Automated Detection and Diagnosis of Pathological DRGs in PHN Patients Using Deep Learning and Magnetic Resonance

NCT06274502 | Completed

• 1 other identifier: deep learning
• Study Type: observational
• Target: 41
• Locations: 1 country
• Sites: 2

Brief Summary

Here, this study aimed to develop an automated system for detecting and diagnosing lesion DRGs in PHN patients based on deep learning. This study retrospectively analyzed the DRG images of all patients with postherpetic neuralgia who underwent magnetic resonance neuroimaging examinations in our radiology department from January 2021 to February 2022. After image post-processing, the You Only Look Once (YOLO) version 8 was selected as the target algorithm model. Model performance was evaluated using metrics such as precision, recall, Average Precision, mean average precision and F1 score.

Conditions

Deep Learning

Keywords

deep learning; Magnetic resonance neurography; dorsal root ganglion; postherpetic neuralgia; YOLOv8

Outcome Measures

Primary Outcomes (1)

• Develop an automated system for detecting and diagnosing lesion DRGs in PHN patients based on deep learning

  the You Only Look Once (YOLO) version 8 was selected as the target algorithm model

  202310-202402

Interventions

YOLOv8 OTHER

After image post-processing, the You Only Look Once (YOLO) version 8 was selected as the target algorithm model.

Eligibility Criteria

• Age: 18 Years - 85 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with postherpetic neuralgia due who underwent magnetic resonance neuroimaging examinations in the Radiology Department at our hospital from January 2021 to February 2022.

You may qualify if:

• Patients aged 18 years or older;
• Patients with herpes zoster who continue to experience pain for over one month after the crust forms over the skin lesions;
• Clear MRI images showing evident dorsal root ganglia (DRG) lesions.

You may not qualify if:

• Patients with severe systemic, metabolic, or neurological diseases that can lead to polyneuropathy, such as multiple myeloma, diabetes, or thyroid diseases;
• Patients with a history of psychiatric disorders, other chronic pain conditions, or substance abuse;
• Patients with a history of thoracic or back surgeries and a history of pain;
• Presence of artifacts in the imaging or unclear image display;
• Target images obscured by other tissues.

Sponsors & Collaborators

• Huazhong University of Science and Technology: lead

Study Sites (2)

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, Hubei, 430030, China

Location

Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology

Wuhan, China

Location

MeSH Terms

Conditions

Neuralgia, Postherpetic

Condition Hierarchy (Ancestors)

Neuralgia; Peripheral Nervous System Diseases; Neuromuscular Diseases; Nervous System Diseases; Pain; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical Professor

Study Record Dates

• First Submitted: February 16, 2024
• First Posted: February 23, 2024
• Study Start: October 1, 2023
• Primary Completion: January 31, 2024
• Study Completion: January 31, 2024
• Last Updated: March 6, 2024

Record last verified: 2024-03

Locations

CN (2)