ArticleSensors (Basel, Switzerland)2021
Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 29 citations in OpenAlex.
- Artificial intelligence and oral microbiome: Reshaping the diagnostic and therapeutic paradigm of OSCC.Clinical and translational medicine · 2026Review
- Temperature-induced hemoglobin dynamics: oxygenation-dependent evolution of hemoglobin spectral response in the near-infrared.Biophotonics discovery · 2026Article
- Vasomics of the liver.Gut · 2025Review
- Surgical optomics: hyperspectral imaging and deep learning towards precision intraoperative automatic tissue recognition-results from the EX-MACHYNA trial.Surgical endoscopy · 2024Article
- Non-Fourier Bioheat Transfer Analysis in Brain Tissue During Interstitial Laser Ablation: Analysis of Multiple Influential Factors.Annals of biomedical engineering · 2024Article
- In Vitro Antibody Quantification with Hyperspectral Imaging in a Large Field of View for Clinical Applications.Bioengineering (Basel, Switzerland) · 2023Article
- Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.Sensors (Basel, Switzerland) · 2022Article
- Automatic optical biopsy for colorectal cancer using hyperspectral imaging and artificial neural networks.Surgical endoscopy · 2022Article
- Estimation of porcine pancreas optical properties in the 600-1100 nm wavelength range for light-based therapies.Scientific reports · 2022Article
- Interstitial Optical Monitoring of Focal Laser Ablation.IEEE transactions on bio-medical engineering · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 3 countries.
Funding
Abstract
Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser ablation (LA) is one of the least invasive approaches, especially for tumors in high-risk locations. Precise control of the LA effect is required to safely destroy the tumor. Although temperature imaging techniques provide an indirect measurement of the thermal damage, a degree of uncertainty remains about the treatment effect. Optical techniques are currently emerging as tools to directly assess tissue thermal damage. Among them, hyperspectral imaging (HSI) has shown promising results in image-guided surgery and in the thermal ablation field. The highly informative data provided by HSI, associated with deep learning, enable the implementation of non-invasive prediction models to be used intraoperatively. Here we show a novel paradigm "peak temperature prediction model" (PTPM), convolutional neural network (CNN)-based, trained with HSI and infrared imaging to predict LA-induced damage in the liver. The PTPM demonstrated an optimal agreement with tissue damage classification providing a consistent threshold (50.6 ± 1.5 °C) for the damage margins with high accuracy (~0.90). The high correlation with the histology score (r = 0.9085) and the comparison with the measured peak temperature confirmed that PTPM preserves temperature information accordingly with the histopathological assessment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.