Immunofluorescence and histopathological assessment using ex vivo confocal laser scanning microscopy in lichen planus

Bağcı, Işın Sinem; Aoki, Rui; Krammer, Sebastian; Vladimirova, Gabriela; Ruzicka, Thomas; Sárdy, Miklós; French, Lars E.; Hartmann, Daniela

doi:10.1002/jbio.202000328

Cited by 15 publications

(12 citation statements)

References 26 publications

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“…Moreover, DIF findings in both oral and cutaneous LP were described in only one study (Table 3). 1,3–5 The lowest rates of positive DIF findings previously reported were 37% in oral and 34% in cutaneous LP, 6,7 which was markedly lower than the rates of 79.3% and 93.3%, respectively, found in our study. Several factors are involved in diagnostic sensitivity, including age of lesion, biopsy site, and lesional and nonlesional skin.…”

Section: Reportcontrasting

confidence: 80%

Direct immunofluorescence staining patterns compared between oral and cutaneous lichen planus

Rujitharanawong

Tuchinda

Chularojanamontri

et al. 2021

Clin Experimental Derm

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This retrospective study performed to investigate direct immunofluorescence (DIF) findings in oral and cutaneous lichen planus (LP), and to identify any differences between them. There were 147 patients with a definite diagnosis of LP by clinical and histological criteria, with 87 (59.2%) oral and 60 (40.8%) cutaneous specimens. Of these, 125 (85%) had positive DIF findings, with positive yields being significantly lower in oral (79.3%) than in cutaneous (93.3%) LP. Deposition of immunoreactants at the dermoepidermal junction (DEJ) was significantly greater in oral than in cutaneous LP, and fibrin deposition with shaggy pattern at the DEJ was also significantly greater in oral than in cutaneous LP. Deposition of immunoreactants at colloid bodies (CBs) with or without DEJ was significantly greater in cutaneous than in oral LP. IgM deposition at CBs was commonly detected in both groups. We propose that fibrin deposition with shaggy pattern at the DEJ is the best diagnostic indicator of oral LP.

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Section: Reportcontrasting

confidence: 80%

Direct immunofluorescence staining patterns compared between oral and cutaneous lichen planus

Rujitharanawong

Tuchinda

Chularojanamontri

et al. 2021

Clin Experimental Derm

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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%

“…Ex vivo confocal laser scanning microscopy (ex vivo CLSM) is one of the diagnostic innovations developed to overcome current challenges in traditional pathology [ 10 , 11 , 12 ]. It allows instant, high-resolution, bedside imaging of intact freshly excised tissue samples at a subcellular level [ 13 ]. The integrated features such as optical sectioning and mosaicking enable visualization of the whole tissue samples (generally up to 25 × 25 mm) at various depths and up to a 550-fold magnification [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

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

Ruini

Schlingmann

Jonke³

et al. 2021

Cancers

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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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“…Recently, we have investigated the applicability of ex vivo CLSM in DIF examination of bullous pemphigoid 4 and pemphigus vulgaris (unpublished data) using FITC‐labelled anti‐human antibodies and showed for the first time that immune depositions can be identified using ex vivo CLSM. Combination of immunofluorescence and histomorphological examinations could enhance the diagnostic accuracy of ex vivo CLSM not only in autoimmune blistering diseases but also in other inflammatory skin diseases characterized by immune depositions in tissue such as cutaneous vasculitis 3 and lichen planus 14 . In this study, we aimed to further investigate the applicability of ex vivo CLSM in the diagnosis of inflammatory diseases, specifically in different types of CLE, and compare its performance with conventional diagnostic methods.…”

Section: Discussionmentioning

confidence: 99%

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

Bağcı

Aoki²,

Vladimirova³

et al. 2021

Experimental Dermatology

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Ex vivo confocal laser scanning microscopy (CLSM) offers real‐time examination of excised tissue in reflectance, fluorescence and digital haematoxylin‐eosin (H&E)–like staining modes enabling application of fluorescent‐labelled antibodies. We aimed to assess the diagnostic performance of ex vivo CLSM in identifying histopathological features and lupus band test in cutaneous lupus erythematosus (CLE) with comparison to conventional histopathology and direct immunofluorescence (DIF). A total of 72 sections of 18 CLE patients were stained with acridine orange (AO), anti‐IgG, anti‐IgM and anti‐IgA; 21 control samples were stained with AO. Subsequently, ex vivo CLSM examination of all samples was performed in reflectance, fluorescence and digital H&E‐like staining modes. Superficial and deep perivascular inflammatory infiltration (94.4%), interface dermatitis (88.9%), spongiosis (83.3%) and vacuolar degeneration (77.7%) were the most common features detected with ex vivo CLSM. Kappa test revealed a level of agreement ranging within “perfect” to “good” between ex vivo CLSM and conventional histopathology. ROC analysis showed that the combination of perivascular infiltration, interface dermatitis and spongiosis detected by ex vivo CLSM has the potential to distinguish between CLE and controls. Basement membrane immunoreactivity with IgG, IgM and IgA was identified in 88.8% (n = 15), 55.5% (n = 10) and 55.5% (n = 10) of the CLE samples using ex vivo CLSM, respectively, whereas DIF showed IgG, IgM and IgA positivity in 94.4% (n = 17), 100% (n = 18) and 88.9% (n = 16) of patients, respectively. In conclusion, ex vivo CLSM enables simultaneous histopathological and immunofluorescence examination in CLE showing a high agreement with conventional histopathology, albeit with a lower performance than conventional DIF.

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Immunofluorescence and histopathological assessment using ex vivo confocal laser scanning microscopy in lichen planus

Cited by 15 publications

References 26 publications

Direct immunofluorescence staining patterns compared between oral and cutaneous lichen planus

Direct immunofluorescence staining patterns compared between oral and cutaneous lichen planus

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

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

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