Contribution of 18FDG PET-Scan in Tumour Volume Determination in Patients Operated of Breast Cancer (VOSETEP)
Use of positron emission tomography (PET) in determination of functional tumour volume can provide usable information for radiotherapy to define the irradiated volume.
To determine the best tumour volume measure method, the investigators have chosen as model the breast cancer which allows us to study a stationary or moving organ by the patient position and belonging to a primary surgery.
The used methodology is based on lesion volume measure in preoperative time, obtained with PET, and on the measure of specimen volume by the anatomic laboratory after surgery.
This study's main objective is to compare this two measure of tumour size and secondarily to compare TEP with or without respiratory gating.
The PET-scan is achieved with FDG, under his French permission marketing, and acquire in 3 times:
A whole body acquisition in supine position, follow by a centered tumour acquisition with respiratory gating, then an acquisition in prone position to immobilise the lesion.
This study is monocentric and descriptive. It provides to include 30 patients in 1 year.
Infiltrating Ductal Carcinoma
|Study Design:||Observational Model: Cohort
Time Perspective: Prospective
|Official Title:||Contribution of 18FDG PET-Scan in Tumour Volume Determination in Patients Operated of Breast Cancer|
|Study Start Date:||February 2010|
|Study Completion Date:||May 2012|
|Primary Completion Date:||May 2012 (Final data collection date for primary outcome measure)|
The use of positron emission tomography (PET) in determination of functional tumour volume may pose two major problems especially for the exact delineation of tumour contours:
- Respiratory movements, when the tumour is thoracic, may induce an overestimation
- The PET's low spatial resolution, linked to the emission of photons
The usual method to define tumour contours result of three types of delineation usually used: the visual contouring, the segmentation based on an activity threshold fixed, and the segmentation with adaptive thresholding.