In 1895 the father of radiology German physicist Wilhelm C Roentgen took the first X-Ray an image of his wife’s hand. On that November day, a vital diagnostic tool was born. We will explore how far radiology has come in 123 years and how far is it expected to go in the future?
Radiology involves the use of imaging machines to create internal images of the human body to detect diseases and injuries. Radiologists are specialists who interpret radiological images and have an extra five years of training.
Current Advancements in Radiology
Until fairly recently radiological images were analog meaning they were created using film. The problem with using film is that each time an image is reproduced definition is lost. Now, digital image acquisition allows for the infinite reproduction of images with no loss of clarity.
As an alternative to x-ray film flat-panel detectors reduce the patient’s exposure to radiation because the flat-panel detectors are more sensitive to light. Greater light sensitivity means images are produced faster and clearer than they would be on film. In the field of mammography, as compared to analog technology, flat-panel technology generates more useful information faster.
A sonogram (ultrasound) uses high-frequency sound waves to create images of soft tissue and organs. Ultrasound is non-invasive and offers the added advantage of being portable. 3D and 4D ultrasounds produce a video like an image. Neonatal 4D ultrasounds reveal details of the baby’s face that allow for the detection of a cleft palate or other birth malformity. Ultrasound can be used to diagnose a variety of conditions including soft tissue injuries and is used to help guide the needle during a biopsy.
Advances in Tomography (CT) are creating higher resolution images in less time. In cardiac care improvements in tomography have reduced the need for catheterization during an angiogram. Catheterization can result in a number of uncommon but serious reactions including stroke, heart attack, and reduced kidney functions
The Future of Radiology
Artificial Intelligence (AI) is projected to have a major role in radiology future. Deep learning neural networks are computer programs that mimic the functions of the brain. Neural networks have proven successful in identifying fractures and lesions that may indicate the presence of cancer. To date, the diagnostic abilities of AI had proven equal to that of radiologists.
The introduction of artificial intelligence is projected to be a boon to patients and radiologists alike. The Harvard Business Review states that the number of images taken of a single patient for a single suspected illness or injury can number in the hundreds. There are not enough radiologists to keep up with the workload.
The speed with which AI can scan images and interpret radiology information will take the pressure off of radiologists, reduce misdiagnosis, and operating costs. AI will not render human radiologists obsolete. Radiologists who refuse to accept artificial intelligence will render themselves obsolete.
The future of imaging equipment may include machines that create clear images even if the patient moves. Currently, 3D CT scans can only be taken of the extremities. Research is underway to make whole body 3D imaging a reality.
A system that turns 3D images into 3D anatomical models that surgeons can study prior to operating has been developed. Used to create 3D dental images cone-beam computed tomography (CBCT) machines circle the patient’s head emitting x-ray beans in a conical pattern. John Hopkins University is researching the potential use of CBCT to create images of acute intracranial hemorrhages.