- Global Pharma News & Resources

OptraSCAN Announces CytoSiA – A Complete Digital Solution For Scanning And Analysis Of Cytology Slides At Affordable Pricing

OptraSCAN®, the leading On-Demand Digital Pathology solution provider, today announced its intelligent solution CytoSiA for rapid yet affordable scanning and analyzing of liquid-based cytology slides and pap-smears. It is a complete solution consisting of a digital pathology scanner, storage, and powerful artificial intelligence (AI) algorithms to assist pathologists and cytotechnologists in screening and detection of cervical cancer, pre-cancerous lesions, atypical cells, and all other cytologic categories. Multiple hospitals and pathology laboratories globally have already installed CytoSiA and are witnessing improved patient outcomes, increased efficiency, and productivity needed to cope with the ever-increasing demand of cytology cases. 

“We are redefining cervical cancer screening by introducing CytoSiA, it offers a plethora of features, to effectively screen liquid-based cytology slides, and pap smears to differentiate between normal and abnormal cervical cells using Bethesda classifications on normal to squamous cell carcinoma (NILM/LSIL/HSIL/SCC)”, said Abhi Gholap, Founder of OptraSCAN. With a range of scanning devices handling as low as 50 slides a week to 5000 slides a week at an extremely affordable price,” he further added.

Our scanners can scan cytology slides of size 15x15 mm area at 40x magnification in less than 60 seconds while generating the highest quality image. CytoSia incorporates patented technology- composite imaging which finds all pixels in focus from various Z plane images and stitches back to create a single layer composite image. This composite imaging technology is considerably efficient as compared to traditional Z-Stacking Technology. It allows for rapid and precise screening of the entire slide within seconds. This level of precision and quality is imperative for analyzing the samples. Furthermore, it presents to the screener images of fields that would be essential in providing a cytological interpretation, place them into categories, and filter out the redundancies.

CytoSiA when used as a companion diagnostic tool it notifies pathologists when inconsistencies between their interpretation and the AI algorithm's findings are observed, offering a safeguard against error or misinterpretation, while also improving overall care quality.

Features of CytoSiA:

  • Automated computation of sample adequacy for the whole slide cytology image
  • Identification of abnormal cells and other entities based on morphological features and AI-based classification using Bethesda scoring
  • Identification of reactive, endometrial, actinomyces, candida, clue cells, trichomonas vaginalis, and herpes entities
  • Identification of entities including blood, inflammation, and lubricant

 “AI-based image analysis requires images that are of superior quality,” said Dr. Aparna Joshi, Medical Director. “Our team has developed an intelligent imaging technology that transforms physical glass cytology slides into digital images with exceptional clarity. Advanced image analysis and standardization are now achievable with this quality of digitization”, she further added.

About Us: 

We are pioneers in the On-Demand Digital Pathology® System, focused on delivering fully integrated, affordable solutions that will maximize your return on investment and improve the performance of your pathology services. An ISO 13485 certified company and CE-marked whole slide scanners for IVD use, We are working to eliminate the barriers to “Go Digital” no matter the size of the pathology lab, the lab’s throughput, or global location.

Our end-to-end digital pathology solution provides effective acquisition of whole slide images, viewing, storing, real-time sharing, reporting, and AI & ML based Image analysis solutions via On-Demand or outright purchase models. Follow Us on LinkedIn and Twitter.

Media Inquiries Contact:

Anjana Athanikar | Manager – Marketing Communications | 91.20.66540900 x 231 |

Editor Details

Last Updated: 16-Jul-2021