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Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

Artificial Intelligence Across the PSMA Theranostic Continuum in Prostate Cancer.

Gowtham Murugesan¹, Stephen Moore¹, Anthony Chang¹

¹BAMF Health, Grand Rapids, MI 49503, USA.

|April 12, 2026

Summary

Prostate cancer management is advancing with PSMA theranostics for imaging and treatment. Artificial intelligence (AI) offers potential to improve accuracy, patient selection, and monitoring in this evolving field.

Keywords:

Artificial intelligence Imaging biomarkers PSMA PET/RT Personalized medicine Theranostics

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Last Updated: Apr 14, 2026

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

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Published on: June 10, 2025

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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

Oncology
Radiology
Nuclear Medicine

Background:

Prostate cancer is a leading male malignancy globally.
PSMA theranostics, combining imaging and therapy, are revolutionizing prostate cancer care.
Current PSMA theranostics face challenges in specialist capacity and interpretation consistency.

Purpose of the Study:

To explore the role of artificial intelligence (AI) in enhancing PSMA theranostics for prostate cancer.
To identify how AI can address current limitations in PSMA-based management.
To outline AI's potential impact on imaging, treatment, and monitoring.

Main Methods:

Review of current literature on PSMA theranostics and AI in oncology.
Analysis of AI applications in medical imaging and treatment planning.
Synthesis of potential AI integration points within the PSMA theranostic workflow.

Main Results:

PSMA PET/CT enables sensitive disease detection.
PSMA-directed radioligand therapy offers effective treatment.
AI can potentially improve imaging interpretation accuracy and consistency.
AI may optimize patient selection and treatment response monitoring.

Conclusions:

AI and machine learning are poised to significantly enhance PSMA theranostics in prostate cancer.
AI integration can improve diagnostic accuracy, personalize treatment selection, and refine response assessment.
The synergy of AI with PSMA theranostics promises to advance prostate cancer management.