Fiber-based SORS-SERDS System and Chemometrics for the Diagnostics and Therapy Monitoring of Psoriasis Inflammatory Disease in vivo

in: Biomedical Optics Express (2021)
Bocklitz, Thomas W.; Schleusener, Johannes; Guo, Shuxia; Darvin, Maxim E.; Thiede, Gisela; Chernavskaia, Olga; Knorr, Florian; Lademann, Jürgen; Popp, Jürgen
Psoriasisisconsideredawidespreaddermatologicaldiseasethatcanstronglyaffect thequalityoflife. Currently,thetreatmentiscontinueduntiltheskinsurfaceappearsclinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminatethetreatmenttooearlycanhighlyincreasetheriskofrelapses. Therefore,techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modificationsindeeperlayers. Inthisstudy,wedevelopedafiber-basedSORS-SERDSsystem in combination with machine learning algorithms to non-invasively determine the treatment efficiencyofpsoriasis. ThesystemwasdesignedtoacquireRamanspectrafromthreedifferent depthsintotheskin,whichproviderichinformationabouttheskinmodificationsindeeperlayers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. Themethodwasverifiedwithastudyof24patientsupontheirtwovisits: thedataisacquired atthebeginningofastandardtreatment(visit1)andfourmonthsafterwards(visit2). Amean sensitivityof≥85%wasachievedtodistinguishpsoriasisfromnormalskinatvisit1. Atvisit2, wherethepatientswerehealedaccordingtotheclinicalappearance,themeansensitivitywas ≈65%.

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