DIGITAL HISTOLOGIC ANALYSIS SOFTWARE FOR HIRSCHSPRUNG’S DISEASE

| Written by Kevin Facun

INVENTORS:

Dr. Alvin Caballes; Prof. Prospero C. Naval, Jr.; Dr. Mark Angelo Ang; Mr. Martin Roy Nabus

 

DESCRIPTION

Hirschsprung Disease is a congenital disorder in the colon that is characterized by the absence of nerve ganglion cells in the diseased tissue. The diagnosis of this disease depends on the histologic evaluation of multiple biopsies to determine the absence of the ganglion cells, which can be tedious, time-consuming, and may be prone to misdiagnosis in low-volume settings.

The technology is that can detect, quantify, and annotate the presence of ganglion cells through deep learning. The absence of ganglion cells confirms the diagnosis.

 

VALUE PROPOSITION

  • Accurate assessment of histologic slides
  • High sensitivity and specificity for diagnosis
  • Uses deep learning algorithm

 

MARKET APPLICATIONS AND COMMERCIAL OPPORTUNITIES

In the Philippines, Hirschsprung’s Disease ranks 9th over the top 10 cases causing morbidity to Filipino children and the mortality rate can reach up to 50%.

The technology is applicable to healthcare institutions facilitating maternity services. This could help pathologists in accurately diagnosing the presence of ganglion cells in the histologic slides of the colon of infants.

 

DEVELOPMENT STATUS

Technology is undergoing further development.

 

IP STATUS

Patent Application Filed

Patent Application No. 1-2021-050409

 

TYPE OF PARTNERSHIP BEING SOUGHT

Licensing. Looking for technology adopters.