ABSTRACT
Background There is a high prevalence of mucosal abnormalities of paranasal sinuses on CT Head scans performed for all indications. The purpose of this study is to see whether or not such abnormalities are more common in scans performed on patients presenting with headaches when compared with those without headaches. Methods Images of CT scans of the brain of 100 consecutive patients from each of the two study groups (a total of 200 scans) were retrospectively reviewed for the presence of sinus mucosal abnormalities and their Lund-Mackay (LM) scores were calculated. A corrected LM score was also calculated using a correction factor for non-visualized sinuses in some scans and osteomeatal complexes in all scans. Radiological reports for these scans were also reviewed to note whether or not they contained any comments on the sinuses. All the reviewed scans were performed between January 1, 2021 and January 22, 2021. Results In the headache group, 17 patients had an LM score above 4 (which was used as the main cut-off point for this study). In the non-headache group, 16 patients had a score greater than 4. The mean LM score in the headache group was 1.24 and in the non-headache group was 1.4. There has been no significant difference in the comparison when corrected LM scores were used. In the headache group, 22 radiology reports contained comments on the sinuses compared to 11 reports in the non-headache group. Conclusion Results of this study indicate that there is no significant difference in the prevalence of clinically important sinus mucosal abnormalities in patients who had a brain CT for headache when compared with other indications. It was found that radiologists tend to comment on the sinuses more often when the indication was headache. It may be reasonable for radiologists to consider reviewing this practice. This might reduce unnecessary referrals to ENT and, more importantly, avoid missing other reasons for headaches.
ABSTRACT
Radiology has seen rapid growth over the last few decades. Technological advances in equipment and computing have resulted in an explosion of new modalities and applications. However, this rapid expansion of capability and capacity has not been matched by a parallel growth in the number of radiologists. This has resulted in global shortages in the workforce, with the UK being one of the most affected countries. The UK National Health Service has been employing several conventional strategies to deal with the workforce situation with mixed success. The emergence of artificial intelligence (AI) tools that have the potential to increase efficiency and efficacy at various stages in radiology has made it possible for radiology departments to use new strategies and workflows that can offset workforce shortages to some extent. This review article discusses the current and projected radiology workforce situation in the UK and the various strategies to deal with it, including applications of AI in radiology. We highlight the benefits of AI tools in improving efficiency and patient safety. AI has a role along the patient's entire journey from the clinician requesting the appropriate radiological investigation, safe image acquisition, alerting the radiologists and clinicians about critical and life-threatening situations, cancer screening follow up, to generating meaningful radiology reports more efficiently. It has great potential in easing the workforce crisis and needs rapid adoption by radiology departments.
