[en] Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each daily CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.

[en] Purpose: Develop a method to segment regions of interest (ROIs) in tumor with statistically similar Hounsfield unit (HU) values and/or HU changes during chemoradiation therapy (CRT) delivery, to assess spatial tumor treatment response based on daily CTs during CRT delivery. Methods: Generate a three region map of ROIs with differential HUs, by sampling neighboring voxels around a selected voxel and comparing to the mean of the entire ROI using a t-test. The cumulative distribution function, P, is calculated from the t-test. The P value is assigned to be the value at the selected voxel, and this is repeated over all voxels in the initial ROI. Three regions are defined as: (1-P) < 0.00001 (mid region), and 0.00001 < (1-P) (mean greater than baseline and mean lower than baseline). The test is then expanded to compare daily CT sets acquired during routine CT-guided RT delivery using a CT-on-rails. The first fraction CT is used as the baseline for comparison. We tested 15 pancreatic head tumor cases undergoing CRT, to identify the ROIs and changes corresponding to normal, fibrotic, and tumor tissue. The obtained ROIs were compared with MRI-ADC maps acquired pre- and post-CRT. Results: The ROIs in 13 out of 15 patients’ first fraction CTs and pre-CRT MRIs matched the general region and slices covered, as well as in 6 out of the 9 patients with post-CRT MRIs. The high HU region designated by the t-test was seen to correlate with the tumor region in MR, and these ROIs are positioned within the same region over the course of treatment. In patients with poorly delineated tumors in MR, the t-test was inconclusive. Conclusion: The proposed statistical segmentation technique shows the potential to identify regions in tumor with differential HUs and HU changes during CRT delivery for patients with pancreas head cancer.

[en] Purpose: To determine whether Presage 3D polymer dosimeter dose response is sensitive to dose delivery fractionation. Bang gels have demonstrated a dose fractionation related dependence in which a single 400 cGy irradiation would produce a different detector response than four 100 cGy irradiations even if delivered closely in time to one another. Such a fractional dependent response in Presage would be detrimental for measuring multi-beam irradiations. Methods: Two separate batches of Presage were poured into cuvettes, and a third batch was molded into cuvette shaped blocks. A total of 37 cuvettes/blocks were irradiated in a Cobalt-60 irradiator to 400 cGy within solid water phantoms in either one, eight, or sixteen fractions. Another group of 15 cuvettes were also kept unirradiated and used for background subtraction between the pre-scan and post-scan results. The times between fractional deliveries were held constant at 30 seconds and the Cobalt irradiator dose rate was 49 cGy/min. Each Presage batch has a separate dose sensitivity and therefore fractionation response comparisons were only performed within the same batch. The cuvettes were first pre-scanned the day prior to irradiation and post-scanned the day after irradiation. Other than approximately 3 hours warming time prior to each irradiation and optical density measurement the cuvettes were stored in a refrigerator. All cuvettes were stored in a lightless environment throughout manufacturing and testing. The cuvettes’ optical densities were optically measured at 632 nm with a spectrophotometer. Results: No noticeable dose fractionation dependence was detected for any of the three independent batches of Presage for either the eight or sixteen fraction irradiation schemes. Conclusion: These results indicate using Presage 3D dosimeters to measure multi-beam photon irradiations common in IMRT, Gamma Knife, and Cyberknife treatment delivery schemes. Presage dosimeters are made by and trademarked by Heuris Inc. Skillman, NJ. Dr. John Adamovics is a founder of Heuris Inc

[en] Experimental measurements of the projectile angular distributions for 2.5-keV Ar⁸⁺ ions capturing one to five electrons from a gas-phase C₆₀ target are presented. The number of captured electrons was determined by demanding a coincidence between the scattered projectile and a charge-state-analyzed intact C₆₀ recoil ion. The results are compared to calculations based on a dynamical classical overbarrier model. Good agreement is obtained only if the influence on the projectile trajectory by the large polarizability of the C₆₀ target is taken into account, thereby making the collective dielectric response of the cluster target observable in a scattering experiment. copyright 1998 The American Physical Society