Impact on the long-term prognosis of FDG PET/CT in luminal-A and luminal-B breast cancer

Comparison of MRI vs. [18F]FDG PET/CT for Treatment Response Evaluation of Primary Breast Cancer after Neoadjuvant Chemotherapy: Literature Review and Future Perspectives

The purpose of this systematic review was to investigate the diagnostic accuracy of [18F]FDG PET/CT and breast MRI for primary breast cancer (BC) response assessment after neoadjuvant chemotherapy (NAC) and to evaluate future perspectives in this setting. We performed a critical review using three bibliographic databases (i.e., PubMed, Scopus, and Web of Science) for articles published up to the 6 June 2023, starting from 2012. The Quality Assessment of Diagnosis Accuracy Study (QUADAS-2) tool was adopted to evaluate the risk of bias. A total of 76 studies were identified and screened, while 14 articles were included in our systematic review after a full-text assessment. The total number of patients included was 842. Eight out of fourteen studies (57.1%) were prospective, while all except one study were conducted in a single center. In the majority of the included studies (71.4%), 3.0 Tesla (T) MRI scans were adopted. Three out of fourteen studies (21.4%) used both 1.5 and 3.0 T MRI and only two used 1.5 T. [18F]FDG was the radiotracer used in every study included. All patients accepted surgical treatment after NAC and each study used pathological complete response (pCR) as the reference standard. Some of the studies have demonstrated the superiority of [18F]FDG PET/CT, while others proved that MRI was superior to PET/CT. Recent studies indicate that PET/CT has a better specificity, while MRI has a superior sensitivity for assessing pCR in BC patients after NAC. The complementary value of the combined use of these modalities represents probably the most important tool to improve diagnostic performance in this setting. Overall, larger prospective studies, possibly randomized, are needed, hopefully evaluating PET/MR and allowing for new tools, such as radiomic parameters, to find a proper place in the setting of BC patients undergoing NAC.

18F-FDG PET-Derived Volume-Based Parameters to Predict Disease-Free Survival in Patients with Grade III Breast Cancer of Different Molecular Subtypes Candidates to Neoadjuvant Chemotherapy

We investigated whether baseline [¹⁸F] Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)-derived semiquantitative parameters could predict disease-free survival (DFS) in patients with grade III breast cancer (BC) of different molecular subtypes candidate to neoadjuvant chemotherapy (NAC). For each ¹⁸F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used to determine the capability to predict DFS and find the optimal threshold for each parameter. Ninety-five grade III breast cancer patients with different molecular types were retrieved from the databases of the University Hospital of Padua and the University Hospital of Ferrara (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In luminal B patients, WB_MTV (AUC: 0.75; best cut-off: WB_MTV > 195.33; SS: 55.56%, SP: 100%; p = 0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG > 1066.21; SS: 55.56%, SP: 100%; p = 0.05) were the best predictors of DFS. In luminal B-HER2 patients, WB_SUVmax was the only predictor of DFS (AUC: 0.857; best cut-off: WB_SUVmax > 13.12; SS: 100%; SP: 71.43%; p < 0.001). No parameter significantly affected the prediction of DFS in patients with grade III triple-negative BC. Volume-based parameters, extracted from baseline ¹⁸F-FDG PET, seem promising in predicting recurrence in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC.

Classifying Breast Cancer Metastasis Based on Imaging of Tumor Primary and Tumor Biology

The molecular classification of breast cancer has allowed for a better understanding of both prognosis and treatment of breast cancer. Imaging of the different molecular subtypes has revealed that biologically different tumors often exhibit typical features in mammography, ultrasound, and MRI. Here, we introduce the molecular classification of breast cancer and review the typical imaging features of each subtype, examining the predictive value of imaging with respect to distant metastases.

Is CT or FDG-PET more useful for evaluation of the treatment response in metastatic HER2-positive breast cancer? a case report and literature review

Response evaluation criteria in solid tumors version 1.1 (RECIST ver1.1) has been widely adopted to evaluate treatment efficacy in solid tumors, including breast cancer (BC), in clinical trials and clinical practice. RECIST is based mainly on computed tomography (CT) images, and the role of fluorodeoxyglucose-positron emission tomography (FDG-PET) is limited. However, because the rate of tumor shrinkage on CT does not necessarily reflect the potential remaining tumor cells, there may be a discrepancy between the treatment response and prognosis in some cases. Here we report a case of metastatic human epidermal growth factor receptor 2 (HER2)-positive BC where FDG-PET was preferable to CT for evaluation of the treatment response. A 40-year-old woman became aware of a lump in her right breast in September 201X. She was pregnant and underwent further examinations, including a biopsy, in November. The diagnosis was HER2-positive BC (cT2N2bM1, stage IV). Trastuzumab plus pertuzumab plus docetaxel (TPD) therapy was initiated in December 201X. CT performed in February 201X+1 showed cystic changes in the metastatic lesions in the liver, and the treatment response was stable disease (SD) according to RECIST. However, FDG-PET in March 201X+1 did not detect abnormal uptake of FDG in the hepatic lesions. The disease remained stable thereafter. Thus, tumor shrinkage may not be apparent in situations where the response to treatment results in rapid changes in blood flow within the tumor, which is associated with cystic changes. When patients with hypervascular liver metastases receive treatment with highly effective regimens, the target lesion may show cystic changes rather than shrinkage, as observed in the present case. Therefore, FDG-PET is sometimes superior to CT in judging a tumor response.

The Value of Semiquantitative Parameters Derived from 18F-FDG PET/CT for Predicting Response to Neoadjuvant Chemotherapy in a Cohort of Patients with Different Molecular Subtypes of Breast Cancer

Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is a strong prognostic factor in breast cancer (BC). The aim of this study was to investigate whether semiquantitative parameters derived from baseline [¹⁸F]Fluorodeoxyglucose ([¹⁸F]FDG) positron emission computed tomography/computed tomography (PET/CT) could predict pCR after NAC and survival outcomes in patients affected by different molecular subtypes of BC. We retrospectively retrieved patients from the databases of two Italian hospitals (Centre A: University Hospital of Ferrara; Centre B: University of Padua) meeting the following inclusion criteria: (1) diagnosis of BC; (2) history of NAC; (3) baseline [¹⁸F]FDG PET/CT performed before the first cycle of NAC; (4) available follow-up data (response after NAC and survival information). For each [¹⁸F]FDG PET/CT scan, semiquantitative parameters (SUVmax, SUVmean, MTV and TLG) related to the primary tumor (B), to the reference lesion for both axillary (N) and distant lymph node (DN), and to the whole-body burden of disease (WB) were evaluated. Patients enrolled were 133: 34 from centre A and 99 from centre B. Patients' molecular subtypes were: 9 luminal A, 49 luminal B, 33 luminal B + HER-2, 10 HER-2 enriched, and 32 triple negative (TNBC). Luminal A and HER-2 enriched BC patients were excluded from the analysis due to the small sample size. pCR after NAC was achieved in 47 patients (41.2%). [¹⁸F]FDG PET/CT detected the primary tumor in 98.3% of patients and lymph node metastases were more frequently detected in Luminal B subgroup. Among Luminal B patients, median SUVmean_B values were significantly higher (p = 0.027) in responders (7.06 ± 5.9) vs. non-responders (4.4 ± 2.1) to NAC. Luminal B + HER-2 non-responders showed a statistically significantly higher median MTV_B (7.3 ± 4.2 cm³ vs. 3.5 ± 2.5 cm³; p = 0.003) and TLG_B (36.5 ± 24.9 vs. 18.9 ± 17.7; p = 0.025) than responders at baseline [¹⁸F]FDG PET/CT. None of the semiquantitative parameters predicted pCR after NAC in TNBC patients. However, among TNBC patients who achieved pCR after NAC, 4 volumetric parameters (MTV_B, TLG_B, MTV_WB and TLG_WB) were significantly higher in patients dead at follow-up. If confirmed in further studies, these results could open up a widespread use of [¹⁸F]FDG PET/CT as a baseline predictor of response to NAC in luminal B and luminal B + HER-2 patients and as a prognostic tool in TNBC.

PET-Derived Radiomics and Artificial Intelligence in Breast Cancer: A Systematic Review

Breast cancer (BC) is a heterogeneous malignancy that still represents the second cause of cancer-related death among women worldwide. Due to the heterogeneity of BC, the correct identification of valuable biomarkers able to predict tumor biology and the best treatment approaches are still far from clear. Although molecular imaging with positron emission tomography/computed tomography (PET/CT) has improved the characterization of BC, these methods are not free from drawbacks. In recent years, radiomics and artificial intelligence (AI) have been playing an important role in the detection of several features normally unseen by the human eye in medical images. The present review provides a summary of the current status of radiomics and AI in different clinical settings of BC. A systematic search of PubMed, Web of Science and Scopus was conducted, including all articles published in English that explored radiomics and AI analyses of PET/CT images in BC. Several studies have demonstrated the potential role of such new features for the staging and prognosis as well as the assessment of biological characteristics. Radiomics and AI features appear to be promising in different clinical settings of BC, although larger prospective trials are needed to confirm and to standardize this evidence.