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Three-phase scintigraphy as an addition to the traditional singlephoton diagnosis of patients with neuroendocrine tumors

2025· article· W4416056350 on OpenAlexaff
С. М. Каспшик, А. Д. Рыжков, А. С. Крылов, Е. В. Артамонова, А. А. Маркович, М. Е. Билик

Bibliographic record

VenueMedical alphabet · 2025
Typearticle
Language
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsNational Defence Medical Centre
Fundersnot available
KeywordsNeuroendocrine tumorsScintigraphyRadiological weaponEndocrine systemSomatostatinImmunohistochemistrySomatostatin receptor

Abstract

fetched live from OpenAlex

Introduction . Neuroendocrine tumors (NET) are a heterogeneous group of neoplasms originating from enterochromaphin cells of the diffuse endocrine system. Nuclear medicine, imaging of somatostatin receptors, plays a leading role in identifying and assessing the status of NET. Purpose . To determine the complex of X-ray and radiological signs characteristic of neuroendocrine tumors and compare them with an immunohistochemical study of expression levels of somatostatin receptors. Materials and methods . The study included 119 patients with NET of various localizations who were examined at the N. N. Blokhin National Research Medical Center of Oncology from 2019 to 2022. There are 75 women and 44 men among them (63 % and 37 %, respectively). The age of the patients ranged from 1 to 84 years (median – 60). Results . When comparing the Grade values depending on the «flash» in a dynamic study, we found statistically significant differences (p=0.010).Conclusions. Clinical and radiological criteria for the qualitative characteristics of dynamic scintigraphy in NET make it possible to predict the effectiveness of treatment and the course of the disease, and the use of 3-phase scintigraphy with 99mTc-tectrotide makes it possible to diagnose a neuroendocrine tumor in 46 % of patients before receiving histological material or when it is impossible to obtain it.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.316
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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