Summary: Ibex Medical Analytics has introduced advancements to its AI-powered platform, enhancing breast cancer diagnostics, improving algorithm accuracy, and more.

Takeaways:

  1. Ibex’s platform now offers automated, AI-enhanced HER2 scoring for breast cancer diagnostics, improving accuracy and consistency in pathologist workflows.
  2. Enhanced algorithms, validated by expert pathologists, increase diagnostic reliability across prostate, breast, and gastric tissue types, identifying dozens of tissue morphologies.
  3. The platform’s interoperability is expanded with DICOM support, improving workflow integration for pathologists, and it now holds IVDR certification, underscoring regulatory compliance.

Ibex Medical Analytics (Ibex), a provider in artificial intelligence (AI)-powered cancer diagnostics, unveiled new advancements to its product platform. 

Improved Breast Cancer Diagnostics

Central to this release is an expanded focus on breast cancer, reflecting Ibex’s ongoing mission to bolster diagnostic confidence, the company says, The platform now includes fully automated “zero-click”, AI-enhanced HER2 immunohistochemistry (IHC) scoring, offering pathologists a powerful tool for improving accuracy and reproducibility.(1,2,3) Ibex Breast HER2 automatically identifies areas of invasive cancer, detects the tumor cells within them, classifies their staining patterns and delineates HER2 expression into four standard scores: 0, 1+, 2+ and 3+, based on the 2023 ASCO/CAP guidelines.(4) This enhancement automates and optimizes case review, including the highly subjective HER2-low cases, according to Ibex. Ibex Breast HER2 is part of Ibex Breast, an integrated AI solution offering a streamlined diagnostic workflow. Pathologists can review H&E and IHC stained slides with AI support, facilitating rapid, consistent and objective diagnosis, scoring and reporting of breast biopsies and excision.(5,6,7)

Enhanced Algorithms

Ibex’s accurate and robust algorithms have also been enhanced. By leveraging large and diverse datasets, incorporating insights from the company’s extensive international network of expert pathologists, and implementing features validated by live customers and clinical studies, the algorithms are increasingly reliable and versatile across all supported tissue types—prostate, breast and gastric—with broad capabilities identifying dozens of tissue morphologies.

DICOM Support Added

Recognizing the importance of seamless lab workflows, Ibex has enhanced the platform’s interoperability to include DICOM support and continues to partner with industry leaders on integrations that make it easier than ever for pathologists to incorporate the AI technology into daily practice. The latest product version boasts the Leica Image Quality certification, which recognizes inclusion of the International Color Consortium (ICC) profile and ensures the highest quality diagnostic images.

These new features were developed in collaboration with expert pathologists around the world who use the product in routine clinical practice

Additionally, Ibex’s newest platform ushers in enhanced capabilities for tissue and tumor length measurements and supports a wider range of tissue preparation techniques to meet the diverse needs of labs worldwide, the company says.

Further reading: Alverno Labs Launches Ibex AI Platform for Enhanced Cancer Diagnostics

Finally, Ibex recently announced that its product platform received In Vitro Diagnostic Medical Devices Regulation (IVDR) certification. Together with HiTrust qualification and existing International Organization for Standardization (ISO) certificates, these achievements highlight dedication to meeting the highest regulatory, security and privacy standards, which accompany the platform’s performance.

Photo: Ibex

*The Ibex platform includes solutions that are CE-IVD cleared and registered with the UK MHRA, TGA in Australia and ANVISA in Brazil. It is for Research Use Only (RUO) in the United States and pending FDA clearance. For additional details please approach Ibex.

References:

  1. Cyrta et al. ESMO Open (2024), 9; 54: 103071
  2. Globerson et al. Cancer Research (2023) 83:P6-04-05
  3. Krishnamurthy et al. Virchows Arch (2023) 483 (Suppl 1): S35
  4. Wolff AC, et al. Arch Pathol Lab Med. 2023 Sep 1;147(9):993-1000
  5. Sandbank et al. NPJ Breast Cancer (2022); 8:129
  6. Salomon et al. Cancer Res (2023); 83(5 Suppl):P6-04-07
  7. Broeckx et al. Virchows Arch (2023) 483 (Suppl 1): S36