ArticleJournal of personalized medicine2021
Improved Personalised Neuroendocrine Tumours' Diagnosis Predictive Power by New Receptor Somatostatin Image Processing Quantification.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although neuroendocrine tumours (NETs) are intensively studied, their diagnosis and consequently personalised therapy management is still puzzling due to their tumoral heterogeneity. In their theragnosis algorithm, receptor somatostatin scintigraphy takes the central place, the diagnosis receptor somatostatin analogue (RSA) choice depending on laboratory experience and accessibility. However, in all cases, the results depend decisively on correct radiotracer tumoral uptake quantification, where unfortunately there are still unrevealed clues and lack of standardization. We propose an improved method to quantify the biodistribution of gamma-emitting RSA, using tissular corrected uptake indices. We conducted a bi-centric retrospective study on 101 patients with different types of NETs. Three uptake indices obtained after applying new corrections to areas of interest drawn for the tumour and for three reference organs (liver, spleen and lung) were statistically analysed. For the corrected pathological uptake indices, the results showed a significant decrease in the error of estimating the occurrence of errors and an increase in the diagnostic predictive power for NETs, especially in the case of lung-referring corrected index. In conclusion, these results support the importance of corrected uptake indices use in the analysis of
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.