Search

Breast Screening Information System (BSIS) records all breast screening personnel’s quality assurance results for England. The PERFORMS self-assessment scheme also invites these individuals to take part annually to report a series of challenging breast screening cases and feedback to them to help them improve their real life screening performance. How PERFORMS data relate to actual screening performance were investigated between these two sets of data. In this study, 582 screeners consented to take part. Their performance over a three-year period were acquired from BSIS database. Also, each individual’s comparative data were extracted from the PERFORMS database over the same time period and the relationship between the two sets of measures were examined. 533 participants’ data were successfully matched and validated. A kendall’s tau-b correlation was run to determine the relationship between the PPV values calculated from real-life data (cancer detected/ total recalls) over the past three years and the PERFORMS average PPV values over the same period. There was a strong, positive correlation between them, which was statistically significant (τb = .141, p

This paper describes the implementation of serial communication between the PLC and the host-computer in the control system of home environment, gives a detailed introduction to the communication protocols, parameters setting and also gives part of the serial-communication program based on visual basic 6.0. It shows that this control system meets the requirements as expected.

In this paper a new approach is proposed to track the perceptual behaviour of radiologists when they examine mammographic images displayed on large dual clinical monitors. Zooming and panning are inevitably performed by the radiologist to examine such large images by using the DICOM viewing software. Such image manipulating movements on the target displays makes eye tracking techniques difficult to perform and also the size of the dual clinical monitors makes existing eye tracking techniques generally inadequate. Hence a method using the Smart Eye Pro eye tracker and optical character recognition techniques was designed to relate the recorded radiologists’ eye gaze behaviour on the monitors to the actual zoomed and panned medical image areas. This then allows clinical studies involving radiologists interacting with these mammographic images to be successfully carried out.

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.

This paper describes the implementation of serial communication between the PLC and the host- computer in the control system of Spatial Carport, gives a detailed introduction to the communication protocols, parameters setting and also gives part of the serial-communication program based on visual basic 6.0. It shows that this control system meets the requirements as expected.

In the UK all screeners undertake the PERFORMS scheme where they read annual sets of challenging cases. During this assessment, they give each case a confidence rating on whether it should be recalled. If they decide to recall a case, they also indicate the center of any key mammographic features on a display of the relevant mammographic case view. Expert radiological opinion defines what the key abnormalities (targets) are in any case. Data can then be analyzed using ROC and JAFROC approaches, and particularly for the latter, assessing whether a user has correctly located a feature or not is important. Using image pixel information alone it is possible to delineate correct localization of an abnormality from an incorrect location by defining an area of interest. To explore such location information in more detail, data from the last year of the PERFORMS scheme were reanalyzed and the location responses for each of the 675 participants on 120 screening cases examined. Additionally, expert radiological opinions had been garnered for various reasons, including accurately delineating any abnormalities. An algorithmic approach is developed which assesses whether users’ indications should be included as correct abnormality identification or not, based on the feedback location information of all participants’ indicated locations and the relative position of an indicated location to the abnormality. This approach is proposed to be superior to simple pixel distance approaches which measure a fixed distance from the centre of a target to the user’s indicated location. The approach adds to the experimenter’s repertoire of tools when examining user errors and case difficulty in medical imaging research.

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.