Scientific Publications

Men who are 90+ years old with metastatic castration-resistant (mCRPC) prostate cancer are at risk of significant side effects if they undergo chemotherapy treatment. Targeted radioligand (radiopharmaceutical) therapy presents a promising alternative. Our team evaluated the response, side effects, and quality of life of patients 90+ years old who received radioligand therapy at BAMF Health.

BAMF Health, in partnership with Nihon Medi-Physics Co., Ltd. (NMP), imaged the first patient in the world at BAMF Health using the novel molecular imaging agent NMK89 developed by NMP. This was an important first step in developing improved imaging and a potential therapy for pancreatic cancer.

Read BAMF Health’s announcement.

BAMF Health was chosen to partner with the National Cancer Institute to develop AI models to rapidly analyze scans and correctly identify cancer.

In part one of the project, BAMF analyzed approximately 3,000 lung, liver, and prostate cancer PET/CT scans and developed AI algorithms to distinguish tumors from surrounding healthy tissue. Our team then partnered with radiologists to continually adjust the AI models to improve accuracy. In part two, we followed a similar process for breast and brain cancer images. In all, our team of seven created 11 AI algorithms and analyzed more than 6,000 scans. Our results were compiled on a public dashboard and are now used by cancer experts across the globe.

The BAMF Health AI team developed a new method to improve how artificial intelligence identifies cancerous lesions in PET/CT scans. Normally, AI models can mistake certain organs, like the liver, brain, and bladder, for cancer because they also absorb a lot of the imaging tracer. To fix this, the team trained the AI to recognize both organs and cancerous lesions separately, making its predictions more accurate. They tested their approach on a large dataset of over 1,000 patients and found it worked better than other methods. Their model ranked highest in a competitive test, showing that this technique could help doctors more accurately assess cancer and improve patient care.

The BAMF Health AI team developed an advanced artificial intelligence (AI) model to help detect and outline head and neck tumors in PET/CT scans. In medical imaging, accurately identifying tumors can be challenging because they often blend in with surrounding tissues. To improve accuracy, the team used a powerful deep learning model trained on a large dataset from the HECKTOR 2021 challenge. Their AI system learned to distinguish tumors more effectively, making it easier for doctors to assess cancer and plan treatments. Their approach performed well in the competition, showing promise for improving cancer diagnosis and patient care.

Case report showing how PSMA PET detected an unexpected intrahepatic cholangiocarcinoma in a patient with metastatic prostate cancer, enabling multidisciplinary management with Pluvicto, radiation therapy, and follow-up molecular imaging.

Review article framing theranostics as a broader precision-medicine pathway in which molecular imaging verifies target expression and helps guide targeted treatment decisions beyond radiopharmaceutical therapy alone.

Review article describing how AI and machine learning may support PSMA PET interpretation, patient selection, treatment planning, response monitoring, and scalable prostate cancer theranostics workflows.

Review article outlining the infrastructure, workforce, radiopharmacy, radiation safety, reimbursement, and access considerations needed to build scalable theranostics programs.

Applied Radiology sponsored article/case series comparing intraindividual Illuccix and Gozellix PSMA PET/CT findings, showing comparable biodistribution and lesion uptake across representative prostate cancer cases.

Featured scientific magazine article describing how total-body PET/CT can support theranostic patient selection, therapy planning, response assessment, dosimetry, and scalable precision oncology workflows.