Evidence map›Paper›PMID 28779247›Full record

ArticleSurgical endoscopy2018

Optimization of liposomal indocyanine green for imaging of the urinary pathways and a proof of concept in a pig model.

Yael Friedman-Levi, Liraz Larush, Michele Diana, Francesco Marchegiani, Jacques Marescaux, Noam Goder, Guy Lahat, Joseph Klausner, Sara Eyal, Shlomo Magdassi and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Surgical endoscopy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
1.4field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 4 institutions in 2 countries.

Yael Friedman-LeviInstitute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel.
Liraz LarushCasali Institute for Applied Chemistry, The Hebrew University of Jerusalem, Jerusalem, Israel.
Michele DianaIHU-Strasbourg, Institute of Image-Guided Surgery, 1, place de l'Hôpital, 67091, Strasbourg, France.
Francesco MarchegianiIHU-Strasbourg, Institute of Image-Guided Surgery, 1, place de l'Hôpital, 67091, Strasbourg, France.
Jacques MarescauxIHU-Strasbourg, Institute of Image-Guided Surgery, 1, place de l'Hôpital, 67091, Strasbourg, France.
Noam GoderLaboratory of Surgical Oncology, Division of Surgery, Department of Surgery A, Tel-Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
Guy LahatLaboratory of Surgical Oncology, Division of Surgery, Department of Surgery A, Tel-Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
Joseph KlausnerLaboratory of Surgical Oncology, Division of Surgery, Department of Surgery A, Tel-Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.
Sara EyalInstitute for Drug Research, The Hebrew University of Jerusalem, Jerusalem, Israel.
Shlomo MagdassiCasali Institute for Applied Chemistry, The Hebrew University of Jerusalem, Jerusalem, Israel.
Eran NizriLaboratory of Surgical Oncology, Division of Surgery, Department of Surgery A, Tel-Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. erann@tlvmc.gov.il.
Hebrew University of Jerusalem · ILInstitut de Chirurgie Guidée par l'Image · FRTel Aviv Sourasky Medical Center · ILTel Aviv University · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIatrogenic ureteral injury is an increasing concern in the laparoscopic era, affecting both patient morbidity and costs. Current techniques enabling intraoperative ureteral identification require invasive procedures or radiations. Our aim was to develop a real-time, non-invasive, radiation-free method to visualize ureters, based on near-infrared (NIR) imaging. For this purpose, we interfered with the biliary excretion pathway of the indocyanine green (ICG) fluorophore by loading it into liposomes, enabling renal excretion. In this work, we studied various parameters influencing ureteral imaging.

methodsFluorescence intensity (FI) of various liposomal ICG sizes and doses were characterized in vitro and subsequently tested in vivo in mice and pigs. Quantification was performed by measuring FI in multiple points and applying the ureteral/retroperitoneum ratio (U/R).

resultsThe optimal liposomal ICG loading dose was 20%, for the different liposomes' sizes tested (30, 60, 100 nm). Higher concentration of ICG decreased FI. In vivo, the optimal liposome size for ureteral imaging was 60 nm, which yielded a U/R of 5.2 ± 1.7 (p < 0.001 vs. free ICG). The optimal ICG dose was 8 mg/kg (U/R = 2.1 ± 0.4, p < 0.05 vs. 4 mg/kg). Only urine after liposomal ICG injection had a measurable FI, and not after free ICG injection. Using a NIR-optimized laparoscopic camera, ureters could be effectively imaged in pigs, from 10 min after injection and persisting for at least 90 min. Ureteral peristaltic waves could be clearly identified only after liposomal ICG injection.

conclusionsOptimization of liposomal ICG allowed to visualize enhanced ureters in animal models and seems a promising fluorophore engineering, which calls for further developments.

Indexed as

AnimalsFemaleFluorescent DyesIndocyanine GreenLiposomesMaleMiceOptical ImagingSpectroscopy, Near-InfraredSwineUreterFluorescent DyesIndocyanine GreenLiposomesIndocyanine greenLiposomesMinimal invasive surgeryUreteral injury

Identifiers

PMID28779247
OpenAlexW2743840743

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.