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Evaluation of multifunctional imaging parameters in gastro-oesophageal cancer using F-18-FDG-PET/CT with integrated perfusion CT

2018· article· en· W2898313397 on OpenAlexaff
Bert-Ram Sah, C Leissing, Gaspar Delso, Edwin E. G. W. ter Voert, Stefan Krieg, Sebastian Leibl, Paul M. Schneider, Cäcilia S. Reiner, Martin Hüllner, Patrick Veit‐Haibach

Bibliographic record

VenueThe Quarterly Journal of Nuclear Medicine and Molecular Imaging · 2018
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineNuclear medicinePerfusionRadiologyPerfusion scanningPET-CTPet imagingCancerTomographyPositron emission tomographyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Positron emission tomography (PET) / computed tomography (CT) is among the most frequently used imaging modalities for initial staging of gastro-oesophageal (GE) cancer, whereas CT-perfusion (CTP) provides different multiparametric information. This proof of concept study compares CTP- and PET-parameters in patients with GE cancer to evaluate correlations and a possible prognostic value of a combined PET/CTP imaging procedure.METHODS: A total of 31 patients with F-18-FDG-PET/CT and CTP studies were prospectively analysed. Patients had adenocarcinoma (n = 22) and oesophageal squamous cell carcinoma (SCC, n = 9). Imaging was performed before start of treatment. CTP parameters [blood flow (BF), blood volume (BV), mean transit time (MTT)] and metabolic parameters [(maximum and mean standardised uptake values and standard deviation (SUVmax, SUVmean, SUVsd), metabolic tumour volume (MTV) and tumour lesion glycolysis (TLG)], as well as flow metabolic product [FMP (BF × SUVmax)] were determined and their relationship was compared. Additionally their association to clinical parameters (differentiation grading, staging, HER2-status, follow-up status) and to histopathological regression (post-neoadjuvant regression grading) was evaluated.RESULTS: Correlation between parameters of both modalities was significant between MTT and MTV (r = 0.375, p = 0.038); no other significant correlation was found. Patients with complete histopathological regression showed significantly lower BF and BV than patients with nearly complete or partial response. TLG and regression grading showed significant correlation with staging. All other quantitative parameters for CTP and PET data did not correlate significantly with histopathological regression grading, differentiation or staging.CONCLUSIONS: The combination of PET and CTP parameters (FMP) showed no significant prognostic value. Significant correlations were only found between MTT and MTV, which indicates a possible perfusional/metabolic coupling. Therefore, pre-therapeutic CTP and PET- parameters provide complementary information about the pre-therapeutic tumour status and are not interchangeable. Only CTP parameters might be able to predict complete histopathological regression. On the other hand, only PET parameters are correlated with staging.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.347
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations1
Published2018
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