Clinical Report: Utilizing Artificial Intelligence with 3D Total-Body Imaging

Background

Skin cancer detection is critical due to the potential lethality of melanoma when diagnosed late. Traditional methods often focus on individual lesions, which may not reflect real-world clinical scenarios where multiple lesions need to be assessed. The advent of AI and 3D TBP offers a new paradigm for comprehensive skin surveillance.

Data Highlights

No numerical data available in the source material.

Key Findings

• AI-assisted 3D TBP can capture a wider skin surface, aiding in lesion selection and triage.
• Current applications include automated triage, lesion detection, and longitudinal tracking.
• Evidence supporting the clinical value of AI-assisted 3D TBP remains limited and requires further research.
• Key challenges include skin tone reporting, workflow integration, and dataset transparency.
• Prospective studies are needed to evaluate the effectiveness of this technology in routine practice.

Clinical Implications

Clinicians should consider the potential of AI-assisted 3D TBP for comprehensive skin cancer surveillance.

Conclusion

Further evidence is necessary to support the routine clinical use of AI-assisted 3D TBP.

Related Resources & Content

1. npj Digital Medicine, 2025 -- Automated triage of cancer-suspicious skin lesions with 3D total-body photography
2. Frontiers in Medicine, 2026 -- Skin malformation assessment by triple wavelength imaging
3. The ASCO Post, 2025 -- AI Enhances Detection of Missed Breast Cancers on Screening Tomosynthesis
4. Recommendation: Skin Cancer: Screening | United States Preventive Services Taskforce
5. 3D Total-Body Photography in Patients at High Risk for Melanoma: A Randomized Clinical Trial | Trials | JAMA Dermatology
6. the asco post — AACR 2025: Pretrained AI Models Could Help Accurately Diagnose Nonmelanoma Skin Cancers in Resource-Limited Settings
7. Recommendation: Skin Cancer: Screening | United States Preventive Services Taskforce
8. 3D Total-Body Photography in Patients at High Risk for Melanoma: A Randomized Clinical Trial | Trials | JAMA Dermatology | JAMA Network
9. Performance of an automated total body mapping algorithm to detect melanocytic lesions of clinical relevance
10. 3D imaging Total Body Photography Vectra® WB360 and 2D imaging FotoFinder ATBM® Master imaging system and Smartphone application (SkinVision®) in Melanoma (Skin) - Clinical Trials Registry - ICH GCP