Super-Resolution PET Technique Enhances Brain Imaging
By MedImaging International staff writers Posted on 08 Jul 2021 |

Image: The same Hoffman phantom PET slice reconstructed with different imaging techniques (Photo courtesy of Gordon Center for Medical Imaging)
A new study shows how combining position emission tomography (PET) with an external head-motion tracking device can create highly detailed images of the brain.
Researchers at Institut Polytechnique de Paris (France), Massachusetts General Hospital (MGH; Boston, USA), and other institutions conducted a study that aimed to use super-resolution (SR) to improve PET image resolution by exploiting spatial sampling information obtained from multiple acquisitions of the same object. To do so, they used the high-resolution infra-red (IR) Polaris Vega tracking camera, which has a tracking accuracy of up to 0.12 mm isotropic and a 60 Hz frame rate.
A transformation linking the Polaris and scanner coordinates space to the same reference object, using squares minimization, was then used to spatially align the two instruments. To enable SR, a PET reconstruction algorithm was developed that incorporated the high-resolution tracking data from the Polaris Vega to correct motion for measured line of responses (LORs) on an event-by-event basis. Simulation models were then conducted using a Hoffman phantom and a rhesus monkey.
The results showed that for both Hoffman phantom and primate studies, SR reconstruction yielded PET images with visibly increased spatial resolution, allowing for improved visualization of small cortical and subcortical brain phantom structures. Overall, the SR method achieved better noise control than the static reconstruction with the same voxel size. For the Hoffman phantom, the SR images showed improved correspondence with the high-resolution CT, compared to conventional methods. The study was presented at the Society of Nuclear Medicine and Molecular Imaging virtual annual meeting, held during June 2021.
“This work shows that one can obtain PET images with a resolution that outperforms the scanner's resolution by making use, counterintuitively perhaps, of usually undesired patient motion,” said Yanis Chemli, MSc, PhD, of the MGH Gordon Center for Medical Imaging. “Our technique not only compensates for the negative effects of head motion on PET image quality, but it also leverages the increased sampling information associated with imaging of moving targets to enhance the effective PET resolution.”
PET is a nuclear medicine imaging technique that produces a 3D image of functional processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide tracer. Tracer concentrations within the body are then constructed in 3D by computer analysis. In more modern PET-CT scanners, 3D imaging is often accomplished with the aid of a CT X-ray scan performed on the patient during the same session, in the same machine.
Related Links:
Institut Polytechnique de Paris
Massachusetts General Hospital
Researchers at Institut Polytechnique de Paris (France), Massachusetts General Hospital (MGH; Boston, USA), and other institutions conducted a study that aimed to use super-resolution (SR) to improve PET image resolution by exploiting spatial sampling information obtained from multiple acquisitions of the same object. To do so, they used the high-resolution infra-red (IR) Polaris Vega tracking camera, which has a tracking accuracy of up to 0.12 mm isotropic and a 60 Hz frame rate.
A transformation linking the Polaris and scanner coordinates space to the same reference object, using squares minimization, was then used to spatially align the two instruments. To enable SR, a PET reconstruction algorithm was developed that incorporated the high-resolution tracking data from the Polaris Vega to correct motion for measured line of responses (LORs) on an event-by-event basis. Simulation models were then conducted using a Hoffman phantom and a rhesus monkey.
The results showed that for both Hoffman phantom and primate studies, SR reconstruction yielded PET images with visibly increased spatial resolution, allowing for improved visualization of small cortical and subcortical brain phantom structures. Overall, the SR method achieved better noise control than the static reconstruction with the same voxel size. For the Hoffman phantom, the SR images showed improved correspondence with the high-resolution CT, compared to conventional methods. The study was presented at the Society of Nuclear Medicine and Molecular Imaging virtual annual meeting, held during June 2021.
“This work shows that one can obtain PET images with a resolution that outperforms the scanner's resolution by making use, counterintuitively perhaps, of usually undesired patient motion,” said Yanis Chemli, MSc, PhD, of the MGH Gordon Center for Medical Imaging. “Our technique not only compensates for the negative effects of head motion on PET image quality, but it also leverages the increased sampling information associated with imaging of moving targets to enhance the effective PET resolution.”
PET is a nuclear medicine imaging technique that produces a 3D image of functional processes in the body. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide tracer. Tracer concentrations within the body are then constructed in 3D by computer analysis. In more modern PET-CT scanners, 3D imaging is often accomplished with the aid of a CT X-ray scan performed on the patient during the same session, in the same machine.
Related Links:
Institut Polytechnique de Paris
Massachusetts General Hospital
Latest General/Advanced Imaging News
- CT Colonography Beats Stool DNA Testing for Colon Cancer Screening
- First-Of-Its-Kind Wearable Device Offers Revolutionary Alternative to CT Scans
- AI-Based CT Scan Analysis Predicts Early-Stage Kidney Damage Due to Cancer Treatments
- CT-Based Deep Learning-Driven Tool to Enhance Liver Cancer Diagnosis
- AI-Powered Imaging System Improves Lung Cancer Diagnosis
- AI Model Significantly Enhances Low-Dose CT Capabilities
- Ultra-Low Dose CT Aids Pneumonia Diagnosis in Immunocompromised Patients
- AI Reduces CT Lung Cancer Screening Workload by Almost 80%
- Cutting-Edge Technology Combines Light and Sound for Real-Time Stroke Monitoring
- AI System Detects Subtle Changes in Series of Medical Images Over Time
- New CT Scan Technique to Improve Prognosis and Treatments for Head and Neck Cancers
- World’s First Mobile Whole-Body CT Scanner to Provide Diagnostics at POC
- Comprehensive CT Scans Could Identify Atherosclerosis Among Lung Cancer Patients
- AI Improves Detection of Colorectal Cancer on Routine Abdominopelvic CT Scans
- Super-Resolution Technology Enhances Clinical Bone Imaging to Predict Osteoporotic Fracture Risk
- AI-Powered Abdomen Map Enables Early Cancer Detection
Channels
Radiography
view channel
AI Radiology Tool Identifies Life-Threatening Conditions in Milliseconds
Radiology is emerging as one of healthcare’s most pressing bottlenecks. By 2033, the U.S. could face a shortage of up to 42,000 radiologists, even as imaging volumes grow by 5% annually.... Read more
Machine Learning Algorithm Identifies Cardiovascular Risk from Routine Bone Density Scans
A new study published in the Journal of Bone and Mineral Research reveals that an automated machine learning program can predict the risk of cardiovascular events and falls or fractures by analyzing bone... Read more
AI Improves Early Detection of Interval Breast Cancers
Interval breast cancers, which occur between routine screenings, are easier to treat when detected earlier. Early detection can reduce the need for aggressive treatments and improve the chances of better outcomes.... Read more
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read moreMRI
view channel
New MRI Technique Reveals Hidden Heart Issues
Traditional exercise stress tests conducted within an MRI machine require patients to lie flat, a position that artificially improves heart function by increasing stroke volume due to gravity-driven blood... Read more
Shorter MRI Exam Effectively Detects Cancer in Dense Breasts
Women with extremely dense breasts face a higher risk of missed breast cancer diagnoses, as dense glandular and fibrous tissue can obscure tumors on mammograms. While breast MRI is recommended for supplemental... Read moreUltrasound
view channel
New Medical Ultrasound Imaging Technique Enables ICU Bedside Monitoring
Ultrasound computed tomography (USCT) presents a safer alternative to imaging techniques like X-ray computed tomography (commonly known as CT or “CAT” scans) because it does not produce ionizing radiation.... Read more
New Incision-Free Technique Halts Growth of Debilitating Brain Lesions
Cerebral cavernous malformations (CCMs), also known as cavernomas, are abnormal clusters of blood vessels that can grow in the brain, spinal cord, or other parts of the body. While most cases remain asymptomatic,... Read moreNuclear Medicine
view channel
New Imaging Approach Could Reduce Need for Biopsies to Monitor Prostate Cancer
Prostate cancer is the second leading cause of cancer-related death among men in the United States. However, the majority of older men diagnosed with prostate cancer have slow-growing, low-risk forms of... Read more
Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more