Ex vivo confocal microscopy features of common benign lesions that mimic non-melanoma skin cancers: Towards clinical integration

Ex vivo confocal microscope (EVCM) rapidly images freshly excised tissue at a histopathological resolution. EVCM features of keratinocyte skin cancers are well-established, but those of benign clinical mimickers remain scarce. We describe EVCM features of common benign lesions and compare them with their malignant differentials. EVCM was used to image 14 benign and 3 cancer tissues. We compared EVCM features of benign lesions with corresponding histopathology and with those of keratinocyte cancers. Key features of benign lesions were identified and differentiated from malignant lesions. Elastin and fat appeared prominent in EVCM; while koilocytes and melanin were difficult to identify. Visualization of entire epidermis was challenging due to difficulty of tissue flattening during imaging. Benign lesions can be differentiated from keratinocyte cancers with EVCM. Using EVCM, a rapid, bedside diagnosis and management of skin neoplasms is possible, especially in a remote location without a histopathology lab.

Quantitative collagen analysis using second harmonic generation images for the detection of basal cell carcinoma with ex vivo multiphoton microscopy

Basal cell carcinoma (BCC) is the most common skin cancer, and its incidence is rising. Millions of benign biopsies are performed annually for BCC diagnosis, increasing morbidity, and healthcare costs. Non-invasive in vivo technologies such as multiphoton microscopy (MPM) can aid in diagnosing BCC, reducing the need for biopsies. Furthermore, the second harmonic generation (SHG) signal generated from MPM can classify and prognosticate cancers based on extracellular matrix changes, especially collagen type I. We explored the potential of MPM to differentiate collagen changes associated with different BCC subtypes compared to normal skin structures and benign lesions. Quantitative analysis such as frequency band energy analysis in Fourier domain, CurveAlign and CT-FIRE fibre analysis was performed on SHG images from 52 BCC and 12 benign lesions samples. Our results showed that collagen distribution is more aligned surrounding BCCs nests compared to the skin's normal structures (p < 0.001) and benign lesions (p < 0.001). Also, collagen was orientated more parallelly surrounding indolent BCC subtypes (superficial and nodular) versus those with more aggressive behaviour (infiltrative BCC) (p = 0.021). In conclusion, SHG signal from type I collagen can aid not only in the diagnosis of BCC but could be useful for prognosticating these tumors. Our initial results are limited to a small number of samples, requiring large-scale studies to validate them. These findings represent the groundwork for future in vivo MPM for diagnosis and prognosis of BCC.

Non-invasive, in vivo, characterization of cutaneous metastases using a novel multimodal RCM-OCT imaging device: a case-series

BACKGROUND

Cutaneous metastases (CM) diagnosis is clinically challenging, requiring an invasive biopsy for confirmation. A novel, RCM-OCT device combines the advantage of horizontal high-resolution reflectance confocal microscopy (RCM) images and vertical deeper optical coherence tomography (OCT) images to aid in non-invasive diagnosis of CM from breast cancers.

OBJECTIVE

Characterize CM from breast cancers using RCM-OCT device.

METHODS

Seven patients suffering from breast cancers with suspicious CM were consented and imaged with RCM-OCT device. CM features were defined by comparing with histopathology. Tumour depths were measured on OCT and on H&E-images and correlated using statistical analysis Pearson test. 3D-OCT images were reconstructed to enhance tumour visualization.

RESULTS

6/7 lesions were CM from breast cancers, and one was vascular ectasia, on histopathology. CM appeared as greyish-darkish oval to round structures within the dermis on RCM and OCT-images. On RCM, individual tumour cells were seen, enabling identification of even small tumour foci; while, on OCT deeper tumours were detected. Inflammatory cells, dilated vessels and coarse collagen were identified in the dermis. Pearson correlation had an r2 of 0.38 and a significant P-value <0.004 for depth measurements. CM from breast cancers could be differentiated from ecstatic vessels on 3D-reconstructed OCT image.

LIMITATION

Small sample size and lack of clinical mimickers.

CONCLUSION

RCM-OCT can detect CM and has potential in aiding non-invasive diagnosis and management.

Interim analysis of a single-center, single-arm, prospective phase 2 study to evaluate the efficacy and safety of benralizumab for alpelisib rash in metastatic PIK3CA-mutant, hormone receptor–positive breast cancer

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Background: Rash associated with increased peripheral eosinophils develops in approximately 50% of metastatic breast cancer patients receiving alpelisib. Antihistamines and corticosteroids have limited benefit. Refractory rash may lead to decreased dose intensity and affect clinical outcome. Benralizumab is an anti-IL-5Rα chimeric monoclonal antibody that depletes peripheral eosinophils and has demonstrated benefit in eosinophilic asthma and hypereosinophilic syndrome. We investigate the efficacy and safety of benralizumab for the treatment of alpelisib rash. Methods: We performed a single-center, single-arm, prospective phase 2 study to evaluate the efficacy and safety of benralizumab in cancer patients who developed CTCAE grade 2/3 skin events resulting from immunotherapy or targeted therapies with absolute blood eosinophil counts of ≥300/mcl. While remaining on culprit drugs, patients were treated with benralizumab 30mg once every 4 weeks for the first 3 doses followed by once every 8 weeks for 3 additional doses (approved dosing for eosinophilic asthma). Primary endpoint was clinical response measured as reduction in CTCAE grade 2/3 skin event to grade ≤1 by week 4. Secondary endpoints were patient quality of life (QoL) measured by skindex16, safety data, need for supportive oral corticosteroids, and changes in cytokines and eosinophil biomarkers. This interim analysis focuses on patients with PIK3CA-mutant metastatic breast cancer receiving alpelisib. Results: Between September 16th 2020 and January 1st 2022, we enrolled 10 metastatic breast cancer patients with grade 2/3 rash attributed to alpelisib (5 pts with G3). All patients had a reduction of rash to grade ≤1 (n = 10, p < 0.0001), and a decrease in peripheral absolute eosinophils (mean 500/mcl to 0, p < 0.0001). Of these, 6 patients had been on prophylactic oral antihistamines and 2 had oral steroid coadministration. QoL significantly improved (Skindex16 mean score 58 to 16, p = 0.0001) and eosinophils in skin histology decreased per HPF (mean 6.25 to 0.25, n = 8, p = 0.2) by week 4. An increase in IL-5 > 600% and reduction IL-6 and TNF-α > 50% were reported by week 4 and 8. Grade 1/2 mucositis in 4 patients were reported as adverse events. Conclusions: Our findings suggest that benralizumab is safe and effective for the treatment of grade 2/3 rash with eosinophilia related to alpelisib in patients with breast cancer. A reduction in rash severity was evidenced in all patients, along with improved QoL. Larger controlled studies are in development to evaluate the efficacy of benralizumab for the prevention of alpelisib rash. Clinical trial information: NCT04552288.

Classification of Basal Cell Carcinoma in Ex Vivo Confocal Microscopy Images from Freshly Excised Tissues Using a Deep Learning Algorithm

Ex vivo confocal microscopy (EVCM) generates digitally colored purple-pink images similar to H&E without time-consuming tissue processing. It can be used during Mohs surgery for rapid detection of basal cell carcinoma (BCC); however, reading EVCM images requires specialized training. An automated approach using a deep learning algorithm for BCC detection in EVCM images can aid in diagnosis. A total of 40 BCCs and 28 negative (not-BCC) samples were collected at Memorial Sloan Kettering Cancer Center to create three training datasets: (i) EVCM image dataset (663 images), (ii) H&E image dataset (516 images), and (iii) a combination of the two datasets. A total of seven BCCs and four negative samples were collected to create an EVCM test dataset (107 images). The model trained with the EVCM dataset achieved 92% diagnostic accuracy, similar to the H&E model (93%). The area under the receiver operator characteristic curve was 0.94, 0.95, and 0.94 for EVCM-, H&E-, and combination-trained models, respectively. We developed an algorithm for automatic BCC detection in EVCM images (comparable accuracy to dermatologists). This approach could be used to assist with BCC detection during Mohs surgery. Furthermore, we found that a model trained with only H&E images (which are more available than EVCM images) can accurately detect BCC in EVCM images.

Combined PARP1-targeted nuclear contrast and reflectance contrast enhances confocal microscopic detection of basal cell carcinoma

Reflectance confocal microscopy (RCM) with endogenous backscattered contrast can noninvasively image basal cell carcinomas (BCCs) in skin. However, BCCs present with high nuclear density and the relatively weak backscattering from nuclei impose a fundamental limit on contrast, detectability, and diagnostic accuracy. We investigated PARPi-FL, an exogenous nuclear poly (ADP-ribose) polymerase (PARP1)-targeted fluorescent contrast agent and fluorescence confocal microscopy (FCM) towards improving BCC diagnosis. Methods: We tested PARP1 expression in 95 BCC tissues using immunohistochemistry, followed by PARPi-FL staining in 32 fresh surgical BCC specimens. Diagnostic accuracy of PARPi-FL contrast was evaluated in 83 surgical specimens. Optimal parameters for trans-epidermal permeability of PARPi-FL through intact skin was tested ex vivo on 5 human skin specimens and in vivo in 3 adult Yorkshire pigs. Results: We found significantly higher PARP1 expression and PARPi-FL binding in BCCs, as compared to normal skin structures. Blinded reading of RCM-and-FCM images by two experts demonstrated a higher diagnostic accuracy for BCCs with combined fluorescence and reflectance contrast, as compared to RCM-alone. Optimal parameters (time and concentration) for PARPi-FL trans-epidermal permeation through intact skin were successfully determined. Conclusion: Combined fluorescence and reflectance contrast may improve noninvasive BCC diagnosis with confocal microscopy.