[R01] Artificial Intelligence-powered Advanced Ultrasound for Early Diagnosis of Intraocular Melanoma
Ente: National Cancer Institute
Scadenza: 2031-05-31
Importo max: 643.606 EUR
Paese: US
Descrizione
SUMMARY
Choroidal melanoma is the most common primary intraocular malignancy in adults and a potentially fatal cancer
that continues to be challenging in all respects. Choroidal melanoma can arise from preexisting choroidal nevus
or de novo. Distinguishing early-stage choroidal melanoma from nevus can be challenging as they share similar
ophthalmoscopic appearances when small. Up now, no single objective gold standard modality can successfully
discriminate between these two entities. Formation of new and aberrant vascular networks are seen in de novo
cases of choroidal melanoma as well as in the transformation of an existing nevus to melanoma. Our long-term
goal is to combine novel artificial intelligence techniques with such new noninvasive tool for the diagnosis of
early-stage choroidal melanoma. A secondary gain from such an imaging method will be assessment of
treatment monitoring. Here, we propose to advance a new ultrasound-based technology, quantitative high
definition microvessel imaging (qHDMI) that reveals tumor microvessels as small as 150µm and quantifies the
microvessel morphological structures as new quantitative imaging biomarkers. Our goal is to combine novel
artificial intelligence techniques with such new noninvasive tool for the diagnosis of early-stage choroidal
melanoma. An advantage of the proposed qHDMI technique is that it does not require the use of contrast agents
to produce high-resolution images of the microvasculature. We plan to address two aspects: Diagnose early-
stage choroidal melanoma and assess the response to radiation therapy or transpupillary thermotherapy in
patients with choroidal melanoma. The project includes 2 specific aims: Specific Aim #1 includes two sub-aims:
Sub-Aim1.1: Determine the feasibility of the combined AI techniques with new qHDMI biomarkers and images
for differentiation of choroidal melanoma from choroidal nevus and correlate with the clinical diagnosis based on
all multimodality ophthalmic imaging together and gene expression profiling if clinically recommended. Sub-Aim
1.2: Longitudinal monitoring of the clinically diagnosed benign choroidal nevi in Aim 1.1 and determine the
feasibility of qHDMI for detecting the transformation of choroidal nevus to Melanoma. Specific Aim #2:
Determine the feasibility of qHDMI for treatment monitoring in patients with choroidal melanoma and correlate
the results with the clinical diagnosis based on all multimodal ophthalmic imaging together. This proposal is the
result of collaboration among leading experts in the field and benefits from the world-class research environment
at the Mayo Clinic. Successful completion of this research will pave the way for novel, non-invasive, low-cost,
and user-friendly technology for patients with ocular tumors. The qHDMI technique, enhanced with advanced AI-
powered deep learning algorithms, holds strong potential for clinical translation and broad accessibility. We
anticipate it will significantly benefit patients wit
Istituzione: MAYO CLINIC ROCHESTER
PI: Azra Alizad, MOSTAFA FATEMI
Progetto: 1R01CA304060-01A1
Settori: National Cancer Institute
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