Phase contrast imaging is used to observe Bose-Einstein condensates at finite temperature in situ. The imaging technique is used to accurately derive the absolute phase shift of a probe laser beam due to both the condensate and the thermal cloud. The accuracy of the method is enhanced by using the periodicity of the intensity signal as a function of the accumulated phase. The measured density profiles can be described using a two-relevant-parameter fit, in which only the chemical potential and the temperature are to be determined. This allows us to directly compare the measured density profiles to different mean-field models in which the interaction between the condensed and the thermal atoms is taken into account to various degrees.

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At our institution EPID (electronic portal imaging device) dosimetry is routinely applied to perform in vivo dose verification of all patient treatments with curative intent since January 2008. The major impediment of the method has been the amount of work required to produce and inspect the in vivo dosimetry reports (a time-consuming and labor-intensive process). In this paper we present an overview of the actions performed to implement an automated in vivo dosimetry solution clinically. We reimplemented the EPID dosimetry software and modified the acquisition software. Furthermore, we introduced new tools to periodically inspect the record-and-verify database and automatically run the EPID dosimetry software when needed. In 2012, 95% of our 3839 treatments scheduled for in vivo dosimetry were analyzed automatically (27,633 portal images of intensity-modulated radiotherapy (IMRT) fields, 5551 portal image data of VMAT arcs, and 2003 portal images of non-IMRT fields). The in vivo dosimetry verification results are available a few minutes after delivery and alerts are immediately raised when deviations outside tolerance levels are detected. After the clinical introduction of this automated solution, inspection of the detected deviations is the only remaining work. These newly developed tools are a major step forward towards full integration of in vivo EPID dosimetry in radiation oncology practice.

A prototype online 3D dose verification tool using portal imaging has been developed and successfully tested for two different kinds of gross delivery errors. Thus, online 3D dose verification has been technologically achieved.

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Purpose: To assess the sensitivity of various EPID dosimetry alert indicators to patient-related variations and to determine alert threshold values that ensure excellent error detectability. Methods: Our virtual dose reconstruction method uses in air EPID measurements to calculate virtual 3D dose distributions within a CT data set. Patient errors are introduced by transforming the plan-CT into an error-CT data set. Virtual patient dose distributions reconstructed using the plan-CT and the error-CT data set are compared to the planned dose distributions by c(3%/3 mm) and DVH analysis using seven indicators: DD ISOC , c-mean, near c-max, c-pass rate, DPTV D2 , DPTV D50, and DPTV D98 . Translation and rotation patient setup errors and uniform contour changes are studied for 104 VMAT plans of 4 treatment sites. Lung expansions and contractions to simulate changes in lung density are considered for 26 IMRT lung plans. A ROC curve is generated for each combination of error and indicator. For each ROC curve, the AUC value and the optimal alert threshold value of the indicator are determined. Results: AUC values for c-indicators and DPTV D2 are consistently higher than for DD ISOC and DPTV D98 . For VMAT plans, error detectability to patient position shifts is worse for pelvic treatments and best for head-and-neck and brain plans. Excellent detectability is observed for 5 mm translations in head-and-neck plans (AUC = 0.94) and for 4°rotations in brain plans (AUC = 0.89). All sites but prostate show good-to-excellent detectability (AUC > 0.8) for 10 mm translations and 8°r otations and excellent detectability (AUC > 0.9) for AE6 mm patient contour changes. For head-andneck, excellent detectability is obtained with c-mean and c-pass rate threshold values of around 0.63 and 83%, respectively. For brain and rectum, these threshold values are 0.53 and 90%, respectively. In IMRT lung plans, expansions of 3 mm and contractions of 6 mm are detected (AUC > 0.8).Conclusions: By combining virtual dose reconstructions with synthetic patient data, we developed a framework to assess the sensitivity of our 3D EPID transit dosimetry method to patient-related variations. The detectability of each introduced error is specific to the treatment site and indicator used. Optimal alert criteria can be determined to ensure excellent detectability for each combination of error type and indicator. The alert threshold values and the magnitude of the error that can be detected are site-specific. In situations where the minimum error that can be detected is larger than the clinically desirable action level, EPID transit dosimetry must be used in combination with IGRT procedures to ensure correct patient positioning and early detection of anatomy variations.

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