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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.

Purpose: This study seeks to evaluate MR imaging morphological factors and other covariates that influence the presence of residual glandular tissue after risk-reducing mastectomy in patients with a familial predisposition. Methods: We analyzed women of a high-risk collective with pathogenic mutation (BRCA1 (n = 49), BRCA2 (n = 24), or further mutation (n = 9)). A total of 117 breasts were analyzed, 63 left and 54 right, from a cohort of 81 patients, who were on average 40 years old. The mean follow-up was 63 months (range 12–180 months, SD = 39.67). Retrospective analysis of MR imaging data from 2006–2022 of patients of a high-risk collective (all carriers of a pathogenic mutation) with contralateral (RRCM) or bilateral risk-reducing mastectomy (RRBM) was performed. In the image data the remaining skin flap thickness by distance measurements at eight equally distributed, clockwise points and the retromamillary area, as well as by volumetry of each breast, was elected. Residual glandular tissue was also volumetrized. In addition, patient-related covariates were recorded and their influence on postoperative residual glandular tissue and skin flap thickness was analyzed by uni- and multivariate regressions. Results: A significant association with postoperative residual glandular tissue was shown in multivariate analysis for the independent variables breast density, skin flap mean, and surgical method (all p-values < 0.01). A negatively significant association could be seen for the variables preoperative breast volume (p-values < 0.01) and surgeon experience (most p-values < 0.05&ndash

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.

Locoregional therapy options for CCA are used, in particular, for non-resectable tumors and aim to reduce tumor viability or delay tumor growth and ultimately prolong overall survival. In addition to local ablative procedures such as radiofrequency- or microwave-ablation, transarterial procedures such as transarterial embolization (TAE), transarterial chemoembolization (TACE), or selective internal radiotherapy (SIRT) play a major role. In particular, in combination with advances in molecular medicine and immunotherapy, there has been a further development in the therapy of primary malignant liver tumors in recent years. In this review, we analyze data from recent studies and examine the implications for therapy of CCA, particularly with regard to the combination of locoregional therapies with modern systemic therapies.

Simple Summary In this study, we assessed the potential of simultaneously acquired 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) and magnetic resonance imaging-derived quantitative imaging parameters to predict the tumor grade, metastatic status, and response to neoadjuvant therapy of primary soft-tissue sarcomas of the extremities. Based on the results of the present study, quantifications of the 18F-FDG PET uptake provide useful prognostic data for the evaluation of histopathological response to neoadjuvant treatment as well as the aggressiveness of high-risk sarcomas, whereas no correlation between the different outcome variables and the results for tumor size and diffusion-weighted imaging-derived apparent diffusion coefficient values was found. Accordingly, measurements of the metabolic activity of primary and untreated soft-tissue sarcomas could non-invasively deliver relevant information, that may be used for treatment planning and risk-stratification of sarcoma patients in a pretherapeutic setting. Abstract Background: To evaluate the potential of simultaneously acquired 18F-FDG PET- and MR-derived quantitative imaging data sets of primary soft-tissue sarcomas for the prediction of neoadjuvant treatment response, the metastatic status and tumor grade. Methods: A total of 52 patients with a high-risk soft-tissue sarcoma underwent a 18F-FDG PET/MR examination within one week before the start of neoadjuvant treatment. For each patient, the maximum tumor size, metabolic activity (SUVs), and diffusion-restriction (ADC values) of the tumor manifestations were determined. A Mann–Whitney-U test was used, and ROC analysis was performed to evaluate the potential to predict histopathological treatment response, the metastatic status or tumor grade. The results from the histopathological analysis served as reference standard. Results: Soft-tissue sarcomas with a histopathological treatment response revealed a significantly higher metabolic activity than tumors in the non-responder group. In addition, grade 3 tumors showed a significant higher 18F-FDG uptake than grade 2 tumors. Furthermore, no significant correlation between the different outcome variables and tumor size or calculated ADC-values could be identified. Conclusion: Measurements of the metabolic activity of primary and untreated soft-tissue sarcomas could non-invasively deliver relevant information that may be used for treatment planning and risk-stratification of high-risk sarcoma patients in a pretherapeutic setting.