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<p>Near-infrared (NIR) fluorescence-guided surgery (FGS) is limited by operator-dependent acquisition and non-uniform datasets, hindering quantitative comparison between users, devices, and institutions. To address these limitations, we evaluated an advanced wearable Cancer Vision Goggles (CVG) platform that standardizes imaging via dual green-pointer alignment, enabling reproducible acquisition geometry. The preclinical component benchmarked imaging standardization, quantitative robustness, and agreement with established systems, whereas the clinical arm assessed feasibility and performance relative to an FDA-approved system. Performance was evaluated using quantitative endpoints, including tumor-to-nontumor ratio (TNR), normalized intensity maps (NIMs), and Sørensen-Dice (Dice) coefficient spatial overlap. CVG achieved comparable or superior tumor contrast with high spatial overlap, as confirmed by these quantitative analysis metrics. Unlike handheld systems, CVG maintained stable fluorescence detection with no significant change in tumor-to-nontumor ratio from 10 to 60 cm, enabling reproducible quantitative imaging over a broad working-distance range. Extension to human tumors from patients injected with an NIR molecular probe (ClinicalTrials.gov: NCT05576974, 04/08/2025) demonstrated performance equivalent to that of an established FGS system with a substantial footprint in the operating room. In addition, CVG provided practical advantages through standardized single-operator acquisition, reduced operator-dependent variability relative to handheld or cart-based imaging, and quantitative real-time threshold-based visualization. These findings establish a quantitatively validated wearable platform that standardizes FGS from preclinical benchmarking to clinically relevant tumor assessment.</p>

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Bridging preclinical and clinical fluorescence-guided surgery with advanced cancer vision goggles

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月25日

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  • Haini Zhang,
  • Xiao Xu,
  • Christopher Ta,
  • Ian Zurutuza,
  • Krishna Sharmah Gautam,
  • Cody Hongsermeier,
  • Nicole Blasi,
  • Sindhu Voorugonda,
  • Neije Mukherjee-Roy,
  • Jinming Gao,
  • Baran Sumer,
  • Walter J. Akers,
  • Samuel Achilefu

摘要

Near-infrared (NIR) fluorescence-guided surgery (FGS) is limited by operator-dependent acquisition and non-uniform datasets, hindering quantitative comparison between users, devices, and institutions. To address these limitations, we evaluated an advanced wearable Cancer Vision Goggles (CVG) platform that standardizes imaging via dual green-pointer alignment, enabling reproducible acquisition geometry. The preclinical component benchmarked imaging standardization, quantitative robustness, and agreement with established systems, whereas the clinical arm assessed feasibility and performance relative to an FDA-approved system. Performance was evaluated using quantitative endpoints, including tumor-to-nontumor ratio (TNR), normalized intensity maps (NIMs), and Sørensen-Dice (Dice) coefficient spatial overlap. CVG achieved comparable or superior tumor contrast with high spatial overlap, as confirmed by these quantitative analysis metrics. Unlike handheld systems, CVG maintained stable fluorescence detection with no significant change in tumor-to-nontumor ratio from 10 to 60 cm, enabling reproducible quantitative imaging over a broad working-distance range. Extension to human tumors from patients injected with an NIR molecular probe (ClinicalTrials.gov: NCT05576974, 04/08/2025) demonstrated performance equivalent to that of an established FGS system with a substantial footprint in the operating room. In addition, CVG provided practical advantages through standardized single-operator acquisition, reduced operator-dependent variability relative to handheld or cart-based imaging, and quantitative real-time threshold-based visualization. These findings establish a quantitatively validated wearable platform that standardizes FGS from preclinical benchmarking to clinically relevant tumor assessment.