Deep Learning to Increase Accessibility, Ease of Heart Imaging

Coronary artery disease is the leading cause of death globally. One of the most common tools used to diagnose and monitor heart disease, myocardial perfusion imaging (MPI) by single photon emission computed tomography (SPECT), uses a radioactive tracer and special camera to provide detailed images of blood flow to the heart, helping doctors detect coronary artery disease and other cardiovascular abnormalities. However, traditional SPECT imaging requires an additional CT scan to ensure accurate results, exposing patients to more radiation and increasing costs.

A new deep learning technique developed by researchers at Washington University in St. Louis with collaborators from Cleveland Clinic and University of California Santa Barbara could transform the way heart health is monitored, making it safer and more accessible.

The method, known as CTLESS, leverages deep learning to remove the CT requirement without compromising diagnostic accuracy. The project, led by Abhinav Jha, associate professor of biomedical engineering in the McKelvey School of Engineering and of radiology at WashU Medicine Mallinckrodt institute of Radiology, was published online Nov. 25 in IEEE Transactions in Medical Imaging.

The next stage of research is for them to validate this method while working to make this tech more available to rural community hospitals. Their cost-saving technique is particularly significant for cases where access to such scans may be limited, such as in rural or otherwise resource-limited communities, said Jha.

SPECT imaging requires an additional CT scan for attenuation compensation (AC), which corrects for how the emitted signal weakens, or attenuates, as it moves through body tissue, potentially obscuring heart images and leading to diagnostic inaccuracies. Such CT scans are typically acquired on a SPECT/CT scanner, but many facilities do not have this CT component.

"Due to cost, complexity, equipment availability, regulatory concerns and other local factors at hospitals and remote care centers, approximately 75% of all SPECT MPI scans are performed without AC, potentially compromising the diagnostic accuracy of these scans," Jha said. “By integrating concepts in physics and deep learning, the proposed CTLESS method estimates a synthetic attenuation map that is then used for AC. Thus, CTLESS may enable a mechanism where an additional scan may not be required.”

CTLESS uses photons from the emission scan to estimate attenuation, which can then be used to enhance image quality and improve diagnostic interpretation. Jha and his collaborators evaluated the performance of CTLESS using real-world clinical data and found that their method showed comparable results to traditional attenuation compensation.

Notably, CTLESS demonstrated robust performance across different scanner models, degrees of heart damage and patient demographics. Jha noted that anatomical differences between men and women result in varying levels of attenuation in these groups and confirmed that the CTLESS method yields similar performance as traditional AC for both sexes. The performance of CTLESS was also relatively stable even as the size of the training data was reduced. All these observations make CTLESS a promising option for widespread clinical adoption following additional validation.

“Our results provide promise that in the future, a separate CT scan may not be required for performing attenuation correction in MPI SPECT. This is particularly significant for cases where access to such scans may be limited, such as in rural or otherwise resource-limited communities,” Jha said. “By providing the ability to perform AC without requiring a CT, the proposed CTLESS method may help boost technological health equality across the U.S. and worldwide.”

Yu Z, Rahman MA, Abbey CK, Laforest R, Siegel BA, Jha A.
CTLESS: A scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT.
IEEE Transactions in Medical Imaging, Nov. 25, 2024, doi: 10.1109/TMI.2024.3496870

Most Popular Now

Stepping Hill Hospital Announced as SPAR…

Stepping Hill Hospital, part of Stockport NHS Foundation Trust, has replaced its bedside units with state-of-the art devices running a full range of information, engagement, communications and productivity apps, to...

DMEA 2025: Digital Health Worldwide in B…

8 - 10 April 2025, Berlin, Germany. From the AI Act, to the potential of the European Health Data Space, to the power of patient data in Scandinavia - DMEA 2025...

Is AI in Medicine Playing Fair?

As artificial intelligence (AI) rapidly integrates into health care, a new study by researchers at the Icahn School of Medicine at Mount Sinai reveals that all generative AI models may...

Generative AI's Diagnostic Capabili…

The use of generative AI for diagnostics has attracted attention in the medical field and many research papers have been published on this topic. However, because the evaluation criteria were...

New System for the Early Detection of Au…

A team from the Human-Tech Institute-Universitat Politècnica de València has developed a new system for the early detection of Autism Spectrum Disorder (ASD) using virtual reality and artificial intelligence. The...

Diagnoses and Treatment Recommendations …

A new study led by Prof. Dan Zeltzer, a digital health expert from the Berglas School of Economics at Tel Aviv University, compared the quality of diagnostic and treatment recommendations...

AI Tool can Track Effectiveness of Multi…

A new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS) has been developed by UCL researchers. AI uses...

Surrey and Sussex Healthcare NHS Trust g…

Surrey and Sussex Healthcare NHS Trust has marked an important milestone in connecting busy radiologists across large parts of South East England, following the successful go live of Sectra's enterprise...

DMEA 2025 Ends with Record Attendance an…

8 - 10 April 2025, Berlin, Germany. DMEA 2025 came to a successful close with record attendance and an impressive program. 20,500 participants attended Europe's leading digital health event over the...

Dr Jason Broch Joins the Highland Market…

The Highland Marketing advisory board has welcomed a new member - Dr Jason Broch, a GP and director with a strong track record in the NHS and IT-enabled transformation. Dr Broch...

AI-Driven Smart Devices to Transform Hea…

AI-powered, internet-connected medical devices have the potential to revolutionise healthcare by enabling early disease detection, real-time patient monitoring, and personalised treatments, a new study suggests. They are already saving lives...

Multi-Resistance in Bacteria Predicted b…

An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically...