What is this study trying to find out about blood volume analysis?

This study aims to develop a new deep learning model to estimate blood volume before surgery using ultrasound videos. Researchers want to find a non-invasive and accurate way to assess blood volume to help prevent surgery complications. The study is led by Shanghai 6th People's Hospital and focuses on improving preoperative care.

Who may be eligible for this blood volume analysis clinical trial?

Adults between 18 and 75 years old scheduled for surgery may be eligible. Participants must have a body mass index between 18 and 30 and be in good general health based on anesthesia risk scores. People with certain health problems or very low hemoglobin levels may not qualify. Please review eligibility criteria for more details.

Is there any cost to participate in this blood volume analysis clinical trial?

Study-related care, including the ultrasound scans and all trial visits, is provided at no cost. However, personal travel and other expenses may vary and are not guaranteed to be covered. Participants should plan accordingly for any costs related to attending study visits.

Actively Recruiting

Age: 18Years - 75Years

All Genders

ID06957587

Using Multi-modal Ultrasound and Deep Learning to Estimate Blood Volume Before Surgery in Adults Aged 18 to 75

Led by Shanghai 6th People's Hospital · Updated on 2025-11-17

800

Participants Needed

Research Sites

4 weeks

Total Duration

AI-Summary

What this Trial Is About

Researchers are evaluating a new deep learning model that uses ultrasound video data to estimate blood volume before surgery. This prospective, single-center observational study focuses on adult patients scheduled for surgery, aiming to provide an accurate, non-invasive way to assess blood volume, which is important to prevent complications during surgery. The study is led by Shanghai 6th Peoples Hospital and addresses the current lack of practical methods for direct blood volume measurement. Participants will undergo preoperative ultrasound scans capturing videos of four major blood vessels the Internal Jugular Vein, Subclavian Vein, Inferior Vena Cava, and Common Carotid Artery. The true blood volume is calculated using a clinical method involving hemoglobin concentration changes before and after acute normovolemic hemodilution. The collected ultrasound videos will be used to train and validate a deep learning model that combines convolutional and temporal analysis techniques to estimate blood volume from the ultrasound data. During the study, participants will have ultrasound video clips taken shortly before surgery. Researchers will analyze these images alongside blood volume values determined by the clinical method. The main outcome measured is the accuracy of the blood volume estimate within 30 minutes before surgery. The study does not involve treatment changes but focuses on data collection and model validation. Participation lasts through the preoperative period up to surgery, with no additional follow-up specified.

CONDITIONS

Brief Title

A Deep Learning Model for Blood Volume Estimation From Multi-modal Ultrasound

Who Can Participate

Age: 18Years - 75Years

All Genders

Eligibility Criteria

You may qualify if you...

Agree to join this study and sign the informed consent form
Age between 18 and 75 years old (inclusive)
Body mass index (BMI) between 18 and 30 kg/m2
American Society of Anesthesiologists (ASA) grades I-II

You will not qualify if you...

Preoperative hemoglobin less than 10 g/dl
Cardiac dysfunction classified as NYHA class III-IV
Respiratory dysfunction classified as ATS class 2-4
History of liver or kidney dysfunction including abnormal transaminase, albumin, bilirubin, hepatitis, elevated serum creatinine or urea nitrogen
Nervous system abnormalities preventing cooperation such as stroke, its sequelae, or Alzheimer's disease
Poor ultrasound image quality of the inferior vena cava, internal jugular vein, subclavian vein, or common carotid artery
Presence of venous thrombosis or anatomical abnormalities
Multiple injuries involving chest, abdomen, or brain
Pregnancy

Research Team

xiuxiu sun, MD

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