Basal Cell Carcinoma
Conditions
Brief summary
The aim is to use AI to assist surgeons in analyzing CLSM tissue slide images obtained during BCC surgeries with the aim to integrate it in real time. We plan to use AI to analyze CLSM images of BCCs and distinguish between tumor tissue, inflammatory tissue, and non-tumor/non-inflammatory tissue. This approach would provide surgeons with real-time feedback and automated image analysis, leading to a more targeted and efficient approach to tissue analysis. By improving the accuracy and speed of tissue analysis, our proposal could ultimately improve operative patient outcomes and benefit healthcare professionals.
Interventions
PROCEDUREEx vivo confocal microscopy
The aim is to use AI to assist surgeons in analyzing CLSM tissue slide images obtained during BCC surgeries with the aim to integrate it in real time. We plan to use AI to analyze CLSM images of BCCs and distinguish between tumor tissue, inflammatory tissue, and non-tumor/non-inflammatory tissue. This approach would provide surgeons with real-time feedback and automated image analysis, leading to a more targeted and efficient approach to tissue analysis. By improving the accuracy and speed of tissue analysis, our proposal could ultimately improve operative patient outcomes and benefit healthcare professionals.
Sponsors
LMU Klinikum
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Patients with Basal Cell Carcinoma
Exclusion criteria
* Patient unable to consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Ex vivo confocal laser scanning microscopy | 2 years | Reaching the planned number of 1000 patients |
Countries
Germany
Contacts
CONTACTMaximilian Deußing, Dr.
Outcome results
None listed