ArticleEuropean radiology2018
Hepatic neuroendocrine tumour: Apparent diffusion coefficient as a potential marker of prognosis associated with tumour grade and overall survival.
Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 10 citations in OpenAlex.
- Synthetic data generation method improves risk prediction model for early tumor recurrence after surgery in patients with pancreatic cancer.Scientific reports · 2025Article
- The combination of hepatobiliary phase with Gd-EOB-DTPA and DWI is highly accurate for the detection and characterization of liver metastases from neuroendocrine tumor.European radiology · 2020Article
- Correlation Between Apparent Diffusion Coefficient Value on MRI and Histopathologic WHO Grades of Neuroendocrine Tumors.Journal of the Belgian Society of Radiology · 2020Article
- CT radiomics may predict the grade of pancreatic neuroendocrine tumors: a multicenter study.European radiology · 2019Article
- Prognostic value of baseline volumetric multiparametric MR imaging in neuroendocrine liver metastases treated with transarterial chemoembolization.European radiology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate the correlation between grade of hepatic neuroendocrine tumours (NETs) according to the 2010 World Health Organization (WHO) classification and the apparent diffusion coefficient (ADC) and to assess whether ADC value can predict overall survival (OS) after diagnosis of hepatic NETs.
methodsThe study included 63 patients who underwent magnetic resonance (MR) imaging with diffusion-weighted images for the evaluation of hepatic NETs. The correlation between qualitative and quantitative MR imaging findings, including ADC values, and WHO classifications was assessed. The association between ADC value and OS was analyzed.
resultsThe ADC values and WHO classification of hepatic NETs were moderately negatively correlated in a statistically significant manner (ρ = -0.57, p < 0.001). The OS rates were significantly different according to the ADC value (low ADC vs. high ADC, p = 0.006) as well as WHO classifications (G1+ G2 vs. G3, p = 0.038). However, multivariate analysis revealed that the only independent predictor for OS was a low ADC value (hazard ratio: 3.37, p = 0.010).
conclusionThere was a significant correlation between the ADC value of hepatic NETs and the WHO tumour grade. Additionally, the ADC value of a hepatic NET might be more accurate than the current WHO tumour grade for predicting OS. KEY POINTS: • ADC values of hepatic NET and WHO tumour grade were negatively correlated. • Lower ADC values of hepatic NET were significantly correlated with worse OS. • ADC value might be more accurate than WHO grade for predicting OS.
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.