Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for stereotactic body radiation therapy

The motion of lung tumors during respiration makes the accurate delivery of radiation therapy to the thorax difficult because it increases the uncertainty of target position. The adoption of four-dimensional computed tomography (4D-CT) has allowed us to determine how a tumor moves with respiration for each individual patient. Using information acquired during a 4D-CT scan, we can define the target, visualize motion, and calculate dose during the planning phase of the radiotherapy process. One image data set that can be created from the 4D-CT acquisition is the maximum-intensity projection (MIP). The MIP can be used as a starting point to define the volume that encompasses the motion envelope of the moving gross target volume (GTV). Because of the close relationship that exists between the MIP and the final target volume, we investigated four MIP data sets created with different methodologies (3 using various 4D-CT sorting implementations, and one using all available cine CT images) to compare target delineation. It has been observed that changing the 4D-CT sorting method will lead to the selection of a different collection of images; however, the clinical implications of changing the constituent images on the resultant MIP data set are not clear. There has not been a comprehensive study that compares target delineation based on different 4D-CT sorting methodologies in a patient population. We selected a collection of patients who had previously undergone thoracic 4D-CT scans at our institution, and who had lung tumors that moved at least 1 cm. We then generated the four MIP data sets and automatically contoured the target volumes. In doing so, we identified cases in which the MIP generated from a 4D-CT sorting process under-represented the motion envelope of the target volume by more than 10% than when measured on the MIP generated from all of the cine CT images. The 4D-CT methods suffered from duplicate image selection and might not choose maximum extent images. Based on our results, we suggest utilization of a MIP generated from the full cine CT data set to ensure a representative inclusive tumor extent, and to avoid geometric miss.

A biophysical model of synaptic plasticity and metaplasticity can account for the dynamics of the backward shift of hippocampal place fields.

Hippocampal place cells in the rat undergo experience-dependent changes when the rat runs stereotyped routes. One such change, the backward shift of the place field center of mass, has been linked by previous modeling efforts to spike-timing-dependent plasticity (STDP). However, these models did not account for the termination of the place field shift and they were based on an abstract implementation of STDP that ignores many of the features found in cortical plasticity. Here, instead of the abstract STDP model, we use a calcium-dependent plasticity (CaDP) learning rule that can account for many of the observed properties of cortical plasticity. We use the CaDP learning rule in combination with a model of metaplasticity to simulate place field dynamics. Without any major changes to the parameters of the original model, the present simulations account both for the initial rapid place field shift and for the subsequent slowing down of this shift. These results suggest that the CaDP model captures the essence of a general cortical mechanism of synaptic plasticity, which may underlie numerous forms of synaptic plasticity observed both in vivo and in vitro.

The relationship between the field-shifting phenomenon and representational coherence of place cells in CA1 and CA3 in a cue-altered environment.

Subfields of the hippocampus display differential dynamics in processing a spatial environment, especially when changes are introduced to the environment. Specifically, when familiar cues in the environment are spatially rearranged, place cells in the CA3 subfield tend to rotate with a particular set of cues (e.g., proximal cues), maintaining a coherent spatial representation. Place cells in CA1, in contrast, display discordant behaviors (e.g., rotating with different sets of cues or remapping) in the same condition. In addition, on average, CA3 place cells shift their firing locations (measured by the center of mass, or COM) backward over time when the animal encounters the changed environment for the first time, but not after that first experience. However, CA1 displays an opposite pattern, in which place cells exhibit the backward COM-shift only from the second day of experience, but not on the first day. Here, we examined the relationship between the environment-representing behavior (i.e., rotation vs. remapping) and the COM-shift of place fields in CA1 and CA3. Both in CA1 and CA3, the backward (as well as forward) COM-shift phenomena occurred regardless of the rotating versus remapping of the place cell. The differential, daily time course of the onset/offset of backward COM-shift in the cue-altered environment in CA1 and CA3 (on day 1 in CA1 and from day 2 onward in CA3) stems from different population dynamics between the subfields. The results suggest that heterogeneous, complex plasticity mechanisms underlie the environment-representating behavior (i.e., rotate/remap) and the COM-shifting behavior of the place cell.