The association between lesion tracer uptake on 68Ga-DOTATATE PET with morphological response to 177Lu-DOTATATE therapy in patients with progressive metastatic neuroendocrine tumors
Bibliographic record
Abstract
PURPOSE: To determine in a group of patients with progressive metastatic neuroendocrine tumors (PM-NETs) treated with 177Lu-DOTATATE whether a correlation exists between somatostatin receptor (SSTR)-2 expression in various tumors on baseline 68Ga-DOTATATE PET and their response to therapy. A secondary aim was to determine whether an association exists between tumor product of diameter (POD) and PET-derived Krenning score. MATERIALS METHODS: Patients treated PM-NETs who had SSTR-2 overexpression (SSTR-RADS 5) on screening 68Ga-DOTATATE PET and CT at baseline and 3 months after therapy completion were included. Marker lesions on baseline CT were reassessed on CT after therapy using adapted Southwest Oncology Group solid tumor evaluation criteria. For each lesion, bidimensional diameter on CT and SSTR expression on PET (SSTR-RADS uptake score & PET-derived Krenning score) were recorded. Logistic regression models fitted through generalized estimating equations were used to assess for an association between SSTR expression and response to therapy, or lesion's POD. RESULTS: Forty-one patients with SSTR-RADS 5 PM-NETs treated with 177Lu-DOTATATE were included. There were 135 marker lesions (mean 3.2 lesions/patient) with Krenning score of 4 (n = 74), 3 (n = 44) or 2 (n = 17). There was no association found between SSTR-2 expression, as determined by SSTR-RADS uptake score or PET-derived Krenning score, and POD or response to therapy. CONCLUSION: In patients with SSTR-RADS 5 PM-NETs treated with 177Lu-DOTATATE, there was similar response to therapy for all lesions with PET-generated Krenning score ≥2. No correlation was found between lesion's POD and level of tracer uptake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".