Automated segmentation of the craniofacial skeleton with “Black Bone” MRI

3D imaging of the craniofacial skeleton is integral in managing a wide range of bony pathologies. We have previously demonstrated the potential of “Black Bone” MRI (BB) as a non-ionising alternative to CT. However, even in experienced hands 3D rendering of BB datasets can be challenging and time consuming. The objectives of this study were to develop and test a semi- and fully-automated segmentation algorithm for the craniofacial skeleton. Previously acquired adult volunteer (n=15) BB datasets of the head were utilised. Imaging was initially 3D rendered with our conventional manual technique. An algorithm to remove the outer soft-tissue envelope was developed and 3D rendering completed with the processed datasets (semi-automated). Finally, a fully automated 3D-rendering method was developed and applied to the datasets. All 3D rendering was completed with Fovia High Definition Volume Rendering® (Fovia Inc, Palo Alto, CA. USA). Analysis was undertaken of the 3D visual results and the time taken for data processing and interactive manipulation. The mean time for manual segmentation was 12.8 minutes, 3.1 minutes for the semi- automated algorithm, and 0 minutes for the fully automated algorithm. Further fine adjustment was undertaken to enhance the automated segmentation results, taking a mean time of 1.4 minutes. Automated segmentation demonstrates considerable potential, offering significant time saving in the production of 3D BB imaging in adult volunteers. We continue to undertake further development of our segmentation algorithms to permit adaption to the paediatric population in whom non-ionising imaging confers the most potential benefit.cademy of Medical Sciences Clinical Lecturer Starter Grant (K. Eley) [SGL019\1012

MR Image Based Approach for Metal Artifact Reduction in X-Ray CT

For decades, computed tomography (CT) images have been widely used to discover valuable anatomical information. Metallic implants such as dental fillings cause severe streaking artifacts which significantly degrade the quality of CT images. In this paper, we propose a new method for metal-artifact reduction using complementary magnetic resonance (MR) images. The method exploits the possibilities which arise from the use of emergent trimodality systems. The proposed algorithm corrects reconstructed CT images. The projected data which is affected by dental fillings is detected and the missing projections are replaced with data obtained from a corresponding MR image. A simulation study was conducted in order to compare the reconstructed images with images reconstructed through linear interpolation, which is a common metal-artifact reduction technique. The results show that the proposed method is successful in reducing severe metal artifacts without introducing significant amount of secondary artifacts

Automated 3D MRI rendering of the craniofacial skeleton: using ZTE to drive the segmentation of black bone and FIESTA-C images

Abstract: Purpose: Automated bone segmentation from MRI datasets would have a profound impact on clinical utility, particularly in the craniofacial skeleton where complex anatomy is coupled with radiosensitive organs. Techniques such as gradient echo black bone (GRE-BB) and short echo time (UTE, ZTE) have shown potential in this quest. The objectives of this study were to ascertain (1) whether the high-contrast of zero echo time (ZTE) could drive segmentation of high-resolution GRE-BB data to enhance 3D-output and (2) if these techniques could be extrapolated to ZTE driven segmentation of a routinely used non bone-specific sequence (FIESTA-C). Methods: Eleven adult volunteers underwent 3T MRI examination with sequential acquisition of ZTE, GRE-BB and FIESTA-C imaging. Craniofacial bone segmentation was performed using a fully automated segmentation algorithm. Segmentation was completed individually for GRE-BB and a modified version of the algorithm was subsequently implemented, wherein the bone mask yielded by ZTE segmentation was used to initialise segmentation of GRE-BB. The techniques were subsequently applied to FIESTA-C datasets. The resulting 3D reconstructions were evaluated for areas of unexpected bony defects and discrepancies. Results: The automated segmentation algorithm yielded acceptable 3D outputs for all GRE-BB datasets. These were enhanced with the modified algorithm using ZTE as a driver, with improvements in areas of air/bone interface and dense muscular attachments. Comparable results were obtained with ZTE+FIESTA-C. Conclusion: Automated 3D segmentation of the craniofacial skeleton is enhanced through the incorporation of a modified segmentation algorithm utilising ZTE. These techniques are transferrable to FIESTA-C imaging which offers reduced acquisition time and therefore improved clinical utility

PET-MR imaging using a tri-modality PET/CT-MR system with a dedicated shuttle in clinical routine

Tri-modality PET/CT-MRI includes the transfer of the patient on a dedicated shuttle from one system into the other. Advantages of this system include a true CT-based attenuation correction, reliable PET-quantification and higher flexibility in patient throughput on both systems. Comparative studies of PET/MRI versus PET/CT are readily accomplished without repeated PET with a different PET scanner at a different time point. Additionally, there is a higher imaging flexibility based on the availability of three imaging modalities, which can be combined for the characterization of the disease. The downside is a somewhat higher radiation dose of up to 3mSv with a low dose CT based on the CT-component, longer acquisition times and potential misalignment between the imaging components. Overall, the tri-modality PET/CT-MR system offers comparative studies using the three different imaging modalities in the same patient virtually at the same time, and may help to develop reliable attenuation algorithms at the same tim

Clinical Evaluation of 11C-Met-Avid Pituitary Lesions Using a ZTE-Based AC Method

Pituitary tumours account for ~16% of central nervous system tumors and they are the second most frequently reported histology in this group. Due to their small size, pituitary surgery is challenging and precise lesion localization through imaging is therefore a critical factor for a successful outcome. Simultaneous positron emission tomography and magnetic resonance imaging is well suited for lesion identification and localization but it requires accurate attenuation correction (AC) to ensure optimal positron emission imaging (PET) imaging. Atlas-based AC methods are often used for this purpose, as they overcome the difficulty of estimating bone tissue density with conventional MR sequences. However, atlas methods can only partially account for interpatient variability. The goal of this paper was to investigate whether direct bone measurement, by means of a zero echo time MR sequence, can significantly improve the accuracy of pituitary tumor imaging with PET

3D nonlinear PET-CT image registration algorithm with constrained Free-Form Deformations

International audienceThis paper presents a 3D nonlinear PET-CT image registration method guided by a B-Spline Free-Form Deformations (FFD) model, dedicated to thoracic and abdominal regions. It is divided into two stages: one FFD-based registration of structures that can be identified in both images; and a whole-image intensity registration step constrained by the FFD computed during the first step. Different similarity criteria have been adopted for both stages: Root Mean Square (RMS) to register recognized structures and Normalized Mutual Information (NMI) for optimizing the whole-image intensity stage. Structure segmentation is performed according to a hierarchical procedure, where the extraction of a given structure is driven by information derived from a simpler one. This information is composed of spatial constraints and expressed by the means of regions of interest, in which a 3D simplex mesh deformable model based method is applied. The results have been very positively evaluated by three medical experts

Black bone MRI with 3D reconstruction for the detection of skull fractures in children with suspected abusive head trauma.

PURPOSE: The purpose of this study was to determine the accuracy of "black bone" (BB) MRI for the detection of skull fractures in children with potential abusive head trauma. METHODS: A total of 34 pediatric patients were evaluated for potential abusive head trauma. All patients had both a non-contrast head CT (HCT) with multiplanar reformatted images and 3D volumetric reformatted images where available (gold standard) for fracture diagnosis and BB of the head with multiplanar reformatted images and 3D volumetric images. BB was performed using an ultrashort TE pointwise encoding time reduction with radial acquisition (PETRA) sequence at 1.5 T or 3 T. BB datasets were post-processed and 3D images created using Fovia's High Definition Volume Rendering® software. Two board-certified pediatric neuroradiologists independently reviewed the HCT and BB imaging, blinded to the findings from the other modality. RESULTS: Median patient age was 4 months (range 1.2-30 months). A total of 20 skull fractures in six patients (18% incidence of skull fractures) were detected on HCT. BB demonstrated 83% sensitivity (95%[CI] 36-99%), 100% specificity (95%[CI] 88-100%), 100% PPV (95%[CI] 46-100%), 97% NPV (95%[CI] 82-99%), and 97% accuracy (95%[CI] 85-99%) for diagnosis of a skull fracture. BB detected 95% (19/20) of the skull fractures detected by CT. CONCLUSION: A black bone MRI sequence may provide high sensitivity and specificity for detection of skull fractures in pediatric patients with abusive head trauma

Characterization of the impact to PET quantification and image quality of an anterior array surface coil for PET/MR imaging

Object: The aim of this study was to determine the impact to PET quantification, image quality and possible diagnostic impact of an anterior surface array used in a combined PET/MR imaging system. Materials and methods: An extended oval phantom and 15 whole-body FDG PET/CT subjects were re-imaged for one bed position following placement of an anterior array coil at a clinically realistic position. The CT scan, used for PET attenuation correction, did not include the coil. Comparison, including liver SUVmean, was performed between the coil present and absent images using two methods of PET reconstruction. Due to the time delay between PET scans, a model was used to account for average physiologic time change of SUV. Results: On phantom data, neglecting the coil caused a mean bias of −8.2% for non-TOF/PSF reconstruction, and −7.3% with TOF/PSF. On clinical data, the liver SUV neglecting the coil presence fell by −6.1% (±6.5%) for non-TOF/PSF reconstruction; respectively −5.2% (±5.3%) with TOF/PSF. All FDG-avid features seen with TOF/PSF were also seen with non-TOF/PSF reconstruction. Conclusion: Neglecting coil attenuation for this anterior array coil results in a small but significant reduction in liver SUVmean but was not found to change the clinical interpretation of the PET images

Regional accuracy of ZTE-based attenuation correction in static and dynamic brain PET/MR

Accurate MR-based attenuation correction (MRAC) is essential for quantitative PET/MR imaging of the brain. In this study, we analyze the regional bias caused by MRAC based on Zero-Echo-Time MR images (ZTEAC) compared to CT-based AC (CTAC) in static and dynamic PET imaging. In addition the results are compared to the performance of the current default Atlas-based AC (AtlasAC) implemented in the GE SIGNA PET/MR. Methods: Thirty static [18F]FDG and 11 dynamic [18}F]PE2I acquisitions from a GE SIGNA PET/MR were reconstructed using ZTEAC (using a research tool, GE Healthcare), single-subject AtlasAC (the current default AC in GE's SIGNA PET/MR) and CTAC (from a PET/CT acquisition of the same day). In the 30 static [18F]FDG reconstructions, the bias caused by ZTEAC and AtlasAC in the mean uptake of 85 anatomical volumes of interest (VOIs) of the Hammers' atlas was analyzed in PMOD. For the 11 dynamic [18}F]PE2I reconstructions, the bias caused by ZTEAC and AtlasAC in the non displaceable binding potential BPnd in the striatum was calculated with cerebellum as the reference region and a simplified reference tissue model. Results: The regional bias caused by ZTEAC in the static [18F]FDG reconstructions ranged from -8.0% to +7.7% (mean 0.1%, SD 2.0%). For AtlasAC this bias ranged from -31.6% to +16.6% (mean -0.4%, SD 4.3%). The bias caused by AtlasAC showed a clear gradient in the cranio-caudal direction (-4.2% in the cerebellum, +6.6% in the left superior frontal gyrus). The bias in the striatal BPnd for the [18F]PE2I reconstructions ranged from -0.8% to +4.8% (mean 1.5%, SD 1.4%) using ZTEAC and from -0.6% to +9.4% using AtlasAC (mean 4.2%, SD 2.6%). Conclusion: ZTEAC provides excellent quantitative accuracy for static and dynamic brain PET/MR, comparable to CTAC, and is clearly superior to the default AtlasAC currently implemented in the GE SIGNA PET/MR.Comment: 23 pages in total, 7 figures, 1 table, 3 supplementary figures, 5 supplementary table