Prognostic utility of FDG PET/CT and bone scintigraphy in breast cancer patients with bone-only metastasis

18 F FDG PET/CT versus 99m Tc MDP Bone scintigraphy in imaging of metastatic osseous disease in breast cancer patients; Solving the discrepancies in light of serum markers

AIM

To assess the performance of 18 F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) versus 99m Tc MDP bone scan in assessment of metastatic osseous disease in breast cancer patients in relation to serum markers.

MATERIAL AND METHODS

We reviewed PET/CT studies and bone scans for 37 patients (mean age of 55.38 ± 13.08 years) with metastatic breast cancer to bone. To assess metastatic osseous burden, we used semiquantitative scores derived from PET/CT (PMS) and bone scans (BMS). We used McNemar test to compare lesion detection between both modalities and receiver operator characteristic analysis to define the cutoff value of serum CA 15-3 that best predicts additional value for PET/CT over bone scan.

RESULTS

In 13 patients (35.1%), more lesions or higher-intensity lesions were detected on PET/CT, while only 4 patients (10.8%) had more prominent lesions on bone scans ( P = 0.049). Additional lesions seen on PET/CT are predominantly osteolytic or medullary (early phase). Most lesions with higher uptake on bone scans appear sclerotic (late phase). CA 15-3 was positively correlated to PMS ( r = 0.386; P = 0.018) but not to BMS ( r = -0.027; P = 0.874). However, serum alkaline phosphatase was positively correlated to both PMS ( r = 0.389; P = 0.017) and BMS ( r = 0.363; P = 0.027). CA 15-3 value of >47 U/ml best predicted additional findings on PET/CT compared to bone scans (area under the curve = 0.708; P = 0.0261).

CONCLUSION

FDG PET/CT detects metastatic osseous lesions during an earlier phase. A higher CA 15-3 predicts a higher metastatic burden on PET/CT but not on bone scan. Bone scans are less specific, likely by missing early lesions and detecting persistent uptake in healing sclerotic lesions.

Joint EANM-SNMMI guideline on the role of 2-[18F]FDG PET/CT in no special type breast cancer : (endorsed by the ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA)

INTRODUCTION

There is much literature about the role of 2-[18F]FDG PET/CT in patients with breast cancer (BC). However, there exists no international guideline with involvement of the nuclear medicine societies about this subject.

PURPOSE

To provide an organized, international, state-of-the-art, and multidisciplinary guideline, led by experts of two nuclear medicine societies (EANM and SNMMI) and representation of important societies in the field of BC (ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA).

METHODS

Literature review and expert discussion were performed with the aim of collecting updated information regarding the role of 2-[18F]FDG PET/CT in patients with no special type (NST) BC and summarizing its indications according to scientific evidence. Recommendations were scored according to the National Institute for Health and Care Excellence (NICE) criteria.

RESULTS

Quantitative PET features (SUV, MTV, TLG) are valuable prognostic parameters. In baseline staging, 2-[18F]FDG PET/CT plays a role from stage IIB through stage IV. When assessing response to therapy, 2-[18F]FDG PET/CT should be performed on certified scanners, and reported either according to PERCIST, EORTC PET, or EANM immunotherapy response criteria, as appropriate. 2-[18F]FDG PET/CT may be useful to assess early metabolic response, particularly in non-metastatic triple-negative and HER2+ tumours. 2-[18F]FDG PET/CT is useful to detect the site and extent of recurrence when conventional imaging methods are equivocal and when there is clinical and/or laboratorial suspicion of relapse. Recent developments are promising.

CONCLUSION

2-[18F]FDG PET/CT is extremely useful in BC management, as supported by extensive evidence of its utility compared to other imaging modalities in several clinical scenarios.

SPECT/CT, PET/CT, and PET/MRI for Response Assessment of Bone Metastases

Recent developments in hybrid SPECT/CT systems and the use of cadmium-zinc-telluride (CZT) detectors have improved the diagnostic accuracy of bone scintigraphy. These advancements have paved the way for novel quantitative approaches to accurate and reproducible treatment monitoring of bone metastases. PET/CT imaging using [18F]F-FDG and [18F]F-NaF have shown promising clinical utility in bone metastases assessment and monitoring response to therapy and prediction of treatment response in a broad range of malignancies. Additionally, specific tumor-targeting tracers like [99mTc]Tc-PSMA, [68Ga]Ga-PSMA, or [11C]C- or [18F]F-Choline revealed high diagnostic performance for early assessment and prognostication of bone metastases, particularly in prostate cancer. PET/MRI appears highly accurate imaging modality, but has associated limitations notably, limited availability, more complex logistics and high installation costs. Advances in artificial intelligence (Al) seem to improve the accuracy of imaging modalities and provide an assistant role in the evaluation of treatment response of bone metastases.

Development and Validation of Prognostic Nomogram for Elderly Breast Cancer: A Large-Cohort Retrospective Study

Purpose

Our research aims to study the bone metastatic patterns and prognostic outcomes in elderly breast cancer (BC) and to develop elder-specific nomograms.

Methods

We downloaded the data of BC patients between 2010 and 2016 from the Surveillance, Epidemiology, and End Results database. The differences in clinical features and prognosis between young (age < 65) and elderly (age ≥ 65) BC patients were compared. The univariate and multivariate Cox analyses were used to determine the overall survival (OS)- and cancer-specific survival (CSS)-related variables and establish two nomograms of BC patients with bone metastasis (BCBM). The receiver operating characteristic (ROC) curve with area under the curve (AUC), calibration curve, decision curve analysis (DCA), and Kaplan–Meier survival curve were selected to evaluate nomograms.

Results

A total of 230,177 BC patients were enrolled in our research, including 142,025 young and 88,152 elderly patients. The prognosis of elderly BCBM patients was significantly worse than young patients. Age, race, breast subtype, tumor size, tumor grade, brain metastasis, liver metastasis, surgery, and chemotherapy were independent prognostic variables for elderly BCBM patients, including OS and CSS. The AUC values at 12, 18, and 24 months were 0.750, 0.751, and 0.739 for OS nomogram and 0.759, 0.762, and 0.752 for CSS nomogram in the training cohort, which were higher than the AUC values of all single independent prognostic variables. The survival curve showed a distinct prognosis between low-, median- and high-risk groups (p < 0.001). Finally, calibration curves and DCA indicated that both nomograms have favorable performance.

Conclusion

Elderly and young patients presented with different bone metastatic frequencies, clinical features, and prognostic outcomes. Two elder-specific nomograms incorporating nine clinical variables were established and validated to be a valuable predictor for elderly BCBM patients.

Diagnosis of bone metastases in breast cancer: Lesion-based sensitivity of dual-time-point FDG-PET/CT compared to low-dose CT and bone scintigraphy

We compared lesion-based sensitivity of dual-time-point FDG-PET/CT, bone scintigraphy (BS), and low-dose CT (LDCT) for detection of various types of bone metastases in patients with metastatic breast cancer. Prospectively, we included 18 patients with recurrent breast cancer who underwent dual-time-point FDG-PET/CT with LDCT and BS within a median time interval of three days. A total of 488 bone lesions were detected on any of the modalities and were categorized by the LDCT into osteolytic, osteosclerotic, mixed morphologic, and CT-negative lesions. Lesion-based sensitivity was 98.2% (95.4-99.3) and 98.8% (96.8-99.5) for early and delayed FDG-PET/CT, respectively, compared with 79.9% (51.1-93.8) for LDCT, 76.0% (36.3-94.6) for BS, and 98.6% (95.4-99.6) for the combined BS+LDCT. BS detected only 51.2% of osteolytic lesions which was significantly lower than other metastatic types. SUVs were significantly higher for all lesion types on delayed scans than on early scans (P<0.0001). Osteolytic and mixed-type lesions had higher SUVs than osteosclerotic and CT-negative metastases at both time-points. FDG-PET/CT had significantly higher lesion-based sensitivity than LDCT and BS, while a combination of the two yielded sensitivity comparable to that of FDG-PET/CT. Therefore, FDG-PET/CT could be considered as a sensitive one-stop-shop in case of clinical suspicion of bone metastases in breast cancer patients.

Prospective comparison of the diagnostic accuracy of 18F-FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients

OBJECTIVES

To compare the diagnostic performance of [18F]FDG PET/MRI, MRI, CT, and bone scintigraphy for the detection of bone metastases in the initial staging of primary breast cancer patients.

MATERIAL AND METHODS

A cohort of 154 therapy-naive patients with newly diagnosed, histopathologically proven breast cancer was enrolled in this study prospectively. All patients underwent a whole-body [18F]FDG PET/MRI, computed tomography (CT) scan, and a bone scintigraphy prior to therapy. All datasets were evaluated regarding the presence of bone metastases. McNemar χ2 test was performed to compare sensitivity and specificity between the modalities.

RESULTS

Forty-one bone metastases were present in 7/154 patients (4.5%). Both [18F]FDG PET/MRI and MRI alone were able to detect all of the patients with histopathologically proven bone metastases (sensitivity 100%; specificity 100%) and did not miss any of the 41 malignant lesions (sensitivity 100%). CT detected 5/7 patients (sensitivity 71.4%; specificity 98.6%) and 23/41 lesions (sensitivity 56.1%). Bone scintigraphy detected only 2/7 patients (sensitivity 28.6%) and 15/41 lesions (sensitivity 36.6%). Furthermore, CT and scintigraphy led to false-positive findings of bone metastases in 2 patients and in 1 patient, respectively. The sensitivity of PET/MRI and MRI alone was significantly better compared with CT (p < 0.01, difference 43.9%) and bone scintigraphy (p < 0.01, difference 63.4%).

CONCLUSION

[18F]FDG PET/MRI and MRI are significantly better than CT or bone scintigraphy for the detection of bone metastases in patients with newly diagnosed breast cancer. Both CT and bone scintigraphy show a substantially limited sensitivity in detection of bone metastases.

KEY POINTS

• [18F]FDG PET/MRI and MRI alone are significantly superior to CT and bone scintigraphy for the detection of bone metastases in patients with newly diagnosed breast cancer. • Radiation-free whole-body MRI might serve as modality of choice in detection of bone metastases in breast cancer patients.

Prognostic Factors in Hormone Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative (HR+/HER2-) Advanced Breast Cancer: A Systematic Literature Review

PURPOSE

Advanced breast cancer is a heterogeneous disease with several well-defined subtypes, among which, hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) is most prevalent. Determination of HR and HER2 status influences prognosis and, thus, disease management. Although literature on these prognostic factors exist, especially in the early breast cancer setting, it remains unclear to what extent these factors can guide clinical decision-making in the advanced disease setting. Therefore, we sought to identify the strength and consistency of evidence for prognostic factors in patients with HR+/HER2- advanced breast cancer.

METHODS

A systematic literature review (SLR) of the major electronic databases was conducted in November 2018 for primary research studies published since 2010. Endpoints of interest were tumor response, progression-free survival (PFS), overall survival (OS), and breast cancer-specific survival (BCSS).

RESULTS

Seventy-nine studies were included wherein all patients were diagnosed with advanced breast cancer and ≥50% of the population were HR+/HER2-. OS was the most commonly assessed endpoint (n=67) followed by PFS (n=33), BCSS (n=5) and tumor response (n=3). The prognostic factors with strongest evidence of association with worse OS were negative progesterone receptor status, higher tumor grade, higher circulating tumor cell (CTC) count and higher Ki67 level, number of metastatic sites (eg multiple vs single) and sites of metastases (eg presence of liver metastases vs absence), shorter time to recurrence or progression to advanced breast cancer, poor performance status, prior therapy attributes in the early or metastatic setting (type of therapy, treatment line, response of prior therapy), and race (black vs white). The prognostic factors that had strongest evidence of association with PFS included CTC count, number and sites of metastases, and absence of prior therapy or higher lines of therapy in the early or metastatic setting. The directionality of association was consistent for all prognostic factors except between lymph node and OS, and de novo metastatic breast cancer and PFS.

CONCLUSION

Multiple disease, treatment, and patient-related prognostic factors impact survival, particularly OS, in patients with HR+/HER2- advanced breast cancer. Treatment outcomes can vary considerably due to these factors. Understanding poorer prognostic factors for patients can result in improved clinical decision-making.

Prognostic value of metabolic tumor volume and total lesion glycolysis in breast cancer: a meta-analysis

OBJECTIVES

PET using F-fluorodeoxyglucose (FDG) has proven to be valuable in staging and monitoring of treatment response in breast cancer. We aimed to assess the prognostic value of metabolic tumor volume (MTV) and total lesion glycolysis (TLG) in patients with breast cancer.

METHODS

A systematic search of MEDLINE and EMBASE was performed using the keywords of breast cancer, PET, and volume. Inclusion criteria were F-FDG PET used as an initial imaging tool; studies limited to patients with breast cancer who had not undergone any treatment before PET scans; and studies reporting survival data. Event-free survival (EFS) and overall survival (OS) were considered markers of outcome.

RESULTS

Nine studies comprising 975 patients were included in this study. The pooled hazard ratio (HR) for adverse events was 33.73 (P < 0.00001; I = 0%) with MTV from primary tumor and 2.89 (P < 0.00001; I = 45%) with TLG from primary tumor, meaning that primary tumors with high volumetric parameters were associated with progression or recurrence. However, the combined HRs for EFS of MTV, and TLG, and those for OS of MTV from whole-body tumor were NS. The pooled HR for OS of TLG from whole-body tumor was 2.95 (P = 0.18; I = 71%).

CONCLUSION

Volumetric parameters from F-FDG PET are significant prognostic factors for outcome in patients with breast cancer. Patients with a high MTV or TLG from primary tumor have a higher risk of adverse events. Patients with a high TLG from whole-body tumor have a higher risk of deaths.

A Deep-Learning Approach for Diagnosis of Metastatic Breast Cancer in Bones from Whole-Body Scans

(1) Background: Bone metastasis is one of the most frequent diseases in breast, lung and prostate cancer; bone scintigraphy is the primary imaging method of screening that offers the highest sensitivity (95%) regarding metastases. To address the considerable problem of bone metastasis diagnosis, focused on breast cancer patients, artificial intelligence methods devoted to deep-learning algorithms for medical image analysis are investigated in this research work; (2) Methods: Deep learning is a powerful algorithm for automatic classification and diagnosis of medical images whereas its implementation is achieved by the use of convolutional neural networks (CNNs). The purpose of this study is to build a robust CNN model that will be able to classify images of whole-body scans in patients suffering from breast cancer, depending on whether or not they are infected by metastasis of breast cancer; (3) Results: A robust CNN architecture is selected based on CNN exploration performance for bone metastasis diagnosis using whole-body scan images, achieving a high classification accuracy of 92.50%. The best-performing CNN method is compared with other popular and well-known CNN architectures for medical imaging like ResNet50, VGG16, MobileNet, and DenseNet, reported in the literature, providing superior classification accuracy; and (4) Conclusions: Prediction results show the efficacy of the proposed deep learning approach in bone metastasis diagnosis for breast cancer patients in nuclear medicine.