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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. [ABSTRACT FROM AUTHOR]

Simple Summary: Histological and molecular breast cancer (BC) characteristics are highly important for individualized therapeutical strategies and personalized risk assessment. Despite the improvement of existing image-based staging examinations over the last years, especially the implementation of PET/MRI examinations at leading tumor centers, the invasive part of BC staging is unavoidable. However, the diagnostic potential of PET/MRI has not yet been fully explored. Thus, this study aimed to analyze possible correlations between PET/MRI imaging markers and invasive acquired biomarkers in newly diagnosed early BC to possibly spare invasive procedures for BC patients in the future. At a population of 169 women a correlation between glucose metabolism and estrogen-receptor and progesterone-receptor expression, Ki67, and tumor grading was shown, whereas no correlation regarding disseminated tumor cells (DTCs) could be found. Thus, [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. 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. [ABSTRACT FROM AUTHOR]

Simple Summary: Image-based primary staging in women with newly-diagnosed breast cancer is important to exclude distant metastases, which affect up to 10% of women. The increasing implementation of [18F]FDG-PET/MRI as a radiation-saving primary staging tool bears the risk of missing lung nodules. Thus, chest CT serves as the diagnostic of choice for the detection and classification of pulmonary nodules. The aim of this study was 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. We demonstrated in an homogeneous population of 152 patients that 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 of MRI in detecting lung nodules, a small proportion of clinically-relevant lung nodules were missed. Thus, a supplemental low-dose chest CT after neoadjuvant therapy should be considered for backup. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate and compare the diagnostic potential of whole-body MRI and whole-body 18F-FDG PET/MRI for N and M staging in newly diagnosed, histopathologically proven breast cancer. Material and methods: A total of 104 patients (age 53.4 ± 12.5) with newly diagnosed, histopathologically proven breast cancer were enrolled in this study prospectively. All patients underwent a whole-body 18F-FDG PET/MRI. MRI and 18F-FDG PET/MRI datasets were evaluated separately regarding lesion count, lesion localization, and lesion characterization (malignant/benign) as well as the diagnostic confidence (5-point ordinal scale, 1–5). The N and M stages were assessed according to the eighth edition of the American Joint Committee on Cancer staging manual in MRI datasets alone and in 18F-FDG PET/MRI datasets, respectively. In the majority of lesions histopathology served as the reference standard. The remaining lesions were followed-up by imaging and clinical examination. Separately for nodal-positive and nodal-negative women, a McNemar chi2 test was performed to compare sensitivity and specificity of the N and M stages between 18F-FDG PET/MRI and MRI. Differences in diagnostic confidence scores were assessed by Wilcoxon signed rank test. Results: MRI determined the N stage correctly in 78 of 104 (75%) patients with a sensitivity of 62.3% (95% CI: 0.48–0.75), a specificity of 88.2% (95% CI: 0.76–0.96), a PPV (positive predictive value) of 84.6% % (95% CI: 69.5–0.94), and a NPV (negative predictive value) of 69.2% (95% CI: 0.57–0.8). Corresponding results for 18F-FDG PET/MRI were 87/104 (83.7%), 75.5% (95% CI: 0.62–0.86), 92.2% (0.81–0.98), 90% (0.78–0.97), and 78.3% (0.66–0.88), showing a significantly better sensitivity of 18F-FDG PET/MRI determining malignant lymph nodes (p = 0.008). The M stage was identified correctly in MRI and 18F-FDG PET/MRI in 100 of 104 patients (96.2%). Both modalities correctly staged all 7 patients with distant metastases, leading to false-positive findings in 4 patients in each modality (3.8%). In a lesion-based analysis, 18F-FDG PET/MRI showed a significantly better performance in correctly determining malignant lesions (85.8% vs. 67.1%, difference 18.7% (95% CI: 0.13–0.26), p < 0.0001) and offered a superior diagnostic confidence compared with MRI alone (4.1 ± 0.7 vs. 3.4 ± 0.7, p < 0.0001). Conclusion: 18F-FDG PET/MRI has a better diagnostic accuracy for N staging in primary breast cancer patients and provides a significantly higher diagnostic confidence in lesion characterization than MRI alone. But both modalities bear the risk to overestimate the M stage. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the influence of contrast agent administration on attenuation correction (AC) based on a CAIPIRINHA (CAIPI)-accelerated T1-weighted Dixon 3D-VIBE sequence in 68Ga-DOTATOC PET/MRI.Material and Methods: Fifty-one patients with neuroendocrine tumors underwent whole-body 68Ga-DOTATOC PET/MRI for tumor staging. Two PET reconstructions were performed using AC-maps that were created using a high-resolution CAIPI-accelerated Dixon-VIBE sequence with an additional bone atlas and truncation correction using the HUGE (B0 homogenization using gradient enhancement) method before and after application of Gadolinium (Gd)-based contrast agent. Standardized uptake values (SUVs) of 21 volumes of interest (VOIs) were compared between in both PET data sets per patient. A student's t-test for paired samples was performed to test for potential differences between both AC-maps and both reconstructed PET data sets. Bonferroni correction was performed to prevent α-error accumulation, p < 0.0024 was considered to indicate statistical significance.Results: Significant quantitative differences between SUVmax were found in the perirenal fat (19.65 ± 48.03 %, p < 0.0001), in the axillary fat (17.46 ± 63.67 %, p < 0.0001) and in the dorsal subcutaneous fat on level of lumbar vertebral body L4 (10.26 ± 25.29 %, p < 0.0001). Significant differences were also evident in the lungs apical (5.80 ± 10.53 %, p < 0.0001), dorsal at the level of the pulmonary trunk (15.04 ± 19.09 %, p < 0.0001) and dorsal in the basal lung (51.27 ± 147.61 %, p < 0.0001).Conclusion: The administration of (Gd)-contrast agents in this study has shown a considerable influence on the AC-maps in PET/MRI and, consequently impacted quantification in the reconstructed PET data. Therefore, dedicated PET/MRI staging protocols have to be adjusted so that AC-map acquisition is performed prior to contrast agent administration. [ABSTRACT FROM AUTHOR]

Objectives: To investigate if the combined analysis of the apparent diffusion coefficient (ADC) and standardized uptake values (SUV) measured in 18F-fluoro-deoxy-glucose-positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI) examinations correlates with overall survival in non-small cell lung cancer (NSCLC).Material and Methods: A total of 92 patients with newly diagnosed, histopathologically proven NSCLC (44 women and 48 men, mean age 63.1 ± 9.9y) underwent a dedicated thoracic 18F-FDG PET/MRI examination. A manually drawn polygonal region of interest (ROI), encompassing the entire primary tumor mass, was placed over the primary tumor on fused PET/MR images to determine the maximum and mean standardized uptake values (SUVmax; SUVmean) as well as on the ADC maps to quantify the mean and minimum ADC values (ADCmean, ADCmin). The impact of these parameters to predict patient's overall survival was tested using hazard ratios (HR). Pearson's correlation coefficients were calculated to assess dependencies between the different values. A p-value < 0.05 indicated statistical significance.Results: In all 92 patients (n = 59 dead at time of retrospective data collection, mean time till death: 19 ± 16 month, n = 33 alive, mean time to last follow-up: 56 ± 22 month) the Hazard ratios (HR) as independent predictors for overall survival (OS) of SUVmax were 2.37 (95 % CI: 1.23-4.59, p = 0.008) and for SUVmean 1.85 (95 % CI: 1.05-3.26, p = 0.03) while ADCmin showed a HR of 0.95 (95 % CI: 0.57-1.59, p = 0.842) and ADCmean a HR of 2.01 (95 % CI: 1.2-3.38, p = 0.007). Furthermore, a combined analysis for SUVmax/ADCmean, SUVmax / ADCmin and SUVmean/ADCmean revealed a HR of 2.01 (95 % CI: 1.10-3.67, p = 0.02), 1.75 (95 % CI: 0.97-3.15, p = 0.058) and 1.78 (95 % CI: 1.02-3.10, p = 0.04).Conclusion: SUVmax and SUVmean of the primary tumor are predictors for OS in therapy-naive NSCLC patients, whereas the combined analysis of SUV and ADC values does not improve these results. Therefore, ADC values do not further enhance the diagnostic value of SUV as a prognostic biomarker in NSCLC. [ABSTRACT FROM AUTHOR]