Comparison of cone beam CT scans with enhanced photostimulated phosphor plate images in the detection of root fracture of endodontically treated teeth.

OBJECTIVES: Two-dimensional intraoral radiography is the most common tool for diagnosing root fractures (RFs). Cone beam CT (CBCT) is widely used to depict RFs in endodontically treated teeth. Beam hardening and other artefacts caused by gutta percha may result in an incorrect diagnosis when using CBCT only. A comparison of two CBCT machines with photostimulated phosphor (PSP) plate images enhanced with the equalization tool was carried out to detect RFs in endodontically treated teeth. METHODS: 66 roots were collected, decoronated and treated endodontically using the same technique with gutta percha. 33 of these roots were randomly selected and fractured; the 2 root fragments were glued together with 1 layer of methyl methacrylate and placed randomly in 8 prepared beef rib fragments. Large fields of view (FOVs) were acquired with one CBCT unit and small FOVs with the second CBCT unit. Periapical radiographs (using intraoral PSP plates) were also acquired. A contrast enhancement tool was used when evaluating the PSP plate images. RESULTS: Small FOV images had significantly higher accuracy (area under the receiver operating characteristic curve) and sensitivity in detecting RFs than PSP plates and large FOV images. The specificity of the enhanced PSP images was higher than, although not significantly higher than, the small FOV images and was significantly higher than the large FOV images. CONCLUSIONS: CBCT small FOVs should be acquired for depicting RFs of endodontically treated teeth. Images obtained using PSP plates had the lowest rate of false-positive results and their use can save the patient a radiation dose.

Cone beam CT scans with and without artefact reduction in root fracture detection of endodontically treated teeth.

OBJECTIVES: Cone beam CT (CBCT) is used widely to depict root fracture (RF) in endodontically treated teeth. Beam hardening and other artefacts due to gutta-percha may increase the time of the diagnosis and result in an incorrect diagnosis. Two CBCT machines, ProMax(®) (Planmeca, Helsinki, Finland) and Master 3D(®) (Vatech, Hwaseong, Republic of Korea), have the option of applying an artefact reduction (AR) algorithm. The aim of this study was to determine whether using an AR algorithm in two CBCT machines enhances the accuracy of detecting RFs in endodontically treated teeth. METHODS: 66 roots were collected and decoronated. All roots were treated endodontically using the same technique with gutta-percha and zinc oxide cement. One-half of the roots were randomly selected and fractured using a nail that was tapped gently with a hammer until complete fracture resulted in two root fragments; the two root fragments were glued together with one layer of methyl methacrylate. The roots were placed randomly in eight prepared beef rib fragments. RESULTS: The highest accuracy was obtained when the ProMax was used without AR. The lowest accuracy was obtained with the Master 3D when used with AR. For both machines, accuracy was significantly higher without AR than with AR. Both with and without AR, the ProMax machine was significantly more accurate than the Master 3D machine. The same rank ordering was obtained for both sensitivity and specificity. CONCLUSIONS: For both machines, AR decreased the accuracy of RF detection in endodontically treated teeth. The highest accuracy was obtained when using the ProMax without AR.

A mathematical model relating changes of grey values to changes of thicknesses of a stepwedge.

The purpose of this report is to present a mathematical model relating changes in grey values to changes of thicknesses of a stepwedge. Radiographs of a stepwedge were obtained through a limited exposure range on a single Kodak 6100 charge-coupled device detector at 63 kVp and 70 kVp. Grey values from each step were evaluated relative to the corresponding step thickness. All possible regression fits were evaluated based on their coefficient of determination (R(2)) value and their mean squared errors (MSEs) relative to the original thickness. For all exposure settings, the fifth-degree polynomial was the best possible fit, with the highest R(2) value and the lowest MSE.

Evaluation of a cone beam CT artefact reduction algorithm.

OBJECTIVES: An algorithm and software to reduce metal artefact has been developed recently and is available in the Picasso Master 3D® (VATECH, Hwaseong, Republic of Korea), which under visual assessment produces better quality images than were obtainable previously. The objective of this in vitro study was to investigate whether the metal artefact reduction (MAR) algorithm of the Picasso Master 3D machine reduced the incidence of metal artefacts and increased the contrast-to-noise ratio (CNR) while maintaining the same gray value when there was no metallic body present within the scanned volume. METHODS: 20 scans with a range of 50-90 kVp were acquired, of which 10 had a metallic bead inserted within a phantom. The images obtained were analysed using public domain software (ImageJ; NIH Image, Bethesda, MD). Area histograms were used to evaluate the mean gray level variation of the epoxy resin-based substitute (ERBS) block and a control area. The CNR was calculated. RESULTS: The MAR algorithm increased the CNR when the metallic bead was present; it enhanced the ERBS gray level independently of the presence of the metallic bead. The image quality also improved as peak tube potential was increased. CONCLUSION: Improved quality of images and regaining of the control gray values of a phantom were achieved when the MAR algorithm was used in the presence of a metallic bead.

Metal artefact reduction with cone beam CT: an in vitro study.

BACKGROUND: Metal in a patient's mouth has been shown to cause artefacts that can interfere with the diagnostic quality of cone beam CT. Recently, a manufacturer has made an algorithm and software available which reduces metal streak artefact (Picasso Master 3D® machine; Vatech, Hwaseong, Republic of Korea). OBJECTIVES: The purpose of this investigation was to determine whether or not the metal artefact reduction algorithm was effective and enhanced the contrast-to-noise ratio. METHODS: A phantom was constructed incorporating three metallic beads and three epoxy resin-based bone substitutes to simulate bone next to metal. The phantom was placed in the centre of the field of view and at the periphery. 10 data sets were acquired at 50-90 kVp. The images obtained were analysed using a public domain software ImageJ (NIH Image, Bethesda, MD). Profile lines were used to evaluate grey level changes and area histograms were used to evaluate contrast. The contrast-to-noise ratio was calculated. RESULTS: The metal artefact reduction option reduced grey value variation and increased the contrast-to-noise ratio. The grey value varied least when the phantom was in the middle of the volume and the metal artefact reduction was activated. The image quality improved as the peak kilovoltage increased. CONCLUSION: Better images of a phantom were obtained when the metal artefact reduction algorithm was used.

Application of a semiautomated contour segmentation tool to identify the intervertebral nucleus pulposus in MR images.

BACKGROUND AND PURPOSE: Accurate identification of the NP in MR images is crucial to properly and objectively assess the intervertebral disk. Therefore, computerized segmentation of the NP in T2WI is necessary to produce repeatable and accurate results with minimal user input. MATERIAL AND METHODS: A semiautomated CS method was developed to identify the NP in T2WI on the basis of intensity differences compared with the AF. The method was validated by segmenting computer-generated images with a known ROI. The method was tested by using 63 MR images of rabbit lumbar disks, which were segmented to detect disk degeneration. An ICC was used to assess the repeatability of this method compared with manual segmentation. RESULTS: The error in the detected area of the rabbit NP by using CS was -3.49% ± 4.4% (mean ± SD) compared with 22.36% ± 5.55% by using manual segmentation. Moreover, the method was capable of detecting disk degeneration in a known rabbit puncture model of disk degeneration. Finally, this method had an ICC of 0.97 and 0.99 in regard to segmenting the area and calculating the MR imaging index of the NP, deeming it highly repeatable. CONCLUSIONS: The CS method is a semiautomated computer method able to segment the NP of the rabbit disk and detect disk degeneration. In addition, it could assist in clinical detection, assessment, and monitoring of early degeneration in human disks.