Engineering Conferences International

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Shooner, Thomas

Picard-Deland, Maxime

Quémener, Mireille

Gagnon, Philippe.

Gosselin, Benoit

Côté, Daniel C.

OPTICAL MEASUREMENT OF A GUIDEWIRE DISPLACEMENT DURING PERCUTANEOUS CORONARY 
INTERVENTIONS 
 
Thomas Shooner, Université Laval, CERVO research center 
Thomas.shooner.1@ulaval.ca 
Maxime Picard-Deland, OpSens inc. 
Mireille Quémener, Université Laval 
Philippe Gagnon, OpSens inc. 
Benoit Gosselin, Université Laval 
Daniel C. Côté, Université Laval 
 
 
Key Words: Percutaneous Coronary Intervention, Optics, Biomechanics, Pullback, Guided Surgery 
 
Percutaneous coronary intervention (PCI) is the most common treatment for stenosis of the coronaries. 
Accurate assessment of stenosis length and location is crucial to achieve optimal PCI outcomes. In the context 
of complex procedures involving diffuse or tandem lesions, pressure guidewires can be used as a tool to aid 
clinicians in determining the number of stents and their length. While pressure sensing in coronary arteries is an 
efficient method to improve PCI, it doesn’t provide the surgeons with an objective metric of stent length and 
location. The SyncVision solution from Philips uses co-registration of pressure values and positions of the 
guidewire on angiogram images to visualize pressure variation and help surgeons in stent positioning and length 
choice. However, this technology brings new constraints to surgeons like slow and constant pullbacks, while 
having a weak spatial resolution due to low frequency angiography. It also requires heavy real-time image 
processing with complex implementation. We developed a novel guidewire motion detection method using 
compact, low-cost and highly performant optical sensor from computer mouse. With this method, detection is 
done outside of the body, directly on the guidewire. Since it doesn’t rely on angiogram images, it allows for 
higher accuracy and precision while removing slow and constant pullback constraints to clinicians. Preliminary 
results suggest a precision of 50 µm with a relative error of 1.6% for a 100 mm pullback (Figure 1, Figure 2). 
This new detection method, co-registered with pressure values, will facilitate clinicians in achieving 
unprecedented precision in stent positioning and length selection, thus significantly improving surgery 
outcomes. 
 
 
Figure 1 – Accuracy assessment of the optical 
device performed during a motor-assisted pullback 
with a 0.14” standard guidewire. The relative error 
has a constant value of 1.6% for all displacements.  
Figure 2 – Precision assessment of the optical 
device performed during a motor-assisted pullback 
with a 0.14” standard guidewire. The device can 
measure displacement variations as low as 50 µm.  


English

Optical measurement of a guidewire displacement during percutaneous coronary interventions

Choi, Bernard

Dunn, Cody

Crouzet, Christian

COHERENT SPATIAL IMAGING OF HEMODYNAMICS 
 
Bernard Choi, Beckman Laser Institute and Medical Clinic, Departments of Surgery and Biomedical 
Engineering, University of California, Irvine 
choib@uci.edu 
Christian Crouzet, Beckman Laser Institute and Medical Clinic, University of California, Irvine 
Cody Dunn, Beckman Laser Institute and Medical Clinic, Department of Biomedical Engienering, University of 
California, Irvine 
 
 
Key Words: laser speckle imaging, wearable sensor, speckle contrast, speckleplethysmography, coherent 
spatial frequency domain imaging 
 
We explored the integration of laser speckle imaging (LSI) and spatially resolved diffuse reflectance 
spectroscopy (srDRS) in a wearable coherent spatial imaging (CSI) sensor for assessing tissue perfusion and 
oxygenation. LSI analyzes laser light scattered by moving red blood cells to measure hemodynamics with high 
temporal resolution. srDRS measures tissue reflectance properties to provide insights into tissue composition 
and oxygenation. By combining LSI and srDRS, CSI enables continuous quantitative monitoring of perfusion 
dynamics and tissue oxygenation. In our presentation, we will describe the theoretical framework and previous 
imaging studies that culminate in the development and validation of the wearable sensor.  
 
 
 
 
 
 
Figure 1 (Left) Prototype coherent spatial imaging sensor (Right) Representative 
comparison of simultaneous measurements collected with a coherent spatial imaging 
and a laboratory-grade diffuse optical spectroscopy/diffuse correlation spectroscopy 
(DOS/DCS) device during a brachial artery occlusion experiment.  


Coherent spatial imaging of hemodynamics

Daly, Michael

Won, Natalie

Adewale, Anjolaoluwa

Wan, Jerry

Najjar, Esmat

Wilson, Brian C.

Irish, Jonathan C

Bartling, Mandolin

FLUORESCENCE DEPTH QUANTICATION USING  
SPATIAL FREQUENCY IMAGING AND DEEP LEARNING RECONSTRUCTION 
 
Michael J. Daly, Princess Margaret Cancer Centre 
michael.daly@rmp.uhn.ca 
Natalie Won, Princess Margaret Cancer Centre 
Anjolaoluwa Adewale, Princess Margaret Cancer Centre 
Jerry Wan, Princess Margaret Cancer Centre 
Mandolin Bartling, Princess Margaret Cancer Centre 
Esmat Najjar, Princess Margaret Cancer Centre 
Brian C. Wilson, Princess Margaret Cancer Centre 
Jonathan C. Irish, Princess Margaret Cancer Centre 
 
Key Words: Fluorescence-guided surgery, spatial frequency domain, optical tomography, deep learning 
 
There is an unmet clinical need to reduce the rate of positive margins following cancer surgery.1 Clinical trials in 
fluorescence-guided surgery are showing promise across a number of applications;2 however, existing 
fluorescence devices provide limited tumor depth information prior to resection, which is often the most critical 
challenge.3 To this end, our group is developing a deep learning (DL)-enabled spatial frequency domain imaging 
(SFDI) system for fluorescence depth quantification. A prototype SFDI system (Fig. 1a) acquires reflectance and 
fluorescence images using phase-shifted sinusoidal illumination across six spatial frequencies (fx=0-0.25 mm-1). 
Reflectance is used to recover absorption (µa) and scattering (µs’) maps using Monte Carlo lookup tables,4 while 
fluorescence enables depth sampling across spatial frequency.5 A deep convolutional neural network (Fig. 1b) 
predicts depth and concentration using in silico training data from numerical fluorescence simulations based on 
composite spherical harmonic (CSH) tumor shapes. Testing was performed with contoured tumors from MRI 
images of over 30 tongue cancer patients (T1-T4). The predicted maximum depth of invasion for tumors 
originating at the mucosal surface (“iceberg model”) was assessed for each case. In simulations, the mean error 
was 0.9 mm (SD=0.7 mm) for tumors < 1 cm deep, with degradations for larger tumors due to limited optical 
penetration depth. In experiments, we will present results from agar-based optical phantoms fabricated from the 
patient-derived contours. Future studies will include models with heterogeneities in optical properties and 
fluorescence uptake.   
 
 
Figure 1 – (a) Prototype SFDI system (b) Deep convolutional neural network architecture  
 
1. Orosco RK, Tapia VJ, Califano JAet al. Positive Surgical Margins in the 10 Most Common Solid 
Cancers. Sci Rep 2018; 8. 
2. Azari F, Kennedy G, Bernstein Eet al. Intraoperative molecular imaging clinical trials: a review of 2020 
conference proceedings. J Biomed Opt 2021; 26:050901. 
3. Brouwer de Koning SG, Schaeffers A, Schats W, van den Brekel MWM, Ruers TJM, Karakullukcu MB. 
Assessment of the deep resection margin during oral cancer surgery: A systematic review. Eur J Surg 
Oncol 2021; 47:2220-2232. 
4. Cuccia DJ, Bevilacqua F, Durkin AJ, Ayers FR, Tromberg BJ. Quantitation and mapping of tissue optical 
properties using modulated imaging. J Biomed Opt 2009; 14:024012. 
5. Hayakawa CK, Karrobi K, Pera V, Roblyer D, Venugopalan V. Optical sampling depth in the spatial 
frequency domain. J Biomed Opt 2018; 24:1-14 


Fluorescence depth quantification using spatial frequency imaging and deep learning reconstruction

PARHAM, ELAHE

. Côté, Daniel C

FIBER-BASED WAVELENGTH-SWEPT SPONTANEOUS RAMAN SPECTROSCOPY FOR BRAIN TISSUE 
CLASSIFICATION 
 
ELAHE PARHAM, CERVO Brain Research Center, Centre d'optique, photonique et laser, Université Laval 
Elahe.parham@cervo.ulaval.ca 
Mireille Quémener, CERVO Brain Research Center, Centre d'optique, photonique et laser, Université Laval 
Martin Parent, CERVO Brain Research Center 
Daniel C. Côté, CERVO Brain Research Center, Centre d'optique, photonique et laser, Université Laval 
 
 
Key Words: Raman spectroscopy, wavelength-swept, brain, classification 
 
Raman scattering has been used for brain tissue identification and characterization. Raman spectroscopy is a 
technique that provides information about the molecular composition of a sample by measuring the scattering of 
laser light. It is based on the inelastic scattering of photons, known as Raman scattering, which occurs when 
light interacts with the vibrational modes of molecules. In the context of brain tissue, Raman spectroscopy can 
be used to analyze the molecular composition such as protein, lipids, and other biomolecules. Raman 
spectroscopy has been shown to be a powerful tool for tissue identification and it has the advantage of being 
non-destructive and minimally interfering with the ongoing process inside the tissue. The conventional setup 
includes a monochromatic light source for excitation and a spectrometer for collection suffers from extremely 
low efficiency due to light scattering in tissue. We present a wavelength-swept Raman spectroscopy strategy 
that overcomes this limitation by using a laser that can sweep over a significant wavelength range to excite 
tissue with different wavelength over time, and a photodetector with a fixed narrow-bandpass filter to collect the 
Raman signal at the given wavelength and therefore a varying Raman frequency. The most important gain of 
this strategy is the large optical invariant of the setup that advantageously compares to that of a spectrometer. 
Indeed, the diameter of the detector is 1 mm which is 20 to 100 times larger than the typical entrance slit of a 
spectrometer with a resolution of 1 nm for an approximately equal acceptance cone. 
Theoretical comparison of the detection efficiency between swept-source Raman spectroscopy (SSRS) and 
spectrometer-based Raman spectroscopy has been done using the Raytracing Python module [1]. For the 
experimental data acquisition, the swept-source is a Ti:Sapphire that automatically sweeps the excitation 
wavelengths from 800 nm to 820 nm. A bifurcated fiber bundle is used to deliver the laser light to the sample 
and to collect the light from scattered back from the sample. An ultra-narrow bandpass filter 1064/1 nm and an 
InGaAs femtowatt photoreceiver are employed for signal collection, allowing to cover the Raman shift region 
from 2800 to 3100 cm-1. Finally, the photoreceiver is connected to a lock-in amplifier to enable phase-sensitive 
detection, thus increasing even more the SNR. The setup was tested on non-human primate fixed brain tissue 
of 1 mm thickness. We acquired 140 spectra, 20 from each region including white matter (WM) and regions with 
gray matter (GM) such as subthalamic nucleus (STN), the internal (GPi) and external (GPe) globus pallidus, 
substantia nigra (SN)and striatum (putamen and caudate nucleus).  
Fiber collection efficiency and coupling efficiency have been calculated 
with simulations for several diameter and NA of fiber. The collection 
efficiency increases as we use a larger fiber with a higher NA. When 
collection fiber diameter and NA are increased, the coupling efficiency into 
the spectrometer decreases significantly while it is not the case in SSRS, 
meaning that using a large area detector result in a better efficiency. With 
a spectrometer there is a tradeoff between the collection efficiency and 
the coupling efficiency. Additionally, the signal-to-noise ratio (SNR) is 
improved significantly with SSRS setup. Using principal component 
analysis (PCA) with a k-nearest neighbor (KNN) classifier and leave-one-
out cross validation, we can observe the the first principal component 
(PC) has a very high explained variance ratio and it can be used to 
separate WM and GM in two classes with 100% accuracy. If we take the 
three first PCs into account and perform the classification on 5 different 
regions including striatum (caudate and putamen), GP (GPi and GPe), 
STN, SN, and WM, we still have 98.5% accuracy for classification (Fig 1). 
 
Reference: 
[1] Pineau Noël V, Masoumi S, Parham E, Genest G, Bégin L, Vigneault M-A, et al. Tools and tutorial on 
practical ray tracing for microscopy. Neurophotonics. 2021;8: 010801. 
Figure 1 – The confusion matrix of 
classification using 3 first principal 
components with 98.5% accuracy. 


Fiber-based wavelength-swept spontaneous Raman spectroscopy for brain tissue classification

Kang, Dongkyun

LOW-COST, IN VIVO MICROSCOPY 
 
Dongkyun Kang, Colleges of Optical Sciences and Department of Biomedical Engineering, University of Arizona 
dkkang@arizona.edu 
 
 
Key Words: in vivo microscopy, reflectance confocal microscopy, scattering-based light sheet microscopy, 
non-invasive imaging 
 
In vivo microscopy is an optical microscopy approach that can visualize cellular details of human tissues non-
invasively. Some of the in vivo microscopy technologies such as reflectance confocal microscopy, optical 
coherence tomography, and two-photon microscopy have become available as medical imaging devices and 
have been evaluated for a wide range of clinical applications. Since in vivo microscopy could reveal cellular 
changes associated with disease progression without taking biopsies from the patient, it can be used to aid 
diagnosis of various diseases in low-resource settings, where the facilities, equipment, and trained personnel 
needed for standard histopathologic diagnosis are scarce. However, widespread implementation of in vivo 
microscopy has not occurred yet, and one of the main reasons for this is the high device cost. We have 
developed several low-cost, in vivo microscopy devices for imaging applications in low-resource settings. In this 
talk, we will present our research on the portable confocal microscopy for imaging skin and eye diseases, 
smartphone-compatible confocal endoscopy for imaging cervical precancers, and scattering-based light sheet 
microscopy for imaging anal precancers. 
 


Low-cost, in vivo microscopy

Turnbull, Alan

IS LABORATORY TESTING OF SCC SUSCEPTIBILITY FIT FOR PURPOSE? 
 
Alan Turnbull, NPL 
alan.turnbull@npl.co.uk 
 
 
Key Words: stress corrosion cracking, testing, standards. 
 
There has been remarkable progress in the development of international standards for evaluating the 
susceptibility of metals and alloys to stress corrosion cracking, with more than 30 ISO and ASTM standards and 
various industry-specific testing standards produced over the last 40 years or so. Despite this, the occasional 
failure does occur, and this poses concern in the deployment of novel alloys and additive manufactured metals, 
for which there is limited or no prior service experience in hostile environments. How can one be confident that 
laboratory testing will be sufficiently discriminating in ensuring the integrity of associated structures and 
components over the projected lifetime? In that respect, it is emphasised that qualifying materials for service 
application is not in the scope of testing standards. The selection of test method, the detailed specification of 
variables in the test standard, and the use of the test data generated are the responsibility of an informed end-
user.  
 
Some failures can be attributed to poor fabrication or to uncontrolled excursions in stress/strain, environment, 
and temperature (see ISO 21601) that are not always captured in the adopted test method. An example will 
given of a pressure vessel failure where the stainless steel vessel fractured because of an increased 
temperature following breakdown of a cooling system. The grade of stainless steel selected was appropriate to 
the operating temperature but could not accommodate the excursion. This was not a failure of a test method but 
limitations in system analysis, identification of potential failure mechanisms, and risk assessment.  
 
There are many variables that can affect the outcome of a laboratory stress corrosion cracking test in adopting 
existing standards. Nevertheless, surface preparation, dynamic strain rate, and environmental simulation are 
perhaps the most concerning in terms of opportunity for greatest variability or misplaced confidence in the 
relevance of the methodology adopted. Examples for each will be described to highlight the issues.  
 
Progress is being made towards developing test methods for additive manufactured metals and alloys, in which 
the range of factors that may impact on the testing methodology or susceptibility are highlighted. An example 
will be given of the impact of specimen preparation and microstructural orientation on cracking susceptibility. 
 
Finally, in closing, the need for test method development and testing specification will be commented on as a 
framework for discussion on qualifying advanced materials as fit-for service.  
 
 


Is laboratory testing of SCC susceptibility fit for purpose?

Kujawski, Daniel

Vasudevan, Asuri K.

Plano, Stefano

Gabellone, Davide

USE OF AN INVERSE LIFE PLOT FOR FATIGUE ENDURANCE/LIMIT ESTIMATION    
 
Daniel Kujawski, Mechanical and Aerospace Engineering, Western Michigan University, USA 
daniel.kujawski@wmich.edu 
 Asuri K. Vasudevan, Technical Data Analysis, Inc. Falls Church, VA22043 
Stefano Plano, Stellantis, EMEA Product Development BCI, Orbassano, Italy 
 Davide Gabellone, Stellantis, EMEA Product Development BCI, Orbassano, Italy 
 
 
This paper describes the use of a reverse life plot, S vs. 1/Nf for determining a fatigue endurance/limit. The 
method is applicable for different environments and load R-ratios. Due to inherent scatter in the fatigue data 
approaching fatigue limit, a ‘staircase’ method is often utilized but requires relatively large number of individual 
specimens (around 15-20) to be tested just for fatigue endurance/limit determination alone. The proposed 
method uses only high-cycle-fatigue (HCF) S-N data. The estimated fatigue endurance/limit is verified against 
the data from staircase method for 6000 Al alloy and steel. The comparison with the staircase method shows 
fairly good agreement with an error around of less than 5%. In addition, we show the example on 4140 steek in 
NaCl And in 90%RH how this method gives reliable endurance limit results. 
 
 
 


Use of an inverse life plot for fatigue endurance/limit estimation

Taylor, Chris

MODELING ELECTROCHEMICALLY ASSISTED HYDROGEN ADSORPTION ON ALLOYSURFACES
Chris Taylor, DNV GL and Ohio State University, USA


Modeling electrochemically assisted hydrogen adsorption on alloy   surfaces

Bayer, Marcus

IS COMPONENT PART STANDARDIZATION OF ESTABLISHED SYSTEMS POSSIBLE? 
 
Marcus Bayer, Hamilton, Switzerland 
mbayer@hamilton.ch 


German

Is component part standardization of established systems possible?

Alaria, Matteo

DRIVING ENVIRONMENTAL SUSTAINABILITY IN THE BIOPHARMACEUTICAL INDUSTRY 
 
Matteo Alaria, Sartorius 
matteo.alaria@sartorius.com 
 
 
Key Words: Partnerships, process intensification, material circularity, water use efficiency, climate action 
 
SU technologies are increasingly employed in modern biopharmaceutical manufacturing as an alternative to 
traditional stainless steel solutions, owing to their contributions towards reproducibility, flexibility, time efficiency, 
and safety. These technologies are implemented across the bioprocess workflow from cell line development to 
final filling, including storage bags, mixers, bioreactors, tubing, filters, chromatography systems, and sensors. 
The adoption of SU technologies helps the industry reach environmental goals and strive against resource 
depletion, particularly water, energy, emissions, and footprint reduction. 
 
The paper’s goal is to present initiatives developed internally by Sartorius and with our partners, focused on our 
products and processes’ sustainability. We will highlight results and examples of how suppliers in the biopharma 
industry can help customers achieve their sustainability goals. Moreover, we talk about the role of process 
intensification in driving resources optimization upstream and downstream. 
We will be looking at material circularity, carbon footprint reduction, partnerships, and water consumption 
optimization. 
 
We believe that the best results can be achieved through collaboration between end users, suppliers, and 
academia, and hope to see the whole industry continue its progress on sustainability. 
 
 
 
Figure 1 - Process Intensification Strategies help limit PMI 
 


Not a member yet

Optical measurement of a guidewire displacement during percutaneous coronary interventions

Coherent spatial imaging of hemodynamics

Fluorescence depth quantification using spatial frequency imaging and deep learning reconstruction

Fiber-based wavelength-swept spontaneous Raman spectroscopy for brain tissue classification

Low-cost, in vivo microscopy

Is laboratory testing of SCC susceptibility fit for purpose?

Use of an inverse life plot for fatigue endurance/limit estimation

Modeling electrochemically assisted hydrogen adsorption on alloy surfaces

Is component part standardization of established systems possible?

Driving environmental sustainability in the biopharmaceutical industry

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