Comparison of Diagnostic Accuracy of Radiation Dose-Equivalent Radiography, Multidetector Computed Tomography and Cone Beam Computed Tomography for Fractures of Adult Cadaveric Wrists

PURPOSE

To compare the diagnostic accuracy of radiography, to radiography equivalent dose multidetector computed tomography (RED-MDCT) and to radiography equivalent dose cone beam computed tomography (RED-CBCT) for wrist fractures.

METHODS

As study subjects we obtained 10 cadaveric human hands from body donors. Distal radius, distal ulna and carpal bones (n = 100) were artificially fractured in random order in a controlled experimental setting. We performed radiation dose equivalent radiography (settings as in standard clinical care), RED-MDCT in a 320 row MDCT with single shot mode and RED-CBCT in a device dedicated to musculoskeletal imaging. Three raters independently evaluated the resulting images for fractures and the level of confidence for each finding. Gold standard was evaluated by consensus reading of a high-dose MDCT.

RESULTS

Pooled sensitivity was higher in RED-MDCT with 0.89 and RED-MDCT with 0.81 compared to radiography with 0.54 (P = < .004). No significant differences were detected concerning the modalities' specificities (with values between P = .98). Raters' confidence was higher in RED-MDCT and RED-CBCT compared to radiography (P < .001).

CONCLUSION

The diagnostic accuracy of RED-MDCT and RED-CBCT for wrist fractures proved to be similar and in some parts even higher compared to radiography. Readers are more confident in their reporting with the cross sectional modalities. Dose equivalent cross sectional computed tomography of the wrist could replace plain radiography for fracture diagnosis in the long run.

IVEU: IT-based collection and reporting of radiological examination parameters

In Germany, each site using ionising radiation in human medicine is assigned to a competent medical authority (CMA) for quality assurance. Duties of these CMAs are, e.g. the inspection of medical aspects of the use of X-rays and nuclear medicine at the sites as well as technical quality assurance of X-ray devices. The CMAs themselves have to report the collected exposure values to the ministries and the Federal Office for Radiation Protection. The IVEU (IT-gestütztes Verfahren zur Erfassung von Untersuchungsparametern) Software Framework assists CMAs and radiological departments in collecting and analysing data provided in DICOM headers.

Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system

The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and x-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.

Reduction of metal artifact in single photon-counting computed tomography by spectral-driven iterative reconstruction technique

Purpose

The exciting prospect of Spectral CT (SCT) using photon-counting detectors (PCD) will lead to new techniques in computed tomography (CT) that take advantage of the additional spectral information provided. We introduce a method to reduce metal artifact in X-ray tomography by incorporating knowledge obtained from SCT into a statistical iterative reconstruction scheme. We call our method Spectral-driven Iterative Reconstruction (SPIR).

Method

The proposed algorithm consists of two main components: material decomposition and penalized maximum likelihood iterative reconstruction. In this study, the spectral data acquisitions with an energy-resolving PCD were simulated using a Monte-Carlo simulator based on EGSnrc C++ class library. A jaw phantom with a dental implant made of gold was used as an object in this study. A total of three dental implant shapes were simulated separately to test the influence of prior knowledge on the overall performance of the algorithm. The generated projection data was first decomposed into three basis functions: photoelectric absorption, Compton scattering and attenuation of gold. A pseudo-monochromatic sinogram was calculated and used as input in the reconstruction, while the spatial information of the gold implant was used as a prior. The results from the algorithm were assessed and benchmarked with state-of-the-art reconstruction methods.

Results

Decomposition results illustrate that gold implant of any shape can be distinguished from other components of the phantom. Additionally, the result from the penalized maximum likelihood iterative reconstruction shows that artifacts are significantly reduced in SPIR reconstructed slices in comparison to other known techniques, while at the same time details around the implant are preserved. Quantitatively, the SPIR algorithm best reflects the true attenuation value in comparison to other algorithms.

Conclusion

It is demonstrated that the combination of the additional information from Spectral CT and statistical reconstruction can significantly improve image quality, especially streaking artifacts caused by the presence of materials with high atomic numbers.

Categorization of two-photon microscopy images of human cartilage into states of osteoarthritis

OBJECTIVE

The degeneration of articular cartilage is part of the clinical syndrome of osteoarthritis (OA) and one of the most common causes of pain and disability in middle-aged and older people(1). However, the objective detection of an initial state of OA is still challenging. In order to categorize cartilage into states of OA, an algorithm is presented which offers objective categorization on the basis of two-photon laser-scanning microscopy (TPLSM) images.

METHODS

The algorithm is based on morphological characteristics of the images and results in a topographical visualization. This paper describes the algorithm and shows the result of a categorization of human cartilage samples.

RESULTS

The resulting map of the analysis of TPLSM images can be divided into areas which correspond to the grades of the Outerbridge-Categorization. The algorithm is able to differentiate the samples in coincidence with the macroscopic impression.

CONCLUSION

The method is promising for early OA detection and categorization. In order to achieve a higher benefit for the physician the method must be transferred to an endoscopic setup for an application in surgery.