18 research outputs found
Development and evaluation of metal artifact reduction and image segmentation techniques in PET/CT
Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma
Purpose: Several methods have been proposed for the segmentation of 18F-FDG uptake in PET. In this study, we assessed the performance of four categories of 18F-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the benchmark. Methods: Nine PET image segmentation techniques were compared including: five thresholding methods; the level set technique (active contour); the stochastic expectation-maximization approach; fuzzy clustering-based segmentation (FCM); and a variant of FCM, the spatial wavelet-based algorithm (FCM-SW) which incorporates spatial information during the segmentation process, thus allowing the handling of uptake in heterogeneous lesions. These algorithms were evaluated using clinical studies in which the segmentation results were compared to the 3-D biological tumour volume (BTV) defined by histology in PET images of seven patients with T3-T4 laryngeal squamous cell carcinoma who underwent a total laryngectomy. The macroscopic tumour specimens were collected "en bloc”, frozen and cut into 1.7- to 2-mm thick slices, then digitized for use as reference. Results: The clinical results suggested that four of the thresholding methods and expectation-maximization overestimated the average tumour volume, while a contrast-oriented thresholding method, the level set technique and the FCM-SW algorithm underestimated it, with the FCM-SW algorithm providing relatively the highest accuracy in terms of volume determination (−5.9 ± 11.9%) and overlap index. The mean overlap index varied between 0.27 and 0.54 for the different image segmentation techniques. The FCM-SW segmentation technique showed the best compromise in terms of 3-D overlap index and statistical analysis results with values of 0.54 (0.26-0.72) for the overlap index. Conclusion: The BTVs delineated using the FCM-SW segmentation technique were seemingly the most accurate and approximated closely the 3-D BTVs defined using the surgical specimens. Adaptive thresholding techniques need to be calibrated for each PET scanner and acquisition/processing protocol, and should not be used without optimizatio
Qualitative and Quantitative Assessment of Metal Artifacts Arising from Implantable Cardiac Pacing Devices in Oncological PET/CT Studies: A Phantom Study
Purpose: We evaluate the magnitude of metallic artifacts caused by various implantable cardiac pacing devices (without leads) on both attenuation maps (μ-maps) and positron emission tomography (PET) images using experimental phantom studies. We also assess the efficacy of a metal artifact reduction (MAR) algorithm along with the severity of artifacts in the presence of misalignment between μ-maps and PET images. Methods: Four pacing devices including two pacemakers (pacemakers 1 and 2) and two cardiac resynchronization therapy (CRT) devices of pacemaker (CRT-P) and defibrillator (CRT-D) type were placed in three phantoms including a cylindrical Ge-68 phantom, a water-bath phantom and an anthropomorphic heart/thorax phantom. The μ-maps were derived from computed tomography (CT) images reconstructed using the standard method supplied by the manufacturer and those reconstructed using the MAR algorithm. In addition, the standard reconstructed CT images of the last two phantoms were manually misaligned by 10mm along the patient's axis to simulate misalignment between CT and PET images. Results: The least and severest artifacts produced on both μ-maps and PET images of the Ge-68 phantom were induced by CRT-P and pacemaker 1 devices, respectively. In the water-bath phantom, CRT-P induced 17.5% over- and 9.2% underestimation of tracer uptake whereas pacemaker 1 induced 69.6% over- and 65.7% underestimation. In the heart/thorax phantom representing a pacemaker-bearing patient, pacemaker 1 induced 41.8% increase and 36.6% decrease in tracer uptake and attenuation coefficients on average in regions corresponding to bright and dark streak artifacts, respectively. Statistical analysis revealed that the MAR algorithm was successful in reducing bright streak artifacts, yet unsuccessful for dark ones. In the heart/thorax phantom, the MAR algorithm reduced the overestimations to 4.4% and the underestimations to 35.5% on average. Misalignment between μ-maps and PET images increased the peak of pseudo-uptake by approximately 20%. Conclusions: This study demonstrated that, depending on their elemental composition, different implantable cardiac pacing devices result in varying magnitudes of metal artifacts and thus pseudo-uptake on PET images. The MAR algorithm was not successful in compensating for underestimations which calls for a more efficient algorithm. The results showed that misalignments between PET and CT images render metal-related pseudo-uptake more sever
Reduction of artefacts caused by hip implants in CT-based attenuation-corrected PET images using 2-D interpolation of a virtual sinogram on an irregular grid
Purpose: Metallic prosthetic replacements, such as hip or knee implants, are known to cause strong streaking artefacts in CT images. These artefacts likely induce over- or underestimation of the activity concentration near the metallic implants when applying CT-based attenuation correction of positron emission tomography (PET) images. Since this degrades the diagnostic quality of the images, metal artefact reduction (MAR) prior to attenuation correction is required. Methods: The proposed MAR method, referred to as virtual sinogram-based technique, replaces the projection bins of the sinogram that are influenced by metallic implants by a 2-D Clough-Tocher cubic interpolation scheme performed in an irregular grid, called Delaunay triangulated grid. To assess the performance of the proposed method, a physical phantom and 30 clinical PET/CT studies including hip prostheses were used. The results were compared to the method implemented on the Siemens Biograph mCT PET/CT scanner. Results: Both phantom and clinical studies revealed that the proposed method performs equally well as the Siemens MAR method in the regions corresponding to bright streaking artefacts and the artefact-free regions. However, in regions corresponding to dark streaking artefacts, the Siemens method does not seem to appropriately correct the tracer uptake while the proposed method consistently increased the uptake in the underestimated regions, thus bringing it to the expected level. This observation is corroborated by the experimental phantom study which demonstrates that the proposed method approaches the true activity concentration more closely. Conclusion: The proposed MAR method allows more accurate CT-based attenuation correction of PET images and prevents misinterpretation of tracer uptake, which might be biased owing to the propagation of bright and dark streaking artefacts from CT images to the PET data following the attenuation correction procedur
Reduction of artefacts caused by hip implants in CT-based attenuation-corrected PET images using 2-D interpolation of a virtual sinogram on an irregular grid
Metallic prosthetic replacements, such as hip or knee implants, are known to cause strong streaking artefacts in CT images. These artefacts likely induce over- or underestimation of the activity concentration near the metallic implants when applying CT-based attenuation correction of positron emission tomography (PET) images. Since this degrades the diagnostic quality of the images, metal artefact reduction (MAR) prior to attenuation correction is required
Comparative methods for PET image segmentation in pharyngolaryngeal squamous cell carcinoma
Several methods have been proposed for the segmentation of ¹⁸F-FDG uptake in PET. In this study, we assessed the performance of four categories of ¹⁸F-FDG PET image segmentation techniques in pharyngolaryngeal squamous cell carcinoma using clinical studies where the surgical specimen served as the benchmark
Development and evaluation of metal artifact reduction and image segmentation techniques in PET/CT
Rekentechnieken om meer informatie uit PET-beeld te halen Artsen baseren hun behandelplan onder andere op beelden van een PET-scan. Maar deze zijn niet altijd vrij van onvolkomenheden, bijvoorbeeld door ruis of strepen veroorzaakt door metalen implantaten. Bovendien komen twee artsen op basis van dezelfde beelden vaak tot een andere conclusie. Mehrsima Abdoli ontwikkelde in haar promotieonderzoek verschillende rekentechnieken om de onvolkomenheden in PET-beelden te corrigeren. Met de resultaten die deze opleveren kunnen artsen en radiologen een preciezere diagnose stellen. Abdoli bestudeerde twee problemen: de strepen die metalen implantaten veroorzaken op PET-beelden, met als gevolg een onjuist of verkeerd beeld van het weefsel in de buurt van dat implantaat, en de moeilijkheid om tot een accurate inschatting te komen van de omvang van een tumor. Met betrekking tot dat eerste probleem stelt ze dat er verschillende technieken zijn om het beeld te corrigeren, en dat een combinatie van twee technieken (sinogram en interpolatie-gebaseerde technieken) de beste resultaten geeft. In het tweede deel van haar proefschrift stelt Abdoli dat het correct aflijnen van tumorvolume op PET-beelden lastig is, door de beperkte resolutie en ruis van die beelden. Handmatig aflijnen levert vaak verschillende berekeningen op. Na vergelijking van verschillende segmentatietechnieken, waarbij de tumor laagje voor laagje bestudeerd wordt, concludeert ze dat mogelijk is om het ruisniveau van PET-beelden te verminderen door in plaats van die segmentatietechnieken een vervormbaar contourmodel te gebruiken.
Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging
Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images, which in turn propagate to corresponding functional positron emission tomography (PET) images during the CT-based attenuation correction procedure commonly used on hybrid clinical PET/CT scanners. Therefore, visual artifacts and overestimation and/or underestimation of the tracer uptake in regions adjacent to metallic implants are likely to occur and as such, inaccurate quantification of the tracer uptake and potential erroneous clinical interpretation of PET images is expected. Accurate quantification of PET data requires metal artifact reduction (MAR) of the CT images prior to the application of the CT-based attenuation correction procedure. In this review, the origins of metallic artifacts and their impact on clinical PET/CT imaging are discussed. Moreover, a brief overview of proposed MAR methods and their advantages and drawbacks is presented. Although most of the presented MAR methods are mainly developed for diagnostic CT imaging, their potential application in PET/CT imaging is highlighted. The challenges associated with comparative evaluation of these methods in a clinical environment in the absence of a gold standard are also discussed. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4709599
A virtual sinogram method to reduce dental metallic implant artefacts in computed tomography-based attenuation correction for PET
OBJECTIVE: Attenuation correction of PET data requires accurate determination of the attenuation map (mumap), which represents the spatial distribution of linear attenuation coefficients of different tissues at 511 keV. The presence of high-density metallic dental filling material in head and neck X-ray computed tomography (CT) scanning is known to generate streak artefacts in the resulting CT images and thus in the corresponding mumaps generated using CT-based attenuation correction. Consequently, an under/overestimation of activity concentration occurs in corresponding regions of the corrected PET images. The purpose of this study is to develop a simple yet practical approach for reduction of metallic dental implant artefacts in the generated mumaps. METHODS: Currently available sinogram-based metal artefact reduction (MAR) algorithms operate directly on the raw sinograms. These usually consist of huge files stored in proprietary format not easily disclosed by the manufacturers and thus are not straightforward to read and manipulate. The proposed method uses the concept of virtual sinograms produced by forward projection of CT images in Dicom format for MAR. The projection data affected by metallic objects are detected in the sinogram space through segmentation of metallic objects in the CT image followed by forward projection of the metal-only image. Thereafter, the affected sinogram bins are replaced by interpolated values from adjacent projections using the spline interpolation technique. The algorithm was assessed using a polyethylene phantom containing materials simulating different tissues and a dedicated jaw phantom scanned before and after the insertion of metallic objects, where the corrected and noncorrected mumaps were compared with the artefact-free mumap. In addition, the Jaszczak and standard germanium phantoms including four metallic inserts were scanned on a PET/CT scanner to evaluate the impact of the MAR procedure on PET data through the comparison of uncorrected and corrected PET images to the actual activity concentrations in the phantoms. The proposed algorithm was also applied to head and neck CT images of 10 patients with metallic dental implants. RESULTS: The MAR method proved to be practical in a clinical setting and reduced substantially the visible metal induced artefacts. The mean relative error in regions close to metallic objects is reduced by approximately 90%. The statistical analysis of the Jaszczak and solid Ge-68 phantoms PET images did not reveal statistically significant differences between the corrected and artefact-free images (P>0.05). Moreover, the evaluation of clinical studies did not reveal statistically significant differences between the attenuation coefficients of the corrected mumaps and the expected theoretical values. CONCLUSION: The proposed MAR method provides a simple and convenient approach allowing correction for the presence of metal artefacts caused by dental implants without the need to manipulate the complex raw CT data. Further evaluation using a larger clinical PET/CT database is under way to evaluate the potential of the technique in a clinical setting
Qualitative and quantitative assessment of metal artifacts arising from implantable cardiac pacing devices in oncological PET/CT studies: a phantom study
We evaluate the magnitude of metallic artifacts caused by various implantable cardiac pacing devices (without leads) on both attenuation maps (μ-maps) and positron emission tomography (PET) images using experimental phantom studies. We also assess the efficacy of a metal artifact reduction (MAR) algorithm along with the severity of artifacts in the presence of misalignment between μ-maps and PET images