Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery
Multimodal spectral histopathology (MSH), an optical technique combining tissue auto-fluorescence (AF) imaging and Raman micro-spectroscopy (RMS), was previously proposed for detection of residual basal cell carcinoma (BCC) at the surface of surgically-resected skin tissue. Here we report the develo...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
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Optical Society of America
2017
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| Online Access: | https://eprints.nottingham.ac.uk/48117/ |
| _version_ | 1848797695630639104 |
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| author | Boitor, Radu Kong, Kenny Shipp, Dustin Varma, Sandeep Koloydenko, Alexey Kusum, Kulkarni Elsheikh, Somaia Bakker Schut, Tom Caspers, Peter Puppels, Gerwin Wolf, Martin van der Sokolova, Elena Nijsten, T.E.C. Salence, Brogan Williams, Hywel C. Ioan, Notingher |
| author_facet | Boitor, Radu Kong, Kenny Shipp, Dustin Varma, Sandeep Koloydenko, Alexey Kusum, Kulkarni Elsheikh, Somaia Bakker Schut, Tom Caspers, Peter Puppels, Gerwin Wolf, Martin van der Sokolova, Elena Nijsten, T.E.C. Salence, Brogan Williams, Hywel C. Ioan, Notingher |
| author_sort | Boitor, Radu |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Multimodal spectral histopathology (MSH), an optical technique combining tissue auto-fluorescence (AF) imaging and Raman micro-spectroscopy (RMS), was previously proposed for detection of residual basal cell carcinoma (BCC) at the surface of surgically-resected skin tissue. Here we report the development of a fully-automated prototype instrument based on MSH designed to be used in the clinic and operated by a non-specialist spectroscopy user. The algorithms for the AF image processing and Raman spectroscopy classification had been first optimised on a manually-operated laboratory instrument and then validated on the automated prototype using skin samples from independent patients. We present results on a range of skin samples excised during Mohs micrographic surgery, and demonstrate consistent diagnosis obtained in repeat test measurement, in agreement with the reference histopathology diagnosis. We also show that the prototype instrument can be operated by clinical users (a skin surgeon and a core medical trainee, after only 1-8 hours of training) to obtain consistent results in agreement with histopathology. The development of the new automated prototype and demonstration of inter-instrument transferability of the diagnosis models are important steps on the clinical translation path: it allows the testing of the MSH technology in a relevant clinical environment in order to evaluate its performance on a sufficiently large number of patients. |
| first_indexed | 2025-11-14T20:07:58Z |
| format | Article |
| id | nottingham-48117 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:07:58Z |
| publishDate | 2017 |
| publisher | Optical Society of America |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-481172020-05-04T19:19:03Z https://eprints.nottingham.ac.uk/48117/ Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery Boitor, Radu Kong, Kenny Shipp, Dustin Varma, Sandeep Koloydenko, Alexey Kusum, Kulkarni Elsheikh, Somaia Bakker Schut, Tom Caspers, Peter Puppels, Gerwin Wolf, Martin van der Sokolova, Elena Nijsten, T.E.C. Salence, Brogan Williams, Hywel C. Ioan, Notingher Multimodal spectral histopathology (MSH), an optical technique combining tissue auto-fluorescence (AF) imaging and Raman micro-spectroscopy (RMS), was previously proposed for detection of residual basal cell carcinoma (BCC) at the surface of surgically-resected skin tissue. Here we report the development of a fully-automated prototype instrument based on MSH designed to be used in the clinic and operated by a non-specialist spectroscopy user. The algorithms for the AF image processing and Raman spectroscopy classification had been first optimised on a manually-operated laboratory instrument and then validated on the automated prototype using skin samples from independent patients. We present results on a range of skin samples excised during Mohs micrographic surgery, and demonstrate consistent diagnosis obtained in repeat test measurement, in agreement with the reference histopathology diagnosis. We also show that the prototype instrument can be operated by clinical users (a skin surgeon and a core medical trainee, after only 1-8 hours of training) to obtain consistent results in agreement with histopathology. The development of the new automated prototype and demonstration of inter-instrument transferability of the diagnosis models are important steps on the clinical translation path: it allows the testing of the MSH technology in a relevant clinical environment in order to evaluate its performance on a sufficiently large number of patients. Optical Society of America 2017-11-22 Article PeerReviewed Boitor, Radu, Kong, Kenny, Shipp, Dustin, Varma, Sandeep, Koloydenko, Alexey, Kusum, Kulkarni, Elsheikh, Somaia, Bakker Schut, Tom, Caspers, Peter, Puppels, Gerwin, Wolf, Martin van der, Sokolova, Elena, Nijsten, T.E.C., Salence, Brogan, Williams, Hywel C. and Ioan, Notingher (2017) Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery. Biomedical Optics Express, 8 (12). pp. 5749-5766. ISSN 2156-7085 https://www.osapublishing.org/boe/abstract.cfm?uri=boe-8-12-5749 doi:10.1364/BOE.8.005749 doi:10.1364/BOE.8.005749 |
| spellingShingle | Boitor, Radu Kong, Kenny Shipp, Dustin Varma, Sandeep Koloydenko, Alexey Kusum, Kulkarni Elsheikh, Somaia Bakker Schut, Tom Caspers, Peter Puppels, Gerwin Wolf, Martin van der Sokolova, Elena Nijsten, T.E.C. Salence, Brogan Williams, Hywel C. Ioan, Notingher Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| title | Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| title_full | Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| title_fullStr | Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| title_full_unstemmed | Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| title_short | Automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| title_sort | automated multimodal spectral histopathology for quantitative diagnosis of residual tumour during basal cell carcinoma surgery |
| url | https://eprints.nottingham.ac.uk/48117/ https://eprints.nottingham.ac.uk/48117/ https://eprints.nottingham.ac.uk/48117/ |