The bore of a magnetic resonance imaging (MRI) machine can be intimidating. The claustrophobic atmosphere, paired with knocking sounds that are sometimes louder than an aircraft flyover, can frighten even those comfortable with medical procedures. Children are especially susceptible to these fears, and as a result, MR scanning failure rates can be as high as 50% in young children.

MR technicians employ many simple methods to distract patients during imaging, including audiovisual systems, which they can also use to stimulate brain activity for functional MRI scanning. However, these techniques fail to remove the sensation of entering the MRI bore or assuage the jarring sensations that arise during its function. A research team centred at King’s College London envisioned a technology that would immerse patients in a game environment, distracting them and even replacing the sensations of being inside an MRI machine. The team, led by MRI specialists Kun Qian, Tomoki Arichi and Jo Hajnal, published the study findings in Scientific Reports.

The group investigated a virtual reality (VR) system that replaces the visual scene seen by a patient with immersive and tailored content, in an attempt to alleviate claustrophobia and allow more effective scanning of vulnerable groups like children. The system consists of a 3D-printed headset, a projector and multiple MRI-compatible cameras used to record the patient’s eye movements. The cameras allow the subject to control a VR environment using gaze tracking.

The gaze tracking system acts as the crux of the VR system, as it allows immersive control of the environment without bodily movement. First, the cameras obtain images of the patient’s eyes and surrounding areas. A computer then identifies the coordinates of the eye corners and pupils on these images and feeds this information into a progressive interaction interface. The patient then calibrates the system by gazing at dots on the screen. Their gaze coordinates at these times are fed into a regression model, which is constantly updated, improving robustness as they interact with the scene.

Participants reported more attention diversion when playing the video game than they did while watching a film, and no subjects required selection support from carers while exploring the system.

The researchers note that maintaining congruence with external physical stimuli was especially important to the subject’s immersion experience. Therefore, in addition to standard audio-visual stimuli from the VR system, the system integrated external stimuli into its storyline and function. For example, the system integrates the loud knocking and vibration of the MRI scanner by introducing construction characters into the scene, whose tools would be likely to cause said disturbances. If the subject gazes at these characters, they apologize for causing the disruption.

Further, to fully immerse the user in the virtual environment from the start, the system synchronizes the environment with the movement of the patient table sliding into the bore. In this way, subjects of the study noted that they were left without the impression of even having entered the scanner bore.

This technology demonstrates the potential to act as an immersive, engaging escape for patients requiring MRI scans. The researchers call for more in-depth testing of the VR system, especially for integration of full MRI exams and systematic studies with children.

Detecting a brain tumour at the earliest possible stage enables faster treatment and safer surgery, which are essential to improve the patient’s chance of a good clinical outcome. But brain tumour diagnosis is a difficult task, as common symptoms such as headaches or memory change are not specific to cancer. As such, many tumours remain undetected until they are larger or of a higher grade. A research team in the UK has now demonstrated that spectroscopic liquid biopsy can detect both small and low-grade gliomas – and could increase the likelihood of early diagnosis.

Liquid biopsies are a minimally invasive diagnostic tool in which small samples of blood are analysed. For cancer diagnostics, most liquid biopsies detect genetic material such as circulating DNA. But early-stage tumours can have extremely low levels of cancerous genetic material in the blood, and for brain tumours, the blood–brain barrier creates further limitations.

The researchers are developing an alternative approach. Instead of detecting specific genetic material, they analyse the molecular composition of a blood sample using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy combined with machine learning algorithms.

“The spectroscopy is used as a broad assessment of the entire composition of the blood sample, which contains over 20,000 molecules,” explains first author Ashton Theakstone from the University of Strathclyde.

Serum sample studies

In their latest study, described in Cancers, Theakstone and colleagues examined 177 blood serum samples from patients with varying sizes of brain tumours, including 90 patients with high- and low-grade gliomas, as well as 87 asymptomatic controls. They measured the tumour volumes using MR imaging and divided the patients were into two groups depending on their MRI parameters (T1-weighted with contrast enhancement, or T2-weighted/FLAIR).

The researchers performed the liquid biopsies by depositing 3 µl of each patient’s serum onto an optical sample slide and collecting nine spectra per patient, which typically took 15 minutes. They collected spectra in the wavenumber range 4000–450 cm^-1, with spectral analysis focused on the fingerprint region (1800–1000 cm⁻¹).

The team first used principal component analysis (PCA) to examine spectra from the T1 group, all of whom had grade IV glioblastoma tumours, and from control patients. PCA provides clear visualization of any variation between these datasets and identifies important wavenumber regions within the spectral data. The analysis revealed a distinction between tumours and controls, which the researchers used to determine the wavenumber bands responsible for this separation.

“Any variances within particular wavenumber regions correspond to certain functional groups that are known within the literature,” Theakstone explains. “For example, the region between roughly 1700 to 1500 cm^-1 corresponds to the amide I and amide II of proteins, therefore variances within this region relate to fluctuations in protein content within the blood.”

Cancer classification

Next, the team examined the ability of three classification models (random forest, partial least squares-discriminant analysis (PLS-DA) and support vector machine) to differentiate these high-grade tumours from controls. For each model, the data were split into a training set, used to identify biosignatures, and a test set.

The PLS-DA model had the greatest predictive ability, with a sensitivity of 98.5%, specificity of 95.1% and balanced accuracy of 96.8%. The team repeated this process with the T2/FLAIR group, which included mostly low-grade (grade II) tumours and some grade III tumours. Again, PLS-DA performed the best in differentiating tumours from controls, with a sensitivity of 88.7%, specificity of 94.7% and balanced accuracy of 91.7%.

To minimize sensitivity and specificity errors whilst also minimizing analysis time, the researchers repeated each classification 51 times. They note that the first iteration for each classification model gave correct predictions for all patients within the T1 cohort and the majority of the T2/FLAIR group.

Significantly, the model correctly identified a patient with a tumour size of just 0.2 cm³ as a cancer patient for each iteration and for all nine of their recorded spectra. “Therefore, we can confidently state that this model will identify tumours as small as 0.2 cm³ with 100% success rate in this particular example,” says Theakstone.

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The researchers conclude that their spectroscopic liquid biopsy shows great promise as a potential diagnostic tool for early diagnosis of brain tumours. Importantly, and unlike other liquid biopsies, this approach appears insensitive to tumour volume. They note that the test could be used to fast track patients who need medical imaging, and are continuing this research to deliver an early-stage triage tool for brain cancer detection.

Furthermore, Glasgow-based Dxcover, a spin-out from the University of Strathclyde, is commercializing an early detection platform based on the spectroscopic liquid biopsy technique.

“This breakthrough is a watershed moment in the development of early cancer detection,” says Matthew Baker, Dxcover’s chief technical officer and co-founder, in a press statement. “The study demonstrates the effectiveness of our Dxcover Brain Cancer Liquid Biopsy at detecting even the smallest brain tumours, which is great news for the care of future brain cancer patients, increasing treatment options and potentially extending life expectancy.”

A wearable, flexible X-ray detector that is constructed without using harmful heavy metals has been developed by researchers from China and the US. The prototype, which is made from metal–organic frameworks layered with gold electrodes and plastic, could provide a safer and more environmentally friendly route to the next generation of radiology devices.

Conventional radiation detectors for X-ray imaging – whether integrated into large, immobile instruments like CT scanners or the small bitewing detectors used by dentists – are typically fashioned into rigid panels. For some applications, however, flexible sensors would be more appropriate, for example in allowing detectors to conform to rounded body parts or to be moulded into the inside of confined spaces. To this end, researchers have turned to so-called metal–organic frameworks – flexible, semiconducting materials that respond to electromagnetic radiation by producing a measurable electric current.

Unfortunately, however, many of these metal–organic frameworks have a drawback that they share with conventional, rigid X-ray detectors: they are partly made from lead, the mining and use of which brings both environmental and health risks.

“Although the encapsulated detectors present a low risk of exposure to patients, there is a significant health risk to the manufacturing and maintenance personnel involved,” explains mechanical engineer Shenqiang Ren of the State University of New York at Buffalo.

In their study, Ren and colleagues produced a lead-free metal–organic framework by mixing a nickel chloride salt with 2,5-diaminobenzene-1,4-dithiol (DABDT) for several hours. The nickel linked the DABDT molecules, resulting in a compound that was more sensitive to 20 keV X-rays (suitable for use in diagnostic imaging applications) than recently reported flexible detectors made from amorphous selenium, Cs₂TeI₆ or gallium(III) trioxide. To make a basic sensor array, the team sandwiched individual pixels of their metal–organic framework between gold electrodes before attaching each to a plastic surface and linking them up with copper wiring. Finally, they coated the whole device in a flexible, silicone-based polymer.

Proof-of-concept

Tests imaging an aluminium letter “H” placed on the detector array confirmed that a significantly lower current output was recorded by the pixels covered by the metal shape than those that were unimpeded. The detector, Ren says, “manifests a high detection sensitivity and low detection limit, demonstrating a proof-of-concept wearable X-ray detector for radiation monitoring and imaging”.

While the researchers’ prototype featured only a 12 x 12 grid – and measured 6 x 6 cm – the design is inherently scalable to both higher resolutions and pixel densities. “Traditional X-ray imagers are rigid and uncomfortable to wear on the body or to place near the examined organ,” Ren explains. “The flexible detector shown in this work could be mounted onto objects with curved geometries and complex surfaces, such as wearable electronics.” Alongside applications for medical imaging, the flexible sensor could also be used for dosimetry measurements and for non-destructive object scanning.

“The need to implement large area, low-power operated and conformable radiation detectors has recently triggered a quest for novel material platforms able to reliably detect ionizing radiation,” comments Beatrice Fraboni, a physicist from the University of Bologna, Italy, who was not involved in the present study. The metal–organic framework developed by Ren and colleagues, she adds, is a “novel and promising candidate that well compares with the other material platforms so far proposed for this task – organic semiconductors and perovskites – and grants a lead-free, and thus sustainable, option”.

Imalka Jayawardena – an engineer from the University of Surrey who was also not involved in the study – agrees, noting that metal–organic frameworks have also shown promise in other areas, including photodetection and energy storage. “This work certainly shows the potential of such material systems for future X-ray detector technologies that should not only have high sensitivity but can also curved to conform to complex geometries,” he says.

With their initial study complete, the researchers are now moving to explore the structural design and controlled sensing performance of a variety of different metal–organic frameworks, alongside improving the resolution of their detector design and exploring the potential for large-scale manufacturing.

The study is described in Nano Letters.