Current status of optoacoustic breast imaging and future trends in clinical application: is it ready for prime time?
Berat Bersu ÖzcanHashini WanniarachchiRalph P MasonBasak E DoganPublished in: European radiology (2024)
Optoacoustic imaging (OAI) is an emerging field with increasing applications in patients and exploratory clinical trials for breast cancer. Optoacoustic imaging (or photoacoustic imaging) employs non-ionizing, laser light to create thermoelastic expansion in tissues and detect the resulting ultrasonic emission. By combining high optical contrast capabilities with the high spatial resolution and anatomic detail of grayscale ultrasound, OAI offers unique opportunities for visualizing biological function of tissues in vivo. Over the past decade, human breast applications of OAI, including benign/malignant mass differentiation, distinguishing cancer molecular subtype, and predicting metastatic potential, have significantly increased. We discuss the current state of optoacoustic breast imaging, as well as future opportunities and clinical application trends. CLINICAL RELEVANCE STATEMENT: Optoacoustic imaging is a novel breast imaging technique that enables the assessment of breast cancer lesions and tumor biology without the risk of ionizing radiation exposure, intravenous contrast, or radionuclide injection. KEY POINTS: • Optoacoustic imaging (OAI) is a safe, non-invasive imaging technique with thriving research and high potential clinical impact. • OAI has been considered a complementary tool to current standard breast imaging techniques. • OAI combines parametric maps of molecules that absorb light and scatter acoustic waves (like hemoglobin, melanin, lipids, and water) with anatomical images, facilitating scalable and real-time molecular evaluation of tissues.
Keyphrases
- high resolution
- clinical trial
- current status
- gene expression
- squamous cell carcinoma
- small cell lung cancer
- ejection fraction
- risk assessment
- low dose
- high dose
- radiation therapy
- randomized controlled trial
- mass spectrometry
- computed tomography
- climate change
- deep learning
- magnetic resonance imaging
- newly diagnosed
- radiation induced
- prognostic factors
- machine learning
- fluorescent probe
- high speed