Towards an Effective Imaging-Based Decision Support System for Skin Cancer

The usage of expert systems to aid in medical decisions has been employed since 1980s in distinct ap plications. With the high demands of medical care and limited human resources, these technologies are required more than ever. Skin cancer has been one of the pathologies with higher growth, which suf fers from lack of dermatology experts in most of the affected geographical areas. A permanent record of examination that can be further analyzed are medical imaging modalities. Most of these modalities were also assessed along with machine learning classification methods. It is the aim of this research to provide background information about skin cancer types, medical imaging modalities, data mining and machine learning methods, and their application on skin cancer imaging, as well as the disclosure of a proposal of a multi-imaging modality decision support system for skin cancer diagnosis and treatment assessment based in the most recent available technology. This is expected to be a reference for further implementation of imaging-based clinical support systems.info:eu-repo/semantics/publishedVersio

Technological Advances in the Diagnosis and Management of Pigmented Fundus Tumours

Choroidal naevi are the most common intraocular tumour. They can be pigmented or non-pigmented and have a predilection for the posterior uvea. The majority remain undetected and cause no harm but are increasingly found on routine community optometry examinations. Rarely does a naevus demonstrate growth or the onset of suspicious features to fulfil the criteria for a malignant melanoma. Because of this very small risk, optometrists commonly refer these patients to hospital eye units for a second opinion, triggering specialist examination and investigation, causing significant anxiety to patients and stretching medical resources. This PhD thesis introduces the MOLES acronym and scoring system that has been devised to categorise the risk of malignancy in choroidal melanocytic tumours according to Mushroom tumour shape, Orange pigment, Large tumour size, Enlarging tumour and Subretinal fluid. This is a simplified system that can be used without sophisticated imaging, and hence its main utility lies in the screening of patients with choroidal pigmented lesions in the community and general ophthalmology clinics. Under this system, lesions were categorised by a scoring system as ‘common naevus’, ‘low-risk naevus’, ‘high-risk naevus’ and ‘probable melanoma.’ According to the sum total of the scores, the MOLES system correlates well with ocular oncologists’ final diagnosis. The PhD thesis also describes a model of managing such lesions in a virtual pathway, showing that images of choroidal naevi evaluated remotely using a decision-making algorithm by masked non-medical graders or masked ophthalmologists is safe. This work prospectively validates a virtual naevus clinic model focusing on patient safety as the primary consideration. The idea of a virtual naevus clinic as a fast, one-stop, streamlined and comprehensive service is attractive for patients and healthcare systems, including an optimised patient experience with reduced delays and inconvenience from repeated visits. A safe, standardised model ensures homogeneous management of cases, appropriate and prompt return of care closer to home to community-based optometrists. This research work and strategies, such as the MOLES scoring system for triage, could empower community-based providers to deliver management of benign choroidal naevi without referral to specialist units. Based on the positive outcome of this prospective study and the MOLES studies, a ‘Virtual Naevus Clinic’ has been designed and adapted at Moorfields Eye Hospital (MEH) to prove its feasibility as a response to the COVID-19 pandemic, and with the purpose of reducing in-hospital patient journey times and increasing the capacity of the naevus clinics, while providing safe and efficient clinical care for patients. This PhD chapter describes the design, pathways, and operating procedures for the digitally enabled naevus clinics in Moorfields Eye Hospital, including what this service provides and how it will be delivered and supported. The author will share the current experience and future plan. Finally, the PhD thesis will cover a chapter that discusses the potential role of artificial intelligence (AI) in differentiating benign choroidal naevus from choroidal melanoma. The published clinical and imaging risk factors for malignant transformation of choroidal naevus will be reviewed in the context of how AI applied to existing ophthalmic imaging systems might be able to determine features on medical images in an automated way. The thesis will include current knowledge to date and describe potential benefits, limitations and key issues that could arise with this technology in the ophthalmic field. Regulatory concerns will be addressed with possible solutions on how AI could be implemented in clinical practice and embedded into existing imaging technology with the potential to improve patient care and the diagnostic process. The PhD will also explore the feasibility of developed automated deep learning models and investigate the performance of these models in diagnosing choroidal naevomelanocytic lesions based on medical imaging, including colour fundus and autofluorescence fundus photographs. This research aimed to determine the sensitivity and specificity of an automated deep learning algorithm used for binary classification to differentiate choroidal melanomas from choroidal naevi and prove that a differentiation concept utilising a machine learning algorithm is feasible

Risk factors and biomarkers for metastatic cutaneous squamous cell carcinoma

The incidence of cutaneous squamous cell carcinoma (cSCC), the most common skin cancer with metastatic potential, continues to increase. Although proportion of cSCCs metastasize and cause mortality, sufficient means to identify the metastasis-prone tumors are not available. In this thesis the metastatic cSCCs from the area served by Turku University Hospital were identified and characterized revealing that the rate of metastasis in the study region was 2.3%. Further, it was discovered that metastasis occurs rapidly and that there was no history of cSCC in 85% of patients with metastatic cSCC. Invasion depth, tumor diameter, age and location on lower lip or forehead were associated with increased risk of metastasis. On the other hand, usage of isosorbide mono-/dinitrate and aspirin as well as comorbidity with premalignant lesions or basal cell carcinoma were associated with lower risk of metastasis. With multiplexed immunohistochemistry, it was demonstrated that the activity and phenotype of cancer-associated fibroblasts (CAFs) evolve during the progression of cSCC. Elevation of α-smooth muscle actin (αSMA), secreted protein acidic and rich in cysteine (SPARC) and fibroblast activating protein (FAP) expression was associated with invasion and expression of FAP and platelet-derived growth factor receptor-β (PDGFRβ) with metastasis. High expression of stromal PDGFRβ and periostin were associated with worse prognosis. CAF107 (PDGFRα-/PDGFRβ+/FAP+) subset was associated with invasion and metastasis, and predicted poor prognosis of cSCC. A deep learning algorithm was harnessed to distinguish primary tumors that metastasize rapidly from non-metastatic cSCCs with slide level area under the receiver operating characteristic curve (AUROC) of 0.747 on whole slide images representing primary cSCCs. Furthermore, a risk factor model, that utilized prediction by AI, was created and provided staging systems and comparative risk factor models surpassing classification and prognostivity. These results characterize features associated with the metastasis risk of cSCC and indicate that CAF-markers and AI could provide clinical tools for the metastasis risk assessment and thus improve the prognosis of patient with metastatic cSCC.Etäpesäkkeitä lähettävän okasolusyövän riskitekijät ja biomarkkerit Yleisimmän etäpesäkkeitä lähettävän ihosyövän, okasolusyövän, ilmaantuvuus jatkaa kasvuaan. Vaikka osa okasolusyövistä lähettää etäpesäkkeitä ja aiheuttaa kuolleisuutta, ei etäpesäkkeitä lähettämään tulevien okasolusyöpien tunnistamiseksi ole toistaiseksi riittäviä keinoja. Tässä väitöskirjassa karakterisoitiin Turun yliopistollisen keskussairaalan vastuualueen metastasoituneet okasolusyövät ja osoitettiin että tutkimusalueen okasolusyövistä 2.3% etenee etäpesäkkeitä lähettäväksi. Metastasoituminen tapahtui nopeasti ja valtaosassa tapauksista (85%) etäpesäkkeen lähetti ensimmäinen potilaalla todettu okasolusyöpä. Ikä, kasvaimen invaasiosyvyys, halkaisija ja sijainti alahuulessa tai otsalla yhdistyivät kohonneeseen metastaasiriskiin. Isosorbidinitraatin ja aspiriinin käyttö sekä esiasteiden ja tyvisolusyövän esiintyminen taas liittyivät alentuneeseen metastaasiriskiin. Multiplex-immunohistokemiaa hyödyntäen osoitettin, että syöpään liittyvien fibroblastien (CAF) aktiviteetti ja ilmiasu muuttuu okasolusyövän edetessä. Kohonnut sileälihasaktiini alfan (αSMA), osteonektiinin ja fibroblastia aktivoivan proteiinin (FAP) ilmentyminen liittyi invaasioon ja FAP:n sekä verihiutaleista johdetun kasvutekijäreseptori β:n (PDGFRβ) etäpesäkkeiden lähettämiseen. PDGFRβ:n ja periostiinin ilmentyminen taas yhdistyi huonoon ennusteeseen. CAF107 (PDGFRα-/PDGFRβ+/FAP+) alatyyppi liittyi invaasioon, metastasointiin ja huonoon ennusteeeseen. Etäpesäkkeitä lähettämään tulevien okasolusyöpien tunnistamiseen valjastettu syväoppimisalgoritmi erotti okasolusyöpiä edustavista digitalisoiduista mikroskopiakuvista nopeasti etäpesäkkeitä lähettävät okasolusyövät okasolusyövistä, jotka eivät lähetä etäpesäkkeitä, leiketason AUROC-arvolla 0.747. Tekoälyarviota hyödyntävä riskitekijämalli voitti luokittelujärjestelmät ja kilpailevat riskitekijämallit okasolusyöpien luokittelussa ja ennusteen arvioinnissa. Tulokset antavat lisätietoa metastasoituvan okasolusyövän luonteesta ja osoittavat CAF-markkereiden sekä tekoälyn voivan tarjota kliinisiä työkaluja okasolusyövän metastaasiriskin arviointiin ja täten voivan parantaa etäpesäkkeitä lähettävän okasolusyöpäpotilaan ennustetta tulevaisuudessa

Mechanisms and Novel Therapeutic Approaches for Gynecologic Cancer

This book—entitled “Mechanisms and Novel Therapeutic Approaches for Gynecologic Cancer”—was edited as a Special Issue of Biomedicines, focusing on basic research such as genomics, epigenomics, and proteomics, as well as clinical research in the field of gynecologic oncology. The number of patients with gynecological cancer has been increasing worldwide due to its high lethality and lack of early detection tools and effective therapeutic interventions. In this regard, basic research on its pathophysiology and novel molecular targeting intervention is required to improve the prognosis of gynecologic cancer. This book contains 13 papers, including 8 original research papers and 5 reviews focusing on the basic research of gynecologic oncology. The reader can learn about state-of-the-art research and obtain extensive knowledge of the current advances in the field of gynecologic oncology. It is my hope that this book contributes towards the progress of gynecologic oncology

Textbook on Scar Management

This text book is open access under a CC BY 4.0 license. Written by a group of international experts in the field and the result of over ten years of collaboration, it allows students and readers to gain to gain a detailed understanding of scar and wound treatment – a topic still dispersed among various disciplines. The content is divided into three parts for easy reference. The first part focuses on the fundamentals of scar management, including assessment and evaluation procedures, classification, tools for accurate measurement of all scar-related elements (volume density, color, vascularization), descriptions of the different evaluation scales. It also features chapters on the best practices in electronic-file storage for clinical reevaluation and telemedicine procedures for safe remote evaluation. The second section offers a comprehensive review of treatment and evidence-based technologies, presenting a consensus of the various available guidelines (silicone, surgery, chemical injections, mechanical tools for scar stabilization, lasers). The third part evaluates the full range of emerging technologies offered to physicians as alternative or complementary solutions for wound healing (mechanical, chemical, anti-proliferation). Textbook on Scar Management will appeal to trainees, fellows, residents and physicians dealing with scar management in plastic surgery, dermatology, surgery and oncology, as well as to nurses and general practitioners ; Comprehensive reference covering the complete field of wounds and scar management: semiology, classifications and scoring Highly educational contents for trainees as well as professionals in plastic surgery, dermatology, surgery, oncology as well as nurses and general practitioners Fast access to information through key points, take home messages, highlights, and a wealth of clinical cases Book didactic contents enhanced by supplementary material and video