Prediction of Axillary Lymph Node Metastasis Status in Breast Cancer Based on PET/CT Radiomics

NCT05826197 — Unknown, 100 participants, First Affiliated Hospital Xi'an Jiaotong University

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A Study on the Construction of a Comprehensive Predictive Model for Axillary Lymph Node Metastasis in Breast Cancer

RegistryNCT05826197
StatusUnknown
Study typeObservational
Enrollment100 (Estimated)
SponsorFirst Affiliated Hospital Xi'an Jiaotong University (Other)
ConditionsBreast Neoplasms
InterventionsRadiomics (Other)
Datesstart 2023-05-10 (estimated), primary completion 2024-05-01 (estimated), completion 2024-12-01 (estimated), first posted 2023-04-24, last updated 2023-05-09

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-Summary

Patients with suspected breast cancer undergoing PET/CT at our hospital. The PET/CT center's chief physician and senior attending physician reviewed the films together and disagreement, if any, was resolved by consensus. The lesion was visually identified. A 3D region of interest(ROI) of the lesion was automatically outlined using the 40% threshold method, and PET metabolic parameters were measured . Breast lesions with radionuclide concentrations greater than those in normal breast tissue are considered to be breast cancer lesions, while lymph nodes with radionuclide concentrations greater than those in muscle tissue are considered to be metastatic lymph nodes.

Image segmentation: Image segmentation was performed using ITK-SNAP software (4) (version 3.6.0, http://www.itksnap.org/), Brush Style: circular, Brush Size: 10, Brush Options: 3D. The entire tumor volume was outlined on the PET image as ROI for segmentation.

An open source Python package (PyRadiomics version 3.0.1(5)) was used to extract the radiomics features from the ROI.

Univariate and multivariate binary logistic regressions were used to construct model for predicting lymph node metastasis in breast cancer.

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+Arms and interventions

ArmTypeInterventionsDescription
Axillary lymph node metastasisOther: Radiomics
No axillary lymph node metastasis
  • Radiomics (Other): PET Radiomics

+Outcome measures

Primary outcomes

  • Radiomics score [1 day During the inspection]: Higher radiomics scores indicate better model prediction performance

+Eligibility

Sex: Female, ages: 18 Years to 80 Years

Inclusion Criteria:

* 1\) 18F-FDG PET/CT for breast occupancy; 2) adult female patients with pathologically confirmed breast cancer (age ≥18 years); 3) no history of surgery, radiotherapy, or chemotherapy before 18F-FDG PET/CT; and 4) interval between 18F-FDG PET/CT and puncture/surgery ≤2 weeks.

Exclusion Criteria:

* 1\) multifocal, bilateral, or occult breast cancer; 2) incomplete clinical or pathological data; 3) poor PET/CT image quality, when metabolic tumor volume(MTV) cannot be automatically segmented; and 4) concomitant malignant tumors.

+Publications

  • Results publication: Li Y, Han D, Shen C. Prediction of the axillary lymph-node metastatic burden of breast cancer by 18F-FDG PET/CT-based radiomics. BMC Cancer. 2024 Jun 7;24(1):704. doi: 10.1186/s12885-024-12476-3. PMID 38849770
  • Results publication: Li Y, Han D, Shen C, Duan X. Construction of a comprehensive predictive model for axillary lymph node metastasis in breast cancer: a retrospective study. BMC Cancer. 2023 Oct 24;23(1):1028. doi: 10.1186/s12885-023-11498-7. PMID 37875818