PurposeTumor delineation using conventional CT images can be a challenge for pancreatic adenocarcinoma where contrast between the tumor and surrounding healthy tissue is low. This work investigates the ability of a split‐filter dual‐energy CT (DECT) system to improve pancreatic tumor contrast and contrast‐to‐noise ratio (CNR) for radiation therapy treatment planning.Materials and methodsMultiphasic scans of 20 pancreatic tumors were acquired using a split‐filter DECT technique with iodinated contrast medium, OMNIPAQUE TM. Analysis was performed on the pancreatic and portal venous phases for several types of DECT images. Pancreatic gross target volume (GTV) contrast and CNR were calculated and analyzed from mixed 120 kVp‐equivalent images and virtual monoenergetic images (VMI) at 57 and 40 keV. The role of iterative reconstruction on DECT images was also investigated. Paired t‐tests were used to assess the difference in GTV contrast and CNR among the different images.ResultsThe VMIs at 40 keV had a 110% greater image noise compared to the mixed 120 kVp‐equivalent images (P < 0.0001). VMIs at 40 keV increased GTV contrast from 15.9 ± 19.9 HU to 93.7 ± 49.6 HU and CNR from 1.37 ± 2.05 to 3.86 ± 2.78 in comparison to the mixed 120 kVp‐equivalent images. The iterative reconstruction algorithm investigated decreased noise in the VMIs by about 20% and improved CNR by about 30%.ConclusionsPancreatic tumor contrast and CNR were significantly improved using VMIs reconstructed from the split‐filter DECT technique, and the use of iterative reconstruction further improved CNR. This gain in tumor contrast may lead to more accurate tumor delineation for radiation therapy treatment planning.

Purpose Several dual‐energy computed tomography (DECT) techniques require a deformable image registration to correct for motion between the acquisition of low and high energy data. However, current DECT software does not provide tools to assess registration accuracy or allow the user to export deformed images, presenting a unique challenge for image registration quality assurance (QA). This work presents a methodology to evaluate the accuracy of DECT deformable registration and to quantify the impact of registration errors on end‐product images. Methods The deformable algorithm implemented in Siemen Healthineers's Syngo was evaluated using a deformable abdomen phantom and a rigid phantom to mimic sliding motion in the thorax. Both phantoms were imaged using sequential 80 and 140 kVp scans with motion applied between the two scans. Since Syngo does not allow the export of the deformed images, this study focused on quantifying the accuracy of various end‐product, dual‐energy images resulting from processing of deformed images. Results The Syngo algorithm performed well for the abdomen phantom with a mean registration error of 0.4 mm for landmark analysis, Dice similarity coefficients (DSCs) > 0.90 for five organs contoured, and mean iodine concentrations within 0.2 mg/mL of values measured on static images. For rigid sliding motion, the algorithm performed poorer and resulted in noticeable registration errors toward the superior and inferior scan extents and DSCs as low as 0.41 for iodine rods imaged in the phantom. Additionally, local iodine concentration errors in areas of misregistration exceeded 3 mg/mL. Conclusions This work represents the first methodology for DECT image registration QA using commercial software. Our data support the clinical use of the Syngo algorithm for abdominal sites with limited motion (i.e., pancreas and liver). However, dual‐energy images generated with this algorithm should be used with caution for quantitative measurements in areas with sliding motion.

Purpose: To characterize the energy dependence for TLD‐100 microcubes in water at kilovoltage energies. Methods: TLD‐100 microcubes with dimensions of (1 × 1 × 1) mm3 were irradiated with kilovoltage x‐rays in a custom‐built thin‐window liquid water phantom. The TLD‐100 microcubes were held in Virtual Water™ probes and aligned at a 2 cm depth in water. Irradiations were performed using the M‐series x‐ray beams of energies ranging from 50‐250 kVp and normalized to a 60Co beam located at the UWADCL. Simulations using the EGSnrc Monte Carlo Code System were performed to model the x‐ray beams, the 60Co beam, the water phantom and the dosimeters in the phantom. The egs_chamber user code was used to tally the dose to the TLDs and the dose to water. The measurements and calculations were used to determine the intrinsic energy dependence, absorbed‐dose energy dependence, and absorbed‐dose sensitivity. These values were compared to TLD‐100 chips with dimensions of (3.2 × 0.9 × 0.9) mm3. Results: The measured TLD‐100 microcube response per dose to water among all investigated x‐ray energies had a maximum percent difference of 61% relative to 60Co. The simulated ratio of dose to water to the dose to TLD had a maximum percent difference of 29% relative to 60Co. The ratio of dose to TLD to the TLD output had a maximum percent difference of 13% relative to 60Co. The maximum percent difference for the absorbed‐dose sensitivity was 15% more than the used value of 1.41. Conclusion: These results confirm that differences in beam quality have a significant effect on TLD response when irradiated in water. These results also indicated a difference in TLD‐100 response between microcube and chip geometries. The intrinsic energy dependence and the absorbed‐dose energy dependence deviated up to 10% between TLD‐100 microcubes and chips.

Purpose: To explore the dosimetric consequences of uncorrected rotational setup errors during SBRT for pancreatic cancer patients. Methods: This was a retrospective study utilizing data from ten (n=10) previously treated SBRT pancreas patients. For each original planning CT, we applied rotational transformations to derive additional CT images representative of possible rotational setup errors. This resulted in 6 different sets of rotational combinations, creating a total of 60 CT planning images. The patients’ clinical dosimetric plans were then applied to their corresponding rotated CT images. The 6 rotation sets encompassed a 3, 2 and 1‐degree rotation in each rotational direction and a 3‐degree in just the pitch, a 3‐degree in just the yaw and a 3‐degree in just the roll. After the dosimetric plan was applied to the rotated CT images, the resulting plan was then evaluated and compared with the clinical plan for tumor coverage and normal tissue sparing. Results: PTV coverage, defined here by V33 throughout all of the patients’ clinical plans, ranged from 92–98%. After an n degree rotation in each rotational direction that range decreased to 68–87%, 85–92%, and 88– 94% for n=3, 2 and 1 respectively. Normal tissue sparing defined here by the proximal stomach V15 throughout all of the patients’ clinical plans ranged from 0–8.9 cc. After an n degree rotation in each rotational direction that range increased to 0–17 cc, 0–12 cc, and 0–10 cc for n=3, 2, and 1 respectively. Conclusion: For pancreatic SBRT, small rotational setup errors in the pitch, yaw and roll direction on average caused under dosage to PTV and over dosage to proximal normal tissue. The 1‐degree rotation was on average the least detrimental to the normal tissue and the coverage of the PTV. The 3‐degree yaw created on average the lowest increase in volume coverage to normal tissue. This research was sponsored by the AAPM Education Council through the AAPM Education and Research Fund for the AAPM Summer Undergraduate Fellowship Program.