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Record W3113327466 · doi:10.1002/jmri.27458

Comparison Between Diffusion‐Weighted MRI and <sup>123</sup>I‐mIBG Uptake in Primary High‐Risk Neuroblastoma

2020· article· en· W3113327466 on OpenAlexfundno aff
Laura Privitera, Patrick W. Hales, Layla Musleh, Elizabeth Morris, Natalie Sizer, Giuseppe Barone, Paul Humphries, Kate Cross, Lorenzo Biassoni, Stefano Giuliani

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2020
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilMedical Research CouncilCHILDREN with CANCER UKMedical Research Council CanadaUniversity College LondonWellcome Trust
KeywordsNeuroblastomaMedicineNuclear medicineDiffusion MRIPrimary (astronomy)Nuclear magnetic resonanceRadiologyMagnetic resonance imagingPhysicsBiology

Abstract

fetched live from OpenAlex

Background High‐risk neuroblastoma (HR‐NB) has a variable response to preoperative chemotherapy. It is not possible to differentiate viable vs. nonviable residual tumor before surgery. Purpose To explore the association between apparent diffusion coefficient (ADC) values from diffusion‐weighted magnetic resonance imaging (DW‐MRI), 123 I‐meta‐iodobenzyl‐guanidine ( 123 I‐mIBG) uptake, and histology before and after chemotherapy. Study Type Retrospective. Subjects Forty patients with HR‐NB. Field Strength/Sequence 1.5T axial DW‐MRI (b = 0,1000 s/mm 2 ) and T 2 ‐weighted sequences. 123 I‐mIBG scintigraphy planar imaging (all patients), with additional 123 I‐mIBG single‐photon emission computed tomography / computerized tomography (SPECT/CT) imaging (15 patients). Assessment ADC maps and 123 I‐mIBG SPECT/CT images were coregistered to the T 2 ‐weighted images. 123 I‐mIBG uptake was normalized with a tumor‐to‐liver count ratio (TLCR). Regions of interest (ROIs) for primary tumor volume and different intratumor subregions were drawn. The lower quartile ADC value (ADC 25prc ) was used over the entire tumor volume and the overall level of 123 I‐mIBG uptake was graded into avidity groups. Statistical Tests Analysis of variance (ANOVA) and linear regression were used to compare ADC and MIBG values before and after treatment. Threshold values to classify tumors as viable/necrotic were obtained using ROC analysis of ADC and TLCR values. Results No significant difference in whole‐tumor ADC 25prc values were found between different 123 I‐mIBG avidity groups pre‐ ( P = 0.31) or postchemotherapy ( P = 0.35). In the “intratumor” analysis, 5/15 patients (prechemotherapy) and 0/14 patients (postchemotherapy) showed a significant correlation between ADC and TLCR values ( P &lt; 0.05). Increased tumor shrinkage was associated with lower pretreatment tumor ADC 25prc values ( P &lt; 0.001); no association was found with pretreatment 123 I‐mIBG avidity ( P = 0.17). Completely nonviable tumors had significantly lower postchemotherapy ADC 25prc values than tumors with &gt;10% viable tumor ( P &lt; 0.05). Both pre‐ and posttreatment TLCR values were significantly higher in patients with &gt;50% viable tumor than those with 10–50% viable tumor ( P &lt; 0.05). Data Conclusion 123 I‐mIBG avidity and ADC values are complementary noninvasive biomarkers of therapeutic response in HR‐NB. Level of Evidence 4. Technical Efficacy Stage 3.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.266
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.273
Teacher spread0.258 · 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.

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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Citations13
Published2020
Admission routes1
Has abstractyes

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