It’s time to look back on our achievements and highlights after the first 12 months of the fastMOT project!
In the months following our kick-off meeting in April 2023, we have already seen some encouraging early results, from promising tests and experiments to our first publications and presentations. All work packages are up and running, and contributing towards our vision of developing a revolutionary new light sensing solution for non-invasive imaging of deep organ structures:
WP1: Detector development
In Work Package 1, we finished first tests of proof-of-principle capacitive readout and optical testing. Things went well although we still must verify scaling issues and make sure ideas and components work accordingly in large arrays. Along these lines, we are prototyping another chip which will target scaling issues.Furthermore, we published one paper in APL photonics titled “High-performance photon number resolving detectors for 850–950 nm wavelength range” (partial overlap with the fastMOT project), a collaboration between TU Delft and Single Quantum. We also have a paper under investigation in Nature Electronics, with ideas and demonstrations that can be of use for fastMOT arrays.
(a) System detection efficiency curves of the detector under study: we measured an average efficiency of 94.5% at the wavelength of 940 nm taken from three consecutive measurements (with similar input photon fluxes). System detection efficiencies for 850 and 913 nm are shown in blue and light green, respectively. (b) Typical voltage pulse from the studied detector. (c) Photon number resolving capabilities of the detector with different voltage trigger levels.
Figure from J. Los et. al., APL Photonics 9: 066101 (2024)
WP2: Detector system development
We focused on the electrical aspect of scaling up the number of pixels in an SNSPD array and the way we bias them to allow for fast electrical gating. We achieved good results on this front and now we are focusing on developing a new cryostat to host the chips that WP1 is developing.
WP3: Physics light simulation and modelling
We adapted a novel parallel, multiple-purpose, GPU-accelerated Monte Carlo (MC) algorithm on our advanced desktop. With that, we can simulate light propagation in biological tissues. We also built an MC framework based on the MC simulation outputs, which could generate TD-NIRS’s DTOF, TD-DCS’s g1 and g2 curve, speckle contrast of TD-SCOS, and other important results. With the MC framework and a digital brain phantom, we investigated the depth penetration under different wavelengths (785nm, 1064nm) and source detector distances (30mm, 40mm, 60mm) to discover deep tissue monitoring strategies. In addition, we incorporated the realistic sensor characteristics reported in WP2 and verified their minimal effects on the instrument performance of TD-NIRS and TD-SCOS, but the effects will become great in late time gates.
WP4: Tomographic work station
We realized an exploratory workstation (i.e., first laboratory system) based on: i) an upgraded version of a state-of-the-art custom Ti:Sa laser source featuring a wide tuning wavelength range, adjustable pulse width and tunable temporal coherence; ii) the best-available Superconducting Nanowire Single-Photon Detectors (SNSPDs); iii) the best-available technologies for multi-channel timing electronics. We built the system and tested it in its basic performances. The results show that the realized workstation has the required performances thus enabling the possibility of using it to enable the explorative studies both for Time Domain Near Infrared Spectroscopy as well as for Time Domain Speckle Contrast Optical Spectroscopy.
WP5: Laboratory and in vivo validation
We have worked in close collaboration with our partners of WP4, and conducted the first experiments using the exploratory workstation to demonstrate the feasibility of time-domain near infrared spectroscopy, diffuse correlation spectroscopy, and speckle contrast optical spectroscopy. This was demonstrated both in phantom measurements as well as in-vivo tests. Preliminary analysis has shown that our methods are able to differentiate between shallow and deep tissue – however in the upcoming year we will be working to demonstrate this more definitively.
Besides, do not forget to take a look at our #WomeninScience interview series, in which the female scientific staff working on fastMOT tells us about their roles in our project and their experiences of finding their career in science.
We look forward to the second year of our project with many upcoming events, and where we continue to work on innovating medical imaging!
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