Assessing 18F-FDG Uptake in the Sentinel Lymph Node in Breast Cancer

Biology of Cancer and PET Imaging: Pictorial Review

Development and spread of cancer is a multi-step and complex process which involves number of alterations, interactions and molecular networks. PET imaging is closely related with biology of cancer as it detects the cancer based on biological and pathological changes in tumor cells and tumor microenvironment. In this review article, biology of development and spread of cancer and role of PET imaging in Oncology was summarized and supported with various PET images demonstrating cancer spread patterns.

Prediction of Metastasis in the Axillary Lymph Nodes of Patients With Breast Cancer: A Radiomics Method Based on Contrast-Enhanced Computed Tomography

Background

The use of traditional techniques to evaluate breast cancer is restricted by the subjective nature of assessment, variation across radiologists, and limited data. Radiomics may predict axillary lymph node metastasis (ALNM) of breast cancer more accurately.

Purpose

The aim was to evaluate the diagnostic performance of a radiomics model based on ALNs themselves that used contrast-enhanced computed tomography (CECT) to detect ALNM of breast cancer.

Methods

We retrospectively enrolled 402 patients with breast cancer confirmed by pathology from January 2016 to October 2019. Three hundred and ninety-six features were extracted for all patients from axial CECT images of 825 ALNs using Artificial Intelligent Kit software (GE Medical Systems, Version V3.1.0.R). Next, the radiomics model was trained, validated, and tested for predicting ALNM in breast cancer by using a support vector machine algorithm. Finally, the performance of the radiomics model was evaluated in terms of its classification accuracy and the value of the area under the curve (AUC).

Results

The radiomics model yielded the best classification accuracy of 89.1% and the highest AUC of 0.92 (95% CI: 0.91-0.93, p=0.002) for discriminating ALNM in breast cancer in the validation cohorts. In the testing cohorts, the model also demonstrated better performance, with an accuracy of 88.5% and an AUC of 0.94 (95% CI: 0.93-0.95, p=0.005) for predicting ALNM in breast cancer.

Conclusion

The radiomics model based on CECT images can be used to predict ALNM in breast cancer and has significant potential in clinical noninvasive diagnosis and in the prediction of breast cancer metastasis.

Combined 68Ga-NOTA-Evans Blue Lymphoscintigraphy and 68Ga-NOTA-RM26 PET/CT Evaluation of Sentinel Lymph Node Metastasis in Breast Cancer Patients

In this study, we applied a new strategy to identify sentinel lymph node (SLN) metastasis by combining ⁶⁸Ga-NOTA-Evans Blue (⁶⁸Ga-NEB) for SLN mapping and ⁶⁸Ga-NOTA-RM26 for LN metastasis detection in breast cancer patients. A total of 24 female patients with breast cancer diagnosed by core biopsy or suspected by mammography or ultrasonography were recruited and provided informed consent. All patients underwent ⁶⁸Ga-NEB and ⁶⁸Ga-NOTA-RM26 PET/CT imaging. Visual analysis of ⁶⁸Ga-NEB PET/CT images was used to determine SLNs, and then compared with the ⁶⁸Ga-NOTA-RM26 results and histopathological findings. SLNs were visualized in 24 of 24 patients (100.0%) within 4.0-10.0 (5.6 ± 1.4) min. All patients were pathologically diagnosed with breast cancer, and 12 patients had ipsilateral lymph node metastasis. By combining ⁶⁸Ga-NEB and ⁶⁸Ga-NOTA-RM26 images, 7/12 (58.3%) patients showed mild to intense uptake of ⁶⁸Ga-NOTA-RM26 in SLNs, 1/12 patient (8.3%) had moderate uptake of ⁶⁸Ga-NOTA-RM26 in the non-SLNs rather than SLN, indicating possible bypass lymphatic drainage, partially accounting for the false negatives in SLN biopsy during surgery. No false positives were found. The SUV_max of ⁶⁸Ga-NOTA-RM26 activity in metastatic SLNs was significantly higher than that in non-metastatic SLNs (2.2 ± 2.3 vs 0.7 ± 0.1, P = 0.047). This study manifests the value of combination of ⁶⁸Ga-NEB and ⁶⁸Ga-NOTA-RM26 dual tracer PET/CT in preoperative evaluation of SLN metastasis in breast cancer patients, especially in those patients with lymphatic obstruction and bypass drainage. In general, positive ⁶⁸Ga-NOTA-RM26 uptake in either SLN or other lymph nodes can apply lymph node dissection rather than intraoperative SLN biopsy.

Is there a difference in FDG PET findings of invasive ductal carcinoma of the breast with and without coexisting DCIS?

OBJECTIVES

Studies have reported that invasive ductal carcinoma (IDC) with coexisting ductal carcinoma in situ (DCIS) show lower metastatic potential and recurrence and better overall survival than pure IDC. In this study, we assessed F-18 fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) images of patients with newly diagnosed IDC to determine if there is any difference in PET findings in IDC-DCIS and pure IDC cases.

METHODS

FDG PET/CT images of patients with newly diagnosed IDC of the breast who subsequently underwent breast surgery and had histopathology result in our records were further evaluated. Tumor grade, pathological staging, and presence of DCIS were noted from the histopathology results. Standardized uptake value (SUV) of the primary tumor (SUVmax and SULmax), other hypermetabolic foci in the breast, and ipsilateral normal breast were measured. Presence of axillary and distant metastases was noted.

RESULTS

Fifty seven (57) patients with IDC were included. Coexisting DCIS was present in 44 (IDC-DCIS) and not present in 13 (pure IDC) cases. Per histopathology, the primary tumor was unifocal in 33 IDC-DCIS (75%) and 12 pure IDC (92.3%) cases, and multifocal in 11 IDC-DCIS cases (25%), and 1 pure IDC case (7.7%). FDG uptake was multifocal in 20 IDC-DCIS cases (45.5%) and 1 pure IDC case (7.7%), and unifocal in 24 IDC-DCIS (54.5%), and 12 pure IDC (92.3%) cases. There was no significant difference in patient age, size of the primary tumor, SUVmax and SULmax of the primary tumor and SUVmax of the normal breast in IDC-DCIS and pure IDC cases (p>0.05). Pathology showed axillary metastasis in all 13 pure IDC (100%), and 27 IDC-DCIS (61.4%) cases. PET showed axillary uptake in 25 IDC-DCIS (56.8%), and 8 pure IDC (61.5%) cases, and abnormal/questionable distant uptake in 12 IDC-DCIS cases and 1 pure IDC case.

CONCLUSION

In our preliminary findings, multifocal breast FDG uptake and multifocal tumor appear to be more common in IDC-DCIS than pure IDC. There is no significant difference in SUV and size of the primary tumor in IDC-DCIS and pure IDC cases. Axillary metastases appear to be more common in pure IDC than IDC-DCIS cases.