AI in PET/CT: Detecting Multiple Cancers with Whole-Body Imaging

A revolutionary AI tool is transforming PET/CT imaging by automating the detection of six major cancer types with unmatched precision. Presented at the 2024 Society of Nuclear Medicine and Molecular Imaging (SNMMI) Annual Meeting, this breakthrough research illustrates how AI can quantify tumor burden, predict treatment response, and improve survival outcomes through whole-body molecular imaging.

Traditional AI cancer models have been limited by small datasets and narrow clinical focus — typically detecting just one malignancy type at a time, using a single radiotracer. According to Kevin H. Leung, PhD, research associate at Johns Hopkins University School of Medicine, this presents a serious limitation:

“Automatic detection and characterization of cancer are important clinical needs to enable early treatment.”

To overcome these boundaries, researchers developed a deep transfer learning model trained on whole-body PET/CT scans. The goal was to deliver fully automated tumor segmentation and outcome prediction across a wide range of cancer types.

Read the full study in the Journal of Nuclear Medicine.

The study analyzed two large datasets:

• • 611 FDG PET/CT scans from patients with:
  • Lung cancer
  • Melanoma
  • Lymphoma
  • Head and neck cancer
  • Breast cancer
  • 408 PSMA PET/CT scans focused on prostate cancer

The AI system extracted radiomic features and quantified tumor burden, enabling it to:

• • Stratify patients by risk level
  • Predict treatment response
  • Estimate survival rates based on tumor activity and spread

These insights move PET/CT from being a diagnostic tool to a powerful predictive imaging platform.

If you’re expanding oncology services, our Mobile PET/CT Solutions offer flexible deployment without fixed infrastructure costs.

AI in PET/CT now extends far beyond simple detection. The technology supports personalized care by identifying tumor subtypes and mapping the entire disease landscape in a single scan. Notable benefits include:

• • Predictive Biomarkers — Identify high-risk patients and tailor treatment
  • Earlier Detection — Improve outcomes through timely intervention
  • Therapy Optimization — Support late-stage care with accurate radiopharmaceutical dosing

Dr. Leung adds:

“This approach provides a framework that will help improve patient outcomes and survival by identifying robust predictive biomarkers, characterizing tumor subtypes, and enabling early cancer detection.”

The integration of AI into PET/CT workflows promises a new era of diagnostic precision and efficiency. Looking ahead, these tools will help:

• Automate and enhance scan interpretation
• Uncover molecular insights into complex disease pathways
• Improve imaging center efficiency and resource allocation

For imaging centers seeking next-generation diagnostics, our Mobile Imaging Solutions bring state-of-the-art PET/CT directly to your facility.

Media Contact:
Blake Kenney
Senior Marketing Specialist
Shared Medical Services, Inc.
Phone: (608) 910-1332
Email: contactsms@sharedmed.com