Heidrun Wabnitz

SignificanceThe international standard IEC 80601-2-71 defines requirements for the basic safety and essential performance of medical continuous wave functional near-infrared spectroscopy (fNIRS) equipment, including a set of tests based on a dedicated tissue-equivalent phantom consisting of switchable apertures sandwiched between two diffusing media.AimIn a companion paper, we described a first implementation of this phantom developed by AIST, its basic characterization of attenuation properties, and results of its application in the testing of commercial fNIRS devices. In the present paper, we provide the absorption and reduced scattering spectra of the AIST phantom and of alternative silicone phantom matrices, complemented with extensive simulations on the effect of the phantom optical properties and geometry on the features of the phantom relevant for the fNIRS standard test.ApproachAll spectral measurements were performed with time-domain diffuse optical spectrometers for accurate quantification of the absorption and reduced scattering coefficient, whereas simulations were obtained using a Monte Carlo code.ResultsThe POM-C matrix of the AIST phantom exhibits negligible absorption (<0.01 cm−1) and a monotonically decreasing reduced scattering coefficient (from 10.5 down to 8.5 cm−1) in the 650 to 850 nm range. Monte Carlo simulations explain the independence from wavelength, geometry, and partially also optical properties in the change in attenuation when switching between two apertures of 6 and 4 mm diameter within the phantom, with <0.1 dB spectral variation. Extended spectral characterization of POM-C and silicone matrices in the 600 to 1100 nm range showed additional marked absorption peaks around 900 and 1020 nm.ConclusionsWe provide valid support for researchers and manufacturers to understand the operation of the phantom described in the fNIRS standard and to replicate it in their labs. In addition, we provide a basis for further evolution of the standard itself to encompass alternative probe geometries or functional tests.

SignificanceThe use of functional near-infrared spectroscopy (fNIRS) is expanding, including examples of devices approved for routine clinical use for specific indications. Instrument standardization is a critical element to facilitate clinical adoption. Currently, there is no published description of a phantom that meets the requirements of IEC 80601-2-71, the IEC/ISO standard for fNIRS equipment.AimWe report an example of the implementation of the fNIRS standard phantom described in IEC 80601-2-71. We further report results from measurement campaigns with this phantom prototype in Japan and Europe.ApproachA phantom prototype was built and circulated among multiple academic and commercial fNIRS groups with diverse instrumentation. The phantom prototype was characterized by wavelength-dependent measurements of its diffuse optical features and utilized in a test for fNIRS signal magnitude as described in IEC 80601-2-71.ResultsThe optical loss of this phantom prototype as well as its change by varying an internal aperture were found to be ∼40 dB and between 3.5 and 3.6 dB, respectively. The test for fNIRS signal magnitude based on this phantom was successfully carried out on various commercial fNIRS devices.ConclusionsThe characteristics of the phantom prototype agreed with the specifications in the standard. The phantom prototype proved suitable for the related test in IEC 80601-2-71.

SignificanceA shared understanding of terminology is essential for clear scientific communication and minimizing misconceptions. This is particularly challenging in rapidly expanding, interdisciplinary domains that utilize functional near-infrared spectroscopy (fNIRS), where researchers come from diverse backgrounds and apply their expertise in fields such as engineering, neuroscience, and psychology.AimThe fNIRS Glossary Project was established to develop a community-sourced glossary covering key fNIRS terms, including those related to the continuous-wave (CW), frequency-domain (FD), and time-domain (TD) NIRS techniques.ApproachThe glossary was collaboratively developed by a diverse group of 76 fNIRS researchers, representing a wide range of career stages (from PhD students to experts) and disciplines. This collaborative process, structured across five phases, ensured the glossary’s depth and comprehensiveness.ResultsThe glossary features over 300 terms categorized into six key domains: analysis, experimental design, hardware, neuroscience, mathematics, and physics. It also includes abbreviations, symbols, synonyms, references, alternative definitions, and figures where relevant.ConclusionsThe fNIRS glossary provides a community-sourced resource that facilitates education and effective scientific communication within the fNIRS community and related fields. By lowering barriers to learning and engaging with fNIRS, the glossary is poised to benefit a broad spectrum of researchers, including those with limited access to educational resources.

Near-infrared spectroscopy (NIRS) is an established technique for measuring tissue oxygen saturation (StO₂), which is of high clinical value. For tissues that have layered structures, it is challenging but clinically relevant to obtain StO₂ of the different layers, e.g. brain and scalp. For this aim, we present a new method of data analysis for time-domain NIRS (TD-NIRS) and a new two-layered blood-lipid phantom. The new analysis method enables accurate determination of even large changes of the absorption coefficient (Δµ_a) in multiple layers. By adding Δµ_a to the baseline µ_a, this method provides absolute µ_a and hence StO₂ in multiple layers. The method utilizes (i) changes in statistical moments of the distributions of times of flight of photons (DTOFs), (ii) an analytical solution of the diffusion equation for an N-layered medium, (iii) and the Levenberg–Marquardt algorithm (LMA) to determine Δµ_a in multiple layers from the changes in moments. The method is suitable for NIRS tissue oximetry (relying on µ_a) as well as functional NIRS (fNIRS) applications (relying on Δµ_a). Experiments were conducted on a new phantom, which enabled us to simulate dynamic StO₂ changes in two layers for the first time. Two separate compartments, which mimic superficial and deep layers, hold blood-lipid mixtures that can be deoxygenated (using yeast) and oxygenated (by bubbling oxygen) independently. Simultaneous NIRS measurements can be performed on the two-layered medium (variable superficial layer thickness, L), the deep (homogeneous), and/or the superficial (homogeneous). In two experiments involving ink, we increased the nominal µ_a in one of two compartments from 0.05 to 0.25 cm⁻¹, L set to 14.5 mm. In three experiments involving blood (L set to 12, 15, or 17 mm), we used a protocol consisting of six deoxygenation cycles. A state-of-the-art multi-wavelength TD-NIRS system measured simultaneously on the two-layered medium, as well as on the deep compartment for a reference. The new method accurately determined µ_a (and hence StO₂) in both compartments. The method is a significant progress in overcoming the contamination from the superficial layer, which is beneficial for NIRS and fNIRS applications, and may improve the determination of StO₂ in the brain from measurements on the head. The advanced phantom may assist in the ongoing effort towards more realistic standardized performance tests in NIRS tissue oximetry. Data and MATLAB codes used in this study were made publicly available.

The editorial introduces the JBO Special Section on Tissue Phantoms to Advance Biomedical Optical Systems.

Diffuse optics (DO) encompasses a range of photonics tools based on the study of random photon migration in highly scattering media—biological tissues in particular. Due to its unique features, DO is emerging as a powerful means for clinical or homecare diagnostics.¹ The basic physics of DO is related to the detection of temporal or spatial alteration in photon distribution re-emitted on the tissue surface.² Due to the low power (typically few mW) of injected near-infrared light (600- to 1100-nm range), DO is inherently noninvasive. The photon temporal (or spatial) distribution carries information on the absorption—ultimately related to tissue chemical composition, such as water, lipid, collagen content, oxy- and deoxy-hemoglobin concentration, cytochrome c-oxidase³—and scattering properties—linked to tissue microstructure. Further, DO is one of the few noninvasive modalities capable of providing functional information, e.g., brain or muscle activation.⁴ It can be operated noncontact through remote light illumination and collection.⁵ It explores the tissue well below the skin at depths of up to 2 to 4 cm. It can provide quantitative operator-independent assessment of the tissue status, such as hemoglobin oxygenation level in the brain. Finally, it is highly scalable, sharing the same technology from large clinical tomographic systems down to wearable devices or homecare appliances.⁶ For all these aspects, DO is attracting more and more interest in many fields, such as monitoring vital signs like brain oxygenation in critical care or during interventions,⁷ tumor diagnostics as for breast cancer,⁸ investigating the impact of lifestyle and nutrition on our body,⁹ or other fields such as neuroscience and psychology,¹⁰ sports, and leisure.¹¹ Even further, the operator independence, the depth sensitivity, and the scalability in addition to noninvasiveness make this option attractive for telemedicine and homecare of patients remotely.

A lack of accepted standards and standardized phantoms suitable for the technical validation of biophotonic instrumentation hinders the reliability and reproducibility of its experimental outputs. In this Perspective, we discuss general criteria for the design of tissue-mimicking biophotonic phantoms, and use these criteria and state-of-the-art developments to critically review the literature on phantom materials and on the fabrication of phantoms. By focusing on representative examples of standardization in diffuse optical imaging and spectroscopy, fluorescence-guided surgery and photoacoustic imaging, we identify unmet needs in the development of phantoms and a set of criteria (leveraging characterization, collaboration, communication and commitment) for the standardization of biophotonic instrumentation.

Performance assessment and standardization are indispensable for instruments of clinical relevance in general and clinical instrumentation based on photon migration/diffuse optics in particular. In this direction, a multi-laboratory exercise was initiated with the aim of assessing and comparing their performances. 29 diffuse optical instruments belonging to 11 partner institutions of a European level Marie Curie Consortium BitMap1 were considered for this exercise. The enrolled instruments covered different approaches (continuous wave, CW; frequency domain, FD; time domain, TD and spatial frequency domain imaging, SFDI) and applications (e.g. mammography, oximetry, functional imaging, tissue spectroscopy). 10 different tests from 3 well-accepted protocols, namely, the MEDPHOT2 , the BIP3 , and the nEUROPt4 protocols were chosen for the exercise and the necessary phantoms kits were circulated across labs and institutions enrolled in the study. A brief outline of the methodology of the exercise is presented here. Mainly, the design of some of the synthetic descriptors, (single numeric values used to summarize the result of a test and facilitate comparison between instruments) for some of the tests will be discussed.. Future actions of the exercise aim at deploying these measurements onto an open data repository and investigating common analysis tools for the whole dataset.

Errors in the Acknowledgments section of the originally published article are corrected. This article [Neurophotonics 8(1), 012101 (2020) doi: 10.1117/1.NPh.8.1.012101] was originally published on 7 January 2021 with erroneous attributions in the Acknowledgments section. Original: “fNIRS; F.S., Strategy for statistical tests and removal of confounding signals; M.Y and S.T., Filtering and drift regression;” Corrected: “fNIRS; M.Y. and S.T., Strategy for statistical tests and removal of confounding signals; M.Y, Filtering and drift regression;” Original: “M.Y., fNIRS signal quality metrics and channel rejection” Corrected: “M.Y. and A.L., fNIRS signal quality metrics and channel rejection” The article was corrected and republished on 13 January 2021.