New‐generation diagnostics in inflammatory skin diseases: Immunofluorescence and histopathological assessment using ex vivo confocal laser scanning microscopy in cutaneous lupus erythematosus

Bağcı, Işın Sinem; Aoki, Rui; Vladimirova, Gabriela; Ergün, Ecem Zeliha; Ruzicka, Thomas; Sárdy, Miklós; French, Lars E.; Hartmann, Daniela

doi:10.1111/exd.14265

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…The detailed structural analyses are discussed in the Section 2.2. Therefore, even high-resolution optical microscopies for investigating of highly scattering medium (i.e., skin), such as confocal laser scanning microscopy, are unfeasible to identify the exact structure of VSPP. − Scanning electron microscopy (SEM) can resolve the internal pores, however, the top saturated layer completely screens the observation of SEM on the internal pores.…”

Section: Resultsmentioning

confidence: 99%

Visually Hidden, Self-Assembled Porous Polymers for Optical Physically Unclonable Functions

Kim

Lee

2023

ACS Appl. Mater. Interfaces

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Owing to the advancement of security technologies, several encryption methods have been proposed. Despite such efforts, forging artifices is financially and somatically becoming a constraint for individuals and society (e.g., imprinting replicas of luxury goods or directly life-connected medicines). Physically unclonable functions (PUFs) are one of the promising solutions to address these personal and social issues. The unreplicability of PUFs is a crucial factor for high security levels. Here, this study proposes a visually hidden and self-assembled porous polymer (VSPP) as a tag for optical PUF systems. The VSPP has virtues in terms of wavelength dependency, lens-free compact PUF system, and simple/affordable fabrication processes (i.e., spin coating and annealing). The VSPP consists of an external saturated surface, which covers the inner structures, and an internally abundant porous layer, which triggers stochastic multiple Mie scattering with wavelength dependency. We theoretically and experimentally validate the unobservability of the VSPP and the uniqueness of optical responses by image sensors. Finally, we establish a wavelength-dependent PUF system by using the following three components: solid-state light sources, a VSPP tag, and an image sensor. The captured raw images by the sensor serve as “seed” for unique bit sequences. The robustness of our system is successfully confirmed in terms of bit uniformity (∼0.5), intra/interdevice Hamming distances (∼0.04/∼0.5), and randomness (using NIST test).

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Section: Resultsmentioning

confidence: 99%

Visually Hidden, Self-Assembled Porous Polymers for Optical Physically Unclonable Functions

Kim

Lee

2023

ACS Appl. Mater. Interfaces

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“…The digitally H&E‐stained confocal scans provide intuitive comparison to standard histology and may substitute histological examination in cases where quick evaluation of tissue is desired 3,19 . To enhance a broader usage of EVCM in research and for possible clinical indications, recent studies have investigated the use of fluorescent‐labelled antibodies to increase the diagnostic accuracy of EVCM in inflammatory skin diseases with immune depositions such as autoimmune blistering diseases, cutaneous vasculitis, cutaneous lupus and lichen planus 18,22–25 . Additional staining methods have been tested to enhance the contrast of different cell structures without altering the tissue prior to histological examination 2 .…”

Section: Discussionmentioning

confidence: 99%

“… 3 , 19 To enhance a broader usage of EVCM in research and for possible clinical indications, recent studies have investigated the use of fluorescent‐labelled antibodies to increase the diagnostic accuracy of EVCM in inflammatory skin diseases with immune depositions such as autoimmune blistering diseases, cutaneous vasculitis, cutaneous lupus and lichen planus. 18 , 22 , 23 , 24 , 25 Additional staining methods have been tested to enhance the contrast of different cell structures without altering the tissue prior to histological examination. 2 Prior to conventional histological examination, tissue preparation and paraffin embedding are required but can lead to tissue shrinkage that might compromise qualitative evaluation of tissue.…”

Section: Discussionmentioning

confidence: 99%

Visualization of energy‐based device‐induced thermal tissue alterations using bimodal ex‐vivo confocal microscopy with digital staining. A proof‐of‐concept study

Fredman

Christensen

Ortner

et al. 2022

Skin Research and Technology

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Background: Ex-vivo confocal microscopy (EVCM) enables examination of tissue alterations immediately after treatment with energy-based devices (EBDs). This proof-ofconcept study aimed to describe EBD-induced tissue effects in ex-vivo porcine skin after treatment with microneedle radiofrequency (MNRF) and ablative fractional CO 2laser (AFL) using EVCM.Materials and Methods: Ex-vivo porcine skin was treated with MNRF and AFL. Three cryosections from each intervention were stained with acridine orange (AO) and scanned with EVCM. Reflectance confocal microscopy (RCM, 638 nm) and fluorescence confocal microscopy (FCM, 488 nm) images were captured and evaluated individually, after image fusion, and after digital hematoxylin and eosin (H&E) staining. Results:Bimodal EVCM was able to visualize EBD-induced thermal alterations in porcine skin. In RCM mode, the full width and depth of the vertically aligned microscopic treatment zones (MTZs) were displayed with clear demarcation to surrounding intact skin. In FCM mode, the ablation of the epidermis after AFL was prominent in contrast with the almost intact epidermis observed in MNRF treated skin. In fusion mode, fluorescence signal from AO marked the surrounding coagulation zone (CZ) from both interventions, with enhanced discrimination between ablation and coagulation. Digitally H&E-stained images closely resembled conventional histopathology but proved superior in terms of visualization of the CZ. Conclusion:Bimodal EVCM with digital H&E-staining facilitates the identification and qualitative evaluation of thermal alterations induced by treatment with EBD.

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“…For instance, different types of prostatic and periprostatic tissue could be successfully differentiated on ex vivo CLSM images [ 26 ]. In addition, potential applications of ex vivo CLSM are not limited to the field of cancer but can also be expanded to characterization of autoimmune and inflammatory skin diseases such as pemphigus, pemphigoid, lichen planus, lupus erythematosus and vasculitis [ 13 , 57 , 58 , 59 , 60 , 61 ].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy

Ruini

Schlingmann

Jonke³

et al. 2021

Cancers

Self Cite

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Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the forefront of artificial intelligence (AI) revolution, conventional pathology, which commonly relies on examination of tissue samples on a glass slide, is falling behind in leveraging this technology. On the other hand, ex vivo confocal laser scanning microscopy (ex vivo CLSM), owing to its digital workflow features, has a high potential to benefit from integrating AI tools into the assessment and decision-making process. Aim of this work was to explore a preliminary application of CNN in digitally stained ex vivo CLSM images of cutaneous squamous cell carcinoma (cSCC) for automated detection of tumor tissue. Thirty-four freshly excised tissue samples were prospectively collected and examined immediately after resection. After the histologically confirmed ex vivo CLSM diagnosis, the tumor tissue was annotated for segmentation by experts, in order to train the MobileNet CNN. The model was then trained and evaluated using cross validation. The overall sensitivity and specificity of the deep neural network for detecting cSCC and tumor free areas on ex vivo CLSM slides compared to expert evaluation were 0.76 and 0.91, respectively. The area under the ROC curve was equal to 0.90 and the area under the precision-recall curve was 0.85. The results demonstrate a high potential of deep learning models to detect cSCC regions on digitally stained ex vivo CLSM slides and to distinguish them from tumor-free skin.

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New‐generation diagnostics in inflammatory skin diseases: Immunofluorescence and histopathological assessment using ex vivo confocal laser scanning microscopy in cutaneous lupus erythematosus

Cited by 10 publications

References 26 publications

Visually Hidden, Self-Assembled Porous Polymers for Optical Physically Unclonable Functions

Visually Hidden, Self-Assembled Porous Polymers for Optical Physically Unclonable Functions

Visualization of energy‐based device‐induced thermal tissue alterations using bimodal ex‐vivo confocal microscopy with digital staining. A proof‐of‐concept study

Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy

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