Search

Hyperspectral imaging (HSI) captures a greater level of spectral detail than traditional optical imaging, making it a potentially valuable intraoperative tool when precise tissue differentiation is essential. Hardware limitations of current optical systems used for handheld realtime video HSI result in a limited focal depth, thereby posing usability issues for integration of the technology into the operating room. This work integrates a focus-tunable liquid lens into a video HSI exoscope, and proposes novel video autofocusing methods based on deep reinforcement learning. A first-of-its-kind robotic focal-time scan was performed to create a realistic and reproducible testing dataset. We benchmarked our proposed autofocus algorithm against traditional policies, and found our novel approach to perform significantly ( p < 0.05) better than traditional techniques (0.070 ±.098 mean absolute focal error compared to 0.146 ±.148). In addition, we performed a blinded usability trial by having two neurosurgeons compare the system with different autofocus policies, and found our novel approach to be the most favourable, making our system a desirable addition for intraoperative HSI.

Introduction: Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous iterations of intra-operative HSI systems have shown limitations, either due to carrying a large footprint limiting ease of use within the confines of a neurosurgical theater environment, having a slow image acquisition time, or by compromising spatial/spectral resolution in favor of improvements to the surgical workflow. Lightfield hyperspectral imaging is a novel technique that has the potential to facilitate video rate image acquisition whilst maintaining a high spectral resolution. Our pre-clinical and first-in-human studies (IDEAL 0 and 1, respectively) demonstrate the necessary steps leading to the first in-vivo use of a real-time lightfield hyperspectral system in neuro-oncology surgery., Methods: A lightfield hyperspectral camera (Cubert Ultris ×50) was integrated in a bespoke imaging system setup so that it could be safely adopted into the open neurosurgical workflow whilst maintaining sterility. Our system allowed the surgeon to capture in-vivo hyperspectral data (155 bands, 350-1,000 nm) at 1.5 Hz. Following successful implementation in a pre-clinical setup (IDEAL 0), our system was evaluated during brain tumor surgery in a single patient to remove a posterior fossa meningioma (IDEAL 1). Feedback from the theater team was analyzed and incorporated in a follow-up design aimed at implementing an IDEAL 2a study., Results: Focusing on our IDEAL 1 study results, hyperspectral information was acquired from the cerebellum and associated meningioma with minimal disruption to the neurosurgical workflow. To the best of our knowledge, this is the first demonstration of HSI acquisition with 100+ spectral bands at a frame rate over 1Hz in surgery., Discussion: This work demonstrated that a lightfield hyperspectral imaging system not only meets the design criteria and specifications outlined in an IDEAL-0 (pre-clinical) study, but also that it can translate into clinical practice as illustrated by a successful first in human study (IDEAL 1). This opens doors for further development and optimisation, given the increasing evidence that hyperspectral imaging can provide live, wide-field, and label-free intra-operative imaging and tissue differentiation., Competing Interests: The authors declare that the research was conducted in collaboration between Hypervision Surgical and Kings College London. MEb, TV, JS, SO, PN, MJ, CH, TT, and JJ are all employees of Hypervision Surgical. MEb, TV, SO, and JS are shareholders and co-founders of Hypervision Surgical. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 MacCormac, Noonan, Janatka, Horgan, Bahl, Qiu, Elliot, Trotouin, Jacobs, Patel, Bergholt, Ashkan, Ourselin, Ebner, Vercauteren and Shapey.)

The performance of tertiary moving bed biofilm reactors (MBBRs) was evaluated in terms of micropollutants (MPs) removal from secondary-treated municipal wastewater. After stepwise establishment of a mature biofilm, monitored by scanning electron and confocal microscopies, abiotic and biotic removals of MPs were deeply studied. Since no MPs reduction was observed by the both photodegradation and volatilization, abiotic removal of MPs was ascribed to the sorption onto the biomass. Target MPs i.e. Naproxen, Diclofenac, 17β-Estradiol and 4n-Nonylphenol, arranged in the ascending order of hydrophobicity, abiotically declined up to 2.8%, 4%, 9.5% and 15%, respectively. MPs sorption onto the suspended biomass was found around two times more than the biofilm, in line with MPs' higher sorption kinetic constants (k sor ) found for the suspended biomass. When comparing abiotic and biotic aspects, we found that biotic removal outperformed its counterpart for all compounds as Diclofenac, Naproxen, 17β-Estradiol and 4n-Nonylphenol were biodegraded by 72.8, 80.6, 84.7 and 84.4%, respectively. The effect of the changes in organic loading rates (OLRs) was investigated on the pseudo-first order degradation constants (k biol ), revealing the dominant biodegradation mechanism of co-metabolism for the removal of Diclofenac, Naproxen, and 4n-Nonylphenol, while 17β-Estradiol obeyed the biodegradation mechanism of competitive inhibition. Biotic removals and k biol values of all MPs were also seen higher in the biofilm as compared to the suspended biomass. To draw a conclusion, a quite high removal of recalcitrant MPs is achievable in tertiary MBBRs, making them a promising technology that supports both pathways of co-metabolism and competitive inhibition, next to the abiotic attenuation of MPs., (Copyright © 2018 Elsevier B.V. All rights reserved.)