MRI services across Australia and New Zealand continue to operate under sustained pressure. Demand for diagnostic imaging is rising, while scanner availability and workforce growth remain constrained. As a result, extended MRI waiting lists have become a persistent challenge for many public hospital systems across the region.¹ ²
MRI backlogs are often discussed in administrative terms, but in practice they reflect something more fundamental: limits in effective MRI throughput.
Growing demand in a constrained system
Across Australia and New Zealand, diagnostic imaging volumes continue to increase as imaging becomes central to modern clinical decision‑making. MRI utilisation has expanded steadily across oncology, neurology, musculoskeletal imaging, and chronic disease management.¹
At the same time, scanner density across the region remains modest. Australia operates approximately 14 MRI units per million people, while New Zealand operates approximately 9 per million — both below the OECD average of around 19 per million.² In lower‑density systems, there is limited ability to absorb inefficiencies or redistribute workload.
Workforce growth has been measured rather than exponential, placing additional pressure on existing teams.³ Under these conditions, departments often operate close to capacity, and small inefficiencies quickly compound into waiting list growth.
The challenge is not whether MRI demand exists. It is whether existing infrastructure can continue to absorb that demand reliably.
Throughput defines access
MRI access is ultimately governed by throughput — the number of completed, diagnostic examinations delivered consistently each day.
Exam setup, patient positioning, protocol execution, reconstruction time, and patient tolerance all contribute to total scan duration. Individually, each step may add only minutes. Across a full operating list, those minutes define daily and annual capacity.
Even modest reductions in average exam time can translate into hundreds of additional scans per scanner each year. Conversely, variability in protocol duration or the need for repeat imaging erodes effective capacity.
GE HealthCare MRI platforms are designed to address these throughput drivers in a coordinated way. Technologies such as AIR™ Recon DL deep‑learning reconstruction reduce reconstruction time variability and improve image consistency, while workflow‑integrated acceleration technologies such as Sonic DL™ support faster and more predictable exam completion. Patient‑centric system design and ergonomic AIR™ Coil technology further support efficient positioning and improved patient tolerance.
MRI backlogs form when demand persistently exceeds effective throughput.
Variability, not speed, drives MRI backlog growth
In many departments, the primary challenge is not raw scanning speed, but predictability.
Inconsistent exam durations reduce scheduling accuracy and compress daily lists. Motion artefacts or image quality issues that require reacquisition further reduce capacity, often without being immediately visible.⁴ ⁵
Reducing variability across examinations is therefore critical. Predictable protocol execution, reliable reconstruction output, and improved patient tolerance all support more stable throughput.
GE HealthCare’s MRI portfolio is intentionally designed to reduce this operational variability. Deep‑learning reconstruction with AIR™ Recon DL improves signal robustness and image consistency, reducing the likelihood of repeat imaging. Motion‑robust imaging applications including 3D PROMO, Propeller, LAVA STAR and DISCO STAR, paired with acceleration technologies, and ergonomic system design further support reliable exam completion.
Predictability protects capacity.
Recovering capacity through cumulative gains
When variability is reduced, capacity recovery does not occur as a single step change, but as a series of small, compounding improvements.
Fewer repeat scans, more consistent exam durations, and improved patient tolerance gradually return minutes to each operating list. Individually, these gains may appear marginal. Over time, across full operating days and full operating years, they accumulate into measurable increases in completed examinations per scanner.⁴
Technologies that improve signal robustness, motion tolerance, and patient comfort help stabilise performance across varied clinical workloads, reducing the likelihood of reacquisition and unplanned list overruns.
In constrained systems, these cumulative gains represent one of the most practical pathways to expanding access without increasing scanner or workforce footprint.
Infrastructure performance and capacity ceilings
Many MRI systems operating across ANZ continue to deliver high diagnostic quality but are approaching or beyond mid‑life. Earlier generation platforms may operate with slower reconstruction, lower gradient performance, or less integrated workflow design.
Over time, these incremental limitations accumulate. Across full operating lists and full years, they translate into fewer completed examinations.
Modern MRI platforms are designed to reduce workflow friction and stabilise performance across a wide range of clinical applications. High‑performance gradient systems available on platforms such as SIGNA™ Hero 3.0T, SIGNA™ Premier 3.0T, SIGNA™ Voyager 1.5T, and SIGNA Champion support fast, consistent imaging while maintaining diagnostic standards.
Importantly, capacity recovery does not rely solely on system replacement. Software and hardware upgrades to existing MRI platforms can also play a meaningful role in improving performance, reconstruction speed, and workflow consistency.
From backlog management to capacity stability
In healthcare systems where scanner density remains constrained, improving throughput per existing scanner becomes a critical lever.
By reducing variability, stabilising workflows, and improving patient experience, MRI departments can expand effective capacity without compromising diagnostic quality — supporting patient access, workforce sustainability, and long‑term system resilience.
Sources
Footnotes
- Australian Institute of Health and Welfare (AIHW). Pathology, imaging and other diagnostic services 2022–23.
- Organisation for Economic Co‑operation and Development (OECD). Health at a Glance: Diagnostic technologies.
- Jeganathan S. The growing problem of radiologist shortages: Australia and New Zealand’s perspective. Korean Journal of Radiology, 2023.
- Zaitsev M, Maclaren J, Herbst M. Motion artifacts in MRI: A complex problem with many partial solutions. Journal of Magnetic Resonance Imaging, 2015.
- Sommer K et al. Correction of motion artifacts using deep learning. American Journal of Neuroradiology, 2020.
The information on this website is aimed exclusively at Licensed Healthcare Practitioners.
