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The multicellular spheroid model partly mimics tumor microenvironments in vivo and has been reported in plenty of studies regarding radiosensitivity. However, clear isolation of quiescent and proliferating cells in live conditions has been quite difficult owing to technical limitations; therefore, comprehensive characterization could not be done thus far. In this study, we succeeded in separately isolating different cell types using a fluorescent ubiquitination‐based cell cycle indicator (Fucci) and determining their radiosensitivities. Unexpectedly, proliferating cells were more radioresistant than quiescent cells due to the contact effect when spheroids were disaggregated immediately after irradiation. However, the radiosensitivity of quiescent cells was not influenced by mild hypoxia (hypoxia‐inducible factor‐1α‐positive but pimonidazole‐negative), but their radioresistance became similar to that of proliferating cells due to potentially lethal damage repair when disaggregated 24 h after irradiation. The Fucci system further allowed long‐term observation of cell kinetics inside of the spheroid following irradiation using real‐time confocal fluorescence scanning. Repeated cycles of recruitment from the quiescent to the proliferating phase resulted in cell loss from the outside of the spheroid toward the inside, causing gradual shrinkage. Interestingly, the central region of the spheroid entered a dormant stage approximately 40 days after irradiation and survived for more than 2 months. Using the Fucci system, we were able to comprehensively characterize the radiosensitivity of spheroids for the first time, which highlights the importance of cell cycle kinetics after irradiation in determining the radiosensitivity under tumor microenvironments.

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Deformable image registration (DIR) is fundamental technique for adaptive radiotherapy and image-guided radiotherapy. However, further improvement of DIR is still needed. We evaluated the accuracy of B-spline transformation-based DIR implemented in elastix. This registration package is largely based on the Insight Segmentation and Registration Toolkit (ITK), and several new functions were implemented to achieve high DIR accuracy. The purpose of this study was to clarify whether new functions implemented in elastix are useful for improving DIR accuracy. Thoracic 4D computed tomography images of ten patients with esophageal or lung cancer were studied. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomical landmarks that had been manually identified. DIR between peak-inhale and peak-exhale images was performed with four types of parameter settings. The first one represents original ITK (Parameter 1). The second employs the new function of elastix (Parameter 2), and the third was created to verify whether new functions improve DIR accuracy while keeping computational time (Parameter 3). The last one partially employs a new function (Parameter 4). Registration errors for these parameter settings were calculated using the manually determined landmark pairs. 3D registration errors with standard deviation over all cases were 1.78 (1.57), 1.28 (1.10), 1.44 (1.09) and 1.36 (1.35) mm for Parameter 1, 2, 3 and 4, respectively, indicating that the new functions are useful for improving DIR accuracy, even while maintaining the computational time, and this B-spline-based DIR could be used clinically to achieve high-accuracy adaptive radiotherapy.