To compare 7 T magnetic resonance imaging (MRI) of pituitary macroadenomas (PMA) with standard MRI and intraoperative findings regarding tumor detection, localization, size, and extension. Patients with suspected pituitary adenoma underwent pre-operative 1.5 T or 3 T and 7 T MRI; 14 patients with a PMA were included. A qualitative (lesion detection, location, cavernous sinus infiltration) and quantitative (lesion size, depth of cavernous sinus infiltration) analysis of 1.5 T, 3 T and 7 T MRI was performed and compared with intraoperative findings. Both 1.5/3 T and 7 T MRI enabled the detection of all PMAs; lesion size determination was equal. 7 T MRI enables more precise assessments of cavernous sinus infiltration of PMA (n_{correct 7T} = 78.6%, n_{correct 1.5/3T} = 64.3%). Ultra-high-field MRI is a reliable imaging modality for evaluation of PMAs providing exact information on lesion location and size. 7 T MRI yielded more accurate information on cavernous sinus infiltration with better agreement with intraoperative findings than standard MRI.

Treated cerebral aneurysms (IA) require follow-up imaging to ensure occlusion. Metal artifacts complicate radiologic assessment. Our aim was to evaluate an innovative metal-artifact-reduction (iMAR) algorithm for flat-detector computed tomography angiography (FD-CTA) regarding image quality (IQ) and detection of aneurysm residua/reperfusion in comparison to 2D digital subtraction angiography (DSA). Patients with IAs treated by endovascular coiling or clipping underwent both FD-CTA and DSA. FD-CTA datasets were postprocessed with/without iMAR algorithm (MAR+/MAR−). Evaluation of all FD-CTA and DSA datasets regarding qualitative (IQ, MAR) and quantitative (coil package diameter/CPD) parameters was performed. Aneurysm occlusion was assessed for each dataset and compared to DSA findings. In total, 40 IAs were analyzed (n_coiling = 24; n_clipping = 16). All iMAR+ datasets demonstrated significantly better IQ (p_{IQ coiling} < 0.0001; p_{IQ clipping} < 0.0001). iMAR significantly reduced the metal-artifact burden but did not affect the CPD. iMAR significantly improved the detection of aneurysm residua/reperfusion with excellent agreement with DSA (n_{aneurysm detection MAR+/MAR−/DSA} = 22/1/26). The iMAR algorithm significantly improves IQ by effective reduction of metal artifacts in FD-CTA datasets. The proposed algorithm enables reliable detection of aneurysm residua/reperfusion with good agreement to DSA. Thus, iMAR can help to reduce the need for invasive follow-up in treated IAs.

Background: Processing whole-slide images (WSI) to train neural networks can be intricate and labor intensive. We developed an open-source library dealing with recurrent tasks in the processing of WSI and helping with the training and evaluation of neuronal networks for classification tasks. Methods: Two histopathology use-cases were selected and only hematoxylin and eosin (H&E) stained slides were used. The first use case was a two-class classification problem. We trained a convolutional neuronal network (CNN) to distinguish between dysembryoplastic neuroepithelial tumor (DNET) and ganglioglioma (GG), two neuropathological low-grade epilepsy-associated tumor entities. Within the second use case, we included four clinicopathological disease conditions in a multilabel approach. Here we trained a CNN to predict the hormone expression profile of pituitary adenomas. In the same approach, we also predicted clinically silent corticotroph adenoma. Results: Our DNET-GG classifier achieved an AUC of 1.00 for the ROC curve. For the second use case, the best performing CNN achieved an area under the curve (AUC) of 0.97 for the receiver operating characteristic (ROC) for corticotroph adenoma, 0.86 for silent corticotroph adenoma, and 0.98 for gonadotroph adenoma. All scores were calculated with the help of our library on predictions on a case basis. Conclusions: Our comprehensive and fastai-compatible library is helpful to standardize the workflow and minimize the burden of training a CNN. Indeed, our trained CNNs extracted neuropathologically relevant information from the WSI. This approach will supplement the clinicopathological diagnosis of brain tumors, which is currently based on cost-intensive microscopic examination and variable panels of immunohistochemical stainings.

Background: The objective of this study was to compare results after endoscopic (ES) and open surgery (OpS) for esthesioneuroblastoma over a 40-year period. Methods: In a retrospective study, patients who had undergone ES and OpS for esthesioneuroblastoma with curative intent were included. The following outcome parameters were compared after ES and OpS: epidemiologic, clinical (including known tumor classifications), histopathologic, therapeutic (resection state, adjuvant therapy), and development of recurrences. Crude survival and Kaplan–Meier 10 y, 20 y, and 35 y actuarial survival were calculated. Results: Between 1981 and 2021, 15 patients were operated with ES and 28 with OpS. Advanced-stage tumors were significantly more often treated using OpS. For all other parameters, there were no other significant differences between ES and OpS. After ES, the 35 y OS, DSS, and DFS were 48.1%, 100%, and 55.9%, respectively. After OpS, they were 40.5%, 77.5%, and 35.3%. Conclusions: ES is an effective approach in esthesioneuroblastoma, even in the long-term course over decades, if the appropriate indication compared to OpS is respected.