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Record W4410633736 · doi:10.1101/2025.05.22.25328092

Evaluating the metabolic effects of neoadjuvant treatment in clear cell renal cell carcinoma using hyperpolarised [1- <sup>13</sup> C]pyruvate MRI

2025· preprint· en· W4410633736 on OpenAlexfundno aff
Ines Horvat‐Menih, Mary A. McLean, Jonathan R. Birchall, Maria Jesus Zamora Morales, Marta Wylot, Stephan Ursprung, Ramona Woitek, Eva Serrão, Ashley Grimmer, Elizabeth Latimer, Alixander S. Khan, Andrew N. Priest, Andrew B. Gill, Joshua Kaggie, Martin J. Graves, Tristan Barrett, James Wason, Helen Mossop, Martin G. Thomas, Salmiah Md Said, Anne Y. Warren, Kate Fife, Tim Eisen, Athena Matakidou, Will Ince, Brent O’Carrigan, James Jones, Sarah J. Welsh, Thomas J. Mitchell, James N. Armitage, Antony C. P. Riddick, Grant D. Stewart, Ferdia A. Gallagher

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
FundersNIHR Cambridge Biomedical Research CentreNational Institute for Health and Care ResearchDepartment of Health and Social CareCancer Research UKCanadian Institute for Advanced ResearchAstraZeneca
KeywordsRenal cell carcinomaOncologyNeoadjuvant therapyCellInternal medicineMedicineEndocrinologyCancer researchChemistryCancerBiochemistry

Abstract

fetched live from OpenAlex

Abstract Despite recent advances, ∼50% of people developing renal cell carcinoma (RCC) will die of the disease. The development of new neoadjuvant therapeutic strategies requires reliable companion biomarkers to measure early and successful response to treatment. Tumour size changes are often late markers of response, but novel imaging-based biomarkers may be more accurate for treatment response prediction. Here we evaluated the potential of hyperpolarised carbon-13 MRI (HP 13 C-MRI) as an emerging clinical imaging technique for assessing response to neoadjuvant treatment in RCC, as part of the WIndow of opportunity in REnal cancer (WIRE) trial. The change in LAC/PYR ratio following treatment was variable across the four patients (mean±S.D. %change = +6±27%). LAC/PYR decreased in the patient treated with cediranib monotherapy (−21%), and in one of the patients receiving combination treatment (−14%). A higher LAC/PYR ratio post-treatment was observed in the second patient receiving combination treatment (+21%) and in the patient receiving olaparib monotherapy (+35%). This is the first study to evaluate the potential of clinical HP 13 C-MRI in assessing early treatment response in renal cancer, which detected metabolic changes following treatment in the absence of significant changes in tumour size. Future studies should assess this finding in larger patient cohorts. Patient summary In this study we used an emerging clinical imaging technique, called hyperpolarised carbon-13 MRI, to visualise how kidney cancer changes with drug treatment before surgery. The method visualised rapid changes in cancer metabolism before substantial changes were seen in tumour size, the latter being the conventional method for detecting response to treatment. Hyperpolarised carbon-13 MRI holds promise in informing clinicians which cancers have successfully responded, and which may benefit from a change in treatment.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.046
GPT teacher head0.316
Teacher spread0.270 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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