Recent Developments in X-ray Imaging Techniques

X-ray imaging has significantly evolved since its 1895 invention. Nowadays, this technology can quickly provide healthcare providers with the information they need to make the best recommendations for you. What new X-ray imaging techniques are emerging in life sciences? Researchers are wielding advanced technologies to achieve better results. Here’s what you need to know about modern X-rays.

Why New X-ray Imaging Techniques Are Important

When you visit a doctor’s office, you hope for the most accurate results possible in testing. These checkups examine your body for cancer and other diseases to ensure you have a clean bill of health. If you need an examination, the healthcare provider could for an X-ray.

X-rays expose your body to radiation because it needs to pass through your body. While radiation exposure can be concerning, it’s necessary to view your soft tissues. If you can’t handle radiation, you may need low doses to keep your body healthy.

These instances show why the life sciences benefit from emerging X-ray imaging techniques. New technologies have demonstrated better accuracy with lower radiation doses. With innovative techniques, you get better results and treatment plans for long-term care. Some take advantage of advanced technologies to deliver quicker results.

8 Emerging X-ray Imaging Techniques

X-ray technology has rapidly grown as researchers continue innovating and experimenting with new ideas. What emerging X-ray techniques should you pay close attention to? Here are the top eight affecting the life sciences.

1. Field Portable X-ray

You typically have to go to a medical center to get an X-ray. However, technology has evolved to bring these scans to you. Portable X-ray machines are among the critical new imaging techniques because you can carry them to a patient’s bed if they have mobility issues.

Additionally, portable X-rays are helpful outside hospitals because you can use them in a patient’s residence. Imagine bringing them to a nursing home or their house and providing easier access to an X-ray diagnosis. With increased portability, the future of these imaging techniques is bright.

Case Study

One example in life science is field portable X-ray fluorescence spectroscopy (FP-XRF). This tool has become prominent because it is quicker and less destructive than other X-ray techniques. Some say FP-XRF is controversial because it incorporates computational algorithms, thus making it semi-quantitative.

A 2023 TrAC Trends in Analytical Chemistry study examined FP-XRF in forensic analysis to determine its effectiveness. The researchers found the new technology cost-effective and critical to situ analysis. What does it mean for the future? With further development, FP-XRF will be integral to forensic sciences.¹

2. AI-powered X-ray

The role of artificial intelligence (AI) has rapidly increased because it aids in personalized medicine, drug discovery, and other critical innovations. AI has also seen increased responsibility in life sciences as researchers leverage it for emerging X-ray techniques. This technology can process quickly and generate more accurate diagnostics.

While it likely won’t replace healthcare providers, AI can work with physicians to improve X-ray technology. These intelligent systems process large amounts of historical data to find abnormalities. Medical professionals may overlook the images, so it’s essential to have AI by your side to recognize patterns.

Case Study

AI is one of the most vital new X-ray techniques because of its ability to detect bias. If bias occurs, your healthcare provider could misinterpret the diagnosis. Therefore, you could miss the treatment you need for your condition. AI lets you remove the potential human biases and gain a clearer picture.

A 2022 International Journal of Network Dynamics and Intelligence study investigated AI’s impact on X-ray imaging and biases. The researchers acknowledged AI’s neural networks have challenges, though efficient models can benefit healthcare providers and patients. The results demonstrated 15% more accuracy with AI applications.²

3. Deep Learning Imaging

AI’s role in X-ray techniques extends to deep learning and cancer imaging. This advanced technology is an excellent imaging tool because it heightens objectivity and accuracy. Recently, deep learning has become more valuable when searching for breast cancer, one of the most prevalent diseases in women.

Traditional methods — such as mammograms — detect and diagnose breast abnormalities using X-ray technology. Since the early 20th century, other techniques have emerged as formidable solutions for cancer detection. For example, your healthcare provider could recommend tomosynthesis or nuclear medicine imaging because of deep learning.³

Case Study

The available breast cancer imaging techniques allow healthcare providers to leverage deep learning technology. How can you incorporate this AI subsection into your mammograms? Deep learning assists with reconstructing images and predicting the risk of cancer. Experts say breast cancer is second only to lung cancer in causing female fatalities.⁴

A 2022 Seminars in Nuclear Medicine study explored the various applications of deep learning in breast cancer imaging. The researchers said deep learning has improved accuracy in lesion classification and segmentation. A key finding was that deep learning algorithms matched and exceeded radiologists, proving this AI technology is here to stay.⁵

4. Improving DEXA Efficiency

Bone density is critical, especially as you age. Older adults tend to lose density and muscle mass, so your healthcare provider may recommend dual-energy X-ray absorptiometry (DEXA). DEXA gives a clearer picture of your body composition and what treatment you need in the future.

DEXA’s role in patient care is to detect osteoporosis in your bones. While the process is effective, this technology has improved because of advanced scanners. Contemporary devices have better image quality and allow healthcare providers to diagnose bone issues accurately.

Case Study

DEXA is another place where you can see AI’s impact. This technology has helped older adults combat sarcopenia, the loss of muscle and strength with aging. However, this radiological examination can be expensive and complicated for seniors and healthcare providers. AI could be the next big thing in DEXA technology.

A 2023 Heliyon study examined an inexpensive screening tool to build on DEXA. The team wanted to aid in early sarcopenia diagnoses for patients with muscle mass loss. Researchers found the new AI models are less complicated and more accurate, suggesting these X-ray techniques are a financially feasible alternative.⁶

5. Deep Learning in Digital Radiography

When treating cancer, you need high amounts of radiation to kill these cells. This treatment lets you stop division and damage the DNA, thus mitigating the spread. However, you may need lower doses of radiation because it can harm your existing healthy tissues.

If you need less radiation, digital radiography could be an excellent approach. This technology has heightened sensitivity to radiation, thus requiring less of it to generate imagery. Your average X-ray machine has a film base and necessitates more radiation for the patients.

Case Study

Digital radiography makes X-rays easier for healthcare providers and patients. How has the technology become more accessible? Deep learning has improved digital radiography by X-ray images and helping radiologists identify abnormalities. This advantage is critical when observing fresh vertebral compression fractures (VCF).

A 2022 European Radiology study developed a deep learning model to identify fresh VCFs from digital radiography. The researchers wanted to compare it to magnetic resonance imaging (MRI) to distinguish the two techniques. Nearly 1100 patients participated, and the study concluded the deep learning model effectively diagnosed VCF.⁷

6. Cone-beam Computed Tomography

Cone-beam computed tomography (CBCT) is another technology for low doses of radiation. This innovation is prominent among dental practices, providing 3D imagery of your teeth and jaw structure. X-rays are standard practice during patient checkups, so you may have seen this treatment at a recent visit.

CBCT is a relatively new technology, so its uses evolve annually. Dental professionals first used computed tomography in the 1980s to treat inflammation and tumors, and the 1990s made it more efficient with the cone beam. Recent innovations have made CBCT more effective and less time-consuming with reduced radiation.⁸

Case Study

A 2023 Parker University study analyzed computed tomography applications to distinguish them from planar X-ray beam, flat, and curve receivers. The researchers wanted to see how computed tomography had evolved and found that larger capture devices for X-rays were significant.

This advancement lets you use lower-dose cone beams while improving image clarity. The researchers said CBCT was preferable in chiropractic practices because it lowers the radiation exposure without compromising the image quality. Therefore, CBCT has advantages over traditional multidetector CT and other practices.⁹

7. Synchrotron X-ray Imaging

Synchrotron X-ray imaging has emerged as one of contemporary science’s most powerful new techniques. This technology is integral to X-rays because it lets you examine specimens at the molecular level. Archaeologists use synchrotron X-ray imaging to examine fossils and inspect their internal contents.

One drawback of synchrotron X-ray imaging is its cost. Expensive investments are necessary to see its applications in clinics and laboratories. However, some advancements have made the future brighter with emerging X-ray imaging techniques. Affordable and efficient imaging increases healthcare access to more people who need it.

Case Study

A 2022 Applied Sciences study explored the technology’s applications while evaluating the latest applications. The researchers highlighted the potential of machine and deep learning methods to produce synthetic images. Therefore, the possibility of advanced neural networks could benefit healthcare providers and patients.¹⁰

The study focused on a photon-counting detector (PCD) because it is one of the new X-ray imaging techniques. This technology enhanced the signal-to-noise ratio in synchrotron radiation and improved the soft tissue contrast. The researchers found combining these strategies makes synchrotron X-ray imaging more cost-effective and affordable while generating high-resolution images.¹⁰

8. X-Ray Microscopy

X-ray microscopy lets you see magnified images of an object and improves vision over visible light. The technology wields X-ray penetration to shorten the wavelengths and penetrate the specimen in view, thus making life easier for life science professionals.

With this technology, you can easily view the internal composition of tiny objects and animals. For example, you may use X-ray microscopy to examine the anatomy of an insect. Recent developments have elevated X-ray microscopes to make them more efficient alongside supercomputers.

Recent Innovation

The Argonne National Laboratory in Lemont, Illinois, has leveraged machine learning (ML) to improve X-ray microscopy techniques. Their innovation uses neural networks to reduce the sampling time and increase the amount of data retrieved. How much has it improved? Researchers say the data processed is 100 times faster.¹¹

“The new neural network means that we can run many of these experiments in a few minutes at the full speed of the instrument,” said Argonne group leader and computational scientist Mathew Cherukara, an author of the study. The team would need days or weeks to process without the neural network.¹¹

Finding the New X-ray Imaging Techniques

X-ray technology has been pivotal for medical and life sciences for over 125 years. Emerging imaging techniques help healthcare providers obtain better X-ray diagnostics for patients. Life science researchers wield AI and other powerful technologies to continue improvement and pinpoint patient issues.

Sources:

1. Kobylarz, D., et al. Field portable X-ray fluorescence (FP-XRF) as powerful, rapid, non-destructive and ‘white analytical tool’ for forensic sciences - State of the art. TrAC Trends in Analytical Chemistry 2023;169. https://doi.org/10.1016/j.trac.2023.117355
2. Kwasniewska, A., Szankin, M. Can AI See Bias in X-ray images? International Journal of Network Dynamics and Intelligence 2022;1(1):48-64. https://doi.org/10.53941/ijndi0101005
3. Clear Connect Medical Imaging. Penetrative Imaging Explained.
4. American Cancer Society. Key Statistics for Breast Cancer.
5. Balkenende, L., et al. Application of Deep Learning in Breast Cancer Imaging. Seminars in Nuclear Medicine 2022;52(5):584-596.  https://doi.org/10.1053/j.semnuclmed.2022.02.003
6. Buccheri, E., et al. Can artificial intelligence simplify the screening of muscle mass loss? Heliyon 2023;9(5).  https://doi.org/10.1016/j.heliyon.2023.e16323
7. Chen, W., et al. A deep-learning model for identifying fresh vertebral compression fractures on digital radiography. European Radiology 2021;32:1496-1505. https://doi.org/10.1007/s00330-021-08247-4
8. Bromberg, N., Brizuela, M. Dental Cone Beam Computed Tomography. StatPearls.
9. Scholten, J., et al. Cone Beam Computed Tomography: Technology Overview, Dose, and Utility Considerations for Chiropractors and Regulatory Bodies. JCC 2023;6(1):92-99.
10. Tamal, M., et al. Synchrotron X-ray Radiation (SXR) in Medical Imaging: Current Status and Future Prospects. Applied Sciences 2022;12(8):3790. https://doi.org/10.3390/app12083790
11. Argonne National Laboratory. Scientists pioneer new X-ray microscopy method for data analysis ​“on the fly”.