Automatic Segmentation of Polycystic Liver

Summary

Assessing the volume of the liver before surgery, predicting the volume of liver remaining after surgery, detecting primary or secondary lesions in the liver parenchyma are common applications that require optimal detection of liver contours, and therefore liver segmentation.

Several manual and laborious, semi-automatic and even automatic techniques exist.

However, severe pathology deforming the contours of the liver (multi-metastatic livers...), the hepatic environment of similar density to the liver or lesions, the CT examination technique are all variables that make it difficult to detect the contours. Current techniques, even automatic ones, are limited in this type of case (not rare) and most often require readjustments that make automatisation lose its value.

All these criteria of segmentation difficulties are gathered in the livers of hepatorenal polycystosis, which therefore constitute an adapted study model for the development of an automatic segmentation tool.

To obtain an automatic segmentation of any lesional liver, by exceeding the criteria of difficulty considered, investigators have developed a convolutional neural network (artificial intelligence - deep learning) useful for clinical practice.

Conditions

• Polycystic Liver Disease
• Polycystic Hepatorenal Disease
• Liver Injury

Interventions

OTHER

Anonymized CT examinations

The anonymized CT examinations will be reviewed in Lyon, in the imaging department of Edouard Herriot Hospital, by an expert radiologist and an intern from the Lyon hospitals.

OTHER

Training (1)

An initial training phase of the artificial intelligence network will be carried out : \- Segmentation of the livers of a first part of the CT examination, by an intern of the Lyon hospitals

OTHER

Training (2)

An initial training phase of the artificial intelligence network will be carried out : \- Use of computer data to drive the artificial intelligence network.

OTHER

Validation (1)

A validation phase of the artificial intelligence tool will be carried out with segmentation of the livers of the second part of the CT examinations : \- Carried out by an intern at the Lyon hospitals

OTHER

Validation (2)

A validation phase of the artificial intelligence tool will be carried out with segmentation of the livers of the second part of the CT examinations : \- Carried out by the neural network

Sponsors & Collaborators

• Hospices Civils de Lyon

  lead OTHER

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2019-04-01

Primary Completion

2019-07-31

Completion

2019-09-30

Countries

• France

Study Locations