Clinical Image Quality Evaluation Research Articles

Correlation Between Contrast-Detail Analysis and Clinical Image Quality Assessment of Intrapulmonary Lesions in Dual-Energy Subtraction Chest Radiography Using the Two-Shot Method: A Phantom Study

Dual-energy subtraction (DES) imaging constitutes a technique that has demonstrated efficacy in enhancing the detectability of pulmonary nodules on chest radiographs. However, a simple and quantitative methodology for evaluating the clinical image quality of DES images is currently lacking. The objective of this study was to investigate the applicability of contrast-detail (C-D) phantom analysis to the visual clinical image quality evaluation of chest DES images. We employed a custom-made phantom incorporating the C-D phantom and a multipurpose anthropomorphic adult chest phantom. Two phantom sizes were utilized to simulate standard- and large-bodied adult patients for each phantom. The custom-made phantom images were scored automatically using dedicated software, yielding an inverse image quality figure (IQFinv) value. The multipurpose anthropomorphic adult chest phantom was employed in a visual grading analysis (VGA) study that was conducted by two experienced radiologists and five radiological technologists. Each nodule placed in the chest phantom image was rated on a 4-point Likert scale. A statistically significant correlation was observed between the VGA scores of the seven observers and the obtained IQFinv values. The findings of this study suggest that DES image analysis of the C-D phantom possesses the potential to be utilized for the evaluation of clinical DES image quality based on chest lesion detectability.

Correlation between physical measurements and observer evaluations of image quality in digital chest radiography.

The aim of this paper was to investigate the relationship between the physical and subjective (observer) image quality metrics in digital chest radiography. Five digital radiography systems, four with indirect flat panel detector and one with storage phosphor-based computed radiography system, were used in the study. The physical image quality assessments were carried out using effective detective quantum efficiency (eDQE) metric and subjective performance of the digital radiography systems was evaluated in terms of inverse image quality figure (IQFinv ) derived from the contrast-detail (CD) diagrams using CDRAD 2.0 phantom and CDRAD phantom analyzer software. All measurements were performed for different tube voltages (70, 81, 90, 102, 110, and 125kVp) and polymethyl methacrylate (PMMA) phantom thicknesses. An anthropomorphic chest phantom and visual grading analysis (VGA) technique based on European image quality criteria for chest radiography were used for clinical image quality evaluation. The Spearman correlation coefficients were calculated for the investigation of the correlation between physical image quality and clinical image quality. The results showed strong positive correlation between the physical and clinical image quality findings. The minimum correlation coefficient was 0.91 (p<0.011) for IQFinv vs VGA scores and 0.92 (p<0.009) for IeDQE vs VGA scores. Our results confirm that clinical image quality can be predicted with both physical assessments and contrast-detail detectability studies.

Image quality assessment of pre-processed and post-processed digital panoramic radiographs in paediatric patients with mixed dentition.

PurposeTo determine the impact of an image processing technique on diagnostic accuracy of digital panoramic radiographs for the assessment of anatomical structures in paediatric patients with mixed dentition.Materials and MethodsThe study consisted of 50 digital panoramic radiographs of children aged from 6 to 12 years, which were later on processed using a dedicated image processing method. A modified clinical image quality evaluation chart was used to evaluate the diagnostic accuracy of anatomical structures in maxillary and mandibular anterior and maxillary premolar region of processed images.ResultsA statistically significant difference was observed between pre and post-processed evaluation of anatomical structures (P<0.05) in the maxillary and mandibular anterior region. The anterior region was found to be more accurate in post-processed images. No significant difference was observed in the maxillary premolar region (P>0.05). The Inter-observer and intra-observer reliability of both pre and post processed images were excellent (>0.82) for anterior region and good (>0.63) for premolar region.ConclusionThe application of image processing technique in digital panoramic radiography can be considered a reliable method for improving the quality of anatomical structures in paediatric patients with mixed dentition.

Evaluation of automatic image quality assessment in chest CT – A human cadaver study

PurposeThe evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers. MethodsChest CT’s of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized. ResultsGood correlations were found between IQs and the measured physical-technical image quality: noise (ρ=−1.00), contrast-to-noise (ρ=1.00) and contrast-detail (ρ=0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively. ConclusionsThe automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs.

Series: Practical Evaluation of Clinical Image Quality (4): Determination of Image Quality in Digital Radiography System.

Recently, for medical imaging, digital radiography systems are widely used in clinical practices. However, a study in the past reported that a patient radiation exposure level by digital radiography is in fact not lower than that by analog radiography system. High level of attention needs to be paid for over-exposure when using the conventional analog radiography with a screen and a film, as it results in high density of the film. However, for digital radiography systems, since the automatic adjusting function of image density is equipped with them, no attention for radiation dose need to be paid. Thus technologists tend to be careless and results in higher chance for over-exposure. Current digital radiography systems are high-performance in the image properties and capable of patient dose reduction. Especially, the image quality of the flat panel detector system is recognized, higher than that of the computed radiography system by imaging plates, in both objective and subjective evaluations. Therefore, we technologists are responsible for optimizing the balance between the image quality of the digital radiogram and the radiation dose required for each case. Moreover, it is also required for us as medical technologists to make effective use of such evaluation result of medical images for patients.

Performance evaluation of a retrofit digital detector-based mammography system

A retrofit flat panel detector was integrated with a GE DMR+ analog mammography system and characterized using detective quantum efficiency (DQE). Technical system performance was evaluated using the European Guidelines protocol, followed by a limited evaluation of clinical image quality for 20 cases using image quality criteria in the European Guidelines. Optimal anode/filter selections were established using signal difference-to-noise ratio measurements. Only small differences in peak DQE were seen between the three anode/filter settings, with an average value of 0.53. For poly(methyl methacrylate) (PMMA) thicknesses above 60 mm, the Rh/Rh setting was the optimal anode/filter setting. The system required a mean glandular dose of 0.54 mGy at 30 kV Rh/Rh to reach the Acceptable gold thickness limit for 0.1 mm details. Imaging performance of the retrofit unit with the GE DMR+ is notably better than of powder based computed radiography systems and is comparable to current flat panel FFDM systems.

Series: Practical Evaluation of Clinical Image Quality (2): Image Quality Measurements for Digital Radiography Systems.

In recent years, the manuals and data analysis tools to evaluate the basic imaging properties of medical imaging systems, such as digital radiography system, CT, and MRI, are easily available. For the image quality evaluation of digital radiography systems, special measurement system, such as a microdensitometer, required for the analysis of analog radiography system, is not needed. This enabled anyone to perform the evaluation of digital radiography system.On the other hand, to make accurate measurements, obtaining appropriate image data is a must. To enable this, appropriate setting of the hardware and the software is also required. In addition, we are asked to acquire sufficient knowledge to make highly reproducible measurements.

Series: Practical Evaluation of Clinical Image Quality (3): Subjective Evaluation of Image Quality in Digital Radiography Systems.

In the environment of picture archiving and communication system (PACS), the subjective evaluation of medical image quality is performed using an image display monitor. Commonly, PACS and its image viewer can handle digital imaging and communications in medicine (DICOM) format image files that are displayed as 8-bit grayscale images in the monitor. However, the original grayscale of DICOM image is between 10-bit to 16-bit depth. Therefore, in order for DICOM images to be displayed in the monitor by PACS image viewer, they need to be converted into 8-bit depth grayscale. This conversion indicates that the original characteristics of DICOM images are altered when they are displayed in the monitor by PACS image viewer. Moreover, image data interpolation to match the image matrix for the resolution of the monitor also alters the characteristics of images. For these reasons, it is a must to recognize the influential factors of image display settings for the subjective evaluation of medical image quality.

Contrast reference values in panoramic radiographic images using an arch-form phantom stand

PurposeThe purpose of this study was to investigate appropriate contrast reference values (CRVs) by comparing the contrast in phantom and clinical images.Materials and MethodsPhantom contrast was measured using two methods: (1) counting the number of visible pits of different depths in an aluminum plate, and (2) obtaining the contrast-to-noise ratio (CNR) for 5 tissue-equivalent materials (porcelain, aluminum, polytetrafluoroethylene [PTFE], polyoxymethylene [POM], and polymethylmethacrylate [PMMA]). Four panoramic radiographs of the contrast phantom, embedded in the 4 different regions of the arch-form stand, and 1 real skull phantom image were obtained, post-processed, and compared. The clinical image quality evaluation chart was used to obtain the cut-off values of the phantom CRV corresponding to the criterion of being adequate for diagnosis.ResultsThe CRVs were obtained using 4 aluminum pits in the incisor and premolar region, 5 aluminum pits in the molar region, and 2 aluminum pits in the temporomandibular joint (TMJ) region. The CRVs obtained based on the CNR measured in the anterior region were: porcelain, 13.95; aluminum, 9.68; PTFE, 6.71; and POM, 1.79. The corresponding values in the premolar region were: porcelain, 14.22; aluminum, 8.82; PTFE, 5.95; and POM, 2.30. In the molar region, the following values were obtained: porcelain, 7.40; aluminum, 3.68; PTFE, 1.27; and POM, - 0.18. The CRVs for the TMJ region were: porcelain, 3.60; aluminum, 2.04; PTFE, 0.48; and POM, - 0.43.ConclusionCRVs were determined for each part of the jaw using the CNR value and the number of pits observed in phantom images.

Metal artifact reduction and image quality evaluation of lumbar spine CT images using metal sinogram segmentation.

Metal artifacts often appear in the images of computed tomography (CT) imaging. In the case of lumbar spine CT images, artifacts disturb the images of critical organs. These artifacts can affect the diagnosis, treatment, and follow up care of the patient. One approach to metal artifact reduction is the sinogram completion method. A mixed-variable thresholding (MixVT) technique to identify the suitable metal sinogram is proposed. This technique consists of four steps: 1) identify the metal objects in the image by using k-mean clustering with the soft cluster assignment, 2) transform the image by separating it into two sinograms, one of which is the sinogram of the metal object, with the surrounding tissue shown in the second sinogram. The boundary of the metal sinogram is then found by the MixVT technique, 3) estimate the new value of the missing data in the metal sinogram by linear interpolation from the surrounding tissue sinogram, 4) reconstruct a modified sinogram by using filtered back-projection and complete the image by adding back the image of the metal object into the reconstructed image to form the complete image. The quantitative and clinical image quality evaluation of our proposed technique demonstrated a significant improvement in image clarity and detail, which enhances the effectiveness of diagnosis and treatment.

Post-processing, is it a burden or a blessing? Part 1 evaluation of clinical image quality

BackgroundThe dynamic range of modern detectors tolerates a higher detector dose or Detector Air Kerma (DAK) without negative effect on image quality. Necessary image quality is closely related to the clinical question: in order to keep the patient dose as low as possible, image quality criteria are needed for each type of radiography. The purpose of this study was to investigate the relation between image quality, described as an overall judgement versus the visibility of well-defined structures, and DAK in clinically accepted radiographs. Methods and materials168 AP radiographs of the knee and 152 radiographs of the pelvis were collected randomly in 19 radiologic centres. Six radiologists with at least five-years experience scored the overall image quality and the visibility of seven different anatomic structures, in a controlled environment on a five-point scale, using a Visual Grading Analysis (VGA). The relation between the DAK and the VGA Score (VGAS) was evaluated. ResultsThe VGAS was 3.92 for the knee and 3.71 for the pelvis. The VGAS for CR and DR were significantly different (p < 0.01). Intra-observer variability was not significant and inter-observer correlations were high and significant. Only for the pelvis radiographs produced with computed radiography, a rather weak but significant correlation was found between DAK and VGAS. ConclusionThe VGA revealed an image quality higher than diagnostically necessary in both datasets, and high inter-observer correlation. Based on the DAK-range, it could be hypothesized that below a certain noise level no further visible improvement of the image quality was reached.

Clinical image quality evaluation for panoramic radiography in Korean dental clinics

PurposeThe purpose of this study was to investigate the level of clinical image quality of panoramic radiographs and to analyze the parameters that influence the overall image quality.Materials and MethodsKorean dental clinics were asked to provide three randomly selected panoramic radiographs. An oral and maxillofacial radiology specialist evaluated those images using our self-developed Clinical Image Quality Evaluation Chart. Three evaluators classified the overall image quality of the panoramic radiographs and evaluated the causes of imaging errors.ResultsA total of 297 panoramic radiographs were collected from 99 dental hospitals and clinics. The mean of the scores according to the Clinical Image Quality Evaluation Chart was 79.9. In the classification of the overall image quality, 17 images were deemed 'optimal for obtaining diagnostic information,' 153 were 'adequate for diagnosis,' 109 were 'poor but diagnosable,' and nine were 'unrecognizable and too poor for diagnosis'. The results of the analysis of the causes of the errors in all the images are as follows: 139 errors in the positioning, 135 in the processing, 50 from the radiographic unit, and 13 due to anatomic abnormality.ConclusionPanoramic radiographs taken at local dental clinics generally have a normal or higher-level image quality. Principal factors affecting image quality were positioning of the patient and image density, sharpness, and contrast. Therefore, when images are taken, the patient position should be adjusted with great care. Also, standardizing objective criteria of image density, sharpness, and contrast is required to evaluate image quality effectively.

A review of methods of clinical image quality evaluation in mammography

Purpose Consistency in evaluation of mammography images in research and clinical practice is dependent on a standardised clinical image quality evaluation system. Currently two such systems are available—one developed by the American College of Radiology (ACR) and the other by the European Commission (EU guidelines). The purpose of this study was to review mammography clinical evaluation methods in research studies and their adherence to these systems . Method A total of 23 research articles were reviewed from the period 2000–2006, 11 of these studies used digital images. The focus of the review was the criteria and rating scales used. Results Only 5 studies used either the ACR (3) or EU guidelines (2). The remainder included aspects of these systems together with a range of other criteria and rating scales. Variation was found in the categories of criteria used, number of criteria, the descriptors of the criteria and the instructions used to evaluate the criteria. Instructions were frequently not specific and open to individual interpretation. Although breast density is an important criterion of image quality and contributes to perception of breast lesions, inclusion of this criterion was not universal, and even when used the area of breast density to be evaluated was not identified, thus enhancing inter-observer variability. Scales that were absolute or relative were used for evaluation, all of which incorporated inconsistent numbers of steps. Conclusion Low adherence to ACR and EU Guidelines has resulted in considerable variation in the evaluation methods used in research studies. The implications of this variability are considerable both for evaluation of image quality in research outcomes and clinical practice.