The dawn of the modern medical imaging world, where doctors can examine and diagnose illnesses without necessarily requiring biopsies or physical examination, started at the end of the 19th century.

After Wilhelm Röntgen captured an image of his wife’s hand in 1895, it unlocked an entire field of medical diagnosis, which would later include CAT scans and ultrasound.

Whilst the history of the X-ray and computer tomography are well-documented and well-known, ultrasound in a medical context had a far more complex history, in part because it took so many steps to even realise it could be used in a medical context.

Ultrasound has existed for as long as bats have, but the echolocation ability of these flying mammals was only discovered in 1794 by scientist Lazzaro Spallanzani, and it took another century for the Galton whistle, one of the first ultrasound devices ever made, to be invented.

However, people wanted to know if it would be possible to make a device that took advantage of ultrasound and echolocation to inspect objects without opening them where an X-ray would be unusable.

This led in the late 1930s to several scientists in a wide range of fields attempting to piece together this functionality.

Floyd Firestone would create a testing device known as the Supersonic Reflectoscope in 1940, but it would not be used for medical purposes.

Meanwhile, Karl Theo Dussik and his brother Friedrich completed the first partial scan of a human body part in 1941, creating a faint outline of the brain.

The first successful ultrasound used for clinical purposes rather than research purposes was by John Wild in 1949 to check the intestines and bowels of patients who had been the victims of bomb strikes.

This work was refined and first published in The Lancet medical journal in March of 1951, and it very quickly was found to have particular promise for identifying tumours.

This early pioneering work has steered the imaging world ever since, as ever more advanced technology is used to help save lives.

The government has announced it will invest £21 million in rolling out artificial intelligence (AI) tools across the NHS.

It hopes the technology will help diagnose and treat patients more quickly, helping to improve healthcare across the country. 

Health and social care secretary Steve Barclay stated: “AI tools are already making a significant impact across the NHS in diagnosing conditions earlier, meaning people can be treated more quickly.”

NHS Trusts can apply to the AI Diagnostic Fund for AI imaging and decision support tools for patients suffering from cancers, heart conditions and strokes. 

The technology will be able to analyse chest X-rays, of which more than 600,000 are performed every month in England alone. 

Being able to assess the tests quickly could help lung cancer patients get the diagnosis and help they need faster.

Mr Barclay also committed to providing AI stroke-diagnosis technology to all stroke networks by the end of the year. 

Currently, 86 per cent of centres have this technology, which is thought to halve the time for stroke patients to get treatment. This can triple the chance of stroke sufferers being able to live independently. 

The NHS is also piloting AI software to reduce the number of missed hospital appointments. 

By analysing data and external insights like traffic and weather conditions, it can provide patients with more convenient times for their appointments, so they are less likely to miss it. 

If you’re looking for medical imaging management that can support AI tools, get in touch with us today.

The importance of medical image sharing in helping to provide access to crucial data and help specialists make diagnoses is well known, but it could gain even more significance in an age when the capacity for images to be used effectively in identifying conditions is increasing.

A key factor in enhancing diagnostic capacity is the use of artificial intelligence (AI). While there are ways in which this technology has been seen by some as a threat to humanity, the Department for Health and Social Care has just announced £21 million of ringfenced funding to roll out AI across the NHS.

The announcement listed cancers, strokes and heart conditions as examples of the sort of things AI can help identify.

AI is available in 86 per cent of stroke network settings, but the government is committed to increasing this to 100 per cent by the end of 2023.

Health secretary Steve Barclay said: “AI tools are already making a significant impact across the NHS in diagnosing conditions earlier, meaning people can be treated more quickly.”

Adding image-sharing services using facilities like the Cloud can maximise this benefit, by helping get the information from more accurate and speedy diagnoses to those who need it as fast and efficiently as possible. This will enable the right treatment to begin quickly.

A separate announcement will provide a further boost to those who may be suffering from lung cancer, with the full roll-out of a new £270 million targeted lung cancer screening programme being launched.

This will focus on people aged between 55 and 74 with a history of smoking, who may benefit from having the condition spotted at an earlier stage.

It will involve nearly a million scans a year and is expected to provide a potentially life-saving early diagnosis for around 9,000 cancer patients.

The move follows an initial phase in which 76 per cent of the lung cancers detected were at an early stage.

Missed hospital appointments cost the NHS millions of pounds every year, which is why it is piloting artificial intelligence (AI) software to reduce the number of incidents.

AI will use algorithms, data, and external insights, such as weather, traffic, and jobs, to determine the likelihood of a missed appointment, so that a booking is arranged for a more convenient time. This will lower the probability of the patient missing their slot. 

It also provides back-up bookings, so no appointment is wasted, increasing efficiency of the health service. 

Chief executive of the NHS Amanda Pritchard said: “[The new pilot] shows the NHS testing the latest technological advancements to address the real world challenges we face.”

She added: “The system will help ensure patients receive ‘smart’ appointments, that are convenient and fit into people’s increasingly busy lives.”

The scheme is being trialled in Mid and South Essex NHS Foundation Trust, where there is an average did not attend (DNA) rate of eight per cent. Data will be collected and analysed to determine whether the DNA will improve with the AI.

It is hoped an extra 80-100,000 patients will be able to be seen at the Trust every year, as a result of the technology. 

Every year, eight million appointments are missed, costing the NHS around £1.2 billion. 

The new software could help the health service reduce its huge backlog of patients waiting for appointments. It was recently revealed that 39,903 people are currently waiting more than 18 months for a referral. 

If this pilot is successful, AI technology could become more commonplace in the NHS, from being used as a diagnostic tool to remote radiology reporting.

Medical images of rounded hearts could be an early sign of cardiovascular disease.

The National Institutes of Health revealed research in the journal Med that suggests analysis of pictures of the shape of hearts could become a diagnostic tool. 

David Ouyang, co-corresponding author or the study and a Smidt Heart Institute of Cedars-Sinair cardiologist, said: “These findings might allow physicians to gain greater clinical intuition on how patients are likely to do at a very rapid glance.”

The scientists used the shape and measurements of heart chambers, as well as anatomical changes, to determine a heightened risk of cardiomyopathy or other heart ailments.

They used machine learning and big data for their study, looking at the UK Biobank, which has clinical and genetic information on around half a million people. The researchers examined 38,000 participants who had normal MRI images of their hearts and made a correlation with those who went on to develop heart diseases based on subsequent medical records. 

They discovered that those who had increased cardiac sphericity had a greater chance of future heart problems. There was also a link between the genetic drivers for heart roundness and cardiomyopathy. 

Using deep-learning analysis, they determined that intrinsic heart muscle disease resulted in cardiac sphericity. 

Mr Ouyang added: “Just as we’ve previously known that a bigger heart isn’t always better, we’re learning that a rounder heart is also not better.”

More data taken from medical imaging storage is required for greater analysis, according to the scientists, including ultrasound images instead of MRI screenings to see if these confirm what they have found already.

If further research can be carried out, this could help the 7.6 million people living with heart and circulatory diseases in the UK. It may also help to reduce the number of heart disease-related fatalities from one person every three minutes.