Artificial intelligence in digital pathology of cutaneous lymphomas: A review of the current state and future perspectives

Primary cutaneous lymphomas (CLs) represent a heterogeneous group of T-cell lymphomas and B-cell lymphomas that present in the skin without evidence of extracutaneous involvement at time of diagnosis. CLs are largely distinct from their systemic counterparts in clinical presentation, histopathology, and biological behavior and, therefore, require different therapeutic management. Additional diagnostic burden is added by the fact that several benign inflammatory dermatoses mimic CL subtypes, requiring clinicopathological correlation for definitive diagnosis. Due to the heterogeneity and rarity of CL, adjunct diagnostic tools are welcomed, especially by pathologists without expertise in this field or with limited access to a centralized specialist panel. The transition into digital pathology workflows enables artificial intelligence (AI)-based analysis of patients’ whole-slide pathology images (WSIs). AI can be used to automate manual processes in histopathology but, more importantly, can be applied to complex diagnostic tasks, especially suitable for rare disease like CL. To date, AI-based applications for CL have been minimally explored in literature. However, in other skin cancers and systemic lymphomas, disciplines that are recognized here as the building blocks for CLs, several studies demonstrated promising results using AI for disease diagnosis and subclassification, cancer detection, specimen triaging, and outcome prediction. Additionally, AI allows discovery of novel biomarkers or may help to quantify established biomarkers. This review summarizes and blends applications of AI in pathology of skin cancer and lymphoma and proposes how these findings can be applied to diagnostics of CL

The Advanced Applications For Optical Coherence Tomography In Skin Imaging

Optical coherence tomography (OCT), based on the principle of interferometry, is a fast and non-invasive imaging modality, which has been approved by FDA for dermatologic applications. OCT has high spatial resolution up to micrometer scale compared to traditional ultrasound imaging. In addition, OCT can provide real-time cross-sectional images with 1 to 2 mm penetration depth, which makes it an ideal imaging technique to assess the skin micro-morphology and pathology without any tissue removal. Many studies have investigated the possibilities of using OCT to evaluate dermatologic conditions, such as skin cancer, dermatitis, psoriasis, and skin damages. Hence, OCT has tremendous potential to provide skin histological and pathological information and assist differential diagnosis of various skin diseases. In this study, we used a swept-source OCT with 1305 nm central wavelength to explore its advanced applications in dermatology. This dissertation consists of four major research projects. First, we explored the feasibility of OCT imaging for assisting real-time visualization in skin biopsy. We showed that OCT could be used to guide and track a needle insertion in mouse skin in real-time. The structure of skin and the movement of needle can be clearly seen on the OCT images without any time delay during the procedures. Next, we tested the concept of performing the punch biopsy using OCT hand-held probe attached to a piercing tip in a phantom. We proved that using the OCT is a reliable technique to delineate the margin of lesion in phantom. And it is possible to perform the punch biopsy with the OCT probe. Second, we tested the performance of contrast-enhanced OCT in melanoma detection in an in vitro study. Melanoma is the most lethal type of skin cancer. Early detection could significantly improve the long-term survival rate of patients. In this initial study, a contrast agent (Gal3-USGNPs) is developed by conjugating melanoma biomarker (Gal3) to ultra-small gold nanoparticles (USGNPs). We showed that the contrast agent can differentiate B16 melanoma cells from normal skin keratinocytes in vitro. To avoid systemic administration of USGNPs, the third project continues to explore the enhanced topical delivery of USGNPs. In this study, we used OCT to monitor the topical delivery of nanoparticles on pig skin over time. And the diffusion and penetration of USGNPs in skin can be improved by applying chemical and physical enhancers such as DMSO and sonophoresis. Finally, in addition to image the cross-sectional structure of skin, we also aim to extract quantitative information from OCT images. The skin optical properties such as attenuation coefficient can be measured from OCT images. We measured and compared the skin attenuation coefficient in the skin of forehead and lateral hip, the skin of three different age groups, and the skin of three different Fitzpatrick types. The statistical analysis showed that epidermis has much higher attenuation coefficient than dermis. And the skin type V & VI have a relatively lower attenuation coefficient than the other skin types. These studies could aid the detection of skin cancer using imaging techniques and provide some new insights into the future applications of OCT in dermatology

Dynamic optical coherence tomography of blood vessels in cutaneous melanoma — correlation with histology, immunohistochemistry and dermoscopy

Dermoscopy adds important information to the assessment of cutaneous melanoma, but the risk of progression is predicted by histologic parameters and therefore requires surgery and histopathologic preparation. Neo-vascularization is crucial for tumor progression and worsens prognosis. The aim of this study was the in vivo evaluation of blood vessel patterns in melanoma with dynamic optical coherence tomography (D-OCT) and the correlation with dermoscopic and histologic malignancy parameters for the risk assessment of melanoma. In D-OCT vessel patterns, shape, distribution and presence/type of branching of 49 melanomas were evaluated in vivo at three depths and correlated with the same patterns in dermoscopy and with histologic parameters after excision. In D-OCT, blood vessel density and atypical shapes (coils and serpiginous vessels) increased with higher tumor stage. The histologic parameters ulceration and Hmb45- and Ki67-positivity increased, whereas regression, inflammation and PD-L1-positivity decreased with risk. CD31, VEGF and Podoplanin correlated with D-OCT vasculature findings. B-RAF mutation status had no influence. Due to pigment overlay and the summation effect, the vessel evaluation in dermoscopy and D-OCT did not correlate well. In summary, atypical vessel patterns in melanoma correlate with histologic parameters for risk for metastases. Tumor vasculature can be noninvasively assessed using D-OCT before surgery

Molecular classification and prediction of metastatic potential in early malignant melanoma: improvement of prognostic accuracy by quantitative in situ proteomic analysis

The incidence of cutaneous malignant melanoma continues to increase every year, and remains the leading cause of skin cancer death in industrialized countries. In spite of the aggressive nature of advanced melanoma, there are no standard biological assays in clinical usage that can predict metastasis. This may be due, in part, to the inadequacy of reproducible assessment of protein expression using traditional immunohistochemistry. This dissertation will discuss the use of tissue microarrays combined with quantitative in situ molecular analysis of protein expression to allow prediction of melanoma metastasis. Through the identification and validation of novel prognostic biomarkers, we seek to identify subsets of patients that are at high or low risk for melanoma recurrence or melanoma-related death. Some of these biomarkers may also serve as potential targets for future biologic therapy in melanoma, a disease for which no effective medical treatment is currently available. We demonstrate that quantitative assessment of a small number of markers is predictive of metastasis and outcome, augmenting the current system of prognosis.The dissertation begins with a brief introduction on the current state of melanoma diagnosis, staging, and treatment, as well as a review of current efforts to understand the biology of melanoma progression and metastasis. The fundamentals of tissue microarray technology are then described. Critical aspects of quantitative immunohistochemistry, including a description of the Automated Quantitative Analysis (AQUA) system developed in our laboratory, are also addressed. The second chapter demonstrates the use of tissue microarray technology to examine melanoma specimens by the current field standard, with a study of activating transcription factor 2 (ATF2); an example of semi-quantitative immunohistochemical analysis of protein expression. The third chapter provides validation of the AQUA technology on melanoma tissue by evaluation of the human homologue of murine double minute 2 protein (HDM2). Chapter four demonstrates an example of the critical--and beneficial--aspect of subcellular compartmentalization that the AQUA system provides, demonstrating that the ratio of cytoplasmic-to-nuclear expression of activator protein 2 (AP-2) predicts outcome in melanoma patients. The last chapter draws these concepts together and presents results from the analysis of 50 protein biomarkers in melanoma. It also introduces the use of a number of statistical methods (traditional and novel) employed to develop an optimal biomarker set for future analyses

Improving biomarker assessment in breast pathology

The accuracy of prognostic and therapy-predictive biomarker assessment in breast tumours is crucial for management and therapy decision in patients with breast cancer. In this thesis, biomarkers used in clinical practice with emphasise on Ki67 and HER2 were studied using several methods including immunocytochemistry, in situ hybridisation, gene expression assays and digital image analysis, with the overall aim to improve routine biomarker evaluation and clarify the prognostic potential in early breast cancer. In paper I, we reported discordances in biomarker status from aspiration cytology and paired surgical specimens from breast tumours. The limited prognostic potential of immunocytochemistry-based Ki67 scoring demonstrated that immunohistochemistry on resected specimens is the superior method for Ki67 evaluation. In addition, neither of the methods were sufficient to predict molecular subtype. Following this in paper II, biomarker agreement between core needle biopsies and subsequent specimens was investigated, both in the adjuvant and neoadjuvant setting. Discordances in Ki67 and HER2 status between core biopsies and paired specimens suggested that these biomarkers should be re-tested on all surgical breast cancer specimens. In paper III, digital image analysis using a virtual double staining software was used to compare methods for assessment of proliferative activity, including mitotic counts, Ki67 and the alternative marker PHH3, in different tumour regions (hot spot, invasive edge and whole section). Digital image analysis using virtual double staining of hot spot Ki67 outperformed the alternative markers of proliferation, especially in discriminating luminal B from luminal A tumours. Replacing mitosis in histological grade with hot spot-scored Ki67 added significant prognostic information. Following these findings, the optimal definition of a hot spot for Ki67 scoring using virtual double staining in relation to molecular subtype and outcome was investigated in paper IV. With the growing evidence of global scoring as a superior method to improve reproducibility of Ki67 scoring, a different digital image analysis software (QuPath) was also used for comparison. Altogether, we found that automated global scoring of Ki67 using QuPath had independent prognostic potential compared to even the best virtual double staining hot spot algorithm, and is also a practical method for routine Ki67 scoring in breast pathology. In paper V, the clinical value of HER2 status was investigated in a unique trastuzumab-treated HER2-positive cohort, on the protein, mRNA and DNA levels. The results demonstrated that low levels of ERBB2 mRNA but neither HER2 copy numbers, HER2 ratio nor ER status, was associated with risk of recurrence among anti-HER2 treated breast cancer patients. In conclusion, we have identified important clinical aspects of Ki67 and HER2 evaluation and provided methods to improve the prognostic potential of Ki67 using digital image analysis. In addition to protein expression of routine biomarkers, mRNA levels by targeted gene expression assays may add further prognostic value in early breast cance

Image analysis of cutaneous melanoma histology: a systematic review and meta-analysis

The current subjective histopathological assessment of cutaneous melanoma is challenging. The application of image analysis algorithms to histological images may facilitate improvements in workflow and prognostication. To date, several individual algorithms applied to melanoma histological images have been reported with variations in approach and reported accuracies. Histological digital images can be created using a camera mounted on a light microscope, or through whole slide image (WSI) generation using a whole slide scanner. Before any such tool could be integrated into clinical workflow, the accuracy of the technology should be carefully evaluated and summarised. Therefore, the objective of this review was to evaluate the accuracy of existing image analysis algorithms applied to digital histological images of cutaneous melanoma. Database searching of PubMed and Embase from inception to 11th March 2022 was conducted alongside citation checking and examining reports from organisations. All studies reporting accuracy of any image analysis applied to histological images of cutaneous melanoma, were included. The reference standard was any histological assessment of haematoxylin and eosin-stained slides and/or immunohistochemical staining. Citations were independently deduplicated and screened by two review authors and disagreements were resolved through discussion. The data was extracted concerning study demographics; type of image analysis; type of reference standard; conditions included and test statistics to construct 2 × 2 tables. Data was extracted in accordance with our protocol and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Diagnostic Test Accuracy (PRISMA-DTA) Statement. A bivariate random-effects meta-analysis was used to estimate summary sensitivities and specificities with 95% confidence intervals (CI). Assessment of methodological quality was conducted using a tailored version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The primary outcome was the pooled sensitivity and specificity of image analysis applied to cutaneous melanoma histological images. Sixteen studies were included in the systematic review, representing 4,888 specimens. Six studies were included in the meta-analysis. The mean sensitivity and specificity of automated image analysis algorithms applied to melanoma histological images was 90% (CI 82%, 95%) and 92% (CI 79%, 97%), respectively. Based on limited and heterogeneous data, image analysis appears to offer high accuracy when applied to histological images of cutaneous melanoma. However, given the early exploratory nature of these studies, further development work is necessary to improve their performance

Immune profiling of the tumour microenvironment in prostate cancer

Prostate cancer is the most common cancer among men in the UK and is characterised by large biological and clinical heterogeneity. There is an urgent need for better-personalised patient stratification, for example in accurately identifying patients with regional lymph node metastasis. Nodal involvement negatively impacts on patient survival outcomes and the current pre-operative staging tools to determine the need for extended pelvic lymph node dissection at time of radical prostatectomy are far from precise. The primary tumour immune microenvironment influences tumour immune editing and therefore disease progression. The primary aim of this research was to investigate the in situ phenotype of prostate cancer tumour infiltrating immune cells and determine their potential as biomarkers for regional lymph node invovlement and further explore possible underlying mechanisms for their distribution. The discovery tissue microarray comprised of index lesions from 94 patients undergoing radical prostatectomy and pelvic node dissection (50 with and 44 without histologic evidence of pelvic nodal disease respectively, referred to as LN+ and LN- thereafter). Two multiplex immunofluorescence panels were optimised to comprehensively characterise the immune microenvironment: (1) The macrophage and B cell panel includes CD68, CD163, CD20, AE1/3 (PanCK) and DAPI and (2) The T lymphocytic panel assays for CD4, CD8, FoxP3, PD-1, AE1/3 and DAPI. The macrophage (CD68, CD163+), T (CD8+, CD4+) and B (CD20+) cell immune cell subpopulations within the malignant epithelium and associated stroma were measured and correlated to the nodal status. Stromal infiltration by M1-like macrophages (CD68+CD163-) (p=0.047), CD8 effector (CD8+FoxP3-PD-1-) (p=0.008) and CD4 effector (CD4+FoxP3-PD-1-) T cells (p=0.0003, Mann Whitney test) were lower in LN+ patients. Stromal CD4 effector immune cell density remained a statistically significant independent predictor of lymph node spread in multivariate regression analysis (OR= 0.15, p=0.004). Additionally, in an independent validation cohort of 184 radical prostatectomy specimens, stromal CD4 effector immune cell density predicted the presence of nodal metastasis (OR=0.26, p=0.0004). Addition of stromal CD4 effector T cell density to currently used clinicopathological factors, namely T stage, PSA level, Gleason score and percentage of tumour positive cores, improved the predictive accuracy of current nomograms (from 63.5% to 76.8%, p<0.0001). Tumour infiltrating immune cells did not however correlate with common molecular alterations of prostate cancer such as ERG overexpression and PTEN deletion. Transcriptomic analysis (by HTG EdgeSeq) of the tumour microenvironment was performed to assay 1,041 host immune response related genes. Surprisingly, I did not observe significant differences in the expression levels of adhesion molecules or chemokines (common regulators of immune cell migration) between LN+ and LN- cases. Instead, there was significant upregulation (FC>1.5, adj p value <0.05) of extracellular matrix components (collagen I, collagen III, fibronectin 1) in LN+ tumours, suggesting increased extracellular matrix fibrosis to be associated with reduced T lymphocytic infiltration and tumour immune evasion. Increased collagen III and fibronectin 1 protein expression were confirmed in LN+ patients. Collagen I had increased density score (by second generation harmonic), but not overall abundance, in LN+ patients, eluding to a disorganised stroma with increased cross-linking and elongated fibres. B7-H3 is a newly discovered member of the B7 family of immune checkpoint molecules with both immune and non-immune functions. I investigated the relationship of B7-H3 to the tumour microenvironment as well as its non-immune functions in prostate cancer. Contrast to PD-1, high B7-H3 expression correlated with worse clinicopathological patient features: higher T stage (p<0.0001), perineural invasion (p=0.01) and lymph node spread (p=0.0006). Furthermore, there was significant decrease in migration and invasion in vitro following suppressed B7-H3 expression in multiple human prostate cancer cell lines. RNA sequencing identified extracellular space chemotactic cytokines and their receptors to be highly downregulated genes in PC3M cells with B7-H3 knocked out. Future experiments will investigate the mechanistic downstream pathways of this phenotype and further evaluate the role of B7-H3 in metastasis in vivo. Data presented in this thesis reveal differences in the immune infiltrates, particularly CD4 effector (CD4+FoxP3-PD-1-) T cells between LN+ and LN- patients. Prospective clinical studies are needed to test the predictive value of stromal CD4 effector T cell density in diagnostic prostatic biopsies for regional nodal disease. The role of increased extracellular matrix components in determining tumour immune infiltrates also warrants additional research

Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine

Radiogenomics, a combination of “Radiomics” and “Genomics,” using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computa-tional as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles

ЦИФРОВА ПАТОЛОГІЯ ПРИ МЕЛАНОМІ: ДОСЯГНЕННЯ, БАР’ЄРИ ТА ПЕРСПЕКТИВИ

Background. This review is focused on the assessment of the current state of development and implementation of digital pathology in pathologists practice for better diagnostics, counseling, and personalization of melanoma treatment. Materials and methods. The data concerning the digital pathology tools used for melanoma diagnostics and prognostic/ predictive biomarkers assessment were extracted and analysed. Results. The convergence of digital pathology and artificial intelligence has led to a paradigm shift in pathologists' practice. Thanks to digital pathology, pathologists got the opportunity to improve the accuracy, efficiency and consistency of melanoma diagnosis. Access to digital tools with assessing whole slide images facilitated improvement of the remote primary diagnostics, provision of teleconsultations, increased efficiency and balance of workload, improves collaboration between general pathologists and dermatopathologists, flourished virtual education and innovative studies. Detection of sub-visual morphometric features and integration of multi-omics data are prerequisites for improving prognostic and predictive information for personalizing the treatment of melanoma patients, which discovers new prospects for precision medicine. Conclusions. Despite the progress in digital pathology, the implementation of artificial intelligence in diagnostic algorithms of pathologists and personalized treatment requires to solve a number of challenges related to the development and clinical validation of digital tools.В огляді проаналізовано сучасний стан розвитку та впровадження цифрової патології у патологоанатомічну практику з метою діагностики, консультування та персоналізації лікування меланоми. Конвергенція цифрової патології та штучного інтелекту призвела до зміни парадигм у патолоанатомічній практиці. Завдяки цифровій патології, патологоанатоми мають можливість покращити точність, ефективність і узгодженість діагностики меланоми. Доступ до цифрових слайдів полегшує дистанційну первинну діагностичну роботу. Надання телеконсультацій, підвищує ефективність і збалансованість робочого навантаження, покращує співпрацю між загальними патологами та дерма-топатологами, стимулює віртуальну освіту та інноваційні дослідження. Виявлення субвізуальних морфометричних особливостей та інтеграція даних мультиоміки являються передумовами покращення прогностичної та предиктив-ної інформації для персоналізації лікування пацієнтів із меланомою, що відкриває нові перспективи прецизійної медицини. Однак впровадження цифрової патології в алгоритми діагностики та персоналізованого лікування потребує вирішення низки важливих проблем, пов'язаних із клінічною валідацією цифрових інструментів

Evaluation of PD-L1 expression in various formalin-fixed paraffin embedded tumour tissue samples using SP263, SP142 and QR1 antibody clones

Background & objectives: Cancer cells can avoid immune destruction through the inhibitory ligand PD-L1. PD-1 is a surface cell receptor, part of the immunoglobulin family. Its ligand PD-L1 is expressed by tumour cells and stromal tumour infltrating lymphocytes (TIL). Methods: Forty-four cancer cases were included in this study (24 triple-negative breast cancers (TNBC), 10 non-small cell lung cancer (NSCLC) and 10 malignant melanoma cases). Three clones of monoclonal primary antibodies were compared: QR1 (Quartett), SP 142 and SP263 (Ventana). For visualization, ultraView Universal DAB Detection Kit from Ventana was used on an automated platform for immunohistochemical staining Ventana BenchMark GX. Results: Comparing the sensitivity of two different clones on same tissue samples from TNBC, we found that the QR1 clone gave higher percentage of positive cells than clone SP142, but there was no statistically significant difference. Comparing the sensitivity of two different clones on same tissue samples from malignant melanoma, the SP263 clone gave higher percentage of positive cells than the QR1 clone, but again the difference was not statistically significant. Comparing the sensitivity of two different clones on same tissue samples from NSCLC, we found higher percentage of positive cells using the QR1 clone in comparison with the SP142 clone, but once again, the difference was not statistically significant. Conclusion: The three different antibody clones from two manufacturers Ventana and Quartett, gave comparable results with no statistically significant difference in staining intensity/ percentage of positive tumour and/or immune cells. Therefore, different PD-L1 clones from different manufacturers can potentially be used to evaluate the PD- L1 status in different tumour tissues. Due to the serious implications of the PD-L1 analysis in further treatment decisions for cancer patients, every antibody clone, staining protocol and evaluation process should be carefully and meticulously validated