AIxTHY Solution | AIxMed, Inc.

Thyroid Cancer Facts

Fine-Needle Aspiration Cytology (FNAC) is the gold standard tool to aid in distinguishing between malignant and benign thyroid nodules. Unfortunately, thyroid biopsies do not always offer a definitive cytological diagnosis.

5TH(1)

Most common cancer in women

2.2K(2)

Estimated U.S. deaths
per year

53K(2)

Estimated new U.S. cases

25%(3)

High-grade 10-year recurrence rate

$6.1B(4)

Estimated U.S. expenditure for thyroid cancer care

Over-diagnosis may result in unnecessary procedures

Invasive surgeries may trigger patient anxiety

Unwarranted procedures and complications increase healthcare costs

Key Features of AIxTHY
Revolutionizing Thyroid Cancer Diagnosis with AI

AIxTHY is an AI-powered tool that analyzes thyroid cytology samples to improve diagnostic accuracy and efficiency. By automating analysis, it supports pathologists in making faster, more reliable cancer diagnoses, leading to better patient outcomes.

Functionality

It uses algorithms to identify suspicious cells, classify nodules, and detect malignancy, integrating molecular and histopathological data.

Integration with Clinical Practice

AIxTHY aids pathologists by reducing errors, accurately classifying nodules, and guiding treatment decisions, especially in distinguishing benign vs. malignant cases.

Benefits

AIxTHY automates cell classification and generates detailed reports, speeding decision-making, reducing unnecessary surgeries, and ensuring earlier, more accurate cancer detection for better outcomes.

Cellular Pattern Recognition

AIxTHY categorizes groups by cell types and provides the total number of groups identified per category
Categories include follicular cells, oncocytic cells, histiocytes, lymphocytes, and colloid
Diagnosis is pathologist-dependent

AI Enhances Diagnostic Confidence

AI analyzes all digital images for morphologic features to include: pale nuclei, marginal micronucleoli, nuclear grooving, pseudoinclusions, microfollicles, plasmacytoid/spindled cells, and salt and pepper chromatin.
A section entitled Traits Statistics provides a per-slide bar graph of morphologic features

Automated Reporting

AIxTHY software allows hierarchical reporting of positive, negative or nondiagnostic cases.
Reports are based on The Bethesda System (TBS) for Reporting Thyroid Cytopathology, with subclassification of positive cases into TBSIII, TBS IV, TBSV and TBSIV.
Integration with LIS for seamless resulting

Digital Screening Simplifies Review

All AI-analyzed digital images are displayed in thumbnail galleries by category.
Microscopic view augments the gallery so that relationships to background are easily assessed.
Revert to full WSI review at any time with one click.

Practice Efficiencies

AIxTHY permits easy sharing of cases for consultation, quality assurance, tumor planning conferences, education and research.

Be First in AI Thyroid Research

Explore future uses of AI in thyroid research by designing studies to define morphologic metrics and future clinical applications

Why choose AIxTHY

As part of a diagnostic strategy, AIxTHY from AIxMed helps to detect suspicious and atypical cells using samples collected using fine needle aspiration techniques.

Book demo

In development and soon available for Research Use Only (RUO) in the United States

Quantitative scoring based on the Bethesda System for Reporting Thyroid Cytopathology (TBSRTC)

Ideal for use with current
FNAC methods

Where AIxTHY Aids the Thyroid Cancer Patient Journey

Sample Collection

Cytology samples are collected and prepared.

AI Analysis

AIxTHY analyzes the samples to identify abnormal cells.

Scoring

The tool uses the Bethesda System (TBSRTC) for quantitative scoring of malignancy risk.

Reporting

AIxTHY generates a report to assist pathologists in making diagnostic decisions.

Step Up to a New Bladder Cancer Workflow

Data Collection and Preprocessing

Gathering patient data, imaging, and health records

AI Model Training

Training models on labeled datasets to recognize patterns and predict outcomes

Diagnosis and Prediction

High-resolution images of the stained slides are captured

Surgical Assistance

Repeat voided urines with AI Enhancing robotic surgery with image-guided precision and outcome predictions

Post-Operative Analysis

Monitoring recovery and assessing long-term health impacts

Other Applications

For Urine Cytology:
Bladder Cancer

Find out more

AIxURO: Detects suspicious and atypical cells from a non-invasive urine sample.

Find out more

For Cervical Cytology:
Cervical Cancer

Coming soon

AIxPAP: Cervical cancer is preventable but remains a major health challenge.

Coming soon

For Pulmonary Cytology:
Lung Cancer

Coming soon

AIxPUL: Empowering precision in lung cancer detection.

Coming soon

1. American Cancer Society (ACS) Cancer, Facts & Figures 2024, Slide Set: Cancer Facts & Figures 2024, accessed 2024.
2. SEER Cancer Stat Facts: Bladder Cancer. National Cancer Institute. Bethesda, MD, accessed 2024.
3. Wan H, Zhan X, Li X, et al. Assessing the prognostic impact of prostatic urethra involvement and developing a nomogram for T1 stage bladder cancer. BMC Urol. 2023;23(1):182. Published 2023 Nov 10. doi: 10.1186/s12894-023-01342-2
4. Cancer Trends Progress Report, National Cancer Institute, Bethesda, MD, accessed 2024.