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Take a look at a selection of our recent media coverage:
9th August 2023
Using an AI-supported mammography screening tool results in a similar breast cancer detection rate compared with standard double reading but with a substantially lower screen-reading workload, according to the interim safety findings of a new randomised controlled trial.
Making use of AI-supported software, researchers from Lund University in Sweden, have shown that a screening mammography avoids the need for double reading of all mammograms, without increasing false positives and almost halving radiologists‘ screen-reading workload.
Although previous retrospective analyses have indicated that combining AI with a radiologist improves the accuracy of breast cancer detection and reduces radiologist workload, there have been no randomised trials evaluating this approach until now.
Commenting on the findings, lead author Dr Kristina Lång said: ‘These promising interim safety results should be used to inform new trials and programme-based evaluations to address the pronounced radiologist shortage in many countries. But they are not enough on their own to confirm that AI is ready to be implemented in mammography screening.
‘We still need to understand the implications on patients’ outcomes, especially whether combining radiologists’ expertise with AI can help detect interval cancers that are often missed by traditional screening, as well as the cost-effectiveness of the technology’.
Published in The Lancet Oncology, the Mammography Screening with Artificial Intelligence (MASAI) trial enrolled 80,033 Swedish women aged 40-80 years who were eligible for mammography screening. Participants were randomly allocated 1:1 to either AI-supported screening (the intervention group, n = 40,003) or standard double reading without AI (the control group, n = 40,030).
The primary outcome measure of the MASAI trial was the interval cancer rate. Secondary outcomes examined included early screening performance (cancer detection rate, recall rate, false positive rate) and screen-reading workload (number of screen readings and consensus meetings).
The AI-supported system provided an examination-based malignancy risk score on a continuous scale ranging from 1 to 10. These examination were then categorised as either low risk (risk score 1 to 7), intermediate risk (risk scores 8 and 9) or high risk (risk score 10). In the intervention group, examinations with risk scores of 1 to 9 underwent single reading, whereas examinations with risk scores of 10 underwent double reading.
The cancer detection rate (per 1,000 screened women) was broadly similar, with a rate of 6.1% for the AI group and 5.1% in the control group. Similarly, recall rates were also not significantly different (2.2% vs 2.0%) and neither were the false positive rates (1.5% in both arms).
The number of screen readings was considerably lower for the AI-supported group (46,345 vs 83,231), representing a 44.3% workload decrease for reading screening mammograms.
23rd September 2022
Radiographer diagnostic performance for screening mammography is no different to radiologists for double reading digital mammograms and therefore offers a potential solution to the shortages of radiologists according to the results of a retrospective study by UK researchers.
Screening mammography is widely used in the detection of breast cancer and has been proven to decrease mortality. Moreover, the rate of cancer detection can be further increased by double reading of scans. For example, one study revealed how the relative increase in cancer detection as a result of a second reviewer was 6.3%.
In a 2016 survey, it was found that UK radiographers are already involved with interpreting and reporting images across the full spectrum of clinical indications for mammography including: low-risk population screening, symptomatic, annual surveillance, family history and biopsy/surgical cases. However, despite this change in role, there is limited evidence on the real-life radiographer diagnostic performance in double reading mammograms.
For the present study, the UK team examined the performance of radiographers and radiologists for all screening mammograms in England between 2015 and 2016. The researchers used three key metrics for comparison between radiographers and radiologists: the cancer detection rate (CDR); recall rate (RR) and positive predictive value (PPV) of recall on the basis of biopsy-proven pathological findings for the first readers. Each of the breast scans were analysed based on the reader profession (i.e., radiologist or radiographer) and years of experience.
Radiographer diagnostic performance on screening mammography
A total of 401 readers were included and double read the mammograms of 1,404,395 women. There were 224 radiologists who first read 763,958 mammograms and 177 radiographers who first read 640,437 mammograms.
The overall mean CDR was 7.7 per 1000 examinations and the mean radiographer diagnostic performance was 7.53/1000 examinations and 7.84 for radiologists (p = 0.08). When the researchers analysed CDR’s based on years of experience, there was no variation for either profession (p = 0.87).
The overall recall rate was 5% and again there was no significant difference between radiographers and radiologists (5.2% vs 5%, radiographers vs radiologists, p = 0.63) though the RR was lower for those with more years of experience.
Finally, the overall PPV was 16.7% and again differences between radiographers and radiologists were not significant (16.1% vs 17.1%, radiographers vs radiologists, p = 0.42). As with the RR, PPV improved with more years of experience.
The authors concluded that there were no clear differences in radiographer diagnostic performance and radiologists as readers of screening digital mammograms. They speculated that the use of trained radiographers in the double-reading workflow may offer a potential solution to the shortage of radiologists but suggested that more studies were needed to determine if such physician extender roles can and should, be used to read screening mammograms independent of the radiologist.
Chen Y et al. Performance of Radiologists and Radiographers in Double Reading Mammograms: The UK National Health Service Breast Screening Program Radiology 2022
26th August 2022
Racial disparity appears to be a significant factor in delayed follow-up among women who have an incomplete screening mammography and which has the potential for malignancy progression according to the findings of a study by researchers from New York, USA.
Screening mammography provides a means for the early detection of breast cancer and a 2007 systematic review found a 7% to 23% reduction in breast cancer mortality rates with screening mammography in women 40 to 49 years of age.
The Breast Imaging Reporting and Database System score (BI-RADS) is used by radiologists to describe the results of a mammogram and categorises the scans from 0 to 6. A BI-RADS score of 0 indicates an incomplete test and requires additional tests and images to provide a final assessment.
The National Breast and Cervical Cancer Early Detection Program in the US, has set a standard that the timeline from abnormal screening result to final diagnosis is 60 days for breast cancer screening. Factors known to be associated with delayed follow-up include language barriers although the impact of other factors is less clear.
In the present study, the US researchers sought to further identify risk factors for delayed follow-up of abnormal screening results and undertook a retrospective, observational study of individuals with a BR-RADS-0 screening mammogram.
At the first visit, individuals answered a questionnaire that provided routine electronic clinical and sociodemographic characteristics and the research team examined the factors associated with a < 60 day and a > 60 day delay.
Racial disparity and follow-up delays
A total of 4,552 individuals were included and among those having a follow-up, 76.7% did so within 60 days.
When the researchers looked at factors associated with delays > 60 days, there were clear racial disparities. For example, individuals self-identifying as Black, had a 1.64 increased odds (95% CI 1.54 – 1.75, p < 0.0001) of a > 60 day delayed follow-up compared to those of White ethnicity.
This was also seen for those of Asian ethnicity (odds ratio, OR = 1.43, 95% CI 1.27 – 1.58, p = 0.022) as did those self-identifying as “other” (OR = 1.45, 95% CI 1.32 – 1.58, p = 0.005). However, among those of Hispanic heritage, the difference was not significant (OR = 1.05, 95% CI 0.93 – 1.17, p = 0.69).
There was also a higher odds for a delayed follow-up among those who completed their questionnaire in Spanish (OR = 1.67, 955 CI 1.51 – 1.83).
Further analysis also highlighted racial disparities. For instance, White individuals had a shorter median follow-up compared to Black and those identified as “other”.
The authors concluded that with racial disparities associated with an increased risk of delayed follow-up for abnormal mammography screening, further work is required to identify the causes for these delays.
Platt S et al. BI-RADS-0 screening mammography: Risk factors that prevent or delay follow-up time to diagnostic evaluation J Am Coll Radiol 2022