Clinical medicine continues to seek novel rapid non-invasive tools capable of providing greater insight into disease progression and management. Raman scattering based technologies constitute a set of tools under continuing development to address outstanding challenges spanning diagnostic medicine, surgical guidance, therapeutic monitoring, and histopathology. Here we review the mechanisms and clinical applications of Raman scattering, specifically focusing on high-speed imaging methods that can provide spatial context for translational biomedical applications. The technological developments of high-speed spontaneous and coherent Raman scattering based imaging for translational applications including surgical guidance, histopathology, and pathophysiological monitoring. This fundamental curiosity, to explore the interactions of light with matter, has continued to drive the development of vibrational imaging technologies from the realms of physics and chemistry to new advances and applications in biology and medicine.In his 1930 Nobel lecture, Sir C. V. Raman alluded to the discoveries and developments in comprehending the interactions between light and matter as a starting point in the development of a new branch of knowledge.2 Using strongly converging sunlight to illuminate the samples, this report described the inelastic scattering of light in material. The Raman effect occurs with the creation of an induced dipole moment in a molecule, causing an instantaneous transition to a virtual state; this process enables coupling between vibrational states and the transfer of a quantum of vibrational energy with the molecule (Ω) and is highly specific to the molecular bond and the physico-chemical properties of the sample, such that extremely precise information about the composition, state, and polarization of a material can be determined. Furthermore, the intensity of spontaneous Raman scattering is proportional to the concentration of the scattering species, yielding the potential for quantitative analysis. Years after the advent of the laser, stable light sources were used to demonstrate this compositionally-specific scattering in biological specimens.3Raman scattering was first described in 1928 as “new type of secondary radiation” appearing as a “modified scattered radiation of degraded frequency” that accompanies the diffuse radiation scattered from molecules in dust-free liquids and gases.molecule . This trin vivo4–6 were able to demonstrate the molecular specificity of this technique for characterizing anatomical differences and discriminating diseases. These studies primarily utilized point-based measurements either with fiber optic probes or with confocal microscopes for data acquisition due to the long integration times needed to obtain adequate signal contrast. In general, spontaneous Raman scattering is a weak or infrequent process that has rendered image acquisition impractical for in vivo applications or visualizing dynamic processes. This lack of spatial information has been a challenge for Raman scattering methods and has required the development of numerous advances that combine new techniques and innovations in order to make Raman imaging a reality.Early research groups using Raman scattering 7astronomy,8 food & agriculture,9,10 forensics,11 geology,12 industrial combustion,13 and pharmaceutical development,14–16 and have continually expanded as the instrumentation for spectroscopic studies has become more widely available.The intrinsic sensitivity of the Raman effect to both organic and inorganic moieties has been applied to a wide array of fields for analyses. The breadth of applications have been recently reviewed, spanning archaeology & art,ex vivo and in vivo).17–20 While many promising analytical methods for biomarker development, pathophysiological assessment, and diagnostic applications have been described ex vivo, most investigations continue to utilize point-based spectroscopic measurements, which provide limited spatial context into the molecular variations present in these biological samples. Raman imaging approaches comprise a valuable advancement in the assessment of biomedical samples with non-destructive label-free contrast.21,22 Despite the promise of Raman imaging for numerous applications, the fundamentally weak spontaneous Raman scattering process leads to long acquisition times for microspectroscopic imaging applications. As such, there have been numerous investigations into technological and analytical advancements that can dramatically increase the generated Raman signal or efficiently acquire data at high-speeds to propel these techniques towards clinical utility. Ultimately, the factor of greatest importance is the speed by which actionable biochemical information can be obtained and conveyed for clinical decision making. As a non-destructive and non-invasive tool that does not require labels for molecularly specific detection and has the ability to provide this information within the context of an image with respect to cells and tissues, Raman scattering methods still hold great promise to address challenges in translational biomedicine, but high-speed imaging has been a major hurdle for the field. This targeted review highlights developments in Raman imaging for translational applications, targeting advances that have been implemented to increase detection and imaging speeds within a spatial context for intraoperative ex vivo or clinical in vivo imaging.A wide range of biological and medical investigations have applied Raman spectroscopic techniques to cells, animal models, biofluids, and tissues  obtained from samples, specimens, and patients, these point-based measurements provide little to no spatial context for the comparison of samples; this lack of spatial information has been a challenge for translation. Furthermore, interpretation of the spectroscopic data within a clinical setting is hampered by the complex spectral signatures obtained, which likely has contributed to the limited adoption of these methods despite the extensive field of research addressing clinical applications.2.1e.g. Rayleigh) and autofluorescence, the latter of which can be minimized by utilizing longer wavelength sources that are less likely to efficiently excite the electronic transitions in molecules that generate fluorescence. These longer excitation wavelengths, often near-infrared (NIR) at 785 nm or 830 nm, fall within an optical window in most biological samples where the absorption from most chromophores is reduced and facilitates greater photon penetration for deeper interrogation. This, however, can be a costly trade-off as the efficiency of the Raman scattering phenomenon is inversely proportional to wavelength (follows 1/λ4). In all cases, high resolution spontaneous Raman imaging requires the careful selection of excitation sources from the available, stable lasers needed for experiments.As many biomedical imaging applications of Raman scattering are interested in cellular changes associated with disease, Raman microspectroscopic imaging has often been utilized for the analysis of cells and tissues. This approach is typically based on confocal laser scanning microscope designs where the beam is raster scanned across the specimen to acquire a full spectrum at each location , left. Iex vivo samples such as tissues prepared for histological analysis. Efforts have been made to reduce imaging times to more clinically-relevant durations and include line-scanning, multifocal, or wide-field imaging approaches24 along with predictive-methods for sparse spatial sampling,25 the combination of on-line chemometrics,26 or integration with other imaging modalities such as autofluorescence imaging.27 One promising demonstration of this augmented Raman data collection method combined multimodal spectral imaging of tissue autofluorescence with multifocal Raman microspectroscopy.28 By using rapid autofluorescence imaging to acquire spatial maps and predict segmentation, spatial light modulation to multiplex Raman excitation, and digital micromirror devices to replace the conventional fixed spectrometer slit with a programmable binary array, automated segmentation and imaging of nearly 800 points of interest on a single excised skin sample (∼1 cm2) could be achieved in approximately 11 minutes  overlay of specific sample locations that correspond to a particular tissue type. In a similar approach, by adding simple fiducial markers onto a typical handheld Raman probe, Horgan et al. were able to demonstrate in ex vivo and in vivo animal studies that digital probe tracking could be used to define a tumor tissue margin through the combined use of Raman spectral measurements and exogenous fluorescence detection.31 For surgical guidance, the use of a handheld tool is familiar for surgeons assuming the technique is compatible with sterilization protocols and can be integrated into standard practice to provide new information. Extending this method for clinical implementation can have greater requirements on probe localization and imaging resolution, depending on the application of interest. Skin tumor demarcation, for example, typically uses a relatively wide excision margin to minimize the chance of recurrence, however this margin is determined based upon the location of the lesion. Alternatively, brain cancer excision requires a narrow margin to preserve critical structures and precise determination of measurement position is typically compared against pre-operative magnetic resonance imaging. In a study of 17 patients undergoing surgical excision of brain tumors, Jermyn et al. used intraoperative tracking of a Raman probe to acquire and overlay in situ spectral measurements from various locations that demonstrated this point-based detection could differentiate tissue type and glioma grade with high sensitivity and specificity.32 This work and that of other research groups suggests that these tools could be used for guidance and tissue differentiation in the operating theater to provide biochemical information during procedures.Microscopic approaches can obtain subcellular resolution at the cost of long integration times and high fluence rates. However, there have been alternative intraoperative investigations based on non-destructive Raman scattering methods to balance imaging time and sampling performance. Several groups have accomplished this balance through the combination of widefield imaging and Raman fiber optic probe tracking to quickly acquire Raman spectral data with a spatial resolution that is suited for surgical guidance. For example, Yang 33 One such implementation for intraoperative imaging of breast tumor margins utilized a large area SORS probe design that acquired spectra from the surface and several hundered micrometers of superficial depths of excised tissue following lumpectomy.34 By mounting the ex vivo tissue on an automated tissue scanning system that rotated the sample and positioned the SORS probe, sparse spatial sampling of the superficial tissue could be mapped. Raman spectral signatures that differed by composition were determined using multivariate analysis and enabled the identification of spatial regions corresponding to a particular disease status. While this approach does not convey the high spatial resolution of other imaging approaches, this 3D scanner-based SORS imaging approach has the potential for intraoperative excised margin assessment within a clinically-relevant timescale. An alternative fiber probe design combining point-based Raman spectroscopic measurements with fluorescence lifetime imaging was also reported for ex vivo tissue mapping, here using both Raman mapping and fluorescence signals to guide spectral acquisition with the potential for in vivo application.35 The use of guided spatial sampling introduces a balance in utilizing spontaneous Raman scattering approaches for imaging within the constraints of clinically relevant time-frames, a limitation conferred due to the relative weakness of the spontaneous Raman scattering phenomenon.Other approaches have investigated the use of low spatial resolution Raman fiber probe based images to study excised tissue after removal as a means to map tissue margins and guide surgical procedures. Determining whether a sufficient margin of healthy tissue has been used for surgical excision requires the ability to determine the tissue composition as a function of depth from the exposed specimen surface. Spatially offset Raman spectroscopy (SORS) based methods have been investigated for probing depth specific information by altering the separation between the light source and detector, with numerous applications in biomedicine.14 fold greater than those observed from spontaneous Raman scattering. SERS enhancement can be gained from nanoscale surfaces, found on either patterned structures36 or nanoparticles,37 with nanoparticles being a preferred means of delivering probes within cells and tissues.38 A wide range of bespoke SERS structures have been created to boost the Raman scattering intensity, including spheres,39,40 rods,41 bowties,42,43 stars44,45 and other shapes.46 Nanoparticles for SERS can be readily targeted using antibodies, peptides, and aptamers to reach specific cellular and tissue compartments.38To circumvent the need for lengthy integration times that prohibit clinical Raman imaging studies, approaches that increase the scattered signal intensity have also been investigated. Surface-enhanced Raman scattering (SERS) is an optical phenomenon exhibited by the interaction of Raman-active molecules with specifically-crafted surfaces of noble metals that form “hot spots”. Confined to this highly localized volume of interaction, the surface plasmon resonance  can lead to Raman scattering intensity enhancements ≥1047 Furthermore, the combinatorial approach of utilizing a widefield imaging modality such as MRI, PET, or fluorescence in combination with point-wise SERS measurements has been further investigated. With regards to directly imaging SERS signals, Garai et al. developed a SERS imaging fiber bundle assembly intended to acquire ratiometric images from tissue with both targeted and untargeted nanoparticles  however each of these components must be carefully considered. Biomedical specimens are often of interest because of dynamic changes which further require imaging systems to acquire data at a high enough rate to capture changes on a relevant time scale. This combination of fast, stable imaging at a high enough spatial resolution to visualize and quantify changes is a challenge for translational imaging systems, often resulting in large devices that dampen vibrations and provide mechanical stability for optical paths, but which may be incompatible with the clinical environment. The methods and advancements described above for increasing imaging speed of Raman scattering methods at microscopic spatial resolutions indicate the potential for numerous clinical applications, however, for some dynamic processes, further advances are still necessary.Fiber optic probe based methods for detecting Raman scattering, either alone or in combination with other rapid imaging approaches, have the potential to provide biochemical information to characterize a tissue 3in vivo applications without the need for exogenous materials.Spontaneous Raman methods provide considerable molecular information, however, the inherent weakness of the Raman signal stands as a major barrier to many imaging applications. While surface-enhanced Raman methods boost the Raman signal strength, the requirement for exogenous nanoscale structures poses regulatory issues for clinical adoption and translation. An ideal approach would comprise enhanced Raman signal strength for 52–55 Based on the nonlinear mixing of two (or more) ultrafast laser sources, Raman-active vibrations can be selectively driven in a coherent manner by tuning the difference in the frequency (ωΔ) of the excitation sources, pump (ωpump) and Stokes (ωStokes), to match the vibrational resonance (Ω) of the target molecule  and stimulated Raman scattering (SRS) imaging methods are the most commonly used given both their practicality and inherent sensitivity to Raman features that enable species separation and identification. To achieve the nonlinear interactions of the copropagating laser sources, high photon densities are facilitated using high numerical aperture (NA) microscope objectives to strongly focus the light. While not intrinsically a challenge for investigations of cells in vitro or thin sections of ex vivo tissue, coherent Raman scattering can be strongly directional, and differs between modalities: transmission mode measurements can be advantageous for both CARS and SRS carried out in thin samples, however, for many biological applications, epi-collection is a necessity. By relying upon the multiple linear scattering events in turbid samples, epi-collection for these techniques has been demonstrated with differing levels of success.52,58 Furthermore, these CRI methods offer the potential for quantitative imaging of sample constituents; while CARS displays a quadratic relationship between signal intensity and concentration, SRS signals are linear, allowing direct visualization of composition and structure for quantitative image analysis.Coherent Raman methods provide video-rate, non-destructive, chemically-specific imaging of tissues without the need for exogenous labels for contrast. Coherent Raman imaging (CRI) has been developed as a viable tool set that continues to grow as a field for translation from the laboratory bench to clinical and intraoperative settings.molecule . To achimolecule , right. 3.159CRI methods offer approximately 10 000 times greater signal strength over spontaneous Raman for micron-sized objects, converting acquisition times of hours with spontaneous Raman imaging to only fractions of a second. This dramatic speed improvement has been realized for tissue mapping, and several instruments and applications have been described for tissue analysis within or adjacent to the operative theater. A major benefit to CRI based optical imaging is the removal of the need for time consuming staining and sample processing, the limited volume of biopsy tissue that is eventually examined, and the restriction of specific tissue features to those for which staining protocols are well-established. A recent targeted review of SRS histopathology and computationally-aided diagnostics covers some of the these topics in detail for further insight on the topic as part of this themed collection on Biomedical Raman Imaging.et al., ex vivo tissues that have been freshly excised can be imaged at multiple vibrational bands to provide contrast akin to stain-free histopathology using CRI. In an initial report, SRS was implemented instead of CARS to remove the contribution of non-resonant background signals that can degrade image contrast, and imaging in mouse models indicated potential applications for several diseases of the nervous system, including glioma and stroke.60 The promising performance54 of this ex vivo tissue imaging approach for intraoperative brain tumor histology prompted the development an operating room compatible SRS microscope based on a portable fiber-laser.61 The authors imaged unprocessed excised specimens from 101 neurosurgical patients using stimulated Raman histology (SRH) and were able to generate virtual staining that recapitulated hematoxylin and eosin (H&E) stain appearance with essential diagnostic features. These images, generated using unprocessed surgical specimens, when compared with conventional tissue staining protocols, provided concordance for over 92% diagnostic accuracy. A further benefit of this stain-free, real-time imaging approach is the potential for automated image classification for diagnostic prediction. Capitalizing on machine learning techniques, in this case a multilayer perceptron, the classifier was trained with image attributes automatically extracted from over 120 000 fields of view (FOVs) and comprises a proof-of-principle demonstration of automated diagnostic predictions.Initially demonstrated by Freudiger 62 This study utilized a different set of extracted image features and different design of machine learning, but was able to capture diagnostic histological features to differentiate tumors of the posterior fossa. Extending this technique as a direct comparison with standard pathological evaluation for cancer subtyping, Shin et al. utilized simultaneous two-color SRH imaging for intraoperative assessment of skull base tumors.63 Using the lipid- and protein-tuned SRS imaging to generate pseudo-H&E images from fresh resected tumor tissues  to train an automated image feature extractor based on a library of 2.5 million SRH images. To test the developed CNN for 13 histological classes, imaging was performed at three tertiary medical centers in a randomized clinical trial comparing pathologist interpretation of standard H&E histology with CNN-based interpretation of SRH images from small excised tissue specimens. Both the control and experimental arms of the study achieved nearly 94% diagnostic accuracy, demonstrating the potential for SRH with deep learning diagnosis to improve intraoperative decision making for neurosurgical oncology.Most recently, an automated tissue-to-diagnosis pipeline based on deep learning and two-color SRH imaging of brain tumors was evaluated in a multi-center trial.65 and the combination of deep learning with SRS microscopy66 have been utilized for gastrointestinal and laryngeal tumors, respectively, in addition to other disease targets; however, these demonstrations were simulations of intraoperative performance and have yet to advance to the stage of intraoperative SRH. However, with continued instrumentation and analytical development, these and many other applications will be likely targets for intraoperative investigation in the near future.Similar methods using frequency modulation SRS3.2ex vivo CRI histology may improve the evaluation of excised specimens and enable automated diagnosis for disease states such as cancer. Given that these images can be acquired from unprocessed tissues with no additional contrast, are inherently three-dimensional due to the nonlinear optical excitation, and are non-destructive in nature, an overarching goal is to directly apply CRI to native tissues in situ within a clinical setting or operating theater. This translation of the complex instrumentation for clinical compatibility is further complicated by the methods needed to interact with the tissues of interest, however, several groups have explored new instruments and implementations to enable in vivo CRI.The value of rapid, in situ. Despite the numerous technical and translational challenges, early work adapting multiphoton tomographic systems for CARS measurements in human skin was first reported by König et al. This initial system was based upon a tunable NIR femtosecond laser oscillator combined with an optical parametric oscillator (OPO) to achieve synchronized ωpump and ωStokes pulses.67 Using low total excitation power at the focus of a high NA objective, femtoliter volumes within the skin were imaged based on beam scanning. The initial demonstration, tuned to the 2845 cm−1 CH2 stretching vibrations, simultaneously acquired two photon excited fluorescence (TPEF), second harmonic generation (SHG), and CARS images from healthy control skin, psoriatic lesion skin, and skin following the topical application of omega-3 oil, with a clinically-compatible, albeit large, instrument. Further reports from this same group have expanded the demonstrated dermatologic targets to include multiple depths , diseases , and technical improvements to enhance flexibility .58 In this work, the authors utilized a large area photodiode in front of the laboratory microscope objective near the tissue interface to collect the multiple linearly-scattered photons back-propagating though the skin, coupled with custom lock-in amplifiers for the high-frequency modulated laser. The combination of technological challenges associated with in vivo SRS detection make the implementation of this technique non-trivial, however, the sensitivity and background-free nature of this CRI modality holds significant potential and will be the focus of on-going investigations.These approaches have all utilized CARS imaging; however, the confounding non-resonant background signals that coincide with CARS imaging and the quadratic dependence of CARS signal with the concentration of the Raman scatterer are limitations for this approach. Stimulated Raman scattering, conversely, is background-free and exhibits linear concentration-dependent signals. Despite these features, there are, as yet, no 3.3et al. have utilized flexible, articulated arms and condensed the optical layout of the devices into more readily positioned tools that can accommodate human subjects and tissues in a variety of positions , conventional optical fibers exhibit many drawbacks for remote imaging applications for CRI.74Much like the tools developed to interface spontaneous Raman systems with tissues, CRI methods continue to see development in designs to interface with the patient. Improvement from large, rigid systems such as those first reported in 2011 by König ositions . Anotherin vivo clinical applications. The general decrease in size for the optical components is paired with challenges for miniaturization, potential for increased system aberrations, and limitations in performance: efficient fiber delivery of ultrafast laser pulses, efficient fiber optic collection for CRI signals, miniaturized devices for laser scanning and image formation, and design of miniature optics for high resolution imaging that are aberration corrected. Many of these efforts have focused on the excitation and image formation with optical fibers, yet have still relied upon conventional optical tools such as galvanometric scanners and commercial microscope objectives. Despite these challenges, Murugkar et al. took an alternate approach to develop a miniaturized handheld multimodal CARS, TPEF, and SHG microscope based on a microelectromechanical system (MEMS) two-dimensional scanning device and custom designed miniaturized probe for nonlinear imaging.75 Utilizing computer-aided design for the beam expander and collection optics within the custom-designed barrel, the system uses fast 2D scanning from the MEMS mirror with a 0.6 NA lens to achieve a 100 × 100 μm field of view and a 400 μm working distance. Chromatic aberrations between the pump and Stokes excitation pulses were compensated for using multiple optics and two differing glass types, ultimately yielding a 1.8 mm diameter barrel that was sealed with a thin glass window for immersion imaging. The silicon MEMS mirror employed was coated with aluminum for enhanced reflective performance in the NIR, and resonant operation was controlled using electronics to sweep the fast and slow axes of the mirror. The use of the MEMS mirror introduced a conical distortion in imaging, as the authors expected from the relative angle between the slow axis of the MEMS mirror and the incident beam, however, they suggested this could be corrected with appropriate post processing. This group further developed this work, ultimately culminating in the development of a multimodal CARS exoscope with the potential for non- or minimally-invasive in vivo imaging.76 This proof of principle work utilized a table top laser source and fixed or fresh rodent tissues for demonstrative purposes of TPEF, SHG, and CARS imaging; however, the development of such a handheld multimodal nonlinear imaging tool is indicative of the ongoing efforts to improve the flexibility and decrease the size of these technologies toward versatile translational devices.Capitalizing on the developments of optical fiber technologies compatible with ultrafast laser pulses, several groups have made efforts to develop CRI tools for portability, with handheld tissue interface devices that could one day be applied to et al. developed a two color synchronized picosecond laser system for CARS and SRS77 that was subsequently improved and built into the clinical histopathology system offered by Invenio Imaging.60 This effort opened the doors for further work in the coherent Raman community, with multiple fiber lasers demonstrated.61,62,64,78 While the rate of progress has been impressive, many of these systems have not yet been able to access vibrations across the Raman spectrum. Efforts beginning in the Fallnich lab, and now commercialized by Refined Laser Systems GmBH, led to the creation of a robust fiber laser for CRI capable of rapid tuning across the Raman spectrum in microseconds.79 This light source, which is portable and resistant to mechanical shock, can fit in a standard rack mount and holds promise for incorporation into portable CRI systems.In order to build a truly portable system, however, the light source for coherent Raman imaging must be built to meet and withstand the challenges of the clinical environment. Systems must be mobile, rollable, and bump-proof, with turn-key operation across a range of temperatures and humidities. Traditional ultrafast laser systems are based on free-space optics and make use of components such as mirrors and mirror mounts that can be sensitive to motion, mechanical vibration, and temperature changes. For this reason, many of the light sources used in laboratory CRI imaging have been restricted to laminar flow floating tables within temperature-controlled laboratory spaces. Fiber laser technologies offer considerable promise for building fully portable CRI systems, as they can be made relatively insensitive to mechanical shock and temperature changes. Engineering efforts led by Freudiger 3.4Optical microscopy tools, such as CRI, excel at high resolution imaging in relatively shallow depths. CRI requires both the penetration of light into tissue, as well as a tight focus to bias the nonlinear process. This has made applications of CRI in dermatology relatively straightforward, given both the relative ease of access to tissue as well as the depth of many skin structures of interest. To reach within the body, endoscopic approaches, in particular fiber optic endoscopic methods, are required.80 still hinder development and translation. There remains a need for stable ultrashort pulsed laser excitation sources and means to efficiently deliver ultrafast pulse train light to distant locations in the body without pulse and wavelength perturbations. Generating images in situ remains challenging in small endoscopic form factors, requiring laser scanning minimization to the millimeter scale with scanning speeds faster than the dynamics of the target systems to monitor changes characteristic of biological processes. Finally, there also must exist efficient methods to acquire the scattered light signal for detection. All of these features must be compatible with optical system designs that can maintain flexibility while still being compact enough to interface with existing medical equipment and interrogate organs and tissues within the body. Thankfully, developments in CRI share common needs with other nonlinear imaging modalities including TPEF, three photon excited fluorescence (3PEF), SHG, and third harmonic generation (THG), making work across these fields highly synergistic.Compared to free-space optical systems for non-linear optical microscopy, the nascent field of fiber optic nonlinear optical microscopy is still in a period of exploration and discovery. Many of the same challenges that have existed for over a decade in this field18,80 Conventional single mode fibers (SMF) have been the choice for imaging as they enable optical coupling with near diffraction limited spot sizes by allowing propagation of only a single spatial mode which improves image formation. However, this performance is paired with lower NAs and smaller core diameters which confer reduced light collection efficiency in comparison to multimode optical fibers. Early work in the development of CARS endoscopy by Légaré and Evans demonstrated the use of a step index silica SMF to couple 5–7 ps laser pulses which enabled excitation and image acquisition of 0.75 μm polystyrene beads based on the νs CH2 stretching mode (2845 cm−1).74 Here, the authors calculated the threshold power limits for self-phase modulation and self-focusing; utilizing excitation powers below this threshold, a 1 m SMF was selected for this proof-of-concept investigation as they noted that longer fiber lengths induced significant spectral broadening. The spatial resolution obtained by this system was defined by the focusing optics selected, and efficiently collected epi-CARS signals from small (0.75 and 5 μm diameter) beads. However, multiply forward scattered CARS signals, which are a primary source of contrast in thicker samples such as tissue, were not captured due to the SMF acting as a confocal pinhole. Despite the insensitivity to forward scattered CARS signals due to the collection optics used, this work fundamentally demonstrated the potential for CARS endoscopy, yet highlighted the limitations for imaging within deep tissue cavities, as only 1 m of optical fiber was used here and greater SMF lengths induced imaging aberrations.One of the primary fields of development that continues to drive progress towards CRI endoscopic imaging is advancement in optical fiber technology. As a relatively flexible and compact medium for light transport, optical fibers have long been used with biomedical imaging systems spanning a range of complexities.et al. was further able to demonstrate the design and testing of a combined CARS and SRS endoscope system for tissue imaging.81 Here, the authors coupled both pump and Stokes beams through a 1 m polarization maintaining fiber and the image was scanned using a miniature spiral scanning piezoelectric actuator. Light delivery into the tissue was achieved through a gradient indexed (GRIN) objective lens at the distal tip of the fiber and collected using a 10 mm × 10 mm photodiode at the tissue interface. Similar to the only report of epi-collection SRS imaging in human skin, this approach requires a large detection surface at the tissue interface to collect sufficient multiply-forward scattered SRS photons to generate images, and demonstrated depth sensitive image acquisition for lipid and protein structures in mouse skin and hair. This work further highlights the challenge for adequate detection of nonlinear coherent Raman scattering signals for endoscopic application, as the detector element utilized here is not compatible with the accessory channels of conventional endoscopes, indicating the need for further development towards clinically relevant designs for endoscopic SRS imaging.Adapting the initial system developments reported for SRS imaging, Saar 82 Wang et al. implemented a four wave mixing (FWM) suppression approach83 that enabled the delivery of pump and Stokes light as well as the collection of CARS generated signals using a single multimode fiber.84 In this and subsequent reports from the same group, the pump and Stokes beams were coupled into the single mode fiber at distinct polarizations, then combined at the distal tip of the fiber prior to sample illumination and paired with an array of detection fibers for improved collection efficiency.85 Other methods, using GRIN lenses with multicore imaging fibers86,87 or multimode GRIN fibers,88 have recently been reported as well. These approaches enabled the use of laser scanning or spatial light modulators proximal to the fiber in order to achieve the desired focus at the distal fiber tip, and were capable of image formation with reasonable SNRs. While the frame rates achieved in these reports are still slow compared to the speed of some dynamic biological processes, these initial demonstrations are promising developments towards fiber based in vivo CRI and multimodal endoscopy systems.In an effort to achieve endoscope designs with multimode fibers that typically exhibit reduced self-phase modulation and increased coupling efficiency,80 An important consideration, especially when economical use of space is required, such as with flexible endoscope design, is that copropagating laser pulse trains are capable of generating FWM signals at the CARS frequency which can interfere with image extraction, and may necessitate the use of separate excitation and collection fibers.89These studies applied single and multi mode fibers for CRI, however, they were limited to a fiber length of roughly 1 m to mitigate nonlinear processes that degrade image formation. In the case of nonlinear optical excitation in longer fibers, the performance of single mode fibers significantly hinders excitation and image formation. Nonlinear excitation pulses (often ≥80 fs to ≤7 ps in duration) are altered through spectral and temporal broadening from group-velocity dispersion, self-phase modulation, and potentially cross-phase modulation (XPM) if two colors of pulse trains are co-propagated. Advanced optical fibers based on structured crystal arrays  have improved the transport performance of light delivery for nonlinear optical microscopy, enabling endlessly-single mode delivery of ultrashort pulses.et al. marks one of the advancements in fiber technology with potential to mitigate some of the effects of nonlinear excitation for CRI.90 Here, by using pure fused silica in a stack and draw process, custom optical fibers were produced that surrounded a conventional hollow core PCF design with an outer annular silica waveguide for coupling of collected coherent Raman signals. As the excitation light is confined to the hollow core PCF and the multiply scattered light generated in the sample is mostly coupled through the annular silica waveguide, this design was capable of both CARS and SRS collection. Similar to the larger surface area for multiply scattered SRS signals previously reported by the Xie group, the inclusion of a larger source-detector offset in this fiber design aided in the collection of SRS signal, and indicates the potential for further improvement and integration for CRI fiber endoscopes. A more recent development using a double cladding hollow-core fiber with a Kagomé-lattice and an embedded microsphere was further reported by this same group  with high uniformity and minimal distortion. Despite this performance, long imaging times were required, but the authors reported that performance could be improved by controlling chromatic aberrations, laser spot sizes, and focal spot sizes. The ability to optimize system designs to meet application specific needs will be crucial for these technologies to impact clinical medicine and surgery in the years to come.Some of the same technological developments for flexible CRI endoscope systems have been adapted for rigid endoscope designs to obtain high resolution imaging with large fields of view. Zirak 4in situ, Raman approaches have the potential to provide new diagnostic information, guide therapeutic planning and outcomes, and open up new areas of investigation. The pace of innovation, particularly in the coherent Raman imaging community, has been rapid over the past decade, with new advances in fiber lasers, fiber optics, and computational resources driving the translation of Raman spectroscopic imaging tools.94,95 These innovations in the hardware, the analysis, and the medical application space continue to enhance the versatility of Raman scattering based methods to achieve the high-speed imaging that is needed for clinical applications.Raman tools offer considerable benefits in both current and future clinical applications. By providing chemically-selective contrast without the need for labels As optical tools, Raman methods have the advantage of being complementary to a wide range of existing optical imaging and spectroscopy methods. For example, Raman spectroscopy is routinely paired with white light and fluorescence imaging, while coherent Raman imaging can readily be carried out simultaneously with multiphoton fluorescence and harmonic imaging. This complementarity has allowed a myriad of imaging studies utilizing different contrast mechanisms that can provide prompt information to clinicians. This is of great importance when introducing new imaging tools into the clinical workflow, as physicians, nurses, and caregivers are already trained and proficient with numerous existing tools. Pairing Raman imaging methods with well-known, established imaging approaches, such as white light or fluorescence contrast, has the capability of leveraging existing expertise and familiarity to build and augment future clinical tools. In dermatology, for example, there has been a growing number of physicians trained in the use of reflectance confocal microscopy (RCM) for the diagnosis of skin lesions. It is relatively easy to build both CRI and RCM into the same device, with RCM contrast providing an important gateway and guide for dermatologists interested in using coherent Raman methods.96–100 With the continued increases in imaging speed, unprecedented amounts of data are being generated by biomedical studies visualizing and quantifying dynamic processes. There are vast opportunities in the acquisition and analysis of Raman data. For example, a time-lapse hyperspectral volumetric coherent Raman dataset, such as those acquired with devices developed in the Cheng lab,101 can be hundreds of gigabytes in size and require considerable computational power to extract meaningful information. For the Raman community, developing analytical tools that are suited for overwhelming amounts of data, for storage, processing, and analysis, will required retooling of many of the advanced analytical approaches that have been employed thus far. There has been considerable progress integrating artificial intelligence and machine learning methods into pipelines in recent years. These automated data analysis approaches that leverage machine learning will likely be extremely important in sifting through such high dimensionality clinical datasets.64,102 Efforts thus far are very much the tip of the iceberg: major advances in Raman data analysis techniques have begun to focus on handling the volumes of high-dimensional data generated during a single experiment, yet the expected developments that continue to focus on these efforts in the near-term will drive future clinical translation.While this review has largely focused on optical hardware, equally important for clinical translation is the software that not only runs clinical devices but also drives the analysis of the generated image data. Spectral data is inherently high-dimensional and as such Raman scattering methods have led to the adoption and continued development of advanced chemometric methods to analyze both point-based and imaging data.via chemometric analysis methods. In a similar vein, many of the hyperspectral CRI techniques developed also acquire continuous spectra, albeit over relatively narrow spectral ranges. These approaches, however, contain considerable extra information, as the spectra are essentially over-sampled depending upon the complexity of the samples and the correlations between distinct Raman features. Work to optimize data collection has been a topic of great interest for decades, attempting to enhance data acquisition speeds by ignoring redundant or non-informative information. Laboratory based methods to selectively acquire spectral data while still capturing salient differences within a sample have been performed using a variety of approaches including multivariate optical computing,103 compressive sensing,104,105 and low spectral resolution.106,107 Other approaches have sought to use hyperspectral Raman image content to efficiently collect sparse spatial features of a sample25,101,108–111 while still providing biochemical contrast. Further efforts combining both spatial and spectral sparse sampling have been demonstrated as well112 as a method to acquire Raman spectral imaging data in a rapid and efficient manner. Each of these techniques seeks to maximize the sample information obtained for either spectroscopic or imaging methods in the least amount of time, a necessity for the translation of clinical tools. These developments in instrumentation and algorithms for determination of sparse sampling patterns have also led to investigations of numerous analytical methods to determine efficient sparse spectral feature selection by which to sample Raman spectral information with the goal of reducing data acquisition times for both laboratory and clinical applications.113–117 Continued development of these approaches for both spontaneous and coherent Raman imaging methodologies may enable selective sparse spectral or spatial tools that are capable of acquiring efficient hyperspectral Raman data at sufficiently high speeds to visualize and quantify dynamic processes in cells and tissues and may offer the ability to translate Raman tools for applications requiring rapid time resolutions including pharmacology, histology, or surgical guidance.There is also a similar drive in Raman imaging to “do more with less”. Traditional Raman spectroscopy has relied on the acquisition of high resolution, low signal-to-noise spectra that can either be interpreted or quantified Beyond these technological leaps, there certainly exist many engineering and regulatory barriers that must be overcome to truly translate Raman imaging methods to the clinic. In some ways, adoption of Raman methods for clinical utility has been limited due to applications – there has yet to be a break-through use for Raman spectroscopy or imaging into the clinical or surgical space. Advances in spontaneous or coherent Raman histopathology may prove to be this tipping point, however continued development across the broad application space may yet identify another candidate use. This push will hopefully be both facilitated by and drive the development of technology, which will in-turn help to expand developers of optical hardware and democratize techniques by making instrumentation more affordable. The opportunity to obtain continued funding from government and private agencies to develop and apply Raman imaging tools to address major needs in the healthcare sector is extremely important. Continuing to push these entities to prioritize optical and imaging technologies to solve biomedical problems must be a point of emphasis for academic, industry, and professional organizations alike. The focus of the translational biophotonics community must be to continue to creatively apply these tools to solve health challenges that impact the healthcare economy while improving patient care, outcomes, and quality of life. Especially given the sensitivity of these tools for such a wide array of biomedical applications, making Raman imaging systems affordable and translatable for global healthcare is a major hurdle that requires the attention of the entire community, but has not been widely addressed. In fact, most current Raman imaging devices are bespoke creations, which is ideal for early phase development, but makes eventual clinical translation challenging. Working groups will need to be formed to establish clear standards and benchmarks for devices and analysis methods following, for example, the path laid out by optical coherence tomography (OCT) working groups and standardization protocols that paved the way for the many current clinical uses of OCT. This step will require buy-in from academic leaders, engineers, industry partners, government agencies, and regulatory bodies. For any major use in the clinic, Raman imaging methods will need methods of payment and reimbursement. The recent success of RCM gaining CPT codes shows that such an approach is not only possible – it is absolutely necessary to bring new diagnostic imaging methods to the bedside.CLE is an inventor on patents for CARS microscopy that have been licensed to multiple microscope manufacturers.


This case report study aims to identify the differences in the ground reaction forces (GRF) placed on the forefoot, hindfoot, and entire foot between the paretic and non-paretic legs in two stroke patients to identify potential targets for improved physiotherapy treatment. A digital gait analysis foot pressure insole was fitted inside the participants’ shoes to measure the percentage of body weight taken during the stance phase, and the vertical GRF of the two subjects are reported in this paper. Both patients presented noteworthy differences in gait parameters individually and between their paretic and non-paretic legs. The trend shows a decreased percentage of body weight on the paretic forefoot and hindfoot, although the percentage bodyweight placed on the entire foot remained similar in both feet. The gait patterns shown were highly individual and indicated that both legs were affected to some degree. These findings identify key motion targets for an improved physiotherapy treatment following a stroke, suggesting that physiotherapy treatment should be targeted and individually tailored and should include both extremities. The characteristics of normal human walking include a cyclical upward vertical shift of the body’s centre of gravity that moves through the cycle of vertical motion with each step or two cycles during each stride (100% gait cycle) .An abnormal gait pattern is one of the most significant contributions to functional disability post-stroke ,4. GrounThis study reports two distinct bodyweight distribution gait patterns following stroke, for both paretic and non-paretic legs, and discusses a need for a tailored physiotherapy intervention to correct the potentially debilitating complications of an abnormal gait. The gait patterns in this report were characterised by the vertical GRF measured at the hindfoot, forefoot, and entire foot when walking at comfortable walking speeds. The vertical GRF was measured using plantar pressure insoles from the SmartStep™ Gait System Andante Medical Devices (Israel) and reported as a percentage body weight.We present the vertical GRF of two patients with ischemic stroke verified through the computerised tomography (CT) scans in which percentage body weight (% BW) placed on the paretic and non-paretic legs was measured using a digital gait analysis tool B,C. NeitThe entire foot vertical GRF can be further analysed and segmented to GRF at the hind and forefoot. The gait cycle of the second study participant, a 73-year-old woman six months post-stroke, is shown in The individual analyses of the gait patterns show how altering the loading weight on the leg may alter the motor output pattern. In addition, we noted that a gait abnormality in the paretic leg could affect the foot trajectory and placements of the opposite non-paretic foot, thereby affecting the entire gait cycle. Thus, our findings suggest that individual gait parameters should be measured in all patients following stroke, and physiotherapy treatment should focus on appropriate foot contact for paretic and non-paretic lower limbs . This apOur findings are, however, inherently associated with some limitations. In particular, each leg was assessed only once, without a trial run. It is acknowledged that performing more trials may have improved the results’ reliability ; howeverThis study provides supportive evidence that the entire gait pattern in the paretic and non-paretic legs may be affected following a stroke, indicating that a more patient-centered approach to physiotherapy intervention is needed.


The PTs used included off label use , drug ineffective , product use in unapproved indication , pathogen resistance , and drug resistance . 54% of the reports were on Watch antibiotics and 19% were involved in the Reserve group. In the Watch group, “off label use” and “product use in unapproved indication” were the most frequent PTs and the majority of reports on Reserve antibiotics were coded as “Off label”. A sharp increase in the number of reports was observed in the three consecutive years with 21 in 2013, 54 in 2014, and 83 in 2015; (4) Conclusions: In addition to existing AMR monitoring strategies, pharmacovigilance databases can serve as a source of data on suspected resistance and inappropriate use. Future research should explore how these AMR-relevant MedDRA Terms are used in resource-limited settings with less capacity to generate laboratory-confirmed resistance data.(1) Background: Antimicrobial resistance (AMR) requires urgent multidisciplinary solutions, and pharmacovigilance has the potential to strengthen current antimicrobial stewardship strategies. This study aimed to characterize AMR-relevant adverse drug reaction (ADR) reports submitted to The Netherlands Pharmacovigilance Centre; (2) Methods: We carried out a descriptive analysis of ADR reports submitted to Lareb, coded with AMR-relevant MedDRA Preferred Terms (PTs); (3) Results: Between 1998 and January 2019, 252 AMR-relevant ADR reports were submitted to Lareb. The most frequent antibiotics were tobramycin ( Antimicrobials include a broad range of medicines used to prevent and treat infections in humans, animals, and plants . These mAntimicrobial stewardship refers to efforts that encourage the responsible use of antimicrobials with the aim of minimizing the development of resistance and including actions that minimize dose and duration of treatment and ensure use of the correct antibiotic ,4. WhilsPreserving antibiotic effectiveness while ensuring universal access is at the heart of public health dilemmas, as policies for good access must be accompanied with strong measures to minimize inappropriate use that would lead to further resistance ,13.To address the issue of availability while ensuring appropriate use, since 2017, the Word Health Organization (WHO) Essential Medicines List (EML) includes a classification of antimicrobials into three categories known as “Access”, “Watch”, and “Reserve” (AWaRe), based on the indication, availability, and awareness . A globaAs the world puts in place various measures to curb the rising threat caused by the rising resistance to existing antibiotics, specific pharmacovigilance data could constitute an important part of the wider multi-disciplinary approaches used for resistance surveillance and warning. The AWaRe classification is a useful tool to be considered by monitoring activities targeting specific antibiotics.Pharmacovigilance is the science of the activities relating to the detection, assessment, understanding and prevention of adverse effects or any other possible drug-related problems . AdverseEstablished in 1968, the WHO Program for International Drug Monitoring (PIDM) had The Netherlands as one of its ten founding members. Since then, the program has expanded to include 145 full member countries and 26 associate member countries . As a foThe objective of this study was to characterize ADR reports in the database of The Netherlands Pharmacovigilance Centre (Lareb) following use of antibiotics and coded with MedDRA Preferred Terms that suggest suspicion of resistance, ineffectiveness, off-label use, or medication errors (RIOLE).(a)Reports on Antibiotics classified under the Anatomical Therapeutic Chemical (ATC) Classification ATC J01 or ATC J04.(b)Reports coded with at least one of the following MedDRA (version 21.1) Preferred terms and codes included the following: pathogen resistance (10034133); drug ineffective (10013709); treatment failure (10066901); drug resistance (10059866); therapeutic product ineffective (10060769); therapy non-responder (10051082); decreased activity (10011953); drug ineffective for unapproved indication (10051118); therapeutic response decreased (10043414); multiple drug resistance (10048723); off label use (10053762); medication error (10027091); product use in unapproved indication (10076476); contraindicated product administered (10078504)We carried out a descriptive analysis of ADR reports in the database of The Netherlands Pharmacovigilance Center (Lareb) database. Patients and healthcare professionals can report directly to Lareb. Marketing authorization holders reports directly to Eudravigilance. The reports are then forwarded to Lareb so that Lareb has a complete overview of reported ADRs which have occurred in the Netherlands. Reports fulfilling the following criteria were included:For each report meeting the criteria in , the following information was collected and included in the dataset for further analysis: report identifier; suspected ADR; year of report; reporter type; suspected drug; indication and action taken.n = 89; 35%), colistin , ciprofloxacin , doxycycline , and aztreonam . The most frequently used PTs were off label use , drug ineffective , product use in unapproved indication , pathogen resistance , and drug resistance .Between 1998 and January 2019, a total of 252 ADR reports (study sample) were submitted to Lareb using a PT or a combination of PTs that suggested suspicion of AMR or use-related issues . The following antibiotics were the most frequently reported as suspected causes of AMR-relevant ADRs: tobramycin  and product use in unapproved indication . More than half of the 91 reports coded with PT off label use described events in patients on tobramycin as the suspect drug ; additionally, 24 (26%) were on colistin. The reports coded as product use in unapproved indication were predominantly on tobramycin . Out of the 252 reports of the study sample, 35 (14%) were coded each with more than 1 PT, combining PTs that refer to suspicion of both resistance and use-related issues.As shown in As shown in The 91 off label use ADR reports include predominantly tobramycin (Watch) and colistin (Reserve) as the suspected drug with 53 (58%) and 24 (26%) reports, respectively.From the 252 ADR reports submitted over a period of about 20 years, 82 (34%) reports were submitted in 2015 as illustrated by As the world seeks and puts in place strategies to tackle rising AMR, living reviews of pharmacovigilance data should be seen as a strong potential source of data on trends in suspected resistance and possible irrational use of antimicrobials. The present analysis of the Lareb database has shown that the AMR-relevant preferred terms can be identified in a national spontaneous reporting database.These pharmacovigilance data can signal use-related issues which can be used to provide a bigger picture to prescribers who have a choice to make during each consultation. Reports on off-label use or drug use in contraindicated indications can be shared with entities responsible for national policies on antimicrobials use to timely inform the decision-making process. The pharmacovigilance data also identified reports with antibiotics belonging to the Reserve and Watch list, which is of special interest from an AMR perspective. Analysis of these reports can possibly lead to information regarding how and why different Watch and Reserve antibiotics are potentially overused or used off-label, depending on the indications and available formulations. In this study we have noted an increased number of reports in the period from 2013 to 2015. A spike in reports can also signal that something has changed regarding the drug. By analyzing a reporting spike, it is possible to see if there are changing in how a drug is being used.In this study, most reports were submitted by manufacturers, and this makes it more difficult to interpret what the data mean in the context of identifying AMR-related issues. It should be noted that The Netherlands has an advanced regulatory pharmacovigilance system with stringent rules for reporting . The surge in reports needs to be interpreted in the light of both clinical relevance as well as reporting obligations for MAHs. It is not clear if the spike represents a difference in use or just that it was not reported in earlier years. The 2015 peak may be related to an intensified reporting from specific MAHs responding to reporting obligations, following up specific cohorts involving for example tobramycin and colistin. However, without more detailed reports from the responsible MAH, it is impossible to have a solid explanation of the reasons behind the peak. Therefore, future research focusing of this intersection between antimicrobial resistance and pharmacovigilance should also pay more attention to the specific reporting obligations that MAHs must comply with.In many countries, health care professionals play a crucial role in gathering and submitting safety data to competent authorities. Manufacturers rely on health care professionals working on clinical trials or seeing patients in clinics to provide solicited or unsolicited safety data on products. According to the Guideline on Good Pharmacovigilance Practices Module V, in their risk management plans, manufacturers are required to address undesirable clinical outcomes for which there is sufficient scientific evidence that they are caused by the medicinal product .If the drug safety community agrees that resistance or ineffectiveness are undesirable clinical outcomes following use of antimicrobials with the intention to prevent or treat a disease, the manufacturers should consider the use of AMR-relevant MedDRA terms in collecting data to inform their risk management plans. The Guideline on Good Pharmacovigilance Practices also indicates that reports of adverse reactions may be derived from multiple sources including spontaneous data sources and may be linked to situations such as off label use and medication errors. If the concerned medicinal product is antimicrobial, competent authorities should consider the risk associated with off label use and medication in the antimicrobial stewardship context.This study shows that a national pharmacovigilance database has reports coded with AMR-relevant PTs. However, as some pharmacovigilance centers may have limited capacity and skills to assess received ADR reports and assign them with a correct code, the replicability of this study could be difficult, especially in countries with a weak pharmacovigilance system.Further, as this study was conducted in a country with stringent regulations for manufacturers, the reproducibility could be difficult in countries with weak regulatory capacity.Expanding the role of pharmacovigilance requires both promotion of existing tools and education for the potential reporters of observed or suspected effects. In this study, the analyzed reports include those submitted by manufacturers, and there may be other potential similar cases that went unreported by prescribers and patients.Promoting the existence of AMR-relevant MedDRA terms and explaining their relevance to surveillance of antimicrobial resistance could lead to increased submission of similar reports from prescribers and patients. Public health will gain from different angles if pharmacovigilance is integrated in the antimicrobial stewardship programs package. pharmacovigilance centers at country level should be encouraged to actively promote these AMR relevant PTs and invite reporters to collect and send this information to relevant agencies. By getting actively involved in this process: (1) pharmacovigilance centers will receive more spontaneous reports, and the centers’ work will be more visible and appreciated by other public health stakeholders; and (2) suspected AMR could be timely detected, potential clusters could be highlighted and, if necessary, ad-hoc microbiological tests could be conducted. The integration of pharmacovigilance in this process could lead to a win-win situation for different scientific disciplines tackling AMR from traditionally isolated perspectives. Pharmacovigilance is already a multidimensional science with potential to expand further. Tackling AMR questions using the existing pharmacovigilance methods will also provide an opportunity for pharmacovigilance as a field to evolve further and countries will see more value in investing in their pharmacovigilance systems. As technology further advances the field of pharmacovigilance, methods traditionally used in post-marketing drug safety monitoring have the potential to serve as surveillance strategies for antimicrobial stewardship programs.


Machine learning techniques, also known as artificial intelligence (AI), is about to dramatically change workflow and diagnostic capabilities in diagnostic radiology. The interest in AI in Interventional Radiology is rapidly gathering pace. With this early interest in AI in procedural medicine, IR could lead the way to AI research and clinical applications for all interventional medical fields. This review will address an overview of machine learning, radiomics and AI in the field of interventional radiology, enumerating the possible applications of such techniques, while also describing techniques to overcome the challenge of limited data when applying these techniques in interventional radiology. Lastly, this review will address common errors in research in this field and suggest pathways for those interested in learning and becoming involved about AI. Artificial intelligence (AI) has been prominent in different fields including diagnostic radiology. AI breakthroughs are now also empowering the field of interventional radiology (IR) and recent surge in popularity was initially driven by the phenomenal success of deep neural networks in processing unstructured data such as images and audio through pattern recognition. The term AI has come to encompass all forms of machine learning (ML). In this review the term AI is used synonymously with ML, referring to techniques that construct predictive models from data, including deep learning, radiomics and other traditional machine learning techniques. The importance of the usage of AI is summarized in Table .Table 1A brief history of the field is difficult to summarize given its fragmented nature; however, the most popular techniques currently, artificial neural networks, date back to work by Rosenblatt on the cArtificial neural networks are inspired by the connectionist design of biological neural networks, comprisAI using artificial neural networks were recently re-popularized in 2012 by Krizhevsky et al.  with theRecent research in medical imaging AI has focused on 3D CNNs such as 3D versions of popular 2D CNNs such as EfficientNet or Densenet.  AlternatOne limitation of neural networks is that most deep learning algorithms have been restricted to data-rich domains such as photography or speech recognition, as training these algorithms requires large datasets. Radiology is well suited to this, being a data-rich specialty born into the information age, with explosive growth in AI research in diagnostic radiology. InterveIn comparison with other interventional and procedural fields such as surgery or endoscopy, IR is data-rich. IR is one of a few specialties where a record is kept of the entire procedure in a standardized format, is available retrospectively and these datasets are mostly unexploited today. With the recent developments in few shot learning made by the deep learning community, novel tPotential applications of AI in IR can be divided into pre-procedural, peri-procedural and post procedural.Better patient selection is similar to the concept of precision medicine. AI decision support systems may help tailor treatment decisions based on imaging phenotypes, yielding better clinical results.Interventional radiologists often rely on multidisciplinary boards for oncological treatment strategies. These board discussions perform multiparametric risk-stratification, integrating the patient’s full data before a treatment is advised.Several AI applications replicate and outperform these discussions by predicting the outcome from data available in each specialty . The ability to incorporate clinical information, radiomics and genetic information may improve the objectivity and accuracy of decision-making. Such an approach could potentially play a role in triaging patients for IR and subsequent therapy by assessing risks and making predictions about therapeutic outcomes An example of this application in the field of acute ischaemic stroke is the use of CT perfusion software in endovascular clot retrieval to estimate physiological parameters such as ischaemic core and penumbral volume, facilitating the selection of patients who are likely to have an optimal outcome. AI approaches to identifying patients for clot retrieval are being investigated, for instance based on CT angiography rather than CT perfusion. –17Pretreatment patient selection using deep learning is also being investigated for interventional oncology. Morshid et al.  describeMultimodal planning may also integrate genetic information using AI models. Ziv et al.  trained AI can improve interventional procedures by accelerating computationally intensive or manual procedures, such as the correction of translational motion via pixel shifting in angiography. Traditional image registration techniques such as those proposed by Meijering et al.  are compDeep learning approaches have also been applied to identifying guidewire and catheters during angiography . Such meAI-based ultrasound guidance  has beenThe selection and personalization of endovascular devices is another area for AI. Yang et al.  used AI Cho et al. developeAI has been proposed for skin dose estimation by taking into account angulation of the X-ray tube and tissue density. Radiation exposure during endoscopy has been reduced using an AI-equipped fluoroscopy unit with an ultrafast collimation system that reduced radiation exposure by ~ 38%. Similar techniques could be used in interventional radiology. Respiratory motion compensation in PET/CT imaging has been implemented via elastic motion correction algorithms where AI determines a blurring kernel between a single motion corrected image and a single non-motion corrected target image. This results in a final image with reduced motion. SimilarFollowing treatment, AI has a role to play in measuring response to treatment, prognostication and determining future management.Most criteria used in diagnostic radiology for treatment response were not developed for interventional radiology, which may lead to misevaluation during follow-up. AI research could help better assess these specific treatment responses. AI can be useful in longitudinal studies during follow-up of treatments to detect subtle changes between images identifying disease progress or recurrence earlier.In oncology, automated volumetric measurements of tumour sizes or response evaluation criteria in solid tumours (RECIST) reads may be possible through deep learning. . RECIST Procedural findings and histological features can also play a role in the choice of adjuvant therapy as suggested by Saillard et al. who builSimilarly, AI has a role in assessing response to treatment in acute ischaemic stroke. Thrombolysis in cerebral infarction (TICI) scores are often used to grade results following endovascular clot retrieval. AI can improve interobserver reliability and thereby improve the utility of such scores in prognosticating patients. , 37 AI aWhile genetics and molecular pathology have played a large role in precision medicine, pre- and post-treatment imaging may identify additional disease phenotypes as well as quantify intervention success, which may help fine-tune management by prognosticating as well as determining the timing and need for follow-up imaging. The breadth of potential applications of AI in interventional radiology has seen a rise in academic papers published on this subject. Such projects face a common set of challenges..The major challenge facing AI in interventional radiology is the relatively small dataset sizes when compared to diagnostic radiology, or in fact, to other non-medical applications of AI entirely. For instance, ImageNet, a widely used natural imagery database, contains over 14 million images.  In contrPerhaps the most simple method to reduce the number of samples required for a useful model is transfer learning, where models trained on different datasets might be used as a starting point, as information that these models might have learned from other datasets may be translated to this setting as well. Other approaches include the use of handcrafted features, an approach popular in the “traditional” computer vision literature in the early 2000s. These approaches, also known as radiomics when applied to imaging, reduce the number of required samples as the model does not have to learn the low-level features itself.Another approach is to use data augmentation – standard transformations like affine transforms, adjusting brightness and contrast are useful, but novel augmentation techniques like MixUp  may helpRecent developments in the deep learning field in semi-supervised learning, such as few-shot and zero-shot learning techniques , 43–46, For categorical data, such as models using clinical variables like age and sex, oversampling techniques such as synthetic minority oversampling technique (SMOTE)  may helpSmall dataset sizes also exacerbate common mistakes made in AI projects. The use of checklists  may helpThe training and testing datasets must also have defined inclusion and exclusion criteria to prevent “Frankenstein” datasets, where pTo prevent overstating the significance of any result, especially in small datasets, any measure of performance such as the accuracy or the area under the receiver operating characteristic (AUC) should be accompanied with confidence intervals. When applicable, AI models trained on images should be compared to a baseline clinical model using age, sex and other clinical features. If an AI model uses both imaging and clinical features, a sensitivity analysis should be performed by systematically modifying each input to assess its contribution on the final prediction.  In post-Another source of unreliability stems from the constant evolution of clinical practice over time due to the introduction of new treatment approaches, technologies or changes in patient population . InterveThe use of AI in augmenting interventional radiologists is likely to increase as research in pretreatment, intra-treatment and post-treatment applications translate into clinical practice. Due to the potential benefits and risks for patients, stringent prospective evaluation such as controlled trials should be undertaken where necessary to ensure that promising applications translate well.Given the promise of AI in interventional radiology many clinicians may wish to get involved in AI research and development. Key factors to be able to successfully translate a project into clinical practice include a clear understanding of the clinical benefits andadvantages of using AI, the availability of data measured in independent samples , the use of computing resources such as graphics processing units or tensor processing units and the technical skills to construct an AI model.Specific steps around training and coding of AI models are beyond the scope of this review article; however, it is becoming easier the advent of open source deep learning framework libraries such as Pytorch  and TensThe emergence of novel deep learning techniques and applications in interventional radiology is hugely exciting and offers multiple opportunities to aid in patient selection for intervention, improve patient care during interventional treatment and optimize post-treatment clinical follow-up. Interventional radiology with its smaller dataset sizes compared to diagnostic radiology stands to benefit from novel techniques such as semi-supervised learning, zero and few shot learning in the deep learning literature. The application of such techniques in interventional radiology must be rigorous and generalizable, and common errors must be avoided in order for successful clinical translation.


Paraplegia in aortic surgery is due to its impact on spinal cord perfusion whose hemodynamic patterns (SCPHP) are not clearly defined. Detailed morphological analysis of vascular network and collateral network modifications within Monro–Kellie postulate due to the fixed theca confines was performed to identify SCPHP. SCPHP may begin with intraspinal “backflow” (I-BF), that is, hemorrhage from anterior and posterior spinal arteries, backward via the connected anterior and posterior radicular medullary arteries, through the increasing diameter and decreasing resistance of segmental arteries (SAs), off their aortic orifices outside vascular network at 0 operative field pressure. The I-BF blood bypasses both intra- and extraspinal capillary networks and causes depressurization (0 diastolic pressure) and full ischemia of dependent spinal cord. When the occlusion of those SAs orifices arrests I-BF, the hemodynamic pattern of intraspinal “steal” (I-S) may take place. The formerly I-BF blood, in fact, is now variably shared between the fraction maintained in its physiological intraspinal network and that keeping flowing as I-S through the extraspinal capillary network. I-S is, however, counteracted by the extraspinal “steal” from the connected mammary/paraspinous-independent extraspinal feeders, all physically competing for the same room left by the missed physiological SA direct aortic blood inflow. Steal phenomenon evolves within the 120-hour time frame of CNm, whose intraspinal anatomical changes may offer the physical basis within the Monro–Kelly postulate, respectively of the intraoperative and postoperative paraplegia. The current procedures could not prevent the unphysiological SCPHP but awareness of details of their various features may offer the basis for improvements tailored, to the adopted intra- and postoperative procedures. The extensive thoracoabdominal aortic aneurysm repair (TAAAR) carries a significant incidence of ischemic spinal cord injury, despite the evolution of surgicalRecent experimental studies showed significant modifications of the arterial intra- and extraspinal network in the immediate postoperative period, opening new perspectivesThe arterial blood supply to the spinal cord  comprisAn important although inconsistent and highly variable part of the arterial supply to the spinal cord is provided by the anterior radiculomedullary arteries  has the peculiar feature of being entirely confined within a rigid osseous structure, the skull and vertebral canal,According to the Monro–Kellie postulate, the sum of the volumes of the brain–spinal cord tissue, cerebrospinal fluid, and intracranial–intraspinal blood is constant.Although the relationship between the vascular supply to the spinal cord and the neurological complications associated with aortic surgery was thoroughly analyzed in the early years of aortic surgery,Moreover, several cases of paraplegia that appeared in the postoperative period fully recovered almost immediately following insertion of a spinal fluid drain, usually maintained for a few days and then removed.Hemodynamic patterns of spinal cord perfusion vary with the circulatory conditions that may be either physiological, modified or extracorporeal, and established during and after the repair that may differ in open or endovascular procedures, as well as by various surgical options, and may include periods of total circulatory arrest. All that may obviously variably impact on the hemodynamic models as outlined below, allowing however to accordingly predict the effects on them.The harmful effect of backflow from the aortic orifices of the SA in the tract between the clamps was first described, as “steal” phenomenon, by Wadouh et alAnalysis of the arterial system excluded from direct SAs, aortic blood supply within the limits of aortic repair  permitsIt is clear that arterial intraspinal “backflow” (I-BF) may occur only through those branches of the SA that are directly connected with the major longitudinal arterial axes of the spinal cord, that is, the ASA mainly via the connected ARMAs , P”, maWithin the limits of the aortic tract under repair, the I-BF could not occur from all of the other arterial branches terminal to the spinal nervous tissue, including the terminal branches of the SA  can be predicted to occur via the internal mammary system backward through the intercostal arteries to each SA aortic orifice along the aortic tract under repair, as well as backward via the paraspinous longitudinal and side-to-side arterial connections of the posterior branches of the SAs  along the new backward pathway . When the SAs aortic orifices are blocked instead, it is uncertain whether and how much, if any, of this formerly back-flowing blood that fully bypassed the physiological capillary network of both intra- and extraspinal networks can now be shared, at each side of every metamere, between the fractions that can be kept within its physiological intraspinal network  from even a small breach in the wall of any single extrathecal branch of either the arterial network of the brain or the spinal cord segment.The ideal comparison of the common carotid arteries with the SAs of each spinal metamere may even better fit when considering the reperfusion phase where avoiding clots, debris and air embolism, and late false lumen thrombosis, all along the whole thoracoabdominal aortic tract in repairMoreover, reperfusion injuriesThe comparison between the configurations of the brain and spinal cord arterial systems makes also clear the different proportional widths of their respective intra- and extrathecal compartments  and, moIn fact, the extrathecal arterial network of each spinal metamere  includeThat difference favors the brain physiological intrathecal perfusion, when delivered through any of the current extracorporeal circulation techniques, also because its proportion with the extrathecal network does not vary during aortic arch repair.On the contrary, when only selected SAs are revascularized or intraoperatively perfused,These considerations may allow us to predict that prevention of backflow requires appropriate maneuvers depending on the open operative technique used. The steal phenomenon, on the other hand, accordingly to its hemodynamic pattern cannot be fully prevented other than by reestablishing perfusion of all SAs .Then full preservation of the whole SAs aortic perfusion with accurate prevention of any intraspinal thromboembolism is the ideal prerequisite to the paraplegia-free repair that is not yet constantly achieved with any of the current techniques and needs then shared efforts for applying new conceptual approaches.This article can be concluded with the following four points:Backflow is defined as the free hemorrhage from the orifices of the SAs within the aortic tract under repair that causes depressurization (0 diastolic pressure), bypass of intra- and extraspinal arterial capillary networks, and then full ischemia of the dependent spinal cord tract. Backflow can occur in conjunction with any open extended aortic prosthetic repair procedure.Steal phenomenon is caused by the occlusion of those same SAs, whose missed direct aortic blood supply leaves room at the extraspinal network for intraspinal blood “bad” steal at each side of every spinal metamere, particularly via critical ARMAs that is counteracted by extraspinal blood “good” steal potentially coming from mammary and paraspinal persistent feeders of extra spinal network. Steal phenomenon preserves diastolic pressure in both the intra- and extraspinal compartments and may be fully prevented only by keeping (cET) or restoring (revascularization) allSAs anatomical analogies with common carotids may suggest that prevention of air, debris, clots, etc., embolism at each side of every spinal metamere is as important as in carotid surgery.Reperfusion injuries and/or any blood–spinal fluid Monro–Kellie volumes conflicts are other possible, distinct paraplegia pathogenic events during aortic repair.


Branched-chain volatiles (BCVs) constitute an important family of fruit volatile metabolites essential to the characteristic flavor and aroma profiles of many edible fruits. Yet in contrast to other groups of volatile organic compounds important to fruit flavor such as terpenoids, phenylpropanoids, and oxylipins, the molecular biology underlying BCV biosynthesis remains poorly understood. This lack of knowledge is a barrier to efforts aimed at obtaining a more comprehensive understanding of fruit flavor and aroma and the biology underlying these complex phenomena. In this review, we discuss the current state of knowledge regarding fruit BCV biosynthesis from the perspective of molecular biology. We survey the diversity of BCV compounds identified in edible fruits as well as explore various hypotheses concerning their biosynthesis. Insights from branched-chain precursor compound metabolism obtained from non-plant organisms and how they may apply to fruit BCV production are also considered, along with potential avenues for future research that might clarify unresolved questions regarding BCV metabolism in fruits. Volatile organic compounds (VOCs) are essential components of fruit flavor, being necessary for human perception of the distinct flavors produced by the many different types of fruit found in nature . The impBranched chain volatiles are defined as those volatile organic compounds that contain a branched-chain functional group structurally similar to those of the branched-chain amino acids- valine, leucine, and isoleucine . Due to This review seeks to collate and evaluate published research regarding the biosynthesis of branched chain volatiles in plants, with an emphasis on these processes as they might occur in fruit crops. While BCV biosynthesis has been touched upon in other reviews on the subject of plant volatiles , a comprBranched-chain volatiles are ubiquitous components of fruit aroma volatile profiles. An examination of research literature concerning fruit volatile profiles found that 127 unique branched-chain volatile compounds were identified in 106 distinct types of edible fruit across 175 published studies . A list An overwhelming majority of the branched-chain volatiles identified in fruits are classified as volatile esters. Out of the 127 distinct BCVs identified in Branched-chain volatiles have been recognized as being crucially responsible for the distinctive flavor and aroma properties of many commercially important fruits such as apple, banana, melon, and pineapple, among others . In termBecause of the importance of branched-chain volatiles to the characteristic flavors of several important fruit crops much research has been done in trying to understand the general biosynthesis pathways that lead to BCV production, though this area remains relatively understudied when compared to the biosynthetic processes that produce other classes of important fruit volatiles such as terpenoids and oxylipins. The body of published experimental evidence regarding this topic points to four possible hypotheses regarding BCV biosynthesis , none ofThe oldest and most studied of the four possibilities, this hypothesis posits that BCVs are generated through the catabolic degradation of BCAAs in mitochondria. It has long been known that plants possess the capability to break down excess BCAAs into the energy-rich metabolites acetyl-CoA and propionyl-CoA and that several of the key enzymes involved in this process are localized to mitochondria . An exceSince numerous volatile esters are known to be biosynthesized in fruit tissue by alcohol acyltransferase (AAT) enzymes  and becaHowever, several difficulties remaining with this hypothesis indicate that it may not be generally applicable across all fruits. Evidence from tomato seems to show that BCAA catabolism may not be primarily responsible for the formation of BCVs in that fruit; when disks of tomato fruit tissue were fed elevated levels of BCAAs, no significant measurable increase in BCV quantity was detected as compared to control . FurtherBased primarily off of research done in tomato, this hypothesis posits that BCAAs are not the main source of carbon used for biosynthesis of fruit BCVs but that instead it is branched-chain α-ketoacids that fill this role. In this hypothesis, the biosynthesis of BCAAs proceeds as normal up until the last step, where instead of conversion to BCAAs by BCAT enzymes branched-chain α-ketoacids produced so far are directly exported to the mitochondria for BCKDH-mediated catabolism into BCVs and associated precursors. This hypothesis has several explanatory advantages. For one, it explains the findings in tomato that feeding excess BCAAs to tomato fruit tissue does not result in elevated BCV volatile production, while feeding excess BCKAs does . Anotherin vitro assays would show that BCKAs do not cause feedback inhibition of the upstream biosynthesis enzyme isoforms present in fruit, or the discovery and characterization of a chloroplast transporter expressed in fruit tissue that preferentially exports BCKAs before they can be converted to BCAAs by chloroplastic BCATs.Much more experimental evidence is needed to conclude whether or not this hypothesized pathway is involved in BCV biosynthesis in certain fruits. In particular, labeling experiments where deuterated BCKAs are fed to fruit tissue and deuterated BCVs are observed but not deuterated BCAAs would provide robust evidence for the validity of this hypothesis. Supporting evidence could include an observation that BCAT transcripts become drastically reduced in fruit tissue as compared to the other upstream BCAA biosynthesis enzymes. These It is important to note that this hypothesis may not be mutually exclusive with the BCAA catabolism hypothesis: it may be possible that fruit cells produce elevated levels of BCKAs while also simultaneously catabolizing BCAAs into volatiles. In fact, doing both might actually increase the quantity of carbon shunted into mitochondrial BCKDH-mediated volatile precursor production: catabolizing BCAAs would reduce inhibitory pressure on key BCAA biosynthesis enzymes which would then be free to produce greater quantities of BCKAs that would be directly used to support BCV production. Further investigation is needed to determine if such a scenario indeed occurs in fruit tissue in nature and if so, what quantifiable impact each pathway has on overall BCV production.13C-labeled acetate feeding and in vitro biochemical characterization of CMS and IPMI enzymes expressed in apple fruit tissue , an enzyme previously known to be involved in BCAA biosynthesis only in bacteria . Brieflyt tissue . SupportThe primary explanatory advantage of this hypothesis is that it enables the production of massive quantities of 2-methylbutyl volatile compounds in fruit without being subject to the feedback inhibition that large concentrations of isoleucine exert on threonine deaminase (TD), an enzyme that catalyzes the first committed step in isoleucine biosynthesis . Further15N-labeled BCAAs to tissue from fruits known to produce nitrogenous BCVs would be one way to empirically demonstrate such a role for this pathway. The biosynthesis of both types of branched-chain volatile compound have been shown to be accomplished without the involvement of the mitochondrial BCKDH enzyme complex, a key feature of the previous three hypotheses.The last possible mechanism of BCV biosynthesis is direct conversion of BCAAs into volatile compounds or immediate precursors. Rather than undergoing several steps of degradation through the established BCAA catabolism process before being incorporated into BCVs, this hypothesis proposes that some volatiles are directly transformed through enzymatic action into BCVs or the immediate precursors of such. Evidence from alfalfa and chickpea indicates that plants form branched-chain aldehydes and alcohols through this pathway: in both species, cDNAs for serine decarboxylase-like (SDC-L) enzymes were found that when heterologously expressed in bacteria produced enzymes capable of directly forming branched-chain aldehydes from branched-chain amino acids . BrancheIt is interesting to note that this pathway can theoretically provide a possible route for the biosynthesis of branched-chain acyl esters that also does not rely on the activity of the mitochondrial BCKDH complex . In thisDespite significant progress in understanding the molecular correlates of BCV biosynthesis in plants, much remains to be uncovered. In comparison, the metabolic bases of the biosynthesis of other important classes of fruit volatile such as the terpenoid, oxylipin, and phenylpropanoid families have been quite thoroughly characterized. For a similar level of understanding to be achieved for branched-chain volatiles, several important questions need to be resolved. A few of these unresolved questions regarding BCV biosynthesis most relevant to fruit volatile metabolism are explored below:in vitro -thiazole and re found . Comparere found  as well re found  justifie15N-labeled leucine to portions of tomato fruit tissue and examining any generated 2-isobutylthiazole molecules for that radioisotope could confirm or refute that assertion. Far more difficult would be accounting for the sulfur component of the thiazole ring and the two carbons at the four- and five-positions. While experiments using radiolabeled cysteine or methionine could yield some insight into the thiazole ring’s origin, ultimately it may be more feasible to use the abundant genetic resources available for tomato to track down potential biosynthesis enzymes using fine mapping of quantitative trait loci robustly associated with variable levels of this compound.The compound 2-(2-methylpropyl)-thiazole, hereafter referred to as 2-isobutylthiazole, is a known enhancer of tomato flavor that finds frequent use in the preparation of artificial condiments . It has S-methyl 3-methylbutanethioate, isolated from cantaloupe (13C5-L-methionine gave evidence that volatile S-methyl thioesters are formed through methionine catabolism (S-methyl thioesters incorporated a radiolabeled carbon at the methyl group. As it has been shown in strawberry that alcohol acyltransferase can catalyze the formation of straight-chain thioesters by condensing thioalcohols with acyl-CoAs (S-methyl thioesters in fruit arise from AAT-mediated condensation of branched-chain acyl-CoAs with methanethiol derived from the MGL-catalyzed cleavage of methionine (The other sulfur-containing BCV identified is the compound ntaloupe . Severalntaloupe . Due to tabolism . This stcyl-CoAs , it may thionine . EmpiricOnly one branched-chain alkane volatile was reported from all of the literature examined, the compound being 2-methylbutane and its presence being reported in raspberry . Becausein vivo. It is clear that properly elucidating which metabolic processes are responsible for fruit BCV biosynthesis will require a great deal of further experimental work, and it may very well be that the precise mechanisms vary from fruit to fruit.While knowledge regarding the biochemical basis of branched-chain volatile metabolism in fruits has advanced significantly in recent years, it is still rather inadequate especially when compared to our detailed understanding of oxylipin, terpenoid, and phenylpropanoid volatile biosynthesis. Much more is known regarding the impact BCVs have on the flavor and aroma qualities of several edible fruits, yet this underlies the importance of obtaining a more thorough understanding of the molecular correlates underlying fruit BCV production. What has been published regarding this topic points to four general hypotheses concerning the mechanisms of BCV volatile biosynthesis in fruits, any or all of which might be operational S-methyl thioesters. Furthermore, the regulation of important parts of several proposed BCV biosynthesis routes remains little known in plants. Whether well-studied regulatory mechanisms known to control similar pathways in mammals are also active in plants is a particularly relevant question, especially if bypassing these mechanisms presents a potential way to modulate BCV content in fruit tissue. Information gained on this aspect of BCV metabolism could prove quite useful to groups researching ways to improve the flavor of certain fruits by manipulating levels of important volatile compounds.Several questions regarding BCV metabolism remain unresolved, particularly those concerning the biosynthesis of more unusual compounds such as branched-chain alkanes and Ultimately, advancing our understanding of BCV metabolism represents a way to further our knowledge of the molecular basis of fruit flavor and aroma. The fact that important progress has been made should not detract from the fact that significant gaps remain regarding our understanding of how specifically these compounds are generated in fruits. Filling these gaps through rigorous experimental work will go a long way to making branched-chain volatiles as well understood as their oxylipin, terpenoid, and phenylpropanoid counterparts.LB and PM conceived the idea to develop the manuscript. LB reviewed and wrote the original draft. DT and PM reviewed and helped to create the final version. All authors contributed to the article and approved the submitted version.The 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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