Delineating Margins of Lentigo Maligna Using a Hyperspectral Imaging System
Neittaanmäki-Perttu, N., Grönroos, M., Jeskanen, L., Pölönen, I., Ranki, A., Saksela, O., & Snellman, E. (2015). Delineating Margins of Lentigo Maligna Using a Hyperspectral Imaging System. Acta Dermato-Venereologica, 95(5), 549-552. https://doi.org/10.2340/00015555-2010
Published in
Acta Dermato-VenereologicaAuthors
Date
2015Copyright
© 2015 The Authors. Published by the Society for the Publication of Acta Dermato-Venereologica.
Lentigo maligna (LM) is an in situ form of melanoma
which can progress into invasive lentigo maligna melanoma
(LMM). Variations in the pigmentation and thus
visibility of the tumour make assessment of lesion borders
challenging. We tested hyperspectral imaging system
(HIS) in in vivo preoperative delineation of LM and
LMM margins. We compared lesion margins delineated
by HIS with those estimated clinically, and confirmed
histologically. A total of 14 LMs and 5 LMMs in 19 patients
were included. HIS analysis matched the histopathological
analysis in 18/19 (94.7%) cases while in 1/19
(5.3%) cases HIS showed lesion extension not confirmed
by histopathology (false positives). Compared to clinical
examination, HIS defined lesion borders more accurately
in 10/19 (52.6%) of cases (wider, n=7 or smaller,
n=3) while in 8/19 (42.1%) cases lesion borders were the
same as delineated clinically as confirmed histologically.
Thus, HIS is useful for the detection of subclinical LM/
LMM borders. Key words: lentigo maligna; lentigo maligna
melanoma; tumour margin assessment; hyperspectral
imaging.
...
Publisher
Society for the Publication of Acta Dermato - VenereologicaISSN Search the Publication Forum
0001-5555Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/24680529
Metadata
Show full item recordCollections
Related items
Showing items with similar title or keywords.
-
Hyperspectral imaging in detecting dermal invasion in lentigo maligna melanoma
Neittaanmäki, N.; Salmivuori, M.; Pölönen, Ilkka; Jeskanen, L.; Ranki, A.; Saksela, O.; Snellman, E.; Grönroos, M. (Blackwell Scientific Publications, 2017) -
Hyperspectral Imaging Reveals Spectral Differences and Can Distinguish Malignant Melanoma from Pigmented Basal Cell Carcinomas : A Pilot Study
Räsänen, Janne; Salmivuori, Mari; Pölönen, Ilkka; Grönroos, Mari; Neittaanmäki, Noora (Society for Publication of Acta Dermato-Venereologica, 2021)Pigmented basal cell carcinomas can be difficult to distinguish from melanocytic tumours. Hyperspectral imaging is a non-invasive imaging technique that measures the reflectance spectra of skin in vivo. The aim of this ... -
Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions
Paoli, John; Pölönen, Ilkka; Salmivuori, Mari; Räsänen, Janne; Zaar, Oscar; Polesie, Sam; Koskenmies, Sari; Pitkänen, Sari; Övermark, Meri; Isoherranen, Kirsi; Juteau, Susanna; Ranki, Annamari; Grönroos, Mari; Neittaanmäki, Noora (Medical Journals Sweden AB, 2022)Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral ... -
Agent‐based time delay margin in consensus of multi‐agent systems by an event‐triggered control method : Concept and computation
Hosseini, Seyed Hamid; Tavazoei, Mohammad Saleh; Kuznetsov, Nikolay V. (Wiley-Blackwell, 2023)This paper deals with defining the concept of agent-based time delay margin and computing its value in multi-agent systems controlled by event-triggered based controllers. The agent-based time delay margin specifying the ... -
Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity
Tuominen, Sakari; Näsi, Roope; Honkavaara, Eija; Balazs, Andras; Hakala, Teemu; Viljanen, Niko; Pölönen, Ilkka; Saari, Heikki; Ojanen, Harri (MDPI, 2018)Recognition of tree species and geospatial information on tree species composition is essential for forest management. In this study, tree species recognition was examined using hyperspectral imagery from visible to ...