ArticleSurgical endoscopy2016
A novel approach of optical biopsy using probe-based confocal laser endomicroscopy for peritoneal metastasis.
Article in Surgical endoscopy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Flexible intraoperative detectors for robotic and laparoscopic image-guided surgery: a systematic review.European journal of nuclear medicine and molecular imaging · 2026Pooled it
- Artificial intelligence-based real-time histopathology of gastric cancer using confocal laser endomicroscopy.NPJ precision oncology · 2024Article
- Evolution of photodynamic medicine based on fluorescence image-guided diagnosis using indocyanine green and 5-aminolevulinic acid.Surgery today · 2020Review
- Towards an Optical Biopsy during Visceral Surgical Interventions.Visceral medicine · 2020Review
- Radiopharmaceuticals and Fluorescein Sodium Mediated Triple-Modality Molecular Imaging Allows Precise Image-Guided Tumor Surgery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2019Article
- Confocal laser microscopy as novel approach for real-time and in-vivo tissue examination during minimal-invasive surgery in colon cancer.Surgical endoscopy · 2019Article
- Feasibility of real-time intestinal bloodstream evaluation using probe-based confocal laser endomicroscopy in a porcine intestinal ischemia model.Surgical endoscopy · 2018Article
- Patent blue V and indocyanine green for fluorescence microimaging of human peritoneal carcinomatosis using probe-based confocal laser endomicroscopy.Surgical endoscopy · 2016Article
- Real-time Histological Evaluation of Gastric Cancer Tissue by Using a Confocal Laser Endomicroscopic System.In vivo (Athens, Greece)Article
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Authors and funding
14 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn digestive cancers, it is mandatory to diagnose peritoneal metastasis prior to selecting therapy. Therefore, exploratory laparoscopy has gained wider clinical acceptance. In laparoscopy, the peritoneal metastasis is pathologically confirmed by excisional biopsy; however, there remain technical difficulties in performing precise diagnosis and adequate biopsy on small peritoneal lesions without damaging organs. We have focused on "optical biopsy" using probe-based confocal laser endomicroscopy (pCLE). The aims of this study were (1) to optimize current CLE system for real-time observation of peritoneal metastases and (2) to assess its potential usefulness as diagnostic modality in preclinical settings.
methodsTo optimize condition and evaluate feasibility, we prepared peritoneal metastasis mice model with gastric cancer cell line (MKN-45). On Day 10 after seeding, the mice were laparotomized and performed pCLE observations with CellvizioLAB (LSU-F 400/488 nm, Mauna Kea Technologies, Paris, France). We evaluated two different CLE probes, three different dyes, and optimal interval time. The detected sites were excised and pathologically evaluated on its morphology. Next, the feasibility and safety were validated in porcine model for clinical usage. After injection of fluorescein, pCLE was applied for the observation of intra-abdominal organs.
resultA miniature probe-type pCLE system with 60 μm focal depth (UltraMini O) and 1 % fluorescein dye was chosen for good visualization in mice model. The irregular microarchitecture images suspected to malignancy were obtained from the metastases. In the porcine model, observation of abdominal organs was feasible without any organ injury in the laparoscopic procedures. The dosage of 1 % fluorescein (3 ml/body) was appropriate in observing intra-abdominal organs, and each intra-abdominal organ was clearly observed with the same imaging quality we obtained in mice model.
conclusionThe pCLE was feasible and safe and potentially useful for the diagnosis of the peritoneal metastasis in in vivo animal models.
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