3 resultados para X-ray computed tomography

em DigitalCommons@The Texas Medical Center


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RATIONALE AND OBJECTIVES: Polyethylene glycol-coated liposomal blood pool contrast agents maintain contrast enhancement over several hours. This study aimed to evaluate (long-term) imaging of pulmonary arteries, comparing conventional iodinated contrast with a liposomal blood pool contrast agent. Also, visualization of the (real-time) therapeutic effects of tissue plasminogen activator (t-PA) on pulmonary embolism (PE) was attempted. MATERIALS AND METHODS: Six rabbits (weight approximately 4 kg) had autologous blood clots injected through the superior vena cava. Imaging was performed using conventional contrast (iohexol, 350 mg I/ml; GE HealthCare, Princeton, NJ) at a dose of 1400 mg I per animal, and after wash-out, animals were imaged using an iodinated liposomal blood pool agent (88 mg I/mL, dose 900 mg I/animal). Subsequently, five animals were injected with 2 mg of t-PA and imaging continued for up to 4(1/2) hours. RESULTS: Both contrast agents identified PE in the pulmonary trunk and main pulmonary arteries in all rabbits. Liposomal blood pool agent yielded uniform enhancement, which remained relatively constant throughout the experiments. Conventional agents exhibited nonuniform opacification and rapid clearance postinjection. Three of six rabbits had mistimed bolus injections, requiring repeat injections. Following t-PA, pulmonary embolus volume (central to segmental) decreased in four of five treated rabbits (range 10-57%, mean 42%). One animal showed no response to t-PA. CONCLUSIONS: Liposomal blood pool agents effectively identified acute PE without need for reinjection. PE resolution following t-PA was quantifiable over several hours. Blood pool agents offer the potential for repeated imaging procedures without need for repeated (nephrotoxic) contrast injections.

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BACKGROUND: Situs inversus (SI) is a relatively rare occurrence in patients with pancreatic adenocarcinoma. Pancreatic resection in these patients has rarely been described. CT scan imaging is a principle modality for detecting pancreatic cancer and its use in SI patients is seldom reported. CASE PRESENTATION: We report a 48 year old woman with SI who, despite normal CT scan 8 months earlier, presented with obstructive jaundice and a pancreatic head mass requiring a pancreaticoduodenectomy. The surgical pathology report demonstrated pancreatic adenocarcinoma. CONCLUSION: SI is a rare condition with concurrent pancreatic cancer being even rarer. Despite the rarity, pancreaticoduodenectomy in these patients for resectable lesions is safe as long as special consideration to the anatomy is taken. Additionally, radiographic imaging has significantly improved detection of early pancreatic cancer; however, there continues to be a need for improved detection of small neoplasms.

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Proton radiation therapy is gaining popularity because of the unique characteristics of its dose distribution, e.g., high dose-gradient at the distal end of the percentage-depth-dose curve (known as the Bragg peak). The high dose-gradient offers the possibility of delivering high dose to the target while still sparing critical organs distal to the target. However, the high dose-gradient is a double-edged sword: a small shift of the highly conformal high-dose area can cause the target to be substantially under-dosed or the critical organs to be substantially over-dosed. Because of that, large margins are required in treatment planning to ensure adequate dose coverage of the target, which prevents us from realizing the full potential of proton beams. Therefore, it is critical to reduce uncertainties in the proton radiation therapy. One major uncertainty in a proton treatment is the range uncertainty related to the estimation of proton stopping power ratio (SPR) distribution inside a patient. The SPR distribution inside a patient is required to account for tissue heterogeneities when calculating dose distribution inside the patient. In current clinical practice, the SPR distribution inside a patient is estimated from the patient’s treatment planning computed tomography (CT) images based on the CT number-to-SPR calibration curve. The SPR derived from a single CT number carries large uncertainties in the presence of human tissue composition variations, which is the major drawback of the current SPR estimation method. We propose to solve this problem by using dual energy CT (DECT) and hypothesize that the range uncertainty can be reduced by a factor of two from currently used value of 3.5%. A MATLAB program was developed to calculate the electron density ratio (EDR) and effective atomic number (EAN) from two CT measurements of the same object. An empirical relationship was discovered between mean excitation energies and EANs existing in human body tissues. With the MATLAB program and the empirical relationship, a DECT-based method was successfully developed to derive SPRs for human body tissues (the DECT method). The DECT method is more robust against the uncertainties in human tissues compositions than the current single-CT-based method, because the DECT method incorporated both density and elemental composition information in the SPR estimation. Furthermore, we studied practical limitations of the DECT method. We found that the accuracy of the DECT method using conventional kV-kV x-ray pair is susceptible to CT number variations, which compromises the theoretical advantage of the DECT method. Our solution to this problem is to use a different x-ray pair for the DECT. The accuracy of the DECT method using different combinations of x-ray energies, i.e., the kV-kV, kV-MV and MV-MV pair, was compared using the measured imaging uncertainties for each case. The kV-MV DECT was found to be the most robust against CT number variations. In addition, we studied how uncertainties propagate through the DECT calculation, and found general principles of selecting x-ray pairs for the DECT method to minimize its sensitivity to CT number variations. The uncertainties in SPRs estimated using the kV-MV DECT were analyzed further and compared to those using the stoichiometric method. The uncertainties in SPR estimation can be divided into five categories according to their origins: the inherent uncertainty, the DECT modeling uncertainty, the CT imaging uncertainty, the uncertainty in the mean excitation energy, and SPR variation with proton energy. Additionally, human body tissues were divided into three tissue groups – low density (lung) tissues, soft tissues and bone tissues. The uncertainties were estimated separately because their uncertainties were different under each condition. An estimate of the composite range uncertainty (2s) was determined for three tumor sites – prostate, lung, and head-and-neck, by combining the uncertainty estimates of all three tissue groups, weighted by their proportions along typical beam path for each treatment site. In conclusion, the DECT method holds theoretical advantages in estimating SPRs for human tissues over the current single-CT-based method. Using existing imaging techniques, the kV-MV DECT approach was capable of reducing the range uncertainty from the currently used value of 3.5% to 1.9%-2.3%, but it is short to reach our original goal of reducing the range uncertainty by a factor of two. The dominant source of uncertainties in the kV-MV DECT was the uncertainties in CT imaging, especially in MV CT imaging. Further reduction in beam hardening effect, the impact of scatter, out-of-field object etc. would reduce the Hounsfeld Unit variations in CT imaging. The kV-MV DECT still has the potential to reduce the range uncertainty further.