Disclosures

Did you receive any funding to support your research for this TOPIC?
No

Were you provided with any honoraria, payment or other compensation for your work on this study?
No

Do you have any financial relationship with any entity which may closely compete with the medications, materials or instruments covered by your study?
No

Do you own or have you applied for any patents in conjunction with the instruments, medications or materials discussed in your study?
No

This work was not supported by any direct or non direct funding. It is under the author's own responsability

Disclosures

Did you receive any funding to support your research for this TOPIC?
No

Were you provided with any honoraria, payment or other compensation for your work on this study?
No

Do you have any financial relationship with any entity which may closely compete with the medications, materials or instruments covered by your study?
No

Do you own or have you applied for any patents in conjunction with the instruments, medications or materials discussed in your study?
No

This work was not supported by any direct or non direct funding. It is under the author's own responsability

Disclosures

Did you receive any funding to support your research for this TOPIC?
No

Were you provided with any honoraria, payment or other compensation for your work on this study?
No

Do you have any financial relationship with any entity which may closely compete with the medications, materials or instruments covered by your study?
No

Do you own or have you applied for any patents in conjunction with the instruments, medications or materials discussed in your study?
No

This work was not supported by any direct or non direct funding. It is under the author's own responsability

Objectives: To investigate the diagnostic accuracy and safety of a real-time noninvasive in vivo skin cancer diagnostics utilizing non-discrete molecular LIPS combined with a deep neural network (DNN)-based diagnostic algorithm.

Introduction: Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of skin lesions using an ultrashort pulsed laser.

Materials / method: In vivo LIPS spectra were acquired from 296 skin cancers (186 BCCs, 96 SCCs and 14 melanomas) and 316 benign lesions in a multisite clinical study. The diagnostic performance was validated using 10-fold cross-validations.

Results: The sensitivity and specificity for differentiating skin cancers from benign lesions using LIPS and the DNN-based algorithm were 94.3% (95% CI: 91.6 – 96.9%) and 88.6% (95% CI: 85.1 – 92.1%), respectively. No adverse events, including macroscopic or microscopic visible marks or pigmentation due to laser irradiation, were observed.

Conclusion: This LIPS system with a DNN-based diagnostic algorithm is a promising tool to distinguish skin cancers from benign lesions with high diagnostic accuracy in real clinical settings.

Disclosures

Did you receive any funding to support your research for this TOPIC?
No

Were you provided with any honoraria, payment or other compensation for your work on this study?
No

Do you have any financial relationship with any entity which may closely compete with the medications, materials or instruments covered by your study?
No

Do you own or have you applied for any patents in conjunction with the instruments, medications or materials discussed in your study?
No

This work was not supported by any direct or non direct funding. It is under the author's own responsability

Disclosures

Did you receive any funding to support your research for this TOPIC?
No

Were you provided with any honoraria, payment or other compensation for your work on this study?
Yes
Please specify entities (individual, company, society): CANFIELD

Do you have any financial relationship with any entity which may closely compete with the medications, materials or instruments covered by your study?
Yes
Please specify entities (individual, company, society): CANFIELD

Do you own or have you applied for any patents in conjunction with the instruments, medications or materials discussed in your study?
No

This work is presented thanks to the support of: CANFIELD

Disclosures

Did you receive any funding to support your research for this TOPIC?
No

Were you provided with any honoraria, payment or other compensation for your work on this study?
No

Do you have any financial relationship with any entity which may closely compete with the medications, materials or instruments covered by your study?
No

Do you own or have you applied for any patents in conjunction with the instruments, medications or materials discussed in your study?
No

This work was not supported by any direct or non direct funding. It is under the author's own responsability