A reinforcement learning model for AI-based decision support in skin cancer

: We investigated whether human preferences hold the potential to improve diagnostic artificial intelligence (AI)-based decision support using skin cancer diagnosis as a use case. We utilized nonuniform rewards and penalties based on expert-generated tables, balancing the benefits and harms of various diagnostic errors, which were applied using reinforcement learning. Compared with supervised learning, the reinforcement learning model improved the sensitivity for melanoma from 61.4% to 79.5% (95% confidence interval (CI): 73.5-85.6%) and for basal cell carcinoma from 79.4% to 87.1% (95% CI: 80.3-93.9%). AI overconfidence was also reduced while simultaneously maintaining accuracy. Reinforcement learning increased the rate of correct diagnoses made by dermatologists by 12.0% (95% CI: 8.8-15.1%) and improved the rate of optimal management decisions from 57.4% to 65.3% (95% CI: 61.7-68.9%). We further demonstrated that the reward-adjusted reinforcement learning model and a threshold-based model outperformed naïve supervised learning in various clinical scenarios. Our findings suggest the potential for incorporating human preferences into image-based diagnostic algorithms

Risk of ablative therapy for "elevated firm growing" lesions: Merkel cell carcinoma diagnosed after laser surgical therapy

In the clinical assessment of melanoma, it has been proposed that Elevated, Firm and continuously Growing (‘‘EFG’’) be added to the well-known clinical ‘‘ABCD’’ rule.1 This is to improve detection of nodular melanoma, especially the amelanotic variant. Early detection of these rapidly growing lesions is essential if mortality is to be minimized. These ‘‘EFG’’ criteria will also detect other less common, aggressive skin malignancies such as Merkel cell carcinoma (MCC).2 MCC is a rare malignant primary cutaneous neoplasm with epithelial and neuroendocrine differentiation. 3 It is thought to derive from the Merkel cell, a neuroendocrine cell, first described by Friedrich Merkel in 1875.4 MCC was first reported in 1972 as trabecular carcinoma of the skin.5 Most MCCs are solitary and present as painless dome-shaped, pink nodules or plaques that may at times be ulcerated. Growth is typically rapid over a period of weeks to months. These clinical characteristics are summarized in the ‘‘EFG’’ rule, which has been primarily designed for the diagnosis of amelanotic nodular melanoma (AMM).1 Although spontaneous regression has been reported rarely,6 MCC has a high incidence of local recurrence, regional lymph node metastasis, and ultimately hematogenous or distant lymphatic spread. The tumor most frequently affects elderly patients, with a preference for the head and neck.7 Adverse prognostic factors include older age, location on the head and neck, size greater than 2 cm, immunosuppression, and advanced disease stage.8–10 Surgery has been the mainstay of treatment of primary MCC, with a 2- to 3-cm tumor-free margin recommended. This is often difficult to achieve on the head and neck, where Mohs micrographic surgery has proved to be effective.7 Recent evidence suggests that smaller margins may not necessarily compromise outcome if adjuvant radiotherapy is given.11 We present an 83-year-oldman with a rapidly growing pink nodule on his left forehead. In unusual circumstances, the lesion was initially treated using laser therapy without prior biopsy. It was subsequently diagnosed asMCC after wide excision of the treated area

Dermoscopy of squamous cell carcinoma and keratoacanthoma

Objectives: To characterize dermoscopic criteria of squamous cell carcinoma (SCC) and keratoacanthoma and to compare them with other lesions

Prediction without Pigment: a decision algorithm for non-pigmented skin malignancy

While there are several published comprehensive stepwise algorithmic methods for diagnosing pigmented skin malignancy, only limited material has been published for the stepwise assessment of non-pigmented lesions. We present a method based on pattern analysis, with a stepwise assessment, first, for ulceration, second, for white clues (defined as white lines, or in the case of a raised lesion any of the keratin clues: dermatoscopic white circles, dermatoscopic white structureless areas or surface keratin), and third, if no ulceration or white clues are present, proceed to vessel pattern analysis. This is a novel method, and apart from the assessment of white clues in raised lesions, it has not been formally tested. The priority of keratin clues in raised lesions over vessel pattern analysis has, however, been verified. It is conceded that this method is less specific than methods which have clues of pigmented structures, and accepting these limitations, Prediction without Pigment is a decision algorithm intended to guide the clinician in the decision as to whether to perform a biopsy rather than consistently leading to a specific diagnosis. Reaching a more specific diagnosis at the end of our flowchart can be achieved by weighing of clues both clinical and dermatoscopic, and that ability can be expected to improve with both knowledge and experience, but no diagnostic method, including this one, can be 100% sensitive in diagnosing malignancy, in particular, melanoma. Taking these limitations into account, any non-pigmented lesion, regardless of pattern analysis, which is raised and firm (nodular) and for which a confident, specific benign diagnosis cannot be made, should be excised to exclude the nodular variant of amelanotic melanoma

Dermatoscopy of facial actinic keratosis, intraepidermal carcinoma, and invasive squamous cell carcinoma: A progression model

Intraepidermal carcinoma (IEC) is a type of in situ squamous cell carcinoma (SCC), although progression of IEC is rare. We sought to investigate differences between the actinic skin changes preceding the development of both SCC and IEC. Photographs of 63 skin sites at which either SCC or IEC subsequently developed in 37 renal transplant recipients (RTRs) were examined for features of actinic change. We found that areas of skin with an actinic keratosis (AK) > 1 cm(2) in size were four times more likely to develop SCC as opposed to IEC (OR = 4.42; 95% CI 1.25-15.60). Skin sites with ≥ 25% of the area affected by AK were again four times more likely to develop SCC than IEC. These results highlight the scale of visible actinic damage required for development of SCC compared with IEC, emphasizing the importance of treating areas of skin with marked visible actinic change to reduce SCC risk in RTRs

Vascular Diameter as Clue for the Diagnosis of Clinically and/or Dermoscopically Equivocal Pigmented and Non-Pigmented Basal Cell Carcinomas and Nodular Melanomas

Background and objectives: Dermoscopy is a useful tool for the early and non-invasive diagnosis of skin malignancies. Besides many progresses, heavily pigmented and amelanotic skin tumors remain still a challenge. We aimed to investigate by dermoscopy if distinctive morphologic characteristics of vessels may help the diagnosis of equivocal nodular lesions. Materials and Methods: A collage of 16 challenging clinical and dermoscopic images of 8 amelanotic and 8 heavily pigmented nodular melanomas and basal cell carcinomas was sent via e-mail to 8 expert dermoscopists. Results: Dermoscopy improved diagnostic accuracy in 40 cases. Vessels were considered the best clue in 71 cases. Focusing on the diameter of vessels improved diagnosis in 5 cases. Conclusions: vascular diameter in addition to morphology and arrangement may be a useful dermoscopic clue for the differential diagnosis of clinically equivocal nodular malignant tumors

Gender-specific changes of the gut microbiome correlate with tumor development in murine models of pancreatic cancer

Summary: Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a dismal outcome. To improve understanding of sequential microbiome changes during PDAC development we analyzed mouse models of pancreatic carcinogenesis (KC mice recapitulating pre-invasive PanIN formation, as well as KPC mice recapitulating invasive PDAC) during early tumor development and subsequent tumor progression. Diversity and community composition were analyzed depending on genotype, age, and gender. Both mouse models demonstrated concordant abundance changes of several genera influenced by one or more of the investigated factors. Abundance was significantly impacted by gender, highlighting the need to further elucidate the impact of gender differences. The findings underline the importance of the microbiome in PDAC development and indicate that microbiological screening of patients at risk and targeting the microbiome in PDAC development may be feasible in future