Soft X-Ray Tomography 3D Scans Show How Cells Respond to SARS-CoV-2 Infection and to Possible Treatments
By MedImaging International staff writers Posted on 28 Feb 2022 |

An extremely fast new 3D imaging method can show how cells respond to SARS-CoV-2 infection and to possible treatments.
Researchers from Berkeley Lab (Berkeley, CA, USA) and Heidelberg University (Heidelberg, Germany) have cranked up the speed of imaging infected cells using soft X-ray tomography (SXT), a microscopic imaging technique that can generate incredibly detailed, three-dimensional scans. Their approach takes mere minutes to gather data that would require weeks of prep and analysis with other methods, giving scientists an easy way to quickly examine how our cells’ internal machinery responds to SARS-CoV-2, or other pathogens, as well as how the cells respond to drugs designed to treat the infection.
SXT was developed at Berkeley Lab in the early 2000s to fill in the gaps left by other cellular imaging techniques and is currently offered to investigators worldwide even as the researchers continue to refine the approach. As part of a study, the researchers performed SXT on human lung cell samples. The team carefully infected the cells with SARS-CoV-2 and then chemically fixed them with aldehyde-based compounds – a process that kills cells and preserves them, immobilized, in their last living state (and also inactivates any remaining viral particles) – at six and 24 hours post-infection.
The entire team was jubilant when the resulting 3D images had the same level of exquisite detail and clarity that SXT is known for, despite the chemical fixation done to the cells. The takeaway is that their approach will allow many labs to safely image infected cells without the inherent risks – and corresponding required safety protocols – of working with live infected cells. Upon conducting the tomography sessions and image analysis, the researchers were pleasantly surprised to see how SXT captured changes to different organelles within the lung cells at very high resolution after very little time spent on sample preparation and without use of stains or labeling. These additional steps are often needed to generate cell maps wherein the different internal components are easily distinguishable.
Now that they’ve demonstrated the potential of using whole-cell SXT to safely image virus-infected cells, the researchers believe that their findings will help the global scientific community study COVID-19 and potentially other diseases. The team is already putting the technique to good use and has begun using whole-cell SXT to examine how human cells respond to several experimental COVID-19-treating drugs. They hope the rapid turnaround for results will help expedite the drug development process, getting additional effective treatments on the market sooner. They also plan to use the technology to understand the progress of infections caused by other viral agents.
“Prior to our imaging technique, if one wanted to know what was going on inside a cell, and to learn what changes had occurred upon an infection, they'd have to go through the process of fixing, slicing, and staining the cells in order to analyze them by electron microscopy. With all the steps involved, it would take weeks to get the answer. We can do it in a day,” said project co-lead Carolyn Larabell, a Berkeley Lab faculty scientist in the Biosciences Area. “So, it really speeds up the process of examining cells, the consequences to infection, and the consequences of treating a patient with a drug that may or may not cure or prevent the disease.”
Related Links:
Berkeley Lab
Heidelberg University
Latest Radiography News
- World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
- AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
- Higher Chest X-Ray Usage Catches Lung Cancer Earlier and Improves Survival
- AI-Powered Mammograms Predict Cardiovascular Risk
- Generative AI Model Significantly Reduces Chest X-Ray Reading Time
- AI-Powered Mammography Screening Boosts Cancer Detection in Single-Reader Settings
- Photon Counting Detectors Promise Fast Color X-Ray Images
- AI Can Flag Mammograms for Supplemental MRI
- 3D CT Imaging from Single X-Ray Projection Reduces Radiation Exposure
- AI Method Accurately Predicts Breast Cancer Risk by Analyzing Multiple Mammograms
- Printable Organic X-Ray Sensors Could Transform Treatment for Cancer Patients
- Highly Sensitive, Foldable Detector to Make X-Rays Safer
- Novel Breast Cancer Screening Technology Could Offer Superior Alternative to Mammogram
- Artificial Intelligence Accurately Predicts Breast Cancer Years Before Diagnosis
- AI-Powered Chest X-Ray Detects Pulmonary Nodules Three Years Before Lung Cancer Symptoms
- AI Model Identifies Vertebral Compression Fractures in Chest Radiographs
Channels
Radiography
view channel
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 more
AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
Percutaneous coronary intervention (PCI), also known as coronary angioplasty, is a minimally invasive procedure where small metal tubes called stents are inserted into partially blocked coronary arteries... Read moreMRI
view channel
AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
Multiple sclerosis (MS) is a condition in which the immune system attacks the brain and spinal cord, leading to impairments in movement, sensation, and cognition. Magnetic Resonance Imaging (MRI) markers... Read more
Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read more
AI-Powered MRI Technology Improves Parkinson’s Diagnoses
Current research shows that the accuracy of diagnosing Parkinson’s disease typically ranges from 55% to 78% within the first five years of assessment. This is partly due to the similarities shared by Parkinson’s... Read more
Biparametric MRI Combined with AI Enhances Detection of Clinically Significant Prostate Cancer
Artificial intelligence (AI) technologies are transforming the way medical images are analyzed, offering unprecedented capabilities in quantitatively extracting features that go beyond traditional visual... Read moreUltrasound
view channel
AI Identifies Heart Valve Disease from Common Imaging Test
Tricuspid regurgitation is a condition where the heart's tricuspid valve does not close completely during contraction, leading to backward blood flow, which can result in heart failure. A new artificial... Read more
Novel Imaging Method Enables Early Diagnosis and Treatment Monitoring of Type 2 Diabetes
Type 2 diabetes is recognized as an autoimmune inflammatory disease, where chronic inflammation leads to alterations in pancreatic islet microvasculature, a key factor in β-cell dysfunction.... Read moreNuclear Medicine
view channel
Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
COX-2, an enzyme that plays a key role in brain inflammation, can be significantly upregulated by inflammatory stimuli and neuroexcitation. Researchers suggest that COX-2 density in the brain could serve... Read more
Novel Radiotracer Identifies Biomarker for Triple-Negative Breast Cancer
Triple-negative breast cancer (TNBC), which represents 15-20% of all breast cancer cases, is one of the most aggressive subtypes, with a five-year survival rate of about 40%. Due to its significant heterogeneity... Read moreGeneral/Advanced Imaging
view channel
AI-Powered Imaging System Improves Lung Cancer Diagnosis
Given the need to detect lung cancer at earlier stages, there is an increasing need for a definitive diagnostic pathway for patients with suspicious pulmonary nodules. However, obtaining tissue samples... Read more
AI Model Significantly Enhances Low-Dose CT Capabilities
Lung cancer remains one of the most challenging diseases, making early diagnosis vital for effective treatment. Fortunately, advancements in artificial intelligence (AI) are revolutionizing lung cancer... 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