Gustaf Ullman

Direct measurement of transcription factor dissociation excludes a simple operator occupancy model for gene regulation

Transcription factors mediate gene regulation by site-specific binding to chromosomal operators. It is commonly assumed that the level of repression is determined solely by the equilibrium binding of a repressor to its operator. However, this assumption has not been possible to test in living cells. Here we have developed a single-molecule chase assay to measure how long an individual transcription factor molecule remains bound at a specific chromosomal operator site. We find that the lac repressor dimer stays bound on average 5 min at the native lac operator in Escherichia coli and that a stronger operator results in a slower dissociation rate but a similar association rate. Our findings do not support the simple equilibrium model. The discrepancy with this model can, for example, be accounted for by considering that transcription initiation drives the system out of equilibrium. Such effects need to be considered when predicting gene activity from transcription factor binding strengths.

High-throughput gene expression analysis at the level of single proteins using a microfluidic turbidostat and automated cell tracking

We have developed a method combining microfluidics, time-lapsed single-molecule microscopy and automated image analysis allowing for the observation of an excess of 3000 complete cell cycles of exponentially growing Escherichia coli cells per experiment. The method makes it possible to analyse the rate of gene expression at the level of single proteins over the bacterial cell cycle. We also demonstrate that it is possible to count the number of non-specifically DNA binding LacI–Venus molecules using short excitation light pulses. The transcription factors are localized on the nucleoids in the cell and appear to be uniformly distributed on chromosomal DNA. An increase in the expression of LacI is observed at the beginning of the cell cycle, possibly because some gene copies are de-repressed as a result of partitioning inequalities at cell division. Finally, a size–growth rate uncertainty relation is observed where cells living in rich media vary more in the length at birth than in generation time, and the opposite is true for cells living in poorer media.

A search for optimal x-ray spectra in iodine contrast media mammography

The aim of this work was to search for the optimal x-ray tube voltage and anode-filter combination in digital iodine contrast media mammography. In the optimization, two entities were of interest: the average glandular dose, AGD, and the signal-to-noise ratio, SNR, for detection of diluted iodine contrast medium. The optimum is defined as the technique maximizing the figure of merit, SNR2/AGD. A Monte Carlo computer program was used which simulates the transport of photons from the x-ray tube through the compression plate, breast, breast support plate, anti-scatter grid and image detector. It computes the AGD and the SNR of an iodine detail inside the compressed breast. The breast thickness was varied between 2 and 8 cm with 10-90% glandularity. The tube voltage was varied between 20 and 55 kV for each anode material (Rh, Mo and W) in combination with either 25 microm Rh or 0.05-0.5 mm Cu added filtration. The x-ray spectra were calculated with MCNP4C (Monte Carlo N-Particle Transport Code System, version 4C). A CsI scintillator was used as the image detector. The results for Rh/0.3 mmCu, Mo/0.3 mmCu and W/0.3 mmCu were similar. For all breast thicknesses, a maximum in the figure of merit was found at approximately 45 kV for the Rh/Cu, Mo/Cu and W/Cu combinations. The corresponding results for the Rh/Rh combination gave a figure of merit that was typically lower and more slowly varying with tube voltage. For a 4 cm breast at 45 kV, the SNR2/AGD was 3.5 times higher for the Rh/0.3 mmCu combination compared with the Rh/Rh combination. The difference is even larger for thicker breasts. The SNR2/AGD increases slowly with increasing Cu-filter thickness. We conclude that tube voltages between 41 and 55 kV and added Cu-filtration will result in significant dose advantage in digital iodine contrast media mammography compared to using the Rh/Rh anode/filter combination at 25-32 kV.

Towards optimization in digital chest radiography using Monte Carlo modelling

A Monte Carlo based computer model of the x-ray imaging system was used to investigate how various image quality parameters of interest in chest PA radiography and the effective dose E vary with tube voltage (90-150 kV), additional copper filtration (0-0.5 mm), anti-scatter method (grid ratios 8-16 and air gap lengths 20-40 cm) and patient thickness (20-28 cm) in a computed radiography (CR) system. Calculated quantities were normalized to a fixed value of air kerma (5.0 microGy) at the automatic exposure control chambers. Soft-tissue nodules were positioned at different locations in the anatomy and calcifications in the apical region. The signal-to-noise ratio, SNR, of the nodules and the nodule contrast relative to the contrast of bone (C/C(B)) as well as relative to the dynamic range in the image (C(rel)) were used as image quality measures. In all anatomical regions, except in the densest regions in the thickest patients, the air gap technique provides higher SNR and contrast ratios than the grid technique and at a lower effective dose E. Choice of tube voltage depends on whether quantum noise (SNR) or the contrast ratios are most relevant for the diagnostic task. SNR increases with decreasing tube voltage while C/C(B) increases with increasing tube voltage.

Evaluation of an improved method of simulating lung nodules in chest tomosynthesis

Background Simulated pathology is a valuable complement to clinical images in studies aiming at evaluating an imaging technique. In order for a study using simulated pathology to be valid, it is important that the simulated pathology in a realistic way reflect the characteristics of real pathology. Purpose To perform a thorough evaluation of a nodule simulation method for chest tomosynthesis, comparing the detection rate and appearance of the artificial nodules with those of real nodules in an observer performance experiment. Material and Methods A cohort consisting of 64 patients, 38 patients with a total of 129 identified pulmonary nodules and 26 patients without identified pulmonary nodules, was used in the study. Simulated nodules, matching the real clinically found pulmonary nodules by size, attenuation, and location, were created and randomly inserted into the tomosynthesis section images of the patients. Three thoracic radiologists and one radiology resident reviewed the images in an observer performance study divided into two parts. The first part included nodule detection and the second part included rating of the visual appearance of the nodules. The results were evaluated using a modified receiver-operating characteristic (ROC) analysis. Results The sensitivities for real and simulated nodules were comparable, as the area under the modified ROC curve (AUC) was close to 0.5 for all observers (range, 0.43–0.55). Even though the ratings of visual appearance for real and simulated nodules overlapped considerably, the statistical analysis revealed that the observers to were able to separate simulated nodules from real nodules (AUC values range 0.70–0.74). Conclusion The simulation method can be used to create artificial lung nodules that have similar detectability as real nodules in chest tomosynthesis, although experienced thoracic radiologists may be able to distinguish them from real nodules.

A Monte Carlo-based model for simulation of digital chest tomosynthesis

The aim of this work was to calculate synthetic digital chest tomosynthesis projections using a computer simulation model based on the Monte Carlo method. An anthropomorphic chest phantom was scanned in a computed tomography scanner, segmented and included in the computer model to allow for simulation of realistic high-resolution X-ray images. The input parameters to the model were adapted to correspond to the VolumeRAD chest tomosynthesis system from GE Healthcare. Sixty tomosynthesis projections were calculated with projection angles ranging from +15 to -15 degrees. The images from primary photons were calculated using an analytical model of the anti-scatter grid and a pre-calculated detector response function. The contributions from scattered photons were calculated using an in-house Monte Carlo-based model employing a number of variance reduction techniques such as the collision density estimator. Tomographic section images were reconstructed by transferring the simulated projections into the VolumeRAD system. The reconstruction was performed for three types of images using: (i) noise-free primary projections, (ii) primary projections including contributions from scattered photons and (iii) projections as in (ii) with added correlated noise. The simulated section images were compared with corresponding section images from projections taken with the real, anthropomorphic phantom from which the digital voxel phantom was originally created. The present article describes a work in progress aiming towards developing a model intended for optimisation of chest tomosynthesis, allowing for simulation of both existing and future chest tomosynthesis systems.

Simulation of lung nodules in chest tomosynthesis.

The aim of the present work was to develop an adequate method for simulating lung nodules in clinical chest tomosynthesis images. Based on the visual appearance of real nodules, artificial, three-dimensional nodules with irregular shape and surface structure were created using an approach of combining spheres of different sizes and central points. The nodules were virtually positioned at the desired locations inside the patient and by using the known geometry of the tomosynthesis acquisition, the radiation emitted from the focal spot, passing through the nodule and reaching the detector could be simulated. The created nodules were thereby projected into raw-data tomosynthesis projection images before reconstruction of the tomosynthesis section images. The focal spot size, signal spread in the detector, scattered radiation, patient motion and existing anatomy at the location of the nodule were taken into account in the simulations. It was found that the blurring caused by the modulation transfer function and the patient motion overshadows the effects of a finite focal spot and aliasing and also obscures the surface structure of the nodules, which provides an opportunity to simplify the simulations and decrease the simulation times. Also, the limited in-depth resolution of the reconstructed tomosynthesis section images reduces the necessity to take details of the anatomical structures at the location of the inserted nodule into account.

Investigation of image components affecting the detection of lung nodules in digital chest radiography

The aim of this work was to investigate and quantify the effects of system noise, nodule location, anatomical noise and anatomical background on the detection of lung nodules in different regions of the chest x-ray. Simulated lung nodules of diameter 10 mm but with varying detail contrast were randomly positioned in four different kinds of images: 1) clinical images collected with a 200 speed CR system, 2) images containing only system noise (including quantum noise) at the same level as the clinical images, 3) clinical images with removed anatomical noise, 4) artificial images with similar power spectrum as the clinical images but random phase spectrum. An ROC study was conducted with 5 observers. The detail contrast needed to obtain an Az of 0.80, C0.8, was used as measure of detectability. Five different regions of the chest x-ray were investigated separately. The C0.8 of the system noise images ranged from only 2% (the hilar regions) to 20% (the lateral pulmonary regions) of those of the clinical images. Compared with the original clinical images, the C0.8 was 16% lower for the de-noised clinical images and 71% higher for the random phase images, respectively, averaged over all five regions. In conclusion, regarding the detection of lung nodules with a diameter of 10 mm, the system noise is of minor importance at clinically relevant dose levels. The removal of anatomical noise and other noise sources uncorrelated from image to image leads to somewhat better detection, but the major component disturbing the detection is the overlapping of recognizable structures, which are, however, the main aspect of an x-ray image.

Investigation of the effect of varying scatter-to-primary ratios on nodule contrast in chest tomosynthesis

The primary aim of the present work was to analyze the effects of varying scatter-to-primary ratios on the appearance of simulated nodules in chest tomosynthesis section images. Monte Carlo simulations of the chest tomosynthesis system GE Definium 8000 VolumeRAD (GE Healthcare, Chalfont St. Giles, UK) were used to investigate the variation of scatter-to-primary ratios between different angular projections. The simulations were based on a voxel phantom created from CT images of an anthropomorphic chest phantom. An artificial nodule was inserted at 80 different positions in the simulated phantom images, using five different approaches for the scatter-to-primary ratios in the insertion process. One approach included individual determination of the scatter-to primary-ratio for each projection image and nodule location, while the other four approaches were using mean value, median value and zero degree projection value of the scatter-toprimary ratios at each nodule position as well as using a constant scatter-to-primary ratio of 0.5 for all nodule positions. The results indicate that the scatter-to-primary ratios vary up to a factor of 10 between the different angular tomosynthesis projections (±15°). However, the error in the resulting nodule contrast introduced by not taking all variations into account is in general smaller than 10 %.

Calculation of images from an anthropomorphic chest phantom using Monte Carlo methods

Monte Carlo (MC) computer simulation of chest x-ray imaging systems has hitherto been performed using anthropomorphic phantoms with too large (3 mm) voxel sizes. The aim for this work was to develop and use a Monte Carlo computer program to compute projection x-ray images of a high-resolution anthropomorphic voxel phantom for visual clinical image quality evaluation and dose-optimization. An Alderson anthropomorphic chest phantom was imaged in a CT-scanner and reconstructed with isotropic voxels of 0.7 mm. The phantom was segmented and included in a Monte Carlo computer program using the collision density estimator to derive the energies imparted to the detector per unit area of each pixel by scattered photons. The image due to primary photons was calculated analytically including a pre-calculated detector response function. Attenuation and scatter of x-rays in the phantom, grid and image detector was considered. Imaging conditions (tube voltage, anti-scatter device) were varied and the images compared to a real computed radiography (Fuji FCR 9501) image. Four imaging systems were simulated (two tube voltages 81 kV and 141 kV using either a grid with ratio 10 or a 30 cm air gap). The effect of scattered radiation on the visibility of thoracic vertebrae against the heart and lungs is demonstrated. The simplicity in changing the imaging conditions will allow us not only to produce images of existing imaging systems, but also of hypothetical, future imaging systems. We conclude that the calculated images of the high-resolution voxel phantom are suitable for human detection experiments of low-contrast lesions.