Ignite Creation Date:
2024-05-06 @ 8:26 PM
Last Modification Date:
2024-10-26 @ 3:27 PM
Study NCT ID:
NCT06384924
Status:
NOT_YET_RECRUITING
Last Update Posted:
2024-05-06
First Post:
2024-04-22
Brief Title:
Raman Spectroscopy and Skin Cancer
Sponsor:
Renee Cattell
Organization:
Stony Brook University
Study Overview
Official Title:
Pilot Study of Raman Spectroscopic Imaging for Skin Cancer
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The goal of this observational study is to find out if Raman Spectroscopy a type of imaging can be used to determine the size of skin cancer tumors The main question it aims to answer is
-Can Raman Spectroscopy help figure out how far a tumor spreads
This study will take measurements using laser light from an experimental handheld probe by lightly touching the skin
-Can Raman Spectroscopy help figure out how far a tumor spreads
This study will take measurements using laser light from an experimental handheld probe by lightly touching the skin
Detailed Description:
Radiation therapy is an alternative to surgery for localized tumors with excellent tumor control and cosmetic outcome Raman Spectroscopy has potential to be a useful non-invasive non-destructive real-time in-vivo tool for differentiation of cancerous vs non-cancerous tissues With this knowledge and future studies this will ultimately guide skin brachytherapy more accurately and avoid unnecessary radiation to cosmetically and functionally important tissues including eyelid nose lips or skin folds
The purpose of this study is to determine the feasibility of Raman Spectroscopy to identify microscopic infiltration extent of skin cancer beyond grossly visible tumor using artificial intelligence methods of supervised and un-supervised machine learning algorithms including pattern recognition convolutional neural networks k-means clustering and principal component analysis
The purpose of this study is to determine the feasibility of Raman Spectroscopy to identify microscopic infiltration extent of skin cancer beyond grossly visible tumor using artificial intelligence methods of supervised and un-supervised machine learning algorithms including pattern recognition convolutional neural networks k-means clustering and principal component analysis
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
True
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
None