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Record W2938383621 · doi:10.2967/jnumed.118.225185

The Contribution of Multiparametric Pelvic and Whole-Body MRI to Interpretation of <sup>18</sup>F-Fluoromethylcholine or <sup>68</sup>Ga-HBED-CC PSMA-11 PET/CT in Patients with Biochemical Failure After Radical Prostatectomy

2019· article· en· W2938383621 on OpenAlexaff
Ur Metser, Sue Chua, Bao Ho, Shonit Punwani, Edward W. Johnston, Frédéric Pouliot, Noam Tau, Asmaa Hawsawy, Reut Anconina, Glenn Bauman, Rodney J. Hicks, Andrew Weickhardt, Ian D. Davis, Gregory R. Pond, Andrew M. Scott, Nina Tunariu, Harbir Sidhu, Louise Emmett

Bibliographic record

VenueJournal of Nuclear Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversité LavalMcMaster UniversityLondon Health Sciences CentreUniversity of Toronto
FundersFoundation MedicineUniversity College LondonCancer Research UKMovember FoundationSociety of Nuclear Medicine and Molecular Imaging
KeywordsNuclear medicineMedicineProstatectomyBiochemical recurrenceProstate cancerPositron emission tomographyCancerInternal medicine

Abstract

fetched live from OpenAlex

Our purpose was to assess whether the addition of data from multiparametric pelvic MRI (mpMR) and whole-body MRI (wbMR) to the interpretation of <sup>18</sup>F-fluoromethylcholine (<sup>18</sup>F-FCH) or <sup>68</sup>Ga-HBED-CC PSMA-11 (<sup>68</sup>Ga-PSMA) PET/CT (=PET) improves the detection of local tumor recurrence or of nodal and distant metastases in patients after radical prostatectomy with biochemical failure. <b>Methods:</b> The current analysis was performed as part of a prospective, multicenter trial on <sup>18</sup>F-FCH or <sup>68</sup>Ga-PSMA PET, mpMR, and wbMR. Eligible men had an elevated level of prostate-specific antigen (PSA) (&gt;0.2 ng/mL) and high-risk features (Gleason score &gt; 7, PSA doubling time &lt; 10 mo, or PSA &gt; 1.0 ng/mL) with negative or equivocal conventional imaging results. PET was interpreted with mpMR and wbMR in consensus by 2 radiologists and compared with prospective interpretation of PET or MRI alone. Performance measures of each modality (PET, MRI, and PET/mpMR–wbMR) were compared for each radiotracer and each individual patient (for <sup>18</sup>F-FCH, or <sup>68</sup>Ga-PSMA for patients who had <sup>68</sup>Ga-PSMA PET) and to a composite reference standard. <b>Results:</b> There were 86 patients with PET (<sup>18</sup>F-FCH [<i>n</i> = 76] and/or <sup>68</sup>Ga-PSMA [<i>n</i> = 26]) who had mpMR and wbMR. Local tumor recurrence was detected in 20 of 76 (26.3%) on <sup>18</sup>F-FCH PET/mpMR, versus 11 of 76 (14.5%) on <sup>18</sup>F-FCH PET (<i>P</i> = 0.039), and in 11 of 26 (42.3%) on <sup>68</sup>Ga-PSMA PET/mpMR, versus 6 of 26 (23.1%) on <sup>68</sup>Ga-PSMA PET (<i>P</i> = 0.074). Per patient, PET/mpMR was more often positive for local tumor recurrence than PET (<i>P</i> = 0.039) or mpMR (<i>P</i> = 0.019). There were 20 of 86 patients (23.3%) with regional nodal metastases on both PET/wbMR and PET (<i>P</i> = 1.0) but only 12 of 86 (14%) on wbMR (<i>P</i> = 0.061). Similarly, there were more nonregional metastases detected on PET/wbMR than on PET (<i>P</i> = 0.683) or wbMR (<i>P</i> = 0.074), but these differences did not reach significance. Compared with the composite reference standard for the detection of disease beyond the prostatic fossa, PET/wbMR, PET, and wbMR had sensitivity of 50%, 50%, and 8.3%, respectively, and specificity of 97.1%, 97.1%, and 94.1%, respectively. <b>Conclusion:</b> Interpretation of PET/mpMR resulted in a higher detection rate for local tumor recurrence in the prostatic bed in men with biochemical failure after radical prostatectomy. However, the addition of wbMR to <sup>18</sup>F-FCH or <sup>68</sup>Ga-PSMA PET did not improve detection of regional or distant metastases.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.038
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.274
Teacher spread0.267 · 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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Citations46
Published2019
Admission routes1
Has abstractyes

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