Phone App for cancer study

The manual method is time-consuming and technician-dependent

November 04, 2017 05:17 pm | Updated 05:18 pm IST

 “Health workers can be trained to use the App thus enabling faster results,” says Chandan Chakraborty (right).

“Health workers can be trained to use the App thus enabling faster results,” says Chandan Chakraborty (right).

A new smartphone App, SmartIHC-Analyser, developed by researchers at the Indian Institute of Technology (IIT) Kharagpur can now help in faster and more accurate evaluation of cancer after treatment. The App analyses the expression of a protein marker (Ki-67) for determining an increase in cancer cells. The App, now available for Android phones, analyses microscopic images of stained cancer tissue and in less than a minute tells if there is progression or regression of cancer cells post treatment.

The smart phone is fitted to the eye-piece of the microscope using a specially designed 3D-printed holder to take microscopic images of the cancer cells. To analyse proliferation, the colour variations in the stained cancer cells are studied. Cells positive for the protein marker will appear brown whereas the negative ones will appear blue.

In the manual method, pathologists observe these colours using the naked eye and count the cells. This method is time-consuming and technician-dependent. The new App takes pictures and counts the differently stained cells and gives the proliferation index in less than a minute.

“The proliferation index tells us the rate at which the cells are dividing or how fast the tumour is growing during the progress of cancer and helps in deciding future therapy. In manual counting, pathologists observe only two to four different areas of the tissue and give a mean score. The new automated quantification is repeatable and we can take many pictures in different areas of the tissue slide for a robust mean value,” explains Suman Tewary from the School of Medical Science & Technology at IIT Kharagpur and the first author of the paper published in the journal Analytical Methods.

Comparative analysis

The researchers analysed 30 cases of Ki-67-stained breast cancer tissues collected from Tata Medical Center, Kolkata (which collaborated in the study) and compared the results from the App with manual counting. Compared with manual method, the App had nearly 97% accuracy.

The researchers also compared it with a benchmark web-based application ImmunoRatio. The average difference between manual scoring and new App was only 6%, whereas it was 15% for ImmunoRatio.

“The application of immunohistochemical (study of specific proteins in cells) analysis helps in identifying the degree of severity and in understanding the effects of the given treatment. Health workers at public health centres can be trained to use the App thus enabling faster results,” says Prof. Chandan Chakraborty of School of Medical Science & Technology at IIT Kharagpur and corresponding author of the paper.

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