Record Voxel Rate Nonlinear Optical Microscope to Unravel Brain Connectome and Signaling

NCT ID: NCT05943262

Last Updated: 2024-08-21

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-05-01

Study Completion Date

2026-12-31

Brief Summary

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The research aims to develop a novel pathological technology, including rapid whole-mount tissue H\&E \& IHC staining protocol and high-resolution nonlinear optical microscopy imaging system, to intraoperatively assess brain tumor grade, types and other biological parameters.

Detailed Description

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Brain tumors, especially like glioma, the infiltrative growth pattern resulted in an indistinct margin against normal brain tissues. Surgery is currently the most effective method in prolonging patient's survival, the extent of tumor resection is therefore crucial to the overall outcome. Distinguishing the tumor type and grading can help neurosurgeons plan the intraoperative surgical strategies to cure the suffered patients. Feasible solutions to improve the extent of resections including fluorescence-guided surgery and intraoperative MR imaging are relatively indirect to judge the completeness of tumor resection and its margin; considering means like Moh's surgery performed in the dermatological practice, though it is reasonable to look at the resection proportion by pathological interpretation, it is very time consuming. Besides, many kinds of brain tumors can't be classified only by the outcomes of frozen pathology. There are several related studies trying to solve the problem, but the judgment criteria is not sufficient to meet the standard of modern pathological diagnosis. The research aims to acquire images by optical microscopy from both H\&E and IHC stained tissues, and to compare those images with slides obtained by standard pathological workflow in order to achieve accurate and rapid assessment of tumor categories and grading.

Conditions

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Brain Tumor Brain Cancer

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Study Groups

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mesoscale nonlinear optical microscope + whole-mount H&E & IHC staining protocol

mesoscale nonlinear optical microscope

Intervention Type DEVICE

The mesoscale nonlinear optical microscope based on the principles of nonlinear optics and computed-algorithms can acquire large-area image within few minutes.

Interventions

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mesoscale nonlinear optical microscope

The mesoscale nonlinear optical microscope based on the principles of nonlinear optics and computed-algorithms can acquire large-area image within few minutes.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

1\. Patients older than the age of 20 with diagnosis of brain tumor (both newly-diagnosed or recurrent) who are suitable and willing to receive resection surgery.

Exclusion Criteria

1. Patients who cannot give consent to participate in the study.
2. The tumor samples failed to give a conclusive pathological diagnosis by standard pathological workflow.
3. Patients who only receives biopsy surgery rather than resection surgery.
4. Significant post-irradiation effect or radiation necrosis reported in the pathological examination.
Minimum Eligible Age

20 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Taiwan University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Department of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University

Taipei, , Taiwan

Site Status RECRUITING

Countries

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Taiwan

Central Contacts

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Kuo-Chuan Wang

Role: CONTACT

+886-23123456 ext. 263155

Yao-Chen Tseng

Role: CONTACT

+886-33661552

Facility Contacts

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Kuo-Chuan Wang

Role: primary

+886-23123456 ext. 263155

Other Identifiers

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202302070RIND

Identifier Type: -

Identifier Source: org_study_id

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