Quantitative coating thickness determination using a coefficient-independent hyperspectral scattering model

Background: Hyperspectral imaging is a technique that enables the mapping of spectral signatures across a surface. It is most commonly used for surface chemical mapping in fields as diverse as satellite remote sensing, biomedical imaging and heritage science. Existing models, such as the Kubelka-Munk theory and the Lambert-Beer law also relate layer thickness with absorption, and in the case of the Kubelka-Munk theory scattering, however they are not able to fully describe the complex behavior of the light-layer interaction. Methods: This paper describes a new approach for hyperspectral imaging, the mapping of coating surface thickness using a coefficient-independent scattering model. The approach taken in this paper is to model the absorption and scattering behavior using a developed coefficient-independent model, calibrated using reference sample thickness measurements performed with optical coherence tomography. Results: The results show that this new model, by considering the spectral variation that can be recorded by the hyperspectral imaging camera, is able to measure coatings of 250 μm thickness with an accuracy of 11 μm in a fast and repeatable way. Conclusions: The new coefficient-independent scattering model presented can successfully measure the thickness of coatings from hyperspectral imaging data

Quantitative coating thickness determination

The coating selected in this research was a film-forming low-gloss wood lacquer for outdoors (Transparant zijdeglanslak voor buiten, Wijzonol Bouwverven B.V.). This coating was selected because it is semi-transparent commonly used wood coating, making it a suitable coating to visualize with OCT and hyperspectral imaging. This spruce-colored coating is based on organic solvent with an alkyd binder and applied using a brush. The samples that were prepared are: 1) Coating in a very flat and reflective silicon wafer to be able to determine the refractive index of the coating. 2) Different thickness coatings applied to a thin cover glasses in order to be able to determine the K and S coefficients from the KM-model and the extinction coefficient from the LB model. In order to measure the coefficients, these cover glasses were placed on a black-and-white checkerboard, as described below. 3) One to four layers of the coating were applied to a Medium-Density Fibreboard (MDF) plate covered with acrylic gesso. This reflective non-absorbing background serves as a reference for assessing the performance of the models. The hysperspectral imaging setup used in this study consisted of an IMSPECTOR V10E (Specim©) spectral camera, operating in the 400-1000 nm range. The visible range was selected due to the main absorption characteristics of the studied coating layers which is within the range of 400-1000nm.Optical Coherence Tomography (OCT) is a suitable technique for imaging the interfaces in a semi-transparent material and is therefore a logical choice for measuring coating thickness. This technique is based on low-coherence interferometry to measure light reflections from refractive index interfaces. As shown in Fig. 5, a customized OCT system was built by using a superluminescent diode (FESL-1550-20-BTF, Frankfurt Laser Company) centered at 1550 nm with a full width at half maximum of 60 nm, resulting in a 20 µm spot size and an 11 µm theoretical axial resolution inside the coating layer (considering a refractive index of 1.5). Depth-scanning for OCT was realized by the means of an optical delay line (ODL-650,MC, OZ Optics, Ltd). Lateral scanning of a sample with an x-y translation stage (T-LS28M, Zaber Inc., Canada) allowed for a 28 mm scanning range in two directions. Obtained data were bandpass filtered and an envelope detector was used to recover the depth dependent signal

Prevalence, clinical and molecular characteristics of early stage EGFR-mutated lung cancer in a real-life West-European cohort: Implications for adjuvant therapy

Objectives: The landmark ADAURA study recently demonstrated a significant disease-free survival benefit of adjuvant osimertinib in patients with resected EGFR-mutated lung adenocarcinoma. However, data on prevalence rates and stage distribution of EGFR mutations in non-small cell lung cancer in Western populations are limited since upfront EGFR testing in early stage lung adenocarcinoma is not common practice. Here, we present a unique, real-world, unselected cohort of lung adenocarcinoma to aid in providing a rationale for routine testing of early stage lung cancers for EGFR mutations in the West-European population. Material and methods: We performed routine unbiased testing of all cases, regardless of TNM stage, with targeted next-generation sequencing on 486 lung adenocarcinoma cases between 01- January 2014 and 01 February 2020. Clinical and pathological data, including co-mutations and morphology, were collected. EGFR-mutated cases were compared to KRAS-mutated cases to investigate EGFR-specific characteristics. Results: In total, 53 of 486 lung adenocarcinomas (11%) harboured an EGFR mutation. In early stages (stage 0-IIIA), the prevalence was 13%, versus 9% in stage IIIB-IV. Nine out of 130 (7%) stage IB-IIIA patients fit the ADAURA criteria. Early stage cases harboured more L858R mutations (p = 0.02), fewer exon 20 insertions (p = 0.048), fewer TP53 co-mutations (p = 0.007), and were more frequently never smokers (p = 0.04) compared to late stage cases with EGFR mutations. The KRAS-mutated cases were distributed more evenly across TNM stages compared to the EGFR-mutated cases. Conclusion: As (neo-)adjuvant targeted therapy regimes enter the field of lung cancer treatment, molecular analysis of early stage non-small cell lung cancer becomes relevant. Testing for EGFR mutations in early stage lung adenocarcinoma holds a substantial yield in our population, as our number needed to test ratio for adjuvant osimertinib was 14.4. The observed differences between early and late stage disease warrant further analysis to work towards better prognostic stratification and more personalised treatment