High serum levels of leucine-rich α-2 glycoprotein 1 (LRG-1) are associated with poor survival in patients with early breast cancer.

BACKGROUND: Leucine-rich α-2 glycoprotein 1 (LRG-1) is a secreted glycoprotein that is mainly produced in the liver. Elevated levels of LRG-1 are found in a multitude of pathological conditions including eye diseases, diabetes, infections, autoimmune diseases, and cancer. In patients with early breast cancer (BC), high intratumoral LRG-1 protein expression levels are associated with reduced survival. In this study, we assessed serum levels of LRG-1 in patients with early BC and investigated its correlation with the presence of disseminated tumor cells (DTCs) in the bone marrow and survival outcomes. METHODS: Serum LRG-1 levels of 509 BC patients were determined using ELISA and DTCs were assessed by immunocytochemistry using the pan-cytokeratin antibody A45-B/B3. We stratified LRG-1 levels according to selected clinical parameters. Using the log-rank (Mantel-Cox) test and multivariate Cox regression analysis, Kaplan-Meier survival curves and prognostic relevance were assessed. RESULTS: Mean serum levels of LRG-1 were 29.70 ± 8.67 µg/ml. Age was positively correlated with LRG-1 expression (r = 0.19; p < 0.0001) and significantly higher LRG-1 levels were found in patients over 60 years compared to younger ones (30.49 ± 8.63 µg/ml vs. 28.85 ± 8.63 µg/ml; p = 0.011) and in postmenopausal patients compared to premenopausal patients (30.15 ± 8.34 µg/ml vs. 26.936.94 µg/ml; p = 0.002). Patients with no DTCs showed significantly elevated LRG-1 levels compared to the DTC-positive group (30.51 ± 8.69 µg/ml vs. 28.51 ± 8.54 µg/ml; p = 0.004). Overall and BC-specific survival was significantly lower in patients with high serum LRG-1 levels (above a cut-off of 33.63 µg/ml) compared to patients with lower LRG-1 levels during a mean follow-up of 8.5 years (24.8% vs. 11.1% BC-specific death; p = 0.0003; odds ratio 2.63, 95%CI: 1.56-4.36). Multivariate analyses revealed that LRG-1 is an independent prognostic marker for BC-specific survival (p = 0.001; hazard ratio 2.61). CONCLUSIONS: This study highlights the potential of LRG-1 as an independent prognostic biomarker in patients with early BC.

Prediction of therapy response of breast cancer patients with machine learning based on clinical data and imaging data derived from breast [18F]FDG-PET/MRI.

PURPOSE: To evaluate if a machine learning prediction model based on clinical and easily assessable imaging features derived from baseline breast [18F]FDG-PET/MRI staging can predict pathologic complete response (pCR) in patients with newly diagnosed breast cancer prior to neoadjuvant system therapy (NAST). METHODS: Altogether 143 women with newly diagnosed breast cancer (54 ± 12 years) were retrospectively enrolled. All women underwent a breast [18F]FDG-PET/MRI, a histopathological workup of their breast cancer lesions and evaluation of clinical data. Fifty-six features derived from positron emission tomography (PET), magnetic resonance imaging (MRI), sociodemographic / anthropometric, histopathologic as well as clinical data were generated and used as input for an extreme Gradient Boosting model (XGBoost) to predict pCR. The model was evaluated in a five-fold nested-cross-validation incorporating independent hyper-parameter tuning within the inner loops to reduce the risk of overoptimistic estimations. Diagnostic model-performance was assessed by determining the area under the curve of the receiver operating characteristics curve (ROC-AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. Furthermore, feature importances of the XGBoost model were evaluated to assess which features contributed most to distinguish between pCR and non-pCR. RESULTS: Nested-cross-validation yielded a mean ROC-AUC of 80.4 ± 6.0% for prediction of pCR. Mean sensitivity, specificity, PPV, and NPV of 54.5 ± 21.3%, 83.6 ± 4.2%, 63.6 ± 8.5%, and 77.6 ± 8.1% could be achieved. Histopathological data were the most important features for classification of the XGBoost model followed by PET, MRI, and sociodemographic/anthropometric features. CONCLUSION: The evaluated multi-source XGBoost model shows promising results for reliably predicting pathological complete response in breast cancer patients prior to NAST. However, yielded performance is yet insufficient to be implemented in the clinical decision-making process.

Conventional Imaging, MRI and 18F-FDG PET/MRI for N and M Staging in Patients with Newly Diagnosed Breast Cancer.

Background: This study compares the diagnostic potential of conventional staging (computed tomography (CT), axillary sonography and bone scintigraphy), whole-body magnetic resonance imaging (MRI) and whole-body 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET/)MRI for N and M staging in newly diagnosed breast cancer. Methods: A total of 208 patients with newly diagnosed breast cancer were prospectively included in this study and underwent contrast-enhanced thoracoabdominal CT, bone scintigraphy and axillary sonography as well as contrast-enhanced whole-body 18F-FDG PET/MRI. The datasets were analyzed with respect to lesion localization and characterization. Histopathology and follow-up imaging served as the reference standard. A McNemar test was used to compare the diagnostic performance of conventional staging, MRI and 18F-FDG PET/MRI and a Wilcoxon test was used to compare differences in true positive findings for nodal staging. Results: Conventional staging determined the N stage with a sensitivity of 80.9%, a specificity of 99.2%, a PPV (positive predictive value) of 98.6% and a NPV (negative predictive value) of 87.4%. The corresponding results for MRI were 79.6%, 100%, 100% and 87.0%, and were 86.5%, 94.1%, 91.7% and 90.3% for 18F-FDG PET/MRI. 18F-FDG PET/MRI was significantly more sensitive in determining malignant lymph nodes than conventional imaging and MRI (p < 0.0001 and p = 0.0005). Furthermore, 18F-FDG PET/MRI accurately estimated the clinical lymph node stage in significantly more cases than conventional imaging and MRI (each p < 0.05). Sensitivity, specificity, PPV and NPV for the M stage in conventional staging were 83.3%, 98.5%, 76.9% and 98.9%, respectively. The corresponding results for both MRI and 18F-FDG PET/MRI were 100.0%, 98.5%, 80.0% and 100.0%. No significant differences between the imaging modalities were seen for the staging of distant metastases. Conclusions:18F-FDG PET/MRI detects lymph node metastases in significantly more patients and estimates clinical lymph node stage more accurately than conventional imaging and MRI. No significant differences were found between imaging modalities with respect to the detection of distant metastases.

Elevated sHLA-G plasma levels post chemotherapy combined with ILT-2 rs10416697C allele status of the sHLA-G-related receptor predict poorest disease outcome in early triple-negative breast cancer patients.

Introduction: Triple negative breast cancer (TNBC) shows an aggressive growing and spreading behavior and has limited treatment options, often leading to inferior disease outcome. Therefore, surrogate markers are urgently needed to identify patients at high risk of recurrence and more importantly, to identify additional therapeutic targets enabling further treatment options. Based on the key role of the non-classical human leukocyte antigen G (HLA-G) and its related receptor immunoglobulin-like transcript receptor-2 (ILT-2) in immune evasion mechanisms of tumors, members of this ligand-receptor axis appear to be promising tool for both, defining risk groups and potential therapeutic targets. Materials and methods: To follow this, sHLA-G levels before and after chemotherapy (CT), HLA-G 3' UTR haplotypes, and allele variations rs10416697 at the distal gene promoter region of ILT-2 were defined in healthy female controls and early TNBC patients. The results obtained were associated with clinical status, presence of circulating tumor cell (CTC) subtypes, and disease outcome of patients in terms of progression-free or overall survival. Results: sHLA-G plasma levels were increased in TNBC patients post-CT compared to levels of patients pre-CT or controls. High post-CT sHLA-G levels were associated with the development of distant metastases, the presence of ERCC1 or PIK3CA-CTC subtypes post-CT, and poorer disease outcome in uni- or multivariate analysis. HLA-G 3' UTR genotypes did not influence disease outcome but ILT-2 rs10416697C allele was associated with AURKA-positive CTC and with adverse disease outcome by uni- and multivariate analysis. The prognostic value of the combined risk factors (high sHLA-G levels post-CT and ILT-2 rs10416697C allele carrier status) was an even better independent indicator for disease outcome in TNBC than the lymph nodal status pre-CT. This combination allowed the identification of patients with high risk of early progression/death with positive nodal status pre-CT or with non-pathological complete therapy response. Conclusion: The results of this study highlight for the first time that the combination of high levels of sHLA-G post-CT with ILT-2 rs10416697C allele receptor status is a promising tool for the risk assessment of TNBC patients and support the concept to use HLA-G/ILT-2 ligand-receptor axis as therapeutic targets.

Towards a fast PET/MRI protocol for breast cancer imaging: maintaining diagnostic confidence while reducing PET and MRI acquisition times.

OBJECTIVES: To investigate the diagnostic feasibility of a shortened breast PET/MRI protocol in breast cancer patients. METHODS: Altogether 90 women with newly diagnosed T1tumor-staged (T1ts) and T2tumor-staged (T2ts) breast cancer were included in this retrospective study. All underwent a dedicated comprehensive breast [18F]FDG-PET/MRI. List-mode PET data were retrospectively reconstructed with 20, 15, 10, and 5 min for each patient to simulate the effect of reduced PET acquisition times. The SUVmax/mean of all malign breast lesions was measured. Furthermore, breast PET data reconstructions were analyzed regarding image quality, lesion detectability, signal-to-noise ratio (SNR), and image noise (IN). The simultaneously acquired comprehensive MRI protocol was then shortened by retrospectively removing sequences from the protocol. Differences in malignant breast lesion detectability between the original and the fast breast MRI protocol were evaluated lesion-based. The 20-min PET reconstructions and the original MRI protocol served as reference. RESULTS: In all PET reconstructions, 127 congruent breast lesions could be detected. Group comparison and T1ts vs. T2ts subgroup comparison revealed no significant difference of subjective image quality between 20, 15, 10, and 5 min acquisition times. SNR of qualitative image evaluation revealed no significant difference between different PET acquisition times. A slight but significant increase of IN with decreasing PET acquisition times could be detected. Lesion SUVmax group comparison between all PET acquisition times revealed no significant differences. Lesion-based evaluation revealed no significant difference in breast lesion detectability between original and fast breast MRI protocols. CONCLUSIONS: Breast [18F]FDG-PET/MRI protocols can be shortened from 20 to below 10 min without losing essential diagnostic information. KEY POINTS: • A highly accurate breast cancer evaluation is possible by the shortened breast [18F]FDG-PET/MRI examination protocol. • Significant time saving at breast [18F]FDG-PET/MRI protocol could increase patient satisfaction and patient throughput for breast cancer patients at PET/MRI.

Correlation between Imaging Markers Derived from PET/MRI and Invasive Acquired Biomarkers in Newly Diagnosed Breast Cancer.

PURPOSE: Evaluate the diagnostic potential of [18F]FDG-PET/MRI data compared with invasive acquired biomarkers in newly diagnosed early breast cancer (BC). METHODS: Altogether 169 women with newly diagnosed BC were included. All underwent a breast- and whole-body [18F]FDG-PET/MRI for initial staging. A tumor-adapted volume of interest was placed in the primaries and defined bone regions on each standard uptake value (SUV)/apparent diffusion coefficient (ADC) dataset. Immunohistochemical markers, molecular subtype, tumor grading, and disseminated tumor cells (DTCs) of each patient were assessed after ultrasound-guided biopsy of the primaries and bone marrow (BM) aspiration. Correlation analysis and group comparisons were assessed. RESULTS: A significant inverse correlation of estrogen-receptor (ER) expression and progesterone-receptor (PR) expression towards SUVmax was found (ER: r = 0.27, p < 0.01; PR: r = 0.19, p < 0.05). HER2-receptor expression showed no significant correlation towards SUV and ADC values. A significant positive correlation between Ki67 and SUVmax and SUVmean (r = 0.42 p < 0.01; r = 0.19 p < 0.05) was shown. Tumor grading significantly correlated with SUVmax and SUVmean (ρ = 0.36 and ρ = 0.39, both p's < 0.01). There were no group differences between SUV/ADC values of DTC-positive/-negative patients. CONCLUSIONS: [18F]FDG-PET/MRI may give a first impression of BC-receptor status and BC-tumor biology during initial staging by measuring glucose metabolism but cannot distinguish between DTC-positive/-negative patients and replace biopsy.

Programmed death receptor ligand-2 (PD-L2) bearing extracellular vesicles as a new biomarker to identify early triple-negative breast cancer patients at high risk for relapse.

PURPOSE: Based on the tumor-promoting features of extracellular vesicles (EV) and PD-L1/2-bearing EV subpopulations (PD-L1/2EV), we evaluated their potential as surrogate markers for disease progression or eligibility criteria for PD-1 immune checkpoint inhibition (ICI) approaches in early triple-negative breast cancer (TNBC). METHODS: After enrichment of EV from plasma samples of 56 patients before and 50 after chemotherapy (CT), we determined levels of EV particle number and PD-L1/2EV by nanoparticle tracking analysis or ELISA and associated the results with clinical status/outcome and the presence of distinct circulating tumor cells (CTC) subpopulations. RESULTS: Compared to healthy controls, patients had a tenfold higher EV concentration and significantly elevated PD L2EV but not PD L1EV levels. The most important clinical implications were found for PD-L2EV. High PD-L2EV levels were associated with a significantly reduced 3-year progression-free and overall survival (PFS and OS). A loss of PD-L2EV after CT was significantly more prominent in patients achieving pathological complete response (pCR). Increased pre-CT PD-L2EV levels were found in patients having NOTCH1-positive or ERBB3-positive CTC. The presence of ERBB3-positive CTC combined with high pre-CT PD-L2EV resulted in a shorter PFS. CONCLUSION: This study highlights PD L2EV as a promising biomarker for risk assessment of TNBC patients and represents the basic for additional studies introducing PD-L2EV as an eligibility criterion for PD-1 ICI approaches.

Clinical Decision Support for Axillary Lymph Node Staging in Newly Diagnosed Breast Cancer Patients Based on 18F-FDG PET/MRI and Machine Learning.

In addition to its high prognostic value, the involvement of axillary lymph nodes in breast cancer patients also plays an important role in therapy planning. Therefore, an imaging modality that can determine nodal status with high accuracy in patients with primary breast cancer is desirable. Our purpose was to investigate whether, in newly diagnosed breast cancer patients, machine-learning prediction models based on simple assessable imaging features on MRI or PET/MRI are able to determine nodal status with performance comparable to that of experienced radiologists; whether such models can be adjusted to achieve low rates of false-negatives such that invasive procedures might potentially be omitted; and whether a clinical framework for decision support based on simple imaging features can be derived from these models. Methods: Between August 2017 and September 2020, 303 participants from 3 centers prospectively underwent dedicated whole-body 18F-FDG PET/MRI. Imaging datasets were evaluated for axillary lymph node metastases based on morphologic and metabolic features. Predictive models were developed for MRI and PET/MRI separately using random forest classifiers on data from 2 centers and were tested on data from the third center. Results: The diagnostic accuracy for MRI features was 87.5% both for radiologists and for the machine-learning algorithm. For PET/MRI, the diagnostic accuracy was 89.3% for the radiologists and 91.2% for the machine-learning algorithm, with no significant differences in diagnostic performance between radiologists and the machine-learning algorithm for MRI (P = 0.671) or PET/MRI (P = 0.683). The most important lymph node feature was tracer uptake, followed by lymph node size. With an adjusted threshold, a sensitivity of 96.2% was achieved by the random forest classifier, whereas specificity, positive predictive value, negative predictive value, and accuracy were 68.2%, 78.1%, 93.8%, and 83.3%, respectively. A decision tree based on 3 simple imaging features could be established for MRI and PET/MRI. Conclusion: Applying a high-sensitivity threshold to the random forest results might potentially avoid invasive procedures such as sentinel lymph node biopsy in 68.2% of the patients.

The Role of C-Reactive Protein as a Prognostic Biomarker in Patients with Early Breast Cancer Treated with Neoadjuvant Chemotherapy.

Background: C-reactive protein (CRP) is an acute phase reactant influenced by inflammation and tissue damage. Elevated CRP levels have been associated with poor outcome of various cancers including breast cancer. However, evidence regarding a potential impact of CRP levels on outcome of neoadjuvant chemotherapy (NACT) in patients with early breast cancer (EBC) is insufficient. Methods: Patients who had received NACT for EBC and had available data regarding CRP levels before therapy, pathologic complete remission (pCR), and follow-up were included. The association between CRP at baseline and outcome parameters was analyzed. Results: 152 women were included in this analysis; median follow-up was 5.8 years. No association between CRP at baseline and pCR rates could be detected. 6.6% of the patients developed a local recurrence, 10.5% developed a distant recurrence, and 5.2% died from breast cancer. A negative correlation (Spearman-Rho) between CRP at baseline and overall survival (OS) (correlation coefficient (CC) -0.255; p = 0.45), disease-free survival (DFS) (CC -0.348; p = 0.075), local recurrence-free survival (LRFS) (CC -0.245; p = 0.327), and distant DFS (DDFS) (CC -0.422; p = 0.057) was not statistically significant, although especially in DFS and DDFS a strong trend was detected. The probability of death from breast cancer was 2% if the CRP was <0.08 mg/dL and 40% if the CRP was >2.08 mg/dL; this association was highly statistically significant (χ2; p < 0.001). These results were independent from age, estrogen and progesterone receptor status, HER2 status, nodal status, and grading. The hazard ratio for OS was 5.75 (p = 0.004) for CRP <0.08 mg/dL versus CRP >2.08 mg/dL. Discussion/Conclusion: CRP at baseline is not predictive for pCR in EBC after NACT in our patient dataset. However, an association of parameters of long-term prognosis with CRP could be demonstrated. Although the correlations of higher CRP levels at baseline and shorter OS, DFS, LRFS, and DDFS were not significant, a strong trend could be detected that was reproduced in the analysis of different groups of CRP levels and the probability of breast cancer mortality. Higher CRP levels are indicating a worse prognosis in EBC after NACT in this retrospective analysis. These results justify further investigation of CRP not as a predictive parameter for pCR but as a biomarker of long-term prognosis in EBC in prospective trials and may lead to therapeutic approaches with the aim of lowering CRP levels.

Lung Nodules Missed in Initial Staging of Breast Cancer Patients in PET/MRI-Clinically Relevant?

PURPOSE: The evaluation of the clinical relevance of missed lung nodules at initial staging of breast cancer patients in [18F]FDG-PET/MRI compared with CT. METHODS: A total of 152 patients underwent an initial whole-body [18F]FDG-PET/MRI and a thoracoabdominal CT for staging. Presence, size, shape and location for each lung nodule in [18F]FDG-PET/MRI was noted. The reference standard was established by taking initial CT and follow-up imaging into account (a two-step approach) to identify clinically-relevant lung nodules. Patient-based and lesion-based data analysis was performed. RESULTS: No patient with clinically-relevant lung nodules was missed on a patient-based analysis with MRI VIBE, while 1/84 females was missed with MRI HASTE (1%). Lesion-based analysis revealed 4/96 (4%, VIBE) and 8/138 (6%, HASTE) missed clinically-relevant lung nodules. The average size of missed lung nodules was 3.2 mm ± 1.2 mm (VIBE) and 3.6 mm ± 1.4 mm (HASTE) and the predominant location was in the left lower quadrant and close to the hilum. CONCLUSION: All patients with newly-diagnosed breast cancer and clinically-relevant lung nodules were detected at initial [18F]FDG-PET/MRI staging. However, due to the lower sensitivity in detecting lung nodules, a small proportion of clinically-relevant lung nodules were missed. Thus, supplemental low-dose chest CT after neoadjuvant therapy should be considered for backup.

Multiparametric 18F-FDG PET/MRI-Based Radiomics for Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

BACKGROUND: The aim of this study was to assess whether multiparametric 18F-FDG PET/MRI-based radiomics analysis is able to predict pathological complete response in breast cancer patients and hence potentially enhance pretherapeutic patient stratification. METHODS: A total of 73 female patients (mean age 49 years; range 27-77 years) with newly diagnosed, therapy-naive breast cancer underwent simultaneous 18F-FDG PET/MRI and were included in this retrospective study. All PET/MRI datasets were imported to dedicated software (ITK-SNAP v. 3.6.0) for lesion annotation using a semi-automated method. Pretreatment biopsy specimens were used to determine tumor histology, tumor and nuclear grades, and immunohistochemical status. Histopathological results from surgical tumor specimens were used as the reference standard to distinguish between complete pathological response (pCR) and noncomplete pathological response. An elastic net was employed to select the most important radiomic features prior to model development. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for each model. RESULTS: The best results in terms of AUCs and NPV for predicting complete pathological response in the entire cohort were obtained by the combination of all MR sequences and PET (0.8 and 79.5%, respectively), and no significant differences from the other models were observed. In further subgroup analyses, combining all MR and PET data, the best AUC (0.94) for predicting complete pathologic response was obtained in the HR+/HER2- group. No difference between results with/without the inclusion of PET characteristics was observed in the TN/HER2+ group, each leading to an AUC of 0.92 for all MR and all MR + PET datasets. CONCLUSION: 18F-FDG PET/MRI enables comprehensive high-quality radiomics analysis for the prediction of pCR in breast cancer patients, especially in those with HR+/HER2- receptor status.

A Role of PET/MR in Breast Cancer?

PET/MRI has been available since 2010, representing the newest of the hybrid imaging modalities. It combines functional as well as morphologic high-resolution MRI data with metabolic information from PET, providing image data sets with complementary information. Especially in the field of oncology, PET/MRI is a promising imaging modality with diverse applications. Since its introduction there has already been a large quantity of studies indicating a high diagnostic value of PET/MRI for whole-body cancer staging. The simultaneous acquisition of metabolic PET and MRI data is expected to have a major impact in the assessment of breast cancer due to the superior resolution of MRI in breast tissue compared to CT. While there is an ongoing debate if the added value of breast 18F-FDG PET/MRI in the primary diagnosis of breast cancer has clinical impact compared to breast MRI, a large number of studies have proven that 18F-FDG PET/MRI is extremely valuable for whole-body breast cancer staging and especially for treatment monitoring. Besides molecular markers, distant metastases and axillary lymph node involvement are the most important predictors for overall survival and recurrence in breast cancer patients. Due to the high soft tissue contrast, functional imaging from MRI and metabolic information from PET, distant metastases in organs and in particular in the bones are detected better compared to the conventional staging algorithm with CT and bone scan and can significantly influence the therapy regime. Instead of mastectomy and extensive axillary dissection being performed in many patients, the improved imaging and diagnostic confidence also has helped that local therapy control can be achieved with reduced invasiveness. A future role of 18F-FDG PET/MRI could therefore become treatment response evaluation under neoadjuvant treatment before or instead of operative therapy. In addition to reduced radiation exposure compared to conventional staging examinations, hybrid 18F-FDG PET/MRI might serve as a comprehensive "all-in-one" breast cancer staging tool, providing precise local and whole-body staging including MRI of the head in one procedure, which save patients a diagnostic marathon.

Free-breathing 3D Stack of Stars GRE (StarVIBE) sequence for detecting pulmonary nodules in 18F-FDG PET/MRI.

BACKGROUND: The free-breathing T1-weighted 3D Stack of Stars GRE (StarVIBE) MR sequence potentially reduces artifacts in chest MRI. The purpose of this study was to evaluate StarVIBE for the detection of pulmonary nodules in 18F-FDG PET/MRI. MATERIAL AND METHODS: In this retrospective analysis, conducted on a prospective clinical trial cohort, 88 consecutive women with newly diagnosed breast cancer underwent both contrast-enhanced whole-body 18F-FDG PET/MRI and computed tomography (CT). Patients' chests were examined on CT as well as on StarVIBE and conventional T1-weighted VIBE and T2-weighted HASTE MR sequences, with CT serving as the reference standard. Presence, size, and location of all detectable lung nodules were assessed. Wilcoxon test was applied to compare nodule features and Pearson's, and Spearman's correlation coefficients were calculated. RESULTS: Out of 65 lung nodules detected in 36 patients with CT (3.7 ± 1.4 mm), StarVIBE was able to detect 31 (47.7%), VIBE 26 (40%) and HASTE 11 (16.8%), respectively. Overall, CT showed a significantly higher detectability than all MRI sequences combined (65 vs. 36, difference 44.6%, p < 0.001). The VIBE showed a significantly better detection rate than the HASTE (23.1%, p = 0.001). Detection rates between StarVIBE and VIBE did not significantly differ (7.7%, p = 0.27), but the StarVIBE showed a significant advantage detecting centrally located pulmonary nodules (66.7% vs. 16.7%, p = 0.031). There was a strong correlation in nodule size between CT and MRI sequences (HASTE: ρ = 0.80, p = 0.003; VIBE: ρ = 0.77, p < 0.001; StarVIBE: ρ = 0.78, p < 0.001). Mean image quality was rated as good to excellent for CT and MRI sequences. CONCLUSION: The overall lung nodule detection rate of StarVIBE was slightly, but not significantly, higher than conventional T1w VIBE and significantly higher than T2w HASTE. Detectability of centrally located nodules is better with StarVIBE than with VIBE. Nevertheless, all MRI analyses demonstrated considerably lower detection rates for small lung nodules, when compared to CT.

Comparison of nodal staging between CT, MRI, and [18F]-FDG PET/MRI in patients with newly diagnosed breast cancer.

PURPOSE: To compare CT, MRI, and [18F]-fluorodeoxyglucose positron emission tomography ([18F]-FDG PET/MRI) for nodal status, regarding quantity and location of metastatic locoregional lymph nodes in patients with newly diagnosed breast cancer. MATERIALS AND METHODS: One hundred eighty-two patients (mean age 52.7 ± 11.9 years) were included in this prospective double-center study. Patients underwent dedicated contrast-enhanced chest/abdomen/pelvis computed tomography (CT) and whole-body ([18F]-FDG PET/) magnet resonance imaging (MRI). Thoracal datasets were evaluated separately regarding quantity, lymph node station (axillary levels I-III, supraclavicular, internal mammary chain), and lesion character (benign vs. malign). Histopathology served as reference standard for patient-based analysis. Patient-based and lesion-based analyses were compared by a McNemar test. Sensitivity, specificity, positive and negative predictive values, and accuracy were assessed for all three imaging modalities. RESULTS: On a patient-based analysis, PET/MRI correctly detected significantly more nodal positive patients than MRI (p < 0.0001) and CT (p < 0.0001). No statistically significant difference was seen between CT and MRI. PET/MRI detected 193 lesions in 75 patients (41.2%), while MRI detected 123 lesions in 56 patients (30.8%) and CT detected 104 lesions in 50 patients, respectively. Differences were statistically significant on a lesion-based analysis (PET/MRI vs. MRI, p < 0.0001; PET/MRI vs. CT, p < 0.0001; MRI vs. CT, p = 0.015). Subgroup analysis for different lymph node stations showed that PET/MRI detected significantly more lymph node metastases than MRI and CT in each location (axillary levels I-III, supraclavicular, mammary internal chain). MRI was superior to CT only in axillary level I (p = 0.0291). CONCLUSION: [18F]-FDG PET/MRI outperforms CT or MRI in detecting nodal involvement on a patient-based analysis and on a lesion-based analysis. Furthermore, PET/MRI was superior to CT or MRI in detecting lymph node metastases in all lymph node stations. Of all the tested imaging modalities, PET/MRI showed the highest sensitivity, whereas CT showed the lowest sensitivity, but was most specific.

Prospective comparison of CT and 18F-FDG PET/MRI in N and M staging of primary breast cancer patients: Initial results.

OBJECTIVES: To compare the diagnostic accuracy of contrast-enhanced thoraco-abdominal computed tomography and whole-body 18F-FDG PET/MRI in N and M staging in newly diagnosed, histopathological proven breast cancer. MATERIAL AND METHODS: A total of 80 consecutive women with newly diagnosed and histopathologically confirmed breast cancer were enrolled in this prospective study. Following inclusion criteria had to be fulfilled: (1) newly diagnosed, treatment-naive T2-tumor or higher T-stage or (2) newly diagnosed, treatment-naive triple-negative tumor of every size or (3) newly diagnosed, treatment-naive tumor with molecular high risk (T1c, Ki67 >14%, HER2neu over-expression, G3). All patients underwent a thoraco-abdominal ceCT and a whole-body 18F-FDG PET/MRI. All datasets were evaluated by two experienced radiologists in hybrid imaging regarding suspect lesion count, localization, categorization and diagnostic confidence. Images were interpreted in random order with a reading gap of at least 4 weeks to avoid recognition bias. Histopathological results as well as follow-up imaging served as reference standard. Differences in staging accuracy were assessed using Mc Nemars chi2 test. RESULTS: CT rated the N stage correctly in 64 of 80 (80%, 95% CI:70.0-87.3) patients with a sensitivity of 61.5% (CI:45.9-75.1), a specificity of 97.6% (CI:87.4-99.6), a PPV of 96% (CI:80.5-99.3), and a NPV of 72.7% (CI:59.8-82.7). Compared to this, 18F-FDG PET/MRI determined the N stage correctly in 71 of 80 (88.75%, CI:80.0-94.0) patients with a sensitivity of 82.1% (CI:67.3-91.0), a specificity of 95.1% (CI:83.9-98.7), a PPV of 94.1% (CI:80.9-98.4) and a NPV of 84.8% (CI:71.8-92.4). Differences in sensitivities were statistically significant (difference 20.6%, CI:-0.02-40.9; p = 0.008). Distant metastases were present in 7/80 patients (8.75%). 18 F-FDG PET/MRI detected all of the histopathological proven metastases without any false-positive findings, while 3 patients with bone metastases were missed in CT (sensitivity 57.1%, specificity 95.9%). Additionally, CT presented false-positive findings in 3 patients. CONCLUSION: 18F-FDG PET/MRI has a high diagnostic potential and outperforms CT in assessing the N and M stage in patients with primary breast cancer.

Multiparametric Integrated 18F-FDG PET/MRI-Based Radiomics for Breast Cancer Phenotyping and Tumor Decoding.

BACKGROUND: This study investigated the performance of simultaneous 18F-FDG PET/MRI of the breast as a platform for comprehensive radiomics analysis for breast cancer subtype analysis, hormone receptor status, proliferation rate and lymphonodular and distant metastatic spread. METHODS: One hundred and twenty-four patients underwent simultaneous 18F-FDG PET/MRI. Breast tumors were segmented and radiomic features were extracted utilizing CERR software following the IBSI guidelines. LASSO regression was employed to select the most important radiomics features prior to model development. Five-fold cross validation was then utilized alongside support vector machines, resulting in predictive models for various combinations of imaging data series. RESULTS: The highest AUC and accuracy for differentiation between luminal A and B was achieved by all MR sequences (AUC 0.98; accuracy 97.3). The best results in AUC for prediction of hormone receptor status and proliferation rate were found based on all MR and PET data (ER AUC 0.87, PR AUC 0.88, Ki-67 AUC 0.997). PET provided the best determination of grading (AUC 0.71), while all MR and PET analyses yielded the best results for lymphonodular and distant metastatic spread (0.81 and 0.99, respectively). CONCLUSION: 18F-FDG PET/MRI enables comprehensive high-quality radiomics analysis for breast cancer phenotyping and tumor decoding, utilizing the perks of simultaneously acquired morphologic, functional and metabolic data.

Disseminated tumour cells from the bone marrow of early breast cancer patients: Results from an international pooled analysis.

PURPOSE: Presence of disseminated tumour cells (DTCs) in the bone marrow (BM) has been described as a surrogate of residual disease in patients with early breast cancer (EBC). PADDY (Pooled Analysis of DTC Detection in Early Breast Cancer) is a large international analysis of pooled data that aimed to assess the prognostic impact of DTCs in patients with EBC. EXPERIMENTAL DESIGN: Individual patient data were collected from 11 centres. Patients with EBC and available follow-up data in whom BM sampling was performed at the time of primary diagnosis before receiving any anticancer treatment were eligible. DTCs were identified by antibody staining against epithelial cytokeratins. Multivariate Cox regression was used to compare the survival of DTC-positive versus DTC-negative patients. RESULTS: In total, 10,307 patients were included. Of these, 2814 (27.3%) were DTC-positive. DTC detection was associated with higher tumour grade, larger tumour size, nodal positivity, oestrogen receptor and progesterone receptor negativity, and HER2 positivity (all p < 0.001). Multivariate analyses showed that DTC detection was an independent prognostic marker for overall survival, disease-free survival and distant disease-free survival with hazard ratios (HR) and 95% confidence intervals (CI) of 1.23 (95% CI: 1.06-1.43, p = 0.006), 1.30 (95% CI: 1.12-1.52, p < 0.001) and 1.30 (95% CI: 1.08-1.56, p = 0.006), respectively. There was no association between locoregional relapse-free survival and DTC detection (HR 1.21; 95% CI 0.68-2.16; p = 0.512). CONCLUSIONS: DTCs in the BM represent an independent prognostic marker in patients with EBC. The heterogeneous metastasis-initiating potential of DTCs is consistent with the concept of cancer dormancy.

Determining the axillary nodal status with four current imaging modalities including 18F-FDG PET/MRI in newly diagnosed breast cancer: A comparative study using histopathology as reference standard.

Purpose: To compare breast magnetic resonance imaging (MRI), thoracal MRI, thoracal 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET)/MRI and axillary sonography for the detection of axillary lymph node metastases in women with newly diagnosed breast cancer. Materials and Methods: This prospective double-center study included patients with newly diagnosed breast cancer between March 2018 and December 2019. Patients underwent thoracal (18F-FDG PET/)MRI, axillary sonography, and dedicated prone breast MRI. Datasets were evaluated separately regarding nodal status (nodal+ vs. nodal-). Histopathology served as reference standard in all patients. The diagnostic performance of breast MRI, thoracal MRI, thoracal PET/MRI and axillary sonography in detecting nodal positive patients was tested by creating receiver-operating-characteristic curves (ROC) with a calculated area under the curve (AUC). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for all four modalities. A McNemar test was used to assess differences. Results: 112 female patients (mean age 53.04 ± 12.6 years) were evaluated. Thoracal PET/MRI showed the highest ROC-AUC with a value of 0.892. The AUC for breast MRI, thoracal MRI and sonography were 0.782, 0.814 and 0.834, respectively. Differences between thoracal PET/MRI and axillary sonography, thoracal MRI and breast MRI were statistically significant (PET/MRI vs. axillary sonography, P = 0.01; PET/MRI vs. thoracal MRI, P = 0.02; PET/MRI vs. breast MRI, P = 0.03). PET/MRI showed the highest sensitivity (81.8%, 36/44) (95%-CI: 67.29-91.81%) while axillary sonography had the highest specificity (98.5%, 65/66), 95%-CI: 91.84-99.96%). Conclusion: 18F-FDG PET/MRI outperforms axillary sonography, breast MRI and thoracal MRI in determining the axillary lymph node status. In a clinical setting, the combination of 18F-FDG PET/MRI and axillary sonography might be considered to provide even more accuracy in diagnosis.

Soluble Neuropilin-1 is an independent marker of poor prognosis in early breast cancer.

BACKGROUND: Neuropilin-1 (NRP-1) is a transmembrane protein that acts as a multifunctional non-tyrosine kinase receptor with an established role in development and immunity. NRP-1 also regulates tumor biology, and high expression levels of tissue NRP-1 have been associated with a poor prognosis. Recently, ELISA-based quantification of soluble NRP-1 (sNRP-1) has become available, but little is known about the prognostic value of sNRP-1 in malignancies. MATERIALS AND METHODS: We measured sNRP-1 in the serum of 509 patients with primary early breast cancer (BC) at the time of diagnosis using ELISA. RESULTS: Mean serum values of sNRP-1 were 1.88 ± 0.52 nmol/l (= 130.83 ± 36.24 ng/ml). SNRP-1 levels weakly correlated with age, and were higher in peri- and postmenopausal patients compared to premenopausal patients, respectively (p < 0.0001). Low levels of sNRP-1 were associated with a significant survival benefit compared to high sNRP-1 levels at baseline (p = 0.005; HR 1.94; 95%CI 1.23-3.06). These findings remained significant after adjustment for tumor stage including lymph node involvement, grading, hormone receptor, HER2 status, and age (p = 0.022; HR 1.78; 95%CI 1.09-2.91). CONCLUSION: Our findings warrant further investigations into the prognostic and therapeutic potential of sNRP-1 in BC.

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.