The current shortfalls of the field of radiology affect radiologists, who primarily rely on the time-demanding processes of manual analysis of MRI scans and subjective measurement, but also referrals, such as neurologic and psychiatric practitioners, and purchase departments on administrative levels, as well as patients and their relatives.
Recent developments in neurological computer-assisted analysis could, however, prove a valuable tool in counteracting the current trends. By substituting subjective-based decisionmaking processes with quantifiable metrics for brain volume, radiologists may have found the tool to increase productivity, optimise distribution of resources, reduce subjectivity and establish a new standard of radiological reading ensuring greater assessment confidence. The effects of this could benefit not only radiologic practices but also those that are directly or indirectly affected by it.
In most countries, there is a shortage of radiologists to meet the ever-increasing demand for imaging and diagnostic services. Future prospects are not too bright, as imaging volumes are increasing at a faster rate than new radiologists are entering the field.
This results in a skewed distribution of the experience of the radiologists; with the majority of radiologists still pertaining to manual analysis of brain MRI analysis, a balanced distribution of resources is hard to obtain, especially for the younger and less experienced radiologists. The effects are also seen in more remote places, where there are often less radiological subspecialist experts, such as neuroradiologists.
The current challenges also stem from the fact that the field of neuroradiology still has not fully adopted the possibilities brought along by neurological computer-assisted analysis. Perhaps neuroradiology could seek inspiration from the field of mammography, which, within the past decade, has seen a steady increase in the use of computer-assisted analysis. Using automated techniques for the diagnosis and grading of breast cancer images has resulted in earlier detection of diseases and an improvement in survival rate.
Radiological best practice procedures, in terms of analysis and diagnosis, still rely heavily on individual experience and subjective measurements. As a result, radiologists cannot always fully exploit their expertise or quantify their results. The increased demand for radiological services, along with the global shortage of educated radiologists, means less time for radiological coretasks, such as analysing and assessing brain MRIs and determining diagnoses.
For patients, the stakes are even higher, dealing with repeatable revisitations in the healthcare system. They also suffer from late detection and diagnosing of diseases, which makes treatment less likely to succeed and reduces the chances of recovery.
On a larger scale, continuous revisitations of patients affect the economic stability of the health system, causing higher costs for hospitals, insurance companies and purchase departments.
While the current state of affairs requires more than quick fixes, recent advances in neurological computer-assisted analysis may prove valuable in mitigating a number of challenges by optimising and supporting radiologic resources and work processes.
Computer-assisted analysis of brain MRI scans aims at releasing the full potential of MRI scans by providing a better decision-making foundation for radiologists. Software tools, such as Danish Neuroreader, support subjective measurements of brain volume with quantifiable metrics, thereby supporting a more holistic and objective assessment.
Neuroreader enables radiologists to compare readings with images and outcomes of similar cases, ensuring a decisionmaking foundation independent of individual experience. "Neuroreader gives us easy, reliable, reproducible volume measurements and takes the guesswork out of analysing structures in our patients' brains," says Professor Barton Branstetter, from the University of Pittsburgh Medical Center.
The ability to compare readings makes it easier for the radiologist to direct attention to specific areas of interest. This allows a swifter and more effective analysis, with a more knowledgeable and precise focus. For radiologists, this could mean a reduction of the need for second opinions and second-guessing, thereby increasing productivity and optimising workflow.
"Neuroreader stands out from the crowd by its comprehensive approach, as it performs a fully automated analysis of 45 visually identifiable brain structures in ten minutes," says Professor John L Ulmer, from the Medical College of Wisconsin. "This enables the analysis of patterns of neurodegeneration in patients with MCI. Significant diagnostic benefits have already been realised, such as earlier detection of disease, supporting clinical diagnoses, and the subsequent coherent and more personalised treatment plans.
"Neuroreader has established itself as an essential diagnostic aid in our memory disorders programme. It may also have positive implications for patients depending on radiologic services, as well as those neurologic and psychiatric practitioners who interact with the patients on a regular basis. Finally, the healthcare purchase departments that pay for the services may experience positive consequences," he concludes.
For patients, an early and correct diagnosis is naturally essential, promising fewer revisitations in the healthcare system and, ultimately, better chances of recovery and maintenance of life quality for as long as possible. Computer-assisted brain MRI analysis software points to a potential near future where patients, as well as their physicians, are provided with the possibility to track individual health development over time. In turn, patients may have a more complete understanding of their health situation, in the case of negative and positive changes. In this sense, computer-assisted brain MRI analysis software could have a health-promoting angle, assuring patients if nothing is wrong or building motivation in showing that efforts to stabilise or reverse symptoms are paying off.
For the neurologist or psychiatrist, computer-assisted analysis of brain MRI scans could, among the already mentioned benefits, also prove valuable as a communication frame for conveying technical information to patients and relatives about their health development over time. One could imagine visual representations of, for example, hippocampus growth or regress being used as a concrete and tangible tool in demonstrating current disease or health development to patients.
Finally, hospital administration or purchase departments could benefit from the advances made with computer-assisted brain MRI analysis software. Higher productivity, efficiency and accuracy in brain MRI analysis could amount to reduced costs in terms of less revisitation of patients and a higher number of referred patients to the clinic or hospital due to positive reputation and strengthened image. Brain MRI analysis software, such as Neuroreader, can be applied regardless of the individual radiologist's experience level. This could allow a more nuanced hiring policy where younger radiologists could execute tasks that were previously reserved for more experienced physicians.
The field of radiology is, like everything else, always evolving alongside technological developments. The current challenges require the best from all radiologists, and radiologists should therefore also be supported in the best possible way.
A tight integration of computer-assisted brain MRI analysis software, such as Neuroreader, in radiologic processes may be the next natural step that the field should take.
