of preoperative cases was 0.043 mm, postoperative—0.057 mm, the mean computational time to perform the segmentation was 46 s. The automatic method showed clinically acceptable accuracy results and thus can be used as a new tool for automatic bone segmentation in CBCT data. It can be applied in oral and maxillofacial surgery for performance of 3D Virtual Surgical Plan (VSP) or for postoperative follow-up.

show abstract

Section: Discussionmentioning

confidence: 99%

Automatic Method for Bone Segmentation in Cone Beam Computed Tomography Data Set

Vaitiekūnas

Jegelevičius

Sakalauskas³

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The relation between pain, one of the typical OA symptoms, and structural degeneration is not strong (Glyn‐Jones et al, ). Clinically, the diagnosis of TMJ OA is often based on the osseous changes in the TMJ images, such as those obtained via cone beam computerized tomography (CBCT) (Khojastepour, Vojdani, & Forghani, ; Nicolielo et al, ). However, conventional imaging techniques can detect only quite advanced disease, and the interpretation of early pathological signs in imaging findings is often complicated (Larheim, Hol, Ottersen, Mork‐Knutsen, & Arvidsson, ).…”

Section: Introductionmentioning

confidence: 99%

“…The relation between pain, one of the typical OA symptoms, and structural degeneration is not strong (Glyn-Jones et al, 2015). Clinically, the diagnosis of TMJ OA is often based on the osseous changes in the TMJ images, such as those obtained via cone beam computerized tomography (CBCT) (Khojastepour, Vojdani, & Forghani, 2017;Nicolielo et al, 2017).…”

mentioning

confidence: 99%

Early growth response 1 reduction in peripheral blood involving condylar subchondral bone loss

et al. 2019

View full text Add to dashboard Cite

Objectives To detect whether early growth response 1 (EGR1) in peripheral blood leucocytes (PBLs) indicates temporomandibular joint (TMJ) osteoarthritis (OA) lesions. Materials and Methods Egr1 mRNA expression levels in PBLs were detected in eight malocclusion patients without temporomandibular disorder (TMD) signs and 16 malocclusion patients with clinical TMD signs with (eight) or without (eight) imaging signs of TMJ OA. Twelve 6‐week‐old rats were randomized to a control group and a unilateral anterior crossbite (UAC) group and were sampled at 4 weeks. The Egr1 mRNA expression levels in PBLs and protein expression levels in different orofacial tissues were measured. Results Patients with TMD signs with/without TMJ OA diagnosis showed lower Egr1 mRNA expression levels in PBLs than patients without TMD signs. The lower Egr1 mRNA expression was also found in the PBLs of UAC rats, which were induced to exhibit early histo‐morphological signs of TMJ OA lesions. In subchondral bone of UAC rats, EGR1 protein expression was decreased, co‐localization of EGR1 with osterix or dentin matrix protein‐1 was identified, and the number of EGR1 and osterix double‐positive cells was reduced (all p < .05). Conclusion Egr1 reduction in PBLs potentially indicates subchondral bone OA lesions at an early stage.

show abstract

“…The extraction of meaningful geometrical structures from digital images is a 6 fundamental problem in many research areas with innumerable applications, specially in 7 the medical areas [1][2][3]. Recently we have seen enormous advances in computer-based 8 methods, due to, inter alia: the overall increase of computational power, the 9 development of new algorithms and imaging techniques.…”

mentioning

confidence: 99%

“…Among the 13 imaging modalities employed in those applications, Cone Beam Computer Tomography 14 (CBCT) has been one of the most frequently used. 15 CBCT has several advantages, such as: the greater amount of information obtained 16 in comparison with 2D tomographic methods, lower dose delivery to the patient [4,5] in 17 comparison with conventional Computer Tomography [6] and relatively low cost. Yet, in 18 comparison with Computer Tomography, CBCT images are noisier and have lower 19 contrast resolution [7,8].…”

mentioning

confidence: 99%

Does pixel/voxel-size limit the measurement of distances in CBCT-tomography?

Köberle

Junior

Bianchi

et al. 2018

Preprint

View full text Add to dashboard Cite

The necessity to obtain relevant structural information from tomographic images is an all-pervasive step in a host of clinical and research-areas. Cone Beam Computed Tomography (CBCT) is the imaging modality often used among the many available.Currently approaches to extract structural properties from raw CBCT-images, involve some manual intervention by experts to measure their properties, such as size and displacements of their geometrical structures. Regarding the factors limiting the precision of these measurements, such as voxel-size and image contrast, we find conflicting statements in the literature. It is therefore useful to provide accurate data under well-defined experimental conditions.Here we present a method and associated software to measure displacements of geometrical structures. We also determined the minimum measureable displacement and minimum detectable defect in terms of voxel size. We select as our geometrical structure a sample of bovine bone and to provide a set of defects, we drilled a pattern of holes into it. We determined the hole's three-dimensional structures using confocal spectroscopy.In order to obtain the minimum measurable displacement, we acquired CBCT-tomographies containing a stationary reference and micro-metrically cnc controlled displacements of the sample. We then process these images with our software to extract the distances and compare them with the cnc displacements. All our processing includes a computational interpolation from the voxel-size of 0.35 mm corresponding to our CBCT-tomographies, down to 0.05 mm. We find that sample-displacements can be measured with a precision of ∼ 20µ, 17 times smaller than the voxel-size of 0.35 mm.To measure the size of the holes using our CBCT-tomographies, we first register the 1 holes onto a hole-free region of the sample with our software, then overlay the result 2 with the three-dimensional structure obtained from confocal spectroscopy. We find the 3 minimum detectable hole-size to be 0.7 mm, twice the voxel-size. 4 PLOS 1/9 Hole characterization 76 In order to infer the size of the smallest holes, which we can detect using tomographic 77 images processed by our algorithm, we need a precise enough measure of their spatial 78 geometry. We therefore used confocal microscopy [21] (Lext 3D Laser Measuring, 79 Center Valley, PA, USA) using laser wavelength of 405nm to obtain the 80 three-dimensional structure of the holes. This technique uses a laser to produce 81 PLOS 3/9 110We segment the volumetric image of the whole setup Fig.(1 B), using the region 111 competition algorithm [22] implemented in the ITK-SNAP segmentation software [23], 112 before and after displacement to extract the regions of interest: bone sample, circular 113 dish and rod. Yet the borders of the bone sample, which will be used to measure 114 displacements, are not always well defined. To refine their positions, we expand the 115 region labeled bone sample via a level set contour propagation [24] followed by an AND 116 operation between the bone sample region b...

show abstract

Validation of a novel imaging approach using multi-slice CT and cone-beam CT to follow-up on condylar remodeling after bimaxillary surgery

Cited by 25 publications

References 31 publications

Automatic Method for Bone Segmentation in Cone Beam Computed Tomography Data Set

Automatic Method for Bone Segmentation in Cone Beam Computed Tomography Data Set

Early growth response 1 reduction in peripheral blood involving condylar subchondral bone loss

Does pixel/voxel-size limit the measurement of distances in CBCT-tomography?

Contact Info

Product

Resources

About