ArticleJournal of translational medicine2019
Tissue diagnosis during colorectal cancer surgery using optical sensing: an in vivo study.
Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in colorectal surgery: an AI-powered systematic review.Techniques in coloproctology · 2023Pooled it
- Beveled Fiber Probe for Improving Spectroscopic Signal Sensing from Bowel Mucosa Tissue.Chemical & biomedical imaging · 2026Article
- Identification of colorectal malignancies enabled by phasor-based autofluorescence lifetime macroimaging and ensemble learning.Biophotonics discovery · 2025Article
- Toward the use of diffuse reflection spectroscopy for intra-operative tissue discrimination during sarcoma surgery.Journal of biomedical optics · 2024Article
- [Diagnostic Study of Multi-spectral Intelligent Analyzer in Diagnosis of the Infiltration Degree of Lung Adenocarcinoma].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023Article
- Diffuse reflection spectroscopy at the fingertip: design and performance of a compact side-firing probe for tissue discrimination during colorectal cancer surgery.Biomedical optics express · 2023Article
- Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization.Cancers · 2022Article
- Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy.Scientific reports · 2022Article
- Optical diagnosis of oral cavity lesions by label-free Raman spectroscopy.Biomedical optics express · 2021Article
- Evaluation of wavelength ranges and tissue depth probed by diffuse reflectance spectroscopy for colorectal cancer detection.Scientific reports · 2021Article
- Optical percutaneous needle biopsy of the liver: a pilot animal and clinical study.Scientific reports · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn colorectal cancer surgery there is a delicate balance between complete removal of the tumor and sparing as much healthy tissue as possible. Especially in rectal cancer, intraoperative tissue recognition could be of great benefit in preventing positive resection margins and sparing as much healthy tissue as possible. To better guide the surgeon, we evaluated the accuracy of diffuse reflectance spectroscopy (DRS) for tissue characterization during colorectal cancer surgery and determined the added value of DRS when compared to clinical judgement.
methodsDRS spectra were obtained from fat, healthy colorectal wall and tumor tissue during colorectal cancer surgery and results were compared to histopathology examination of the measurement locations. All spectra were first normalized at 800 nm, thereafter two support vector machines (SVM) were trained using a tenfold cross-validation. With the first SVM fat was separated from healthy colorectal wall and tumor tissue, the second SVM distinguished healthy colorectal wall from tumor tissue.
resultsPatients were included based on preoperative imaging, indicating advanced local stage colorectal cancer. Based on the measurement results of 32 patients, the classification resulted in a mean accuracy for fat, healthy colorectal wall and tumor of 0.92, 0.89 and 0.95 respectively. If the classification threshold was adjusted such that no false negatives were allowed, the percentage of false positive measurement locations by DRS was 25% compared to 69% by clinical judgement.
conclusionThis study shows the potential of DRS for the use of tissue classification during colorectal cancer surgery. Especially the low false positive rate obtained for a false negative rate of zero shows the added value for the surgeons. Trail registration This trail was performed under approval from the internal review board committee (Dutch Trail Register NTR5315), registered on 04/13/2015, https://www.trialregister.nl/trial/5175 .
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.