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  • 1
    In: JEADV Clinical Practice, Wiley
    Abstract: Cutaneous metastases (CM) are a frequent finding in the follow‐up of malignant tumours. Objectives CM were examined with dermoscopy, optical coherence tomography (OCT), dynamic OCT and line‐field confocal OCT (LC‐OCT) to describe common findings. Methods In the University Hospital Carl Gustav Carus Dresden, Germany, 18 patients with 61 CM were examined with dermoscopy. CM ( n = 43, 31 melanoma metastases, two metastases of renal carcinoma, five metastases of cutaneous squamous cell carcinoma and five metastases of pleomorphic dermal sarcoma) were examined with OCT (VivoSight® Michelson Diagnostics). Additional 18 melanoma metastases were examined with LC‐OCT (deepLive™; Damae Medical). Results CM were localized on the head, trunk, neck and limbs. Dermoscopy patterns were angioma‐like, nevus‐like nonglobular, nevus‐like globular, blue nevus‐like and unspecific. CM showed an ulceration, hyperkeratosis with increased entrance signal and disturbed architecture of the epidermis in OCT. In deeper metastases, the dermoepidermal junction (DEJ) was normal; in most cases it was disturbed. CM were visible as subepidermal hyporeflective roundish area, with septae, with either clear margin and shadowing or blurred margin. DOCT showed dot, coiled, serpiginous and branched vessels; there was a disarray in size and distribution and vessels were converging on the centre of the metastasis. In LC‐OCT, CM showed enhanced entrance signal and disturbed architecture of a thinned epidermis, ulceration, atypical honeycomb or cobblestone pattern as well as a broken DEJ. In the dermis, a hyporeflective roundish area with clusters of hyporeflective cells with septae, clear margin and clefting or blurred margin was visible; the hyporeflective area was surrounded by bundles of connective tissue. Subepidermal vessels differentiated in size and distribution. Inflammatory, dendritic and pagetoid cells were visible. Conclusions OCT and LC‐OCT may be useful tools for immediate diagnosis, localization of CM and monitoring under treatment in addition to conventional methods like ultrasound and histopathology.
    Type of Medium: Online Resource
    ISSN: 2768-6566 , 2768-6566
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 3110501-4
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  • 2
    In: Cancers, MDPI AG, Vol. 13, No. 6 ( 2021-03-20), p. 1430-
    Abstract: This decade has brought significant survival improvement in patients with metastatic melanoma with targeted therapies and immunotherapies. As our understanding of the mechanisms of action of these therapeutics evolves, even more impressive therapeutic success is being achieved through various combination strategies, including combinations of different immunotherapies as well as with other modalities. This review summarizes prospectively and retrospectively generated clinical evidence on modern melanoma therapy, focusing on immunotherapy and targeted therapy with BRAF kinase inhibitors and MEK kinase inhibitors (BRAF/MEK inhibitors), including recent data presented at major conference meetings. The combination of the anti-PD-1 directed monoclonal antibody nivolumab and of the CTLA-4 antagonist ipilimumab achieves unprecedented 5-year overall survival (OS) rates above 50%; however, toxicity is high. For PD-1 monotherapy (nivolumab or pembrolizumab), toxicities are in general well manageable. Today, novel combinations of such immune checkpoint inhibitors (ICIs) are under investigation, for example with cytokines and oncolytic viruses (i.e., pegylated interleukin-2, talimogene laherparepvec). Furthermore, current studies investigate the combined or sequential use of ICIs plus BRAF/MEK inhibitors. Several studies focus particularly on poor prognosis patients, as e.g., on anti-PD-1 refractory melanoma, patients with brain metastases, or uveal melanoma. It is hoped, on the road to cure, that these new approaches further improve long term survival in patients with advanced or metastatic melanoma.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2527080-1
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  • 3
    In: Journal of Medical Internet Research, JMIR Publications Inc., Vol. 23, No. 7 ( 2021-7-2), p. e20708-
    Abstract: Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical practice, dermatologists also use other patient data beyond the visual aspects present in a digitized image, further increasing their diagnostic accuracy. Several pilot studies have recently investigated the effects of integrating different subtypes of patient data into CNN-based skin cancer classifiers. Objective This systematic review focuses on the current research investigating the impact of merging information from image features and patient data on the performance of CNN-based skin cancer image classification. This study aims to explore the potential in this field of research by evaluating the types of patient data used, the ways in which the nonimage data are encoded and merged with the image features, and the impact of the integration on the classifier performance. Methods Google Scholar, PubMed, MEDLINE, and ScienceDirect were screened for peer-reviewed studies published in English that dealt with the integration of patient data within a CNN-based skin cancer classification. The search terms skin cancer classification, convolutional neural network(s), deep learning, lesions, melanoma, metadata, clinical information, and patient data were combined. Results A total of 11 publications fulfilled the inclusion criteria. All of them reported an overall improvement in different skin lesion classification tasks with patient data integration. The most commonly used patient data were age, sex, and lesion location. The patient data were mostly one-hot encoded. There were differences in the complexity that the encoded patient data were processed with regarding deep learning methods before and after fusing them with the image features for a combined classifier. Conclusions This study indicates the potential benefits of integrating patient data into CNN-based diagnostic algorithms. However, how exactly the individual patient data enhance classification performance, especially in the case of multiclass classification problems, is still unclear. Moreover, a substantial fraction of patient data used by dermatologists remains to be analyzed in the context of CNN-based skin cancer classification. Further exploratory analyses in this promising field may optimize patient data integration into CNN-based skin cancer diagnostics for patients’ benefits.
    Type of Medium: Online Resource
    ISSN: 1438-8871
    Language: English
    Publisher: JMIR Publications Inc.
    Publication Date: 2021
    detail.hit.zdb_id: 2028830-X
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  • 4
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2018
    In:  Der Onkologe Vol. 24, No. S2 ( 2018-11), p. 99-103
    In: Der Onkologe, Springer Science and Business Media LLC, Vol. 24, No. S2 ( 2018-11), p. 99-103
    Type of Medium: Online Resource
    ISSN: 0947-8965 , 1433-0415
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
    detail.hit.zdb_id: 3120761-3
    detail.hit.zdb_id: 1462966-5
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  • 5
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2022
    In:  best practice onkologie Vol. 17, No. 1-2 ( 2022-02), p. 8-16
    In: best practice onkologie, Springer Science and Business Media LLC, Vol. 17, No. 1-2 ( 2022-02), p. 8-16
    Type of Medium: Online Resource
    ISSN: 0946-4565 , 1862-8559
    Language: German
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2268240-5
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  • 6
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 24, No. 14 ( 2023-07-14), p. 11443-
    Abstract: Leptomeningeal disease (LMD) is a devastating complication of cancer with a particularly poor prognosis. Among solid tumours, malignant melanoma (MM) has one of the highest rates of metastasis to the leptomeninges, with approximately 10–15% of patients with advanced disease developing LMD. Tumour cells that metastasise to the brain have unique properties that allow them to cross the blood–brain barrier, evade the immune system, and survive in the brain microenvironment. Metastatic colonisation is achieved through dynamic communication between metastatic cells and the tumour microenvironment, resulting in a tumour-permissive milieu. Despite advances in treatment options, the incidence of LMD appears to be increasing and current treatment modalities have a limited impact on survival. This review provides an overview of the biology of LMD, diagnosis and current treatment approaches for MM patients with LMD, and an overview of ongoing clinical trials. Despite the still limited efficacy of current therapies, there is hope that emerging treatments will improve the outcomes for patients with LMD.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2018
    In:  Der Onkologe Vol. 24, No. 6 ( 2018-6), p. 478-483
    In: Der Onkologe, Springer Science and Business Media LLC, Vol. 24, No. 6 ( 2018-6), p. 478-483
    Type of Medium: Online Resource
    ISSN: 0947-8965 , 1433-0415
    Language: German
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
    detail.hit.zdb_id: 3120761-3
    detail.hit.zdb_id: 1462966-5
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  • 8
    In: Journal of the European Academy of Dermatology and Venereology, Wiley, Vol. 37, No. 10 ( 2023-10)
    Type of Medium: Online Resource
    ISSN: 0926-9959 , 1468-3083
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2022088-1
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