The decrease in the pH during the pneumoperitoneum was affected by the increase in Pa(CO(2)), which promptly returned to a normal value after the desufflation. On the other hand, the decrease in the pH after laparotomy was affected by the metabolic factors, which persisted an hour after the surgery.

patients received pre and post treatment cone beam CT (CBCT) to evaluate the intrafractional motion of the VSI system. The intrafractional motion with the RSI system was reported to be negligible and not repeated in this study. All remaining patients received pretreatment CBCT or megavoltage CT (MVCT) to assess interfractional setup accuracy. Shifts to the final treatment position were determined based on matching bony anatomy in the pre-treatment setup CT and the planning CT. Setup CT and planning CT were registered retrospectively based on bony anatomy using image registration software to quantify rotational and translational errors. Results: Mean and standard deviation of the intrafractional motions were -0.5AE0.7mm (lateral), 0.1AE0.9mm (vertical), -0.5AE0.6mm (longitudinal), -0.04AE0.18 (pitch), -0.1AE0.23 (yaw), and -0.03AE0.17 (roll). Interfractional rotation errors were -0.10AE0.25 (pitch), -0.20AE0.41 (yaw), and -0.08AE0.16 (roll) for RSI versus 0.20AE0.69 (pitch), 0.35AE0.82 (yaw), -0.34AE0.56 (roll) for frameless VSI. In a 3D vector space, a tumor located 5cm from the center of image fusion would require a 0.9 mm margin with the RSI system and a 2.1 mm margin with VSI. Conclusion: With image guided radiation therapy, translational setup errors can be corrected by image registration between pretreatment setup CT and planning CT. However, rotational errors cannot be accounted for without 6 degree freedom couch. Our study showed that the frameless VSI immobilization system provided negligible intrafractional motion. The interfractional rotation setup error using VSI was larger than rigid immobilization with the RSI system. For single lesion far from the center of image registration or for multiple lesions, additional margin may be needed to account for the uncorrectable rotational setup errors.

Purpose/Objective(s): Lymphedema is a serious long-term complication in breast cancer patients post-surgery; however, the influence of trimodality treatments including surgery, systemic therapy, and radiotherapy (RT) on its occurrence remains unclear despite the rapid development of each modality. We sought to identify the comprehensive risk factors of lymphedema using two large patient databases, thereby enabling more informed multidisciplinary treatment decision-making. Materials/Methods: We retrospectively collected data from 5,549 breast cancer patients who underwent surgery, systemic therapy, and RT between 2007 and 2015 at our institution. Individual RT plans were reviewed for regional nodal irradiation (RNI) field design and fractionation type. Patients were categorized according to the RT field (no RNI [n Z 3,969]; RNI excluding axilla IeII [n Z 478]; and RNI including axilla IeII [n Z 1,102]) and RT fractionation (hypofractionation [n Z 927] and conventional fractionation [n Z 3,100]). The primary end-point was the lymphedema, which was defined based on objective (difference in arm circumference !2 cm) and subjective (patient perception of arm edema) methods. All patients underwent assessment by experts in Oncological Rehabilitation. We identified lymphedema risk factors using Cox's regression and used them to construct predictive nomograms that were validated internally using 1,000 bootstrap samples and externally using a separate dataset of 1,877 patients. Results: In total, 639 patients (11.5%) developed lymphedema over a median follow-up of 60 months. The 3-year lymphedema incidence was 10.5%; this rate increased with larger irradiation volumes (no RNI vs. RNI excluding axilla IeII vs. RNI including axilla IeII: 5.7% vs. 16.8% vs. 24.1%; P <.001) and when using conventional fractionation instead of hypofractionation (6.8% vs. 13.5%; P <.001). On multivariate analysis, a higher body mass index, a larger number of dissected nodes, using a taxane-based regimen, undergoing total mastectomy, a larger irradiation field, and conventional fractionation were strongly associated with the development of lymphedema (all P<.001). Nomograms constructed based on these variables to predict 2-, 3-, and 5-year lymphedema risk of the individual patients. These nomograms showed good discrimination internally (C-index: 0.77; 95% CI, 0.76e0.79) and externally (C-index: 0.83; 95% CI, 0.81e0.86). Conclusion: Factors associated with trimodality breast cancer treatments interact to promote lymphedema development, the risk of which may be decreased by modifying the RNI field and/or selecting a hypofractionated regimen. De-escalation strategy to minimize lymphedema risk should be discussed in a multidisciplinary team.

In this study, we investigated disease distribution and analyzed treatment compliance for elderly patients who have received radiation therapy (RT). Materials/Methods: Among the patients who underwent RT from January 2005 to May 2014 in this hospital, the 670 patients aged over 75 were retrospectively analyzed in this study. We classified the patients by disease and analyzed the RT compliance for each disease. The RT compliance was determined by whether or not the scheduled RT plan was completed. The chi-squared test and multiple logistic regression analysis were used for the factors (region, economic status, age, gender, disease type, treatment aim, and ECOG score) influencing the RT compliance. Results: The median age of the patients was 78 years (range; 75w99 years). The disease distribution was as follows; Lung cancer in 127 patients (19.0%), metastasis in 123 patients (18.4%), gastrointestinal (GI) cancer in 116 patients (17.3%), gynecologic cancer in 110 patients(16.4%), head and neck cancer in 53 patients (7.9%), genitourinary cancer in 44 patients (6.6%), breast cancer in 30 patients (4.5%), hematologic cancer in 22 patients (3.3%), skin cancer in 17 patients (2.5%), brain tumor in 9 patients (1.3%), and others in 19 patients (2.8%). The RT compliance in 670 patients was 82.6% (116 patients of all patients could not complete their course of scheduled treatment). According to the chi-square analysis, the factors found to be related to the RT compliance were; gender (P Z 0.001), disease type (P Z 0.014), and the patient's ECOG score International Journal of Radiation Oncology Biology Physics E410 (P<0.001). Multiple logistic regression analysis showed that gender (P Z 0.016) and the patient's ECOG score (P<0.001) were related to RT compliance. Conclusion: Based on these preliminary results, more than 80% of elderly patients received RT for lung cancer, metastatic cancer, GI cancer, gynecologic cancer, head and neck cancer, and genitourinary cancer. This study showed that the most significant factor related to RT compliance was the patient's functional status.