Ignite Creation Date:
2024-05-06 @ 8:17 PM
Last Modification Date:
2024-10-26 @ 3:24 PM
Study NCT ID:
NCT06321003
Status:
RECRUITING
Last Update Posted:
2024-03-20
First Post:
2024-03-13
Brief Title:
SYsteMatical Trained learnIng aLgorithms for Oral carcInogenesiS Interpretation by Optical Coherence Tomography
Sponsor:
University of Palermo
Organization:
University of Palermo
Study Overview
Official Title:
Single-blind Clinical Trial Assessing the Validity of Optical Coherence Tomography OCT in Diagnosing Potentially Malignant Oral Lesions and Oral Cancer
Status:
RECRUITING
Status Verified Date:
2024-03
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:
SYMILIS OCT
Brief Summary:
This clinical trial aims to assess the efficacy of Optical Coherence Tomography OCT in the early diagnosis of oral cancer It focuses on Oral Potentially Malignant Disorders OPMDs as precursors to Oral Squamous Cell Carcinoma OSCC Despite the availability of oral screening diagnostic delays persist underscoring the importance of exploring non-invasive methodologies The OCT technology provides cross-sectional analysis of biological tissues enabling a detailed evaluation of ultrastructural oral mucosal features
The trial aims to compare OCT preliminary evaluation with traditional histology considered the gold standard in oral lesion diagnosing It seeks to create a database of pathological OCT data facilitating the non invasive identification of carcinogenic processes The goal is to develop a diagnostic algorithm based on OCT enhancing its ability to detect characteristic patterns such as the keratinized layer squamous epithelium basement membrane and lamina propria in oral tissues affected by OPMDs and OSCC
Furthermore the trial aims to implement Artificial Intelligence AI in OCT image analysis The use of machine learning algorithms could contribute to a faster and more accurate assessment of images aiding in early diagnosis The trial aims to standardize the comparison between in vivo OCT images and histological analysis adopting a site-specific approach in biopsies to improve correspondence between data collected by both methods
In summary the trial not only evaluates OCT as a diagnostic tool but also aims to integrate AI to develop a standardized approach that enhances the accuracy of oral cancer diagnosis providing a significant contribution to clinical practice
The trial aims to compare OCT preliminary evaluation with traditional histology considered the gold standard in oral lesion diagnosing It seeks to create a database of pathological OCT data facilitating the non invasive identification of carcinogenic processes The goal is to develop a diagnostic algorithm based on OCT enhancing its ability to detect characteristic patterns such as the keratinized layer squamous epithelium basement membrane and lamina propria in oral tissues affected by OPMDs and OSCC
Furthermore the trial aims to implement Artificial Intelligence AI in OCT image analysis The use of machine learning algorithms could contribute to a faster and more accurate assessment of images aiding in early diagnosis The trial aims to standardize the comparison between in vivo OCT images and histological analysis adopting a site-specific approach in biopsies to improve correspondence between data collected by both methods
In summary the trial not only evaluates OCT as a diagnostic tool but also aims to integrate AI to develop a standardized approach that enhances the accuracy of oral cancer diagnosis providing a significant contribution to clinical practice
Detailed Description:
Background and needs
Despite advancements in oral screening techniques diagnostic delays persist necessitating the exploration of non-invasive methodologies for early detection of oral cancer The current standard diagnostic method histological analysis often requires invasive biopsies and can be time-consuming leading to delays in treatment initiation Moreover traditional screening methods may not always detect early-stage oral lesions accurately Therefore there is a critical need to enhance diagnostic capabilities through the adoption of innovative technologies
In this context Optical Coherence Tomography OCT emerges as a promising technology warranting investigation OCT offers several advantages over conventional diagnostic approaches Its non-invasive nature allows for real-time and non-invasive imaging of tissue morphology with high resolution enabling clinicians to visualize structural changes in oral tissues By providing cross-sectional images of tissue layers OCT has the potential to identify subtle alterations indicative of early-stage oral lesions including potentially malignant disorders OPMDs and squamous cell carcinoma OSCC Additionally OCT can facilitate early detection by enabling repeated examinations over time thereby monitoring lesion progression or regression without the need for repeated biopsies
The exploration of OCT as a diagnostic tool aligns with the urgent need to improve the efficiency and accuracy of oral cancer diagnosis By leveraging the capabilities of OCT clinicians can potentially expedite the identification of suspicious lesions leading to timely intervention and improved patient outcomes Moreover the integration of OCT into routine clinical practice has the potential to reduce the burden associated with invasive procedures and diagnostic delays ultimately enhancing the quality of care for individuals at risk of oral cancer
However despite these potential benefits several challenges remain Currently there is a lack of precise definition of OCT patterns specific to various oral lesions This hinders the consistent interpretation of OCT images and limits its diagnostic utility Additionally the accurate alignment of OCT findings with histological analysis is essential for validation and clinical applicability Yet there is still a need for standardized protocols to ensure proper overlay of OCT images with corresponding histopathological features
Furthermore while computerized OCT analysis holds promise for enhancing diagnostic accuracy existing methodologies may be prone to biases These biases must be addressed to develop robust algorithms capable of reliably detecting early signs of oral cancer trained on standardized techniques of comparison between OCT and histology
Therefore addressing these challenges through the standardization of OCT imaging protocols the establishment of consistent OCT patterns and the development of unbiased computerized analysis methods is imperative Doing so will not only advance the clinical utility of OCT in oral cancer diagnosis but also improve patient outcomes by enabling earlier detection and intervention
Aims and approach
1 Standardization of technique for OCT scans and biopsy of oral lesions
Objective To standardize the biopsy acquisition technique for both OCT and histological analysis ensuring a reliable correlation between imaging modalities
Approach We will develop and implement a standardized biopsy acquisition protocol optimizing tissue preservation and alignment with OCT imaging parameters This may involve specialized instrumentation and procedural guidelines tailored to maximize diagnostic yield focusing on standardization of site and dimension of optical and surgical sampling Detailed protocols will be established for OCT imaging ensuring consistent acquisition parameters across all sites Similarly histological processing of biopsy specimens will adhere to standardized protocols to maintain integrity and facilitate accurate correlation with OCT findings A novel optical and histological procedure of Target biopsy will be performed and assessed
2 Standardization of OCT patterns of oral carcinogenesis
Objective To establish standardized patterns for OCT imaging of OPMDs and OSCCs enhancing diagnostic accuracy
Approach The evaluation of OCT images will entail meticulous analysis to identify consistent patterns reflective of various oral lesions By correlating these patterns with histological findings we aim to develop a comprehensive reference guide for interpreting OCT images with precision and consistency
3 Creation of Image Dataset for the Development of Diagnostic Software
Objective To collect a comprehensive repository of OCT images facilitating the development of digital diagnostic tools
Approach A robust dataset comprising OCT images and corresponding histological data will be meticulously curated This dataset will serve as the foundation for training and validating machine learning algorithms aimed at developing sophisticated diagnostic software capable of detecting early signs of oral cancer with high sensitivity and specificity
By pursuing these objectives we aim to not only evaluate the efficacy of OCT in early oral cancer diagnosis but also contribute to the standardization of diagnostic methodologies and pave the way for the integration of advanced technologies into clinical practice
Despite advancements in oral screening techniques diagnostic delays persist necessitating the exploration of non-invasive methodologies for early detection of oral cancer The current standard diagnostic method histological analysis often requires invasive biopsies and can be time-consuming leading to delays in treatment initiation Moreover traditional screening methods may not always detect early-stage oral lesions accurately Therefore there is a critical need to enhance diagnostic capabilities through the adoption of innovative technologies
In this context Optical Coherence Tomography OCT emerges as a promising technology warranting investigation OCT offers several advantages over conventional diagnostic approaches Its non-invasive nature allows for real-time and non-invasive imaging of tissue morphology with high resolution enabling clinicians to visualize structural changes in oral tissues By providing cross-sectional images of tissue layers OCT has the potential to identify subtle alterations indicative of early-stage oral lesions including potentially malignant disorders OPMDs and squamous cell carcinoma OSCC Additionally OCT can facilitate early detection by enabling repeated examinations over time thereby monitoring lesion progression or regression without the need for repeated biopsies
The exploration of OCT as a diagnostic tool aligns with the urgent need to improve the efficiency and accuracy of oral cancer diagnosis By leveraging the capabilities of OCT clinicians can potentially expedite the identification of suspicious lesions leading to timely intervention and improved patient outcomes Moreover the integration of OCT into routine clinical practice has the potential to reduce the burden associated with invasive procedures and diagnostic delays ultimately enhancing the quality of care for individuals at risk of oral cancer
However despite these potential benefits several challenges remain Currently there is a lack of precise definition of OCT patterns specific to various oral lesions This hinders the consistent interpretation of OCT images and limits its diagnostic utility Additionally the accurate alignment of OCT findings with histological analysis is essential for validation and clinical applicability Yet there is still a need for standardized protocols to ensure proper overlay of OCT images with corresponding histopathological features
Furthermore while computerized OCT analysis holds promise for enhancing diagnostic accuracy existing methodologies may be prone to biases These biases must be addressed to develop robust algorithms capable of reliably detecting early signs of oral cancer trained on standardized techniques of comparison between OCT and histology
Therefore addressing these challenges through the standardization of OCT imaging protocols the establishment of consistent OCT patterns and the development of unbiased computerized analysis methods is imperative Doing so will not only advance the clinical utility of OCT in oral cancer diagnosis but also improve patient outcomes by enabling earlier detection and intervention
Aims and approach
1 Standardization of technique for OCT scans and biopsy of oral lesions
Objective To standardize the biopsy acquisition technique for both OCT and histological analysis ensuring a reliable correlation between imaging modalities
Approach We will develop and implement a standardized biopsy acquisition protocol optimizing tissue preservation and alignment with OCT imaging parameters This may involve specialized instrumentation and procedural guidelines tailored to maximize diagnostic yield focusing on standardization of site and dimension of optical and surgical sampling Detailed protocols will be established for OCT imaging ensuring consistent acquisition parameters across all sites Similarly histological processing of biopsy specimens will adhere to standardized protocols to maintain integrity and facilitate accurate correlation with OCT findings A novel optical and histological procedure of Target biopsy will be performed and assessed
2 Standardization of OCT patterns of oral carcinogenesis
Objective To establish standardized patterns for OCT imaging of OPMDs and OSCCs enhancing diagnostic accuracy
Approach The evaluation of OCT images will entail meticulous analysis to identify consistent patterns reflective of various oral lesions By correlating these patterns with histological findings we aim to develop a comprehensive reference guide for interpreting OCT images with precision and consistency
3 Creation of Image Dataset for the Development of Diagnostic Software
Objective To collect a comprehensive repository of OCT images facilitating the development of digital diagnostic tools
Approach A robust dataset comprising OCT images and corresponding histological data will be meticulously curated This dataset will serve as the foundation for training and validating machine learning algorithms aimed at developing sophisticated diagnostic software capable of detecting early signs of oral cancer with high sensitivity and specificity
By pursuing these objectives we aim to not only evaluate the efficacy of OCT in early oral cancer diagnosis but also contribute to the standardization of diagnostic methodologies and pave the way for the integration of advanced technologies into clinical practice
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
None