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Algorithms for optoacoustically controlled selective retina therapy (SRT)

  • Eric Seifert*
  • , Jan Tode
  • , Amelie Pielen
  • , Dirk Theisen-Kunde
  • , Carsten Framme
  • , Johann Roider
  • , Yoko Miura
  • , Reginald Birngruber
  • , Ralf Brinkmann
  • *Korrespondierende/r Autor/-in für diese Arbeit
  • Medizinische Hochschule Hannover
  • Christian-Albrechts Universität zu Kiel

Abstract

Objectives: Selective Retina Therapy (SRT) uses microbubble formation (MBF) to target retinal pigment epithelium (RPE) cells selectively while sparing the neural retina and the choroid. Intra- and inter-individual variations of RPE pigmentation makes frequent radiant exposure adaption necessary. Since selective RPE cell disintegration is ophthalmoscopically non-visible, MBF detection techniques are useful to control adequate radiant exposures. It was the purpose of this study to evaluate optoacoustically based MBF detection algorithms. Methods: Fifteen patients suffering from central serous chorioretinopathy and diabetic macula edema were treated with a SRT laser using a wavelength of 527 nm, a pulse duration of 1.7 µs and a pulse energy ramp (15 pulses, 100 Hz repetition rate). An ultrasonic transducer for MBF detection was embedded in a contact lens. RPE damage was verified with fluorescence angiography. Results: An algorithm to detect MBF as an indicator for RPE cell damage was evaluated. Overall, 4646 irradiations were used for algorithm optimization and testing. The tested algorithms were superior to a baseline model. A sensitivity/specificity pair of 0.96/1 was achieved. The few false algorithmic decisions were caused by unevaluable signals. Conclusions: The algorithm can be used for guidance or automatization of microbubble related treatments like SRT or selective laser trabeculoplasty (SLT).

OriginalspracheEnglisch
Aufsatznummer100316
ZeitschriftPhotoacoustics
Jahrgang25
ISSN2213-5979
DOIs
PublikationsstatusVeröffentlicht - 10.11.2021

Fördermittel

We thank Lutronic Inc. (Republic of Korea) for resourcing the RGEN Laser Systems. The algorithm implemented in the R:GEN system was not used clinically, nor considered, nor evaluated in this work.

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Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen
  2. SDG 9 – Industrie, Innovation und Infrastruktur
    SDG 9 – Industrie, Innovation und Infrastruktur

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