Development
of a multimodal diagnostic algorithm including PET-MRI-RX for early
diagnosis and monitoring of breast cancer.
Abstract:
Breast
cancer is one of the most common forms of cancer among women in the
"western world". The X-ray mammography is the primary way to check and
diagnose breast cancer as this procedure is very sensitive, though it
is not very specific. When a suspicious abnormality is detected,
biopsies are necessary and / or additional imaging scans using. Breast
biopsy is a highly specific and sensitive method, but is invasive and
sometimes painful, leaving scar tissue that may confuse future breast
exploration. Moreover, about half of the times, the biopsy is negative.
It would therefore be desirable to have an alternative: a noninvasive
method to track ambiguous or difficult to interpret mammograms, or
breast exam inconclusive.
In this project, we start from the previous experience of the
participants to move towards obtaining a multimodal image registration
(based on biomechanical modeling of tissues specific to the
patient) of mammography scans using MRI, PET and X-rays in order to
increase the specificity and sensitivity of these non-invasive
diagnostic methods, thereby reducing the number of unnecessary
biopsies. All impacting in less damage to the patient and increased
diagnostic accuracy without increasing investment in new diagnostic
devices.
Date:
Feb.
2015-Dec. 2017
PI UJI:
María José Rupérez
Moreno
Antonio Pérez
Gonzalez
Partners:
Eresa, Alma
Medical Imaging, UPV, UJI
Funding:
Ministerio de
Economía y Competitividad
(RTC-2015-3287-1)