Detection of simulated nodules on clinical radiographs: dose reduction at digital posteroanterior chest radiography

Radiation dose reduction and improvement of image quality in digital chest radiography by new spatial noise reduction algorithm

Purpose

To evaluate the image quality of low-dose chest digital radiographic images obtained with a new spatial noise reduction algorithm, compared to a conventional de-noising technique.

Materials and methods

In 69 patients, the dose reduction protocol was divided into A, B, and C test groups– 60% (n = 22), 50% (n = 23), and 40% (n = 24) of the baseline dose. In each patient, baseline dose radiographs were obtained with conventional image processing while low-dose images were acquired with new image processing. A set of baseline and low-dose radiographic images per patient was evaluated and scored on a 5-point scale over seven anatomical landmarks (radiolucency of unobscured lung, pulmonary vascularity, trachea, edge of rib, heart border, intervertebral disc space, and pulmonary vessels in the retrocardiac area) and three representative abnormal findings (nodule, consolidation, and interstitial marking) by two thoracic radiologists. A comparison of paired baseline and low-dose images was statistically analyzed using a non-inferiority test based on the paired t-test or the Wilcoxon signed-rank test.

Results

In A, B, and C test groups, the mean dose reduction rate of the baseline radiation dose was 63.4%, 53.9%, and 47.8%, respectively. In all test groups, the upper limit of the 95% confidence interval was less than the non-inferiority margin of 0.5 every seven anatomical landmarks and three representative abnormal findings, which suggested that the image quality of the low-dose image was not inferior to that of the baseline dose image even if the maximum average dose reduction rate was reduced to 47.8% of the baseline dose.

Conclusion

In our study, an image processing technique integrating a new noise reduction algorithm achieved dose reductions of approximately half without compromising image quality for abnormal lung findings and anatomical landmarks seen on chest radiographs. This feature-preserving, noise reduction algorithm adopted in the proposed engine enables a lower radiation dose boundary for the sake of patient’s and radiography technologist’s radiation safety in routine clinical practice, in compliance with regulatory guidelines.

Method for simulating dose reduction in digital mammography using the Anscombe transformation

PURPOSE

This work proposes an accurate method for simulating dose reduction in digital mammography starting from a clinical image acquired with a standard dose.

METHODS

The method developed in this work consists of scaling a mammogram acquired at the standard radiation dose and adding signal-dependent noise. The algorithm accounts for specific issues relevant in digital mammography images, such as anisotropic noise, spatial variations in pixel gain, and the effect of dose reduction on the detective quantum efficiency. The scaling process takes into account the linearity of the system and the offset of the detector elements. The inserted noise is obtained by acquiring images of a flat-field phantom at the standard radiation dose and at the simulated dose. Using the Anscombe transformation, a relationship is created between the calculated noise mask and the scaled image, resulting in a clinical mammogram with the same noise and gray level characteristics as an image acquired at the lower-radiation dose.

RESULTS

The performance of the proposed algorithm was validated using real images acquired with an anthropomorphic breast phantom at four different doses, with five exposures for each dose and 256 nonoverlapping ROIs extracted from each image and with uniform images. The authors simulated lower-dose images and compared these with the real images. The authors evaluated the similarity between the normalized noise power spectrum (NNPS) and power spectrum (PS) of simulated images and real images acquired with the same dose. The maximum relative error was less than 2.5% for every ROI. The added noise was also evaluated by measuring the local variance in the real and simulated images. The relative average error for the local variance was smaller than 1%.

CONCLUSIONS

A new method is proposed for simulating dose reduction in clinical mammograms. In this method, the dependency between image noise and image signal is addressed using a novel application of the Anscombe transformation. NNPS, PS, and local noise metrics confirm that this method is capable of precisely simulating various dose reductions.

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.

Simulation of dose reduction in tomosynthesis

PURPOSE

Methods for simulating dose reduction are valuable tools in the work of optimizing radiographic examinations. Using such methods, clinical images can be simulated to have been collected at other, lower, dose levels without the need of additional patient exposure. A recent technology introduced to healthcare that needs optimization is tomosynthesis, where a number of low-dose projection images collected at different angles is used to reconstruct section images of an imaged object. The aim of the present work was to develop a method of simulating dose reduction for digital radiographic systems, suitable for tomosynthesis.

METHODS

The developed method uses information about the noise power spectrum (NPS) at the original dose level and the simulated dose level to create a noise image that is added to the original image to produce an image that has the same noise properties as an image actually collected at the simulated dose level. As the detective quantum efficiency (DQE) of digital detectors operating at the low dose levels used for tomosynthesis may show a strong dependency on the dose level, it is important that a method for simulating dose reduction for tomosynthesis takes this dependency into account. By applying an experimentally determined relationship between pixel mean and pixel variance, variations in both dose and DQE in relevant dose ranges are taken into account.

RESULTS

The developed method was tested on a chest tomosynthesis system and was shown to produce NPS of simulated dose-reduced projection images that agreed well with the NPS of images actually collected at the simulated dose level. The simulated dose reduction method was also applied to tomosynthesis examinations of an anthropomorphic chest phantom, and the obtained noise in the reconstructed section images was very similar to that of an examination actually performed at the simulated dose level.

CONCLUSIONS

In conclusion, the present article describes a method for simulating dose reduction suitable for tomosynthesis. However, the method applies equally well to any digital radiographic system, although the benefits of correcting for DQE variations may be smaller.

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.

Dose and perceived image quality in chest radiography

Chest radiography is the most commonly performed diagnostic X-ray examination. The radiation dose to the patient for this examination is relatively low but because of its frequent use, the contribution to the collective dose is considerable. Consequently, optimization of dose and image quality offers a challenging area of research. In this article studies on dose reduction, different detector technologies, optimization of image acquisition and new technical developments in image acquisition and post processing will be reviewed. Studies indicate that dose reduction in PA chest images to at least 50% of commonly applied dose levels does not affect diagnosis in the lung fields; however, dose reduction in the mediastinum, upper abdomen and retrocardiac areas appears to directly deteriorate diagnosis. In addition to patient dose, also the design of the various digital detectors seems to have an effect on image quality. With respect to image acquisition, studies showed that using a lower tube voltage improves visibility of anatomical structures and lesions in digital chest radiographs but also increases the disturbing appearance of ribs. New techniques that are currently being evaluated are dual energy, tomosynthesis, temporal subtraction and rib suppression. These technologies may improve diagnostic chest X-ray further. They may for example reduce the negative influence of over projection of ribs, referred to as anatomic noise. In chest X-ray this type of noise may be the dominating factor in the detection of nodules. In conclusion, optimization and new developments will enlarge the value of chest X-ray as a mainstay in the diagnosis of chest diseases.

Effect of bit depth and kVp of digital radiography for detection of subtle differences

OBJECTIVES

The purpose of this study is to investigate the effects of different bit depths and kilovoltage peak (kVp) values used in intraoral digital radiography on observer performance in detecting subtle radiographic density differences.

STUDY DESIGN

Using an intraoral CCD sensor set at 8- or 12-bit depth, kVp set at 60 or 70, and 14 different exposure times, digital radiographs were acquired of a specially designed aluminum step-wedge phantom with small holes of different depths in each step. Ten observers examined all images.

RESULTS

The observers counted more holes with the 12-bit images compared with the 8-bit images, particularly at 60 kVp. Significantly more holes were also counted with images taken at 70 kVp compared with those taken at 60 kVp.

CONCLUSION

Regarding the detection of subtle radiographic density differences, 12-bit images and 70 kVp were superior to 8-bit images and 60 kVp.

Digital chest radiography: an update on modern technology, dose containment and control of image quality

The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems.