Uffe Bernchou

Texture of Lipid Bilayer Domains

We investigate the texture of gel (g) domains in binary lipid membranes composed of the phospholipids DPPC and DOPC. Lateral organization of lipid bilayer membranes is a topic of fundamental and biological importance. Whereas questions related to size and composition of fluid membrane domain are well studied, the possibility of texture in gel domains has so far not been examined. When using polarized light for two-photon excitation of the fluorescent lipid probe Laurdan, the emission intensity is highly sensitive to the angle between the polarization and the tilt orientation of lipid acyl chains. By imaging the intensity variations as a function of the polarization angle, we map the lateral variations of the lipid tilt within domains. Results reveal that gel domains are composed of subdomains with different lipid tilt directions. We have applied a Fourier decomposition method as a convenient way to analyze the angular intensity variations. Texture patterns of the same type have been associated with the presence of hexatic order in monolayers. The present results provide some support for the notion that hexatic order may persist in bilayers. Laurdan exhibits an emission spectral shift which correlates with the phase state of the membrane. This is quantified by the generalized polarization (GP) function, and we demonstrate that a GP analysis can be performed on supported membranes. The results show that although the gel domains have heterogeneous texture, the membrane phase state does not show spatial variation within each domain.

Growth of solid domains in model membranes: quantitative image analysis reveals a strong correlation between domain shape and spatial position

The nucleation and growth of solid domains in supported bilayers composed of a binary mixture of equimolar 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) and 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) have been studied using combined fluorescence microscopy and AFM. We have found that the formation of the DPPC-enriched solid domains occurs by a combination of homogeneous and heterogeneous nucleation and that the nucleation density is directly proportional to the cooling rate. Furthermore, during cooling the shape of the domains evolve from compact to a branched morphology. This suggests that the growth is controlled by the diffusion of DPPC from the liquid phase toward the solid domain interface. In the late stages of the growth, we observe that the size and overall shape of the domains depend on the position of the nucleation points relative to the surrounding nucleation point positions. To analyze this effect, the nucleation points were used as generators in a Voronoi construction. Associated with each generator is a Voronoi polygon that contains all points closer to this generator than to any other. Through a detailed quantitative analysis of the Voronoi cells and the domains, we have found that their area, orientation, and asymmetry correlate and that the correlation becomes stronger for larger domains. This means that the spatial distribution of the nucleation points regulate the domain shape.

Locoregional Control of Non-Small Cell Lung Cancer in Relation to Automated Early Assessment of Tumor Regression on Cone Beam Computed Tomography

PURPOSE Large interindividual variations in volume regression of non-small cell lung cancer (NSCLC) are observable on standard cone beam computed tomography (CBCT) during fractionated radiation therapy. Here, a method for automated assessment of tumor volume regression is presented and its potential use in response adapted personalized radiation therapy is evaluated empirically. METHODS AND MATERIALS Automated deformable registration with calculation of the Jacobian determinant was applied to serial CBCT scans in a series of 99 patients with NSCLC. Tumor volume at the end of treatment was estimated on the basis of the first one third and two thirds of the scans. The concordance between estimated and actual relative volume at the end of radiation therapy was quantified by Pearsons correlation coefficient. On the basis of the estimated relative volume, the patients were stratified into 2 groups having volume regressions below or above the population median value. Kaplan-Meier plots of locoregional disease-free rate and overall survival in the 2 groups were used to evaluate the predictive value of tumor regression during treatment. Cox proportional hazards model was used to adjust for other clinical characteristics. RESULTS Automatic measurement of the tumor regression from standard CBCT images was feasible. Pearsons correlation coefficient between manual and automatic measurement was 0.86 in a sample of 9 patients. Most patients experienced tumor volume regression, and this could be quantified early into the treatment course. Interestingly, patients with pronounced volume regression had worse locoregional tumor control and overall survival. This was significant on patient with non-adenocarcinoma histology. CONCLUSIONS Evaluation of routinely acquired CBCT images during radiation therapy provides biological information on the specific tumor. This could potentially form the basis for personalized response adaptive therapy.

Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients.

BACKGROUND AND PURPOSE This study investigates the ability of pre-treatment factors and response markers extracted from standard cone-beam computed tomography (CBCT) images to predict the lung density changes induced by radiotherapy for non-small cell lung cancer (NSCLC) patients. METHODS AND MATERIALS Density changes in follow-up computed tomography scans were evaluated for 135 NSCLC patients treated with radiotherapy. Early response markers were obtained by analysing changes in lung density in CBCT images acquired during the treatment course. The ability of pre-treatment factors and CBCT markers to predict lung density changes induced by radiotherapy was investigated. RESULTS Age and CBCT markers extracted at 10th, 20th, and 30th treatment fraction significantly predicted lung density changes in a multivariable analysis, and a set of response models based on these parameters were established. The correlation coefficient for the models was 0.35, 0.35, and 0.39, when based on the markers obtained at the 10th, 20th, and 30th fraction, respectively. CONCLUSIONS The study indicates that younger patients without lung tissue reactions early into their treatment course may have minimal radiation induced lung density increase at follow-up. Further investigations are needed to examine the ability of the models to identify patients with low risk of symptomatic toxicity.

Time evolution of regional CT density changes in normal lung after IMRT for NSCLC

PURPOSE This study investigates the clinical radiobiology of radiation induced lung disease in terms of regional computed tomography (CT) density changes following intensity modulated radiotherapy (IMRT) for non-small-cell lung cancer (NSCLC). METHODS A total of 387 follow-up CT scans in 131 NSCLC patients receiving IMRT to a prescribed dose of 60 or 66 Gy in 2 Gy fractions were analyzed. The dose-dependent temporal evolution of the density change was analyzed using a two-component model, a superposition of an early, transient component and a late, persistent component. RESULTS The CT density of healthy lung tissue was observed to increase significantly (p<0.0001) for all dose levels after IMRT. The time evolution and the size of the density signal depend on the local delivered dose. The transient component of the density signal was found to peak in the range of 3-4 months, while the density tends to stabilize at times >12 months. CONCLUSIONS The radiobiology of lung injury may be analyzed in terms of CT density change. The initial transient change in density is consistent with radiation pneumonitis, while the subsequent stabilization of the density is consistent with pulmonary fibrosis.

Correlation between the ripple phase and stripe domains in membranes.

We investigate the relationship between stripe domains and the ripple phase in membranes. These have previously been observed separately without being linked explicitly. Past results have demonstrated that solid and ripple phases exhibit rich textural patterns related to the orientational order of tilted lipids and the orientation of ripple corrugations. Here we reveal a highly complex network pattern of ripple and solid domains in DLPC, DPPC bilayers with structures covering length scales from 10 nm to 100 μm. Using spincoated double supported membranes we investigate domains by correlated AFM and fluorescence microscopy. Cooling experiments demonstrate the mode of nucleation and growth of stripe domains enriched in the fluorescent probe. Concurrent AFM imaging reveals that these stripe domains have a one-to-one correspondence with a rippled morphology running parallel to the stripe direction. Both thin and thick stripe domains are observed having ripple periods of 13.5±0.2 nm and 27.4±0.6 nm respectively. These are equivalent to previously observed asymmetric/equilibrium and symmetric/metastable ripple phases, respectively. Thin stripes grow from small solid domains and grow predominantly in length with a speed of ~3 times that of the thick stripes. Thick stripes grow by templating on the sides of thinner stripes or can emerge directly from the fluid phase. Bending and branching angles of stripes are in accordance with an underlying six fold lattice. We discuss mechanisms for the nucleation and growth of ripples and discuss a generic phase diagram that may partly rationalize the coexistence of metastable and stable phases.

Patient-specific scatter correction in clinical cone beam computed tomography imaging made possible by the combination of Monte Carlo simulations and a ray tracing algorithm

Abstract Purpose. Cone beam computed tomography (CBCT) image quality is limited by scattered photons. Monte Carlo (MC) simulations provide the ability of predicting the patient-specific scatter contamination in clinical CBCT imaging. Lengthy simulations prevent MC-based scatter correction from being fully implemented in a clinical setting. This study investigates the combination of using fast MC simulations to predict scatter distributions with a ray tracing algorithm to allow calibration between simulated and clinical CBCT images. Material and methods. An EGSnrc-based user code (egs_cbct), was used to perform MC simulations of an Elekta XVI CBCT imaging system. A 60keV x-ray source was used, and air kerma scored at the detector plane. Several variance reduction techniques (VRTs) were used to increase the scatter calculation efficiency. Three patient phantoms based on CT scans were simulated, namely a brain, a thorax and a pelvis scan. A ray tracing algorithm was used to calculate the detector signal due to primary photons. A total of 288 projections were simulated, one for each thread on the computer cluster used for the investigation. Results. Scatter distributions for the brain, thorax and pelvis scan were simulated within 2% statistical uncertainty in two hours per scan. Within the same time, the ray tracing algorithm provided the primary signal for each of the projections. Thus, all the data needed for MC-based scatter correction in clinical CBCT imaging was obtained within two hours per patient, using a full simulation of the clinical CBCT geometry. Conclusions. This study shows that use of MC-based scatter corrections in CBCT imaging has a great potential to improve CBCT image quality. By use of powerful VRTs to predict scatter distributions and a ray tracing algorithm to calculate the primary signal, it is possible to obtain the necessary data for patient specific MC scatter correction within two hours per patient.

Hounsfield unit recovery in clinical cone beam CT images of the thorax acquired for image guided radiation therapy

A comprehensive artefact correction method for clinical cone beam CT (CBCT) images acquired for image guided radiation therapy (IGRT) on a commercial system is presented. The method is demonstrated to reduce artefacts and recover CT-like Hounsfield units (HU) in reconstructed CBCT images of five lung cancer patients. Projection image based artefact corrections of image lag, detector scatter, body scatter and beam hardening are described and applied to CBCT images of five lung cancer patients. Image quality is evaluated through visual appearance of the reconstructed images, HU-correspondence with the planning CT images, and total volume HU error. Artefacts are reduced and CT-like HUs are recovered in the artefact corrected CBCT images. Visual inspection confirms that artefacts are indeed suppressed by the proposed method, and the HU root mean square difference between reconstructed CBCTs and the reference CT images are reduced by 31% when using the artefact corrections compared to the standard clinical CBCT reconstruction. A versatile artefact correction method for clinical CBCT images acquired for IGRT has been developed. HU values are recovered in the corrected CBCT images. The proposed method relies on post processing of clinical projection images, and does not require patient specific optimisation. It is thus a powerful tool for image quality improvement of large numbers of CBCT images.

Radiopaque marker motion during pre-treatment CBCT as a predictor of intra-fractional prostate movement

Abstract The intra-fractional movement of the prostate constitutes a hindrance for the reduction of the planning target volume margin for prostate cancer patients. Monitoring the movement of the prostate during treatment is a promising but in most centres not feasible solution. However, the projection images of the pre-treatment cone-beam computed tomography (CBCT) provide information about the motion of the target immediately preceding the treatment. This motion information can be extracted from any standard CBCT scan which is available in many institutions. In this study we measure the motion of the prostate during the pre-treatment CBCT and investigate whether this motion is correlated with the intra-fractional movement of the prostate. Material and methods. Pre- and post-treatment CBCT scans were made during a number of the fractions (average 11 range 8–12) for 13 prostate cancer patients during the radiation treatment course. The displacement of the post-treatment CBCT scans relative to the pre-treatment position was used to assess the intra-fractional motion. Automated image analysis was used to track the 2D position of radiopaque markers in the projection images of the scans. The most probable 3D trajectory of the markers during the CBCT scan was estimated based on a probability density function which was established for each individual scan. Results. The accuracy of the tracking algorithm was found satisfactory and the motion of the markers during the CBCT scans was successfully extracted from the projection images. This motion was generally small and uncorrelated with the subsequent intra-fractional movement of the prostate. The correlation coefficients were 20.05, 0.07, and 20.05 in the LR, AP, and CC direction, respectively. Conclusion. It is tempting to exploit the pre-treatment CBCT to predict the intra-fractional movement of the prostate but, unfortunately, we have found no correlation between the intra-fractional movement and the motion of the prostate immediately prior to treatment.

Automatic treatment planning facilitates fast generation of high-quality treatment plans for esophageal cancer

Abstract Background: The quality of radiotherapy planning has improved substantially in the last decade with the introduction of intensity modulated radiotherapy. The purpose of this study was to analyze the plan quality and efficacy of automatically (AU) generated VMAT plans for inoperable esophageal cancer patients. Material and Methods: Thirty-two consecutive inoperable patients with esophageal cancer originally treated with manually (MA) generated volumetric modulated arc therapy (VMAT) plans were retrospectively replanned using an auto-planning engine. All plans were optimized with one full 6MV VMAT arc giving 60 Gy to the primary target and 50 Gy to the elective target. The planning techniques were blinded before clinical evaluation by three specialized oncologists. To supplement the clinical evaluation, the optimization time for the AU plan was recorded along with DVH parameters for all plans. Results: Upon clinical evaluation, the AU plan was preferred for 31/32 patients, and for one patient, there was no difference in the plans. In terms of DVH parameters, similar target coverage was obtained between the two planning methods. The mean dose for the spinal cord increased by 1.8 Gy using AU (p = .002), whereas the mean lung dose decreased by 1.9 Gy (p < .001). The AU plans were more modulated as seen by the increase of 12% in mean MUs (p = .001). The median optimization time for AU plans was 117 min. Conclusions: The AU plans were in general preferred and showed a lower mean dose to the lungs. The automation of the planning process generated esophageal cancer treatment plans quickly and with high quality.