Project description:PurposeOur purpose was to assess the suitability of airway-implanted internal fiducial markers and an external surrogate of respiratory motion for motion management during radiation therapy of lung tumors.Methods and materialsWe analyzed 4-dimensional computed tomography scans acquired during radiation therapy simulation for 28 patients with lung tumors who had anchored fiducial markers bronchoscopically implanted inside small airways in or near the tumor in a prospective trial. We used a linear mixed model to build population-based correlative models of tumor and surrogate motion. The first 24 of the 28 patients were used to build correlative models, and 4 of the 28 consecutive patients were excluded and used as an internal validation cohort. Of the 24 patients from the model building cohort, all were used for the models based on the internal fiducial. The external surrogate was completely visualized in 11 patients from the model building cohort, so only those were used for the models based on the external surrogate. Furthermore, we determined the predicted residual error sum of squares for our correlative models, which may serve as benchmarks for future research.ResultsThe motion of the internal fiducials was significantly associated with the tumor motion in the anterior-posterior (P < .0001) and superior-inferior (SI) directions (P < .0001). We also observed a strong correlation of the external surrogate anterior-posterior motion to the tumor dominant SI motion (P < .0001). In the validation cohort, the internal fiducial SI motion was the only reliable predictor of lung tumor motion.ConclusionsThe internal fiducials appear to be more reliable predictors of lung tumor motion than the external surrogate. The suitability of such airway-implanted internal fiducial markers for advanced motion management techniques should be further investigated. Although the external surrogate seems to be less reliable, its wide availability and noninvasive application support its clinical utility, albeit the greater uncertainty will need to be compensated for.
Project description:Quantifying small, rapidly evolving forces generated by cells is a major challenge for the understanding of biomechanics and mechanobiology in health and disease. Traction force microscopy remains one of the most broadly applied force probing technologies but typically restricts itself to slow events over seconds and micron-scale displacements. Here, we improve >2-fold spatially and >10-fold temporally the resolution of planar cellular force probing compared to its related conventional modalities by combining fast two-dimensional total internal reflection fluorescence super-resolution structured illumination microscopy and traction force microscopy. This live-cell 2D TIRF-SIM-TFM methodology offers a combination of spatio-temporal resolution enhancement relevant to forces on the nano- and sub-second scales, opening up new aspects of mechanobiology to analysis.
Project description:Rotating mirror cameras represent a workhorse technology for high speed imaging in the MHz framing regime. The technique requires that the target image be swept across a series of juxtaposed CCD sensors, via reflection from a rapidly rotating mirror. Employing multiple sensors in this fashion can lead to spatial jitter in the resultant video file, due to component misalignments along the individual optical paths to each CCD. Here, we highlight that static and dynamic fiducials can be exploited as an effective software-borne countermeasure to jitter, suppressing the standard deviation of the corrected file relative to the raw data by up to 88.5% maximally, and 66.5% on average over the available range of framing rates. Direct comparison with industry-standard algorithms demonstrated that our fiducial-based strategy is as effective at jitter reduction, but typically also leads to an aesthetically superior final form in the post-processed video files.
Project description:Accurate spatial correspondence between template and subject images is a crucial step in neuroimaging studies and clinical applications like stereotactic neurosurgery. In the absence of a robust quantitative approach, we sought to propose and validate a set of point landmarks, anatomical fiducials (AFIDs), that could be quickly, accurately, and reliably placed on magnetic resonance images of the human brain. Using several publicly available brain templates and individual participant datasets, novice users could be trained to place a set of 32 AFIDs with millimetric accuracy. Furthermore, the utility of the AFIDs protocol is demonstrated for evaluating subject-to-template and template-to-template registration. Specifically, we found that commonly used voxel overlap metrics were relatively insensitive to focal misregistrations compared to AFID point-based measures. Our entire protocol and study framework leverages open resources and tools, and has been developed with full transparency in mind so that others may freely use, adopt, and modify. This protocol holds value for a broad number of applications including alignment of brain images and teaching neuroanatomy.