The international use of PERFORMS mammographic test sets

To examine the utility of employing breast screening test sets internationally the data of 1,009 radiologists from the USA, UK and other European countries were examined as they inspected 20 carefully selected difficult recent screening cases. Some 720 UK radiologists, 247 American and 42 European radiologists took part. Whilst similar sensitivity scores between the three groups were found, the main difference was the lower specificity of the American radiologists reflecting their different recall clinical practice. It is argued that using test sets internationally provides participants with useful comparative performance information whilst also providing data on how the same cases are interpreted by radiologists from different countries

A scalable system for microcalcification cluster automated detection in a distributed mammographic database

A computer-aided detection (CADe) system for microcalcification cluster identification in mammograms has been developed in the framework of the EU-founded MammoGrid project. The CADe software is mainly based on wavelet transforms and artificial neural networks. It is able to identify microcalcifications in different datasets of mammograms (i.e. acquired with different machines and settings, digitized with different pitch and bit depth or direct digital ones). The CADe can be remotely run from GRID-connected acquisition and annotation stations, supporting clinicians from geographically distant locations in the interpretation of mammographic data. We report and discuss the system performances on different datasets of mammograms and the status of the GRID-enabled CADe analysis.Comment: 6 pages, 4 figures; Proceedings of the IEEE NNS and MIC Conference, October 23-29, 2005, Puerto Ric

Can high-frequency ultrasound predict metastatic lymph nodes in patients with invasive breast cancer?

Aim To determine whether high-frequency ultrasound can predict the presence of metastatic axillary lymph nodes, with a high specificity and positive predictive value, in patients with invasive breast cancer. The clinical aim is to identify patients with axillary disease requiring surgery who would not normally, on clinical grounds, have an axillary dissection, so potentially improving outcome and survival rates. Materials and methods The ipsilateral and contralateral axillae of 42 consecutive patients with invasive breast cancer were scanned prior to treatment using a B-mode frequency of 13 MHz and a Power Doppler frequency of 7 MHz. The presence or absence of an echogenic centre for each lymph node detected was recorded, and measurements were also taken to determine the L/S ratio and the widest and narrowest part of the cortex. Power Doppler was also used to determine vascularity. The contralateral axilla was used as a control for each patient. Results In this study of patients with invasive breast cancer, ipsilateral lymph nodes with a cortical bulge ≥3 mm and/or at least two lymph nodes with absent echogenic centres indicated the presence of metastatic axillary lymph nodes (10 patients). The sensitivity and specificity were 52.6% and 100%, respectively, positive and negative predictive values were 100% and 71.9%, respectively, the P value was 0.001 and the Kappa score was 0.55.\ud Conclusion This would indicate that high-frequency ultrasound can be used to accurately predict metastatic lymph nodes in a proportion of patients with invasive breast cancer, which may alter patient management

A potential method to identify poor breast screening performance

In the UK all breast screeners undertake the PERFORMS scheme where they annually read case sets of challenging cases. From the subsequent data it is possible to identify any individual who is performing significantly lower than their peers. This can then facilitate them being offered further targeted training to improve performance. However, currently this under-performance can only be calculated once all screeners have taken part, which means the feedback can potentially take several months. To determine whether such performance outliers could usefully be identified approximately much earlier the data from the last round of the scheme were re-analysed. From the information of 283 participants, 1,000 groups of them were selected randomly for fixed group sizes varying from four to 50 individuals. After applying bootstrapping on 1,000 groups, a distribution of low performance threshold values was constructed. Then the accuracy of estimation was determined by calculating the median value and standard error of this distribution as compared with the known actual results. Data indicate that increasing sample sizes improved the estimation of the median and decreased the standard error. Using information from as few as 25 individuals allowed an approximation of the known outlier cut off value and this improved with larger sample sizes. This approach is now implemented in the PERFORMS scheme to enable individuals who have difficulties, as compared to their peers, to be identified very early after taking part which can then help them to improve their performance

How are false negative cases perceived by mammographers? Which abnormalities are misinterpreted and which go undetected?

A radiographic ‘false negative’ or a case which has been ‘missed’ can be categorised in terms of errors of search (where gaze does not fall upon the abnormality); detection (a perceptual error where the abnormality may be physically ‘seen’ but remains undetected) and misinterpretation (a perceptual error whereby an abnormality, although detected, is not deemed worthy of further assessment). This study aims to investigate perceptual errors in mammographic film-reading and will focus on the later of the two error types, namely errors of misinterpretation and errors of non-detection. Previous research has shown, on a self-assessment scheme of recent and difficult breast-screening cases, that certain feature types are susceptible to errors of misinterpretation and others to errors of non-detection. This self assessment scheme, ‘PERFORMS’ (Personal Performance in Mammographic Screening), is undertaken by the majority (at present over 90%) of breast-screening mammographers in the UK Breast Screening Programme. The scheme is completed biannually and confidentially and participants receive immediate and detailed feedback on their performance. Feedback from the scheme includes information detailing their false negative decisions including case classifications (benign or malignant), feature type (masses, calcification, asymmetries, architectural distortions and others) and case perception error (percentage of misinterpretation and percentage of non-detection). Results from a recent round of PERFORMS (n=506), revealed that certain feature types had significantly higher percentages of error overall (including architectural distortion and asymmetries), and that these feature types also showed significant differences for error type. Implications for real-life screening practice were explored using real-life self-reported data on years of screening experience

Breast screening: visual search as an aid for digital mammographic interpretation training

Digital mammography is gradually being introduced across all breast screening centres in the UK during 2010. This provides increased training opportunities using lower resolution, lower cost and more widely available devices, in addition to the clinical digital mammography workstations. This study examined how experienced breast screening personnel performed when they examined sets of difficult DICOM two-view screening cases in three conditions: on GE digital mammography workstations, on a standard LCD monitor (using a DICOM viewer) and an iPhone (running Osirix software). In each condition they either viewed the full images unaided or were permitted to use the post-processing manipulations of pan, zoom and window level/width adjustments. For each case they had to report the feature type, rate their confidence on the presence of abnormality, classify the case and specify case density. Their visual search behaviour was recorded throughout using a head mounted eye tracker. Additionally aspects of their real life screening performance and performance on a national self assessment scheme were examined. Data indicate that screening experience plays a major role in doing well on the self assessment scheme. Task performance was best on the clinical workstation. However, the data also suggest that a DICOM viewer that runs on a PC or laptop with a standard LCD display allows viewing digital images in full resolution support impressive cancer detection performance. The iPhone is not ideal for examining full images due to the amount of scrolling and zooming required. Overall, the results indicate that low cost devices could be used to provide additional tailored training as long as device resolution and HCI aspects are carefully considered