Can the average glandular dose in routine digital mammography screening be reduced? A pilot study using revised image quality criteria

Clinical image quality assessment and mean glandular dose for full field digital mammography

This study aims to assess the image quality (IQ) of 12 mammographic units and to identify units with potential optimisation needs. Data for 350 mammography examinations meeting inclusion criteria were collected retrospectively from April 2021 to April 2022. They were categorised based on the medical reports into 10 normal cases, 10 cases displaying calcifications and 10 cases presenting lesions. Two radiologists assessed the IQ of 1400 mammograms, evaluating system performance per Boitaet al's study and positioning performance following European guidelines. To measure agreement between the two radiologists, the Cohen's Kappa coefficient (κ) was computed, quantifying the excess of agreement beyond chance. The visual grading analysis score (VGAS) was computed to compare system and positioning performance assessments across different categories and facilities. Median average glandular dose (AGD) values for cranio caudal and medio lateral oblique views were calculated for each category and facility and compared to the national diagnostic reference levels. The health facilities were categorised by considering both IQ VGAS and AGD levels. Inter-rater agreement between radiologists ranged from poor (κ< 0.20) to moderate (0.41 <κ< 0.60), likely influenced by inherent biases and distinct IQ expectations. 50% of the facilities were classified as needing corrective actions for their system performance as they had IQ or high AGD that could increase recall rate and radiation risk and 50% of the health facilities exhibited insufficient positioning performance that could mask tumour masses and microcalcifications. The study's findings emphasise the importance of implementing quality assurance programs to ensure optimal IQ for accurate diagnoses while adhering to radiation exposure guidelines. Additionally, comprehensive training for technologists is essential to address positioning challenges. These initiatives collectively aim to enhance the overall quality of breast imaging services, contributing to improved patient care.

Radiation Dose Reduction in Digital Mammography by Deep-Learning Algorithm Image Reconstruction: A Preliminary Study

Purpose

To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer using low-dose mammography imaging.

Materials and Methods

A total of 6 breast radiologists were included in this prospective study. All radiologists independently evaluated low-dose images for lesion detection and rated them for diagnostic quality using a qualitative scale. After application of the denoising network, the same radiologists evaluated lesion detectability and image quality. For clinical application, a consensus on lesion type and localization on preoperative mammographic examinations of breast cancer patients was reached after discussion. Thereafter, coded low-dose, reconstructed full-dose, and full-dose images were presented and assessed in a random order.

Results

Lesions on 40% reconstructed full-dose images were better perceived when compared with low-dose images of mastectomy specimens as a reference. In clinical application, as compared to 40% reconstructed images, higher values were given on full-dose images for resolution (p < 0.001); diagnostic quality for calcifications (p < 0.001); and for masses, asymmetry, or architectural distortion (p = 0.037). The 40% reconstructed images showed comparable values to 100% full-dose images for overall quality (p = 0.547), lesion visibility (p = 0.120), and contrast (p = 0.083), without significant differences.

Conclusion

Effective denoising and image reconstruction processing techniques can enable breast cancer diagnosis with substantial radiation dose reduction.

Development and content validity evaluation of a candidate instrument to assess image quality in digital mammography: A mixed-method study

PURPOSE

To develop a candidate instrument to assess image quality in digital mammography, by identifying clinically relevant features in images that are affected by lower image quality.

METHODS

Interviews with fifteen expert breast radiologists from five countries were conducted and analysed by using adapted directed content analysis. During these interviews, 45 mammographic cases, containing 44 lesions (30 cancers, 14 benign findings), and 5 normal cases, were shown with varying image quality. The interviews were performed to identify the structures from breast tissue and lesions relevant for image interpretation, and to investigate how image quality affected the visibility of those structures. The interview findings were used to develop tentative items, which were evaluated in terms of wording, understandability, and ambiguity with expert breast radiologists. The relevance of the tentative items was evaluated using the content validity index (CVI) and modified kappa index (k*).

RESULTS

Twelve content areas, representing the content of image quality in digital mammography, emerged from the interviews and were converted into 29 tentative items. Fourteen of these items demonstrated excellent CVI ≥ 0.78 (k* > 0.74), one showed good CVI < 0.78 (0.60 ≤ k* ≤ 0.74), while fourteen were of fair or poor CVI < 0.78 (k* ≤ 0.59). In total, nine items were deleted and five were revised or combined resulting in 18 items.

CONCLUSIONS

By following a mixed-method methodology, a candidate instrument was developed that may be used to characterise the clinically-relevant impact that image quality variations can have on digital mammography.

A comparison of mean glandular dose diagnostic reference levels within the all-digital Irish National Breast Screening Programme and the Irish Symptomatic Breast Services

Data on image quality, compression and radiation dose were collected from symptomatic breast units within the Republic of Ireland. Quantitative and qualitative data were analysed using SPSS. Recommendations of mean glandular dose (MGD) diagnostic reference levels were made at various levels for film-screen and full field digital mammography units to match levels published worldwide. MGDs received by symptomatic breast patients within Ireland are higher than those received in the all-digital Irish Breast Screening service; 55-65 mm breast: 1.75 mGy (screening) vs. 2.4 mGy (symptomatic) at the 95th percentile; various reasons are proposed for the differences. MGDs achieved in the screening service may be lower because of the exacting requirements for radiographer training, characteristics of the patients and equipment quality assurance levels. More precise imaging guidelines, standards and training of symptomatic radiographers performing mammography are suggested to remediate MGDs delivered to the breasts of Irish women attending the symptomatic breast services.

Learning aspects and potential pitfalls regarding detection of pulmonary nodules in chest tomosynthesis and proposed related quality criteria

BACKGROUND

In chest tomosynthesis, low-dose projections collected over a limited angular range are used for reconstruction of an arbitrary number of section images of the chest, resulting in a moderately increased radiation dose compared to chest radiography.

PURPOSE

To investigate the effects of learning with feedback on the detection of pulmonary nodules for observers with varying experience of chest tomosynthesis, to identify pitfalls regarding detection of pulmonary nodules, and present suggestions for how to avoid them, and to adapt the European quality criteria for chest radiography and computed tomography (CT) to chest tomosynthesis.

MATERIAL AND METHODS

Six observers analyzed tomosynthesis cases for presence of nodules in a jackknife alternative free-response receiver-operating characteristics (JAFROC) study. CT was used as reference. The same tomosynthesis cases were analyzed before and after learning with feedback, which included a collective learning session. The difference in performance between the two readings was calculated using the JAFROC figure of merit as principal measure of detectability.

RESULTS

Significant improvement in performance after learning with feedback was found only for observers inexperienced in tomosynthesis. At the collective learning session, localization of pleural and subpleural nodules or structures was identified as the main difficulty in analyzing tomosynthesis images.

CONCLUSION

The results indicate that inexperienced observers can reach a high level of performance regarding nodule detection in tomosynthesis after learning with feedback and that the main problem with chest tomosynthesis is related to the limited depth resolution.

The effect of reduced breast compression in breast tomosynthesis: human observer study using clinical cases

The aim of this study was to investigate whether the compression force used with conventional mammography can be reduced with breast tomosynthesis (BT), without adversely affecting the visualisation of normal and pathological structures. Forty-five women were examined with BT using full (same as for 2D mammography) and half compression force. Both examinations were performed with the same acquisition parameters. A total of 103 paired structure images were evaluated according to specified image quality criteria. Three experienced radiologists participated in the study. They had to make a forced choice, i.e. choose the image they felt best fulfilled the image quality criteria. The results showed no evident difference in the image quality, indicating that BT may be performed with substantially less compression force compared with 2D mammography. A majority of the examined women felt that half compression was more comfortable than full compression.

Effect of dose reduction on the ability of digital mammography to detect simulated microcalcifications

The purpose of this article was to report the relationship between radiation dose and the ability of sentence digital mammography to detect microcalcifications. All images were acquired by computed radiography and an anthropomorphic breast phantom. The tube voltage and anode/filter combination used were 28 kVp and Mo/Mo. Simulated microcalcifications with an approximate diameter of 250-350 μm were positioned on the phantom. Groups of six microcalcifications were arranged in one of two patterns, a line cluster 1 cm long or a hexagonal cluster 4 mm wide. One of the six microcalcifications was removed to create a negative control. Each cluster was placed on 25 different points. Four levels of milliampere-second (mAs) values were applied: 100%, 50%, 25%, and 12.5%. Five staff radiologists participated in an observer performance test. All observers used a workstation with a 3-megapixel monochrome LCD monitor. The areas under the receiver-operating characteristics curves (AUC) were used to compare diagnostic performance among the four doses. The overall AUC scores were 0.97 with 100% mAs, 0.93 (n.s.) with 50%, 0.90 (p < 0.05) with 25%, and 0.81 (p < 0.01) with 12.5% mAs. Among the negative series, the percentage of images on which observers were able to identify the removed microcalcification point decreased from 88.8% with 100% mAs to 83.6% (n.s.) with 50%, 74.8% (p < 0.001) with 25%, and 67.2% (p < 0.001) with 12.5% mAs. A certain level of dose reduction in digital mammography may be an option.

Clinical image quality criteria for full field digital mammography: a first practical application

In order to quantify the clinical quality of full-field digital mammography, a set of image quality parameters is developed. The set consisted of 12 image quality criteria and 8 physical characteristics of the image. The first set interrogates the visibility of anatomical structures and typical characteristics of a digital image, such as noise and saturation of dark and white areas. The second set of criteria evaluates contrast, sharpness and confidence with the representation of masses, microcalcifications and the image. The use of these criteria is reported in a retrospective study, in which the impact of dose on the radiological quality of digital mammograms is evaluated. Fifty patients acquired in a low-dose mode were retrieved and compared with 50 patients acquired in a dose mode that was set 41% higher. The dose affects, more than expected, contrast and sharpness of the image, whereas the visibility of the anatomical structures remains unchanged. With these parameters, quantification of the image quality is possible; however, because of subjectivity of the parameters, only intra-observer comparison and evaluation of the individual parameters rather than the overall results are advised. Together with physical tests of image quality, critical radiological evaluation of the quality should be included in the acceptance process of digital mammography.

Semiautomatic mammographic parenchymal patterns classification using multiple statistical features

RATIONALE AND OBJECTIVES

Our project was to investigate a complete methodology for the semiautomatic assessment of digital mammograms according to their density, an indicator known to be correlated to breast cancer risk. The BI-RADS four-grade density scale is usually employed by radiologists for reporting breast density, but it allows for a certain degree of subjective input, and an objective qualification of density has therefore often been reported hard to assess. The goal of this study was to design an objective technique for determining breast BI-RADS density.

MATERIALS AND METHODS

The proposed semiautomatic method makes use of complementary pattern recognition techniques to describe manually selected regions of interest (ROIs) in the breast with 36 statistical features. Three different classifiers based on a linear discriminant analysis or Bayesian theories were designed and tested on a database consisting of 1408 ROIs from 88 patients, using a leave-one-ROI-out technique. Classifications in optimal feature subspaces with lower dimensionality and reduction to a two-class problem were studied as well.

RESULTS

Comparison with a reference established by the classifications of three radiologists shows excellent performance of the classifiers, even though extremely dense breasts continue to remain more difficult to classify accurately. For the two best classifiers, the exact agreement percentages are 76% and above, and weighted kappa values are 0.78 and 0.83. Furthermore, classification in lower dimensional spaces and two-class problems give excellent results.

CONCLUSION

The proposed semiautomatic classifiers method provides an objective and reproducible method for characterizing breast density, especially for the two-class case. It represents a simple and valuable tool that could be used in screening programs, training, education, or for optimizing image processing in diagnostic tasks.

Dose reduction and its influence on diagnostic accuracy and radiation risk in digital mammography: an observer performance study using an anthropomorphic breast phantom

This study aimed to investigate the effect of dose reduction on diagnostic accuracy and radiation risk in digital mammography. Simulated masses and microcalcifications were positioned in an anthropomorphic breast phantom. Thirty digital images, 14 with lesions, 16 without, were acquired of the phantom using a Mammomat Novation (Siemens, Erlangen, Germany) at each of three dose levels. These corresponded to 100%, 50% and 30% of the normally used average glandular dose (AGD; 1.3 mGy for a standard breast). Eight observers interpreted the 90 unprocessed images in a free response study, and the data were analysed with the jackknife free response receiver operating characteristic (JAFROC) method. Observer performance was assessed using the JAFROC figure of merit (FOM). The benefit of radiation risk reduction was estimated based on several risk models. There was no statistically significant difference in performance, as described by the FOM, between the 100% and the 50% dose levels. However, the FOMs for both the 100% and the 50% dose were significantly different from the corresponding quantity for the 30% dose level (F-statistic = 4.95, p-value = 0.01). A dose reduction of 50% would result in three to nine fewer breast cancer fatalities per 100,000 women undergoing annual screening from the age of 40 to 49 years. The results of the study indicate a possibility of reducing the dose to the breast to half the dose level currently used. This has to be confirmed in clinical studies, and possible differences depending on lesion type should be examined further.

Digital mammography: effects of reduced radiation dose on diagnostic performance

PURPOSE

To experimentally determine the relationship between radiation dose and observer accuracy in the detection and discrimination of simulated lesions for digital mammography.

MATERIALS AND METHODS

This HIPAA-compliant study received institutional review board approval; the informed consent requirement was waived. Three hundred normal craniocaudal images were selected from an existing database of digital mammograms. Simulated mammographic lesions that mimicked benign and malignant masses and clusters of microcalcifications (3.3-7.4 cm in diameter) were then superimposed on images. Images were rendered without and with added radiographic noise to simulate effects of reducing the radiation dose to one half and one quarter of the clinical dose. Images were read by five experienced breast imaging radiologists. Results were analyzed to determine effects of reduced dose on overall interpretation accuracy, detection of microcalcifications and masses, discrimination between benign and malignant masses, and interpretation time.

RESULTS

Overall accuracy decreased from 0.83 with full dose to 0.78 and 0.62 with half and quarter doses, respectively. The decrease associated with transition from full dose to quarter dose was significant (P < .01), primarily because of an effect on detection of microcalcifications (P < .01) and discrimination of masses (P < .05). The level of dose reduction did not significantly affect detection of malignant masses (P > .5). However, reduced dose resulted in an increased mean interpretation time per image by 28% (P < .0001).

CONCLUSION

These findings suggest that dose reduction in digital mammography has a measurable but modest effect on diagnostic accuracy. The small magnitude of the effect in response to the drastic reduction of dose suggests potential for modest dose reductions in digital mammography.

Visual grading characteristics (VGC) analysis: a non-parametric rank-invariant statistical method for image quality evaluation

Visual grading of the reproduction of important anatomical structures is often used to determine clinical image quality in radiography. However, many visual grading methods incorrectly use statistical methods that require data belonging to an interval scale. The rating data from the observers in a visual grading study with multiple ratings is ordinal, meaning that non-parametric rank-invariant statistical methods are required. This paper describes such a method for determining the difference in image quality between two modalities called visual grading characteristics (VGC) analysis. In a VGC study, the task of the observer is to rate his confidence about the fulfilment of image quality criteria. The rating data for the two modalities are then analysed in a manner similar to that used in receiver operating characteristics (ROC) analysis. The resulting measure of image quality is the VGC curve, which--for all possible thresholds of the observer for a fulfilled criterion--describes the relationship between the proportions of fulfilled image criteria for the two compared modalities. The area under the VGC curve is proposed as a single measure of the difference in image quality between two compared modalities. It is also described how VGC analysis can be applied to data from an absolute visual grading analysis study.

Clinical evaluation of a new set of image quality criteria for mammography

The European Commission (EC) quality criteria for screen-film mammography are used as a tool to assess image quality. A new set of criteria was developed and initially tested in a previous study. In the present study, these criteria are further evaluated using screen-film mammograms that have been digitised, manipulated to simulate different image quality levels and reprinted on film. Expert radiologists have evaluated these manipulated images using both the original (EC) and the new criteria. A comparison of three different simulated dose levels reveals that the new criteria yield a larger separation of image criteria scores than the old ones. These results indicate that the new set of image quality criteria has a higher discriminative power than the old set and thus seems to be more suitable for evaluation of image quality in mammography.

A software tool for increased efficiency in observer performance studies in radiology

Observer performance studies are time-consuming tasks, both for the participating observers and for the scientists collecting and analysing the data. A possible way to optimise such studies is to perform them in a completely digital environment. A software tool-ViewDEX (Viewer for Digital Evaluation of X-ray images)-has been developed in Java, enabling it to function on almost any computer. ViewDEX is designed to handle several types of studies, such as visual grading analysis (VGA), image criteria scoring (ICS) and receiver operating characteristics (ROC). The results from each observer are saved in a log file, which can be exported for further analysis in, for example, a special software for analysing ROC results. By using ViewDEX for an ROC experiment, an evaluation rate of approximately 200 images per hour can be achieved, compared to approximately 25 images per hour using hard copy evaluation. The results are obtained within minutes of completion of the viewing. The risk of human errors in the process of data collection and analysis is also minimised. The viewer has been used in a major trial containing approximately 2700 images.

Inter-observer variation in masked and unmasked images for quality evaluation of clinical radiographs

PURPOSE

To investigate the influence of masking on the inter-observer variation in image quality evaluation of clinical radiographs of chest and lumbar spine.

BACKGROUND

Inter-observer variation is a big problem in image quality evaluation since this variation is often much bigger than the variation in image quality between, for example, two radiographic systems. In this study, we have evaluated the effect of masking on the inter-observer variation. The idea of the masking was to force every observer to view exactly the same part of the image and to avoid the effect of the overall 'first impression' of the image. A discussion with a group of European expert radiologists before the study indicated that masking might be a good way to reduce the inter-observer variation.

METHODS

Five chest and five lumbar spine radiographs were collected together with detailed information regarding exposure conditions. The radiographs were digitised with a high-performance scanner and five different manipulations were performed, simulating five different exposure conditions. The contrast, noise and spatial resolution were manipulated by this method. The images were printed onto the film and the individual masks were produced for each film, showing only the parts of the images that were necessary for the image quality evaluation. The quality of the images was evaluated on ordinary viewing boxes by a large group of experienced radiologists. The images were examined with and without the masks with a set of image criteria (if fulfilled, 1 point; and not fulfilled, 0 point), and the mean score was calculated for each simulated exposure condition.

RESULTS

The results of this study indicate that-contrary to what was supposed-the inter-observer variation increased when the images were masked. In some cases, especially for chest, this increase was statistically significant.

CONCLUSIONS

Based on the results of this study, image masking in studies of fulfilment of image criteria cannot be recommended.