Abstract A014: Prognostic value of tumor asphericity on initial staging 18F- FDG PET/CT in patients with breast cancer
Bibliographic record
Abstract
Abstract Back ground: Tumor ASP (aspherecity) indicates a more irregular tumor shape and is a quantitative parameter indicating metabolic heterogeneity in tumor microenvironment. A higher degree of tumor ASP is associated with more aggressive behavior and confers a poorer prognosis. Aim: To evaluate role of tumor ASP on initial 18F-FDG PET/CT scans as a prognostic marker in patients with breast IDC. Materials and methods: Clinical and histopathological characterstics of 87 treatment naïve breast carcinoma patients (mean age 29.4 years; range, 28-83 years) and their 18F-FDG PET/CT scans performed between January 2017 and October 2023 were retrospectively analyzed in this study. Calculations: Primary tumor SULpeak, MTV and TLG were calculated using MetaVol (release 2022) and LIFEx software (version 7.6). For calculation of metabolic volumes, a fixed threshold of SUVmax of 2.5 was used. Tumor apshericity was calculated using the formula ASP % = 100 x (∛H-1), where H= (1S3)/(36πV2) where S and V are surface area and MTV of tumor respectively. Statistical analysis: All data analysis was carried out using Medcalc (version 23.0.9, MedCalc Software Ltd, Ostend, Belgium) and Minitab (version 22.1.1; Minitab LLC) statistical softwares. Cox univariate and multivariate regression analysis with forward selection were used to analyze relationship between independent variables and PFS. Kaplan - Meier curves were generated for PFS and difference in survival between groups was assessed using log-rank test. All P values were 2-sided and values of < 0.05 were considered statistically significant. Results: Mean follow-up time was 62 months for entire study sample. PFS rate among 87 patients was 81.6%. Whereas mean time period for regional or metastatic recurrence was 22 months. Cox univariate analysis revealed that primary tumor size (HR = 0.86; p value- 0.05), lymph node metastasis (HR = 14.6; p value = 0.224), negative hormonal receptor (ER, PR) status (HR =6.4; p = 0.038), HER2/neu negative status (HR =1.46; p = 0.947), SULpeak > 3.9 (HR =6.8; p value = 0.094) MTV > 6.8 mL (HR =5.8; p value = 0.046), TLG > 26.4g (HR =7.1; p value = 0.040) and ASP >19.8% (HR =15.6; p<0.0002) adversly influenced PFS. Cox multivariate analysis revealed lymph node metastasis (HR=19.4; P = 0.008) followed by ASP >19.8 (HR=17.3; P = 0.028.), and negative hormonal receptor status ((HR=14.2; P = 0.003) to be strong independent predictors of PFS. Conclusions: A pre-therapeutic tumor ASP of >19.4%, could identify breast IDC patients with reduced PFS. Tumor ASP fared better as an indicator of PFS compared to many clinico-pathological and other FGD PET/CT parameters and hence useful for prognostic stratification. Citation Format: Dr Nitin Gupta. Prognostic value of tumor asphericity on initial staging 18F- FDG PET/CT in patients with breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr A014.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".