954 resultados para CT scan


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Discrepancies in finite-element model predictions of bone strength may be attributed to the simplified modeling of bone as an isotropic structure due to the resolution limitations of clinical-level Computed Tomography (CT) data. The aim of this study is to calculate the preferential orientations of bone (the principal directions) and the extent to which bone is deposited more in one direction compared to another (degree of anisotropy). Using 100 femoral trabecular samples, the principal directions and degree of anisotropy were calculated with a Gradient Structure Tensor (GST) and a Sobel Structure Tensor (SST) using clinical-level CT. The results were compared against those calculated with the gold standard Mean-Intercept-Length (MIL) fabric tensor using micro-CT. There was no significant difference between the GST and SST in the calculation of the main principal direction (median error=28°), and the error was inversely correlated to the degree of transverse isotropy (r=−0.34, p<0.01). The degree of anisotropy measured using the structure tensors was weakly correlated with the MIL-based measurements (r=0.2, p<0.001). Combining the principal directions with the degree of anisotropy resulted in a significant increase in the correlation of the tensor distributions (r=0.79, p<0.001). Both structure tensors were robust against simulated noise, kernel sizes, and bone volume fraction. We recommend the use of the GST because of its computational efficiency and ease of implementation. This methodology has the promise to predict the structural anisotropy of bone in areas with a high degree of anisotropy, and may improve the in vivo characterization of bone.

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PURPOSE To investigate the ex vivo performance of high-resolution computed tomography (CT) for quantitative assessment of percentage diameter stenosis in coronary arteries compared to histopathology. MATERIALS AND METHODS High-resolution CT was performed in 26 human heart specimens after the injection of iodinated contrast media into the coronary arteries. Coronary artery plaques were visually identified on CT images and the grade of stenosis for each plaque was measured with electronic calipers. All coronary plaques were characterized by histopathology according to the Stary classification, and the percentage of stenosis was measured. RESULTS CT depicted 84% (274/326) of all coronary plaques identified by histology. Missed plaques by CT were of Stary type I (n=31), type II (n=16), and type III (n=5). The stenosis degree significantly correlated between CT and histology (r=0.81, p<0.001). CT systematically overestimated the stenosis of calcified plaques (mean difference - 11.0 ± 9.5%, p<0.01) and systematically underestimated the stenosis of non-calcified plaques (mean difference -6.8 ± 10.4%, p<0.05), while there was no significant difference for mixed-type plaques (mean difference -0.4 ± 11.7%, p=0.85). There was a significant underestimation of stenosis degree as measured by CT for Stary II plaques (mean difference -14 ± 9%, p<0.01) and a significant overestimation for Stary VII plaques (mean difference 9 ± 10%, p<0.05), but there was no significant difference in stenosis degree between both modalities for other plaque types. CONCLUSIONS High-resolution CT reliably depicts advanced stage coronary plaques with an overall good correlation of stenosis degree compared to histology, however, the degree of stenosis is systematically overestimated in calcified and underestimated in non-calcified plaques.

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Somatostatin receptor PET tracers such as [68Ga-DOTA,1-Nal3]-octreotide (68Ga-DOTANOC) and [68Ga-DOTA,Tyr3]-octreotate (68Ga-DOTATATE) have shown promising results in patients with neuroendocrine tumors, with a higher lesion detection rate than is achieved with 18F-fluorodihydroxyphenyl-l-alanine PET, somatostatin receptor SPECT, CT, or MR imaging. 68Ga-DOTANOC has high affinity for somatostatin receptor subtypes 2, 3, and 5 (sst2,3,5). It has a wider receptor binding profile than 68Ga-DOTATATE, which is sst2-selective. The wider receptor binding profile might be advantageous for imaging because neuroendocrine tumors express different subtypes of somatostatin receptors. The goal of this study was to prospectively compare 68Ga-DOTANOC and 68Ga-DOTATATE PET/CT in the same patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) and to evaluate the clinical impact of 68Ga-DOTANOC PET/CT. Methods: Eighteen patients with biopsy-proven GEP-NETs were evaluated with 68Ga-DOTANOC and 68Ga-DOTATATE using a randomized crossover design. Labeling of DOTANOC and DOTATATE with 68Ga was standardized using a fully automated synthesis device. PET/CT findings were compared with 3-phase CT scans and in some patients with MR imaging, 18F-FDG PET/CT, and histology. Uptake in organs and tumor lesions was quantified and compared by calculation of maximum standardized uptake values (SUVmax) using volume computer-assisted reading. Results: Histology revealed low-grade GEP-NETs (G1) in 4 patients, intermediate grade (G2) in 7, and high grade (G3) in 7. 68Ga-DOTANOC and 68Ga-DOTATATE were false-negative in only 1 of 18 patients. In total, 248 lesions were confirmed by cross-sectional and PET imaging. The lesion-based sensitivity of 68Ga-DOTANOC PET was 93.5%, compared with 85.5% for 68Ga-DOTATATE PET (P = 0.005). The better performance of 68Ga-DOTANOC PET is attributed mainly to the significantly higher detection rate of liver metastases rather than tumor differentiation grade. Multivariate analysis revealed significantly higher SUVmax in G1 tumors than in G3 tumors (P = 0.009). This finding was less pronounced with 68Ga-DOTANOC (P > 0.001). Altogether, 68Ga-DOTANOC changed treatment in 3 of 18 patients (17%). Conclusion: The sst2,3,5-specific radiotracer 68Ga-DOTANOC detected significantly more lesions than the sst2-specific radiotracer 68Ga-DOTATATE in our patients with GEP-NETs. The clinical relevance of this finding has to be proven in larger studies.

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OBJECTIVE Angiographic C-arm CT may allow performing percutaneous stereotactic tumor ablations in the interventional radiology suite. Our purpose was to evaluate the accuracy of using C-arm CT for single and multimodality image fusions and to compare the targeting accuracy of liver lesions with the reference standard of MDCT. MATERIALS AND METHODS C-arm CT and MDCT scans were obtained of a nonrigid rapid prototyping liver phantom containing five 1-mm targets that were placed under skin-simulating deformable plastic foam. Target registration errors of image fusion were evaluated for single-modality and multimodality image fusions. A navigation system and stereotactic aiming device were used to evaluate target positioning errors on postinterventional scans with the needles in place fused with the C-arm CT or MDCT planning images. RESULTS Target registration error of the image fusion showed no significant difference (p > 0.05) between both modalities. In five series with a total of 25 punctures for each modality, the lateral target positioning error (i.e., the lateral distance between the needle tip and the planned trajectory) was similar for C-arm CT (mean [± SD], 1.6 ± 0.6 mm) and MDCT (1.82 ± .97 mm) (p = 0.33). CONCLUSION In a nonrigid liver phantom, angiographic C-arm CT may provide similar image fusion accuracy for comparison of intra- and postprocedure control images with the planning images and enables stereotactic targeting accuracy similar to that of MDCT.

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Purpose: Respiratory motion causes substantial uncertainty in radiotherapy treatment planning. Four-dimensional computed tomography (4D-CT) is a useful tool to image tumor motion during normal respiration. Treatment margins can be reduced by targeting the motion path of the tumor. The expense and complexity of 4D-CT, however, may be cost-prohibitive at some facilities. We developed an image processing technique to produce images from cine CT that contain significant motion information without 4D-CT. The purpose of this work was to compare cine CT and 4D-CT for the purposes of target delineation and dose calculation, and to explore the role of PET in target delineation of lung cancer. Methods: To determine whether cine CT could substitute 4D-CT for small mobile lung tumors, we compared target volumes delineated by a physician on cine CT and 4D-CT for 27 tumors with intrafractional motion greater than 1 cm. We assessed dose calculation by comparing dose distributions calculated on respiratory-averaged cine CT and respiratory-averaged 4D-CT using the gamma index. A threshold-based PET segmentation model of size, motion, and source-to-background was developed from phantom scans and validated with 24 lung tumors. Finally, feasibility of integrating cine CT and PET for contouring was assessed on a small group of larger tumors. Results: Cine CT to 4D-CT target volume ratios were (1.05±0.14) and (0.97±0.13) for high-contrast and low-contrast tumors respectively which was within intraobserver variation. Dose distributions on cine CT produced good agreement (< 2%/1 mm) with 4D-CT for 71 of 73 patients. The segmentation model fit the phantom data with R2 = 0.96 and produced PET target volumes that matched CT better than 6 published methods (-5.15%). Application of the model to more complex tumors produced mixed results and further research is necessary to adequately integrate PET and cine CT for delineation. Conclusions: Cine CT can be used for target delineation of small mobile lesions with minimal differences to 4D-CT. PET, utilizing the segmentation model, can provide additional contrast. Additional research is required to assess the efficacy of complex tumor delineation with cine CT and PET. Respiratory-averaged cine CT can substitute respiratory-averaged 4D-CT for dose calculation with negligible differences.

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PURPOSE Abundant expression of somatostatin receptors (sst) is a characteristic of neuroendocrine tumors (NET). Thus, radiolabeled somatostatin analogs have emerged as important tools for both in vivo diagnosis and therapy of NET. The two compounds most often used in functional imaging with positron emission tomography (PET) are (68)Ga-DOTATATE and (68)Ga-DOTATOC. Both analogs share a quite similar sst binding profile. However, the in vitro affinity of (68)Ga-DOTATATE in binding the sst subtype 2 (sst2) is approximately tenfold higher than that of (68)Ga-DOTATOC. This difference may affect their efficiency in detection of NET lesions, as sst2 is the predominant receptor subtype on gastroenteropancreatic NET. We thus compared the diagnostic value of PET/CT with both radiolabeled somatostatin analogs ((68)Ga-DOTATATE and (68)Ga-DOTATOC) in the same patients with gastroenteropancreatic NET. PATIENTS AND METHODS Twenty-seven patients with metastatic gastroenteropancreatic NET underwent (68)Ga-DOTATOC and (68)Ga-DOTATATE PET/CT as part of the workup before prospective peptide receptor radionuclide therapy (PRRT). The performance of both imaging methods was analyzed and compared for detection of individual lesions per patient and for eight defined body regions. A region was regarded as positive if at least one lesion was detected in that region. In addition, radiopeptide uptake in terms of the maximal standardized uptake value (SUV(max)) was compared for concordant lesions and renal parenchyma. RESULTS Fifty-one regions were found positive with both (68)Ga-DOTATATE and (68)Ga-DOTATOC. Overall, however, significantly fewer lesions were detected with (68)Ga-DOTATATE in comparison with (68)Ga-DOTATOC (174 versus 179, p < 0.05). Mean (68)Ga-DOTATATE SUV(max) across all lesions was significantly lower compared with (68)Ga-DOTATOC (16.9 ± 6.8 versus 22.1 ± 12.0, p < 0.01). Mean SUV(max) for renal parenchyma was not significantly different between (68)Ga-DOTATATE and (68)Ga-DOTATOC (12.6 ± 2.6 versus 12.6 ± 2.7). CONCLUSIONS (68)Ga-DOTATOC and (68)Ga-DOTATATE possess similar diagnostic accuracy for detection of gastroenteropancreatic NET lesions (with a potential advantage of (68)Ga-DOTATOC) despite their evident difference in affinity for sst2. Quite unexpectedly, maximal uptake of (68)Ga-DOTATOC tended to be higher than its (68)Ga-DOTATATE counterpart. However, tumor uptake shows high inter- and intraindividual variance with unpredictable preference of one radiopeptide. Thus, our data encourage the application of different sst ligands to enable personalized imaging and therapy of gastroenteropancreatic NET with optimal targeting of tumor receptors.

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PURPOSE Computed tomography (CT) accounts for more than half of the total radiation exposure from medical procedures, which makes dose reduction in CT an effective means of reducing radiation exposure. We analysed the dose reduction that can be achieved with a new CT scanner [Somatom Edge (E)] that incorporates new developments in hardware (detector) and software (iterative reconstruction). METHODS We compared weighted volume CT dose index (CTDIvol) and dose length product (DLP) values of 25 consecutive patients studied with non-enhanced standard brain CT with the new scanner and with two previous models each, a 64-slice 64-row multi-detector CT (MDCT) scanner with 64 rows (S64) and a 16-slice 16-row MDCT scanner with 16 rows (S16). We analysed signal-to-noise and contrast-to-noise ratios in images from the three scanners and performed a quality rating by three neuroradiologists to analyse whether dose reduction techniques still yield sufficient diagnostic quality. RESULTS CTDIVol of scanner E was 41.5 and 36.4 % less than the values of scanners S16 and S64, respectively; the DLP values were 40 and 38.3 % less. All differences were statistically significant (p < 0.0001). Signal-to-noise and contrast-to-noise ratios were best in S64; these differences also reached statistical significance. Image analysis, however, showed "non-inferiority" of scanner E regarding image quality. CONCLUSIONS The first experience with the new scanner shows that new dose reduction techniques allow for up to 40 % dose reduction while still maintaining image quality at a diagnostically usable level.

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PURPOSE Positron emission tomography (PET)∕computed tomography (CT) measurements on small lesions are impaired by the partial volume effect, which is intrinsically tied to the point spread function of the actual imaging system, including the reconstruction algorithms. The variability resulting from different point spread functions hinders the assessment of quantitative measurements in clinical routine and especially degrades comparability within multicenter trials. To improve quantitative comparability there is a need for methods to match different PET∕CT systems through elimination of this systemic variability. Consequently, a new method was developed and tested that transforms the image of an object as produced by one tomograph to another image of the same object as it would have been seen by a different tomograph. The proposed new method, termed Transconvolution, compensates for differing imaging properties of different tomographs and particularly aims at quantitative comparability of PET∕CT in the context of multicenter trials. METHODS To solve the problem of image normalization, the theory of Transconvolution was mathematically established together with new methods to handle point spread functions of different PET∕CT systems. Knowing the point spread functions of two different imaging systems allows determining a Transconvolution function to convert one image into the other. This function is calculated by convolving one point spread function with the inverse of the other point spread function which, when adhering to certain boundary conditions such as the use of linear acquisition and image reconstruction methods, is a numerically accessible operation. For reliable measurement of such point spread functions characterizing different PET∕CT systems, a dedicated solid-state phantom incorporating (68)Ge∕(68)Ga filled spheres was developed. To iteratively determine and represent such point spread functions, exponential density functions in combination with a Gaussian distribution were introduced. Furthermore, simulation of a virtual PET system provided a standard imaging system with clearly defined properties to which the real PET systems were to be matched. A Hann window served as the modulation transfer function for the virtual PET. The Hann's apodization properties suppressed high spatial frequencies above a certain critical frequency, thereby fulfilling the above-mentioned boundary conditions. The determined point spread functions were subsequently used by the novel Transconvolution algorithm to match different PET∕CT systems onto the virtual PET system. Finally, the theoretically elaborated Transconvolution method was validated transforming phantom images acquired on two different PET systems to nearly identical data sets, as they would be imaged by the virtual PET system. RESULTS The proposed Transconvolution method matched different PET∕CT-systems for an improved and reproducible determination of a normalized activity concentration. The highest difference in measured activity concentration between the two different PET systems of 18.2% was found in spheres of 2 ml volume. Transconvolution reduced this difference down to 1.6%. In addition to reestablishing comparability the new method with its parameterization of point spread functions allowed a full characterization of imaging properties of the examined tomographs. CONCLUSIONS By matching different tomographs to a virtual standardized imaging system, Transconvolution opens a new comprehensive method for cross calibration in quantitative PET imaging. The use of a virtual PET system restores comparability between data sets from different PET systems by exerting a common, reproducible, and defined partial volume effect.

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The combination of scaled analogue experiments, material mechanics, X-ray computed tomography (XRCT) and Digital Volume Correlation techniques (DVC) is a powerful new tool not only to examine the 3 dimensional structure and kinematic evolution of complex deformation structures in scaled analogue experiments, but also to fully quantify their spatial strain distribution and complete strain history. Digital image correlation (DIC) is an important advance in quantitative physical modelling and helps to understand non-linear deformation processes. Optical non-intrusive (DIC) techniques enable the quantification of localised and distributed deformation in analogue experiments based either on images taken through transparent sidewalls (2D DIC) or on surface views (3D DIC). X-ray computed tomography (XRCT) analysis permits the non-destructive visualisation of the internal structure and kinematic evolution of scaled analogue experiments simulating tectonic evolution of complex geological structures. The combination of XRCT sectional image data of analogue experiments with 2D DIC only allows quantification of 2D displacement and strain components in section direction. This completely omits the potential of CT experiments for full 3D strain analysis of complex, non-cylindrical deformation structures. In this study, we apply digital volume correlation (DVC) techniques on XRCT scan data of “solid” analogue experiments to fully quantify the internal displacement and strain in 3 dimensions over time. Our first results indicate that the application of DVC techniques on XRCT volume data can successfully be used to quantify the 3D spatial and temporal strain patterns inside analogue experiments. We demonstrate the potential of combining DVC techniques and XRCT volume imaging for 3D strain analysis of a contractional experiment simulating the development of a non-cylindrical pop-up structure. Furthermore, we discuss various options for optimisation of granular materials, pattern generation, and data acquisition for increased resolution and accuracy of the strain results. Three-dimensional strain analysis of analogue models is of particular interest for geological and seismic interpretations of complex, non-cylindrical geological structures. The volume strain data enable the analysis of the large-scale and small-scale strain history of geological structures.

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Virtual colonoscopy (VC) is a minimally invasive means for identifying colorectal polyps and colorectal lesions by insufflating a patient’s bowel, applying contrast agent via rectal catheter, and performing multi-detector computed tomography (MDCT) scans. The technique is recommended for colonic health screening by the American Cancer Society but not funded by the Centers for Medicare and Medicaid Services (CMS) partially because of potential risks from radiation exposure. To date, no in‐vivo organ dose measurements have been performed for MDCT scans; thus, the accuracy of any current dose estimates is currently unknown. In this study, two TLDs were affixed to the inner lumen of standard rectal catheters used in VC, and in-vivo rectal dose measurements were obtained within 6 VC patients. In order to calculate rectal dose, TLD-100 powder response was characterized at diagnostic doses such that appropriate correction factors could be determined for VC. A third-order polynomial regression with a goodness of fit factor of R2=0.992 was constructed from this data. Rectal dose measurements were acquired with TLDs during simulated VC within a modified anthropomorphic phantom configured to represent three sizes of patients undergoing VC. The measured rectal doses decreased in an exponential manner with increasing phantom effective diameter, with R2=0.993 for the exponential regression model and a maximum percent coefficient of variation (%CoV) of 4.33%. In-vivo measurements yielded rectal doses ranged from that decreased exponentially with increasing patient effective diameter, in a manner that was also favorably predicted by the size specific dose estimate (SSDE) model for all VC patients that were of similar age, body composition, and TLD placement. The measured rectal dose within a younger patient was favorably predicted by the anthropomorphic phantom dose regression model due to similarities in the percentages of highly attenuating material at the respective measurement locations and in the placement of the TLDs. The in-vivo TLD response did not increase in %CoV with decreasing dose, and the largest %CoV was 10.0%.

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Recent treatment planning studies have demonstrated the use of physiologic images in radiation therapy treatment planning to identify regions for functional avoidance. This image-guided radiotherapy (IGRT) strategy may reduce the injury and/or functional loss following thoracic radiotherapy. 4D computed tomography (CT), developed for radiotherapy treatment planning, is a relatively new imaging technique that allows the acquisition of a time-varying sequence of 3D CT images of the patient's lungs through the respiratory cycle. Guerrero et al. developed a method to calculate ventilation imaging from 4D CT, which is potentially better suited and more broadly available for IGRT than the current standard imaging methods. The key to extracting function information from 4D CT is the construction of a volumetric deformation field that accurately tracks the motion of the patient's lungs during the respiratory cycle. The spatial accuracy of the displacement field directly impacts the ventilation images; higher spatial registration accuracy will result in less ventilation image artifacts and physiologic inaccuracies. Presently, a consistent methodology for spatial accuracy evaluation of the DIR transformation is lacking. Evaluation of the 4D CT-derived ventilation images will be performed to assess correlation with global measurements of lung ventilation, as well as regional correlation of the distribution of ventilation with the current clinical standard SPECT. This requires a novel framework for both the detailed assessment of an image registration algorithm's performance characteristics as well as quality assurance for spatial accuracy assessment in routine application. Finally, we hypothesize that hypo-ventilated regions, identified on 4D CT ventilation images, will correlate with hypo-perfused regions in lung cancer patients who have obstructive lesions. A prospective imaging trial of patients with locally advanced non-small-cell lung cancer will allow this hypothesis to be tested. These advances are intended to contribute to the validation and clinical implementation of CT-based ventilation imaging in prospective clinical trials, in which the impact of this imaging method on patient outcomes may be tested.

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OBJECTIVES To find the best pairing of first and second reader at highest sensitivity for detecting lung nodules with CT at various dose levels. MATERIALS AND METHODS An anthropomorphic lung phantom and artificial lung nodules were used to simulate screening CT-examination at standard dose (100 mAs, 120 kVp) and 8 different low dose levels, using 120, 100 and 80 kVp combined with 100, 50 and 25 mAs. At each dose level 40 phantoms were randomly filled with 75 solid and 25 ground glass nodules (5-12 mm). Two radiologists and 3 different computer aided detection softwares (CAD) were paired to find the highest sensitivity. RESULTS Sensitivities at standard dose were 92%, 90%, 84%, 79% and 73% for reader 1, 2, CAD1, CAD2, CAD3, respectively. Combined sensitivity for human readers 1 and 2 improved to 97%, (p1=0.063, p2=0.016). Highest sensitivities--between 97% and 99.0%--were achieved by combining any radiologist with any CAD at any dose level. Combining any two CADs, sensitivities between 85% and 88% were significantly lower than for radiologists combined with CAD (p<0.03). CONCLUSIONS Combination of a human observer with any of the tested CAD systems provide optimal sensitivity for lung nodule detection even at reduced dose at 25 mAs/80 kVp.