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DOE OSTI2024

Using AI Segmentation Models to Improve Foreign Body Detection and Triage from Ultrasound Images

Medical imaging can be a critical tool for triaging casualties in trauma situations. In remote or military medicine scenarios, triage is essential for identifying how to use limited resources or prioritize evacuation for the most serious cases. Ultrasound imaging, while portable and often available near the point of injury, can only be used for triage if images are properly acquired, interpreted, and objectively triage scored. Here, we detail how AI segmentation models can be used for improving image interpretation and objective triage evaluation for a medical application focused on foreign bodies embedded in tissues at variable distances from critical neurovascular features. Ultrasound images previously collected in a tissue phantom with or without neurovascular features were labeled with ground truth masks. These image sets were used to train two different segmentation AI frameworks: YOLOv7 and U-Net segmentation models. Overall, both approaches were successful in identifying shrapnel in the image set, with U-Net outperforming YOLOv7 for single-class segmentation. Both segmentation models were also evaluated with a more complex image set containing shrapnel, artery, vein, and nerve features. YOLOv7 obtained higher precision scores across multiple classes whereas U-Net achieved higher recall scores. Using each AI model, a triage distance metric was adapted to measure the proximity of shrapnel to the nearest neurovascular feature, with U-Net more closely mirroring the triage distances measured from ground truth labels. Overall, the segmentation AI models were successful in detecting shrapnel in ultrasound images and could allow for improved injury triage in emergency medicine scenarios.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Controlled Assembly of Upconverting Nanoparticles for Low-Threshold Microlasers and Their Imaging in Scattering Media

Micron-sized lasers fabricated from upconverting nanoparticles (UCNP) coupled to whispering gallery mode (WGM) microresonators can exhibit continuous-wave anti-Stokes lasing useful for tracking cells, environmental sensing, and coherent stimulation of biological activity. The integration of these microlasers into organisms and microelectronics requires even smaller diameters, however, which raises threshold pump powers beyond practical limits for biological applications. To meet the need for low lasing thresholds and high fidelity fabrication methods, we use correlative optical and electron microscopy to uncover the nanoparticle assembly process and structural factors that determine efficient upconverted lasing. We show that 5 μm microspheres with controlled submonolayer UCNP coatings exhibit, on average, 25-fold lower laser thresholds (1.7 ± 0.7 kW/cm 2 ) compared to the mean values of the lowest threshold UCNP lasers, and variability is reduced 30-fold. WGMs are observed in the upconversion spectra for TiO 2 -coated microspheres as small as 3 μm, a size at which optical losses had previously prevented such observations. Finally, we demonstrate that the WGM signatures of these upconverting microlasers can be imaged and distinguished through tissue-mimicking phantoms. These advances will enable the fabrication of more efficient upconverting lasers for imaging, sensing, and actuation in optically complex environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1999

Modeling of polychromatic attenuation using computed tomography reconstructed images

This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.

NASA Discipline Musculoskeletal↗

DOE OSTI2021

TomoTwin: A simple digital twin for synchrotron tomography

A digital twin for synchrotron-based tomography for generating synthetic datasets from ground-truth phantoms. The code outputs greyscale projection images / tomographic volumes with realistic artifacts such as noise and phase-contrast and emulates their dependence on the acquisition parameters defining the beam and detector configuration. Some ground-truth phantoms are included with the code.

TEKAWADE, ANIKET↗

DOE OSTI2024

Toward Smart, Automated Junctional Tourniquets—AI Models to Interpret Vessel Occlusion at Physiological Pressure Points

Hemorrhage is the leading cause of preventable death in both civilian and military medicine. Junctional hemorrhages are especially difficult to manage since traditional tourniquet placement is often not possible. Ultrasound can be used to visualize and guide the caretaker to apply pressure at physiological pressure points to stop hemorrhage. However, this process is technically challenging, requiring the vessel to be properly positioned over rigid boney surfaces and applying sufficient pressure to maintain proper occlusion. As a first step toward automating this life-saving intervention, we demonstrate an artificial intelligence algorithm that classifies a vessel as patent or occluded, which can guide a user to apply the appropriate pressure required to stop flow. Neural network models were trained using images captured from a custom tissue-mimicking phantom and an ex vivo swine model of the inguinal region, as pressure was applied using an ultrasound probe with and without color Doppler overlays. Using these images, we developed an image classification algorithm suitable for the determination of patency or occlusion in an ultrasound image containing color Doppler overlay. Separate AI models for both test platforms were able to accurately detect occlusion status in test-image sets to more than 93% accuracy. In conclusion, this methodology can be utilized for guiding and monitoring proper vessel occlusion, which, when combined with automated actuation and other AI models, can allow for automated junctional tourniquet application.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1992

Description of a prototype emission-transmission computed tomography imaging system

We have developed a prototype imaging system that can perform simultaneous x-ray transmission CT and SPECT phantom studies. This system employs a 23-element high-purity-germanium detector array. The detector array is coupled to a collimator with septa angled toward the focal spot of an x-ray tube. During image acquisition, the x-ray fan beam and the detector array move synchronously along an arc pivoted at the x-ray source. Multiple projections are obtained by rotating the object, which is mounted at the center of rotation of the system. The detector array and electronics can count up to 10(6) cps/element with sufficient energy-resolution to discriminate between x-rays at 100-120 kVp and gamma rays from 99mTc. We have used this device to acquire x-ray CT and SPECT images of a three-dimensional Hoffman brain phantom. The emission and transmission images may be superimposed in order to localize the emission image on the transmission map.

NASA Discipline Musculoskeletal↗

DOE OSTI2024

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗

DOE OSTI2025

AAPM Truth‐based CT (TrueCT) reconstruction grand challenge

Background: This Special Report summarizes the 2022, AAPM grand challenge on Truth-based CT image reconstruction. Purpose: To provide an objective framework for evaluating CT reconstruction methods using virtual imaging resources consisting of a library of simulated CT projection images of a population of human models with various diseases. Methods: Two hundred unique anthropomorphic, computational models were created with varied diseases consisting of 67 emphysema, 67 lung lesions, and 66 liver lesions. The organs were modeled based on clinical CT images of real patients. The emphysematous regions were modeled using segmentations from patient CT cases in the COPDGene Phase I dataset. For the lung and liver lesion cases, 1–6 malignant lesions were created and inserted into the human models, with lesion diameters ranging from 5.6 to 21.9 mm for lung lesions and 3.9 to 14.9 mm for liver lesions. The contrast defined between the liver lesions and liver parenchyma was 82 ± 12 HU, ranging from 50 to 110 HU. Similarly, the contrast between the lung lesions and the lung parenchyma was defined as 781 ± 11 HU, ranging from 725 to 805 HU. For the emphysematous regions, the defined HU values were −950 ± 17 HU ranging from −918 to −979 HU. The developed human models were imaged with a validated CT simulator. The resulting CT sinograms were shared with the participants. The participants reconstructed CT images from the sinograms and sent back their reconstructed images. Further, the reconstructed images were then scored by comparing the results against the corresponding ground truth values. The scores included both task-generic (root mean square error [RMSE] and structural similarity matrix [SSIM]), and task-specific (detectability index [d’] and lesion volume accuracy) metrics. For the cases with multiple lesions, the measured metric was averaged across all the lesions. To combine the metrics with each other, each metric was normalized to a range of 0 to 1 per disease type, with “0” and “1” being the worst and best measured values across all cases of the disease type for all received reconstructions. Results: The True-CT challenge attracted 52 participants, out of which 5 successfully completed the challenge and submitted the requested 200 reconstructions. Across all participants and disease types, SSIM absolute values ranged from 0.22 to 0.90, RMSE from 77.6 to 490.5 HU, d’ from 0.1 to 64.6, and volume accuracy ranged from 1.2 to 753.1 mm3. The overall scores demonstrated that participant “A” had the best performance in all categories, except for the metrics of d’ for lung lesions and RMSE for liver lesions. Participant “A” had an average normalized score of 0.41 ± 0.22, 0.48 ± 0.32, and 0.42 ± 0.33 for the emphysema, lung lesion, and liver lesion cases, respectively. Conclusions: The True-CT challenge successfully enabled objective assessment of CT reconstructions with the unique advantage of access to a diverse population of diseased human models with known ground truth. This study highlights the significant potential of virtual imaging trials in objective assessment of medical imaging technologies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Simulation Study of Monoenergetic Photon Source LiDAR System Performance for Emergency Response Applications

The following report summarizes the results of a Monte Carlo simulation and modeling study of the Lawrence Berkeley National Laboratory’s (LBL) Monoenergetic Photon Source (MPS) as part of a high-energy LiDAR system for use in emergency response applications. A set of image quality indicators (IQI) and nonsensitive phantoms or generalized surrogates for search targets have been identified for use in the planned measurement campaign at the Berkeley Lab Laser Accelerator (BELLA) Center toward the end FY2023. These items were modeled and the time-of-flight (TOF) spectral responses following irradiation were calculated for a set of varying operating conditions. The goal of this study was to both predict the LiDAR system performance as well as determine if minor modifications to the IQI and phantom designs were required before fabrication. It was found that the IQI and target designs both overlap and extend towards the limit of performance of the system and are thus suitable for the final project measurement campaign.

43 - PARTICLE ACCELERATORS↗

NASA NTRS2021

Unsteady Pressure-Sensitive-Paint Shot Noise Reduction

In the study of unsteady Pressure-Sensitive Paint (uPSP) image data sets, pixel intensity values collected by Phantom cameras from multiple perspectives are used to calculate the surface pressure of an experimental model. This paper focuses on mitigation of shot noise which is introduced into the image data set by the cameras. Shot noise impacts the quality of data collected, increasing the system error in its pressure value calculations. This paper characterises statistical methods to reduce shot noise within experimental data by taking an average or weighted average across an area of pixels of their respective counts. Each combined-pixel has a higher total effective intensity value and therefore exhibits reduced noise throughout its time history. This is demonstrated by calculating the standard deviations of the combined pixel values through time, which decrease as the combined pixel area increases. Finally, these methods are compared across experimental wind tunnel conditions to examine their effectiveness at different Mach numbers. Ultimately, the results are used to recommend a blur filter type and size which will be applied to the raw image data prior to processing, as well as a minimum camera resolution for future experiments. Downstream of the filter application, the software to convert the 2D image data sets into surface pressure readings on a 3D grid use a ratio of decimation that assigns multiple pixels to each 3D grid node. This decimation ratio will also be aligned with the size of the blur filter, resulting in a more manageable data set size and compromised spatial resolution. Combined with the effect of the blur filter, the resulting pixel intensity readings will exhibit significantly reduced shot noise, reducing the magnitude of uncertainty and error in the final calculated pressure. For future tests, the camera spatial resolution must be sufficient to capture small flow and model features even after the recommended blur filter is applied. The image data set is taken from a uPSP experiment of the Space Launch System Block 1 cargo vehicle model in September 2019.

Lucy Tang↗

NASA NTRS2021

Unsteady Pressure-Sensitive Paint (UPSP) Shot Noise Reduction

Lucy Tang↗

NASA NTRS1999

Effect of optical digitizer selection on the application accuracy of a surgical localization system-a quantitative comparison between the OPTOTRAK and flashpoint tracking systems

Application accuracy is a crucial factor for stereotactic surgical localization systems, in which space digitization camera systems are one of the most critical components. In this study we compared the effect of the OPTOTRAK 3020 space digitization system and the FlashPoint Model 3000 and 5000 3D digitizer systems on the application accuracy for interactive localization of intracranial lesions. A phantom was mounted with several implantable frameless markers which were randomly distributed on its surface. The target point was digitized and the coordinates were recorded and compared with reference points. The differences from the reference points represented the deviation from the "true point." The root mean square (RMS) was calculated to show the differences, and a paired t-test was used to analyze the results. The results with the phantom showed that, for 1-mm sections of CT scans, the RMS was 0.76 +/- 0. 54 mm for the OPTOTRAK system, 1.23 +/- 0.53 mm for the FlashPoint Model 3000 3D digitizer system, and 1.00 +/- 0.42 mm for the FlashPoint Model 5000 system. These preliminary results showed that there is no significant difference between the three tracking systems, and, from the quality point of view, they can all be used for image-guided surgery procedures. Copyright 1999 Wiley-Liss, Inc.

Non-NASA Center↗

NASA NTRS2001

Localization of needle tip with color doppler during pericardiocentesis: In vitro validation and initial clinical application

This study evaluates a new device that uses color Doppler ultrasonography to enable real-time image guidance of the aspirating needle, which has not been possible until now. The ColorMark device (EchoCath Inc, Princeton, NJ) induces high-frequency, low-amplitude vibrations in the needle to enable localization with color Doppler. We studied this technique in 25 consecutive patients undergoing pericardiocentesis, and in vitro, in a urethane phantom with which the accuracy of color Doppler localization of the needle tip was compared with that obtained by direct measurement. Tip localization was excellent in vitro; errors axial to the ultrasound beam (velocity Doppler -0.13 +/- 0.90 mm, power Doppler -0.05 +/- 1.7 mm) were less than lateral errors (velocity -0.36 +/- 1.8 mm, power -0.02 +/- 2.8 mm). In 18 of 25 patients, the needle was identified and guided into the pericardial space with the ColorMark technique, and it allowed successful, uncomplicated drainage of fluid. Initial failures were the result of incorrect settings on the echocardiographic machine and inappropriate combinations of the needle puncture site and imaging window. This study demonstrates a novel color Doppler technique that is highly accurate at localizing a needle tip. The technique is feasible for guiding pericardiocentesis. Further clinical validation of this technique is required.

NASA Discipline Cardiopulmonary↗

DOE OSTI2023

Simulation studies of a full-ring, CZT SPECT system for whole-body imaging of 99m Tc and 177 Lu

Single photon emission computed tomography (SPECT) is an imaging modality that has demonstrated its utility in a number of clinical indications. Despite this progress, a high sensitivity, high spatial resolution, multi-tracer SPECT with a large field of view suitable for whole-body imaging of a broad range of radiotracers for theranostics is not available. With the goal of filling this technological gap, we have designed a cadmium zinc telluride (CZT) full-ring SPECT scanner instrumented with a broad-energy tungsten collimator. The final purpose is to provide a multi-tracer solution for brain and whole-body imaging. Our static SPECT does not rely on the dual- and the triple-head rotational SPECT standard paradigm, enabling a larger effective area in each scan to increase the sensitivity. We provide a demonstration of the performance of our design using a realistic model of our detector with simulated body-sized phantoms filled with 99m Tc and 177 Lu. Our SPECT design can resolve 7.9 mm rods for 99m Tc (140 keV) and 9.5 mm for 177 Lu (208 keV) in a hot-rod Derenzo phantom with a 3-min exposure and reach an image contrast of 78% for 99m Tc and 57% for 177 Lu using the NEMA IQ phantom with a 6-min exposure. Our modified scatter correction shows an improved contrast-recovery ratio compared to a standard correction. In this paper, we demonstrate the good performance of our design for whole-body imaging purposes. This adds to our previous demonstration of improved qualitative and quantitative 99m Tc imaging of brain perfusion and 123 I imaging of dopamine transport with respect to state-of-the-art NaI dual-head cameras. We show that our design provides similar IQ and contrast to the commercial full-ring SPECT VERITON for 99m Tc. Regarding 177 Lu imaging of the 208 keV emissions, our design provides similar contrast to that of other state-of-the-art SPECTs with a significant reduction in exposure. In conclusion, the high sensitivity and extended energy range up to 250 keV makes our SPECT design a promising alternative for clinical imaging and theranostics of emerging radionuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

An empirical method for geometric calibration of a photon counting detector-based cone beam CT system

BACKGROUND: Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors’ limited areas. OBJECTIVE: This study presented an empirical method for the geometric calibration of small area PCD-based cone beam CT systems. METHODS: Unlike the traditional methods, we developed an iterative optimization procedure to determine geometric parameters using the reconstructed images of small metal ball bearings (BBs) embedded in a custom-built phantom. An objective function incorporating the sphericities and symmetries of the embedded BBs was defined to assess performance of the reconstruction algorithm with the given initial estimated set of geometric parameters. The optimal parameter values were those which minimized the objective function. The TIGRE toolbox was employed for fast tomographic reconstruction. To evaluate the proposed method, computer simulations were carried out using various numbers of spheres placed in various locations. Furthermore, efficacy of the method was experimentally assessed using a custom-made benchtop PCD-based cone beam CT. RESULTS: Computer simulations validated the accuracy and reproducibility of the proposed method. The precise estimation of the geometric parameters of the benchtop revealed high-quality imaging in CT reconstruction of a breast phantom. Within the phantom, the cylindrical holes, fibers, and speck groups were imaged in high fidelity. The CNR analysis further revealed the quantitative improvements of the reconstruction performed with the estimated parameters using the proposed method. CONCLUSION: Apart from the computational cost, we concluded that the method was easy to implement and robust.

Instruments & Instrumentation↗

NASA NTRS1993

Cross-calibration of liquid and solid QCT calibration standards: corrections to the UCSF normative data

Quantitative computed tomography (QCT) has been shown to be a precise and sensitive method for evaluating spinal bone mineral density (BMD) and skeletal response to aging and therapy. Precise and accurate determination of BMD using QCT requires a calibration standard to compensate for and reduce the effects of beam-hardening artifacts and scanner drift. The first standards were based on dipotassium hydrogen phosphate (K2HPO4) solutions. Recently, several manufacturers have developed stable solid calibration standards based on calcium hydroxyapatite (CHA) in water-equivalent plastic. Due to differences in attenuating properties of the liquid and solid standards, the calibrated BMD values obtained with each system do not agree. In order to compare and interpret the results obtained on both systems, cross-calibration measurements were performed in phantoms and patients using the University of California San Francisco (UCSF) liquid standard and the Image Analysis (IA) solid standard on the UCSF GE 9800 CT scanner. From the phantom measurements, a highly linear relationship was found between the liquid- and solid-calibrated BMD values. No influence on the cross-calibration due to simulated variations in body size or vertebral fat content was seen, though a significant difference in the cross-calibration was observed between scans acquired at 80 and 140 kVp. From the patient measurements, a linear relationship between the liquid (UCSF) and solid (IA) calibrated values was derived for GE 9800 CT scanners at 80 kVp (IA = [1.15 x UCSF] - 7.32).(ABSTRACT TRUNCATED AT 250 WORDS).

NASA Program Space Physiology and Countermeasures↗

DOE OSTI2025

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a powerful label-free biological imaging technique, but the raw signal requires careful processing. The vibrationally resonant (Raman) fingerprint signal is usually small compared with instrumental noise sources and the nonresonant background (NRB) inherent in the BCARS signal. Fortunately, the NRB exhibits a systematic phase relationship with the coherent Raman response, acting as a heterodyne amplifier for the weak fingerprint signal. Due to this heterodyne effect, the Raman response can be recovered quantitatively and invariantly across different instruments, provided the NRB shape is known. Even with heterodyne amplification, the amplitudes of fingerprint signal components are often comparable to system noise. Singular value decomposition (SVD), which utilizes spatial information, is often employed for additional noise filtering. Consequently, finding optimal processing parameters to properly distinguish the NRB and Raman responses and suppress noise in the complex BCARS signal requires a reference system that realistically represents the spectral and spatial properties of BCARS signals obtained from biological samples. We present a digital tissue phantom that meets these criteria as a tool for testing candidate signal processing pipelines. The digital phantom is generated with simulated hyperspectral Raman images having system-specific noise and background characteristics. Here, we analyze phantom datasets with differing background and signal-to-noise conditions to evaluate their impact on the performance of multiple signal processing pipelines. Specifically, we investigate the application of a Butterworth filter-based routine to directly estimate the NRB from the BCARS signal. Additionally, we evaluate a Lorentzian wavelet transform as an alternative to the Hilbert transform for extracting the Raman spectrum from the BCARS signal. While we demonstrate this phantom for BCARS, it can be used for any spectroscopic Raman imaging approach.

Dixon, Jessica Z. [Georgia Institute of Technology↗

DOE OSTI2024

Visibility and annoyance of the phantom array effect varies with age and history of migraine

The phantom array effect (PAE) is a series of repeated images that may be perceived when a person moves their eyes in large saccades across a light source (or a specular reflection of that light source) that is modulating in output over time. Fifty-five people, including a group of 25 who experience migraine, evaluated the visibility and annoyingness of phantom arrays produced by 85 unique temporal light modulation waveforms (including sine, rectangular, complex and DC waveforms) generated using an LED placed against a black background. Those with migraine exhibited higher average visibility compared to those without migraine ( p = 0.019) and were relatively more sensitive at higher frequencies ( p < 0.001). Younger participants also found more stimuli to be visible ( p < 0.001). The threshold sensitivity function was similar to that developed for the phantom array visibility measure (PAVM), and PAVM was effective in predicting visibility ( R 2 = 0.87 for the relevant region of PAVM < 3). While those in the migraine group did not report seeing the PAE more often in everyday life at a statistically significant level, they reported being more annoyed by it and having more unwanted physiological responses (headaches, eye fatigue and distraction/disorientation). Members of the migraine group were also more likely to have changed their behaviour in architectural spaces (such as leaving a restaurant with ‘flickering’ lights). In the four hours after completing the experiment, 64% of the migraine group (vs. 19% of the non-migraine group) reported experiencing discomfort or an adverse reaction. In particular, 41% reported experiencing a headache (vs. 8% for those in the non-migraine group).

60 APPLIED LIFE SCIENCES↗