British Journal of Radiology 74 (2001),317-322 © 2001 The British Institute of Radiology
Geographical distribution of breast cancers on the mammogram: an interval cancer database
M Brown,
C Eccles, MSc and
M G Wallis, FRCR
Warwickshire, Solihull and Coventry Breast Screening Service, Coventry and Warwickshire Hospital, Stoney Stanton Road, Coventry CV1 4FH, UK
Correspondence: Dr MG Wallis
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Abstract
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Auditing interval cancers is an important part of a breast screening radiologist's continuing education. We set out to determine whether the position of interval cancers on the mammogram differs from those detected at screening. The 773 interval cancers so far identified, and the first 200 screen detected cancers, have been entered onto a Microsoft Access 97 database developed to record pathological and radiological features, including the position of the cancer on a stylized diagram using a "point and click" system. Reports were generated showing positions of all interval cancers by classification and reader. The distribution of true interval cancers is statistically different from screen detected cancers on both views. The distribution of the false negative and screen detected cancers only differs on the oblique view. False negative and true interval cancers are of the same distribution on both craniocaudal and oblique views. However, these differences do not appear to be practically useful when applied to individual readers. We have developed a database that allows systematic recording of pathological and radiological information regarding breast cancers. Additionally, it can record the geographic position of the cancer with minimal memory requirements. Statistical differences in the distribution of false negative and screen detected cancers have been demonstrated and the stylized diagrams reinforce the importance of the conventional review areas. Although this has not identified any "blind spots" in our own readers, it nevertheless provides film readers with a tool to audit their own work.
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Introduction
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From its inception in 1988, the UK National Health Service Breast Screening Programme (NHSBSP) recognized that screening can never be a perfect test and that cancer will present during the interval between screens [1]. The number of these interval cancers is a measure of the quality of the programme and will indirectly predict the mortality reduction that can be expected [2, 3]. The NHSBSP expects all film readers to audit interval cancers as part of their continued professional development, in the anticipation that retrospective review of those cancers that could potentially have been diagnosed earlier will help to improve performance [4]. Several groups have identified radiological features [5–7] that film readers find difficult, but to date there has only been limited work describing where cancers occur on the actual mammograms [8–10]. Whilst developing a database to collect and audit interval cancers, we have developed a relatively simple way of plotting the position of the cancer on a stylized diagram. We can then systematically collect information, not only about radiological signs but also about geographical distribution of interval cancers, to assist film readers in their continual improvement.
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Materials and methods
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All 773 interval cancers identified up to 1 May 2000 by the Warwickshire, Solihull and Coventry Breast Screening Programme, since screening started in 1989, have been classified by both the internal film readers and as part of Regional Quality Assurance initiatives in line with NHSBSP guidance [4]. These have all been entered onto the bespoke database. In addition, the first 200 screen detected cancers have been entered to form a control group.
The bespoke database has been developed using Visual Basic for Applications in the Microsoft Access 97 software environment. The database records the patient's demographic details, clinical information (including pre-operative tests and results), radiological features of the diagnostic mammogram and last screening mammogram, histopathology results and audit details including reader details and classification. A simple "point and click" system is used to mark the position of the cancer on a stylized diagram of the breast using both mediolateral oblique and craniocaudal projections. The position is recorded by the computer as an x–y co-ordinate. The stylized diagram can be displayed and printed. Variables can be selected to include any or all of the film readers and interval classification. For convenience, right-sided cancers are transposed onto and combined with left-sided cancers.
A fine grid is placed over the cancer location diagram created by the database to determine whether the geographical positions of cancers within the breast have a random distribution. The number of cancers in each square can then be observed. The Poisson, 
2 and critical values are calculated using this information. It is then possible to ascertain whether the distribution of cancers within the breast is random.
A two-sample Kolmogorov–Smirnov test is performed to establish whether there is a difference in the distribution of the false negative and true interval cancers. A marker is placed on both the oblique and craniocaudal projections using the diagram showing the geographical location of the cancers from the developed database. The distance from the marker to each individual cancer is measured to the closest millimetre. From this, the cumulative relative frequency polygon is developed for each projection and interval cancer classification. This method is repeated to compare the geographical distribution of the screen detected cancers and the two classifications of interval cancers. By comparing the maximum difference between the cumulative relative frequency polygons and the critical value, it is possible to conclude whether the distributions are significantly different and at what level.
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Results
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The classification of the 773 interval cancers is shown in Table 1
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Table 1. The number and classification of all interval cancers at the Warwickshire, Solihull and Coventry Breast Screening Service
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Figure 1 shows the distribution of the 200 screen detected cancers. The distribution of the 354 true interval cancers is shown in Figure 2 and the 122 false negative interval cancers in Figure 3. The false negative interval cancers for two of the readers is shown in Figure 4.
The distribution of cancers across the breast is uneven, with clusters in the tail and inframammary fold on the oblique projection. On the craniocaudal projection, clustering occurs in the tail, centrally and in the medial portions of the breast. This is confirmed by using the Poisson distribution (critical value 15.087 (3 dp)) and the 2 test (2 value 527.824 (3 dp)).
Simple visual examination of the figures does not suggest any obvious differences in distribution between screen detected controls and the true or false negative interval cancers. However, the following results, shown in Table 2, have been obtained using the Kolmogorov–Smirnov test.
Table 2
shows that the distribution of true interval cancers is significantly different from the distribution of screen detected cancers on both projections. The distributions of false negative interval cancers and screen detected cancers are the same on the craniocaudal projection, but are of a different distribution on the oblique projection. It can also be seen that false negative and true interval cancers are of the same distribution on both the craniocaudal and oblique projections.
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Discussion
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Our frequency of false negative cancers, 19% of classifiable cases, is comparable with other series [11, 12]. The simple user interface allowing the "point and click" is very easy to use on a practical level. It also has only a minimal demand on memory space when compared with describing the position of cancer as either full digitized images or very compressed images. The single point allows for combining data to identify patterns but is admitted to be a crude method for marking a three-dimensional mass. This is only a practical problem when locating a diffuse process such as the microcalcification of ductal carcinoma in situ. It provides a greater degree of flexibility than Hackshaw's method of using a grid to divide the breast disc into eight sectors [10].
Hanley [13] originally described the distribution of 1000 breast cancers within the breast (Figure 5), indicating that 38.2% were situated in the upper outer quadrant. Lundgren and Jackobsson [14] initially described screening with the single mediolateral oblique mammogram, which was used as the basis of the UK NHSBSP until 1995 when the craniocaudal view was introduced for prevalent screen, as a number of papers indicate its importance for the additional detection of small cancers [15, 16]. The way individual areas of the breast are demonstrated on the standard mediolateral oblique projection and craniocaudal projections has been documented by Lee et al [17], and the distribution of our cases conforms well with Hanley's description [13].
Tabár (personal communication) describes a systematic schema for viewing mammograms and graphically indicates the review areas that require special attention (Figure 6); namely the "milky way" and the retroareolar space on the oblique projection, and the medial portion of the breast and "no mans land" at the back of the breast behind the glandular tissue on the craniocaudal projection. Our data reinforce this view as most of our screen detected and interval cancers fall in similar areas. Hackshaw et al [10] shows similar clustering to our own data but with a larger central distribution. Naylor et al [18] used this distribution pattern on the craniocaudal view to advise a neutral radiographic position rather than either medial or lateral rotation, and our data would tend to reinforce this as cancers are seen in both the axillary tail and medial aspects. Interestingly, Daly et al [9] locate their rescreen cancers that were visible 3 years earlier in very similar positions.
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Figure 6. Tabár's "forbidden zones" i.e. areas that require special attention. a, "Milky way" 3–4 cm wide parallel to edge of pectoral muscle; b, "no mans land", retroglandular space; c, medial half of the breast on the craniocaudal projection; d, retroglandular area.
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The number of cases is small and not amenable to statistical analysis when looking at the results for individual readers (Figure 4). However, as with the distribution of true, false negative and control groups, they appear to be distributed in very similar patterns. So, to date, no obvious "blind spots" have been identified for any of our film readers.
In conclusion, we have developed a database that allows systematic recording of pathological and radiological information regarding breast cancers. Additionally, it can record the geographic position of the cancer with minimal memory requirements. Statistical differences in the distribution of false negative and screen detected cancers have been demonstrated and the stylized diagrams reinforce the importance of the conventional review areas. Although this has not identified any "blind spots" in our own readers, it nevertheless provides film readers with a tool to audit their own work. This database is available at www.bcsicd.fsworld.co.uk
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Acknowledgments
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Chris Eccles developed the database as part of his MSc at Coventry University.
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Footnotes
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Melita Brown was funded by the Breast Screening Trust Fund. 
Received for publication September 11, 2000.
Revision received November 24, 2000.
Accepted for publication December 5, 2000.
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References
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Abstract
Introduction
