Padraig T. Looney

The relationship between cancer detection in mammography and image quality measurements

PURPOSE To investigate the relationship between image quality measurements and the clinical performance of digital mammographic systems. METHODS Mammograms containing subtle malignant non-calcification lesions and simulated malignant calcification clusters were adapted to appear as if acquired by four types of detector. Observers searched for suspicious lesions and gave these a malignancy score. Analysis was undertaken using jackknife alternative free-response receiver operating characteristics weighted figure of merit (FoM). Images of a CDMAM contrast-detail phantom were adapted to appear as if acquired using the same four detectors as the clinical images. The resultant threshold gold thicknesses were compared to the FoMs using a linear regression model and an F-test was used to find if the gradient of the relationship was significantly non-zero. RESULTS The detectors with the best image quality measurement also had the highest FoM values. The gradient of the inverse relationship between FoMs and threshold gold thickness for the 0.25mm diameter disk was significantly different from zero for calcification clusters (p=0.027), but not for non-calcification lesions (p=0.11). Systems performing just above the minimum image quality level set in the European Guidelines for Quality Assurance in Breast Cancer Screening and Diagnosis resulted in reduced cancer detection rates compared to systems performing at the achievable level. CONCLUSIONS The clinical effectiveness of mammography for the task of detecting calcification clusters was found to be linked to image quality assessment using the CDMAM phantom. The European Guidelines should be reviewed as the current minimum image quality standards may be too low.

MedXViewer: an extensible web-enabled software package for medical imaging

MedXViewer (Medical eXtensible Viewer) is an application designed to allow workstation-independent, PACS-less viewing and interaction with anonymised medical images (e.g. observer studies). The application was initially implemented for use in digital mammography and tomosynthesis but the flexible software design allows it to be easily extended to other imaging modalities. Regions of interest can be identified by a user and any associated information about a mark, an image or a study can be added. The questions and settings can be easily configured depending on the need of the research allowing both ROC and FROC studies to be performed. The extensible nature of the design allows for other functionality and hanging protocols to be available for each study. Panning, windowing, zooming and moving through slices are all available while modality-specific features can be easily enabled e.g. quadrant zooming in mammographic studies. MedXViewer can integrate with a web-based image database allowing results and images to be stored centrally. The software and images can be downloaded remotely from this centralised data-store. Alternatively, the software can run without a network connection where the images and results can be encrypted and stored locally on a machine or external drive. Due to the advanced workstation-style functionality, the simple deployment on heterogeneous systems over the internet without a requirement for administrative access and the ability to utilise a centralised database, MedXViewer has been used for running remote paper-less observer studies and is capable of providing a training infrastructure and co-ordinating remote collaborative viewing sessions (e.g. cancer reviews, interesting cases).

Using image simulation to test the effect of detector type on breast cancer detection

Introduction: The effect that the image quality associated with different image receptors has on cancer detection in mammography was measured using a novel method for changing the appearance of images. Method: A set of 270 mammography cases (one view, both breasts) was acquired using five Hologic Selenia and two Hologic Dimensions X-ray sets: 160 normal cases, 80 cases with subtle real non-calcification malignant lesions and 30 cases with biopsy proven benign lesions. Simulated calcification clusters were inserted into half of the normal cases. The 270 cases (Arm 1) were converted to appear as if they had been acquired on three other imaging systems: caesium iodide detector (Arm 2), needle image plate computed radiography (CR) (Arm 3) and powder phosphor CR (Arm 4). Five experienced mammography readers marked the location of suspected cancers in the images and classified the degree of visibility of the lesions. Statistical analysis was performed using JAFROC. Results: The differences in the visibility of calcification clusters between all pairs of arms were statistically significant (p<0.05), except between Arms 1 and 2. The difference in the visibility of non-calcification lesions was smaller than for calcification clusters, but the differences were still significant except between Arms 1 and 2 and between Arms 3 and 4. Conclusion: Detector type had a significant impact on the visibility of all types of subtle cancers, with the largest impact being on the visibility of calcification clusters.

Automatic 3D ultrasound segmentation of the first trimester placenta using deep learning

Placental volume measured with 3D ultrasound in the first trimester has been shown to be correlated to adverse pregnancy outcomes. This could potentially be used as a screening test to predict the “at risk” pregnancy. However, manual segmentation whilst previously shown to be accurate and repeatable is very time consuming and semi-automated methods still require operator input. To generate a screening tool, fully automated placental segmentation is required. In this work, a deep convolutional neural network (cNN), DeepMedic, was trained using the output of the semi-automated Random Walker method as ground truth. 300 3D ultrasound scans of first trimester placentas were used to train, validate and test the cNN. Compared against the semi-automated segmentation, resultant median (1st Quartile, 3rd Quartile) Dice Similarity Coefficient was 0.73 (0.66, 0.76). The median (1st Quartile, 3rd Quartile) Hausdorff distance was 27 mm (18 mm, 36 mm). We present the first attempt at using a deep cNN for segmentation of 3D ultrasound of the placenta. This work shows that feasible results compared to ground truth were obtained that could form the basis of a fully automatic segmentation method.

MEDXVIEWER: PROVIDING A WEB-ENABLED WORKSTATION ENVIRONMENT FOR COLLABORATIVE AND REMOTE MEDICAL IMAGING VIEWING, PERCEPTION STUDIES AND READER TRAINING

MedXViewer (Medical eXtensible Viewer) has been developed to address the need for workstation-independent, picture archiving and communication system (PACS)-less viewing and interaction with anonymised medical images. The aim of this paper is to describe the design and features of MedXViewer as well as to introduce the new features available in the latest release (version 1.2). MedXViewer currently supports digital mammography and tomosynthesis. The flexible software design used to develop MedXViewer allows it to be easily extended to support other imaging modalities. Regions of interest can be drawn by a user, and any associated information about a mark, an image or a study can be added. The questions and settings can be easily configured depending on the need of the research allowing both ROC and FROC studies to be performed. Complex tree-like questions can be asked where a given answer presents the user to new questions. The hanging protocol can be specified for each study. Panning, windowing, zooming and moving through slices are all available while modality-specific features can be easily enabled, e.g. quadrant zooming in digital mammography and tomosynthesis studies. MedXViewer can integrate with a web-based image database OPTIMAM Medical Image Database allowing results and images to be stored centrally. The software can, alternatively, run without a network connection where the images and results can be encrypted and stored locally on a machine or external drive. MedXViewer has been used for running remote paper-less observer studies and is capable of providing a training infrastructure and coordinating remote collaborative viewing sessions.

Automated collection of medical images for research from heterogeneous systems: trials and tribulations

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. Over the past two decades both diagnostic and therapeutic imaging have undergone a rapid growth, the ability to be able to harness this large influx of medical images can provide an essential resource for research and training. Traditionally, the systematic collection of medical images for research from heterogeneous sites has not been commonplace within the NHS and is fraught with challenges including; data acquisition, storage, secure transfer and correct anonymisation. Here, we describe a semi-automated system, which comprehensively oversees the collection of both unprocessed and processed medical images from acquisition to a centralised database. The provision of unprocessed images within our repository enables a multitude of potential research possibilities that utilise the images. Furthermore, we have developed systems and software to integrate these data with their associated clinical data and annotations providing a centralised dataset for research. Currently we regularly collect digital mammography images from two sites and partially collect from a further three, with efforts to expand into other modalities and sites currently ongoing. At present we have collected 34,014 2D images from 2623 individuals. In this paper we describe our medical image collection system for research and discuss the wide spectrum of challenges faced during the design and implementation of such systems.

Development and experience of quality control methods for digital breast tomosynthesis systems

OBJECTIVE To develop tomosynthesis quality control (QC) test methods and use them alongside established two-dimensional (2D) QC tests to measure the performance of digital breast tomosynthesis (DBT) systems used in a comparative trial with 2D mammography. METHODS DBT QC protocols and associated analysis were developed, incorporating adaptions of some 2D tests as well as some novel tests. The tomosynthesis tests were: mean glandular dose to the standard breast model; contrast-to-noise ratio in reconstructed focal planes; geometric distortion; artefact spread; threshold contrast detail detection in reconstructed focal planes, alignment of the X-ray beam to the reconstructed image and missed tissue; reproducibility of the tomosynthesis exposure; and homogeneity of the reconstructed focal planes. RESULTS Summaries of results from the tomosynthesis QC tests are presented together with some 2D results for comparison. CONCLUSION The tomosynthesis QC tests and analysis methods developed were successfully applied. The lessons learnt, which are detailed in the Discussion section, may be helpful to others embarking on DBT QC programmes. ADVANCES IN KNOWLEDGE DBT performance test equipment and analysis methods have been developed. The experience gained has contributed to the subsequent drafting of DBT QC protocols in the UK and Europe.

The oncology medical image database (OMI-DB)

Many projects to evaluate or conduct research in medical imaging require the large-scale collection of images (both unprocessed and processed) and associated data. This demand has led us to design and implement a flexible oncology image repository, which prospectively collects images and data from multiple sites throughout the UK. This Oncology Medical Image Database (OMI-DB) has been created to support research involving medical imaging and contains unprocessed and processed medical images, associated annotations and data, and where applicable expert-determined ground truths describing features of interest. The process of collection, annotation and storage is almost fully automated and is extremely adaptable, allowing for quick and easy expansion to disparate imaging sites and situations. Initially the database was developed as part of a large research project in digital mammography (OPTIMAM). Hence the initial focus has been digital mammography; as a result, much of the work described will focus on this field. However, the OMI -DB has been designed to support multiple modalities and is extensible and expandable to store any associated data with full anonymisation. Currently, the majority of associated data is made up of radiological, clinical and pathological annotations extracted from the UK’s National Breast Screening System (NBSS). In addition to the data, software and systems have been created to allow expert radiologists to annotate the images with interesting clinical features and provide descriptors of these features. The data from OMI-DB has been used in several observer studies and more are planned. To date we have collected 34,104 2D mammography images from 2,623 individuals.

Development of a quality control protocol for digital breast tomosynthesis systems in the TOMMY trial

Seven Hologic Dimensions digital breast tomosynthesis (DBT) systems have been installed for the TOMMY trial, a UK based multi-centre trial comparing conventional 2D digital mammography with DBT. In the absence of established guidelines for DBT quality control, a specific protocol was developed and applied. Physics tests of 2D and DBT performance were conducted at baseline and are repeated every 6 months, and include dose to the European standard breast model, tomosynthesis contrast to noise ratio, geometric distortion, z-resolution and threshold contrast detail detection. In addition routine performance checks (daily, weekly and monthly) are conducted on each system and reviewed centrally. Doses delivered under automatic exposure control by the systems were found to be well matched, with a mean glandular dose for the standard breast model (53mm equivalent breast thickness) of 1.89 mGy (range 1.79 to 2.00 mGy) for DBT and 1.41 mGy (range 1.36 to 1.48 mGy) for 2D imaging. Detector performance and image quality measurements were also well matched. All the systems exceeded the achievable image quality standard in the European guidelines for conventional digital mammography.

The effect of system geometry and dose on the threshold detectable calcification diameter in 2D-mammography and digital breast tomosynthesis.

Digital breast tomosynthesis (DBT) is under consideration to replace or to be used in combination with 2D-mammography in breast screening. The aim of this study was the comparison of the detection of microcalcification clusters by human observers in simulated breast images using 2D-mammography, narrow angle (15°/15 projections) and wide angle (50°/25 projections) DBT. The effects of the cluster height in the breast and the dose to the breast on calcification detection were also tested. Simulated images of 6 cm thick compressed breasts were produced with and without microcalcification clusters inserted, using a set of image modelling tools for 2D-mammography and DBT. Image processing and reconstruction were performed using commercial software. A series of 4-alternative forced choice (4AFC) experiments was conducted for signal detection with the microcalcification clusters as targets. Threshold detectable calcification diameter was found for each imaging modality with standard dose: 2D-mammography: 2D-mammography (165  ±  9 µm), narrow angle DBT (211  ±  11 µm) and wide angle DBT (257  ±  14 µm). Statistically significant differences were found when using different doses, but different geometries had a greater effect. No differences were found between the threshold detectable calcification diameters at different heights in the breast. Calcification clusters may have a lower detectability using DBT than 2D imaging.